Abstract
Action potential generation (spiking) in the neocortex is organized into repeating non-random patterns during both awake experiential states and non-engaged states ranging from inattention to sleep to anaesthesia—and even occur in slice preparations. Repeating patterns in a given population of neurons between states may imply a common means by which cortical networks can be engaged despite brain state changes, but super-imposed on this common firing is a variability that is both specific to ongoing inputs and can be re-shaped by experience. This similarity with specifically induced variance may allow for a range of processes including perception, memory consolidation and network homeostasis. Here, we review how patterned activity in neocortical populations has been studied and what it may imply for a cortex that must be both static and plastic.This article is part of the Theo Murphy meeting issue ‘Memory reactivation: replaying events past, present and future’.
Highlights
Action potential generation is thought by neuroscientists to underlie perception and decision making during active behaviour (‘online’ state), but it is thought to underlie many other neural processes including memory consolidation and homeostasis during ‘offline’ brain states
During sharp wave-ripple event (SWR) events, as characterized by their local field potential (LFP) oscillations of approximately 150 Hz, neurons tend to fire at elevated rates and many groups have reported increased replay of the A0, B0, C0 temporal sequence compared to both prior to the ABC running experience and compared to reshuffled spiking data
This ability of experience to reshape offline activity in hippocampal networks has led to the idea that SWR-based replay may represent a critical mechanism for Hebbian memory consolidation
Summary
Action potential generation is thought by neuroscientists to underlie perception and decision making during active behaviour (‘online’ state), but it is thought to underlie many other neural processes including memory consolidation and homeostasis during ‘offline’ brain states. The brain is not ‘off’ during these inactive states as it generates action potentials, often in patterned sequences that may correspond to specific tasks and/or may reshape neural circuits via synaptic learning rules. This reshaping of neural circuits may define the brain activity, memory, larger cognition and actions of the organism into the future. We will explore the role of patterned activations in neocortical circuits
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