Multi-Input, Multi-Output Nonlinear Dynamic Modeling to Identify Biologically-Based Transformations as the “Cognitive Processes” Represented by the Ensemble Coding of Neuron Populations

The successful development of neural prostheses requires an understanding of the neurobiological bases of cognitive processes, i.e., how the collective activity of populations of neurons results in a higher-level process not predictable based on knowledge of the individual neurons and/or synapses alone. We have been studying and applying novel methods for representing nonlinear transformations of multiple spike train inputs (multiple time series of pulse train inputs) produced by synaptic and field interactions among multiple subclasses of neurons arrayed in multiple layers of incompletely connected units.