Robust sequential working memory recall in heterogeneous cognitive networks

Abstract

Psychiatric disorders are often caused by partial heterogeneous disinhibition in cognitive networks, controlling sequential and spatial working memory (SWM). Such dynamic connectivity changes suggest that the normal relationship between the neuronal components within the network deteriorates. As a result, competitive network dynamics is qualitatively altered. This dynamics defines the robust recall of the sequential information from memory and, thus, the SWM capacity. To understand pathological and non-pathological bifurcations of the sequential memory dynamics, here we investigate the model of recurrent inhibitory-excitatory networks with heterogeneous inhibition. We consider the ensemble of units with all-to-all inhibitory connections, in which the connection strengths are monotonically distributed at some interval. Based on computer experiments and studying the Lyapunov exponents, we observed and analyzed the new phenomenon—clustered sequential dynamics. The results are interpreted in the context of the winnerless competition principle. Accordingly, clustered sequential dynamics is represented in the phase space of the model by two weakly interacting quasi-attractors. One of them is similar to the sequential heteroclinic chain—the regular image of SWM, while the other is a quasi-chaotic attractor. Coexistence of these quasi-attractors means that the recall of the normal information sequence is intermittently interrupted by episodes with chaotic dynamics. We indicate potential dynamic ways for augmenting damaged working memory and other cognitive functions.

Itinerancy between attractor states in neural systems

“…Similar state transitions can also arise in deterministic systems, either through chaos [55,56] in which case states have an oscillatory structure [57], or through heteroclinic sequences [58–61] in which case states are weakly unstable fixed points. When comparing these deterministic dynamical models with point-attractor state itinerancy, both the statistics of state-durations across trials and the dynamics of neural activity within a state should differ.…”

Hierarchical dynamics of informational patterns and decision-making

“…A similar concept was used to separate semantic network processes in people with disorders such as Asperger's syndrome, schizophrenia, and healthy people [68]. Such processes can also be theoretically analysed in the framework of the set of canonic models (2.1) that we proposed above (see also [69]). …”

Mathematics of Mind

“…Даже такое шаржированное описание дает представление о далеко идущих возможностях применения нелинейной динамики к описанию процесса творчества и сознания в целом. В дополнение к литературе, указанной на слайдах (см.References ), рекомендуем ознакомиться с недавними публикациями по данному направлению [29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48].…”