How delays matter in an oscillatory whole-brain spiking-neuron network model for MEG alpha-rhythms at rest.
In recent years the study of the intrinsic brain dynamics in a relaxed awake state in the absence of any specific task has gained increasing attention, as spontaneous neural activity has been found to be highly structured at a large scale. This so called resting-state activity has been found to be comprised by nonrandom spatiotemporal patterns and fluctuations, and several Resting-State Networks (RSN) have been found in BOLD-fMRI as well as in MEG signal power envelope correlations. The underlying anatomical connectivity structure between areas of the brain has been identified as being a key to the observed functional network connectivity, but the mechanisms behind this are still underdetermined. Theoretical large-scale brain models for fMRI data have corroborated the importance of the connectome in shaping network dynamics, while the importance of delays and noise differ between studies and depend on the models' specific dynamics. In the current study, we present a spiking neuron network model that is able to produce noisy, distributed alpha-oscillations, matching the power peak in the spectrum of group resting-state MEG recordings. We studied how well the model captured the inter-node correlation structure of the alpha-band power envelopes for different delays between brain areas, and found that the model performs best for propagation delays inside the physiological range (5-10 m/s). Delays also shift the transition from noisy to bursting oscillations to higher global coupling values in the model. Thus, in contrast to the asynchronous fMRI state, delays are important to consider in the presence of oscillation.
Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona 08018, Spain. Electronic address: tristan.nakagawa@upf.edu.
Tristan T
TT
Nakagawa
Oxford Ctr. For Human Brain Activity, Univ. of Oxford, Oxford, United Kingdom.
Mark
M
Woolrich
Oxford Ctr. For Human Brain Activity, Univ. of Oxford, Oxford, United Kingdom.
Henry
H
Luckhoo
Department of Psychiatry, University of Oxford, Oxford, UK; Center of Functionally Integrative Neuroscience (CFIN), Aarhus University, Denmark.
Morten
M
Joensson
Oxford Ctr. For Human Brain Activity, Univ. of Oxford, Oxford, United Kingdom.
Hamid
H
Mohseni
Department of Psychiatry, University of Oxford, Oxford, UK; Center of Functionally Integrative Neuroscience (CFIN), Aarhus University, Denmark.
Morten L
ML
Kringelbach
Institut de Neurosciences des Systèmes UMR INSERM 1106, Aix-Marseille Universitè, 13005 Marseille, France.
Viktor
V
Jirsa
Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona 08018, Spain; Institució Catalana de la Recerca i Estudis Avançats, Universitat Pompeu Fabra, Barcelona 08010, Spain.
Gustavo
G
Deco
D000328:Adult; D000513:Alpha Rhythm / Q000502:physiology*; D001921:Brain / Q000502:physiology*; D063132:Connectome / Q000379:methods; D005260:Female; D006801:Humans; D015225:Magnetoencephalography; D008297:Male; D008875:Middle Aged; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology; D012146:Rest / Q000502:physiology; D055815:Young Adult
Alpha-oscillations; Delays; MEG; Resting-state model; SFA; Spike-frequency adaptation; Spontaneous alpha