Apical dendrite and theory of consiousness (La Berge, 2007)

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Neural Networks 20 (2007) 1004–1020www.elsevier.com/locate/neunet

2007 Special Issue

The apical dendrite theory of consciousness

David LaBerge∗, Ray Kasevich

Bard College at Simon’s Rock and Stanley Laboratory of Electrical Physics, Great Barrington, MA, 01230, United States

Abstract

The neural basis of consciousness is theorized here to be the elevated activity of the apical dendrite within a thalamocortical circuit. Both

the anatomical and functional properties of these two brain structures are examined within the general context of the cortical minicolumn, which

is regarded as the functional unit of the cerebral cortex. Two main circuits of the minicolumn are described: the axis circuit, which sustains

activity for extended durations and produces our sensory impressions, and the shell circuit, which performs input–output processing and produces

identifications, categorizations, and ideas. The apical dendrite operates within the axis circuit to stabilize neural activity, which enables conscious

impressions to be steady and to be sustained over long periods of time. In an attempt to understand how the conscious aspect of subjective

impressions may be related to apical dendrite activity, we examine the characteristics of the electric and magnetic fields during the movement of

charges along the apical dendrite. The physical correlate of consciousness is regarded here as the relatively intense electromagnetic field that is

located along the inside and the outside close to the surface of the active apical dendrite.c 2007 Elsevier Ltd. All rights reserved.

Keywords: Consciousness; Apical dendrite; Minicolumn; Electric and magnetic fields

1. Introduction

The special kind of activity in the brain that is presumed

to underlie consciousness continues to elude the grasp of

our scientific concepts. However, current theories of the

neural correlates of consciousness seem to agree on one

particular aspect of consciousness: its extendable duration.

Consciousness is an activity that is extended in time and

typically its duration continues from the time we awake to

the time we fall asleep. Grossberg (1999, 2005) describes

consciousness in terms of “resonance states” that occur in short-

term memory. When top-down expectations select consistentbottom-up signals and their reciprocal feedback activity

settles into a steady state, their circuits resonate together;

and while this resonance continues, consciousness exists,

according to his Adaptive Resonance Theory (ART). Taylor

(1999, 2005, 2007) describes consciousness as “temporally

extended neural activity” in a buffer store of working memory,

∗ Corresponding address: P.O. Box 301, So. Egremont, MA, 01258, UnitedStates. Tel.: +1 413 528 1303; fax: +1 413 644 9836.

E-mail address: [email protected] (D. LaBerge).

which is based on the corollary discharge of attention

movement (the CODAM model). According to the Theory

of Neuronal Group Selection (TNGS) of Edelman (2003),

consciousness is produced by reentrant interactions involving

the thalamocortical system, whose circuitry is dominated by

recurrent or looping circuits. Newman, Baars, and Cho (1997)

regard the activation loops of the thalamocortical circuit within

a global workspace model as crucial for generating conscious

states.

Unfortunately, mental activities that have extendable

durations, even of a few seconds, are not the kinds of

events that the traditional scientific framework of input–outputprocessing is structured to investigate and explain. Processing

of information is generally regarded as directed toward an

output, and not toward sustaining itself over prolonged periods

of time without apparent outputs. Therefore, if the input-

processing–output framework is the current reigning paradigm,

might the restrictive use of it hinder the quest for the neural

correlates of consciousness? In the present paper this paradigm

is modified to emphasize the input-processing components as

we seek to understand how consciousness may be generated at

the level of the neuron within neural circuits.

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D. LaBerge, R. Kasevich / Neural Networks 20 (2007) 1004–1020 1005

2. The circuitry in minicolumns of the cortex

2.1. The pyramidal neuron in the minicolumn circuit structure

The theory of consciousness described in the present paper

centers on the activity of a particular kind of cortical neuron: the

pyramidal neuron. The defining feature of the pyramidal neuron(the pyramid) that separates it from other neurons of the brain

is its very long apical dendrite, which generates the special

kind of electrical activity that is presumed here to underlie the

subjective impressions we call consciousness.

To set the stage for the description of the pyramidal neuron

and its apical dendrite in the circuit activity of the minicolumn,

we show how the pyramidal neuron is distributed within the

cerebral cortex. In Fig. 1, the top two diagrams show how

the cortical fabric, which is extensively convoluted to fit into

the sphere-like shape of the skull, can be transformed into a

flat surface (Van Essen, Drury, Joshi, & Miller, 1998), whose

thickness is defined by the length of columns of neurons.

Fig. 1 indicates that each column of neurons consists of a cluster of many minicolumns, and the structure of the

minicolumn appears to be organized around the central core

of layer 5 pyramids, which are the pyramids that contain the

longest apical dendrites (Peters & Sethares, 1991). Layer 6

pyramids are not organized within the minicolumn but instead

are organized within the column, which is a cluster of

approximately 100 minicolumns (Mountcastle, 1998). The

minicolumn is regarded as the functional unit of the cortex

(Mountcastle, 1957), which is based on the observation that

neurons in a given minicolumn share many receptive field

properties. The centrality of the long apical dendrites of layer

5 pyramidal neurons in the structure of the minicolumn isapparent in the two diagrams in the lower part of Fig. 1.

Later sections of the present paper will address the possible

centrality of the layer 5 pyramidal neurons in the function of

the minicolumn.

The pyramidal neuron is shown diagrammatically in

Fig. 1 as a triangular shape, representing the soma, with

a relatively long line attached at the top, representing the

apical dendrite. Thus, the axon and the many basal dendrites

of the pyramids are omitted in these diagrams. The other

neurons shown in the figure are stellate neurons, whose

many radiating lines represent the relatively short dendrites

attached to the soma. Visual inspection of Fig. 1 gives the

impression that the considerable majority of neurons in thecerebral cortex are pyramidal neurons, which is confirmed

by Feldman’s (1984) measurements, which estimate their

percentage in the cortex as approximately 70%–80%. The

remaining percentages of stellate and inhibitory neurons

(in area V1) are approximately 5%–8% and 16%–20%,

respectively (Mountcastle, 1998). Under the area of a dime

placed on the human skull over the parietal cortex there are

approximately 18,000,000–20,000,000 pyramidal neurons, of

which approximately 22% or 4,000,000–4,400,000 are layer

5 pyramidal neurons (based a cell count of approximately 70

neurons beneath surface patches of 25 × 30 microns for the

monkey).

Fig. 1. Locations of the pyramidal neurons in the cerebral cortex. The

lateral diagram of the cortex within the skull (upper left) shows a highly

convoluted sheet, which is converted into a flat surface (upper right), whose

area is approximately three times that of the lateral view. This cortical fabric

has an average thickness of approximately 3 mm and is constructed of

neurons organized in columns, which are clusters of minicolumns. Within

each minicolumn are shown the major pyramidal neurons with their vertically

aligned apical dendrites. The star-shaped cells in the middle of the minicolumns

are stellate neurons. For clarity, inhibitory neurons, which make up 15%–20%

of the total number of minicolumn neurons, are omitted. Axons, which exit at

the bottom of the somas, are also omitted.

The average length of the layer 5 apical dendrite varies

with cortical area, with parietal and motor areas showing

20%–50% longer lengths than occipital V1 area, based on

cortical thickness data of Rockel, Hiorns, and Powell (1980).

Also, the average length of the layer 5 apical dendrite varies

across the mammalian species of mouse, rat, cat, monkey

and humans, with the mouse apical dendrite of area V1

measuring approximately 1/3 the length of the human apical

dendrite (LaBerge, 2005, Fig. 1). It seems difficult to avoid

the tantalizing question of why the apical dendrite varies

considerably in length across mammalian species and across

cortical areas within a species. Discovering the function that

apical dendrite activity serves in cortical processing could help

in answering that question.

2.2. The axis and shell circuits within the minicolumn

To explore apical dendrite activity in cortical circuitry, we

simplify the complex arrangements and interconnections of

neurons within a minicolumn by dividing the minicolumn

into two compartments, the axis and the shell. Fig. 2 shows

diagrammatically how the layer 5 pyramids, with their very

long apical dendrites, form the axis part of the minicolumn



1006 D. LaBerge, R. Kasevich / Neural Networks 20 (2007) 1004–1020

Fig. 2. Most of the neurons of a minicolumn are organized around the long

apical dendrites of the layer 5 pyramidal neurons (the axis), with apical

dendrites of layer 2/3 pyramidal neurons (the shell) arranged in a circular

pattern around the top sector of the apical dendrites of the layer 5 pyramidal

neurons.

while the layer 2 and layer 3 pyramids form the shell part

of the minicolumn. Fig. 3 shows the general structure of the

circuit within each of these two parts of the minicolumn.The axis circuit of the cortical minicolumn extends to the

subcortical thalamus in a reciprocally connected manner, such

that a recurrent or looping circuit exists between the layer

5 pyramid and a thalamic neuron. The axis circuit can be

characterized as an “input-stayput” circuit, because its apparent

function is not the processing of inputs into outputs, but instead

the holding of neural activity over time. The shell circuit is

shown as a one-directional input–output circuit that connects

one minicolumn with another, and the processing component

consists of connections between layer 2/3 pyramids within the

minicolumn. One could also characterize the axis circuit as

a “vertical” circuit, because it extends from the cortex to thesubcortical thalamus, and the shell circuit as a “horizontal”

circuit, because it extends within the cortex, linking one cortical

minicolumn to another.

