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Abstract:

The detection and processing of novel stimuli is critical for survival; novelty has powerful effects on attention, learning & memory. Recent work has shown that specific classes of inhibitory neurons in the visual cortex, vasoactive-intestinal peptide (VIP) expressing and somatostatin (SST) expressing cells, are differentially modulated by novelty, and may serve to enhance excitatory stimulus responses through disinhibition. Yet these cell populations contain multiple genetically and morphologically distinct types and it is unlikely that they are uniform in their response to novelty. To investigate diversity in novelty coding, we conducted a survey of neural activity in excitatory, VIP inhibitory, and SST inhibitory neurons in the visual cortex of mice performing a change detection task with familiar and novel stimuli. The effects of stimulus novelty were not limited to sensory representations; behavioral, omission, and task related coding were also influenced by novelty, particularly in VIP neurons. By tracking the activity of individual neurons over days, we found striking diversity in single cell coding properties following repeated stimulus exposure. Unsupervised clustering revealed distinct groups of neurons that differed in the direction and dynamics of coding changes, being either transiently enhanced or suppressed by novelty, or showing more stable coding over days. These unique functional subpopulations may contribute to distinct aspects of novelty processing and subsequent familiarization, such as initial detection of novelty, maintaining learned representations, or associating new stimuli with reward and behavioral actions. 

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Requests for accommodations related to disability should be made to the Department of Biology at 346-4502 as early as possible.

Murray Lab

CANCELLED due to travel delays.  ION & Physics will announce when this seminar will be rescheduled.  ION & Physics members can join at 3:45pm for a social hour today 2/1 in the Willamette Atrium.

This seminar is being co-hosted with the UO Physics Colloquium series which is also held at 4pm on Thursdays. 

Abstract: 

For an animal to perform any function, millions of cells in its body furiously interact with each other. Be it a simple computation or a complex behavior, all biological functions involve the concerted activity of many individual units. A theory of function must specify how to bridge different levels of description at different scales. For example, to predict the weather, it is theoretically irrelevant to follow the velocities of every molecule of air. Instead, we use coarser quantities of aggregated motion of many molecules, e.g., pressure fields. Statistical physics provides us with a theoretical framework to specify principled methods to systematically ‘move’ between descriptions of microscale quantities (air molecules) to macroscale ones (pressure fields). Can we hypothesize equivalent frameworks in living systems? How can we use descriptions at the level of cells and their connections to make precise predictions of complex phenomena? My research focuses on the theory, modeling, and analysis required to discover generalizable forms of scale bridging across species and behavioral functions. In this talk, I will present lines of previous and ongoing research that highlight the potential of this vision. I shall focus on two seemingly very different systems: mouse brain neural activity patterns, and octopus skin cells activity patterns. In the mouse, we reveal striking scaling behavior and hallmarks of a renormalization group- like fixed point governing the system. In the octopus, camouflage skin pattern activity is reliably confined to a (quasi-) defined dynamical space.  Finally, I will touch upon the benefits of comparing across animals to extract principles of multiscale function in biological systems, and discuss potential avenues of investigation that could allow us to decipher how macroscale properties, such as memory or camouflage, emerge from microscale level activity of individual cells. 

Bio:
Leenoy Meshulam is a Swartz Theory fellow at the University of Washington, and a Burroughs Wellcome CASI awardee. Her research interests are at the intersection of neuroscience and physics. Her current focus is on developing coarse-graining schemes for nervous systems across species to achieve compact, simple descriptions, and provide quantitative predictions of the system’s behavior. Previously, Leenoy received her PhD from Princeton University, where she constructed simplified computational models to investigate the collective nature of neural activity in the hippocampus.