MENU
MAR 11, 2020 12:00 PM PDT

PANEL: Cracking a Neural Circuit's Function Through High-Resolution Physiology, Connectomics, and Computational Modeling

Presented at: Neuroscience 2020
C.E. Credits: P.A.C.E. CE Florida CE
Speakers
  • Associate Professor of Computational Neuroscience in the Department of Physiology and Biophysics at Weill Cornell Medicine
    BIOGRAPHY
  • Joel Keizer Chair in Theoretical and Computational Biology at UC Davis, and Professor in the Departments of Neurobiology, Physiology, & Behavior and the Department of Ophthalmology
    BIOGRAPHY
  • Anthony B. Evnin Professor in the Neuroscience Institute and Computer Science Department at Princeton University, and Chief Research Scientist at Samsung Electronics
    BIOGRAPHY
  • Research Associate at the Princeton Neuroscience Institute
    BIOGRAPHY

Abstract

Mechanistic understanding of neural systems is daunting to achieve in large part due to the heterogeneity of the neuronal elements in both form and function and the complexity of the circuits formed by these elements. In this talk, we provide an update on our efforts to understand a neural system with a multi-faceted approach combining large-scale imaging of neuronal activity, reconstruction and analysis of network connectivity, and computational models of network function. We focus our work on the oculomotor neural integrator of the zebrafish, a circuit involved in the control of eye position that has been demonstrated to perform a mathematical integral of its inputs.  We identified through calcium imaging and targeted ablations neurons involved in planning, initiating, and maintaining changes in eye position. We used serial-section electron microscopy and crowd-sourced imaged analysis to reconstruct the circuit formed by these neurons and many of their synaptic partners. Computational analysis revealed a strongly-recurrent module in the circuit, consistent with theoretical predictions for the circuit mechanism of neural integration.  A whole-circuit, neural network model built from the underlying connectome reproduced the encoding of eye position seen experimentally across multiple species. We conclude with thoughts on how this approach can be extended to other domains.

Learning Objectives:

1. Understand how functional imaging, connectomic, and computational modeling approaches can be combined to investigate circuit mechanisms

2. Understand the role of recurrent excitation and mutual inhibition in generating and coordinating persistent neural activity


Show Resources
You May Also Like
SEP 14, 2021 7:00 AM PDT
C.E. CREDITS
SEP 14, 2021 7:00 AM PDT
Date: September 14, 2021 Time: 7am PDT, 10am EDT, 4pm CEST A conventional thermal cycler has long been a commodity product in the lab and end-point PCR techniques can be completed almost wit...
NOV 30, 2021 10:00 AM PST
C.E. CREDITS
NOV 30, 2021 10:00 AM PST
Date: November 30, 2021 Time: 10:00am (PDT), 1:00pm (EDT) The prevalence of thyroid disease worldwide has served as a catalyst for healthcare providers to study various tools and methods to...
AUG 11, 2021 10:00 AM PDT
C.E. CREDITS
AUG 11, 2021 10:00 AM PDT
Date: August 11, 2021 Time: 10:00am (PDT), 1:00pm (EDT) Quality can never be assumed, is never automatic, and requires the long-term commitment of the laboratory, staff, and manufacturers. L...
OCT 12, 2021 9:00 AM PDT
C.E. CREDITS
OCT 12, 2021 9:00 AM PDT
Date: October 12, 2021 Time: 9:00am (PDT), 12:00pm (EDT) SCIEX’s next-generation Biologics Explorer software is an innovative platform for the comprehensive and deep characterization o...
OCT 20, 2021 10:00 AM PDT
C.E. CREDITS
OCT 20, 2021 10:00 AM PDT
Date: October 20, 2021 Time:10:00am (PDT), 1:00pm (EDT) As the prevalence of Diabetes continues to rise in many areas across the globe, healthcare providers continue to look for methods that...
NOV 17, 2021 8:00 AM PST
C.E. CREDITS
NOV 17, 2021 8:00 AM PST
Date: November 17, 2021 Time: 8:00am (PDT), 11:00am (EDT) From waste disposal to promising biomarkers and therapeutic agents, exosomes and other extracellular vesicles are valuable in resear...
Loading Comments...
Show Resources