BME DISTINGUISHED RESEARCH SEMINAR SERIES
September 25, 2024
9:30-10:20 am, MJIS 2001 and via ZOOM
ZOOM LINK:
https://us02web.zoom.us/j/87382040456?pwd=cCGi2aEvgQ5nz6lGXTMwqunY0a65JY.1
Unlocking Intelligence: Insights from Basal Dendritic Computations for Advancing Neural Information Processing and Neuro-inspired AI
Krishna Jayant
Leslie A. Geddes Assistant Professor of Biomedical Engineering
Abstract:
Probing multiplexed basal dendritic computations is significant for understanding how neurons process information, which can directly inform advancements in computation and future neuro-inspired
AI systems. Basal dendrites of layer 5 cortical pyramidal neurons exhibit Na+ and N-methyl-D-aspartate receptor (NMDAR) regenerative spikes and are uniquely poised to influence somatic output. Nevertheless, due to technical limitations, how multibranch
basal dendritic integration shapes and enables multiplexed barcoding of synaptic streams remains poorly mapped. Here, I will describe my group's efforts in combining 3D two-photon holographic transmitter uncaging, whole-cell dynamic clamp, and biophysical
modeling to reveal how synchronously activated synapses (distributed and clustered) across multiple basal dendritic branches are multiplexed under quiescent and
in vivo-like conditions. I will show that while dendritic regenerative Na+ spikes promote millisecond somatic spike precision, distributed synaptic inputs and NMDAR spikes regulate gain. These concomitantly occurring dendritic nonlinearities
enable multiplexed information transfer amid an ongoing noisy background, including under back-propagating voltage resets, by
barcoding the axo-somatic spike structure. Our results unveil a multibranch dendritic integration framework in which dendritic nonlinearities are critical for multiplexing different spatial-temporal synaptic input patterns, enabling optimal feature
binding. Drawing from these biological principles, we envision new algorithms that mimic the brain’s efficiency and adaptability, focusing on principles such as parallel processing, feature binding, and functioning in noisy environments. These insights will
deepen our understanding of neuronal integration and pave the way for more sophisticated AI architectures.
Bio:
Krishna Jayant is an assistant professor at Purdue University's Weldon School of Biomedical Engineering. His laboratory’s research focuses on delivering biophysically based accounts
of behaviorally relevant computations using novel electrical and optical neurotechnologies. Projects in the lab cover various topics, including the examination of synaptic and dendritic computations in individual neurons and network-wide circuit computations
that underlie sensorimotor integration, including synucleinopathies. Dr. Jayant completed his graduate training in electrical and computer engineering at Cornell University, where he worked with Dr. Edwin Kan on bioelectronics. He subsequently completed postdoctoral
training at Columbia University with Dr. Rafael Yuste, Dr. Ken Shepard, and Dr. Ozgur Sahin, researching cutting-edge neurotechnologies to probe synaptic and dendritic biophysics. In addition to the NIH Director’s New Innovator Award, Dr. Jayant has been recognized
as an NIH NIBIB Trailblazer awardee, a Human Frontiers Science Young Investigator grant awardee, a Ralph E. Powe Junior Faculty Enhancement Award, and is also a recipient of an Air Force Office of Scientific Research DURIP award.
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BME Host: Estelle Park ~
Jo Gelfand
Intra/Extramural Relations Administrator
Purdue University
Weldon School of Biomedical Engineering
206 S. Martin Jischke Drive
West Lafayette, IN 47907-2032
765-494-2996
