OpportunityTitle: Temporal Dynamics of Neurophysiological Patterns as Potential Targets for Treating Cognitive Deficits  in Brain Disorders (R01)
AdditionalInformationOnEligibility: Other Eligible Applicants include the following:  Alaska Native and Native Hawaiian Serving Institutions; Asian American Native American Pacific Islander Serving Institutions (AANAPISISs); Eligible Agencies of the Federal Government; Faith-based or Community-based Organizations; Hispanic-serving Institutions; Historically Black Colleges and Universities (HBCUs); Indian/Native American Tribal Governments (Other than Federally Recognized); Regional Organizations; Tribally Controlled Colleges and Universities (TCCUs) ; U.S. Territory or Possession; Non-domestic (non-U.S.) Entities (Foreign Institutions) are not eligible to apply. Non-domestic (non-U.S.) components of U.S. Organizations are not eligible to apply.  Foreign components, as defined in the NIH Grants Policy Statement, are not allowed.
Description: A rich body of evidence suggests that cognitive processes are associated with particular patterns of neural activity. These data indicate that oscillatory rhythms, their co-modulation across frequency bands, spike-phase correlations, spike population dynamics, and other patterns might be useful drivers of therapeutic development for cognitive improvement in neuropsychiatric disorders. This initiative encourages applications to test whether modifying electrophysiological patterns during behavior can improve cognitive abilities. Applications should use experimental designs that incorporate active manipulations to address at least one, and ideally more, of the following topics: (1) in behaving animals, determine which parameters of neural coordination, when manipulated in isolation, improve particular aspects of cognition; (2) in animals or humans, determine how particular abnormalities at the cellular or molecular level, such as specific receptor dysfunction, affect the coordination of electrophysiological patterns during behavior; (3) determine whether in vivo, systems-level electrophysiological changes in behaving animals predict analogous electrophysiological and cognitive improvements in normal humans or clinical populations; and (4) use systems-level computational modeling to develop a principled understanding of the function and mechanisms by which oscillatory and other electrophysiological temporal dynamic patterns unfold across the brain (cortically and subcortically) to impact cognition.
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