Exploring the Inner Workings of Neuron Circuits That Exhibit Persistent Activity To Explain How Working Memory and Executive Function Are Implemented in The Brain
Abstract
In this research we explore in detail how a phenomenon called "sustained persistent activity" is achieved by circuits of interconnected neurons. Persistent activity is a phenomenon that has been extensively studied (Papoutsi et al. 2013; Kaminski et. al. 2017; McCormick et al. 2003; Rahman, and Berger, 2011). Persistent activity consists of neuron circuits whose spiking activity remains even after the initial stimuli are removed. Persistent activity has been found in the prefrontal cortex (PFC) and has been correlated to working memory and decision making (Clayton E. Curtis and Daeyeol Lee, 2010). We go beyond the explanation of how persistent activity happens and show how arrangements of those basic circuits encode and store data and are used to perform more elaborated tasks and computations. The purpose of the model we propose here is to describe the minimum number of neurons and their interconnections required to explain persistent activity and how this phenomenon is actually a fast storage mechanism required for implementing working memory, task processing and decision making.
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