Rxivist logo

Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 70,658 bioRxiv papers from 308,473 authors.

Inferring multi-scale neural mechanisms with brain network modelling

By Michael Schirner, Anthony Randal McIntosh, Viktor Jirsa, Gustavo Deco, Petra Ritter

Posted 28 Jun 2017
bioRxiv DOI: 10.1101/157263 (published DOI: 10.7554/elife.28927)

The neurophysiological processes underlying non-invasive brain activity measurements are not well understood. Here, we developed a novel connectome-based brain network model that integrates individual structural and functional data with neural population dynamics to support multi-scale neurophysiological inference. Simulated populations were linked by structural connectivity and, as a novelty, driven by electroencephalography (EEG) source activity. Simulations not only predicted subjects’ individual resting-state functional magnetic resonance imaging (fMRI) time series and spatial network topologies over 20 minutes of activity, but more importantly, they also revealed precise neurophysiological mechanisms that underlie and link six empirical observations from different scales and modalities: (1) slow resting-state fMRI oscillations, (2) spatial topologies of functional connectivity networks, (3) excitation-inhibition balance, (4, 5) pulsed inhibition on short and long time scales, and (6) fMRI power-law scaling. These findings underscore the potential of this new modelling framework for general inference and integration of neurophysiological knowledge to complement empirical studies.

Download data

  • Downloaded 406 times
  • Download rankings, all-time:
    • Site-wide: 28,951 out of 70,658
    • In bioinformatics: 3,803 out of 6,919
  • Year to date:
    • Site-wide: 38,190 out of 70,658
  • Since beginning of last month:
    • Site-wide: 50,876 out of 70,658

Altmetric data


Downloads over time

Distribution of downloads per paper, site-wide


PanLingua

Sign up for the Rxivist weekly newsletter! (Click here for more details.)


News