2.3. The minicolumn circuitry of primary sensory cortical

areas

Traditionally, the study of connections of neurons in the six

layers of the neocortex has been aimed at the discovery of their

receptive field properties (e.g., Bolz, Gilbert, & Wiesel, 1989).

Here we study the interlaminar connections within the cortical

minicolumn to discover how they could support sustained

activity in recurrent circuits that are believed to underlie

Fig. 3. The two main kinds of minicolumn circuits defining the cortical

minicolumn. The recurrent circuit (left) contains the layer 5 pyramidal neuron

and connects with thalamic neurons; and the input–output circuit that contains

layer 2/3 pyramidal neurons (right) restricts its connections to the cortex. The

inhibitory neurons of thecortex andof thethalamicreticular nucleus (and dorsal

thalamus) are omitted for clarity.

consciousness. It is assumed in this paper that sustained

activity in a primary sensory area provides the ongoing

activity of background consciousness for that particular sense.

Elevated consciousness for selected aspects of background

consciousness is assumed to arise when sustained activity

of a primary sensory area is sent to higher sensory areas,

where a selected part of the sensory scene is amplified

by attentional activity controlled from the frontal lobes.

The elevated attentional activity of a part of the sensory

scene in higher sensory areas is regarded here as foreground

consciousness.

Fig. 4 shows a diagram of the major connections between

excitatory neurons in the primary visual area (V1), which

applies generally to primary auditory (A1) and primary

somatosensory (S1) areas as well. The circuit diagram is

adapted in part from diagrams in two publications by Jones(2002, 2007), which summarize what is known to date about the

reciprocal connections between a sensory area and the thalamic

neurons that serve that area.

Layer 5 and 6 pyramids participate in the two kinds of

corticothalamic loops. Apparently layer 2/3 pyramids do not

participate in major circuit loops; nevertheless they do have

apical dendrites of appreciable length. It has been suggested

(LaBerge, 2001, 2005) that these apical dendrites sustain

activity supplied by tonic input from the layer 5 circuit loop,

and that this sustained activity, operating at subthreshold firing

levels, modulates the input–output processing of basal dendrites

inputs within the soma of layer 2/3 neurons.




Fig. 4. Diagram of the major circuits in a minicolumn of a primary sensory area

(e.g., area V1), involving two kinds of thalamic relay neurons, Tmatrix and

Tcore. Inhibitory neurons are omitted for clarity. Adapted in part from Jones

(2002, 2007).

When the inputs to the layer 5 and layer 6 loops of Fig. 4

are compared, it is clear that the layer 6 loop is capable of

supplying large amounts of activity to the apical dendrite of

the layer 5 loop (via thalamic Tcore axons terminating on

the many layer 4 stellate neurons), while the layer 5 loop

delivers no activity to the apical dendrite of the layer 6 loop

(and apparently only minor activity to the basal dendrites

of the layer 6 pyramid). Thus, while the axons from the

two kinds of thalamic relay neurons drive activity in their

respective thalamocortical circuits, the total activity in the layer

5 circuit includes additional, and relatively strong, inputs from

the activity of the layer 6 pyramidal circuit. This preferential

convergence of activity on the apical dendrite of the layer 5

pyramid is consistent with the anatomical centrality of the layer

5 apical dendrite in the structure of the minicolumn.

2.4. The minicolumn circuitry of higher sensory cortical areas

The neurons in the primary sensory minicolumn send

activity to minicolumns of higher sensory areas along two

pathways: a direct axon pathway from the layer 2/3 pyramid

of the shell circuit, and an indirect axon pathway from the

layer 5 pyramid of the axis circuit that synapses with a relay

thalamic neuron before entering the higher sensory cortical

minicolumn. Fig. 5 shows the terminations of these pathways

Fig. 5. Diagram of the major circuits in a minicolumn of a higher sensory

area (e.g., area V4). Some of the inputs to the thalamic matrix neuron from

the frontal area connect with thalamocortical circuits in the parietal area before

terminating on the thalamic neuron serving this higher sensory area. Adapted

in part from Jones (2002, 2007).

in the higher sensory minicolumn, along with the pattern of

connecting circuitry of neurons.

Perhaps the most salient difference between the circuitry of

the higher sensory minicolumn and the circuitry of the primary

sensory minicolumn is the change in number of stellate neurons

in layer 4. The reduction of stellate neurons in the higher

sensory minicolumn is reflected by the shrinkage in thickness

of layer 4, which is produced also by a corresponding increase

in the thicknesses of layers 3, 5, and 6, which contain pyramidal

neurons that make up the vast majority of neurons of the cortex.

Another noticeable difference between the circuitry of primary

and higher sensory minicolumns is the increase in synaptic

connections of the thalamocortical axon (from the matrix relay

neuron) onto the distal region of the layer 5 and layer 2/3 apical

dendrites. Taken together, going from the primary to the higher

sensory minicolumn, these two changes in circuitry suggest that

the influence of the thalamic core (T core) neuron on activity of

the layer 5 apical dendrite is reduced, while the influence of the

thalamic matrix (T matrix) neuron is increased.

This shift in the influence of the two kinds of thalamic

neurons on activity of the layer 5 apical dendrite is parallel

to the shift in influence of bottom-up and top-down sources

of activity, globally considered. The many stellate neurons




in layer 4 of the primary sensory minicolumn appear to

serve the strong registration in cortex of activity arising from

sensory receptors (retinal, auditory, somatosensory), but once

this registration takes place in the primary sensory area of the

cortex, the need for the special function of the stellate neuron

is apparently reduced. To summarize this section, there are two

major kinds of inputs to the higher sensory minicolumn: onefrom the stimulus registration activity of the primary sensory

minicolumn, and the other from frontal areas of the cortex.

2.5. Attentional activity in higher sensory minicolumns

How does the circuitry of the higher sensory minicolumn

operate on the information arising from the primary sensory

area and from the frontal areas? One answer is that the higher

sensory minicolumn serves as a site for attention, defined as

the elevation of circuit activity corresponding to a selected

part (typically a small part) of the total registration of the

sensory scene in V1, A1, or S1. The operations of attention

are presumed to involve both an enhancement of activity inthose minicolumns that correspond to, or code, the selected

locations and/or appearances of the scene, and a concurrent

suppression of minicolumns that code neighboring parts of the

scene (locations and appearances of distracters). For example,

under attentional conditions, an orientation-sensitive V4 neuron

shows amplification in responding, while the width and mean

of its tuning curve remains unchanged (McAdams & Maunsell,

1999). The control of selective amplification/suppression

during attentional activity is presumed to be produced by axons

of the frontal cortex that make contact with the thalamic relay

neurons that serve those minicolumns (see Fig. 5). Hence,

the thalamic neurons receive activation from two sources:frontal areas of attentional control and the primary sensory

minicolumns. The intensity of activity from the frontal area can

be varied, but the intensity of activity from the primary sensory

minicolumn would seem to remain relatively constant, under

typical conditions. When attentional manipulations produce

changes in V1 (McAdams & Reid, 2005; Silver, Ress, &

Heeger, 2007) and/or lateral geniculate nucleus (LGN) activity

(O’Connor, Fukui, Pinsk, & Kastner, 2002), the change would

seem to be minor relative to the change in activity that

attentional manipulations can produce in higher sensory areas,

given the circuit properties of these areas shown in Figs. 4

and 5. Thus, attention is regarded as the intensification of

a particular part of the sensory scene registered in primarysensory areas by means of the amplification of axis circuit

activities in minicolumns of higher sensory areas that code that

particular part of the sensory scene.

The higher sensory minicolumn is presumed to perform a

function in addition to the expression of attentional activity

in an axis circuit. The shell circuit of these minicolumns

receives inputs from shell circuits of the primary sensory

minicolumn, which are processed into an output that we

assume constitutes the identification of stimuli coded by that

minicolumn. Identification of input information is presumed to

be a brief event, relative to the typically prolonged sustaining

of attention to that event. But in a cluttered scene (visual,

auditory, or somatosensory), attentional enhancement of the

shell circuit activity may be required to produce accurate

identifications. It has been suggested (LaBerge, 2001, 2005)

that tonic enhancement of soma activity in layer 2/3 pyramids

can be produced by inputs from the layer 5 axis circuit, as

shown in Fig. 5. With activity already at an elevated level in

the soma of the layer 2/3 pyramid, the input to a basal dendritefrom a layer 2/3 pyramid in the primary sensory minicolumn

has a higher likelihood of being successfully processed into

an output. This issue will be addressed in more detail in

Section 4.4 of this paper.

