Revealing Geometry of Neuronal Population Dynamics Using Cortex-wide Volumetric Recording of Neuroactivity at Cellular Resolution

Event Details

Type

Monday Lecture Series

Speaker(s)

Alipasha Vaziri, Ph.D., professor and head, Laboratory of Neurotechnology and Biophysics, The Rockefeller University

Speaker bio(s)

Understanding how sensory information is represented, processed, and leads to generation of complex behavior is the major goal of systems neuroscience. However, the ability to detect and manipulate such large-scale functional circuits has been hampered by the lack of appropriate tools and methods that allow parallel and spatiotemporally specific manipulation of neuronal population activity while capturing the dynamic activity of the entire network at high spatial and temporal resolutions. The Vaziri lab has consistently pushed the limits on speed, volume size, and depth at which neuronal population activity can be optically recorded at cellular resolution. Amongst others have demonstrated whole-brain recording of neuroactivity at cellular resolution in small model systems as well as more recently near-simultaneous recording from over 1 million neurons distributed across both hemispheres and different layers of the mouse cortex at cellular resolution.

While our capability to record from ever increasing number of neurons has increased over the years the widespread application of dimensionality reduction tools implies that neural dynamics can be approximated by low-dimensional “latent” signals reflecting neural computations. However, what would be the biological utility of such a redundant encoding scheme, and what is the appropriate resolution and scale of recording to understand brain function? Imaging neural activity at cellular resolution and near-simultaneously across mouse cortex, the Vaziri lab has recently found unbounded scaling of dimensionality of neuronal population activity with neuron number in populations sizes of up to one million neurons. The data suggests that while half of the neural variance is contained within about sixteen dimensions that are correlated with behavior, the majority of the reliable dimensions which collectively account for the other half of total neuronal variance do not have any immediate behavioral or sensory correlates. The activity patterns underlying these higher dimensions are fine-grained and cortex-wide, highlighting that large-scale, cellular-resolution recording is required to uncover the full substrates of neuronal computations.

Alipasha Vaziri earned his Ph.D. from the University of Vienna in quantum optics, then conducted his postdoctoral work at the U.S. National Institutes of Standards and Technology. While a research specialist at HHMI’s Janelia Research Campus, he developed an interest in neuroscience and focused on the development of new high-resolution microscopy, and later on optogenetic techniques. He then joined the University of Vienna in Austria, where he became a group leader at the Research Institute for Molecular Pathology and associate professor and director of the inter-departmental research platform for Quantum Phenomena and Nanoscale Biological Systems. He joined the faculty of The Rockefeller University in 2015 as an associate professor and was named professor in 2020. In 2016 he became associate director of Rockefeller’s Kavli Neural Systems Institute. Vaziri has received the Prize of the City of Vienna and was named a Fellow Member of Optica, among other honors.

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