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A Computational Model of Cortical Conditioning
Produced by a Bidirectional Brain-Machine Interface.
Nedialko I. Krouchev
Abstract
Experimental studies (Jackson et al, Nature 2006) reported that neural connectivity could be
changed through the interplay of an implanted bidirectional brain-machine interface (BMI) and
spike-time-dependent synaptic plasticity (STDP) in the primate cerebral cortex. They observed
electromyographic (EMG) activity and force-production changes in the hand muscles evoked
from the primary motor (M1) sub-populations, targeted by the BMI. Intra-cortical
microstimulation (ICMS) in the M1 region, associated with an agonist muscle led to conditioned
activation of the antagonist muscle. Changes were attributed to enhanced excitatory efficacy
across two distinct M1 sub-populations.
In our computational model, we reproduce closely the preparation and protocol features of the
above work. Our goal is to capture the gist of the neural dynamics and synaptic modifications.
To this purpose, we define sets of model neurons, assumed representative of the populations of
interest. Despite its low parameter count, the model captures essential aspects, such as plausible
conduction delays and STDP rules.
We address factors affecting STDP type and extent. To validate hypotheses, we conduct
numerical experiments matching those by Jackson et al. One such simulation reproduces in silico
the ICMS experiment, and predicts similar effects. The experimental results can be explained by
enhanced long-range excitatory connectivity as well as by suppressed local inhibitory synapses.
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