3. Special functions of apical dendrite activity

3.1. The issue of stability in corticothalamic circuit activity

Under the assumption that activity in corticothalamic

circuits underlies the extended durations of consciousness,

it follows that the circuit activity must maintain stability

over these durations of time. The cortical environment, aswell as the circuit itself, contains sources of excitatory and

inhibitory noise. Wide fluctuations in voltage levels at the

soma of the pyramidal neuron can interrupt ongoing circuit

activity when intense voltage peaks distort circuit operations,

and when momentary drops in voltage shut down the circuit

operations. To maintain steady levels of soma activity some

means must be found to oppose the naturally noisy nature of

both the cortical background activity and the circuit operations

themselves (Tegner, Compte, & Wang, 2002).

Evidently, the brain has solved the stability problem

for apical dendrite activity, because synchronous oscillations

over extended durations have been recorded from implantedelectrodes and electrodes on the scalp while animals sustain

attention (e.g., Bouyer, Montaron, & Rougeul, 1981). Here we

describe one way that oscillatory activity in the apical dendrite

can become uniform so that it can promote stability in the

corticothalamic circuit of which it is a part.

Because stability in a recurrent circuit is related to the extent

or width of momentary fluctuation of its activity level, one

indicator of stability is the variability of successive electrical

events at a given location within the circuit. Therefore, to

increase the stability of circuit activity the variability of activity

level must decrease. The part of the corticothalamic circuit that

appears to be most variable is the pyramidal neuron, particularly

at synaptic sites along the apical dendrite where the almostsimultaneous discharge of many incoming axons induces

strong electric currents that result in large EPSPs (excitatory

postsynaptic potentials). By the time a EPSP propagates to the

soma, the variability of the EPSP must be substantially reduced,

so that a sequence of EPSPs produce a steady level of soma

activity that can generate a synchronous series of axon pulses.

In Fig. 6 are shown four curves that describe the decay of

four levels of initial EPSP voltages as a function of distance

traveled along the apical dendrite from the region of its

initiation to the soma. At any given location on the apical

dendrite the variability of voltage is indicated by the spread of

a Gaussian-shaped distribution. Almost all of the area under




Fig. 6. A family of theoretical exponential functions that describe the decay of

voltage with distance along the apical dendrite from the initiation of the EPSP.

Four levels of voltage, V , are shown at the initiating synapse, and the distance

to the soma is represented by d . The decay constant for this example is k , which

represents the average of the many active and passive membrane conductances.All voltage values are increments in voltage from baseline level. The left-to-

right sequence of Gaussian-like distributions describes the reduction of voltage

variability as the EPSP propagates toward the soma.

a distribution of voltages is assumed to lie below the firing

threshold of an action potential, for reasons indicated in the

next section of this paper. The voltage level at the soma and

its variability are shown to decrease with the distance the

EPSP travels to reach the soma. The exponential equation that

describes the rate of EPSP decay with distance was developed

by Rall (1989), and represents the passive decay of voltage

in a cable model of the dendrite. The average membrane

(outward) conductance is represented by the constant, k , andmore recent versions of the cable model assume that the

membrane conductances of dendrites in the awake animal are

dominated by active inhibitory (outward) currents, with an

inhibitory chem/excitatory ratio that may be as high as 5-to-1

(Destexhe, Rudolph, & Pare, 2003).

3.2. The give-and-take operations of apical dendrite activity

The dendrites of a typical pyramidal neuron contain as many

as 10,000 synapses (DeFelipe & Farina, 1992), and a typical

apical dendrite (of the rat) contains at least 3000 (excitatory)

synaptic spines on its major vertical shaft, with a similar

quantity of spines on oblique dendrites that are branches of the dendrite shaft (Larkman, 1991). Since the length of the

human apical dendrite is approximately 2 times that of the rat,

the estimated quantity of synaptic spines on the major shaft

of the human apical dendrite could be as high as 6000. The

locations of these ubiquitous dendritic spines are indicated in

an abbreviated manner along the apical dendrites shown in

Figs. 4 and 5. Aside from the synapses made by thalamic axons,

the vast majority of synapses are activated from other cortical

neurons (Braitenberg & Schuz, 1998), which provide most of

the background noise for the apical dendrite. Synaptic activity

along the apical dendrite produces a rich variety of intrinsic

electric and chemical effects (Llinas, 1988; Reyes, 2001; Yuste

& Tank, 1996), and the activity at the thousands of spine

synapses on the dendrite maintains membrane depolarization

at subthreshold firing levels. It is estimated that the thousands

of synapses on dendrites are responsible for approximately 80%

of the mainly inhibitory conductance of the dendritic membrane

(Azouz & Gray, 1999; Contreras, Timofeev & Steriade, 1996;

Nowak, Sanchez-Vives, & McCormick, 1997). The chaoticnature of this background input to the apical dendrite produces

fluctuations that sometimes generate action potentials that may

arise from transient calcium currents (Helmchen, Svoboda,

Denk, & Tank, 1999). Action potentials that originate in

dendrites do not always propagate to the soma (Jarsky, Roxin,

Kath, & Spruston, 2005; Larkum & Zhu, 2002), and may

participate in local changes of synaptic long-term potentiation

(Colbert, 2001; Goldberg, Holthoff, & Yuste, 2002). Recent

findings from intracellular recordings of action potentials in

vivo during Up states and during visual stimulation indicate that

action potentials are typically initiated in the axon (Shu, Duque,

Yu, Haider, & McCormick, 2007). The part of the axon that

appears to be the preferred site of action potential initiation isthe initial segment of the axon that typically lies 40–55 microns

from the soma.

Of particular relevance to the stabilizing of thalamocortical

circuits is the effect of the active membrane conductances

maintained by tonic activity in the thousands of synaptic spines

along the apical dendrite. This spine activity produces the

attenuation of the voltage of the EPSP as it propagates along

the apical dendrite shafts illustrated diagrammatically in Figs. 4

and 5. The decaying curves shown in Fig. 6 indicate the

attenuating effect of spinal activity between the site of EPSP

initiation and the soma.

Therefore, it could be said that the propagating EPSP of the apical dendrite is treated in a “give-and-take” manner.

The EPSP is “given” to the apical dendrite by axon activity

of groups of layer 4 stellate neurons and by activity of

thalamic axons. Immediately there ensues a “taking” of the

EPSP, which is the attenuation of the EPSP produced by the

outward conductances of the membrane produced by low-

level synaptic activity in the thousands of spines that dot the

dendritic shaft. As the EPSP approaches the soma, it decreases

in strength, but, importantly, the variability of the strength

also decreases. The average rate of decrease is described by

the exponential decay equation based on average membrane

conductance. The theoretical convergence of decreasing mean

voltage with distance can also be described by equations other

than the exponential equation (see, e.g., Koch (1998)).

The variance of the propagating EPSP at the soma is

assumed to be relatively high for the first cycle of electrical

activity through the recurrent thalamocortical circuit. But in

subsequent cycles, the EPSP at the soma moves more closely

to the mean voltage it will ultimately achieve, so that the

variability of the EPSP at the asymptote can be regarded as the

characteristic level of stability for this recurrent circuit, given

the particular conditions that are present at the time.

Conditions under which the thalamocortical circuit operates

can vary considerably. One important condition is the intensity

level of the afferent input to the thalamic relay neuron, which




can be varied by the brightness contrast of an oriented line in

vision. Variability of input to the thalamic relay neuron can also

be produced by the focusing of attention to the oriented line in

the axons arising from frontal areas of attentional control. In

both of these cases the number of active thalamic relay neurons

can vary the level of EPSPs in a layer 5 apical dendrite (directly,

or via stellate neurons) by varying the number of active axonsthat contact that apical dendrite, while maintaining a constant

frequency of pulses in the input axons. This inference is based

on the finding that, in the cortex, a branching axon seldom

makes more than 10 contacts with any single neuron, and

frequently with only one or two neurons (Mountcastle, 1998).

When the magnitude of the EPSP that is “given” to the apical

dendrite varies, its variability will also change, and this change

will be maintained as it propagates to the soma (see Fig. 6).

When the variability of the EPSP at the soma changes, so will

the stability of the entire thalamocortical circuit. Therefore, to

maintain a high level of stability in the thalamocortical circuit,

some means must be found to make appropriate adjustments in

the trimming operation of the variable EPSP before it reachesthe soma.

3.3. Balancing the “give-and-take” operations in the apical

dendrite

One possible way to compensate for a large initial EPSP

“given” to the apical dendrite is to increase the synaptic

strengths of the thousands of spine synapses that “trim” the

EPSP as it propagates to the soma. Adjustments to the axon

inputs to these spines could be produced in two general ways.

