Nano functional neural interfacesThese alternative nano fNIs hold great potentials for better...

Nano Res

1

Nano functional neural interfaces

Yongchen Wang1,§, Hanlin Zhu2,§, Huiran Yang3,4,§, Aaron D. Argall5, Lan Luan2, Chong Xie2 (), and Liang Guo3,6 ()

Nano Res., Just Accepted Manuscript • https://doi.org/10.1007/s12274-018-2127-4

http://www.thenanoresearch.com on Jun. 12, 2018

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63Nano Res. Nano Res.

TABLE OF CONTENTS (TOC)


Yongchen Wang1†

, Hanlin Zhu2†

, Huiran Yang1,3†

,

Aaron D. Argall1, Lan Luan

2, Chong Xie

2*, and Liang

Guo1*

1 The Ohio State University, U.S.A.

2 The University of Texas at Austin, U.S.A.

3 Nanjing Tech University, China

† Equal contribution

Engineered functional neural interfaces serve as essential abiotic-biotic

transducers between an engineered system and the nervous system.

This review covers the exciting developments and applications of

functional neural interfaces that rely on nanoelectrodes,

nanotransducers, or bionanotransducers to establish an interface with

the nervous system.

Guo Lab: http://guolab.engineering.osu.edu

Xie Lab: http://faculty.engr.utexas.edu/xie



Yongchen Wang1†

, Hanlin Zhu2†

, Huiran Yang3,4†

, Aaron D. Argall5, Lan Luan

2, Chong Xie

2 (), and Liang

Guo3,6

()

1 Department of Biomedical Engineering, The Ohio State University, Columbus 43210, USA

2 Department of Biomedical Engineering, The University of Texas at Austin, Austin 78712, USA

3 Department of Electrical and Computer Engineering, The Ohio State University, Columbus 43210, USA

4 Key Laboratory of Flexible Electronics and Institute of Advanced Materials, Jiangsu National Synergetic Innovation

Center for Advanced Materials, Nanjing Tech University, Nanjing 211816, China 5 Biomedical Sciences Graduate Program, The Ohio State University, Columbus 43210, USA

6 Department of Neuroscience, The Ohio State University, Columbus 43210, USA


Received: day month year

Revised: day month year

Accepted: day month year

(automatically inserted by

the publisher)

© Tsinghua University Press

and Springer-Verlag Berlin

Heidelberg 2014

KEYWORDS

Neural interface,

neurotechnology,

nanoelectrode,

nanomaterial,

neural recording,

neural stimulation

ABSTRACT

Engineered functional neural interfaces (fNIs) serve as essential abiotic-biotic

transducers between an engineered system and the nervous system. They

convert external physical stimuli to cellular signals in stimulation mode, or read

out biological processes in recording mode. Information can be exchanged

using electricity, light, magnetic fields, mechanical forces, heat, or chemical

signals. fNIs have found applications for studying processes in neural circuits

from cell cultures to organs to whole organisms. fNI-facilitated signal

transduction schemes, coupled with easily manipulable and observable external

physical signals, have attracted considerable attentions in recent years. This

enticing field is rapidly evolving toward miniaturization and biomimicry to

achieve long-term interface stability with great signal transduction efficiency.

Not only a new generation of neuroelectrodes has been invented, but advanced

fNIs that explore other physical modalities of neuromodulation and recording

have started to bloom. This review covers these exciting developments and

applications of fNIs that rely on nanoelectrodes, nanotransducers, or

bionanotransducers to establish an interface with the nervous system. These

nano fNIs are promising in offering a high spatial resolution, high target

specificity, and high communication bandwidth by allowing for a high density

and count of signal channels with minimum material volume and area to

dramatically improve the chronic integration of the fNI to the target neural

tissue. Such demanding advances in nano fNIs will greatly facilitate new

opportunities not only for studying basic neuroscience, but also for diagnosing

and treating various neurological diseases.

Nano Research

DOI

Review Article

Address correspondence to Prof. Liang Guo, [email protected]; and Prof. Chong Xie, [email protected]


1. Introduction

1.1 What are functional neural interfaces?

Engineered functional neural interfaces (fNIs)

serve as essential abiotic-biotic transducers between

an engineered system and the nervous system. They

convert external physical stimuli to cellular signals in

stimulation mode, or read out biological processes in

recording mode. Information can be exchanged using

electricity, light, magnetic fields, mechanical forces,

heat, or chemical signals. fNIs have found

applications for studying processes in neural circuits

from cell cultures to organs to whole organisms.

fNI-facilitated signal transduction schemes, coupled

with easily manipulable and observable external

physical signals, have attracted considerable

attentions in recent years. This enticing field is

rapidly evolving toward miniaturization and

biomimicry to achieve long-term interface stability

with great signal transduction efficiency. This review

covers the developments and applications of fNIs

that rely on nanoelectrodes, nanotransducers, or

bionanotransducers to establish an interface with the

nervous system.

1.2 Why are fNIs important?

In the past decade, the field of fNIs has

experienced a dramatic revolution. The once

electrical-engineering concentrated field has evolved

to a new stage that has absorbed an ever-large

research population and ever-diverse

multidisciplinary approaches. Not only a new

generation of neuroelectrodes has been invented, but

advanced fNIs that explore other physical modalities

of neuromodulation and recording have started to

bloom, partially stimulated by the great success of

optogenetics [1]. This new stage is facilitated by

advocations and funding supports on brain-related

research across the globe. Specifically, in the USA, the

Brain Research through Advancing Innovative

Neurotechnologies (BRAIN) and Stimulating

Peripheral Activity to Relieve Conditions (SPARC)

Initiatives aim to significantly promote brain and

bioelectric medicine research by accelerating the

development and application of novel and

paradigm-shifting neurotechnologies, among which

fNIs are of a major focus. Such demanding advances

in fNIs will greatly facilitate new opportunities not

only for studying basic neuroscience, but also for

diagnosing and treating various neurological

diseases.

1.3 Why nano?

Conventional electrode-based neurotechnologies

are facing two major hurdles: (1) susceptibility of the

abiotic-biotic interface to immune responses and (2)

communication inefficiency through the

abiotic-biotic interface [2]. Nano fNIs are compelling

in offering more effective solutions to both of these

two aspects.

1.3.1 Chronic stability

Even though many electrode-based

neurotechnologies have made great strides during

the preceding few decades in proving their feasibility

in treating and restoring impaired neural functions,

their clinical potential is severely restricted by issues

in integration of the neural interface within the

complex tissue environment. Not only do these

mechanically and chemically distinct neural

interfaces cause significant infection, but the

communication at the electrode-tissue interface is

significantly diminished as the implant is isolated by

fibrosis over time as a consequence of the

foreign-body reactions [3]. This discovery of fibrotic

encapsulation developing around the implanted

neuroelectrodes over a short time window of a few

months [4-7], which physically screens the electrical

sensors from accessing to the target neurons, has

largely shaped the thinking and practice in the field

in the past decade. The resulting new concepts in

neural interfacing have motived both the

development of a new generation of miniaturized

neuroelectrodes [2, 8-10] and the exploration of

alternative approaches that feature minimum or even

none invasiveness. Reduction of the footprint of the

neural implant down to the nanoscale to make it

less “sensible” to the host tissue environment has

proven to dramatically improve the chronic stability

of the neural interface [8-10]. Alternatively, to

mitigate the problems associated with the

conventional electrode-based approaches, such as the

requirement for implantation of the bulky interface

into the immediate target neural tissue [11],

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3 Nano Res.

nonspecific and variable activation, bio-fouling,

motion artifacts, and tissue damage [3], remotely

controlled approaches that leverage nanotransducers

or bionanotransducers in the pursuit of minimum

invasiveness, high spatial resolution, and cell-type

specificity have drawn unprecedented attentions.

These alternative nano fNIs hold great potentials for

better integration to the target neural tissue at the

tissue and cellular levels.

1.3.2 Functional efficiency

Realizing neural-realistic communication while

minimizing side-effects to neural circuits is of great

interest in the field. It requires developing fNIs that

comply with the biological mechanism of neural

signaling. Unfortunately, signal transduction at the

macro electrode-tissue interface is inefficient and can

lead to tissue injuries due to mismatched

communication mechanisms between the electronics

and target tissue [12-14]. Neuronal activity is

modulated by ion channel-mediated action potential

signaling, and thus ion channels naturally become

the direct target of physical stimuli. Working at a

scale close to the dimensions of single ion channels,

nano fNIs are promising in offering a high spatial

resolution, high target specificity, and high

communication bandwidth by allowing for a high

density and count of signal channels with minimum

material volume and area to minimize tissue

volumetric displacement and foreign-body reactions

[15, 16].

2. Nano fNIs for neural recording

2.1 Nanoelectrodes

Detecting the complex and dynamic activities of

the nervous system requires precise measurements of

the basic functional units—neurons. Neuroelectrodes

provide one of the most useful neurotechnologies by

allowing for time-resolved electrical detection of

neural activities and direct stimulation of neural

tissues. Therefore, pushing the limits of

electrophysiological recording and stimulation is of

great scientific and clinical interests [17-19]. Despite

important and unique capabilities, conventional

neuroelectrodes have significant limitations.

Intrinsically, electrophysiological recording of action

potentials (spikes) provides insufficient information

to establish definite correlation with individual

neurons, and often bias towards frequently firing

neurons. Unavoidable invasiveness of implanted

electrodes greatly restricts the number and density of

electrodes that can be implanted into the brain,

which leads to sparse sampling of the neural circuitry.

Furthermore, conventional neuroelectrodes typically

fail to provide consistently stable, high-quality neural

recordings over both the short- and long-terms

[20-22]. In time scales as short as hours, substantial

changes to the recording conditions often occur due

to micro-movements of the implanted electrodes

with respect to the brain tissue [23-25]. Over weeks to

months, deterioration in recording efficacy and

fidelity is caused by biotic and abiotic failures [26-29],

including sustained foreign body reactions at the

tissue-probe interface such as neural degeneration,

reoccurring blood leakage in capillaries and glial scar

formation [23, 30-34]. Recently, there have been

increasing interests in taking advantage of nano and

micro technologies to address the aforementioned

challenges in neuroelectrodes.

2.1.1 Nanostructure-enabled intracellular access

Two major types of electrophysiological recording

methods, intracellular and extracellular, have been

developed to measure action potentials with

complementary capabilities. Traditional

intracellular recording methods such as the

whole-cell patch clamp requires rupturing a portion

of the plasma membrane to access the cell interior

directly [35]. Whole-cell patch clamp (recording tip

diameter commonly ranging from close to 1 micron

[36] to several micrometers [37]) is the most

sensitive method to record electrophysiological

events of neurons, but is highly invasive and

technically difficult to implement, which precludes

long-term or large-scale recording. On the other

hand, extracellular recording methods such as

multi-electrode arrays utilize micropatterned

electrodes to afford long-term and multiplexed in

vitro measurements [38-40]. However, extracellular

recording suffers significantly in signal strength

and quality. This has therefore resulted in the need

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4 Nano Res.

for electrophysiological methods that combine the

advantages of both intracellular and extracellular

recording methods. In the past several years, there

have been developments that aim at achieving

intracellular recording with extracellular

nanoelectrodes or transistors while possibly

allowing for advantages of minimal invasiveness

and easy scalability. Although some structures

reviewed in this section fall into microscales instead,

their working mechanisms rely on nanoscale

structures or interactions.

It has been shown in multiple works that micro-

and nanostructures can promote tighter contacts at

the cell-electrode interface, which enhance recording

outcomes. Hai et al. pioneered in creating

mushroom-shaped micrometer-sized gold electrode

arrays that could detect attenuated intracellular

action potentials [41]. Xie et al. fabricated vertical

platinum nanopillar electrodes, with which they

demonstrated that these electrodes formed tight

junctions with cultured cardiomyocytes (Figure 1a

and 1b) [42, 43]. By local electroporation, the

nanopillar electrodes could enhance the action

potential recording with more than ten times greater

amplitudes and intracellular-like waveforms. Lin et

al. discovered that nanotubes were advantageous

than nanopillars in making and maintaining tight

junctions with the cell [44]. It was demonstrated that

iridium oxide nanotubes enabled a more effective

and stable intracellular access to cultured

cardiomyocytes. Robinson et al. fabricated vertical

silicon nanowire arrays that enabled intracellular

access to both record from and stimulate neurons

(Figure 1c and 1d) [45]. Abbott et al. further extended

this strategy by fabricating vertical nanoelectrodes on

a CMOS multiplexer, so that an array of 32 X 32

nanoelectrodes can be simultaneously addressed [46].

A similar strategy was also reported by Liu et al. [47].

Field effect transistor (FET) sensors, due to their

sensing mechanism, do not suffer from thermal noise

as the sensor size decreases, which is the major

limitation of passive electrodes. Tian et al.

developed FET sensors based on kinked silicon

nanowires [48]. Using cultured cardiomyocytes as an

in vitro model, they showed a clear transition from

extracellular to intracellular recording, as the tip of

the device slowly penetrated the cellular membrane

(Figure 1e-1j). A free standing version of the kinked

silicon nanowire FET sensor was created by Qing et

al. [49], in which individual branches of the kinked

nanowire could be adjusted to target specific cell

under a standard microscope. Duan et al. reported

the recording of a full amplitude intracellular action

potential in cardiomyocytes by silicon FET sensors

coupled with silicon dioxide nanotubes [50]. Fu et al.

further pushed the electrical detection limit by

producing a silicon nanotube and nanowire hybrid

FET electrode with the recording tip size less than 10

nm [51]. To probe fine structures in the neuron,

Jayant et al. took advantage of quantum dot (QD)

coated nanopipette electrodes to recover full back

propagation details of action potentials along

targeted dendritic spines [52].


5 Nano Res.

Figure 1 Representative nanoelectrodes. (a) Scanning electron microscopy (SEM) image showing that the nanopillar electrodes were strongly engulfed by a cell [42]. (b) Demonstration of the change in cellular membrane and corresponding recorded signal before and after electroporation. Nanopores were formed in the plasma membrane, enabling intracellular recording [42]. (c) SEM image of a 3-by-3 array of vertical nanowire electrodes [45]. Scale bar: 1 µm. (d) SEM image of nanowires interacting with a rat cortical neuron [45]. (e)-(j) Nanowire FET [48]. (e)-(g) Schematic diagrams showing the recording configurations. (h)-(j) Transition of the recorded signal from extracellular, transition period, to steady-state intracellular, as the probe slowly entered a cell. (a) and (b) adapted with permission from Springer Nature Ref. [42]; (c) and (d) adapted with permission from Springer Nature Ref. [45]; (e)-(j) adapted with permission from The American Association for the Advancement of Science Ref. [48].

2.1.2 Nanomaterials to reduce electrode impedance

As the electrode size decreases to increase

recording density or to minimize invasiveness, the

impedance of the electrode increases dramatically.

The thermal noise associated with the electrode

impedance becomes a major limitation. Nano

structures and materials have great potential in

significantly lowering the electrode impedance and

extending the electrode size limitation.

