Reconstructing fMRI BOLD signals arising from cerebellar granule neurons : comparing GLM and balloon models
Contributo in Atti di convegno
Data di Pubblicazione:
2015
Citazione:
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.
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.
Tipologia IRIS:
03 - Contributo in volume
Keywords:
Balloon Model; BOLD; Cerebellum; Computational Neuroscience; fMRI; GLM; Software; Artificial Intelligence
Elenco autori:
C. Medini, G. Naldi, B. Nair, E. D'Angelo, S. Diwakar
Link alla scheda completa:
Titolo del libro:
2015 International Joint Conference on Neural Networks (IJCNN)