The first way involves specific circuits that respond directly

to the intensity of the initial EPSP. For example, the layer 6pyramid, whose momentary activity presumably keeps pace

with the activity level of the layer 5 pyramid, sends collaterals

of its axons into layer 4, where they branch profusely. If enough

of these axon arborizations contact the spines of the layer 5

apical dendrite, a close link would be formed between the

momentary amount of the “give” operation to the consequent

amount of the “take” operation. As it turns out, however, the

supporting evidence for a high number of layer 6 axon synapses

on layer 5 apical dendrites (McGuire, Hornung, Gilbert, &

Wiesel, 1984) is not strong.

A second way that the “take” operation may be controlled

by the “give” operation is by means of a large and diffuse set

of circuits that operate in a more indirect way than the kind of specific circuit just described. When a large EPSP is delivered

to the apical dendrite by the thalamic relay neurons contacting

pyramidal and stellate neurons of the cortex, it is likely that

many local circuits of the local minicolumn increase the level

of their activity. If these local circuits supply most of the axon

input to the thousands of spines on an apical dendrite, then an

increase in the activity level in these many circuits will result

in an upward adjustment in the spine activity, which would

increase the local outward membrane conductance, thereby

increasing the trimming of the “take” operation. However,

because of the diffuse nature of the connectivity of the many

local minicolumn circuits, it is likely that their activity levels

may not change quickly. Hence, adjustments to the “take”

operations on the propagating EPSP in the dendritic spines may

lag well behind changes in the “give” operation of the initiating

EPSP. Therefore, it would seem that this diffuse circuit model

exhibits much less direct coupling between the “give” and the

“take” operations than would be shown by a specific circuit

model.The adjustment of the “give-and-take” treatment of variable

EPSPs of the apical dendrite may take place by means

other than those described in the foregoing paragraphs. When

attention to an object is intensified over longer time periods,

activity in a thalamocortical circuit is repeated with elevated

intensities of EPSPs occurring in the apical dendrite. As a

result, new spines may appear, which induce the apical dendrite

shaft to elongate to accommodate the additional spines. A

longer length of the spine-covered apical dendrite enables the

EPSP to undergo additional reduction in variability, which

compensates for the additional variability in the initial EPSP

that accompanies higher levels of intensity.

In view of these considerations, it might seem puzzling thatin area V1 the major input synapses of the stellate neurons

on the apical dendrite of layer 5 pyramids are located at the

middle part of the layer 5 pyramidal apical dendrite, and not at

the distal part, whence an initial EPSP could undergo a larger

amount of trimming before it reached the soma. One hypothesis

suggests that the activity in the lateral geniculate neurons

already possesses a moderate level of stability, because the

visual scene that stimulates the retina is typically quite stable.

In comparison, major synapses on apical dendrites of layer 5

pyramids in higher sensory minicolumns appear to be located

at more distal parts, while midsection stellate neurons supply

a minor portion of the synaptic input. The distal synapseson apical dendrites in the higher sensory areas are driven by

thalamic pulvinar neurons, which do not receive the major

part of their inputs from the retina. Therefore these EPSPs at

the distal apical dendrites exhibit a higher level of variability

and require more trimming before they reach the soma. Fig. 5

shows that the thalamic pulvinar neurons are activated from

two major sources: the frontal cortical areas, and area V1.

The variability from area V1 is presumed to be low, having

started at a moderate level (from the relatively stable retinal

source) and having received further refinement by the trimming

operation of the V1 layer 5 apical dendrite. But the source of

variability from frontal cortical areas is presumed to be quite

large, owing to presumed high fluctuations in frontal cortical

circuits. Also, the weight of the frontal input component to the

pulvinar neuron is presumed to be influenced by the intensity

level of attentional control. Therefore, the higher the intensity

of attentional control, the higher the variability of the activity

delivered to the pulvinar neuron. Hence the EPSP induced at

the distal part of the apical dendrite in the higher sensory area

is increased, and a commensurate increase in length of apical

dendrite is needed to reduce this increased variability before

the EPSPs reach the soma.

Therefore, these theoretical considerations predict that high

levels of attention directed to a particular object should, over

weeks and years, elongate the apical dendrites of layer 5




pyramidal neurons in the minicolumns (of higher sensory areas)

that code that object. One potential indicator of apical dendrite

length is cortical thickness, which has been measured with

variations of the fMRI technique. We turn now to an analysis of

the effectiveness of this measure for estimating apical dendrite

length.

3.4. Lengths of apical dendrites and cortical thickness

Many apical dendrites of layer 5 and layers 2/3 extend

to the top of layer 1 and spread laterally in tufts for a short

distance, apparently leaving little space in which to expand

upward. Therefore, an elongation of the shaft of the apical

dendrite should shift the soma in the other direction toward the

bottom of layer 6. However, in the case of stretching apical

dendrites of layer 5 pyramids, it would seem that there is

little space within layer 6 to accommodate the relative massive

somas of layer 5 pyramids, owing to the already high packing

density of neurons in a minicolumn (Hendry, Schwark, Jones,

& Yan, 1987; Rockel, Hiorns, & Powell, 1974). In view of theselimiting factors, it would seem that an elongation of the apical

dendrite shaft would result in an expansion of the individual

cortical layers through which the shaft passes. As a result the

total thickness of the cortex would increase in the local cortical

areas containing these elongated apical dendrites.

A fMRI study of meditation practice by Lazar et al. (2005)

found selected brain regions in which cortical thickness was

larger in participants who had extensive meditation experience

than in controls, and Makris et al. (2006) found smaller

cortical thickness in cortical areas underlying attention in

participants diagnosed with ADHD compared with controls. It

is tempting to infer that the observed change in thickness wasstrongly influenced by the changes in apical dendrite lengths

owing to meditation practice or attentional pathology. However,

even though increases in apical dendrite length could produce

increases in cortical thickness, would these measured increases

in cortical thickness necessarily imply an increase in apical

dendrite lengths? Elevated activity in minicolumns over time is

presumed to generate new synapses, and an increase in number

of synapses (and spines) along with their increased lengths

of local axon branches could also increase cortical thickness

owing simply to the overall increase in volume of neuronal

tissue. However, if an appreciable proportion of new synapses

appear on an apical dendrite, then it would seem that the

apical dendrite would have to elongate to accommodate theseadditional synapses. Also, data from the frontal cortex of rats

that undergo confinement each day for 21 days show that the

loss of spines on apical dendrites is accompanied by a 20%

reduction in the length of the apical dendrite (Radley et al.,

2006). Nevertheless, the more cautious interpretation is that

observed changes in cortical thickness could conceivably be

produced by an increase in synapses without an increase in

apical dendrite length. On this view, cortical thickness measures

by themselves are not an unambiguous indicator of underlying

apical dendrite lengths. What is clearly needed is a technique

that enables apical dendrite lengths to be measured directly in

live animals and humans.

3.5. Lengths of apical dendrites and the ERP

The ERP (event-related potential) measured at the scalp is

a transient EEG that is produced by a relatively abrupt onset

of stimulus whose amplitude is increased when its location

and attribute have been cued in advance of its appearance.

The cue is presumed to induce preparatory attention to thelocation and attributes of the target stimulus, which presumably

produces elevated activity in the columns that code the location

and attributes of the stimulus, relative to the activity levels

in neighboring columns that code for similar locations and

attributes. In the typical ERP task, both target and distracter

stimulus appear in a random sequence, with the target appearing

at a low frequency. The task for the observer is to count the

number of targets over a marked time period. The finding

of interest is that the ERP amplitude is higher at the cued

location of the stimulus attributes than at an uncued location

(e.g., DiRusso, Martinez, and Hillyard (2003)).

According to the present theory, when the cue induces

preparatory attention to a particular stimulus content, thecorresponding minicolumn axis circuits elevate their activity

levels, and they maintain or increase these levels throughout the

time period in which the target stimulus is expected to occur.

When a stimulus of the cued attribute and location appears,

the apical dendrites in the minicolumn axis circuits show a

transient increase in amplitude of electric fields. For vision, the

pathways that are likely to deliver this increase are the relatively

fast conducting Y -cell driven pathways in the cortex and in

the superior colliculus. Both pathways synapse with pulvinar

thalamic neurons before terminating within a minicolumn of

a higher sensory area (see Fig. 5). The Y -cells in the retina

respond only transiently to the onset of a visual stimulus, sothat the activity in their pathways presumably has a transient

effect on the apical dendrites where their pathways eventually

terminate.

In a study by Pantev et al. (1991) the repeated displays of the

target stimulus produced a transient increase in amplitude of the

scalp-recorded EEG 20–130 ms after stimulus onset (the MEG

recording was virtually identical in form to the EEG recording).

The short interval of amplitude increase was shown to consist

of 4 or more cycles of 40 Hz oscillations, which suggests that

the sustained preparatory attention was being produced by axis

oscillations at 40 Hz, and that when a stimulus appeared, the

oscillations were amplified for a fraction of a second.

