Michael Hawken

My broad research interest is in relating visual perception to the underlying brain circuits in visual cortex. We use a range of approaches including large-scale connectomics, multidimensional functional characterization of neuronal receptive field properties, and computational modeling to unify the neural population’s role in visual perception.

Stuctural Connectiomics One of the key features of visual circuits is how they are organized and connected in both feedfoward and recurrent motifs. Our recent studies have determined the neuronal and synaptic structure of the principal input layers of primate visual cortex (Garcia et al., 2019). We have characterized different neuronal populations in primary visual cortex (Kelly et al., 2019) and in extrastriate areas V2 and MT (Kelly & Hawken, 2020). Some of our current work involves extending these studies to human cortex to determine the homolgies between macaque and human. 

Functional Clustering of Neural Populations Neurons in the primary visual pathways encode multiple stimulus dimensions of the visual scene. The activity of the neural populations is a central determinant of visual perception. Much of our previous work involved detailed characterization of neuronal properties along one or a small number of stimulus dimensions, for example spatial freqeuency or orienation and color. We continie this approach as it provides a detailed account of how neurons encode information along these single dimensions (Henry et al., 2019). We have also used a multidimensional stimulus approach—along seven or eight stimulus dimensions—to determine whether there are functional clusters of neurons in different cortical compartments (Hawken et al., 2020). This approach has allowed us to identify small numbers of functionally defined clusters within single cortical layers. Some of our current work involves the use of optogenetic tagging of projection populations from V1 to extrastriate cortex and to determine whether they belong to discrete functional clusters and hence identify specific long range circuit motifs in primate cortex. These motifs are central to informing models of cortical circuits.

Computational Modeling of Neural Populations One of the overall goals of understanding brain function is to understand how circuits give rise to function and inform perception. My current collaborations with mathmeticians and theoretical neuroscientists at NYU have resulted in a large-scale dynamical model of more than 10,000 neurons in layer 4ca of primary visual cortex that includes circuit features that result in the generation of orientation, spatial frequency and rccently direction selectivity (Chariker et al., 2021, 2022). Our current work involves extending these large-scale models to include other cortical layers, thereby providing a picture of the feedfoward information dynamically provided to different extra-striate visual areas.  

Chariker L, Shapley R, Hawken M, Young LS. (2022) A computational model of direction selectivity in Macaque V1 cortex based on dynamic differences between ON and OFF pathways. Journal of Neuroscience 42: 3365-3380.

Chariker L, Shapley R, Hawken M, Young LS (2021) A theory of direction selectivity for macaque primary visual cortex. PNAS 118: e2105062118. doi: 10.1073/pnas.2105062118.

Hawken, M.J. (2020) Advances in the physiology of primary visual cortex in primates. Current Opinion in Physiology 16: 79-84.

Henry, C.A., Jazayeri, M., Shapley, R.M., Hawken, M.J (2020) Distinct spatiotemporal mechanisms underlie extra-classical receptive field modulation in macaque V1 microcircuits. eLife 9:e54264 DOI: 10.7554/eLife.54264

Kelly, J.G., Hawken, M.J. (2020) GABAergic and non-GABAergic subpopulations of Kv3.1b-expressing neurons in macaque V2 and MT: Laminar distributions and proportion of total neuronal population Brain Structure & Function 225: 1135-1152.

Hawken, M.J., Shapley, R.M., Disney, A.A., Garcia-Marin, V., Henrie, J.A., Henry, C.A., Johnson, E.N., Joshi, S., Kelly, J.G., Ringach, D.L., Xing, D. (2020)  Functional clusters of neurons in layer 6 of macaque V1. Journal of Neuroscience 40: 2445-2457.

Kelly J.G., Garcia-Marin, V,  Rudy, B. & Hawken M.J. (2019) Densities and laminar distributions of Kv3.1b-, PV-, GABA-, and SMI-32-immunoreactive neurons in macaque area V1. Cerebral Cortex 29:1921-1937.

Garcia-Marin V, Kelly JG, Hawken M.J. (2019) Major feedforward thalamic input to layer 4C of primary visual cortex in primate.  Cerebral Cortex 29: 134-149.