YKavli October Lunch

YKavli October Lunch

By Kavli Institute for Brain and Mind, UC San Diego

Date and time

Wednesday, October 9, 2019 · 12 - 2pm PDT

Location

KIBM Conference Room - AP&M 1882 (located in the Annex)

Description

The Kavli Institute for Brain and Mind (KIBM) hosts meetings for early career researchers to help foster their research community at UCSD. Our goal is to bring early career researchers (non-faculty) together so they can meet, network and share research. This event is open only to EARLY CAREER RESEARCHERS (grad student/ postdoc/ project scientist).

This luncheon consists of a few short, informal talks by early career researchers, followed by a networking social hour. Lunch will be provided by KIBM.

Talks

1. Chaitanya Ryali - Bio-Inspired Hashing for Unsupervised Similarity Search

Chaitanya Ryali is a Ph.D. student in Computer Science and Engineering at UC San Diego. He's broadly interested in problems at the intersection of neuroscience, psychology, and artificial intelligence.

The fruit fly Drosophila’s olfactory circuit has inspired a new locality sensitive hashing (LSH) algorithm, FlyHash. In contrast with classical LSH algorithms that produce low dimensional hash codes, FlyHash produces sparse high-dimensional hash codes and has also been shown to have superior empirical performance compared to classical LSH algorithms in similarity search. However, FlyHash uses random projections and cannot learn from data. Building on inspiration from FlyHash and the ubiquity of sparse expansive representations in neurobiology, our work proposes a novel hashing algorithm BioHash that produces sparse high dimensional hash codes in a data-driven manner. We show that BioHash outperforms previously published benchmarks for various hashing methods. Since our learning algorithm is based on a local and biologically plausible synaptic plasticity rule, our work provides evidence for the proposal that LSH might be a computational reason for the abundance of sparse expansive motifs in a variety of biological systems. We also propose a convolutional variant BioConvHash that further improves performance. From the perspective of computer science, BioHash and BioConvHash are fast, scalable and yield compressed binary representations that are useful for similarity search. This is joint work with John Hopfield and Dmitry Krotov.

2. Richard McCosh - Neural Mechanisms for Turning off Reproduction During Stress

Richard McCosh is a postdoc in Obstetrics, Gynecology & Reproductive Sciences at UC San Diego.

Reproduction and gonadal steroid secretion are dependent upon adequate luteinizing hormone (LH) secretion which is regulated by numerous physiological and environmental inputs. Impaired LH secretion, such as that caused by stress, can cause infertility and lead to musculoskeletal, cardiovascular, and mental health issues (all of which are supported by gonadal steroids). Therefore, the neural processes that regulate LH secretion, and its impairment during stress, are of great interest. Our recent work has demonstrated that metabolic stress inhibits LH secretion in the mouse via impaired kisspeptin signaling. In this presentation, our ongoing work testing a brainstem-hypothalamic neurocircuit for the suppression of LH will be discussed.


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Chair: Julia Adrian

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