Owning to its highly porous structure that

increases the electrochemical surface area and

subsequently decreases the impedance, platinum

black has long been used in electrical recording. Kim

et al. improved the mechanical stability and electrical

property of platinum black by depositing bioinspired

adhesive polydopamine film in a layer-by-layer

manner [53]. Nanostructured porous platinum was

also demonstrated to increase the surface area of

electrodes by more than 30 times, thus reducing the

impedance by 77% [54]. Weremfo et al. fabricated

surface-roughened platinum electrodes that had

nano features and a superior charge injection

capacity comparing to titanium nitride and similar to

carbon nanotube (Figure 2a-2c) [55]. Park et al.

identified an optimal surface roughness factor of 233

to maximize the performance for electrical

stimulation and recording by nanoporous platinum

and yielded an impedance of 0.039 Ω·cm2 and a

charge injection capacity of 3 mC/cm2 (400 μs) [56].

Lee et al. deposited highly roughened nonporous

platinum film on gold tips of traditional silicon

electrode and greatly decreased the interface

impedance to 0.029 Ω·cm2 [57]. Chung et al. used CF4

plasma treatment to increase the surface roughness

of gold from 1.7 nm to 22 nm, drastically decreasing

the impedance by 98% [58]. Plasma treated electrodes

recorded signal with lower background noises and

evoked local field potentials (LFPs) with higher

amplitudes from anterior cingulate cortex in rats.

Chen et al. fabricated a carbon nanotube-based

electrode which had a lower impedance and 6 times

higher charge transfer capacity than gold

microelectrodes [59]. (More about CNT electrodes are

covered in section 3.1 and Figure 2d and 2e.) Kim et


6 Nano Res.

al. developed Au-nanotube composite electrodes

which reduced the impedance of gold electrodes by

99.3% [60]. They demonstrated in vitro extracellular

recordings from mouse cortical neurons, which had

an average signal-to-noise ratio of 92. Ju-Hyun et al.

modified electrodes with gold nanoflakes which led

to a reduction of impedance from 1.15 MΩ to 26.7 kΩ

at 1 kHz [61]. Kim et al. enhanced the charge storage

capacity as well as decreasing the impedance of

electrodes by depositing gold nanopourous

structures by dealloying Ag-Au alloy [62].

Bruggemann et al. demonstrated the fabrication of

vertical gold nanopillars on electrodes in an effort to

achieve a higher electrode surface area, which led to

a decreased electrode impedance [63]. Zhou et al.

incorporated gold nanorods onto polyimide

substrate to create a flexible thin-film microelectrode

array [64]. The nanostructure was able to bring down

the impedance by 25 folds. Zhao et al. reported a

relatively simple method to reduce electrode

impedance [65]. Electrodes were first

electro-co-deposited Au-Pt-Cu alloy nanoparticles

followed by etching away Cu. The remaining Au-Pt

composite exhibited a rough surface with pores of

different sizes. The electrode impedance was reduced

to 4.7% of that of the bare gold.

Kim et al. took a hybrid approach by depositing a

layer of iridium oxide on nanoporous gold, which

further reduced the impedance and increased the

charge storage capacity of the electrode (Figure 2f)

[66]. By combining the merits of platinum gray and

iridium oxide, Zeng et al. [67] deposited Pt gray and

IrOx on bare Pt in a layer by layer setup (Figure

2g). A decent adhesion of IrOx was enabled by the

large surface area of nanocone-shaped Pt. They

achieved impedance value of 2.45 kΩcm2 at 1 kHz

and a cathodic charge storage capacity (CSCc) 6, 2.8

and 2.7 times higher than those of electrodes with

bare Pt, Pt gray and IrOx, respectively.

Deng et al. [68] invented a one-step

electrochemical process to deposit graphene

oxide/polypyrrole composite sheet on platinum

electrodes in order to increase electrode surface

roughness (Figure 2h). The coated probe reduced the

impedance of bare platinum electrode by 90% and

increased the charge capacity density for more than

two orders of magnitude.

Besides reducing impedance, neurons seeded on

Graphene oxide doped poly(3,4-ethylene

dioxythiophene) (PEDOT) was found to grow longer

neurites than on PEDOT/PSS (polystyrene sulfonate).

Functional biomolecules such as laminin peptides

could be easily bonded to the graphene surface to

increase neurite outgrowth [69]. Such an electrode

demonstrated an improved sensitivity of 151 nA/μM

to dopamine comparing to a glass carbon electrode

and minimized interference from ascorbic acid, a

competing analyte [70].

In addition to being used as a coating material,

graphene oxide could serve as the electrode material

directly. Ng et al. [71] fabricated reduced graphene

oxide into disk microelectrodes of 10 μm diameter

and 60 μm pitch using nanoimprint lithography. The

electrodes featured a high sensitivity of 91 nA/μM to

dopamine with a detection limit of 0.26 μM without

using any functionalization process. The detection

capability was robust to highly resistive media,

continuous flow and mechanical stress.


Figure 2 Nanomaterials used to reduce electrode impedance. (a)-(c) Atomic force microscopy (AFM) images showing the morphologies of smooth, 3-min roughtened, 5-min roughened platinum surfaces [55]. (d) SEM images illustrating the nanofibrous network of

multi-walled nanotube (MWNT) bundle coated on an electrode surface. Scale bar: 500 nm [72] . (e) Carbon nanotube outperformed traditional electrode materials by having a lower impedance [72]. (f) Scanning transmission electron microscope energy-dispersive X-ray spectroscopy (STEM-EDS) element mapping image of iridium oxide coating on a nanoporous gold electrode [66]. (g) Morphology of IrOx/Pt gray coatings [67] . (h) Field emission scanning electron microscope (FESEM) image showing PPy grafted at the surface of graphene oxide sheets (circled) [68]. (a)-(c) adapted with permission from American Chemical Society Ref. [55]; (d)-(e) adapted with permission from American Chemical Society Ref. [72]; (f) adapted with permission from American Chemical Society Ref. [66]; (g) adapted with permission from Elsevier Ref. [67]; (h) adapted with permission from Elsevier Ref. [68].

2.1.3 Minimizing tissue invasiveness of neuroelectrodes

It is commonly agreed that a long-term stable

neural interface that can provide reliable neural

recording and stimulation with minimal tissue

invasiveness is of paramount importance in

advancing our knowledge of brain functions and

dysfunctions, as well as developing the next

generation neurotherapies [73]. A number of failure

modes have been identified and many approaches

have been hypothesized and tested for improving the

chronic stability of neural electrodes, including but

not limited to physical (dimension and mechanical

stiffness), chemical (delamination, corrosion of

electrodes) and biological (neuro-inflammatory, and

foreign body response) [74]. Among those highly

interplayed failure factors, geometry and mechanical

mismatches between neural tissue and electrodes

plays a critical role in determining the long-term

performance of the electrode-tissue interface. As a

result of such mismatches, traditional neural

electrodes may have micro movements with respect

to the host tissues or apply stresses. Such micro

movements not only prevent the tracking of the same

neurons as recording waveforms change accordingly,

but also induce neuron degeneration and bleeding

[75], which further cause chronic inflammatory

responses and accumulation of reactive oxygen

species, and eventually result in glial scarring and

accelerated electrode corrosion [76].

Seymour et al. discovered that thin electrodes (5

μm in thickness) placed as close as 25 μm from the

main silicon electrode shank (50 μm in thickness)

caused noticeably fewer neuronal cell death while

attracting less immune cells [77]. Schouenborg et al.

compared the neuro-inflammatory responses of two

probes having identical surgical damage profile but

different total surface areas [78]. Despite of the same

initial damage, the silicon lattice electrode with the

smaller surface area activated and attracted less

macrophages than their solid silicon counterpart.

Karumbaiah et al. investigated the probe

geometry-dependent inflammation by comparing the

foreign body response in both acute and chronic time


8 Nano Res.

scale of silicon electrode arrays that had disparate

thicknesses [79]. A 15 μm version outperformed a 50

μm version in terms of histological analysis and

activated immune cell density around the probe on

both 3- and 12-week checkpoints. These studies all

underscored the importance of electrode geometrical

dimensions in mitigating tissue reactions.

Carbon fibers have recently been a popular choice

to fabricate thin neuroelectrodes. Kozai et al.

demonstrated ultra-small 7 μm diameter carbon fiber

electrodes for high quality extracellular recording

[80]. These electrodes were shown to have

significantly reduced foreign body responses and

record single unit activities for over 4 weeks in vivo.

Guitchounts et al. employed bundles of 5 μm

diameter carbon nanofibers to fabricate penetrating

electrodes, and demonstrated more stable single-unit

recordings in vivo [81]. Patel et al. fabricated

16-channel arrays of 8.4 μm diameter carbon fiber

electrodes and demonstrated high-quality unit

recordings for up to 3 months post implantation [82].

No neuronal density change and minimal to none

astrocyte activation were observed in post-mortem

histology. Vitale et al. fabricated carbon nanotube

fiber electrodes, which were softer than carbon fibers

and offered smaller impedance and greater charge

injection capacity, making them more suitable for

stimulation [83]. In addition, these softer fiber

electrodes also elicited less chronic tissue responses.

Many efforts have also been put to make

neuroelectrodes flexible. Mercanzini et al. created

polyimide-based flexible probe to record LFPs, single

and multi-unit activities in mouse cortex [84].

Histology results demonstrated a reduction in

inflammatory response comparing to rigid electrodes.

Wu et al. developed a flexible intracortical neural

electrode with an 8 μm thick flexible construction

[85]. The electrodes were shown to record neural

activities for over six weeks. Du et al. compared the

chronic tissue reactions of a novel

poly(3,4-ethylenedioxythiophene)-polyethylene

glycol (PEDOT-PEG) based ultrasoft microwire and

conventional tungsten wire electrodes [86]. At both 1

and 8 weeks post-surgery, a significant reduction in

neuro-inflammatory responses was found for the soft

probe comparing to its rigid counterpart. Sohal et al.

investigated long-term (26–96 weeks) foreign body

responses in rabbit cortex induced by flexible

parylene-C based electrodes with microwire

electrodes as the control [87]. Less gliosis and greater

neuronal density were observed for the flexible probe.

More importantly, such effects were more prominent

towards the chronic time scale.

It is clear that the switch from conventional rigid

materials, such as silicon and metals, to softer

polymers, such as polyimide and parylene, helps

mitigate tissue reactions and promote the recording

stability. However, these polymers are still orders of

magnitude stiffer than the brain tissue [88], and

therefore the mechanical mismatch is still prominent.

On the other hand, it is impractical, at present, to

fabricate functional devices with materials that are as

soft as tissues. This dilemma led researchers to try

different approaches besides alternative materials.

Because most neuroelectrodes are constructed in

high-aspect ratio probe geometries, bending is the

major deformation happening at the interface.

Therefore, the primary goal of mitigating the

electrode-tissue mismatch is to minimize the bending

stiffness of the implanted probe, which is given by Ks

= Eswh3/12 for a probe with a rectangular

cross-section [10], where Es is the elastic modulus of

the material, w is the probe width, and h is the probe

thickness. It is clear that the geometry of the probe

(thickness and width) plays an important role in

modulating the bending stiffness. Therefore,

nanoelectronic devices could have unique and

important impact in promoting tissue integration of

neuroelectrodes.

A series of recent work has demonstrated neural

probes made by nanoelectronic devices based on

ultrathin polymer structures (Figure 3) [9, 10, 89-93].

The key feature of 1 μm thickness yielded

ultraflexibility that allowed for a great reduction in

the mechanical mismatches at the tissue-electrode

interface. This enabled chronically stable recording of

the same neurons over periods of multiple months.


9 Nano Res.

Figure 3 Increased flexibility improved tissue-electrode interface. (a) Photoacoustic images of two flexible carbon nanotube (CNT) electrodes inserted in the brain [93]. (b) Micrograph of a 3D mesh nanoelectronic brain probe suspended in buffer with a cylindrical shape [9]. (c) Chronic tracking of two detected neurons over a course of 4 months post-surgery [10]. Scale bar: vertical, 200 µV; horizontal, 1 ms. (d) Nanoelectronic probe as fabricated on a substrate [10]. Scale bar: 50 µm . (e) Two-photon imaging demonstrating little dislocation between neurons and an ultraflexible electrode during one month [10]. Scale bar: 50 µm. (f) Confocal micrograph of immunochemically labeled brain slice 5 months post-surgery, showing neurons surrounded the probe with minimum microglia activation [10]. Neurons were labeled in orange; electrode labeled as a green rectangle; and microglia indicated by white arrows. Scale bar: 50 µm. (a) adapted with permission from American Chemical Society Ref. [93]; (b) adapted with permission from Springer Nature Ref. [9]; (c)-(f) adapted with permission from American Association for the Advancement of Science Ref. [10].

2.1.4 High-density neural recording

One of the primary challenges of

neurotechnologies is to simultaneously record from a

large number of neurons. The nature of extracellular

recording determines that the electrode must be

within the close vicinity (~100 μm) of a neuron to

precisely detect its activity [94]. To record from many

neurons inevitably requires a large array of

electrodes placed on the surface of the brain or

inserted into non-superficial structures. Besides,

recording throughout a region requires that all

neurons be within the range of a recording site and

that recording sites be densely packed to allow

accurate spike sorting. In particular, the detection

range of each recording site is typically 50–100 μm

[95, 96], and spike sorting requires an electrode

spacing of 20–50 μm center-to-center [97, 98] to

resolve more single neurons.

In the efforts to push limits of recording density,

channel count and single unit yield, significant

challenges arise, such as addressing individual

channels and tissue displacement/injury.

Guo and DeWeerth developed an effective lift-off

method to pattern gold wires at high density on

stretchable substrates [99]. Based on this technique,

high-density compliant and stretchable electrode

arrays were fabricated and demonstrated by

interfacing with muscular tissue [88]. Khodagholy et

al. demonstrated the use of organic transistors to

record in vivo neural signals [100]. The transistors

were made of PEDOT on a highly flexible parylene

substrate with a total thickness of 4 μm. These

devices are capable of amplifying and multiplexing

signals locally, and potentially support high-density

surface recordings. Viventi et al. fabricated a

high-density electrode array multiplexed by silicon

nanomembrane transistors on a flexible

polyimide substrate [101]. LFP recording on the brain

surface was demonstrated in an animal seizure

model.

There are also significant recent efforts on making

penetrating neuroelectrodes with nanofabrication.

Du et al. nanofabricated a 64-channel probe with

interconnect width and spacing of 290 nm and

electrode pitch from 28 μm to 40 μm [95]. They found

that only 50% of all the identified putative thalamic

neurons were detectable with electrodes separated

more than 40 μm, which justifies the importance of

electrode array density. Similarly, Rios et al.

nanofabricated electrodes with features as small as

300 nm to enable high-density 3D recording [102].

They achieved a minimum inter-electrode distance of

16 μm, totaling 1024 channels (64 channels per shank)

and covering a tissue volume of 0.6 mm3. Single units

were found to show up on more than 6 channels,


10 Nano Res.

allowing for neuron trilateration. Unique

layer-specific field potential signatures across the

whole hippocampus facilitated the determination of

layer boundaries, which was subsequently validated

by histology result. An even denser array was created

by Scholvin et al. with 200 nm wiring width and 400

nm spacing [103]. 1000 electrodes (200 channels per

shank) were patterned on silicon probes with 11 μm

electrode separation (Figure 4a and 4b). A typical

recorded unit could manifest on more than 10

channels. Obien et al. fabricated a 128-channel

electrode array with on-chip μLED for

high-resolution electrophysiology coupled with

optogenetics [104]. Wei et al. nanofabricated

high-density electrode arrays on an ultraflexible

structure (Figure 4c-4e) [105]. The interconnect traces

had a width of 200 nm and a pitch of 400 nm,

addressing electrodes spaced as small as 20 μm. The

overall probe cross-section area was as small as 10

μm², which minimized chronic tissue reactions.

