I study the dynamics of neural codes and learning in biologically plausible network models of spiking neurons to understand how memory stability can overcome the natural interference in distributed representations. Are neural oscillations a means for the brain to resolve interference by regulating types of learning? Is there an interdependence between the beneficial process of pattern matching and the evolved laminar circuitry of cortex? What role does sleep play in the oscillatory regulation of this circuitry and interference management? Constructing dynamical systems from current neurophysiological findings, I analyze their behavior computationally with MATLAB, Simulink, and KINNESS to theorize spiking neural architectures of cortex and resolve these questions.
Persistence and storage of activity patterns in spiking recurrent cortical networks: modulation of sigmoid signals by after-hyperpolarization currents and acetylcholine - See more at: http://journal.frontiersin.org/Journal/10.3389/fncom.2012.00042/full#st
Frontiers in Computational Neuroscience (2012) 6
After-hyperpolarization currents and acetylcholine control sigmoid transfer functions in a spiking cortical model.
Journal of computational neuroscience (2011) 1-28-28