WYETH BAIR, PhD

PROFESSOR

Research Focus: Computational and Experimental Visual Neuroscience

RESEARCH

We are a systems neuroscience group that aims to understand neural circuitry and neural coding in the cerebral cortex with a major emphasis on the primate visual system. We approach this problem by recording directly from neurons in the functioning brain in vivo and by creating and refining large scale spiking neural network models that run on parallel computers. Thus, we are an interdisciplinary lab where members may do computational studies, in vivo experiments, or both.

The immediate goals of our computational work are (1) to unify neural circuit models of visual processing across modalities that intersect in the primary visual cortex (V1), i.e., to integrate models of motion, color and form processing to develop a more complete and deeper understanding of the computations carried out by cortical circuitry, (2) to extend these models to higher cortical areas to investigate shape representation in area V4 and motion perception in area V5/MT, and (3) to pioneer a novel web-based modeling framework (www.iModel.org) to promote the use of computer models and to advance collaboration between experimental, computational and theoretical neuroscientists.

Our immediate experimental goals are the development of a cutting-edge optical recording system (2-photon Ca++ imaging) to facilitate the study of both large-scale and small neighborhood representation and computation in V1 and V4 of the primate. For example, we seek to understand inter-neuronal correlation within V1 at the microcircuit level and, in collaboration with the Pasupathy lab, the basis of shape representation within area V4. Our ultimate goal is to understand human visual perception well enough to reproduce it in artificial systems and to guide the future development of brain-machine interfaces.

SELECTED PUBLICATIONS

Bigelow, A., Kim T., Namima, T., Bair W, Pasupathy A. (2023). Dissociation in neuronal encoding of object versus surface motion in the primate brain. Current Biology, 33(4), 711-719.

Kim T, Bair W, Pasupathy A (2019). Neural coding for shape and texture in macaque area V4. The Journal of Neuroscience, 39(24): 4760-74.

Popovkina DV, Bair W, Pasupathy A (2019). Modelling diverse responses to filled and outline shapes in macaque V4. Journal of Neurophysiology, 121(3): 1059-77.

Pospisil DA, Pasupathy A, Bair W (2018). ‘Artiphysiology’ reveals V4-like shape tuning in a deep network trained for image classification. eLife, 2018;7:e38242.

Baker PM, Bair W (2016). A Model of Binocular Motion Integration in MT Neurons. The Journal of Neuroscience, 36(24): 6563-82.

Bennett JE, Bair W(2015). Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity. PLoS computational biology, 11(8): e1004422.

McLelland D, Baker PM, Ahmed B, Kohn A, Bair W (2015). Mechanisms for Rapid Adaptive Control of Motion Processing in Macaque Visual Cortex. The Journal of Neuroscience, 35(28): 10268-80.

Oleskiw TD, Pasupathy A, Bair W (2014). Spectral receptive fields do not explain tuning for boundary curvature in V4. Journal of Neurophysiology, 112(9): 2114-22.

Smith A, Bair W, Movshon A (2006). Dynamics of suppression in macaque primary visual cortex. Journal of Neuroscience, 26(18): 4826-34.