In addition to the passive approach, CMOS-based

active recording devices with buffer amplifiers

placed closely to individual electrodes were also

developed for high-density penetrating electrodes.

Lopez et al. patterned 455 electrodes on a shank

width of 100 μm, among which 52 could record

simultaneously, using 180 nm CMOS technology

[106]. Lopez et al. further developed this technology

and achieved 384 configurable channels out of 966

electrodes on a 70 μm wide shank with 130 nm

CMOS technology [107]. Recording with two of such

active CMOS probes were demonstrated in freely

moving rats (Figure 4f) [108]. A total of 700 single

units were recorded from 5 brain structures,

demonstrating the capability of acquiring large-scale

activities of hundreds of neurons.

High density nanosensors also enabled mapping

of electrochemical activities of neurons at superior

spatial resolution. With more than 20,000 sensors per

cell. Kruss et al. [109] fabricated single wall nanotube

based sensors that detected dopamine release at 100

ms resolution. They were able to investigate how

chemical communication of neurons were affected by

cell morphology and developed models to optimize

their probe design based on the spatially preserved

data [110].

For a detailed review of high-density neural

electrode array architectures and their respective

merits and challenges, readers are referred to Refs.

[111] and [112].

.


Figure 4 Nanofabricated high-density neural electrodes. (a) Individual high-density probe with 200 electrode channels [103]. The electrodes were spaced by 11 µm in a 1D arrangement. (b) Recorded spikes using the probe in (a). (c)-(e) High-density ultraflexible probes with 20 µm electrode pitch and 800 nm thickness [105]. (f) Schematic diagram and microscope image of an active CMOS high-density probe [108]. (a) and (b) adapted with permission from IEEE Ref. [103]; (c)-(e) adapted with permission from Wiley-VCH Ref. [105]; (f) adapted with permission from Springer Nature Ref. [108].

2.2 Nanotransducer-assisted functional neural

imaging

Imaging the electrical activity of neurons and

neural networks is of fundamental importance in

understanding their physiological functions and

treating their pathological dysfunctions. Their

electrical activity can be recorded through the

electrodes in a patch clamp or microelectrode array.

These electrical recording techniques are invasive

and incapable of recording neural activity from a

large region of interest, which has promoted the

optical imaging approaches. As calcium ion (Ca2+) is a

critical indicator of neuronal activity, Ca2+ imaging is

a powerful tool to study the neural activity [113].

However, the Ca2+ dynamics is slower than that of the

actual action potential, and only suprathreshold

neural activities can be recorded [114]. Thus, directly

imaging the transmembrane potential of neurons

with high spatiotemporal (micrometer and

sub-millisecond) resolutions, sensitivity up to

subthreshold activity, and versatility for both

excitation and inhibition, is greatly desired. Although

the voltage-sensitive dyes (VSDs) for voltage imaging

(discussed in details below) have a high

spatiotemporal resolution and capability of imaging

a large region of interest, they are constrained by

sensitivity, photobleaching, and phototoxicity [115].

Thus, semiconducting nanotransducers, especially

QDs, with higher photoluminescence intensity and

photostability have attracted attention for potential

application to voltage sensing in neurons.

Due to quantum confinement, QDs can be excited

by light, creating excitons, pairs of separated

negatively charged electrons and positively charged


12 Nano Res.

holes [116]. An electric field applied onto the excited

QDs leads to a quantum-confined Stark effect,

decreasing the energy of electrons and holes [117]. As

a result, their photoluminescence intensity is

quenched, and the emission peak is red-shifted and

broadened. This property well aligns with the needs

for optical voltage imaging. A theoretical study

showed that the membrane potential of an action

potential could result in such photoluminescence

quenching and red-shift in type-II QDs, and that QDs

would have a higher sensitivity comparing to VSDs

[118]. In a follow-up work, the use of type-I and

quasi-type-II QDs to image a voltage resembling an

action potential with millisecond temporal resolution

was experimentally confirmed [115]. In this work, it

was also claimed that the photoluminescence

quenching by QDs was attributed to an increase of

ionized QDs and that quasi-type-II QDs had a higher

sensitivity than type-I QDs. In a more recent

theoretical study, modeling showed that type-I and

type-II semiconducting nanorods could have even

higher sensitivity than QDs, while the sensitivity of

type-II nanorods was higher than that of type-I

nanorods [119]. However, the nanorods needed to

vertically and symmetrically penetrate the plasma

membrane, which was technically challenging.

Up to now, the QD- or semiconducting

nanorod-assisted voltage imaging has not been

biologically validated. The physiological scenario is

far more complicated than theoretical simulation.

Once tested in neurons, there are still major practical

challenges associated with their voltage sensitivity,

placement and biocompatibility. Voltage imaging

requires the nano sensors to be placed in the vicinity

of or within the plasma membrane. The QDs

delivered to the plasma membrane are, however,

rapidly internalized, and the placement of QDs is

dynamically changing. Considering the fast voltage

dynamics comparing to the endocytosis dynamics,

this should not affect a single measurement within a

short period of time but will require repetitive dosing

for separate measurements, which will worsen the

cytotoxicity of QDs. Thus, exploring nanotransducers

that can convert voltage to an observable and

readable signal and meanwhile can serve as stable

and biocompatible interfaces is essential for the

development of nanotransducer-assisted voltage

imaging in neurons.

2.3 Bionanotransducer-enabled functional neural

imaging

Comparing to electrode-based neural recording

approaches, optical techniques offer complementary,

yet compelling, advantages for imaging the

transmembrane potentials, including less

invasiveness and superior spatial resolution [120].

Optical recording or imaging can capture both the

electrical activities of each neuron in the circuit and

map with micrometer resolution and sub-millisecond

precision.

Nanobiotechnologies for optical neural imaging

are mostly based on genetically encoded proteins, for

their remarkable biocompatibility and optical

properties, fast response dynamics, high effective

sensitivity, and easy functional modification.

Protein-based optical sensors can be used to measure

transmembrane potentials in single cell, tissue, and

living animals through collection of the exhibited

fluorescent signals. A number of optical imaging

methods based a variety of mechanisms have been

explored for the benefits of neuroscience research.

2.3.1 Voltage-sensitive dye imaging

Traditional voltage-sensitive dye imaging (VSDI)

is based on a fluorescent change of small molecular

dyes when subjected to a change of a local electric

field. For its good spatial (up to 20 m) and temporal

(up to tens of microseconds) resolutions, this

approach offers a great potential in visualization of

the information processing in the nervous system

[121, 122]. After decades of development and

optimization, VSDI exhibits facile delivery into living

preparations for long-term observation, from

dissociated neurons to frogs, rats, and nonhuman

primates [123-125].

Typical VSDs possess an amphiphilic structure, in

which the hydrophobic components work as anchors

into the cellular membrane, and the hydrophilic

components, mostly chromophores, array

perpendicularly to the cellular membrane. The

intensity changes of the fluorescent signal correlate to

the transmembrane voltage changes, and the neural

activity can be measured accordingly. The most

common imaging mechanism is redistribution

(Figure 5a). A change in the transmembrane potential

causes the charged chromophores to move in or out


13 Nano Res.

of the cell, leading to a regional concentration change

of the chromophores with a corresponding change in

the fluorescence intensity. Another mechanism is

called reorientation (Figure 5a), which is determined

by the interaction of the intermolecular electric fields.

Additionally, electrical modulation of the electronic

structure and fluorescent resonance energy transfer

(FRET) can cause fluorescence changes in response to

changes of the transmembrane potential (Figure 5b).

In addition to the commonly used VSDs (ANEP

and RH families) [126], QD-based approaches, as

mentioned above, provide an alternative opportunity.

Functional modification using biomolecules can both

reduce the cytotoxicity of QDs and provide

functional targeting sites to the neuronal membrane

for voltage imaging [118]. Recently, Nag et al.

reported a QD-peptide-fullerene nanobioconjugate

for imaging membrane potentials in living cells [127].

This alanine/leucine-rich peptide was designed to be

helix-forming to promote membrane insertion. It also

could append the fullerene component at discrete

fixed distances for the signal detection and facilitate

energy transfer via tunneling. The imaging of PC-12

cells showed a 20- to 40-fold improvement in F/F

with no sacrifice in responsivity. Thus,

protein-modified nanotransducers also play

important roles in specific targeting to the cellular

membrane, enhancement of biocompatibility, and

connection between two FRET components, with

minimum effect on the fluorescent signal.

2.3.2 Genetically encoded fluorescent imaging

Neural activities are encoded in dynamic

fluctuation of the transmembrane potential,

including both subthreshold and action potentials. To

visualize the dynamic changes of the transmembrane

voltage, which range from ~1 mV (e.g., postsynaptic

potential caused by a single vesicle release) to over

100 mV (i.e., action potential) and span from 100 ms

(axonal conduction) to 10 s (plateau potential),

genetically encoded optical indicators offer a great

promise. Nanobiotechnological engineering

approaches have been used to fuse the fluorescent

chromophores with other domains that undergo

conformational changes in response to cellular events

such as intracellular Ca2+ concentration,

transmembrane potentials, and small metabolites

and other ions. Two major classes of genetically

encoded optical indicators have been developed: one

is genetically encoded calcium indicators (GECIs),

which have a Ca2+-binding domain and a Ca2+

concentration response conformation; another is

genetically encoded voltage indicators (GEVIs),

which have a domain responsive to the

transmembrane potential changes.

Genetically encoded calcium indicators: Developed since

1997 [128], GECIs monitor changes to the

intracellular Ca2+ concentration caused by action

potentials. As a ubiquitous second messenger, Ca2+ is

of great significance in all aspects of cellular

physiology. Triggered by an action potential, an

increase in its intracellular concentration, from 20-100

nM (initial concentration) to 5-10 M (peak

concentration), causes a change to the fluorescence

[129]. Briefly, the design of GECIs involves a fusion of

two parts: a naturally evolved Ca2+-binding protein

component that undergoes a conformational state

transition in response to Ca2+ binding (calmodulin

(CaM) [128] or troponin-C (TnC) [130]) and a

reporter component based on a

conformation-sensitive fluorescent protein (FP).

Two types of signals are recorded according to the

type of reporter component (Figure 5c). Simple

fluorescence signal is collected through the

conformational transition of single FP component

[131]. A pair of FPs exhibits FRET, which could

provide a measure of Ca2+ concentration by the ratio

fluorescence signal between the two FPs [128]. FRET

signal is a better alternative due to its independence

on probe concentration, low excitation light intensity,

and low absorption in the optical path. For example,

as a typical GECI, yellow cameleon (YC) 3.60 has a

pair of enhanced cyan FP (ECFP) as donor and Venus

protein FP with circularly permuted conformation

(cpYFP) as acceptor. In the presence of Ca2+, its

intramolecular conformation changes lead to a

reduced spatial distance and illuminate the Venus

protein, and the ratio change of YFP/CFP is up to 6

folds with a high Ca2+ dynamics up to 0.25 M [132].


Figure 5 Bionanotransducer-enabled functional neural imaging. (a) and (b) Mechanisms of VSD imaging: redistribution (a) left, reorientation (a) right, and FRET (b). (c) GECIs based on single fluorophore and FRET mechanisms. After binding of Ca2+ to GCaMP, conformational changes induce an increase in emission (left) or a change to the ratio of emission intensities (YFP/CFP) [131, 132]. (d) Mechanisms of GEVIs. Left, single FP-based VSFPs exhibit fluorescent quenching upon membrane depolarization; right, FRET-based VSFP-Butterfly family has a fused four-transmembrane-segment voltage-sensitive domain between two FPs [133]. (e) VSFP2.3 reported transmembrane voltage transients through two different FPs [134]. (f) Extracellular electrical stimulation induced an increase in intracellular Ca2+ concentration in myotubes with the expression of GCaMP [131]. Figure credits: (e) adapted with permission from Ref. [134]; (f) adapted with permission from Ref. [131].

The mostly optimized GECIs are single-wavelength

green indicators based on the original GCaMP

sensor. The reporter domain of GCaMPs is a

circularly permuted enhanced green FP (EGFP),

which is flanked between Ca2+ binding protein

CaM and CaM-binding peptide M13. In the

presence of Ca2+, CaM-M13 interactions lead to

conformational change and an increase in

fluorescent emission [131, 135]. A number of

engineered variants of GCaMP have been reported,

and these indicators are composed of constituent

molecules to achieve specific manipulation of

sensor applications [136-138].

Since the first GECI was reported with the

chromophore green FP (GFP), the modulation of

indicator color has been well explored. Directed

mutation of the side-chains comprising the

chromophore can tune the excitation and emission.

A number of improved variants of the original blue,

cyan, yellow and red FPs [133] have been

developed to improve the brightness, photostability,

tissue penetration and signal-to-noise ratio.

To avoid interferential interactions of CaM with

endogenous binding factors and improve the

detection precision, two effective approaches are

pursued: one is the replacement of CaM with

troponin C variants, which is the Ca2+ binding

protein in muscle cells and does not have an

endogenous binding site in neurons [139] [130]; the

other is the modification of binding interference.

Palmer et al. reengineered the binding interface

between CaM and a target peptide to generate

selective and specific binding pairs that could be no

longer perturbed by large excesses of native CaM,

and the Ca2+ detection sensitivity turned over a

100-fold range at 0.6-160 M [140].


15 Nano Res.

In addition, optimization of GECIs focuses on

the modulation for specific applications and better

optical properties, such as optimization on the Ca2+

binding constant [135, 141], subcellular targeting

[142], brightness, and red-shifting of the fluorescent

indicators for large penetration and good

resolution [143].

GECIs can be used in combination with

two-photon imaging to achieve improved

measurements in highly scattering medium with a

greater signal-to-noise ratio without the need of

averaging. Mank et al. generated a GECI as

TN-XXL for two-photon ratiometric imaging in

visual cortex. They rearranged the Ca2+ sensing

moiety TnC within the indicator and mutagenesis

of selected amino acid to increase overall signal

strength and sensitivity in the low Ca2+ regime

[144].

GECI fluorescence imaging is a good proxy to

record average action potential changes, but it has

an inherent inadequacy. Because Ca2+ transients are

100-1000 folds slower than the underlying electrical

waveforms, most subthreshold changes of

transmembrane potentials cannot elicit a change to

the Ca2+ concentration, and the Ca2+ dynamics is

confounded by the complicated interactions

between different Ca2+ sources and intrinsic or

extrinsic Ca2+ buffers. Hence, weak and brief

changes of the transmembrane potentials may not

be recorded by the Ca2+ indicators [114, 145].

Genetically encoded voltage indicators (GEVIs): GEVIs

may be preferred over GECIs, for their capability of

directly reporting both synaptic and action

potentials and capturing the entire voltage

dynamics. Several different approaches to build

GEVIs have been developed since 1997. Most

GEVIs consist of two components: a

voltage-sensitive domain from an ion channel as

the voltage sensor and a component that binds in

the plasma membrane and experiences the voltage

changes.

