The Future of Brain-Powered LearningIn the year 2050

Elvis Saravia, 104065891

Brain-Machine Interfaces (BMI) in Science Fiction

BMI in the real world

Brain-Machine Interfaces (BMI) allows for bidirectional communication between brain and external devices.

Signal Acquisition

Pattern Recognition Transformation

BMI Application

Commands

BMI device

Types of BMI (non-invasive)Electroencephalography (EEG)

Tracks neural activity (electrical impulses)

Functional Magnetic Resonance Imaging (fMRI)

Tracks neural activity (blood flow)

Source: Wikimedia Commons

Types of BMI (invasive)Brain chip is implanted directly in an area that can monitor neural activity in the brain, i.e., usually underneath the skull.

In vivo Multielectrode arrays (MEAs)

Electrocorticography (ECoG)

Source: Communications of the ACM, Vol. 54 No. 10, Pages 11-14

State-of-the-art BMI technology?

Miranda et al., 2015 (DARPA-funded Efforts in the Development of Novel Brain–Computer Interface Technologies)

Vieira et al., 2015 (Building an organic computing device with multiple interconnected brains)

Yin et al., 2016 (An automatic experimental apparatus to study arm reaching in New World monkeys)

Control prosthetic armBrain-to-brain communication

Monkey controls wheelchair by pure thoughts

Applications of BMI Medical - Treat Depression and Parkinson’s Disease

Entertainment - BMI games for rehabilitation (ADHD* patients)

Minkyu et al., 2014

* Attention deficit hyperactivity disorder (ADHD)

How about Education?

2050

BMI Learning Network (BLiNK)

BLiNKLearning Cloud

BLiNK brain chip

Learner A Learner B

Lecturer

Wirelessconnection

BCI Learning Network (BLiNK)

BLiNK enables brain-to-brain communication through high-bandwidth networks.● Wireless communication● Instant sharing of ideas and feedback (between learners and lecturers)● Perform instant search to knowledge databases via thoughts

BLiNK allows transfer (share) of: ● Knowledge, thoughts, experiences, dreams, memory, etc...

BLiNK services operate on the cloud?● Stores unlimited memory and information

BLiNK provides real-time analytics for learners● Can monitor learning patterns

Alice wants to learn Physics

Alice in Wonderland

Alice conditions for learning

● Learn quickly (she still wants to have time to go for an adventure)

● She is tidy, so she prefers clean and simplistic virtual classroom (Gestalt Theory)

● She has problem paying attention, so she prefers micro-courses

● She may need fast access to knowledge databases (priori knowledge), since science is not her major (Cognitivism)

● She wants real-world experience by running lab experiments, and she wants to engage with learners to share ideas (Constructivism)

● Monitor her learning progress and patterns● She forget things quickly so she want to improve

memorization.

Alice joins BLiNK (Symbiotic solution)

BLiNKPhysicsModule BLiNK Physics Module

● Personalized learning (adjust learning rate)● Simulated environment (Brain VR)● Communication with peers and lecturers● Instant access to knowledge databases● Download experiences● Real-time analytics● Stimulate brain to increase focus and

memory

● Learn quickly ● Simplistic virtual classroom (Gestalt)● Activation of prior knowledge Cognitivism)● Real-world experience (Constructivism)● Monitor her learning progress and patterns● Improve attention● Concept attainment (memory)

Pros and Cons of BLiNK?Strengths

Learner-centered

On-demand learning

Guided-learning (Personalization)

Fast communication and learning

Unlimited access (knowledge + experiences)

Unlimited memory (cloud + brain)

Weaknesses (mostly unethical)

Brain Hacking

Mind Control

Privacy issues

Health issues

Centralized (cloud) or Decentralized (p2p)

Needs regularization

ReferencesBCI learning - cognitive/motor skill learning using BMI: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4462099/

Intro to BMI: https://www.slideshare.net/udaysaikia/brain-computer-interfaces-by-uday-mc-gill

Neuralink (Elon Musk Company): https://waitbutwhy.com/2017/04/neuralink.html

A review of Brain-Computer Interface Games and an Opinion Survey from Researchers, Developers and User: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4178978/

Invasive vs. Non-Invasive Neuronal Signals for Brain-Machine Interfaces: Will One Prevail?: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4921501/pdf/fnins-10-00295.pdf

Leflore, Dorothy. "Theory supporting design guidelines for web-based instruction." Instructional and cognitive impacts of web-based education(2000): 102-117.

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