Reconstructing fMRI BOLD signals arising from cerebellar granule neurons - Comparing GLM and balloon models

Chaitanya Medini, Giovanni Naldi, Bipin Nair, Egidio D'Angelo, Shyam Diwakar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Understanding the relationship between fMRI BOLD and underlying neuronal activity has been crucial to connect circuit behavior to cognitive functions. In this paper, we modeled fMRI BOLD reconstructions with general linear model and balloon modeling using biophysical models of rat cerebellum granular layer and stimuli spike trains of various response times. Linear convolution of the hemodynamic response function with the known spiking information reconstructed activity similar to experimental BOLD-like signals with the limitation of short stimuli trains. Balloon model through Volterra kernels gave seemingly similar results to that of general linear model. Our main goal in this study was to understand the activity role of densely populated clusters through BOLD-like reconstructions given neuronal responses and by varying response times for the whole stimulus duration.

Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
PublisherInstitute of Electrical and Electronics Engineers Inc.
Volume2015-September
ISBN (Print)9781479919604, 9781479919604, 9781479919604, 9781479919604
DOIs
Publication statusPublished - Sep 28 2015
EventInternational Joint Conference on Neural Networks, IJCNN 2015 - Killarney, Ireland
Duration: Jul 12 2015Jul 17 2015

Other

OtherInternational Joint Conference on Neural Networks, IJCNN 2015
Country/TerritoryIreland
CityKillarney
Period7/12/157/17/15

Keywords

  • Balloon Model
  • BOLD
  • Cerebellum
  • Computational Neuroscience
  • fMRI
  • GLM

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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