Amplifications of the ERP are produced not only bymomentary attention but apparently also by long-term effects

of attention during training. Simple and complex tones produce

higher amplitudes of early ERPs in musicians who have had

many years of musical training compared with non-musicians,

even under passive attention conditions (Kuriki, Kanda, &

Hirata, 2006; Shahin, Bosnyak, Trainor, & Roberts, 2003;

Shahin, Roberts, Pantev, Aziz, & Picton, 2007). Also, trained

meditators show higher amplitude ERPs (and frequencies)

compared to controls (Lutz, Greichar, Rawlings, Ricard, &

Davidson, 2004).

The source of the electric fields that produce an ERP is

assumed to be the electric dipole, which is defined by the




location of the two opposite electric charges along the active

portion of the apical dendrite. The intensity of the dipole,

termed the dipole moment, is influenced by two variables:

the charge at the two poles and the distance between them.

Therefore, an increase in ERP amplitude can be produced

by stronger charges of EPSPs or by a greater length of the

apical dendrite shaft traveled by the EPSP, or by both of these variables. The present theory suggests that the larger

EPSPs produced by strong sustained attention over years of

training induces an elongation of apical dendrite shafts, so that

distance as well as charge of the dipole would be affected

in expert musicians. However, in the short duration of a task

condition that instructs or otherwise induces the observer to

increase attention there is not enough time to elongate the apical

dendrites, so that the increase in dipole strength is apparently

solely due to increase in the charge produced by the larger

EPSPs of heightened attention.

The foregoing analysis suggests a way that training may

increase ERP amplitude by changes in apical dendrite length

over time. Does it follow that an increase in ERP amplitude overtime indicates that the apical dendrite length has increased?

Apparently not, because an observed increase in ERP amplitude

at the scalp could be produced simply by more minicolumns

being recruited, without any change in apical dendrite length

and without any change in EPSP amplitude induced on an

individual apical dendrite.

4. Implications of minicolumn circuitry for cognition

The two different kinds of minicolumn circuits make

possible two different kinds of cognitive activity, according to

the theory of cortical function described in the present paper.The shell circuits, which connect layer 2/3 pyramidal neurons

across minicolumns, operate as input–output mechanisms that

typically complete their processing in a short fraction of a

second. Shell circuits in early sensory areas that receive V1

inputs identify object appearances and locations, and later

sensory areas process these identifications into categories. In

the frontal areas categories are organized into propositions that

may be based mainly on activity in the shell circuitry spread

across many minicolumns. Fig. 7 shows a diagram of the global

shell pathway, along which early identifications of stimulus

objects and locations are processed into the categories and

propositions upon which the operations of intellectual thinking

operate.The second general kind of minicolumn circuit is the axis

circuit, which connects layer 5 pyramidal neurons between

minicolumns through intervening synapses with thalamic

neurons. Fig. 7 shows a diagram of the global axis pathway,

which begins with the initial cortical registration of sensory

inputs in primary sensory minicolumns, and extends into the

frontal cortex where, among other activities, axis circuits are

presumed to perform special supporting functions for the shell-

based processes of thinking. The axis circuits act as holding

circuits that sustain activity for extended periods of time.

When the intensity of the apical dendrite component of the

thalamocortical holding circuit is sufficiently high, it produces

Fig. 7. Global ascending pathways that connect posterior cortical columnswith anterior cortical columns in two ways. One way (the lower-tier pathway)

connects columns by their axis circuits, and the other way (the upper-tier

pathway) connects columns by their shell circuits.

the cognitive event that may be called “having an impression”

of something. The earliest of these subjective impressions takes

place in the primary sensory areas of the cortex where the

entire array of sensory input is first registered in the cortex

(see Fig. 4). We regard a scene that contains many impressions

as background consciousness, and the array of impressions is

typically sustained for very long periods of time while attention

selects impressions of specific objects in the scene. Examples

are visual scenes seen through a window, the ambient sounds of

traffic heard outside a city room, and the continuous sensations

of the somatosensory landscape of the body.

Foreground consciousness is produced by axis circuits that

produce impressions in higher sensory areas (see Fig. 5);

these axis circuits are presumed to be strongly influenced

by top-down frontal activations which elevate activity in

minicolumns that code a selected part of the total registered

input. This attentional activity can take on variable degrees

of spatial focus and intensity, depending on the manner

of control activity received from the frontal areas. Thus

the simultaneous impressions from both foreground and

background consciousness together constitute the momentary

content of consciousness.Fig. 8 shows diagrams of top-down global pathways for

both the shell and axis circuits. Two of the important cognitive

functions served by these pathways are attention and imaging.

In the case of attention, the top-down axis pathway provides one

of the two input sources that activate thalamic neurons serving

the minicolumns of higher sensory areas in the posterior cortex

(see Fig. 5). Thus, the sustaining of attention over extended

time periods is controlled by sustained activity in axis circuits

of frontal areas.

The top-down shell pathway may function to shift attention

rapidly among an array of stimulus items during search.

Axons from frontal attentional control areas are presumed




Fig. 8. Global descending pathwaysthat connect anterior cortical columns with

posterior cortical columns in two ways. One way (the lower-tier pathway)connects columns by their axis circuits, and the other way (the upper-tier

pathway) connects columns by their shell circuits.

to contact layer 2/3 pyramids (through stellate neurons),

whose axon collaterals produce strong lateral inhibition in

neighboring minicolumns that code for distracter locations and

appearances. Since the operations of inhibitory neurons are

typically very rapid compared to the operations of excitatory

neurons, the top-down shell pathway can support a series of

very rapid attentional selection of minicolumns that code for

locations. Identifications of each scanned item can be quickly

accomplished in the shell circuitry of attribute minicolumns

(selected by axons from location minicolumns), and becausethe “dwell time” of attention on any particular item is very brief,

the contribution of axis circuitry has a minimal contribution

to the operation of selecting minicolumns during the scanning

operations. Therefore the major circuit operations supporting

rapid search appear to be the lateral inhibitory connections

within shell circuits.

4.1. Attention and the binding of object attributes

It is generally agreed that the binding of component

attributes produces the unitary impression of an object. The

theory of minicolumn circuitries, described in the present paper,

suggests that the binding of attributes of an object occurs

by the set of impressions produced by the simultaneously

elevated apical dendrite activity in minicolumns that code

those attributes. When this set of minicolumns is linked

to minicolumns coding a common location, attention to

that location raises the activation of the connected attribute

minicolumns in a correlated manner. Therefore, the binding

could take place along the axis pathways shown in Fig. 8

that intersect a common location. The amplified activity in the

axis circuits containing the apical dendrites is based in part

on a common frequency of electric oscillations, and but also

on the amplitude of the EPSPs in the apical dendrites. Phase

locking does not seem crucial to binding, on this view, owing

to the variable lengths of axons that connect axis circuits of

participating minicolumns. When visual objects are displayed

very briefly, the axis circuits may have sufficient time to

produce accurate impressions of attributes but not sufficient

time to produce impressions of precise locations. As a result,

some attributes may be bound to incorrect locations and lose

their correct conjunctive relationships, so that the observerreports seeing objects whose conjunction of attributes is not

correct but “illusory”.

4.2. Holding circuits in frontal areas

Many of the potential cognitive aspects of axis activity in

frontal minicolumns have not yet been explored. Some of the

possible functions of the thalamocortical holding circuit are

suggested by the way the basal ganglia influences activity in

the frontal cortex. Axons from neurons of the basal ganglia do

not directly synapse on neurons of frontal cortex but instead

on thalamic neurons that are connected to frontal cortical

neurons (Alexander & Crutcher, 1990). One implication of this neuroanatomical arrangement is that the thalamocortical

holding circuit is involved when motivational activities in the

basal ganglia act upon the cognitive and motor actions that

are processed in frontal circuits. Activity held in these circuits

can then operate on shell circuits in a modulatory manner,

thereby influencing the way that input–output processing takes

place in these circuits. For example, holding circuit activity

may stabilize the input–output processes involved in choosing

among several tasks to perform in the Wisconsin Card Sorting

Task, for example, sorting by color, or shape, or number.

A thalamocortical holding circuit, controlled from the basal

ganglia, may also stabilize the processes involved in the earlytrials of performing a specific task, such as sorting by color.

An unstable holding circuit of a newly cued task may induce

the participant to revert to the previous task, which is a finding

frequently observed in schizophrenic participants.

Another subcortical circuit that may influence cortical

circuits through the thalamic holding circuit is the limbic

circuit. One cortical target of the limbic circuit is the anterior

cingulate area, which has been shown to be particularly active

during cognitive events that involve conflict. When conflict is

evoked in a task, it typically persists over a period of time; and

while the conflict activity is sustained, it is often accompanied

by “feelings” or impressions of the conflict. These observations

suggest that the holding circuit participates in maintainingstates of conflict. Evidence supporting this conjecture is

given by an fMRI study of attention (Buchsbaum et al.,

2006) in which elevation in activity of the anterior cingulate

and its connected anterior thalamic neurons implicates the

thalamocortical recurrent circuit that connects these two brain

structures.

