Ongoing spontaneous activity in the cerebral cortex exhibits complex spatiotemporal patterns in the absence of sensory stimuli. To elucidate the nature of this ongoing activity, we present a theoretical treatment of two contrasting scenarios of cortical dynamics: (1) fluctuations about a single background state and (2) wandering among multiple “attractor” states, which encode a single or several stimulus features. Studying simplified network rate models of the primary visual cortex (V1), we show that the single state scenario is characterized by fast and high-dimensional Gaussian-like fluctuations, whereas in the multiple state scenario the fluctuations are slow, low dimensional, and highly non-Gaussian. Studying a more realistic model that incorporates correlations in the feedforward input, spatially restricted cortical interactions, and an experimentally derived layout of pinwheels, we show that recent optical-imaging data of ongoing activity in V1 are consistent with the presence of either a single background state or multiple attractor states encoding many features.
Model Type: Connectionist Network
Model Concept(s): Spatio-temporal Activity Patterns; Rate-coding model neurons; Olfaction
Simulation Environment: XPPAUT
Implementer(s): Goldberg, Joshua [JoshG at ekmd.huji.ac.il]
References:
Goldberg JA, Rokni U, Sompolinsky H. (2004). Patterns of ongoing activity and the functional architecture of the primary visual cortex. Neuron. 42 [PubMed]