The generation of rhythms within a cortical region: analysis of a neural mass model.
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The generation of rhythms within a cortical region: analysis of a neural mass model. / Ursino, Mauro; Cona, Filippo; Zavaglia, Melissa.
in: NEUROIMAGE, Jahrgang 52, Nr. 3, 3, 2010, S. 1080-1094.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung
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TY - JOUR
T1 - The generation of rhythms within a cortical region: analysis of a neural mass model.
AU - Ursino, Mauro
AU - Cona, Filippo
AU - Zavaglia, Melissa
PY - 2010
Y1 - 2010
N2 - Rhythms in brain electrical activity are assumed to play a significant role in many cognitive and perceptual processes. It is thus of great value to analyze these rhythms and their mutual relationships in large scale models of cortical regions. In the present work, we modified the neural mass model by Wendling et al. (Eur. J. Neurosci. 15 (2002) 1499-1508) by including a new inhibitory self-loop among GABAA,fast interneurons. A theoretical analysis was performed to demonstrate that, thanks to this loop, GABAA,fast interneurons can produce a gamma rhythm in the power spectral density (PSD) even without the participation of the other neural populations. Then, the model of a whole cortical region, built upon four interconnected neural populations (pyramidal cells, excitatory, GABAA,slow and GABAA,fast interneurons) was investigated by changing the internal connectivity parameters. Results show that different rhythm combinations (beta and gamma, alpha and gamma, or a wide spectrum) can be obtained within the same region by simply altering connectivity values, without the need to change synaptic kinetics. Finally, two or three cortical regions were connected by using different topologies of long range connections. Results show that long-range connections directed from pyramidal neurons to GABAA,fast interneurons are the most efficient to transmit rhythms from one region to another. In this way, PSD with three or four peaks can be obtained using simple connectivity patterns. The model can be of value to gain a deeper insight into the mechanisms involved in the generation of gamma rhythms and provide a better understanding of cortical EEG spectra.
AB - Rhythms in brain electrical activity are assumed to play a significant role in many cognitive and perceptual processes. It is thus of great value to analyze these rhythms and their mutual relationships in large scale models of cortical regions. In the present work, we modified the neural mass model by Wendling et al. (Eur. J. Neurosci. 15 (2002) 1499-1508) by including a new inhibitory self-loop among GABAA,fast interneurons. A theoretical analysis was performed to demonstrate that, thanks to this loop, GABAA,fast interneurons can produce a gamma rhythm in the power spectral density (PSD) even without the participation of the other neural populations. Then, the model of a whole cortical region, built upon four interconnected neural populations (pyramidal cells, excitatory, GABAA,slow and GABAA,fast interneurons) was investigated by changing the internal connectivity parameters. Results show that different rhythm combinations (beta and gamma, alpha and gamma, or a wide spectrum) can be obtained within the same region by simply altering connectivity values, without the need to change synaptic kinetics. Finally, two or three cortical regions were connected by using different topologies of long range connections. Results show that long-range connections directed from pyramidal neurons to GABAA,fast interneurons are the most efficient to transmit rhythms from one region to another. In this way, PSD with three or four peaks can be obtained using simple connectivity patterns. The model can be of value to gain a deeper insight into the mechanisms involved in the generation of gamma rhythms and provide a better understanding of cortical EEG spectra.
KW - Electroencephalography
KW - Models, Theoretical
KW - Neurons/physiology
KW - Models, Neurological
KW - Neural Networks (Computer)
KW - Cerebral Cortex/physiology
KW - Electroencephalography
KW - Models, Theoretical
KW - Neurons/physiology
KW - Models, Neurological
KW - Neural Networks (Computer)
KW - Cerebral Cortex/physiology
M3 - SCORING: Journal article
VL - 52
SP - 1080
EP - 1094
JO - NEUROIMAGE
JF - NEUROIMAGE
SN - 1053-8119
IS - 3
M1 - 3
ER -