Same as GECIs, two types of fluorescent signals

based on different response mechanisms can be

collected: one is the single fluorescent signal from a

single fluorescent moiety [146-148], which

undergoes a significant conformational change that

alters its spectra; and the other is ratiometric

signals based on FRET between a pair of

fluorescent moieties [134, 149], which are both

involved in the molecular interactions and motions,

leading to ratio changes in fluorescence intensity

(Figure 5d). Signals from a single FP have limited

sensitivity, while the ratiometric FRET signals can

significantly reduce the effects of motion and blood

flow in complex environments.

Several GEVIs based on different fluorescent

chromophore families are developed. For example,

the fluorescent Shaker (FlaSh) and sodium channel

protein-based activity reporting construct (SPARC)

are based on simple fluorescent signal detection,

while the voltage sensitive FP (VSFP) uses an FP

pairs based on FRET [150-152].

Siegel et al. reported an early attempt on FlaSh

[150]. They constructed a GFP-Shaker fusion

protein, using a nonconducting mutant of a

voltage-gated K+ channel as the voltage-responsive

site and an FP inserted into the K+ channel protein

as a reporter. This GEVI had a maximal fractional

fluorescent change of 5.1%. Guerrero et al.

expanded the FlaSh GEVIs by modifying the

kinetics, dynamic range, and color. The improved

folding enhanced the detection sensitivity, and the

availability of different FP colors promoted wide

adoptions [153]. The SPARC was developed with a

strategy to insert a GFP molecule into a rat muscle

Na+ ion channel subunit, which exhibited rapid

response kinetics without significant inactivation

[151].

As the key component in the FP-based GEVIs,

VSFP underwent a lot of research. The first

generation of VSFPs was derived from the

voltage-sensing domain of a K+ channel subunit

[152]. This VSFP consisted of a voltage sensing

domain of a K+ channel and a pair of cyan and

yellow emission mutants of FPs. Although this

generation of VSPFs could optically report changes

in the transmembrane potential, their application to

functional imaging of mammalian neurons was

limited by their low targeting capability to the

membrane [154]. The second generation of VSPF

(VSPF2) was based on Ci-VSP (Ciona intestinalis

voltage sensor-containing phosphatase), exhibited

better membrane targeting and formed a big

Ci-VSP GEVI family [120]. Akemann et al.

developed FRET-based VSFP2s by changing the


16 Nano Res.

enzyme domain of Ci-VSP with two tandem

fluorescent domains, which exhibited more

efficient targeting to the cellular membrane and

higher responsiveness to the transmembrane

potentials [134]. The variant VSFP2.3 was

developed as a FRET-based indicator possessing

the capacity of imaging both spontaneous action

and synaptic potentials in neurons [155]. The

indicator VSPF3.1 was the fusion of Ci-VSP and a

single red-shift protein, which offered the

advantages of a red-shifted spectrum and relative

fast overall kinetics [156]. The VSPF Butterfly series,

with a sandwiched structure between two FPs and

a middle voltage sensitive domain, showed a

subthreshold detection range and fast kinetics for

single-cell synaptic responses in applications from

single neurons to the brain [157].

Besides of FP-based GEVIs, microbial rhodopsin

could also be used as the fluorescent voltage

reporter [158, 159]. This retinal chromophore

shows very weak near-infrared fluorescence, while

upon light-driven transport of protons, a change in

the chromophore emission was induced.

Comparing to FP-based GEVIs, GEVIs based on the

microbial rhodopsin have a sub-millisecond

response time and better voltage sensitivity

[158-160]. GEVIs based on non-pumping mutants

of Archaerhodopsin 3 (Arch) have voltage

sensitivities between 30-90% per 100 mV and

half-maximal response times between 50 s and 1.1

ms at room temperature [160]. However,

Arch-derived GEVIs exhibited weak fluorescence,

more than 30-fold weaker than that of FPs.

Meanwhile, to illuminate microbial

rhodopsin-based GEVIs, the excitation laser power

needs to be much higher, typically 300-1000 W/cm2,

much more than that of FP-based GEVIs (10 W/cm2)

[160]. The low brightness of rhodopsin-based

GEVIs presents a challenge for widespread use.

Current efforts on the development of GEVIs

primarily focus on optimization of existing sensor

constructs, including the voltage range, color,

brightness, response kinetics, and cellular targeting

properties. As key indicators to evaluate sensing

performance, response sensitivity (F/F),

half-maximal response times, signal-to-noise ratio

and excitation power all need to be considered. The

first generation of GEVIs exhibited modest voltage

sensitivity (< 5% F/F per 100 mV) and slow

kinetics (10-200 ms). The second generation of

Ci-VSP-based GEVIs had a novel GEVI (Arclight)

consisting of a Ci-VSP and a super ecliptic

pHluorin that carried the point mutation A227D

[146]. Arclight A242, derived from Arclight,

exhibited a fluorescent intensity increase by 35%

F/F per 100 mV, but the response time (10 ms) was

much slower, hindering action potential detection.

In another GEVI design, called ASAP1, a circularly

permuted FP was inserted in an extracellular loop

of a voltage-sensing domain [148]. ASAP1

exhibited high sensitivity (18-29% F/F per 100mV)

and high kinetic speed (2 ms) and could be used for

action potential detection at waveforms up to 200

Hz.

GECIs and GEVIs have exhibited the capability

of recording neuron potentials in multiple

mammals and neuron types, but the use of them in

humans seems unlikely at present, because its

delivery involves viral vectors. The development

and optimization of genetically encoded indicators

still continue. The ideal GECIs and GEVIs should

process properties such as: large voltage/Ca2+

induced fluorescent changes over a physiological

range, quick response kinetic time

(sub-millisecond), targeting capability to different

neuron types, good photostability, large brightness

and signal-to-noise ratio, and red/near infrared

emission for in vivo application.

3. Nano fNIs for neural stimulation

3.1 Nanoelectrodes

3.1.1 Microstimulation with nanomaterial coatings

Nanostructured surfaces and nanomaterial

coatings have been shown to improve the charge

storage capacity and charge injection limit of

microelectrodes, which results in more effective

stimulation including smaller voltage, greater

power efficiency, and less tissue damage.

Carbon nanotube-based electrodes were found

to offer lower impedance and improved charge

injection comparing to platinum, making it a

suitable candidate for electrical recording and

stimulation. Wang et al. first reported the use of

vertically aligned multiwall carbon nanotube to


17 Nano Res.

stimulate excitable cells (rat hippocampus neurons)

[161]. Tsang et al. reported the use of Au-carbon

nanotube composite electrode fabricated on flexible

polyimide substrate [162]. As a result of the lower

stimulation voltage and less power consumption,

the stimulation could be done wirelessly. The

resulting device forms an insect machine interface

in which the flight path of moths could be biased

by selectively stimulating one side of the moth

body. Yi et al. developed vertically aligned carbon

nanotube electrodes on flexible substrates and used

them to stimulate rat sciatic nerve and record from

rat spinal nerve with a signal-to-noise ratio as high

as 12.5 [163]. Jan et al. quantified the impedance

and charge storage capacity of iridium oxide,

PEDOT, and layer-by-layer synthesized multiwall

carbon nanotube [72]. Carbon nanotube

outperformed traditional electrode materials by

having a lower impedance and higher cathodic

charge storage capacity. In addition, no sign of

failure was observed after 300 cycles of cyclic

voltammetry scan.

3.2 Nanotransducer-assisted neural modulation

The emerging concept of going wireless has

been revolutionizing the contemporary

technologies and reshaping the modern lifestyle. It

is also driving the advancement of medical devices

[164]. Conventional neural modulation techniques

deliver electrical signals to the target neural

population. Due to fast dissipation and attenuation

of the electrical signals through tissues, these

traditional techniques often demand invasive

placement of the electrodes in the immediate

vicinity of the target neural regions and

implantation of a pulse generator wiring to the

electrodes to deliver the electrical signals. Surgical

procedures cause tissue damage and surgical

complications [165], and chronic inflammation

around the electrodes causes scar tissue formation

and early device failure [166]. Alternative strategies

to neural modulation, which rely on direct wireless

delivery of magnetic field, ultrasound, and infrared

light to the target neurons, unnecessitate the

electrodes but are limited in spatial resolution

and/or power efficiency. These deficiencies have

motivated the development of a new generation of

nanotransducer-assisted wireless neural

modulation techniques featuring minimal or even

none invasiveness with greatly improved

spatiotemporal precision and cellular targeting

specificity.

Like wireless charging, in which the

electromagnetic energy is transmitted through the

intermedium and converted to electrical currents

by an antenna in the target battery, a primary

wireless signal (e.g., optical, magnetic or acoustic)

can be transmitted through tissues and converted

to a secondary local signal (e.g., electric, thermal,

optical or mechanical signal) by nano

antenna-transducers to modulate the target neuron.

These nanotransducers are essential for delivering

the highly localized secondary signal with spatial

precision, target specificity, and improved

efficiency. Due to their small size and novel

physicochemical properties, these

nanomaterial-based nanotransducers perfectly

align with these demands. Firstly, they can be

delivered to the target region via

minimally-invasive local or intravenous injection.

Secondly, their diverse energy transduction

schemes allow the conversion of a medically safe,

tissue-penetrating primary signal to a localized cell

modulatory secondary signal at the

nanotransducer-neuron interface [167].

Additionally, their ease of surface modification and

bio-conjugation can facilitate specific targeting to

the targeted neuron population at cellular and even

subcellular levels, dramatically improving the

target specificity, selectivity and spatiotemporal

resolution.

Over the past few decades, particularly last

decade, a great deal of efforts has been made to

develop such nanotransducer-assisted wireless

neural modulation techniques. In the literature,

these techniques are commonly categorized by the

primary wireless signals. In contrast, in the present

review these techniques are categorized by the

secondary local signals to elucidate the concepts

and design rationales, as the secondary signal is the

ultimate modulatory signal to the target neuron.

For example, manipulation of ion channels plays

an important role in neural modulation, and there

are various types of ion channels, including

voltage-gated, temperature-gated,

mechanosensitive, and light-gated. Thus, the local


18 Nano Res.

secondary signal needs to be generated by the

nanotransducers to gate the corresponding ion

channels and eventually modulate the neuronal

activities. Here, these diverse types of

nanotransducers can be classified into

electrotransducers, thermotransducers,

optotransducers, and mechanotransducers based

on the type of secondary signal they generate.

To develop such nanotransducer-assisted

wireless neural modulation techniques, there are

several key factors to consider, including the

primary signal, secondary signal, nanotransducer’s

biosafety, biostability, placement, and modification,

as well as cell modification.

Primary signal: The primary signal needs to be safe

and wirelessly transmittable through tissues to

reach the target region. Although light, magnetic

field, and ultrasound can all meet these two criteria

to possibly serve as a primary signal, their

interactions with tissues affect their penetration

depth and spatial resolution (i.e., how well the

primary signal can be focused on the target region).

Light has superior spatial resolution of 10-7 m,

while it can barely pass the cranium (10-6 m travel

depth) and only penetrate dermal tissues as deep

as 4 millimeters [168, 169]. Thus, for deep neural

tissue modulation, implantation of a light source is

usually required. Transcranial focused ultrasound

travelled through skull and modulated the cortical

activity 30 mm deep in human brains with spatial

resolution of 10-3-10-2 m [170]. The penetration

depth and spatial resolution of transcranial

magnetic stimulation are highly dependent on the

coil design. For example, 50 coil design has

penetration depth and spatial resolution of 10-2 m

[171]. For these primary signals, there is a tradeoff

between penetration depth and spatial resolution

[170, 171]. Additionally, the interactions of primary

signals with tissues may also generate noxious heat,

limiting the maximum intensity of the primary

signal.

Secondary signal: The secondary signal needs to be

able to modulate neurons by gating the respective

ion channels, activating cell signaling pathway,

changing the plasma membrane capacitance, etc.

Possible secondary signals include electric field,

heat, light, and mechanical force. Generation of the

secondary signal should be controlled to exceed the

threshold for cellular modulation but not to exceed

the safety limit that can cause cell damages.

Theoretical simulation can be used to help assess

the feasibility of a signal transduction scheme and

guide the experimental design and optimization.

Additionally, the temporal resolution of the

modulation significantly depends on how fast the

neurons respond to the secondary signal.

Nanotransducer biosafety and biostability: The

nanotransducers need to serve as stable neural

interfaces within the modulation period, and they

must be safe in the physiological environment.

They should cause no toxicity and minimal

inflammation. Moreover, they should remain intact

to maintain the functional interfaces and not to

release or leak toxic substances. Their biostability

can be challenging. First, certain nanotransducers

are prone to degradation due to the physiological

acidic pH and enzymatic activities. Second, the

exogenous nanotransducers are also prone to

clearance, so their placement is dynamic instead of

static.

Nanotransducer placement and distribution: Overall,

nanotransducers can either be in a

dispersed/injectable form or immobilized onto a

substrate or microelectrode (Figure 6a). The

dispersed nanotransducers can be placed

extracellularly, targeted to the plasma membrane

(e.g., onto the membrane, receptors, anchoring

proteins or ion channels), or internalized.

Immobilization of nanotransducers onto a

substrate or microelectrode facilitates the build-up

of the secondary signal to reach the threshold and

control of the nanotransducer distribution, but the

implantation increases invasiveness. On the

contrary, injectable and monodispersed

nanotransducers minimize invasiveness, but their

distribution needs to be carefully controlled, as

their placement and distribution affect the

cytotoxicity, modulation efficacy, efficiency, and

consistency. For example, unbound and

extracellularly distributed nanotransducers

prolong the stability of the interface but tend to be

removed by the fluid circulation, such as the

cerebrospinal fluid in the central nerve system. On

the other hand, binding of nanotransducers to the


19 Nano Res.

plasma membrane, receptors or ion channels

improves the specificity and washout resistance,

but they can be rapidly internalized. The

internalized nanoparticles can cause toxicity and

modulation inconsistency [172, 173]. Additionally, a

complete retrieval or clearance of the

nanotransducers after the modulation can be

challenging for dispersed nanoparticles.

Nanotransducer modification: Nanotransducers are

usually surface-modified so that their dispersity

and biocompatibility can be improved. They can be

immobilized on a substrate, specifically targeted to

a neural population or even to the receptors and

ion channels. However, surface modification can

attenuate the secondary local signals and increase

the distance between the nanotransducers and the

modulation target. Moreover, the surface chemistry

needs to be well controlled, because certain surface

chemistry, even without inducing clear cytotoxicity,

may cause false modulatory effects due to plasma

membrane perturbation [174].

Cell modification: Genetically engineering certain

types of neurons to express the target ion channels

enables and optimizes the cells’ response to the

corresponding secondary local signal. Neurons can

also be genetically modified to express binding

sites for nanotransducer docking and create

hallmarks for evaluating the modulatory effect.

These cell modification strategies make the

modulation technique versatile and adaptable for

different types of cells. They can also improve the

modulation specificity and selectivity through

selective engineering of the target neuron

population. However, the viral vectors used for the

cell modification can cause immune responses, and

the transfection is usually irreversible. Thus, cell

modification by genetic engineering brings safety

and moral concerns and thwarts their clinical

applications.

