Spontaneous network activity <35 Hz accounts for variability in stimulus-induced gamma responses
Jan Hirschmann,
Sylvain Baillet,
Mark Woolrich,
Alfons Schnitzler,
Diego Vidaurre,
Esther Florin
Affiliations
Jan Hirschmann
Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University, 40225, Düsseldorf, Germany; Corresponding author. Heinrich-Heine-Universität Düsseldorf, Institut für Klinische Neurowissenschaften, Medizinische Psychologie, Universitätsstr. 1, 40225, Düsseldorf, Germany.
Sylvain Baillet
McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montréal, QC, H3A2B4, Canada
Mark Woolrich
Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, Oxford Centre for Human Brain Activity (OHBA), University of Oxford, Oxford, OX3 7JX, United Kingdom; Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, Oxford Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, OX3 9DU, United Kingdom
Alfons Schnitzler
Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University, 40225, Düsseldorf, Germany; Center for Movement Disorders and Neuromodulation, Department of Neurology, Medical Faculty, Heinrich Heine University, 40225, Düsseldorf, Germany
Diego Vidaurre
Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, Oxford Centre for Human Brain Activity (OHBA), University of Oxford, Oxford, OX3 7JX, United Kingdom
Esther Florin
Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University, 40225, Düsseldorf, Germany
Gamma activity is thought to serve several cognitive processes, including attention and memory. Even for the simplest stimulus, the occurrence of gamma activity is highly variable, both within and between individuals. The sources of this variability, however, are largely unknown.In this paper, we address one possible cause: the cross-frequency influence of spontaneous, whole-brain network activity on visual stimulus processing. By applying Hidden Markov modelling to MEG data, we reveal that the trial-averaged gamma response to a moving grating depends on the individual network dynamics, inferred from slower brain activity (<35 Hz) in the absence of stimulation (resting-state and task baseline). In addition, we demonstrate that modulations of network activity in task baseline influence the gamma response on the level of trials.In summary, our results reveal a cross-frequency and cross-session association between gamma responses induced by visual stimulation and spontaneous network activity. These findings underline the dependency of visual stimulus processing on the individual, functional network architecture.
