title: Spontaneous and driven cortical activity: implications for computation.
abstract: The traditional view of spontaneous neural activity as 'noise' has been challenged by recent findings suggesting that: (a) spontaneous activity in cortical populations is highly structured in both space and time, (b) the spatio-temporal structure of spontaneous activity is linked to the underlying connectivity of the cortical network, (c) spontaneous cortical activity interacts with external stimulation to generate responses to the individual presentations of a stimulus, (d) network connectivity is shaped in part by the statistics of natural signals and (e) ongoing cortical activity represents a continuous top-down prediction/expectation signal that interacts with incoming input to generate an updated representation of the world. These results can be integrated to provide a new framework for the study of cortical computation.
authors: Department of Neurobiology and Psychology, Jules Stein Eye Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095-1563, USA. dario@ucla.edu
authors: Dario L
authors: DL
authors: Ringach
mesh_terms: D000818:Animals; D002540:Cerebral Cortex / Q000502:physiology*; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*; D010775:Photic Stimulation; D014796:Visual Perception / Q000502:physiology