Considering these critical factors, we herein

review four main types of nanotransducers for

wireless neural stimulation: electrotransducers,

thermotransducers, optotransducers, and

mechanotransducers. Each type is further

subdivided by the types of nanomaterial used.

These nanotransducers are summarized regarding

these factors in Table S1.


Figure 6 Nanotransducer-assisted neural modulation. (a) Placement of nanotransducers: nanotransducers can be dispersed extracellularly (1), coated on a substrate (2), bound to the plasma membrane (3), targeted to receptors or anchoring molecules in the plasma membrane (3’), targeted to ion channels in the plasma membrane (3”), and internalized (4). (b) and (c) Semiconducting nanorods-based electrotransducers, adapted with permission from Ref. [175]. (b) Semiconducting nanorods convert light to electric fields. (c) A train of extracellular spikes triggered by a light pulse. (d) and (e) Magnetoelectric nanomaterials-based electrotransducers, adapted with permission from Ref. [176]. (d) Magnetoelectric nanomaterials convert a magnetic field to electric fields. (e) Modulated EEG waveforms. (f) and (g) Piezoelectric nanomaterials-based electrotransducers, adapted with permission from Ref. [177]. (f) Piezoelectric nanomaterials convert ultrasound to electric fields; (g) Ca2+ influxes following an ultrasound pulse. (h) and (i) Gold nanomaterial-based thermotransducers, adapted with permission from Ref. [178]. (h) Gold nanomaterials convert light to heat. (i) A train of action potentials, of which each was evoked by a light pulse. (j) and (k) Superparamagnetic nanoparticle-based thermotransducers, adapted with permission from Ref. [168]. (j) Superparamagnetic nanoparticles convert a magnetic field to heat. (k) Peristimulus time histogram. (l) and (m) Upconverting luminescent nanomaterial-based optotransducers, adapted with permission from Ref. [179]. (l) Upconverting luminescent nanomaterials convert NIR light to visible light. (m) A train of action potentials, of which each was evoked by an NIR light pulse. (n) and (o) Superparamagnetic nanoparticle-based mechanotransducers, adapted with permission from Ref. [180]. (n) Superparamagnetic nanoparticles convert a magnetic field to mechanical forces. (o) Peristimulus time histogram.

3.2.1 Nano electrotransducers

Electrical signals are used to modulate neurons in

the conventional modulation techniques. Instead of

being transmitted from an electrical stimulator to

electrodes through wires, electrical signals can also

be converted locally by nanotransducers from other

wirelessly transmitted physical signals to target

voltage-gated ion channels for neural modulation

[181, 182]. For example, light, magnetic field, and

ultrasound can be converted by QDs, magnetoelectric

nanomaterials, or piezoelectric nanomaterials to local

electric fields to modulate neurons, respectively.

QDs—from light to electric field: Upon excitation, QDs

convert light to electric dipole (electron-hole pair) via

quantum confinement. The electric field created by

the electric dipole can serve as a secondary signal to

modulate neurons [183]. The excitation wavelengths

of QDs range from ultraviolet to visible and


21 Nano Res.

near-infrared (NIR), and the tissue penetration depth

and spatial resolution of light depend on its

wavelength. The shorter the wavelength, the less

penetration and the higher resolution. NIR light

within the first NIR window (700-950 nm) and

second NIR window (1,000-1,350 nm) has the

minimal interactions (scattering and absorption) with

tissues [184, 185], so NIR light has the maximal

penetration through dermal tissues, as deep as 4 mm,

but the lowest resolution [169]. Thus, selection of

QDs with their excitation wavelengths depends on

the target application. For example, light of short

wavelengths is only suitable for superficial neural

modulation, such as in retinal prostheses, while light

of longer wavelengths can be used for deeper

intervention. As to the electric field, mathematical

modeling showed that an excited QD could evoke an

action potential if the distance between the QD and a

voltage-gated ion channel was within 2 nm [186, 187].

Thus, intimate contacts of QDs to the neuron’s

membrane are realized by targeting the QDs to the

plasma membrane or coating them onto a neuronal

culturing substrate.

However, due to their tiny size (2-6 nm), QDs are

easily internalized through endocytosis. Attempts to

creating an fNI by targeting bio-conjugated QDs

directly to the plasma membrane rarely succeeded

[187, 188]. Thus, efforts were mainly focused on

improving the interface stability by immobilizing

QDs onto a substrate.

The initial contrivance of fNIs by immobilizing

QDs onto salinized and poly-D-lysine coated

substrates achieved slightly improved stability for 1

day and 3 days, respectively [187]. By culturing

NG108-15 cells on a layer-by-layer film containing

repeating layers of HgTe QDs and

poly(dimethyldiallylammonium chloride), Pappas et

al. demonstrated that cells were depolarized and

even evoked to fire action potentials upon irradiation

with 532 nm laser pulses (duration: 500 ms;

irradiance: 800 mW/cm2) [189]. This was the first

study revealing an optical-to-electrical cellular

modulation assisted by QDs. Following the same

strategy, CHO cells, RBL cells, NG108-15 cells and

primary hippocampal neurons were cultured on a

stacked film containing repeating layers of QDs and

adhesives, and irradiation with 380 nm laser pulses

depolarized all types of cells and induced Ca2+

influxes and action potentials in NG108-15 cells and

primary hippocampal neurons [190]. However,

LnCap cells cultured on a stacked film of CdTe QDs

were hyperpolarized upon illumination of 430 nm

laser pulses [186]. In this latter work, a simple coating

strategy was used to drop-cast a film of CdSe QDs

with van der Waals force as the anchoring force.

Cortical neurons cultured on top were randomly

hyperpolarized or depolarized upon irradiation with

550 nm laser pulses, and cytotoxicity was found on

the neurons. A CdSe QD-coated micropipette fell

short to achieve consistent stimulation on cortical

neurons, either.

It was clear that direct coating of QDs onto a

substrate could not achieve a long-term stable fNI.

Although layer-by-layer QD films achieved some

modulatory effects, their modulation efficiency and

consistency were fairly low. In order to improve

stability of the fNI, instead of physically stacking

layers of QDs, they were covalently bound to the

substrate. Core-shell structured CdSe/CdS

semiconducting nanorods were bound to highly

dense carbon nanotube films via carbodiimide

crosslinking. Embryonic chick retinas unresponsive

to light were cultured on the composite film and

stimulated by 405 nm light pulses (duration: 100 ms;

irradiance: 3-12 mW/cm2, Figure 6b and 6c) [175]. The

interface was stable for up to 21 days, with a

significant improvement. However, due to the small

photocurrents, the spatial resolution of this platform

was low, with long latency and limited

synchronization.

Up to now, these QD-assisted wireless fNIs have

only been studied in vitro, and the focus is still on

establishing a stable interface to achieve effective and

consistent modulation. The inherent tiny size of QDs

makes it extremely challenging to use dispersed QDs.

One solution is to anchor QDs onto a substrate, and,

for this strategy, chemical bonding creates a more

stable interface than physical stacking or direct

coating. Another solution is to explore

semiconducting nanorods as an alternative. Even

when the fNI is optimized with both chemical

bonding and semiconducting nanorods, its spatial

resolution still needs improvement. Additionally, the

majority of QDs are cytotoxic. Although surface

modification and encapsulation have been used to

alleviate this issue, degradation of the QDs by


22 Nano Res.

physiological acidic pH and enzymes is inevitable.

Magnetoelectric nanomaterials—from magnetic field to

electric field: Magnetoelectric nanomaterials can

convert a magnetic field to an electric field via

magnetoelectric transduction. A computational study

showed that such a transduction could theoretically

recover the deteriorated electric pulses for

Parkinson’s disease [191]. However, the model used a

simplified assessment of nanoparticles in an aqueous

solution without considering many practical factors,

such as the physiological environment, placement of

the nanoparticles, etc. A follow-up in vivo study

demonstrated that 30 nm CoFe2O4-BaTiO3

magnetoelectric core-shell nanoparticles

administrated into a mouse brain under a low-energy

magnetic field (100 Oersted; 0-20 Hz) could modulate

the electroencephalography signals (Figure 6d and 6e)

[176]. However, further studies are needed to assess

the basics underlying this finding, such as the

cellular distribution of the nanoparticles, biostability

of the interface, spatial selectivity, temporal precision,

biochemistry, and, most importantly, the

electrophysiological evidence of cellular modulation

both in vitro and in vivo.

Piezoelectric nanomaterials—from ultrasound to electric

field: Piezoelectric nanomaterials convert mechanical

stress to an electric field via mechanoelectrical

transduction. Ultrasound, a longitudinal wave with a

frequency higher than 20 Hz, can cause a

nanoparticle to vibrate along the transmission path

and exert mechanical stress on it. Ultrasound can

penetrate deeply into soft tissues, and low-intensity,

low-frequency ultrasound can travel through the

skull and be focused on a specific deep brain region

[192]. Thus, ultrasound can serve as a primary

wireless signal to activate piezoelectric

nanotransducers to create a secondary local electric

field.

Zinc oxide nanowires, one of the most studied

piezoelectric nanomaterials, however, induced

cytotoxicity on excitable cells and fell short in

maintaining a stable interface in physiological

environment [167]. Other piezoelectric nanomaterials,

including boron nitride nanotubes [193, 194] and

barium titanate nanoparticles [177, 195], have been

used to develop ultrasound-driven wireless cellular

modulation techniques.

Similar to the development of QD-based fNIs, in

the early efforts, dispersed piezoelectric boron nitride

nanotubes were studied. Dispersed piezoelectric

boron nitride nanotubes were readily internalized by

pheochromocytoma PC-12 cells, neuroblastoma

SH-SY5Y cells, and myoblast C2C12 cells. When

coupled with ultrasound, the piezoelectric boron

nitride nanotubes promoted neurite outgrowth of

PC-12 cells and SH-SY5Y cells and myogenesis of

C2C12 cells [193, 194]. Dispersed gum Arabic coated

barium titanate nanoparticles electrostatically

attached to the plasma membrane of the cell bodies

and neurites of SH-SY5Y cells and induced

high-amplitude Ca2+ influxes when coupled with

ultrasonic treatment (Figure 6f and 6g) [177].

Following a similar placement strategy, dispersed

gum Arabic coated barium titanate nanoparticles

were electrostatically attached to the plasma

membrane of rat hippocampal neurons and cortical

neurons within neuronal networks cultured on a

microelectrode array [196]. Ultrasound treatment

increased the spiking activity of the neuronal

networks in a temporal pattern that matched the

ultrasound pulses.

Besides being applied in the dispersed form,

piezoelectric nanomaterials were also immobilized

onto substrates by blending piezoelectric

nanoparticles into polymers. A micropatterned

photoresist blended with barium titanate

nanoparticles synergistically promoted the

osteogenesis of osteosarcoma Saos-2 cells under

ultrasound [197]. With the same immobilization

strategy, piezoelectric polyvinylidene fluoride

trifluoroethylene (p(VDF-TrFE)) blended with

barium titanate piezoelectric nanoparticles promoted

neurite outgrowth and induced Ca2+ transients in

SH-SY5Y cells cultured on both the p(VDF-TrFE) film

and the blended film under ultrasound [195].

However, both films decreased the cellular

proliferation comparing to a control Ibidi film.

It is worth noting that piezoelectric polymers

coupled with ultrasound were also explored for

neural modulation. A piezoelectric p(VDF-TrFE) film

coupled with ultrasound promoted the neurogenesis

of PC-12 cells [198]. Moreover, electrospun

piezoelectric p(VDF-TrFE) microfibers alone

promoted neurite extension of dorsal root ganglion

neurons [199]. However, no synergetic treatment of


23 Nano Res.

piezoelectric polymer nanofibers and ultrasound has

been reported yet.

Although theoretically piezoelectric

nanomaterials can convert mechanical stimuli to an

electric field, no direct evidence has validated the

generation of an electric field from dispersed

piezoelectric nanomaterials under ultrasound. Many

questions still remain to be answered: How does

ultrasound interact with the dispersed nanoparticles?

Can adequate electric fields be generated? How do

the generated electric fields distribute? Additionally,

the long-term interface stability and biocompatibility

of dispersed piezoelectric nanomaterials must also be

addressed.

3.2.2 Nano thermotransducers

Gold nanomaterials—from light to heat: Rod- and

sphere-shaped gold nanoparticles can convert NIR

and visible light to localized heat through surface

plasmon resonance, respectively [200]. Like QDs, the

excitation (resonant) wavelength of gold

nanomaterials affects the penetration depth and

spatial resolution, and its selection depends on the

target application. The resonant wavelength can be

tuned by controlling the aspect ratio [200]. Incident

irradiation with the corresponding resonant

wavelength excites confined electron oscillation and

collision at the nanoparticle surface, resulting in heat

generation and dissipation. The generated local heat

can change the capacitance of the plasma membrane

[201] and/or modulate temperature-sensitive ion

channels [202], therefore modulating neural activities.

Cell differentiation, such as neurite outgrowth, has

been used as an initial hallmark to show the

feasibility of this stimulation technique. More

affirmative validations have also been provided

involving in vitro and in vivo electrophysiological

tests.

Internalized gold nanorods coupled with NIR

light treatment were initially shown to promote

neural differentiation. Gold nanorods (resonant

wavelength: 780 nm) were internalized in NG108-15

neuronal cells. Neurite outgrowth was promoted

upon irradiation with a 780 nm continuous-wave

laser (duration: 1 min; irradiance: 0–13.75 W/cm2),

and intracellular Ca2+ transients were induced upon

irradiation with 780 nm laser pulses (duration: 20–

100 ms; radiant exposure: 0.07–407 J/cm2) [172].

Untargeted dispersed gold nanorods were found

to stimulate neurons with NIR illumination

proportionally to the laser duration or irradiance. In

vitro rat auditory neurons were treated with

silica-coated gold nanorods (resonant wavelength:

780 nm), and the nanorods were distributed

extracellularly, contacted the plasma membrane, or

internalized [203]. A laser pulse of 780 nm (duration:

0.025–50 ms; power: 90 mW; irradiance: unknown)

induced inward transmembrane currents and

membrane depolarization proportional to the pulse

duration. However, the neural responses were not

consistent among the tested neurons, and a train of

action potentials matching the pulse pattern was not

achieved. Gold nanorods (resonant wavelength: 977

nm) were injected into a rat sciatic nerve in vivo and

extracellularly distributed [204]. Irradiation with a

980 nm laser pulse (duration: 1 ms; irradiance: 159–

1,046 W/cm2) enhanced the amplitude of compound

nerve action potentials proportionally to the radiant

exposure. Comparing to a null control without gold

nanorods, irradiation with gold nanorods increased

the responsivity by 5 times and substantially lowered

the threshold by two thirds.

