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Basis profile curve identification to understand electrical stimulation effects in human brain networks.

ABSTRACT: Brain networks can be explored by delivering brief pulses of electrical current in one area while measuring voltage responses in other areas. We propose a convergent paradigm to study brain dynamics, focusing on a single brain site to observe the average effect of stimulating each of many other brain sites. Viewed in this manner, visually-apparent motifs in the temporal response shape emerge from adjacent stimulation sites. This work constructs and illustrates a data-driven approach to determine characteristic spatiotemporal structure in these response shapes, summarized by a set of unique "basis profile curves" (BPCs). Each BPC may be mapped back to underlying anatomy in a natural way, quantifying projection strength from each stimulation site using simple metrics. Our technique is demonstrated for an array of implanted brain surface electrodes in a human patient. This framework enables straightforward interpretation of single-pulse brain stimulation data, and can be applied generically to explore the diverse milieu of interactions that comprise the connectome.

SUBMITTER: Miller KJ

PROVIDER: S-EPMC8412306 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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Basis profile curve identification to understand electrical stimulation effects in human brain networks.

Miller Kai J KJ Müller Klaus-Robert KR Hermes Dora D

PLoS computational biology 20210902 9

Brain networks can be explored by delivering brief pulses of electrical current in one area while measuring voltage responses in other areas. We propose a convergent paradigm to study brain dynamics, focusing on a single brain site to observe the average effect of stimulating each of many other brain sites. Viewed in this manner, visually-apparent motifs in the temporal response shape emerge from adjacent stimulation sites. This work constructs and illustrates a data-driven approach to determine ...[more]

PMID: 34473701

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Project description:Transcranial Direct Current Stimulation (tDCS) is a non-invasive, low-cost, well-tolerated technique producing lasting modulation of cortical excitability. Behavioral and therapeutic outcomes of tDCS are linked to the targeted brain regions, but there is little evidence that current reaches the brain as intended. We aimed to: (1) validate a computational model for estimating cortical electric fields in human transcranial stimulation, and (2) assess the magnitude and spread of cortical electric field with a novel High-Definition tDCS (HD-tDCS) scalp montage using a 4 × 1-Ring electrode configuration. In three healthy adults, Transcranial Electrical Stimulation (TES) over primary motor cortex (M1) was delivered using the 4 × 1 montage (4 × cathode, surrounding a single central anode; montage radius ~3 cm) with sufficient intensity to elicit a discrete muscle twitch in the hand. The estimated current distribution in M1 was calculated using the individualized MRI-based model, and compared with the observed motor response across subjects. The response magnitude was quantified with stimulation over motor cortex as well as anterior and posterior to motor cortex. In each case the model data were consistent with the motor response across subjects. The estimated cortical electric fields with the 4 × 1 montage were compared (area, magnitude, direction) for TES and tDCS in each subject. We provide direct evidence in humans that TES with a 4 × 1-Ring configuration can activate motor cortex and that current does not substantially spread outside the stimulation area. Computational models predict that both TES and tDCS waveforms using the 4 × 1-Ring configuration generate electric fields in cortex with comparable gross current distribution, and preferentially directed normal (inward) currents. The agreement of modeling and experimental data for both current delivery and focality support the use of the HD-tDCS 4 × 1-Ring montage for cortically targeted neuromodulation.

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Dataset Information

Basis profile curve identification to understand electrical stimulation effects in human brain networks.

Publications

Basis profile curve identification to understand electrical stimulation effects in human brain networks.

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