Frontal holding circuits also would seem to be implicated

during the effort to recall an item from long-term memory (e.g.,

recalling an image of the Eiffel Tower). Although the typical

impression of the effort to recall is not as vivid as the sensory

impression of the item itself, or an image of the item, there

may be occasions in which the effort to recall an item believed




to be “on the tip of the tongue” is indirectly experienced

as an impression of tension somewhere in the body. The

sustained activity of a bodily somatosensory indicator implies

that a holding circuit is maintaining this activity. Because the

occasion that gives rise to the effort is the attempt to recall

an item, it would seem that the holding circuit is located in

or close to the recall operation. However, one ordinarily isnot conscious of an impression of effort activity in these axis

circuits because the intensity of activity in these apical dendrites

is overshadowed by the characteristically strong intensities in

axis circuits of body feelings coded in SS2 minicolumns and

in axis circuits of minicolumns that code ongoing visual and

auditory impressions.

4.3. The continuity of successive conscious impressions

Considered as a unit of the impressions that constitute

consciousness, axis circuit activity can occur in many

minicolumns simultaneously, as is the case in primary sensory

areas where inputs from sensory receptors register manydetails of a scene in parallel. However, in higher sensory

areas, attentional processes typically operate to select parts

of the registered scene, by elevating the axis circuit activity

in minicolumns, which will continue at this higher level

of intensity as long as frontal attentional control sites send

activation to the thalamic neurons of these axis circuits. The

elevated activity in these axis circuits does not abruptly return to

baseline when attentional control is shifted to another part of the

sensory scene, but instead the activity decays gradually toward

baseline. Attentional effects observed in the primary visual area

apparently exhibit this overlap of activity at the destination

and origin sites of attentional shifts (Khayat, Spekreijse, &Roelfsema, 2006). This overlap of minicolumn axis activity

during shifts of attention produces continuity in the succession

of impressions that would not exist if each axis circuit shuts

down immediately when attentional activation is shifted away

from it. If attentional control induces relatively high levels

of intensity in a particular minicolumn (or a column cluster

of minicolumns), then the course of the decay process may

be sufficiently long that some elevated activity remains after

attention has shifted to another minicolumn and then returned

to the original minicolumn. This is the prediction derived and

tested for the case of shifting visual attention between spatial

locations (LaBerge, Carlson, Williams, & Bunney, 1997).

The continuity of successive impressions commonlyobserved during shifts of attention across visual, auditory and

tactual scenes contrasts with the discontinuities of successive

identifications of objects (attended or unattended) during

these shifts of attention. Units of processing are distinct and

separated, owing largely to their typically short durations

and their abrupt terminations when an output occurs. When

identifications evoke categories and ideas further along in the

shell global pathway, there may be overlap between ideas when

they are stored in working memory circuits. But, if working

memory circuits are exclusively shell-based, there will be no

impressions generated. But even if the working memory circuits

contained an axis component, the intensity of apical dendrite

activity within that axis circuit would seem to be of low

intensity so that it would be easily obscured by the typically

high intensities in axis circuits of sensory areas in the posterior

cortex.

Therefore, the appreciable duration of the “passing moment”

implies that axis activity is providing the principal neural

substrate, while the vanishingly small duration of the “presentmoment” implies that shell activity is providing the principal

neural substrate. Stated in another way suggested by the present

theory, the passing moment is an impression of which we are

conscious, and the present moment is a concept which we

process as an idea.

4.4. Interactions between axis and shell circuit activities

A cognitively important relationship between having an

impression of an object and having an idea about an object is

embodied in the connective links between the shell circuit and

the axis circuit within a minicolumn. The main links between

the axis circuit and the shell circuits are shown in Figs. 4 and 5.Thalamocortical axons from the thalamic matrix neurons send

collateral axons to the apical dendrites of layer 2/3 pyramidal

neurons, so that activity in the axis circuit produces and

maintains activity in the layer 2/3 apical dendrites. Therefore,

when minicolumns of higher sensory areas exhibit attentional

activity, the elevated activity in the axis circuits of layer 5

pyramids induces EPSPs in the layer 2/3 apical dendrites.

However, the amplitudes at the soma of layer 2/3 pyramids

of these EPSPs are assumed to remain below threshold firing

levels, so that the axons do not exhibit significant rates of

output pulses. For example, while a driver waits for a traffic

light to change from red to green and wishes to move quicklyahead at the onset of the green light, the driver may direct

preparatory attention to the location and color of the green

light during the time interval leading up to the appearance of

the green light. During this preparatory interval, the level of

attention corresponding to the amplitude of layer 2/3 apical

dendrite activity is elevated at the soma, but not to the level

that will produce axon output. When the green light appears,

axonal pulses from V1 minicolumns coding the location and

color of the green light produce EPSPs in the basal dendrites of

these layer 2/3 pyramids, which sum with the existing level of

activity in the soma and produce axon outputs. Fig. 9 shows two

diagrams of a layer 2/3 pyramidal neuron, one showing activity

in the apical dendrite (received from the layer 5 axis circuit),and the other showing no activity in the apical dendrite. When

axons from area V1 produce EPSPs in the basal dendrites of

these layer 2/3 pyramidal neurons, the pyramidal neuron with

the attentionally induced higher tonic activity at the soma will

emit a train of output pulses in the axon sooner than the other

pyramid, which represents a state of no preparatory attention.

In addition to a shortening of the output latency, the tonic soma

activation by the apical dendrite will increase the rate of pulses

in the output, so that, in effect, the signal-to-noise level of the

input pulses received at the basal dendrite is increased.

But if the level of apical dendrite activity delivered to

the soma of the layer 2/3 pyramid momentarily drifts above




Fig. 9. Apical dendrite activity modulates input–output processing in layer 2/3

pyramidal neurons. Here, the same train of input pulses contacts the basal

dendrites of both neurons, but the sustained elevated apical dendrite activity

in the neuron on the left increases excitability of the soma, so that fewer input

pulses are needed to produce an output pulse.

firing threshold, then axon output will occur, which typically

produces false positive responses, called “jumping the gun”.

Therefore, to produce axon outputs to the onset of the green

light with short latency and without momentary fluctuationsof apical dendrite activity at the soma that produce false

positive outputs, the mean level of apical dendrite activity

delivered to the soma must be elevated as close to the firing

threshold as the variability of the EPSP will allow. Thus, an

observer cannot effectively reduce the time to process the green

light (in the attention-based higher sensory area) simply by

increasing the amplitude of the EPSP delivered to the layer 2/3

apical dendrites unless the lengths of the apical dendrites are

sufficiently long to reduce the variability of the larger EPSP by

the time it reaches the soma. With training, one might expect the

lengths of the apical dendrites to lengthen, so the modulatory

activity delivered to the soma could be raised to progressively

higher levels while maintaining the steady stability of low EPSP

variability.

There are additional benefits for tasks of sustained attention

that are produced by high but steady activity in the apical

dendrites of layer 5 and layer 2/3 pyramids. These pyramids

send collaterals of their axons to neighboring columns, where

they synapse on inhibitory neurons that contact pyramids

and lower their responsiveness. Also, axis circuits that serve

neighboring columns inhibit each other in the thalamus by

their synapses on inhibitory neurons of the thalamic reticular

nucleus (Jones, 2007). When the activity levels of axis circuits

of a column cluster of minicolumns are elevated, the activity

in neighboring columns that code for potential distractingsignals is concurrently suppressed. When this state of affairs

is extended over durations of time, as in anticipation of

an upcoming green light, or in imaging the arrangement of

furniture in a familiar room, or activating a plan of action,

there is less likelihood that the onsets of distracting stimuli

will perturb the ongoing axis activity that supports preparatory

attention, imaging, and planning. Thus, high amplitudes of axis

activity can protect axis circuit activity from interference by

distracting events, much as increased rates of axon outputs can

increase the signal-to-noise ratio in input–output processing

and protect the output information from interference by ambient

noise.

