Jeffrey Beck

Jeffrey Beck

Assistant Professor of Neurobiology

External Address: 
Bryan Research Building, 311 Research Drive Room 301H, Durham, NC 27710
Internal Office Address: 
Box 3209, Durham, NC 27710


We study neural coding and computation from a theoretical perspective with particular emphasis on probabilistic reasoning and decision making under uncertainty, complex behavioral modeling, computational models of cortical circuits and circuit function, dynamics of spiking neural networks, and statistical analysis of neural and behavioral data.  Previous work has been largely concerned with sensory-motor transformations and neural representations of complex stimuli such as odors.  More recently, we have been focusing on developing non-linear latent state space models of neural networks as standard linear models are incapable of generating even very simple behaviors.  

Education & Training

  • Ph.D., Northwestern University 2003

Selected Grants

Mechanisms of efficient coding of dynamic visual motion signals for pursuit awarded by National Institutes of Health (Investigator). 2014 to 2025

Neurobiology Training Program awarded by National Institutes of Health (Mentor). 2019 to 2024

Canonical computations for motor learning by the cerebellar cortex micro-circuit awarded by National Institutes of Health (Co Investigator). 2019 to 2024

Neural Control of Eye Movement awarded by National Institutes of Health (Co Investigator). 2017 to 2022

The Circuit Logic of Modulation of Locomotion by Odors awarded by National Institutes of Health (Research Scientist). 2017 to 2019

The Role of Frontal Cortex in Primate Metacognition awarded by National Science Foundation (Co Investigator). 2015 to 2019

Basic predoctoral training in neuroscience awarded by National Institutes of Health (Training Faculty). 1992 to 2018

Lange, Richard D., et al. “A confirmation bias in perceptual decision-making due to hierarchical approximate inference.Plos Computational Biology, vol. 17, no. 11, Nov. 2021, p. e1009517. Epmc, doi:10.1371/journal.pcbi.1009517. Full Text

Toader, Andrew C., et al. “Probabilistic inferential decision-making under time pressure in rhesus macaques (Macaca mulatta).J Comp Psychol, vol. 133, no. 3, Aug. 2019, pp. 380–96. Pubmed, doi:10.1037/com0000168. Full Text Open Access Copy

Jin, Miaomiao, et al. “Neuronal Adaptation Reveals a Suboptimal Decoding of Orientation Tuned Populations in the Mouse Visual Cortex.J Neurosci, vol. 39, no. 20, May 2019, pp. 3867–81. Pubmed, doi:10.1523/JNEUROSCI.3172-18.2019. Full Text

Tao, Liangyu, et al. “Statistical structure of locomotion and its modulation by odors.Elife, vol. 8, Jan. 2019. Pubmed, doi:10.7554/eLife.41235. Full Text

Darlington, Timothy R., et al. “Neural implementation of Bayesian inference in a sensorimotor behavior.Nat Neurosci, vol. 21, no. 10, Oct. 2018, pp. 1442–51. Pubmed, doi:10.1038/s41593-018-0233-y. Full Text

Oh-Descher, Hanna, et al. “Probabilistic inference under time pressure leads to a cortical-to-subcortical shift in decision evidence integration.Neuroimage, vol. 162, Nov. 2017, pp. 138–50. Pubmed, doi:10.1016/j.neuroimage.2017.08.069. Full Text Open Access Copy

O’Hare, Justin K., et al. “Striatal fast-spiking interneurons selectively modulate circuit output and are required for habitual behavior.Elife, vol. 6, Sept. 2017. Pubmed, doi:10.7554/eLife.26231. Full Text

Chen, Xin, et al. “Neuron's eye view: Inferring features of complex stimuli from neural responses.Plos Comput Biol, vol. 13, no. 8, Aug. 2017, p. e1005645. Pubmed, doi:10.1371/journal.pcbi.1005645. Full Text

Grabska-Barwińska, Agnieszka, et al. “A probabilistic approach to demixing odors.Nat Neurosci, vol. 20, no. 1, Jan. 2017, pp. 98–106. Pubmed, doi:10.1038/nn.4444. Full Text

Oh, Hanna, et al. “Satisficing in split-second decision making is characterized by strategic cue discounting.J Exp Psychol Learn Mem Cogn, vol. 42, no. 12, Dec. 2016, pp. 1937–56. Pubmed, doi:10.1037/xlm0000284. Full Text Open Access Copy


Fan, K., et al. “Fast second-order stochastic backpropagation for variational inference.” Advances in Neural Information Processing Systems, vol. 2015-January, 2015, pp. 1387–95.

Dowd, E. W., et al. “Probability of guessing, not precision, changes in mixture models of visual working memory during cognitive control of attentional guidance.” Visual Cognition, vol. 22, no. 8, 2014, pp. 1027–30. Scopus, doi:10.1080/13506285.2014.960669. Full Text