55. assimilation of biophysical neuronal dynamics in neuromorphic vlsi

Department: Bioengineering
Faculty Advisor(s): Gert Cauwenberghs

Primary Student
Name: Jun Wang
Email: juw087@ucsd.edu
Phone: 858-534-6938
Grad Year: 2019

Student Collaborators
Abraham Akinin, akinin@gmail.com | Daniel Breen, dnlbreen@gmail.com

Abstract
Emulating the biophysics of neuronal dynamics and behavior offers a principled analysis-by-synthesis approach towards understanding mechanisms of brain function. Here we report on a set of procedures assimilating and emulating neurobiological data on a neuromorphic very large-scale integrated (VLSI) circuit. The analog VLSI chip, Neurodyn, features 384 digitally programmable parameters specifying for 4 generalized Hodgkin-Huxley neurons coupled through 12 conductance based chemical synapses, reversal potentials, conductances, and spline regressed gating variables. In one set of experiments, we assimilated membrane potential recorded form one of the neurons on the chip to the model structure upon which NeuroDyn was designed and the known current input sequence, arriving at the programmed parameters save for model errors due to analog imperfections in the chip fabrication. In a related set of experiments, we emulated songbird individual neuron dynamics on NeuroDyn by estimating and configuring parameters extracted using data assimilation (DA) from intracellular neural recordings. Faithful emulation of biological dynamics will enable the use of NeuroDyn as a tool to probe electrical and molecular properties of functional neural circuits. Application of the chip to neurobiological data may help to understand the effects of neuromodulators or neurodegenerative diseases on ion channel kinetics, and may further provide insights into the relationship between molecular properties of neurons and the emergence of different spike patterns or different brain behaviors.

Industry Application Area(s)
Control Systems | Electronics/Photonics | Life Sciences/Medical Devices & Instruments

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