Symbolic Modeling of Asynchronous Neural Dynamics Reveals Potential Synchronous Roots for the Emergence of Awareness - Bonzon, Pierre (Frontiers in Computational Neuroscience, 2019)
A new computational frameworkz implementing asynchronous neural dynamics is used to address the duality between synchronous vs. asynchronous processes, and their possible relation to conscious vs. unconscious behaviors. Extending previous results on modeling the first three levels of animal awareness, this formalism is used here to produce execution traces of the parallel threads that implement these models. Running simulations demonstrate how sensory stimuli associated with a population of excitatory neurons inhibit in turn other neural assemblies i.e., a kind of neuronal asynchronous wiring/unwiring process that is reflected in the progressive trimming of execution traces. Whereas reactive behaviors relying on configural learning produce vanishing traces, the learning of a rule and its later application produce persistent traces revealing potential synchronous roots of animal awareness. In contrast to previous formalisms that use analytical and statistical methods to search for existing patterns in a functioning brain, this new framework, which is constrained solely by a symbolic model of synaptic plasticity, proposes a tool for shaping the brain by linking perception to behavior through a mechanism of hebbian learning.