Cortical free association dynamics: distinct phases of a latching network

TL;DR

This paper models cortical dynamics using a Potts network to identify phases of latching behavior, revealing how adaptation and noise influence transitions between different activity states.

Contribution

It introduces a phase diagram for latching dynamics in a Potts network, combining simulations and analytical methods to understand cortical activity phases.

Findings

Latching behavior depends critically on local attractor strength w.

Phase boundaries between no latching, transient, and sustained latching are mapped.

Analytical phase diagram in the w-T plane explains different cortical activity regimes.

Abstract

A Potts associative memory network has been proposed as a simplified model of macroscopic cortical dynamics, in which each Potts unit stands for a patch of cortex, which can be activated in one of S local attractor states. The internal neuronal dynamics of the patch is not described by the model, rather it is subsumed into an effective description in terms of graded Potts units, with adaptation effects both specific to each attractor state and generic to the patch. If each unit, or patch, receives effective (tensor) connections from C other units, the network has been shown to be able to store a large number p of global patterns, or network attractors, each with a fraction a of the units active, where the critical load p_c scales roughly like p_c ~ (C S^2)/(a ln(1/a)) (if the patterns are randomly correlated). Interestingly, after retrieving an externally cued attractor, the network can continue jumping, or latching, from attractor to attractor, driven by adaptation effects. The occurrence and duration of latching dynamics is found through simulations to depend critically on the strength of local attractor states, expressed in the Potts model by a parameter w. Here we describe with simulations and then analytically the boundaries between distinct phases of no latching, of transient and sustained latching, deriving a phase diagram in the plane w-T, where T parametrizes thermal noise effects. Implications for real cortical dynamics are briefly reviewed in the conclusions.