Nicholas Cain, Ph.D.
Nicholas Cain is a scientist in the Allen Institute's neural coding program, where he develops mathematical models of neural dynamics that aim to discover how neural systems process information about the environment. By applying mathematical theories of network dynamics and processing to the quantitative data collected at the Allen Institute, he hopes to link theory and experiment through detailed mathematical models of neural function. His research interests include theoretical models of decision-making and accumulation of sensory evidence by circuits involved in short-term working memory. Cain received a B.S. in mathematics from Davidson College, and a M.S. and Ph.D. in applied mathematics from the University of Washington.
Research Interests Since joining the modeling, analysis, and theory group at the Allen Institute in 2012, I have contributed to two main Institute-wide platforms. The first, ongoing, contribution is to the Allen Mouse Brain Connectivity Atlas, where I helped formulate reduced models of brain connectivity based on raw fluorescence data, and began a graph theoretic analysis of the whole mouse brain connectivity structure. I have also worked with other members of the modeling team to construct a large-scale population density modeling framework (DiPDE) capable of efficiently simulating the voltage distribution of coupled neuronal populations. These two projects converge in a broader project, in which whole-brain connectivity data are being used to parameterize large-scale neuronal simulations.
- Computational neuroscience
- Numerical analysis
- Mathematical modeling
- Neural coding
Selected Publications View on PUBMED
PLOS | ONE
August 2, 2018
Gratiy SL, Billeh YN, Dai K, Mitelut C, Feng D, Gouwens NW, Cain N, Koch C, Anastassiou CA, Arkhipov A
June 29, 2018
de Vries S, Lecoq J, Buice MA, Groblewski PA, Ocker GK, Oliver M, Feng F, Cain N, Ledochowitsch P, Millman D, Roll K, Garrett M, Keenan T, Kuan L, Mihalas S, Olsen S, Thompson C, Wakeman W, Waters J, Williams D, Barber C, Berbesque N, Blanchard B, Bowles N, Caldejon S, Casal L, Cho A, Cross S, Dang C, Dolbeare T, Edwards M, Galbraith J, Gaudreault N, Griffin F, Hargrave P, Howard R, Huang L, Jewell S, Keller N, Knoblich U, Larkin J, Larsen R, Lau C, Lee E, Lee F, Leon A, Li L, Long F, Luviano J, Mace K, Nguyen T, Perkins J, Robertson M, Seid S, Shea-Brown E, Shi J, Sjoquist N, Slaughterbeck C, Sullivan D, Valenza R, White C, Williford A, Witten D, Zhuang J, Zeng H, Farrell C, Ng L, Bernard A, Phillips JW, R Reid C, Koch C
February 19, 2018
Teeter C, Iyer R, Menon V, Gouwens N, Feng D, Berg J, Szafer A, Cain N, Zeng H, Hawrylycz M, Koch C, Mihalas S
PLoS Computational Biology
November 12, 2018
Arkhipov A, Gouwens NW, Billeh YN, Gratiy S, Iyer R, Wei Z, Xu Z, Berg J, Buice M, Cain N, da Costa N, de Vries S, Denman D, Durand S, Feng D, Jarsky T, Lecoq J, Lee B, Li L, Mihalas S, Ocker GK, Olsen SR, Reid RC, Soler-LLavina G, Sorensen SA, Wang Q, Waters J, Scanziani M, Koch C
Journal of Neurophysiology
Cain N, Barreiro Ak, Shadlen M, Seah-Brown E
Cain N, Shea-Brown E
Current Opinion in Neurobiology
Cain N, Shea-Brown E