An open, online course in neuronal data analysis for the practicing neuroscientist

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 DESCRIPTION (provided by applicant): Advances in technology for measuring neuronal activity at ever-larger scales and with increasing spatial and temporal resolution, concomitant with a decrease in costs of data storage, are driving a revolution in neuroscience. The era of "big data" is reflected in a number of major funding initiatives that have begun worldwide to support neuroscience research, and especially neuronal data collection. As a flood of neuronal data accumulates worldwide, a new challenge faces the global neuroscience community: how to make sense of these complex data to drive basic biological insight and to shed new light on neurological and neuropsychiatric disorders. This new, data-driven era of neuroscientific research demands that investigators master the fundamental methods in time series and image analysis and know when and how to appropriately apply these methods, either in custom applications or in existing software packages. Accessible - yet rigorous - resources to develop hands-on experience with modern data analysis techniques are lacking in neuroscience. To address directly this current and growing worldwide challenge, we propose to develop an innovative open online course (or "OOC"). To reach the largest target audiences - the biologists, psychologists, and clinicians immersed in neuronal data - we will assume only a basic mathematics background and limited familiarity with computer programming, common to those trained in biological sciences. The proposed OOC will target investigators at all career levels - spanning from the beginning undergraduate researcher to the established PI - to analyze and understand neuronal data. Through an interdisciplinary case-study approach, we will use real-world neurophysiological data (including data available from large, emerging public repositories) to motivate the study of modern quantitative analysis methods. The OOC will comprise 15 independent modules. The first two modules will emphasize programming in MATLAB for neuroscientists and computational techniques relevant for large datasets. Each additional module will focus on one category of neuroscience case-study data, and will consist of multimedia material combining video lectures, MATLAB-based examples, and quantitative assessments. The modular format will provide multiple coherent learning paths through the online content, and thereby allow personalized learning for individuals with varying quantitative backgrounds and research interests. The OOC format will also permit the developed resources to be widely available, disseminated, and discoverable. The proposed OOC will prepare researchers with the fundamental skills required for the analysis of neuronal "big data", and elevate the general competencies in data usage and analysis across the research workforce.