To improve the stimulation specificity and

efficiency, gold nanomaterials were targeted to the

plasma membrane and ion channels, and

illumination induced excitatory or inhibitory effects

on stimulated cells. Amine-terminated PEGylated

gold nanorods (resonant wavelength: 785 nm) were

bound to the plasma membrane of rat hippocampal,

cortical and olfactory bulb neurons, and irradiation

of 785 nm laser pulses (duration: 10 s; irradiance: 1.5

W/cm2) inhibited the spontaneous, electrically

stimulated, and chemically hyper-excited neural

network activity, while the unbound nanorods did

not substantially affect the neural network spike rate

[205]. Cationized high-density lipoprotein-coated

gold nanorods (resonant wavelength: 785 nm) were

targeted to the plasma membrane of HEK293T

human epithelial cells, and irradiation with a 780 nm

continuous-wave laser (duration: 120 s; irradiance:

800 W/cm2) induced Ca2+ influxes [174]. Non-coated

gold nanoparticles (resonant wavelength: 565 nm)

and antibody-conjugated PEGylated gold

nanoparticles (resonant wavelength: 568 nm) were

bound to the plasma membrane of non-genetically

engineered and genetically engineered rat


24 Nano Res.

hippocampal neurons, respectively, and irradiation

with 800 nm laser pulses (duration: 140 fs; irradiance:

0.27–1.02 mW/cm2) induced Ca2+ transients at both

the cellular and subcellular levels and evoked action

potentials [206]. Streptavidin-coated gold nanorods

(resonant wavelength: 977 nm) were targeted to the

biotinylated antibodies bound to the plasma

membrane of rat hippocampal neurons, and

irradiation with a 980 nm laser pulse (duration: 400

μs; irradiance: 75.25 W/cm2) improved the

stimulation efficiency, lowered the threshold, and

shortened the latency in comparison to the null

control without gold nanorods [207]. In this work,

antibody-conjugated gold nanorods were also

injected into rat motor cortex, and irradiation with a

980 nm laser pulse (duration: 1.5 ms; irradiance: 85.3

W/cm2) induced whisker oscillation. Following the

same targeting strategy, streptavidin-coated gold

nanorods (resonant wavelength: 982 nm) were also

targeted to the biotinylated antibodies bound to the

plasma membrane of rat astrocytes, and irradiation

with a 980 nm laser pulse (duration: 950 μs;

irradiance: 1381 W/cm2) induced intracellular Ca2+

transients [167]. Ligand-conjugated gold

nanoparticles (resonant wavelength: 523 nm) were

bound to the ion channels in the plasma membrane

of rat dorsal root ganglion neurons in vitro, and

irradiation with 532 nm laser pulses (duration: 1 ms;

irradiance: 31 kW/cm2) evoked a train of action

potentials (Figure 6h and 6i) [178]. In this work, the

ligand-conjugated gold nanoparticles were also

injected into acute mouse hippocampal slices ex vivo,

and irradiation with 532 nm laser pulses (duration:

10 ms; power: 140 mW) induced membrane

depolarization indicated by a VSD.

To improve the interface stability and stimulation

efficiency, gold nanomaterials were immobilized onto

substrates. A monolayer of amine-terminated

PEGylated gold nanorods were coated onto a

microelectrode array for rat hippocampal neuronal

culturing, and irradiation with 785 nm laser pulses

(duration: 120 s; irradiance: 0.3–2.1 W/cm2) inhibited

the neural activities and blocked signal transmission

between neural clusters through axons [208]. The

authors claimed that the nature of the effects

depended on the radiant exposure, i.e. a higher

radiant exposure excited the neurons, whereas a

lower radiant exposure inhibited. In another work, a

gold nanoparticle (resonant wavelength: 532 nm)

coated glass micropipette was placed in the vicinity

of a neuroblastoma SH-SY5Y cell or a rat

cardiomyocyte, and the cellular activity could be

stimulated (duration: 1–5 ms; power: 75–120 mW) or

inhibited (duration: 300 ms; power: 120 mW) upon

irradiation with 532 nm laser pulses [209]. The

authors claimed that the excitatory or inhibitory

effect depended on the pulse duration, i.e. a shorter

pulse of a few milliseconds excited the neurons,

whereas a longer pulse of tens of milliseconds to

minutes inhibited the neurons. However, based on a

complete analysis on this topic (Table 1), neither

assumption could fully account for all the

observations. To discern the excitatory and inhibitory

effects, consideration may not be solely on the

primary signal—the light, but should also be given to

many other factors, particularly the heat generated

locally. Heat is the secondary signal with which the

neurons directly interact. Both the amount and rate

of heat generation affect the neural responses, which

are determined by the light (duration and irradiance),

nanoparticle amount and placement, etc.

Moreover, gold nanomaterials also have a great

tendency to be rapidly internalized, making it

difficult to maintain a stable and effective fNI. The

uptake of gold nanomaterials could also cause

inconsistency and cytotoxicity [172, 203].

Furthermore, although NIR light can penetrate

deeper than visible light, their penetration depth is

still limited within 4 mm through dermal tissues

[169]. Additionally, heat, as a localized secondary

signal, can be limited by its temporal responsivity

[172, 178, 203]. The heat generation must be carefully

controlled, as overheating can lead to protein

denature and cell damage [210].

Nevertheless, gold nanomaterials have good

biocompatibility, and their surface plasmonic

resonant properties can be tailored based on the

application needs. Gold nanorods also have a higher

heat generation efficiency, thus requiring a

nanoparticle concentration almost 1000 times less

than the magnetic nanoparticle-assisted

thermotransduction to be discussed below [174].

More importantly, they don’t require genetic

engineering to the target cells. Thus, gold

nanomaterials have become one of the most

developed types of wireless nanotransducers.


Table 1 Summary of gold nanomaterial-assisted thermotransduction

Reference Laser duration

(ms)

Laser irradiance

(W/cm2)

Irradiant exposure

(mJ/cm2) Modulation effect

[203] 0.025-50 N/A N/A Excitatory

[211] 1 159-1,046 159-1,046 Excitatory

[85] 6×105 1.5 9×105 Inhibitory

[212] 7.2×106 800 5.76×109 Excitatory

[206] 1.4×10-10 2.7×10-4-1.02×10-3 3.78×10-14-1.428×10-13 Excitatory

[207] 0.4 75.25 30.1 Excitatory

1.5 85.3 127.95 Excitatory

[167] 0.95 1381 1311.95 Excitatory

[178] 1 31,000 31,000 Excitatory

[208] 7.2×106 0.3-2.1 2.16×106-1.512×107 Inhibitory

[209] 1-5 75-120 75-600 Excitatory

300 N/A N/A Inhibitory N/A No available information.

Superparamagnetic nanomaterials—from magnetic field to

heat: Superparamagnetic nanoparticles generate

localized heat when exposed to an oscillating or

alternating magnetic field. Similar to the gold

nanomaterial-assisted thermotransduction, this

localized heating phenomenon via hysteresis

triggered by a magnetic field makes these

nanoparticles good candidates as wireless

nanotransducers for cellular modulation. This type of

technique started with targeted placement of these

nanoparticles.

Streptavidin-conjugated superparamagnetic

nanoparticles were targeted to genetically engineered

protein markers in the plasma membrane of

HEK293T human epithelial cells and rat

hippocampal neurons expressing temperature-gated

transient receptor potential vanilloid 1 (TRPV1) ion

channels. Application of a radio-frequency (RF)

magnetic field generated highly localized heat,

inducing Ca2+ influxes in HEK293T cells and evoking

action potentials in hippocampal neurons within 45 s

[11]. In this work, the PEG-phospholipid-coated

nanoparticles were also injected into amphid of C.

elegans having TRPV1 ion channel-expressing

sensory neurons, and application of a magnetic field

initiated the worm’s thermal avoidance response

within 5 s. Besides being anchored onto the plasma

membrane, antibody-conjugated magnetic

nanoparticles were also directly targeted onto the

TRPV1 ion channels in the plasma membrane of

HEK293T cells and mouse embryonic stem cells

expressing Ca2+-dependent promoter for insulin

secretion, and application of an RF magnetic field

resulted in cytosolic Ca2+ increase, enhancing

proinsulin release and relevant gene expressions

[213]. In this work, antibody-conjugated magnetic

nanoparticles were also injected into xenografts of

PC-12 pheochromocytoma cells expressing both

TRPV1 ion channels and Ca2+-dependent promoter

for insulin secretion in mouse, and application of a

magnetic field resulted in a decrease of blood glucose,

an increase of plasma insulin, and an increase of

relevant gene expressions. Additionally, genetically

engineered cells expressing ferritin fusion protein,

TRPV1 ion channels, and Ca2+-dependent promoter

for insulin secretion produced magnetic ferritin

nanoparticles intracellularly, the application of a

magnetic field also resulted in increases of proinsulin

release and relevant gene expressions. In this work,

the Ca2+ influxes were induced faster than in Ref. [11],


26 Nano Res.

and this work was the first one to use endogenous

nanoparticles for cellular modulation.

Stanley et al. extended the use of endogenous

ferritin nanoparticles for wireless cellular modulation

in another study [214]. In genetically engineered

HEK293T human epithelial cells and mouse

mesenchymal stem cells expressing ferritin proteins

(cytoplasmic, membrane-bound, or TRPV1-bound),

TRPV1 ion channels, and Ca2+-dependent promoter

for insulin secretion, the intracellularly produced

ferritin nanoparticles coupled with an RF magnetic

field resulted in increases of proinsulin release and

relevant gene expressions. In this work, in vivo

studies were conducted by either implanting gelatin

scaffolds containing the genetically engineered

mouse mesenchymal stem cells in mouse or injecting

adenovirus to transfect cells, and the application of

an RF magnetic field resulted in a decrease of blood

glucose, an increase of plasma insulin, and an

increase of relevant gene expressions. The

effectiveness was shown to last for at least several

weeks. Application of a static magnetic field led to

similar results in vitro and in vivo only for

TRPV1-bound ferritin proteins, indicating that both

heating and mechanical force could activate TRPV1

ion channels.

Untargeted placement of superparamagnetic

nanoparticles was also implemented for cellular

modulation to suppress internalization and prolong

the interface. PEGylated poly(acrylic acid)-coated

superparamagnetic nanoparticles were distributed in

the adjacent surroundings of HEK-293FT cells and

hippocampal neurons, and application of an

alternating magnetic field induced Ca2+ influxes in

HEK293-FT cells and evoked trains of action

potentials in hippocampal neurons within 5 s (Figure

6j and 6k) [168]. It was worth mentioning that the

cells were genetically engineered to express extra

levels of TRPV1 ion channels than their natural

existence. In this work, superparamagnetic

nanoparticles were also injected to the transfected

ventral tegmental area of mouse brain, and

application of a magnetic field increased the c-fos

gene expression. These nanotransducers lasted more

than a month in vivo.

For magnetic nanoparticle-assisted

thermotransduction, heat was confirmed as the

localized secondary signal. However, mechanical

force as another possible secondary signal cannot be

excluded [214]. Similar to gold nanomaterial-based

thermotransducers, the temporal resolution of this

type of techniques also needs to be significantly

improved. Interestingly, the thermotransduction

enabled by magnetic nanoparticles generally requires

genetic engineering to overexpress TRPV1 ion

channels and other binding proteins, while gold

nanomaterial-assisted thermotransduction usually

doesn’t involve genetic engineering. Although some

of the differences can be attributed to the difference

in experimental designs, the exemption of genetic

engineering may have taken advantage of the higher

heating efficiency of gold nanomaterials. To generate

the same amount of heat, a much larger number of

magnetic nanoparticles is needed than gold

nanomaterials [174]. Nevertheless,

superparamagnetic nanoparticles have good

biocompatibility and biodegradability. And the

primary signal, an RF magnetic field, can penetrate

more deeply than light into tissues without causing

tissue heating. Additionally, magnetic nanoparticles

can also convert a magnetic field to mechanical forces,

a secondary signal that can also interact with cells,

which will be discussed in the mechanotransducers

below.

3.3.3 Nano optotransducers

Upconverting luminescent nanomaterials—from NIR

light to visible light: Optogenetics (to be discussed in

details below), artificially inserting light-sensitive ion

channels into the plasma membrane and modulating

neural activity with light, has become a powerful tool

for neural stimulation with its exceptional

spatiotemporal resolution and specificity [215].

Majority of the light-sensitive ion channels, such as

the channelrhodopsins (ChRs), respond to blue to

green light with some newly developed ChRs

responding to orange to red light, such as the

ReaChR [216], Chrimson [217] and Jaws [218]

through laborious engineering [179]. However,

visible light only penetrates soft tissues superficially.

Thus, optogenetics often demands the implantation

of a light source close to the target neuron population.

On the other hand, NIR light (650-1450 nm) can

penetrate deeper into the soft tissues when the

wavelength lies within the biological window [219].

Additionally, upconverting luminescent


27Nano Res.

nanomaterials can be excited by NIR light and emit

ultraviolet/visible light through an upconversion

process. These inspire the development of a new

wireless neural modulation technique by combining

upconverting luminescent nanomaterials with

optogenetics. The upconverting luminescent

nanomaterial-assisted optogenetics, in comparison to

the original optogenetics, uses an inexpensive light

source and could possibly avoid surgical

implantation of the light source. The emission

wavelength of such optotransducers can be relatively

easily tailored instead of laboriously screening and

engineering of the ion channels [179].

Dispersed untargeted and targeted placement of

the upconverting luminescent nanomaterials could

be coupled with optogenetics to modulate cells.

Synergistic treatment by NaYF4:Sc/Yb/Er

nanoparticles (excitation: 980 nm; maxima emission:

543 nm) and a 976 nm NIR laser pulse induced

photocurrents in the C1V1 (maxima absorbance: 539

nm) expressing mouse neuroblastoma and rat

neuron hybrid ND7/23 cells [220]. However, the

cellular distribution of the nanoparticles was not

assessed in this study, and a single light pulse

induced a series of action potentials due to the slow

off-kinetics of C1V1 channels. 980 nm

quasi-continuous-wave NIR light was used to excite

extracellularly and intracellularly distributed

silica-coated NaYF4:Yb/Tm nanoparticles (excitation:

980 nm; maxima emission: 450 nm), and the emission

induced Ca2+ influxes in ChR2-expressing HEK293T

cells and elicited reversal responses in C. elegans

having ChR2-expressing mechanosensory neurons

[221]. Core-shell structured NaYF4:Yb/Tm@NaYF4


470 nm) were made to improve the upconversion

efficiency, and the nanoparticles were conjugated

with streptavidin and bound to the Ca2+ channels

engineered with streptavidin binding site [222].

Illumination by 980 nm continuous-wave NIR light

induced Ca2+ influxes in HeLa cells, activated

Ca2+/NFAT pathway in T lymphocytes, and promoted

melanoma tumor destruction by promoting dendritic

cell maturation and T lymphocytes’ sensitivity to

antigen.

Immobilizing core-shell structured upconverting

luminescent nanomaterials onto substrates improved

the modulation efficiency and resolution. The ChR2

(maxima absorbance: 470-475 nm) expressing mouse

hippocampal neurons were cultured on a

poly(lactic-co-glycolic acid) scaffold containing

NaYF4:Yb/Tm@NaYF4 core-shell structured


475 nm), and irradiation with a sequence of 980 nm

NIR laser pulses induced a train of action potentials

(Figure 6l and 6m) [179]. More importantly, in this

work, a single pulse could rapidly evoke a single

action potential. Similarly, ChR-expressing rat

hippocampal neurons were cultured on a cover glass

over a poly(methyl methacrylate) film containing

IR-806-sensitized NaYF4:Yb/Er@NaYF4/Yb core-shell

structured nanoparticles (excitation: 800 nm; maxima

emission: ~540 nm), and irradiation with a sequence

of 800 nm continuous-wave NIR light pulses evoked

light intensity-dependent depolarization and a train

of action potentials, the temporal pattern of which

matched that of the light pulses [223]. The improved

efficiency and resolution could be due to the

enhanced upconversion efficiency of core-shell

structured nanoparticles and increased interface

stability.

