Ross S. Williamson, PhD

  • Assistant Professor, Department of Otolaryngology

E-mail

rsw@pitt.edu

Personal Website

website link

Education & Training

Ph.D, University College London (2012)

Location

W1448 Biomedical Science Tower

Research Interest Summary

Auditory systems neuroscience, sensory decision making, theoretical neuroscience & machine learning

Our ability to make decisions based on changes in the sensory environment often involves the accumulation of sensory evidence, where newly acquired information is used to update existing beliefs and to drive future actions. For example, the sound of sirens when driving leads to an accumulation of sensory evidence that leads to a decision regarding the correct motor action to take (whether or not, and where, to pull over). This kind of auditory perceptual decision-making can be found throughout everyday life, whenever we use information from our various senses to guide the decisions we make and the actions that we take.

In order to understand the neurobiological circuits that underlie sensory decision making, it is crucial to understand the flow of sensory information throughout the brain, and how this information is used to drive behavior. Corticofugal neurons located in the deep layers of the neocortex provide the only means of communicating and routing information to the rest of the brain. We believe that the organization of corticofugal networks provides a means for routing and coordinating the flow of behaviorally-relevant sensory information to myriad downstream targets. Our research aims to disambiguate the roles of distinct classes of corticofugal neurons during animal engagement in sensory-guided behaviors in models of health and disease.

PHYSIOLOGY: OBSERVATION AND PERTURBATION OF NEURAL CIRCUITRY
We observe neural dynamics in a number of ways. We monitor large-scale network activity of genetically identified cell-types in the auditory cortex during using two-photon calcium imaging, and we then perturb those networks using optogenetics and spatial light modulation. This allows us to characterize large neural populations and to understand how local networks of different cell-types interact with themselves and each other.

We monitor and perturb neural activity of genetically identified cell-types within the auditory cortex and various downstream projection targets using chronic electrophysiology combined with opto- and chemo-genetics. This allows us to understand how information in the auditory cortex is used by different downstream areas.

Both of these techniques for observing and perturbing neural circuitry are carried out in behaving mice, to understand cortical circuit contributions to auditory-guided behavior.

ANATOMY
We use viral tracing strategies to understand the downstream targets of genetically identified cell-types in the auditory cortex, and the specific inputs that these cell-types receive.

BEHAVIOR
We study auditory-guided behaviors using head-fixed mice that navigate a virtual reality during the presentation of different auditory cues. Using virtual reality for such a task allows for voluntary trial initiation, ensures active listening, and allows for rapid modification of the environment in a way that would be impossible with conventional behavioral training chambers.

THEORY
Advances in experimental techniques allow for the simultaneous observation of thousands of neurons. Such high-dimensional data sets can be difficult to analyze and interpret. We use techniques from machine learning to build statistical models that can characterize neural population responses and extract structure from high-dimensional neural data.

Romero S, Hight AE, Clayton KK, Resnik J, Williamson RS, Hancock KE, Polley DB (2019). Cellular and Widefield Imaging of Sound Frequency Organization in Primary and Higher Order Fields of the Mouse Auditory Cortex. Cerebral Cortex (New York, N.Y. : 1991). PMID 31667491 DOI: 10.1093/cercor/bhz190 


Vila CH, Williamson RS, Hancock K, Polley DB (2019). Optimizing optogenetic stimulation protocols in auditory corticofugal neurons based on closed-loop spike feedback. Journal of Neural Engineering. PMID 31394519 DOI: 10.1088/1741-2552/ab39cf 

 

R.S. Williamson, D.B. Polley (2019). Parallel pathways for sound processing and functional connectivity among layer 5 and 6 auditory corticofugal neurons. eLife 8, e42974

          

M.M. Asokan, R.S. Williamson, K.E. Hancock, D.B. Polley (2018). Sensory overamplification in layer 5 auditory corticofugal projection neurons following cochlear nerve synaptic damage. Nature Communications 9(1), 2468

 

A.F. Meyer, R.S. Williamson, J.F. Linden, M. Sahani (2017). Models of neuronal stimulus-response functions: elaboration, estimation, and evaluation. Frontiers in Systems Neuroscience 10(1), 109

 

R.S. Williamson, M.B. Ahrens, J.F. Linden, M. Sahani (2016). Local sensory context shapes input gain in responses to complex sounds. Neuron 91(2), 467-481

   

R.S. Williamson, K.E. Hancock, B.G. Shinn-Cunningham, D.B. Polley (2015). Locomotion and task demands differentially modulate thalamic audiovisual processing during active search. Current Biology 25, 1885-1891

 

R.S. Williamson, M. Sahani, J.W. Pillow (2015).  The equivalence of information-theoretic and likelihood-based methods for neural dimensionality reduction. PLoS Computational Biology 11(4), e1004141