Quantitative Neuroscience Spanning Molecules, Cells, Circuits, and Behavior

PROJECT SUMMARY Quantitative research, when appropriately planned and executed, yields results that are objective, unbiased, and replicable across experimental systems and labs. This is particularly important in neuroscience, where quantitative tools and methodologies are critical to extract biological meaning from complex and often noisy data

sets that arise from manipulating the brain and nervous system. To provide the next generation of neuroscientists the skillsets necessary to tackle daunting challenges in the field, this proposal requests support for a new postdoctoral training program at the Salk Institute in “Quantitative Neuroscience Spanning Molecules, Cells,

Circuits, and Behavior.” Salk has been home to pioneering neuroscience research since its founding over 50-years ago, and under the leadership of co-Directors, Drs. Samuel Pfaff and Edward Callaway, program faculty have devised a comprehensive training program that will provide early-stage postdoctoral fellows foundational

training in quantitative neuroscience, focusing on the tools and methodologies necessary for BIG DATA approaches. The 30 program faculty include experts in molecular and cellular neuroscience, neural circuits of perception and behavior, BIG DATA and computational neuroscience, and tool development, who together seek

to understand the circuit mechanisms by which animals integrate external stimuli and internal states to generate complex behaviors. Importantly, there are currently ~120 postdoctoral trainees in program faculty labs, representing a robust and highly qualified applicant pool. The training program has four overall goals. (1) To

provide technical training in quantitative neuroscience via mentored lab research and program elements that include a Course on BIG DATA, a quantitative literacy roundtable (journal club and research presentations), Emerging Technologies Tutorials, and a Bio-Computation and Theory Seminar Series. These efforts will be

augmented by a T32 statistician who will ensure that experimental design and statistical methodologies are stressed throughout. Focusing on postdocs with existing competencies in statistics will allow the program to teach advanced statistical methodologies relevant to BIG DATA approaches. (2) To foster collaborative

interdisciplinary research by organizing program-wide meetings that encourage cross-fertilization of ideas across disciplines. (3) To provide Fellows a wealth of career development opportunities such as grant writing workshops, chalk talk tutorials, career panels, and chances to mentor high school or undergraduate students. This will ensure

Fellows acquire the skills necessary to establish careers in academia, industry, or other career paths of their choice. (4) To increase diversity of the neuroscience workforce by actively recruiting graduate students from underrepresented backgrounds into the training program and by cultivating an institutional environment that

prioritizes diversity, equity, and inclusion. The proposed training program will support six early-stage postdoctoral trainees annually for up to two years each, equipping them with the scientific and career skills necessary to establish themselves as successful, independent neuroscience researchers.