Brent Doiron, PhD

  • Associate Professor, Mathematics

Phone

412-624-1759

E-mail

bdoiron@pitt.edu

Personal Website

website link

Location

301 Thackeray Hall

Research Interest Summary

Theoretical investigations of the impact of neural variability on sensory processing

Collections of neurons organize their activity to perform a variety of computational, cognitive, and behavioral tasks. The 'neuro'-mechanics that underlie neural computation is the primary interest of our group. We use a combination of statistical mechanics, nonlinear system theory, and information theory to study this broad field.
Of particular interest is the genesis and impact of neural variability on sensory processing and computation. In collaboration with experimentalists working in visual, somatosensory, auditory, olfactory, and electrosensory systems we study general principles of sensory transduction in populations of neurons. The circuit architecture, nonlinearities inherent in spike transfer, and plasticity of synaptic response allow variability and synchrony to be shaped by stimuli as well as neural state. Understanding the specific mechanisms that mediate this shaping, and the consequences for population coding, are a central challenges for sensory neuroscience.

C Huang, DA Ruff, R Pyle, R Rosenbaum, MR Cohen, B DoironNeuron 101, 337-348 (2019) Attentional modulation of neuronal variability in circuit models of cortexT

Doiron, A Litwin-Kumar, R Rosenbaum, GK Ocker, K JosićNature neuroscience 19, 383-393 (2016)

Litwin-Kumar, A., and Doiron, B. Slow Dynamics and High Variability in Balanced Cortical Networks with Clustered connections. Nature Neuroscience 15: 1498-1505, 2012.

Rosenbaum, R., Rubin, J., and Doiron, B. Synaptic filtering with short term depression. PLoS Computational Biology. 8(6): e1002557. doi:10.1371/journal.pcbi.1002557, 2012.

Kanashiro, GK Ocker, MR Cohen, B DoironElife 6, e23978 (2017)The spatial structure of correlated neuronal variabilityR

Polk, A., Litwin-Kumar, A., and Doiron, B. Correlated Neural Variability in Persistent State Networks. Proceedings of the National Academy of Sciences (USA), 109:6295-6300, 2012.

Rosenbaum, MA Smith, A Kohn, JE Rubin, B DoironNature neuroscience 20, 107-117 (2017)The mechanics of state-dependent neural correlationsB

de la Rocha, J.*, Doiron, B.*, Shea-Brown, E. Josic, K. and Reyes, A. Correlation between neural spike trains increase with firing rate. Nature. 448: 802-806, 2007.

Doiron, B., Chacron, M.J., Maler, L., Longtin, A., and Bastain, J. Inhibitory feedback required for network oscillatory responses to communication but not prey stimuli. Nature 421:539-543, 2003.