Abstract

Pilot clinical trials of human patients implanted with devices that can chronically record and stimulate ensembles of hundreds to thousands of individual neurons offer the possibility of expanding the substrate of cognition. Parallel trains of firing rate activity can be delivered in real-time to an array of intermediate external modules that in turn can trigger parallel trains of stimulation back into the brain. These modules may be built in software, VLSI firmware, or biological tissue as in vitro culture preparations or in vivo ectopic construct organoids. Arrays of modules can be constructed as early stage whole brain emulators, following canonical intra- and inter-regional circuits. By using machine learning algorithms and classic tasks known to activate quasi-orthogonal functional connectivity patterns, bedside testing can rapidly identify ensemble tuning properties and in turn cycle through a sequence of external module architectures to explore which can causatively alter perception and behavior. Whole brain emulation both (1) serves to augment human neural function, compensating for disease and injury as an auxiliary parallel system, and (2) has its independent operation bootstrapped by a human-in-the-loop to identify optimal micro- and macro-architectures, update synaptic weights, and entrain behaviors. In this manner, closed-loop brain-computer interface pilot clinical trials can advance strong artificial intelligence development and forge new therapies to restore independence in children and adults with neurological conditions.

Highlights

  • Connecting the Brain to Itself through an EmulationReviewed by: Karen Moxon, University of California, Davis, United States Kevin J

  • Large-scale neural models primarily seek to identify the operating principles of the mammalian brain

  • The development of novel multi-electrode, optical fiber and biological construct sensor-actuator technologies could allow for the ability to record and stimulate tens of thousands of individual neurons in the human brain across a lifetime

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Summary

Connecting the Brain to Itself through an Emulation

Reviewed by: Karen Moxon, University of California, Davis, United States Kevin J. By using machine learning algorithms and classic tasks known to activate quasi-orthogonal functional connectivity patterns, bedside testing can rapidly identify ensemble tuning properties and in turn cycle through a sequence of external module architectures to explore which can causatively alter perception and behavior. Whole brain emulation both (1) serves to augment human neural function, compensating for disease and injury as an auxiliary parallel system, and (2) has its independent operation bootstrapped by a human-in-the-loop to identify optimal micro- and macro-architectures, update synaptic weights, and entrain behaviors.

INTRODUCTION
THE BRAIN TO EMULATIONS
Data types
SUBSTRATES FOR WHOLE BRAIN EMULATION
CONNECTING THE BRAIN TO ITSELF THROUGH AN EMULATION
EMULATION TO EACH OTHER
EMULATION ARCHITECTURE
CALIBRATION AND CONVERGENCE
AIMING THE ATTENTIONAL SPOTLIGHT ACROSS MORE THAN ONE BRAIN
STRONG ARTIFICIAL INTELLIGENCE
BEYOND A SINGLE EMULATION
SUMMARY
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