TY - GEN
T1 - Explaining Neural Spike Activity for Simulated Bio-plausible Network through Deep Sequence Learning
AU - Kulkarni, Shruti R.
AU - Tabassum, Anika
AU - Lim, Seung Hwan
AU - Schuman, Catherine D.
AU - Theilman, Bradley H.
AU - Rothganger, Fred
AU - Wang, Felix
AU - Aimone, James B.
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - With significant improvements in large-scale simulations of brain models, there is a growing need to develop tools for rapid analysis and interpreting the simulation results. In this work, we explore the potential of sequential deep learning models to understand and explain the network dynamics among the neurons extracted from a large-scale neural simulation in STACS (Simulation Tool for Asynchronous Cortical Stream). Our method employs a representative neuroscience model that abstracts the cortical dynamics with a reservoir of randomly connected spiking neurons with a low stable spike firing rate throughout the simulation duration. We subsequently analyze the spike dynamics of the simulated spiking neural network through an autoencoder model and an attention-based mechanism.
AB - With significant improvements in large-scale simulations of brain models, there is a growing need to develop tools for rapid analysis and interpreting the simulation results. In this work, we explore the potential of sequential deep learning models to understand and explain the network dynamics among the neurons extracted from a large-scale neural simulation in STACS (Simulation Tool for Asynchronous Cortical Stream). Our method employs a representative neuroscience model that abstracts the cortical dynamics with a reservoir of randomly connected spiking neurons with a low stable spike firing rate throughout the simulation duration. We subsequently analyze the spike dynamics of the simulated spiking neural network through an autoencoder model and an attention-based mechanism.
KW - Machine Learning
KW - Neural Algorithms
KW - Neuromorphic simulations
KW - Spiking Neural Networks
UR - http://www.scopus.com/inward/record.url?scp=85196740740&partnerID=8YFLogxK
U2 - 10.1109/NICE61972.2024.10549689
DO - 10.1109/NICE61972.2024.10549689
M3 - Conference contribution
AN - SCOPUS:85196740740
T3 - 2024 IEEE Neuro Inspired Computational Elements Conference, NICE 2024 - Proceedings
BT - 2024 IEEE Neuro Inspired Computational Elements Conference, NICE 2024 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE Neuro Inspired Computational Elements Conference, NICE 2024
Y2 - 23 April 2024 through 26 April 2024
ER -