It is worth noting that although the above

excitation wavelength (975-980 nm) is within the NIR

range, its absorption by water is still significant [224].

It is also worth mentioning that NIR light can only

penetrate through dermal tissues up to 4 mm [169]

and has difficulty to penetrate through bones and

skull. Additionally, for these upconverting

luminescent nanomaterial-assisted optogenetic

techniques, both the optotransducers and ion

channels need to be well designed. On the one hand,

a high upconversion efficiency is greatly demanded

to use a low-power NIR source to reach the light

threshold for ion channel activation while avoiding

thermal hazards to the cells [221]. The emission of

ultraviolet and its toxicity also need to be assessed

[221]. In addition, in vivo biocompatibility of the

upconverting luminescent nanomaterials needs to be

further improved and optimized for clinical

stimulation [221]. On the other hand, the ion

channels should have rapid dynamics and stable

expression.

3.2.4 Nano mechanotransducers

Superparamagnetic nanomaterials—from magnetic field to

mechanical force: Comparing to other recently


28 Nano Res.

developed nanotransducer-assisted cellular

modulation techniques, mechanical manipulation of

cellular responses via magnetic nanoparticles has

been studied much earlier. Magnetic nanoparticles

were bound to the cell surface, and application of a

magnetic field generated either pico-newton forces to

stretch the corresponding ion channels and

cytoskeleton via particle twisting or pulling [225, 226]

or femto-newton forces to induce receptor clustering

via particle aggregation. Internalized magnetic

nanoparticles were also used to manipulate protein

distributions inside the cells [227, 228]. Interestingly,

while the majority of magnetic nanoparticle-assisted

mechanical stimulations were conducted on

non-excitable cells, the concepts can be transferred to

neural modulation straightforwardly.

Magnetic nanoparticles were bound to the cell

surface, and through twisting or pulling on these

nanoparticles, a magnetic field can stretch the ion

channels and cytoskeleton. For example, endothelial

cells were bound to ferromagnetic microparticles via

a molecular linker, and shear stress was applied to

the integrin receptors via the molecular linker by

magnetic twisting, leading to cytoskeleton stiffening

[229-231]. Collagen-coated magnetic microbeads

were bound to human gingival fibroblasts, and the

application of magnetic force on the plasma

membrane promoted Ca2+ influxes via

mechanosensitive channels [232]. Antibody- or

complex-conjugated magnetic nanoparticles were

targeted to a genetically added loop region of the

mechanosensitive TREK-1 ion channels in the plasma

membrane of COS-7 kidney cells, and the application

of a magnetic field induced an increase of the

outward current [233]. Similarly, magnetic

microparticles were bound to the integrin receptors

and chimeric integrin receptors of bovine capillary

endothelial cells, and the magnetic pulling on these

integrin receptors activated the mechanosensitive

transient receptor potential vanilloid 4 (TRPV4) ion

channels and induced almost instantaneous Ca2+

fluxes [234].

Magnetic nanoparticles bound to the cell surface

receptors were magnetized and aggregated upon

exposure to a magnetic field. The receptor clustering

due to particle aggregation activated receptor

oligomerization-dependent cell signaling pathways.

Ligand-conjugated superparamagnetic nanoparticles

were targeted to the transmembrane FcεRI receptors

of RBL-2H3 rat mast cells, and application of a

magnetic field activated the Ca2+ signaling pathway,

increasing cytosolic Ca2+ concentration [235].

Similarly, antibody-conjugated magnetic

nanoparticles were targeted to death receptors at the

surface of DLD-1 human colon cancer cells and

injected into zebrafish embryo, and magnetic

field-induced receptor clustering activated the

apoptosis signaling pathway [236].

Antibody-conjugated or streptavidin-functionalized

superparamagnetic nanoparticles were targeted to

the epidermal growth factor receptors (EGFRs) of

A431 human epidermoid carcinoma cells and

genetically-engineered chimeric EGFRs of HeLa cells,

respectively, and magnetic field-induced receptor

clustering activated the EGFR signaling pathway

[237].

Internalized magnetic nanoparticles could be

controlled by an external magnetic field to

manipulate the intracellular protein and organelle

distribution. The superparamagnetic nanoparticles

internalized into cortical neurons coupled with a

magnetic field exerted magnetic forces to modulate

protein tau distribution and cell polarization [227].

The superparamagnetic nanoparticles were

microinjected into HeLa cells, and a magnetic field

was applied to control the distribution of HaloTag

proteins [228]. Similarly, the anti-TrKB agonist

antibody-functionalized superparamagnetic

nanoparticles were rapidly internalized into the TrKB

signaling endosomes of primary neurons and

promoted neurite outgrowth [238]. A focal magnetic

force halted the neurite outgrowth via modulation of

the location of TrKB signaling endosomes.

Magnetic nanoparticles were recently studied to

modulate neurons. Starch-coated ferromagnetic

nanoparticles were mainly bound to the plasma

membrane of cortical neurons, and chitosan-coated

ferromagnetic nanoparticles were mostly internalized

(Figure 6n and 6o) [180]. Application of a high

gradient magnetic field for both placements of

nanoparticles induced Ca2+ fluxes in the neural

network via activation of the N-type

mechanosensitive ion channels. This mechanism was

further validated in a follow-up study [210]. In this

work, starch-coated magnetic nanoparticles were

bound to the plasma membrane of the neurons of


29Nano Res.

which the N-type mechanosensitive ion channels

were over-expressed, and chronic treatment with a

high gradient magnetic field lowered the expression

of the N-type mechanosensitive ion channels by

chronically activating these channels. Further

electrophysiological validations are needed for these

wireless mechanotransducers to be used for neural

modulation, and their responsivity and temporal

resolution need to be improved.

Considering the widespread existence of

mechanosensitive ion channels and cell signaling

pathways [226], these mechanical cellular

modulations on non-excitable cells can be adapted

and tailored for neural modulation. Magnetic

microparticles are limited for in vivo cellular

modulation due to their relatively large size [11].

Magnetic nanoparticles are usually bio-friendly and

can be rapidly cleared in the human body, thus these

nanoparticles are used clinically in magnetic

resonance imaging. Magnetic nanoparticles bound to

the receptors could also be rapidly internalized [236,

237]. Their biodegradability and tendency for

internalization make it difficult to maintain a stable

fNI lasting for a long time [239]. Similar to the

wireless thermotransducers based on magnetic

nanoparticles, it is necessary to discern if the

secondary signal is heat or mechanical force, so that

the design can be optimized.

Figure 7 Optogenetic molecular applications. (a) Main opsin families that conduct ions upon light stimulation: BR (H+), HR (Cl-), and ChR (Na+, K+, Ca2+, H+) activated via green, yellow, and blue lights, respectively. Adapted with permission from Ref. [240]. (b) Schematic representation of ReaChR consisting of N-terminal domain from ChEF, transmembrane domains from VChR1 except that domain F is from VChR2 and an L171I mutation in domain C. Adapted with permission from Ref. [216]. (c) and (d) Protein control via light stimulation. Adapted with permission from Ref. [241]. (c) Transmembrane protein control over intracellular signaling cascade upon light stimulation. (d) Caged ligands released upon light stimulation causing subsequent protein conformational change and leading to activation. (e) Spectra of emission and activation wavelengths of luciferase and eNpHR3.0 with peaks at ~550 nm and ~600 nm, respectively. Adapted with permission from Ref. [242]. (f) and (g) Photoactivatable CRISPR-Cas9 system, adapted with permission from Ref. [243, 244]. (f) Cleaved Cas9 protein whose photoinducible domains (pMag/nMag) dimerize upon blue-light stimulation, allowing for Cas9 fragments to reassociate and cut DNA at a specific region. (g) dead-Cas9 tagged with CIB1, targeted to a promoter region, serves as a transcription modulator upon blue-light stimulation causing CRY2 tagged with a gene activator to bind to CIB1 and promote transcription.


3.3 Bionanotransducer-enabled functional neural

stimulation

3.3.1 Optogenetics

Nanobiotechnology utilizing light-sensitive

proteins can function as a switch to control neural

activities like intracellular signal transduction

pathways, action potential propagation, and even

gene transcription or protein-protein interactions.

Optogenetics is the combination of genetic and

optical methods to allow for targeted, fast control

of precisely defined events in biological systems.

Once stimulated by extrinsic signals or stimuli,

spatiotemporal changes within neurons will lead to

profound effects on behavior. Optogenetics offers

many advantages, such as cell-type specific

targeting, high spatiotemporal resolution

(subcellular and millisecond), and concurrent

recording with metal electrodes without the

introduction of aberrant artifacts. For a

comprehensive overview, the readers are referred

to many excellent reviews, including Refs.

[245-250].

In 2005, Boyden et al. reported that

mammalian neurons could be precisely modulated

by light with the introduction of a single microbial

ChR gene [215]. Opsins are seven-transmembrane

domain proteins (structurally akin to G-protein

coupled receptors) possessing the chromophore

retinal, which undergoes a conformational change

in response to photon absorption and drives ion

transport across the cell’s membrane. Commonly,

bacteriorhodopsin (BR), ChR and halorhodopsin

(HR) are the most widely used opsin families that

can modulate neural activity in response to

different wavelengths of light (Figure 7a). Two

different effects exhibited by these proteins are

excitation and inhibition of neural activity. BRs are

green-light activated ion pumps that transport

hydrogen ions out the cytoplasm causing

hyperpolarization and preventing an action

potential. ChRs are blue-light activated ion

channels that conduct various cations (Na+, H+, K+,

and Ca2+) across the cellular membrane and

depolarizes neurons, eliciting an action potential.

HRs are yellow-light activated ion pumps that

transport Cl- ions intracellularly and inhibit neuron

firing [251].

Introduction of opsin genes is accomplished via

transgenic (Cre-LoxP) or viral delivery (AAV,

Lentivirus) methods. Cre transgenic mice can be

crossed with another mouse expressing the opsin

of interest in a Cre-dependent manner, an example

of which was accomplished with Ai39 mice with

Cre-dependent Halo3.0/eNpHR3.0 expression [252].

Viral gene delivery using adeno-associated virus

(AAV) is another method where a plasmid

containing an opsin gene under the control of a

promoter (CMV) would be injected into a brain

region or transfected into cells in vitro and

visualized with a fluorescent reporter gene [253].

Owing to the specificity of optogenetics, selection

of similar promoter sequences to target a

cell-subtype will allow cell specific integration

since cells that are expressing the same promoters

will have the required transcription factors to

initiate opsin gene synthesis. Transgenic mice offer

a robust and precise optogenetic activation or

suppression in vivo. While viral delivery methods

have a few limitations, including: limited DNA

packaging space, and transfection efficiency, it still

remains a viable option to genetically modify

specific cells.

A distinct limitation of optical stimulation is its

tissue penetration, where blue light has the

shallowest penetration depth (1-2 mm) and

near-infrared light has the deepest (4 mm). Aside

from inserting an optic fiber deep into the brain or

using upconverting luminescent optotransducers

as discussed above, several opsins have been

discovered and engineered to have shifted light

sensitivities and faster ion transport to compensate

for this deficiency. An inhibitory HR from

Natronomonas pharaonis (Halo3.0/eNpHR3.0) was

developed, which possessed a membrane

localization tag that could hyperpolarize neurons

upon yellow-light stimulation with increased

excitability and faster photokinetics [254-257].

VChR1, a ChR from Volvox carteri, can be activated

at 589 nm, this is slightly red-shifted when

compared to ChR2, however, it expressed poorly in

mammalian cells and had minimal trafficking to

the cellular membrane [258]. VChR1 was further

modified with components of other ChR proteins

and an L171I mutation allowing for its optimal


31Nano Res.

excitation to be red-shifted further (630 nm);

termed red-activatable channelrhodospin (ReaChR),

this opsin had vastly improved membrane

trafficking and kinetic properties (Figure 7b) [216].

Engineered for prolonged periods of neural

depolarization, bistable step-function opsins (SFOs)

allowed for orders of magnitude greater light

sensitivity and had lasting effects without the need

for continuous light stimulation [259]. Persistent

work on opsins for H+/Cl- conducting-based

inhibition is ongoing, for they could mediate the

optical silencing of significant neural activities over

relevant timescales [254, 260-263]. Opsins with

faster kinetics that could deliver more efficient

photocurrents while also being expressed at higher

levels within the cell are of great paramount [264,

265].

Aside from using light to stimulate an opsin

within a cell to drive a response, another way is to

use chemically modified or genetically encoded

caged ligands to control neural activities (Figure

7c-7d) [266, 267]. Light-sensitive proteins

engineered with the attachment of

photo-switchable tethered ligands, could

ultimately regulate the interaction between ligand

and receptor and allow for precise control over

intracellular signaling events. The correct

wavelength of light would effectively activate the

ligand, transitioning from a caged to uncaged state,

allowing for a protein-protein interaction to occur.

However, several considerations have limited the

application of caged proteins, one being that

cleaving the cage tends to be irreversible and may

produce toxic byproducts that can alter cell

signaling. Reversible caged ligands using a short

connecting molecule called azobenzene, controls

the activity of ligands with the ability to go

through many photoactivation cycles without a

reduction in activity [241, 266]. An alternative

approach, typically used concurrently with other

optogenetic methods, uses constitutively expressed

luciferin (light producing compound) within a

specific cell type (Figure 7e). Endogenous light

production from those cells would then stimulate

nearby cells expressing an opsin and further

control cell signaling and intracellular events [242].

Recent advances in gene editing and targeting

methods have supplemented the field of

optogenetics with the advent of photoactivatable

CRISPR-Cas9. One method split Cas9 into two

domains, each tagged with a photoinducible

domain, that when exposed to light, dimerized and

brought the Cas9 domains together allowing for it

to target and edit the genome based upon the

guide RNA (gRNA) (Figure 7f) [243]. The same

group also demonstrated earlier the ability to use

dead-Cas9 (dCas9) as a photoactivatable

transcription system. dCas9 is a useful tool for gene

regulation since it can still target DNA with gRNA,

but lacks nuclease activity, and can be coupled to

gene activators and repressors. Tagged with CIB1,

dCas9 induced gene transcription once CRY2,

tagged with an activator, heterodimerized with

CIB1 upon blue light stimulation (Figure 7g) [244].

Utilizing one or adopting multiple methods

concerning optogenetics can allow for a high

degree of specificity and spatiotemporal control

over neural stimulation.

3.3.2 Magneto(thermo)genetics

Due to its noninvasiveness and deep tissue

penetration, magnetic neural stimulation is of great

interest. To stimulate neurons with cell-type

specificity, magnetic nanoparticles combined with

genetic engineering of certain ion channels have

been developed for nanotransducer-assisted

magnetic stimulation [268, 269], as discussed earlier.

The commonly used channels include the

mechanosensitive channels (TREK) [180, 270] and

the heat-sensitive capsaicin receptor channels (TRP)

[168, 271]. TREK-1 is a type of tandem-pore K+

channel (2PK+) and produces an outwardly

rectifying K+ leak current to regulate resting

membrane potential and cellular excitability [272].