As a general cognitive principle, shell circuit activity enables

the identification of the axis activity that is taking place in

the same minicolumn (or column cluster of minicolumns). The

attachment of a symbol or label to a stimulus input is based on

the process of identifying a stimulus input from the primary

sensory area and then categorizing it in successively higher

sensory areas. Thus, it could be said that the symbolizingprocess produces the basic materials for the construction

of ideas. But the symbolizing process does not capture the

subjective impression itself, because sustained axis activity

does not translate or transform into the shell activity by

input–output processing circuitry. However, the shell circuits

can respond to certain aspects of the axis activity in the

minicolumn they share. In many cases, shell processing will

occur or not occur according to the presence of axis activity,

so that an input to the shell circuit can act as a query about the

existence or non-existence of axis activity in that minicolumn

(see Fig. 9). A succession of these queries can therefore

provide a means of estimating the duration of axis activity

in a minicolumn or cluster of minicolumns. Also, since theintensity of axis activity affects the latency and strength of the

output signals in shell processing (described in the foregoing

example of anticipating a green traffic light), an input query to

the shell circuit provides a means of detecting the intensity of

axis activity in a minicolumn or cluster of minicolumns. Thus,

it could be said that the shell circuitry can have knowledge

about the duration and intensity of axis activity, but shell

circuitry does not have direct knowledge (e.g., knowledge

by acquaintance) of “what it is like” to have the impression

produced by an axis circuit. The sharp limitation of knowledge

about axis activity in a particular minicolumn appears to be

reflected in the manner in which the layer 2/3 pyramidalneurons are arranged around the outside of the apical dendrites

of the layer 5 pyramidal neurons. The etymological form of

the word “about”, prior to 900 A.D. was the word abutan,

which meant “on the outside of”. Thus, the shell circuits

may be viewed as exterior to the interior events of the axis

circuits and specialize in “aboutness”. The symbolic nature of

shell activity enables its outputs concerning this “aboutness”

to be communicated to others through language and gestures.

In contrast, the impressions of axis activity would seem to

constitute a subjective “inwardness” of the individual’s mental

life, and as such are not capable of being communicated to other

individuals. Furthermore, it could be said that the extended

duration of axis activity confers a concrete “existence” to

impressions compared to the specious existence of the fleeting

moments in which ideas are processed. In summary, the

distinctive structures of the axis and shell circuits within the

minicolumn appear to define two very different ways in which

the cerebral cortex responds to and constructs its knowledge of

the sensory inputs from objects of the external world.

4.5. The role of the self in consciousness

The global circuits connecting axis and shell circuits also

serve as a basis for distinguishing two selves, which, for

convenience, we label as the “thinking” self and the “feeling”




self. The thinking self is a product of ideas produced by shell

circuits. It includes items of personal history and verbalized

personal characteristics that arise from the way we interpret

our behaviors in social situations. Gazzanga’s theory of the

“Interpreter” (Turk, Heatherton, Macrae, Kelley, & Gazzaniga,

2003) provides an example of the self as “thought about”. In

contrast, the feeling self is based on the sustained impressionsof the body’s landscape, whose intensities can be modulated

by the emotional activities of the body. The present notions

concerning the relationship of the feeling self to ongoing

emotional events in the internal organs are influenced by the

work of Damasio (1994). By analogy with descriptions of

activities in early cortical areas of vision, audition, and touch,

we conjecture that the ongoing inputs from the internal organs

and external bodily surfaces are registered as impressions in

axis circuits of somatosensory area S1 and selectively attended

in axis circuits of area S2.

The continuing inputs from our body provide impressions

that constitute background consciousness of our bodily feeling.

This ongoing feeling of our body provides the primitive senseof presence, which then can be attributed to objects of the world

that we imagine our body can touch. Thus, when the sustained

bodily impressions are paired in a coordinated manner with

the sustained impressions of objects seen, heard, and especially

touched, these objects also become present to us. Together with

the impression of the presence of the body, the impressions

of the presence of these objects provide our ongoing sense of

presence of ourselves in the world. For example, as we walk

along a path and approach a large tree, we seem to attend more

and more strongly to our body as well as to the tree. As we close

the distance between our body and the tree the impressions of

both body and tree seem to intensify, and this intensity peaksif a part of our body actually touches the tree. These sustained

impressions of the tree and our bodily self are likely to become

very intense if the tree we approach is a giant redwood.

A conductor of an orchestra can experience a similar

impression of the presence of both the self and an external

object, but in this case the looming object is the overall

orchestral sound as the conductor gradually directs a crescendo

from the level of a pianissimo to the level of fortissimo. In a

similar way, the sounds of music or the sounds of voices at a

cocktail party in the hotel room down the hall seem to require

a minimal level of intensity to give the impression of their

presence, but the additional requirement is the relationship to

our current impression of our body. It would seem, therefore,

that it is the attention directed to our body while we attend

to a suitably intense impression of an external object that adds

the impression of presence to the consciousness of that object.

It has been suggested that the term “awareness” should be

reserved for such cases of elevated consciousness that arise

when attention is directed to the body at the same time as

attention is directed to an object (LaBerge, 1997).

In view of these considerations, the present theory

of consciousness does not require the self, considered

either as the felt-body based on axis activity or as an

intellectual construction based on shell activity, as a necessary

component of consciousness. High levels of visual or auditory

consciousness produced by attention can occlude the ongoing

background feelings of the body, so that we can apparently

“forget ourselves” when we are beholding a sunset, or when

we are listening to a favorite piece of music, or when we are

reading a novel. Thus, the body-based or body feeling-based

impression of the self is based on background consciousness of

the current state of the body. As such, this consciousness maybe regarded as another kind of sensory-based consciousness,

with registration of ongoing bodily feelings taking place in the

primary somatosensory area, S1. Foreground consciousness of

a bodily feeling, then, is the elevated intensity of an axis circuit

coding an attentionally selected part of this registered array of

feelings in minicolumns of the higher sensory area S2.

5. Consciousness and the electromagnetic fields of apical

dendrites

The present paper proposes that sustained activity in the axis

circuit of minicolumns is a necessary condition for producing

and maintaining consciousness in the brain. The specific partof the axis circuit that underlies the subjective aspect of

conscious impressions is the electromagnetic activity of the

apical dendrite, according the present theory. In this final

section of the paper we examine in some detail the properties of

the electromagnetic activity of the apical dendrite to determine

what properties of conscious impressions they may underlie.

In particular, do the properties of electromagnetic activity of

the apical dendrite correspond to the properties of extended

duration and variations in intensity that we have attributed to

conscious impressions?

The electrical nature of the propagating EPSP in the

apical dendrite contrasts sharply with the electrical nature of the propagating action potential in the myelinated and un-

myelinated axon in several important and related respects.

Firstly, the initiating current and voltage of the apical dendrite

EPSP can vary considerably in amplitude while the current

and voltage characteristics of the action potential are virtually

constant (and relatively low) in a given axon. Secondly,

the EPSP of the apical dendrite decays substantially as it

propagates toward the soma, while the action potential decays

only very slightly within the inter-nodal segment of the

myelinated axon, except for the highest frequency components

of the Fourier spectrum of the action potential, which affect the

pulse rise-time only. Thirdly, owing to the clustering of several

apical dendrites aligned in parallel there is a strengtheningof the overall electric dipole effect, whereas sites of action

potentials are not consistently aligned within nerve bundles

of axons. We note that the superposition of electrical fields

from many parallel and closely spaced electric dipoles with

codirectional currents produces a local enhancement of the

electric fields in an axial direction along the inner and outer

surface of the apical dendrite membrane. This superposition

of fields concentrates the electromagnetic energy within the

cluster volume, so that the total field energy (inside and

outside the membrane) undergoes a gain that would not occur

in unclustered, well-separated apical dendrites. This gain or

enhancement in localized energy (or power) increases as the




Fig. 10. (Above) The decay in voltage, V , of an EPSP mass of charge shown at

three locations along the apical dendrite shaft as the EPSP mass propagates

toward the soma. (Below) At each of the three EPSP locations there is an

(appropriately small) electric dipole accompanied by its electromagnetic field.

square of the sum of the field amplitudes of individual apical

dendrites.To promote an understanding of how these fields could

relate closely to consciousness we describe the electromagnetic

characteristics of the transient fields in the extracellular region

produced by the propagating EPSP in the apical dendrite.

Because the present theory assumes that the time-dependent

charges decay as they propagate along the apical dendrite (seeFig. 6) we partition the apical dendrite into a collinear spatial

array of electric dipoles at any given instant of time. Each dipole

is a source of electromagnetic wave energy in the form of a

transient pulse of both localized electric field and magnetic

field energy (density) that radiates into the extracellular space

(see Fig. 10). Each electric dipole along the apical dendrite

shaft is derived from the time- and space-dependent current

of the moving EPSP waveform multiplied by an appropriately

chosen short length, d z, of the apical dendrite. These dynamic

dipoles are characterized by both magnetic and electric fields,

and their dipole moments depend on three variables: the charge

at the two poles, the velocity of the charges, and the distance

between them. When these component dipoles are superposed

they produce the overall dipole effect of the apical dendrite

activity.The time-dependent EPSP current at any given segment, d z,

along the dendrite is the excitation source of the dipole. The

pulse shape of the radiation field from this dipole is preserved

as it propagates away from the dendrite at a decreasing velocity.

