Gabriel Koch Ocker, Ph.D.
Gabe Ocker is a member of the modeling, analysis and theory team. He joined the Allen Institute in 2015 to study how the activity of mouse visual cortex subtends visual cognition. In particular, he analyzes mathematical models of neural networks and in vivo optophysiology data, working to relate physiological and anatomical properties of cortical circuits to their activity and function. Before coming to the Institute, Gabe earned a Ph.D. at the University of Pittsburgh. There, he worked on relating single neuron biophysics to joint activity between neurons and on theories describing long-term plasticity of individual synapses and of connectivity patterns in recurrent networks. Before that, he studied applied math and neuroscience at Oberlin College.
The behaviors neural systems give rise to reveal computations they must be able to perform. For example, our visual systems must be able to detect and classify objects. With only few exceptions, however, we still lack an understanding of how the physiology and anatomy of interacting neurons give rise to those computations. New recording methods and genetically engineered model organisms allow exciting progress towards a mechanistic understanding of neuronal function. Gabe joined the Allen Institute to contribute to the analysis of data from large-scale optical recordings in mice during visual behavior, using that data to inform statistical and mechanistic models of cortical dynamics and computation.
- Theoretical and computational neuroscience
- Point neuron models
- Synaptic plasticity
PLOS Computational Biology
August 3, 2020
Ocker GK, Buice MA
October 27, 2020
Millman DJ, Ocker GK, Caldejon S, Kato I, Larkin JD, Lee EK, Luviano J, Nayan C, Nguyen TV, North K, Seid S, White C, Lecoq J, Reid C, Buice MA, de Vries SE
PLoS Computational Biology
July 12, 2019
Recanatesi S, Ocker GK, Buice MA, Shea-Brown E
March 1, 2019
Ocker GK, Doiron B
December 16, 2019
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
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