Hughes et al. inserted a 6-histidine-repeat into the

TREK-1 channel and attached an anti-His antibody

grafted magnetic nanoparticle to it to directly

activate the mechanosensitive channel by exerting

a mechanical force through a permanent magnetic

field (Figure 8a) [233]. Wheeler et al. developed the

Magneto, a new fusion of the nonselective cation

channel TRPV4 and the paramagnetic protein

ferritin (an iron-contained storage protein), and

applied it to mediate Ca2+ influx upon magnetic

stimulation to modulate the behavior of freely

moving zebrafish and mice [273]. TRP channels


32 Nano Res.

form the most important temperature-sensitive ion

channel family, among which TRPM8 and TRPA1

are sensitive to cold temperatures, and TRPV1,

TRPV3 and TRPV4 respond to an elevation in local

temperature [274]. For example, TPRV1 opens

when the local temperature increases from normal

to 42 and causes an influx of Ca2+ to depolarize

the cell. These ion channels can be heated by an RF

magnetic field through nano thermotransducers

(e.g., superparamagnetic nanoparticles) or bionano

thermotransducers (e.g., ferritin) either attaching to

a ligand inserted in the membrane (Figure 8b) or

directly attaching to the ion channel through an

engineered ligand recognition (Figure 8c) [213, 214,

271]. The latter approach of specific ion-channel

binding ensured a higher efficiency in signal

transduction while minimizing heat-induced

side-effects. In this work, Stanley et al. used the

genetically encoded ferritin as the

thermotransducers to control insulin expression

and blood glucose in mice [214]. The ferritin was

targeted to TPRV1 for gating under low RF waves,

which resulted in elevated intracellular Ca2+

concentrations and induced the expression of

proinsulin. They also expanded this ferritin-TPRV1

magnetothermogenetics system to target

hypothalamic glucose sensing neurons to control

proinsulin release in mice [275].

Additionally, Qin et al. reported a single

magnetic protein MagR for neural stimulation [276].

Long et al. invented a non-invasive

magnetogenetics that combined the genetic

targeting of a magnetoreceptor with remote

magnetic stimulation through the use of a

genetically encoded magnetic protein [277],

without the requirement for injection of exogenous

superparamagnetic nanoparticles. Although these

emerging techniques have aroused a great deal of

enthusiasms in the field, there are still many

technical obstacles, and further efforts are required

to decipher the specific stimulation mechanism and

develop new magnetic sensitive receptors.

Figure 8 Mechanisms of magneto(thermo)genetics and sonogenetics. (a) Magnetomechanical stimulation with mechanotransducers to modulate the mechanosensitive channel (TREK1). his-tagged magnetic nanoparticles are targeted on TREK1 with a 6-histidine repeat inserted region [233]. (b) Magnetothermal stimulation with different nanoparticle placements. Top, streptavidin-conjugated nanoparticles bound on the plasma membrane around TRPV1 channels through a genetically engineered linker [11]. Bottom, through his tag binding, superparamagnetic nanoparticles (grey circle) or ferritin proteins (purple circle) are attached to the thermal sensitive channel (TPR family) [213] [214]. (c) Potential mechanism for sonogenetics, involving the mechanosensitive TRP-4 channel [278].

3.3.3 Sonogenetics

Ultrasound can also be used to noninvasively

stimulate the nervous system. To enhance the

power efficiency and target specificity, genetically

encoded acoustic sensitive ion channels can be

used as the bionanotransducers. An early

investigation by Ibsen et al. used the misexpressed

ultrasonic sensitive channel TRP-4, a pore-forming

subunit of a mechanotransduction channel, and

ultrasound-amplified microbubbles to manipulate


33Nano Res.

the functions of interneurons and sensory neurons

in C. elegans for behavior control (Figure 8c) [278].

They termed their technology the “sonogenetics”.

Kubanek et al. measured the effects of ultrasound

on mechanosensitive ion channels embedded

within cellular membrane in the Xenopus oocyte

system, including potassium mechanosensitive

channels (TREK-1, TREK-2, TRAAK) and a sodium

sensitive channel (Nav1.5) [279]. Ultrasound could

modulate the currents flowing through the ion

channels by up to 23%. Comparing to other

bionanotransducer-enabled neural stimulation

techniques, sonogenetics has a much longer way to

go. Much more work is still needed to elucidate the

stimulation mechanism, search for more effective

acoustic sensitive ion channels that can be

transfected into other cells, and expend the

application to mammalian neuron stimulation.

4. Future perspectives

The three thematic nano fNIs covered in this

review, i.e., nanoelectrode-based,

nanotransducer-assisted, and

bionanotransducer-enabled, represent the most

exciting new advances in the field of neural

interface engineering over the past 15 years on

addressing the long-term physical integration issue

of the neural interface. These fascinating advances

embody the insensibility and indistinguishability

principles that we proposed earlier [2] through the

pursuits of miniaturization and biomimicry, and

employment of nature’s materials and designs.

Tackling the inefficiency problem of limited

communication bandwidth through the

abiotic-biotic interface has so far solely relied on

increasing the electrode’s spatial resolution, density,

and number. However, it has been largely ignored

that, in the current design of neuroelectrodes, the

neuron’s “vocabulary” (including action potentials,

excitatory and inhibitory synaptic potentials [280])

in forming the brain’s language is “filtered” into an

overly simplistic binary mode (“1” for action

potential and “0” for no action potential) by each

electrode, with a great loss of the information

contents that can otherwise be conveyed through

the fNI. While some electrode types exist to record

the subthreshold neuronal activities [280], they are,

at present, limited to cell culture interfacing only. A

need to develop the implantable versions of such

“analog” neural interfaces is urgent.

Furthermore, the plastic nature of

neuron-neuron communication has never been

purposely emulated at any fNI. We argue that the

goal of neuroelectrode design in the functional

aspect should not be set to achieve a static

signal-transmission interface, rather, to achieve a

dynamic interface that remodels based on a

memory of the signals transmitted through. These

gaps in interface efficiency and plasticity thus call

for an urgent and serious rethink of the design of

fNIs to capture the full vocabulary of a neuron and

implement plasticity into the interface. With such

new fNIs, it would be more effective and efficient

to wire a neuromorphic chip running biologically

realistic neuronal models to the brain to repair and

even augment the brain [281], as exemplified in the

recent attempts in building cognitive prostheses

[282, 283].

Acknowledgements

Dr. Guo is supported by The Defense Advanced

Research Projects Agency (Grant # D17AP00031) of

the USA. The views, opinions, and/or findings

contained in this article are those of the author and

should not be interpreted as representing the

official views or policies, either expressed or

implied, of the Defense Advanced Research

Projects Agency or the Department of Defense.

Dr. Xie is supported by National Institute of

Neurological Disorders and Stroke through Grant #

R01NS102917, Welch Foundation through Grant #

F-1941-20170325, and Department of Defense

through Clinical and Rehabilitative Medicine

Research Program under award no.

W81XWH-16-1-0580.

Electronic Supplementary Material:

Supplementary material (a summary table on

nanotransducer-assisted wireless neural

modulation) is available in the online version of

this article at

http://dx.doi.org/10.1007/s12274-***-****-*.


34 Nano Res.

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Electronic Supplementary Material


Yongchen Wang1†

, Hanlin Zhu2†

, Huiran Yang3,4†

, Aaron D. Argall5, Lan Luan

2, Chong Xie

2 (), and Liang

Guo3,6

()

1 Department of Biomedical Engineering, The Ohio State University, Columbus 43210, USA

2 Department of Biomedical Engineering, The University of Texas at Austin, Austin 78712, USA

3 Department of Electrical and Computer Engineering, The Ohio State University, Columbus 43210, USA

4 Key Laboratory of Flexible Electronics and Institute of Advanced Materials, Jiangsu National Synergetic Innovation

Center for Advanced Materials, Nanjing Tech University, Nanjing 211816, China 5 Biomedical Sciences Graduate Program, The Ohio State University, Columbus 43210, USA

6 Department of Neuroscience, The Ohio State University, Columbus 43210, USA


Supporting information to DOI 10.1007/s12274-****-****-* (automatically inserted by the publisher)

Address correspondence to Prof. Liang Guo, [email protected]; and Prof. Chong Xie, [email protected]

Nano Res.

Table S1 Nanotransducer-assisted neural modulation

Nanotransducers

Wireless

primary

signal

Localized

secondary

signal

Nanomaterials Review Reference Cell/animal model Placement Genetic

engineering

Modulation

effect Outcome

Nano

Electrotransducers

Light

Electric

field

Quantum dots;

semiconducting

nanorods

[1]

[2] SK-N-SH cells (in vitro) 3 - N/A No stable interfaces

[3] Rat cortical cells (in vitro) 2 - N/A No stable interfaces

[4] SK-N-SH cells (in vitro);

rat cortical cells (in vitro) 3 - N/A No stable interfaces

[5] NG108-15 cells (in vitro) 2 - Excite Action potentials

[6] NG108-15 cells (in vitro);

hippocampal neurons (in vitro) 2 - Excite Action potentials

[7]

LnCap cells (in vitro);

mouse cortical neurons (in

vitro)

2 - Excite;

Inhibit Action potentials

[8] Chick retina (ex vivo) 2 - Excite Extracellular voltage

Magnetic

field

Magnetoelectric

nanomaterials N/A

[9] N/A N/A N/A N/A N/A

[10] Mouse brain (in vivo) N/A - N/A Electroencephalogram

waveforms

Ultrasound Piezoelectric

nanomaterials [11]

[12] PC12 cells (in vitro);

SH-SY5Y cells (in vitro) 4 - Excite Neurite outgrowth

[13] C2C12 cells (in vitro) 4 - Excite Myogenesis

[14] SH-SY5Y cells (in vitro) 3 - Excite Ca2+ influxes

[15]

Neuronal networks of rat

hippocampal neurons and

cortical neurons (in vitro)

3 - Excite Spiking activity

[16] Saos-2 cells (in vitro) 2 - Excite Osteogenesis

[17] PC12 cells (in vitro) 2 - Excite Neurogenesis

[18] SH-SY5Y cells (in vitro) 2 - Excite Neurite outgrowth;

Ca2+ transients

Nano Visible/NIR Heat Gold [19, [21-23] NG108-15 cells (in vitro) 4 - Excite Neurite outgrowth;

Nano Res.

Thermotransducers light nanomaterials 20] intracellular calcium

transients

[24] Rat auditory neurons (in vitro) 1, 3, 4 - Excite Action potentials

[25] Rat sciatic nerves (in vivo) 1 - Excite Compound nerve

action potentials

[26] Rat hippocampal, cortical and

olfactory bulb neurons (in vitro) 3 - Inhibit Action potentials

[27]

Rat dorsal root ganglion

neurons (in vitro); Acute mouse

hippocampal slices (ex vivo)

3” - Excite

Action potentials;

membrane

depolarization

[28] HEK293T cells (in vitro) 3 - Excite Ca2+ influxes

[29] Rat hippocampal neurons (in

vitro) 3 + Excite

Ca2+ transients; action

potentials

[30] Rat hippocampal neurons (in

vitro) 2 - Inhibit Action potentials

[31]

Rat hippocampal neurons (in

vitro);

Rat motor cortex (in vivo)

3 - Excite Action potentials;

rat whisker oscillation

[32] Rat astrocytes (in vitro) 3 - Excite Intracellular Ca2+

transients

[33] SH-SY5Y cells (in vitro);

Rat cardiomyocytes (in vitro) 2 -

Excite;

Inhibit Action potentials

Magnetic

field

Superparamagnetic

nanomaterials N/A

[34]

HEK293T cells (in vitro);

Rat hippocampal neurons (in

vitro);

amphid of C. elegans worms (in

vivo)

3’ + Excite

Ca2+ influxes; action

potentials; worms’

thermal avoidance

response

[35]


mouse embryonic stem cells (in

vitro);

xenografts of PC-12 cells in

3”, 4 + Excite

Cytosolic Ca2+;

proinsulin release;

gene expression;

blood glucose; plasma

Nano Res.

mouse (in vivo) insulin

[36]


mouse mesenchymal stem cells

(in vitro);

scaffolds containing mouse

mesenchymal stem cells in

mouse (in vivo)

3, 3”, 4

+ Excite

Proinsulin release;

gene expression;

blood glucose; plasma

insulin

[37]

HEK-293FT cells (in vitro);

hippocampal neurons (in vitro);

ventral tegmental area of mouse

brain (in vivo)

1 + Excite

Ca2+ influxes; action

potentials; c-fos gene

expression

Nano

Optotransducers NIR light

UV/Vis

light

Upconverting

luminescent

nanomaterials

[38]

[39] C1V1-expressing ND7/23 cells

(in vitro) N/A + Excite Photocurrents

[40]

Channelrhodopsin-2-expressing

mouse hippocampal neurons (in

vitro)

2 + Excite Action potentials

[41]

Channelrhodopsin-expressing

rat hippocampal neurons (in

vitro)

2 + Excite Depolarization; action

potentials

[42]

Channelrhodopsin-2-expressing


C. elegans worms (in vivo)

1, 4 + Excite Ca2+ influxes; worms’

reversal response

[43]

HeLa cells (in vitro);

T lymphocytes (in vitro);

melanoma tumor in mouse (in

vivo)

3” + Excite

Ca2+ influxes;

Ca2+/NFAT pathway

activation; tumor

destruction

Nano

Mechanotransducers

Magnetic

field

Mechanical

force

Magnetic

nanomaterials [44-47]

[48-50] Endothelial cells (in vitro) 3 - N/A Cytoskeleton

stiffening

[51] Human gingival fibroblasts (in

vitro) 3 - Excite Ca2+ influxes

[52] COS-7 cells (in vitro) 3” + Excite Outward current

Nano Res.

[53] Bovine capillary endothelial

cells (in vitro) 3’ + Excite Ca2+ influxes

[54] RBL-2H3 cells (in vitro) 3’ - N/A Ca2+ signaling

pathway activation

[55] DLD-1 cells (in vitro);

zebrafish embryo (in vivo) 3’ - N/A

Apoptosis signaling

pathway activation

[56] A431 cells (in vitro);

HeLa cells (in vitro) 3’ + N/A

EGFR signaling

pathway activation

[57] Cortical neurons (in vitro) 4 - N/A

Protein tau

distribution; cell

polarization

[58] HeLa cells (in vitro) 4 + N/A HaloTag protein

distribution

[59]

Rat retinal ganglion cells and rat

dorsal root ganglion cells (in

vitro)

4 - Excite;

inhibit Neurite outgrowth

[60] Rat cortical neurons (in vitro) 3, 4 - Excite Ca2+ influxes

[61] Rat cortical neurons (in vitro) 3 + Excite

Ca2+ influxes; N-type

ion channel

expression

1 Nanotransducers were distributed extracellularly. 2 Nanotransducers were immobilized on a substrate or microelectrode. 3 Nanotransducers were bound to plasma membrane. 3’

Nanotransducers were bound to receptors or anchoring proteins in the plasma membrane. 3” Nanotransducers were bound to ion channels in the plasma membrane. 4 Nanotransducers

were internalized and distributed intracellularly. + Cells were genetically engineered. - Cells were not genetically engineered. N/A No available information.

Nano Res.

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