Rigorous Research Principles for Practicing Neuroscientists

PROJECT SUMMARY Advances in technology for measuring neural 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. As neural data accumulates worldwide, a new challenge faces the global neuroscience community: how to make sense of these complex data to drive biological insight and to shed new light on neurological and neuropsychiatric disorders. This new, data-driven era of neuroscientific research demands that investigators master rigorous research principles and know when and how to apply these principles. Accessible resources to develop hands-on experience with these rigorous research techniques are lacking in neuroscience. To address this current and growing challenge, we propose to develop educational units focused on specific principles of rigorous research. To reach the largest target audiences - the biologists, psychologists, and clinicians working directly with neural data - we will assume only a basic mathematics background and limited familiarity with computer programing, common to those trained in biological sciences. The proposed educational units will target investigators at all career levels - spanning from the beginning undergraduate researcher to the established PI - to understand and apply principles of rigorous research to neural data. Through an interdisciplinary case-study approach, we will use real-world data from neuroscience to motivate the study and application of rigorous research principles. To engage learners, we will develop multimedia material combining written text, short video lectures, and computer programming exercises, that promote hands-on learning of the material. 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 educational unit format will also permit the developed resources to be widely available, disseminated, and discoverable, and easily integrated into the CENTER framework. The proposed educational units will prepare researchers with the fundamental skills required for the analysis of neural data and elevate the general competencies in rigorous research principles across the research workforce.