4.8 Article

Dynamical consequences of regional heterogeneity in the brain's transcriptional landscape

Journal

SCIENCE ADVANCES
Volume 7, Issue 29, Pages -

Publisher

AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/sciadv.abf4752

Keywords

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Funding

  1. Spanish national research project - Spanish Ministry of Science, Innovation and Universities (MCIU), State Research Agency (AEI) [PID2019-105772GB-I00 MCIU AEI]
  2. HBP SGA3 Human Brain Project Specific Grant [945539]
  3. EU H2020 FET Flagship programme
  4. SGR Research Support Group support - Catalan Agency for Management of University and Research Grants (AGAUR) [101017716, 2017 SGR 1545]
  5. EU H2020 FET Proactive programme [860563]
  6. EU H2020 MSCA-ITN Innovative Training Networks
  7. CECH The Emerging Human Brain Cluster within the framework of the European Research Development Fund Operational Program of Catalonia 2014-2020 [001-P-001682]
  8. Brain-Connects: Brain Connectivity during Stroke Recovery and Rehabilitation - Fundacio La Marato TV3 [201725.33]
  9. Corticity, FLAG-ERA JTC 2017 - Spanish Ministry of Science, Innovation and Universities (MCIU), State Research Agency (AEI) [PCI2018-092891]
  10. Center for Music in the Brain - Danish National Research Foundation [DNRF117]
  11. Centre for Eudaimonia and Human Flourishing - Pettit and Carlsberg Foundations
  12. Sylvia and Charles Viertel Charitable Foundation
  13. National Health and Medical Research Council

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Transcriptional variations in excitatory and inhibitory receptor gene expression play a key role in shaping complex neuronal dynamics, yielding both ignition-like dynamics and a wide variance of regional activity time scales. This study demonstrates the viability of using transcriptomic data to constrain models of large-scale brain function.
Brain regions vary in their molecular and cellular composition, but how this heterogeneity shapes neuronal dynamics is unclear. Here, we investigate the dynamical consequences of regional heterogeneity using a biophysical model of whole-brain functional magnetic resonance imaging (MRI) dynamics in humans. We show that models in which transcriptional variations in excitatory and inhibitory receptor (E:I) gene expression constrain regional heterogeneity more accurately reproduce the spatiotemporal structure of empirical functional connectivity estimates than do models constrained by global gene expression profiles or MRI-derived estimates of myeloarchitecture. We further show that regional transcriptional heterogeneity is essential for yielding both ignition-like dynamics, which are thought to support conscious processing, and a wide variance of regional-activity time scales, which supports a broad dynamical range. We thus identify a key role for E:I heterogeneity in generating complex neuronal dynamics and demonstrate the viability of using transcriptomic data to constrain models of large-scale brain function.

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