Knowledge of cortical rhythms represents an important aspect of modern neuroscience, to understand how the brain realizes its functions. Recent data suggest that different regions in the brain may exhibit distinct rhythms when perturbed by Transcranial Magnetic Stimulation (TMS) (Rosanova et al., 2009) and that these rhythms can change due to the connectivity among regions. In this context, neural mass models can be very useful to simulate specific aspects of electrical brain activity and, above all, to analyze and identify the overall frequency content of EEG in a cortical region of interest (ROI). In this work we implemented a model of connectivity among cortical regions (Ursino, Cona and Zavaglia, 2010) to fit the impulse responses in three ROIs during an experiment of TMS stimulation. In particular we investigated Brodmann Area (BA) 19 (occipital lobe), BA 7 (parietal lobe) and BA 6 (frontal lobe). Results show that the model can reproduce the natural rhythms of the three regions quite well, acting on a few internal parameters. Moreover, model can explain most rhythm changes induced by stimulation of another region, by using just a few long-range connectivity parameters among ROIs.)

Cortical rhythms induced by TMS stimulation: analysis with a neural mass model

CONA, FILIPPO;URSINO, MAURO;ZAVAGLIA, MELISSA;
2010

Abstract

Knowledge of cortical rhythms represents an important aspect of modern neuroscience, to understand how the brain realizes its functions. Recent data suggest that different regions in the brain may exhibit distinct rhythms when perturbed by Transcranial Magnetic Stimulation (TMS) (Rosanova et al., 2009) and that these rhythms can change due to the connectivity among regions. In this context, neural mass models can be very useful to simulate specific aspects of electrical brain activity and, above all, to analyze and identify the overall frequency content of EEG in a cortical region of interest (ROI). In this work we implemented a model of connectivity among cortical regions (Ursino, Cona and Zavaglia, 2010) to fit the impulse responses in three ROIs during an experiment of TMS stimulation. In particular we investigated Brodmann Area (BA) 19 (occipital lobe), BA 7 (parietal lobe) and BA 6 (frontal lobe). Results show that the model can reproduce the natural rhythms of the three regions quite well, acting on a few internal parameters. Moreover, model can explain most rhythm changes induced by stimulation of another region, by using just a few long-range connectivity parameters among ROIs.)
2010
Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation
205
211
F. Cona; M. Ursino; M. Zavaglia; M. Rosanova
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/100890
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