title: Causal network in a deafferented non-human primate brain.
abstract: De-afferented/efferented neural ensembles can undergo causal changes when interfaced to neuroprosthetic devices. These changes occur via recruitment or isolation of neurons, alterations in functional connectivity within the ensemble and/or changes in the role of neurons, i.e., excitatory/inhibitory. In this work, emergence of a causal network and changes in the dynamics are demonstrated for a deafferented brain region exposed to BMI (brain-machine interface) learning. The BMI was controlling a robot for reach-and-grasp behavior. And, the motor cortical regions used for the BMI were deafferented due to chronic amputation, and ensembles of neurons were decoded for velocity control of the multi-DOF robot. A generalized linear model-framework based Granger causality (GLM-GC) technique was used in estimating the ensemble connectivity. Model selection was based on the AIC (Akaike Information Criterion).
authors.forename: Karthikeyan
authors.initials: K
authors.lastname: Balasubramanian
authors.forename: Kazutaka
authors.initials: K
authors.lastname: Takahashi
authors.forename: Nicholas G
authors.initials: NG
authors.lastname: Hatsopoulos
mesh_terms: D000818:Animals; D001921:Brain / Q000502:physiology*; D062207:Brain-Computer Interfaces; D004867:Equipment Design; D018737:Hand Strength; D006801:Humans; D008253:Macaca mulatta; D009044:Motor Cortex / Q000502:physiology; D009046:Motor Neurons / Q000502:physiology*; D009415:Nerve Net / Q000502:physiology*; D012371:Robotics / Q000295:instrumentation