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.

Reconstructing fMRI BOLD signals arising from cerebellar granule neurons : comparing GLM and balloon models / C. Medini, G. Naldi, B. Nair, E. D'Angelo, S. Diwakar - In: 2015 International Joint Conference on Neural Networks (IJCNN)Piscataway : Institute of Electrical and Electronics Engineers, 2015. - ISBN 9781479919604. - pp. 1-6 (( convegno International Joint Conference on Neural Networks (IJCNN) tenutosi a Killarney, Ireland nel 2015.

Reconstructing fMRI BOLD signals arising from cerebellar granule neurons : comparing GLM and balloon models

G. Naldi
Secondo
;
2015

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.
Balloon Model; BOLD; Cerebellum; Computational Neuroscience; fMRI; GLM; Software; Artificial Intelligence
Settore MAT/08 - Analisi Numerica
2015
Centro di Ricerca Interdisciplinare su Modellistica Matematica, Analisi Statistica e Simulazione Computazionale per la Innovazione Scientifica e Tecnologica ADAMSS
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/462971
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