Neural Population Computing – Stephen E. Nadeau

Abstract:

Introduction: Introduction to the principles of parallel distributed processing (PDP) and their power in explaining mechanisms underlying cognitive processes.

Materials and Methods: Analytic review of the PDP and cognitive science literature.

Results and Discussion: This talk will review the basic principles of PDP. Representations in the brain are encoded as patterns of activity of large populations of neurons. The science of population encoded representations — PDP — defines cerebral processes in terms of settling within constellations of attractor basins and eventually into constellations of attractor states, thereby achieving parallel constraint satisfaction. It achieves neurological verisimilitude and has been able to account for a large number of cognitive phenomena in normal people, including stimulus recognition, the effects of stimulus salience, top-down/bottom-up processing, the effect of statistical regularities of experience, frequency, and age of acquisition, instantiation of rules and symbols, content addressable memory and the capacity for pattern completion, preservation of function in the face of noisy or distorted input, and inference. It has made major contributions to our understanding of normal spoken and written language processing; patterns of language impairment in damaged brains in many very different languages; reactive and volitional attention (including hemi-spatial neglect); executive function; episodic and declarative memory; motor planning; visual processing; Piagetian stages of development; and neuroeconomics.

Conclusions: This work provides a mechanistic account for a host of well-studied cognitive phenomena in terms of processes plausibly involving actual neurons.

Key words: attention, cognitive function, executive function, knowledge, language, parallel distributed processing

References: 

S.E. Nadeau, “Neural population dynamics and cognitive function.” Front Hum Neurosci., vol 14, p50. Mar. 2020.