Training Program in Neuroscience at Stony Brook University: Fostering Quantitative Literacy and Experimental Rigor - Summary
Modern neuroscience demands breadth of knowledge as well as quantitative rigor. The goal of this program is
to satisfy the needs for rigorous literacy in experimental design, data analysis and quantitative methods applied
to neuroscience, with the purpose of training generations of responsible, ethical, inclusive students who will
become tomorrow’s innovators. Carefully designed mini courses, workshops and laboratory rotations will support
trainees in developing a deep understanding of the power and limitations of different experimental approaches
and in the appropriate use of statistics. Specialized courses will raise awareness of biases in data analysis and
provide strategies for reducing the negative effects of bias on the interpretation of experimental results. The
activities proposed here are based on active learning pedagogy and will support trainees in developing the skills
they need for successful careers in neuroscience related fields, be it in academia, industry, or other enterprises.
In addition to core courses and laboratory rotations, the curriculum includes two new experimental design and
data analysis courses, a course aimed at training students in grant writing and reviewing, and scientific
communication courses and workshops offered by the Alan Alda Center for Communicating Science here at
Stony Brook University. Mentor/mentee workshops will facilitate the establishment and maintenance of rewarding
and productive mentoring relationships as students advance to the completion of their degree and develop a
long-term career plan. Such comprehensive training will prepare trainees to meet the demands of their
experimental work during their doctoral degree with confidence, supported by committed mentors and by a
program that fosters a diverse and inclusive training environment. A tight network of alumni, together with career
development resources at the institution, will place trainees graduating from this program at a competitive edge
for a variety of careers in STEM disciplines.
The program will provide financial support for 6 trainees per year starting on year 1 of the proposed funding
period. Additionally, 6 trainees will be supported in their second year during years 2 – 5, for a total of 12 supported
predoctoral trainees from year 2-5. Eligible students will be selected for support by an appointed committee.
Financial support will be awarded for 1 year, renewable for the second year based on trainees’ standing and
progress. Program activities will be open to all students in the program, currently a total of 51 trainees. The goal
of this plan is to engage faculty with expertise in new approaches to experimental design and data analysis to
bring quantitative training in signal processing, machine learning, artificial intelligence into neuroscience
experimental design and data analysis, to expand recruitment and increase the number of participating trainees.