This preservation of pulse shape results from the dominance

of conduction currents over Maxwellian displacement currents

in the extracellular medium (approximating that of seawater),

and from the low frequency characteristic of EPSPs. As

a consequence, the propagation of a radiating pulse may

be described by a low-frequency window (LFW), following

the analysis presented by Burrell and Peters (1979). When

propagation is in the LFW, as is the case for the EPSP or

action potentials, the extracellular pulse will propagate with

little distortion. The theoretical behavior of the transient pulse

or electromagnetic field propagation from an electrically small

electric dipole source is well-known for such lossy material as

extracellular fluids, and has been rigorously developed by Songand Chen (1993). For the known frequency content of EPSPs

and action potentials, the electric and magnetic field time

dependence at any localized point in the extracellular region

is identical to the spatially localized current time waveform

of the internal EPSP. Thus, for EPSP propagation along the

apical dendrite we can make the simplifying assumption that

the electric and magnetic fields in the extracellular medium

preserve the current waveform exhibited by the EPSP inside

the dendrite with little distortion.

Therefore, the attenuation of the extracellular electromag-

netic pulse depends only on the cube of the radial distance

from the apical dendrite and simple angular variables within

the LFW. We employ here a spherical coordinate system to de-scribe the field structure of the EPSP pulse, shown in Fig. 11.

Two electric field components (radial and tangential) and one

magnetic field component (circumferential) describe the total

instantaneous field at any point outside the apical dendrite. The

diagram shown in Fig. 11 describes the spatial distribution of

the electric field at a point in time for one current dipole, while

the magnetic field component is always circumferential about

the axis of the current dipole. The angular dependence of each

component specifies that at right angles to the axis of the api-

cal dendrite the tangential component of the electric field that is

parallel (or approximately parallel) to the dendrite is the dom-

inant electric field component. This parallel component willexhibit strong electrical coupling to a neighboring dendrite lo-

cated within several diameters of the dendrite (a typical apical

dendrite diameter is approximately 2 microns, and 6–8 apical

dendrite shafts lie within an area of approximately 12 × 12 mi-

crons (Peters & Sethares, 1991, Fig. 5)).

The equations that describe the near electric and magnetic

fields produced by the velocity-dependent dipole of the apical

dendrite are as follows.

E θ = ( I d z/4πσ r 3) sin θ, (1)

E r = ( I d z/2πσ r 3) cos θ, (2)

H φ = ( I d z/4πr

2

) sin θ, (3)ν ∼ 1/σµ0r , (4)

where E θ and E r are components of the electric field, H φ is

the magnetic field, ν is the field propagation velocity, I is the

current, d z is an appropriately small dipole length, r is the radial

distance from the dipole, θ is the angle defined by the radial

direction and the dipole axis, σ is the electrical conductivity

of the medium, and µ0 is the magnetic permeability of the

medium.Near the axis of the apical dendrite, the radial component

that points in the axial direction of EPSP propagation is the

dominant electric field component. Inside the apical dendrite

this axially directed component is at its strongest level, where




Fig. 11. Detailed diagram (in a spherical coordinate system) of the radiating

electromagnetic field from an EPSP mass of charges at a particular location as

it moves along the apical dendrite. At a given point in space the electric field

intensity is E and the magnetic field intensity is H φ . The radial electric field

component, E r is highest in the interior of the dendritic shaft, and it decays very

rapidly in the radial direction as 1/r 3. For clarity, the circumferential magnetic

field distribution has been omitted from the diagram.

it is closest to the EPSP current flow mechanism. Eq. (4)

indicates that the electromagnetic pulse emitted by the dipole

propagates away from the apical dendrite at a velocity, ν, which

is proportional to the inverse product of radial distance andelectrical conductivity. In effect, the velocity of propagation is

close to the speed of light at the outer surface of the dendrite and

quickly decays with radial distance r to values several orders of

magnitude lower than the speed of light at distances beyond

about a millimeter, according to theoretical predictions. The

velocity decays as 1/r for a constant conductivity and magnetic

permeability.

The relationship between the EPSP voltage waveform and

current waveform can be derived from classical cable theory

using the well-known concept of wave impedance or cable

characteristic impedance. Figs. 10 and 11 contain examples

of EPSP voltage waveforms described as Gaussian pulse

shapes. The exact time dependence of the electromagnetic fieldpulse at a point in the extracellular fluid will depend on the

conductivity, dielectric properties, and thickness of the surface

layer of the apical dendrite. Clusters of apical dendrites in close

proximity therefore will develop electric field energy in their

core structures from the combined electric field components

parallel to the dendritic axes. The development of magnetic

field energy between parallel electric field dipoles is much less

significant compared to electric field energy coupling between

pairs of parallel apical dendrites with internal collinear dipoles

moving at the conduction velocity. According to the present

theory, it is this electromagnetic field intensity that underlies

our immediate conscious impressions.

6. Other ways of producing consciousness

This paper makes the strong claim that the physical correlate

of consciousness is the near electromagnetic field (see Eqs.

(1)–(3)) located along the surface of the neural membrane.

This field contains the “energy of consciousness” that has

the ability to do work on other electric charges and therebyinfluence other neural events (e.g., by modulation effects at the

soma); or it can simply be the state of “being conscious” of

the particular content coded by the apical dendrite (e.g., the

color red). Thus, a major physical property of the field

activity is the intensity of energy, which corresponds to

the cognitive property of intensifying a sensory impression

(e.g., concentrating attention more strongly to the redness of an

apple). Level of intensity determines what content dominates

consciousness, so that low intensity levels of active apical

dendrites in many areas of the brain (e.g., apical dendrites

that code for the ongoing impression of pressure of the feet

on the floor) will normally not be experienced as part of the

momentary content of consciousness. While the long apicaldendrite seems well-suited to provide variations in intensity and

other properties of consciousness (e.g., extendable duration),

we cannot rule out the possibility that other structures, organic

or inorganic, could also produce electric fields with these kinds

of properties. For example, action potentials in stable circuit

loops produce extended durations of electric field oscillations;

an example is the high spectral fields produced by spikes at the

axon initial segment of layer 5 pyramidal neurons within the

corticothalamic circuit loop. Since action potentials fire with

a constant voltage, variations in intensity would be based on

the number of participating axons in the near neighborhood;

however, action potentials at nodes of myelinated axons are notlikely to produce large summation of fields because the nodes

do not line up in close neighborhoods across axon clusters.

Another, more global, view combines the fields of all axons,

dendrites, and somas in subcortical and cortical regions of the

brain into one complex electromagnetic field, and regards this

total brain field as the basis of consciousness (McFadden, 2002;

Pockett, 2000). Finally, the electromagnetic fields produced by

inorganic structures such as wire antennas could, in principle,

serve as the basis of artificial consciousness, but it may

be somewhat difficult to infer the properties of conscious

activity in these structures without additional circuitry (e.g., for

accessing and identification) which the normal human brain

provides.

7. Tentative conclusions

In cortical circuits that operate by input–output processing,

the strengths of electrical signals typically are at relatively low

levels. In comparison, the electrical activity in apical dendrites

normally operates at relatively high levels, as suggested by

the stronger demands upon blood flow of local field potentials

compared to that of the multi-unit activity of action potentials

(Logothetis, Pauls, Augath, Trinath, & Oeltermann, 2001).

Also, EEG recordings, which are driven by electrical activity

of clusters of apical dendrites, can show exceptionally high




amplitudes during meditation (e.g., Lutz et al. (2004)). Given

the level of electrical currents/voltage in an individual apical

dendrite, close clustering of apical dendrites increases the

concentration of field energies as the square of the number

of active apical dendrites within the cluster. Owing to the

length of the apical dendrites, these high levels of electrical

activity will be attenuated before they reach their somas,where they can modulate the input–output activity in circuits

that process signals. Thus, the extended length of the apical

dendrite provides one way to separate the pocket of intense

electrical activity in moderately distal sectors of the apical

dendrite from the input–output processing at the soma. These

pockets of intense electrical activity in the apical dendrite are

also separated from neighboring circuits in the intercellular

medium by the restriction of their high field strengths to small

regions very near the surface of the apical dendrite, because

the near electric field intensity falls off as 1/r 3, where r

is the radial distance from a point in the apical dendrite. It

would seem, therefore, that these small, relatively isolated

regions in the apical dendrites are able to increase their electricfield intensity to a relatively high level, and sustain it there

for extended durations without perturbing the input–output

electrical activities of neurons in neighboring circuits.

Therefore the following question arises: What function is

served by high electric field intensities and their extended

durations in apical dendrites? We have suggested that high

field intensities benefit input–output processing by their

stronger modulatory effects at the somas of pyramidal

neurons, with consequent increases in the strength of lateral

inhibitory connections that protect the axis circuit activity

from interference by neighboring minicolumn activity. But

these pockets of high electric field intensity are activated andsustained even when they are not modulating input–output

processing, for example, when we are attending to sunsets,

music, and other pleasurable activities. These localized high

electric field intensities may serve to raise our raw impressions

of the world to the level of consciousness, and thereby provide

our mental life with its special kind of existence.

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