(AGENPARL) – VENEZIA lun 17 aprile 2023 Speaker: Steven W. Zucker, Yale University

Abstract:
How might one infer circuit properties from neurophysiological data? How do these circuits relate to artificial neural networks? We address these challenges with a novel neural manifold. It is obtained using unsupervised machine learning algorithms and applied to the mouse visual system. Each point on our manifold is a neuron; nearby neurons respond similarly in time to similar parts of a stimulus ensemble. This ensemble includes drifting gratings and flows, i.e. patterns resembling what a mouse would “see” while running through fields. Our manifold differs from the standard practice in computational neuroscience, of embedding trials in neural coordinates. Importantly, for our manifolds topology matters: from spectral theory we infer that, if the circuit consists of separate components, the manifold is discontinuous (illustrated with retinal data). If there is significant overlap between circuits, the manifold is nearly-continuous (cortical data).  To approach real circuits, local neighborhoods on the manifold are identified with actual circuit components. For the retinal data we show these components correspond to distinct ganglion cell types by their mosaic-like receptive field organization, while for cortical data, neighborhoods organize neurons by type (excitatory/inhibitory) and anatomical layer. The manifold topology for deep CNN’s will also be developed.

Joint research with Luciano Dyballa (Yale), Marija Rudzite (Duke), Michael Styrker (UCSF) and Greg Field (UCLA).

Bio Sketch:
Steven W. Zucker is the David and Lucile Packard Professor of Computer Science at Yale University, and also Professor of Biomedical Engineering. He is a member of the Program in Applied Mathematics, which he directed from 2003 to 2009, and a member of the Interdepartmental Neuroscience Program. Currently he co-directs the Swartz Center, which fosters collaborative research and interdisciplinary training in computational and systems neuroscience.

Steve was elected a Fellow of the Royal Society of Canada, a Fellow of the Canadian Institute for Advanced Research, a Fellow of the IEEE, and (by)Fellow of Churchill College, Cambridge. He won the Siemens Award, several Best Paper prizes, and was recently named a Distinguished Investigator by the Paul G. Allen Family Foundation for research in crowd computing by bacteria.

Fonte/Source: http://www.unive.it/data/agenda/1/73792