Cortical networks are shaped by the combined action of excitatory and inhibitory interactions. We elucidate a general noise-induced effect that we call “Jensen’s force” –stemming from the combined effect of excitation/inhibition balance and network sparsity– which is responsible for generating a phase of self-sustained low activity in excitation-inhibition networks. The uncovered phase reproduces all key empirically-observed features of cortical networks in the so-called asynchronous state, characterized by low, un-correlated and highly-irregular activity. Through a parsimonious model we resolve a number of long-standing issues, such as proving that activity can be arbitrarily low, but still self-sustained even in the complete absence of external stimuli or driving. This approach opens new avenues for theoretical and conceptual understanding of the phases and phase transitions of actual neural networks, from a broad statistical-mechanics perspective, with the aim to elucidate how the cortex processes information and computes.
Conferenciante: Pablo Villegas Góngora. Departamento de Electromagnetismo y Física de la Materia. Universidad de Granada
Fecha/Hora: Jueves 29 de Noviembre, 12:00h.
Lugar: Aula de Informática (F6). Departamento de Física de la Materia. Facultad de Ciencias.
