Understanding cortical dynamics requires dealing with nonlinearities, including those induced by local attractors. Attractors are configurations towards which neural activity tends to converge and represent long-term memories. In the cortex they are thought to drive dynamics both at the local level and globally.
Using a Potts neural network as a drastically simplified, effective model of the cortex, a SISSA study just published in Physical Review X Life has investigated the significance of established but long overlooked anatomical measures which suggest stronger attractors in the frontal cortex. A disordered Potts model was considered, with a ‘frontal’ and a ‘posterior’ half: the frontal Potts units have more active states than posterior ones. This model shows glassy behavior and generally slow dynamics.
As authors Kwang Il Ryom and Alessandro Treves have observed, there is an unexpected twist, though. “While in a homogeneous Potts glass network the more the active states per unit are, the slower the dynamics tend to be, in our ‘hybrid’ network posterior units are slowed down and anterior units are sped up, to the point of overtaking the former. The last become the first. This is a speed inversion effect which, as far as we are aware, has not yet been reported in glassy systems.” The inversion appears to be a robust phenomenon likely relevant for the formation of cortical memories, which have been hypothesized to be established in a glassy regime. “Combined with another study just submitted for publication, the speed inversion effect helps understand the mechanisms enabling the frontal cortex to rapidly orchestrate the dynamics of posterior cortical areas and, ultimately, the dysfunctions observed in frontally lesioned patients, when the ‘conductor’ tends to fail,” the two authors conclude.
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