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The McKnight Endowment Fund for Neuroscience supports innovative research designed to bring science closer to the day when diseases of the brain can be accurately diagnosed, prevented, and treated. To that end, the McKnight Endowment Fund for Neuroscience invites Letters of Intent for its 2018 McKnight Technological Innovations in Neuroscience awards. The program encourages and supports scientists working on the development of novel and creative approaches to the understanding of brain function. McKnight is interested in how a new technology may be used to monitor, manipulate, analyze, or model brain function at any level, from the molecular to the entire organism. Technology may take any form, from biochemical tools to instruments to software and mathematical approaches. Because the program seeks to advance and enlarge the range of technologies available to the neurosciences, research based primarily on existing techniques will not be considered. A goal of the Technological Innovations awards is to foster collaboration between the neurosciences and other disciplines; therefore, collaborative and cross-disciplinary applications are explicitly invited.

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.

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.

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.

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.