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<< May 2018 >>

Thursday, May 3, 2018

Perturbation and Control of Human Brain Network Dynamics

Seminar | May 3 | 3:30-4:30 p.m. | 101 Life Sciences Addition


Dani Bassett, University of Pennsylvania

Neuroscience Institute, Helen Wills


Abstract: The human brain is a complex organ characterized by heterogeneous patterns of interconnections. New non-invasive imaging techniques now allow for these patterns to be carefully and comprehensively mapped in individual humans, paving the way for a better understanding of how wiring supports our thought processes. While a large body of work now focuses on descriptive statistics to...   More >

Monday, May 7, 2018

Oxyopia - Graduate Student Seminar

Seminar: Oxyopia Seminar | May 7 | 12-1:30 p.m. | 489 Minor Hall


Paul Cullen, John Flanagan Lab; Brian Cheung, Bruno Olshausen Lab

Neuroscience Institute, Helen Wills


Paul Cullen
John Flanagan Lab
Title: The Secret Lives of Retinal Astrocytes
Abstract: The study of glia – the support cells of the central nervous system – has come a long way since Rudolf Virchow described a connective tissue of the brain that he termed ‘nervenkitt’ in 1856. Rather than a passive scaffolding for neurons (the word ‘glia’ means glue in Greek), these cells are responsible for a...   More >

Tuesday, May 22, 2018

Expander graph architectures for high-capacity neural memory

Seminar: Redwood Seminar | May 22 | 12-1:30 p.m. | 560 Evans Hall


Rishidev Chaudhuri, UT Austin/Simons Institute UC Berkeley

Neuroscience Institute, Helen Wills


Memory networks in the brain must balance two competing demands. On the one hand, they should have high capacity to store the large numbers of stimuli an organism must remember over a lifetime. On the other hand, noise is ubiquitous in the brain and memory is typically retrieved from incomplete input. Thus, memories must be encoded with some redundancy, which reduces capacity. Current neural...   More >

Wednesday, May 23, 2018

Characterizing neurons in the visual area V4 through interpretable machine learning

Seminar: Redwood Seminar | May 23 | 12-1:30 p.m. | 560 Evans Hall


Reza Abbasi-Asl, UC Berekely

Neuroscience Institute, Helen Wills


In the past decade, research in machine learning has been exceedingly focused on the development of algorithms and models with remarkably high predictive capabilities. Models such as convolutional neural networks (CNNs) have achieved state-of-the-art predictive performance for many tasks in computer vision, autonomous driving, and transfer learning in areas such as computational neuroscience....   More >

Thursday, May 24, 2018

Wednesday, May 30, 2018

Inference and Efficient Coding in Natural Auditory Scenes

Seminar: Redwood Seminar | May 30 | 12-1:30 p.m. | 560 Evans Hall


Wiktor Mlynarski, MIT

Neuroscience Institute, Helen Wills


Processing of natural stimuli in sensory systems has been traditionally studied within two theoretical frameworks: probabilistic inference and efficient coding. Probabilistic inference specifies optimal strategies for learning about relevant properties of the environment from local and ambiguous sensory signals. Efficient coding provides a normative approach to study encoding of natural stimuli...   More >