A visual encoding model links magnetoencephalography signals to neural synchrony in human cortex

Eline R. Kupers, Noah C. Benson, Jonathan Winawer

Research output: Contribution to journalArticlepeer-review

Abstract

Synchronization of neuronal responses over large distances is hypothesized to be important for many cortical functions. However, no straightforward methods exist to estimate synchrony non-invasively in the living human brain. MEG and EEG measure the whole brain, but the sensors pool over large, overlapping cortical regions, obscuring the underlying neural synchrony. Here, we developed a model from stimulus to cortex to MEG sensors to disentangle neural synchrony from spatial pooling of the instrument. We find that synchrony across cortex has a surprisingly large and systematic effect on predicted MEG spatial topography. We then conducted visual MEG experiments and separated responses into stimulus-locked and broadband components. The stimulus-locked topography was similar to model predictions assuming synchronous neural sources, whereas the broadband topography was similar to model predictions assuming asynchronous sources. We infer that visual stimulation elicits two distinct types of neural responses, one highly synchronous and one largely asynchronous across cortex.

Original languageEnglish (US)
Article number118655
JournalNeuroImage
Volume245
DOIs
StatePublished - Dec 15 2021

Keywords

  • Computational models
  • Evoked field
  • Evoked potential
  • MEG
  • Stimulus-locked response
  • Synchrony
  • Visual cortex

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

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