Published September 13, 2022 | Version v1
Dataset Open

Data from: Resolving the mesoscopic missing link: biophysical modeling of EEG from cortical columns in primates

  • 1. Vanderbilt University
  • 2. Florida International University
  • 3. York University

Description

Event-related potentials (ERP) are among the most widely measured indices for studying human cognition. While their timing and magnitude provide valuable insights, their usefulness is limited by our understanding of their neural generators at the circuit level. Inverse source localization offers insights into such generators, but their solutions are not unique. To address this problem, scientists have assumed the source space generating such signals comprises a set of discrete equivalent current dipoles, representing the activity of small cortical regions. Based on this notion, theoretical studies have employed forward modeling of scalp potentials to understand how changes in circuit-level dynamics translate into macroscopic ERPs. However, experimental validation is lacking because it requires in vivo measurements of intracranial brain sources. Laminar local field potentials (LFP) offer a mechanism for estimating intracranial current sources. Yet, a theoretical link between LFPs and intracranial brain sources is missing. Here, we present a forward modeling approach for estimating mesoscopic intracranial brain sources from LFPs and predict their contribution to macroscopic ERPs. We evaluate the accuracy of this LFP-based representation of brain sources utilizing synthetic laminar neurophysiological measurements and then demonstrate the power of the approach in vivo to clarify the source of a representative cognitive ERP component. To that end, LFP was measured across the cortical layers of visual area V4 in macaque monkeys performing an attention demanding task. We show that area V4 generates dipoles through layer-specific transsynaptic currents that biophysically recapitulate the ERP component through the detailed forward modeling. The constraints imposed on EEG production by this method also revealed an important dissociation between computational and biophysical contributors. As such, this approach represents an important bridge between laminar microcircuitry, through the mesoscopic activity of cortical columns to the patterns of EEG we measure at the scalp.

Notes

Data are formatted for use in MATLAB. ReadMe contains information pertinent to the dataset variables.

Funding provided by: National Eye Institute
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000053
Award Number: P30EY008126

Funding provided by: National Eye Institute
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000053
Award Number: R01EY019882

Funding provided by: National Eye Institute
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000053
Award Number: R01EY008890

Funding provided by: National Eye Institute
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000053
Award Number: R01EY027402

Funding provided by: NIH Office of the Director
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000052
Award Number: S10OD021771

Funding provided by: National Eye Institute
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000053
Award Number: T32EY007135

Funding provided by: National Eye Institute
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000053
Award Number: F31EY031293

Funding provided by: Natural Sciences and Engineering Research Council of Canada
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100000038
Award Number: RGPIN-2022-04592

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