Mechanisms of Persistent Activity in Cortical Circuits: Possible Neural Substrates for Working Memory

Abstract

A commonly observed neural correlate of working memory is firing that persists after the triggering stimulus disappears. Substantial effort has been devoted to understanding the many potential mechanisms that may underlie memory-associated persistent activity. These rely either on the intrinsic properties of individual neurons or on the connectivity within neural circuits to maintain the persistent activity. Nevertheless, it remains unclear which mechanisms are at play in the many brain areas involved in working memory. Herein, we first summarize the palette of different mechanisms that can generate persistent activity. We then discuss recent work that asks which mechanisms underlie persistent activity in different brain areas. Finally, we discuss future studies that might tackle this question further. Our goal is to bridge between the communities of researchers who study either single-neuron biophysical, or neural circuit, mechanisms that can generate the persistent activity that underlies working memory.

The neural representational geometry of social perception

“…In certain neural-network models and in the actual brain, neural-representational patterns operate as ‘attractors’, such that a neural system is attracted to complete those patterns when presented with a stimulus, allowing the system to descend from a high-energy state where the neuronal pattern is rapidly fluctuating to a lower-energy steady state in which the representational pattern comes to stabilize, i.e., an attractor state [7]. If the neuronal system’s state were imagined as a ball, the process of descending into an attractor state is analogous to a ball’s compulsion to roll down a hill, reflecting the increasing completion of the neural-representational pattern.…”

“…If the neuronal system’s state were imagined as a ball, the process of descending into an attractor state is analogous to a ball’s compulsion to roll down a hill, reflecting the increasing completion of the neural-representational pattern. Such attractor dynamics have long been observed in local populations of neurons in actual cortex, and serve as an intrinsic pattern-completion process allowing neuronal patterns to serve as stored representations [7]. …”

“…Just as a ball’s energy is higher at the top of a hill relative to resting on the ground, each point in neural state space has an associated energy level, which determines the trajectory of where the system will go. The system will gravitate toward energy minima, which are the stored representational patterns, i.e., attractor states [7]. If we were to project this 100-dimensional neural state space onto a more intuitive two-dimensional space, visualizing the energy levels at various points in the space, we can reveal these Angry and Happy category representations in the system (Fig.…”

Switching between persistent firing and depolarization block in individual rat CA1 pyramidal neurons

“…One of the adaptive functions that can be impacted by K + channel modulation in the hippocampus is mnemonic processing. Persistent firing is thought to support short‐term memory (Yoshida et al, ; Zylberberg & Strowbridge, ). Impaired short‐term memory in aged animals could be rescued by up‐regulating of the cholinergic drive (Disterhoft et al, ; Disterhoft & Oh, ; Oh, Power, Thompson, Moriearty, & Disterhoft, ).…”

“…We have selectively studied intrinsic properties of individual neurons. Nonetheless, network mechanisms constitute a crucial component in epileptic discharges (Caciagli, Bernhardt, Hong, Bernasconi, & Bernasconi, ; Phelan et al, ) and network activity is one of the possible mechanisms enabling PF (Zylberberg & Strowbridge, ). However, the network activity is conveyed by the concerted activity of individual neurons and the different levels reciprocally affect each other (Bikson, Hahn, Fox, & Jefferys, ; Schulz et al, ; Zheng, ).…”