The coupling between the spatial and temporal scales of neural processes revealed by a joint time-vertex connectome spectral analysis
Joan Rué-Queralt,
Valentina Mancini,
Vincent Rochas,
Caren Latrèche,
Peter J. Uhlhaas,
Christoph M. Michel,
Gijs Plomp,
Stephan Eliez,
Patric Hagmann
Affiliations
Joan Rué-Queralt
Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland; Perceptual Networks Lab, Department of Psychology, University of Fribourg, Fribourg, Switzerland
Valentina Mancini
Developmental Imaging and Psychopathology Laboratory, University of Geneva School of Medicine, Geneva, Switzerland; Corresponding author.
Vincent Rochas
Functional Brain Mapping Laboratory, Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland; Human Neuroscience Platform, Fondation Campus Biotech Geneva, Switzerland
Caren Latrèche
Developmental Imaging and Psychopathology Laboratory, University of Geneva School of Medicine, Geneva, Switzerland
Peter J. Uhlhaas
Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, Scotland, United Kingdom; Department of Child and Adolescent Psychiatry, Psychosomatic Medicine and Psychotherapy, Charité Universitätsmedizin, Berlin, Germany
Christoph M. Michel
Functional Brain Mapping Laboratory, Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland
Gijs Plomp
Perceptual Networks Lab, Department of Psychology, University of Fribourg, Fribourg, Switzerland
Stephan Eliez
Developmental Imaging and Psychopathology Laboratory, University of Geneva School of Medicine, Geneva, Switzerland; Department of Genetic Medicine and Development, University of Geneva School of Medicine, Geneva, Switzerland
Patric Hagmann
Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland
Brain oscillations are produced by the coordinated activity of large groups of neurons and different rhythms are thought to reflect different modes of information processing. These modes, in turn, are known to occur at different spatial scales. Nevertheless, how these rhythms support different spatial modes of information processing at the brain scale is not yet fully understood. Here we use ''Joint Time-Vertex Spectral Analysis'' to characterize the joint spectral content of brain activity both in time (temporal frequencies) and in space over the connectivity graph (spatial connectome harmonics). This method allows us to characterize the relationship between spatially localized or distributed neural processes on one side and their respective temporal frequency bands in source-reconstructed M/EEG signals. We explore this approach on two different datasets, an auditory steady-state response (ASSR) and a visual grating task. Our results suggest that different information processing mechanisms are carried out at different frequency bands: while spatially distributed activity (which may also be interpreted as integration) specifically occurs at low temporal frequencies (alpha and theta) and low graph spatial frequencies, localized electrical activity (i.e., segregation) is observed at high temporal frequencies (high and low gamma) over restricted high spatial graph frequencies. Crucially, the estimated contribution of the distributed and localized neural activity predicts performance in a behavioral task, demonstrating the neurophysiological relevance of the joint time-vertex spectral representation.
