Evidence map›Paper›PMID 40484327›Full record

ArticleNeuroImage2025

Investigating the neurovascular coupling across multiple motor execution and imagery conditions: a whole-brain EEG-informed fMRI analysis.

Elena Bondi, Yidan Ding, Yisha Zhang, Eleonora Maggioni, Bin He

Abstract read
In one paragraph

Article in NeuroImage, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Elena BondiDepartment of Biomedical Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA; Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy.
Yidan DingDepartment of Biomedical Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA.
Yisha ZhangDepartment of Biomedical Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA.
Eleonora MaggioniDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy; Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122, Milan, Italy.
Bin HeDepartment of Biomedical Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA. Electronic address: bhe1@andrew.cmu.edu.

Funding

Electrophysiological Source Imaging of Partial EpilepsyR01NS096761 · NINDS · UNIVERSITY OF MINNESOTA · PI HE, BIN · 2016 to 2025
$3.6M
Electrophysiology-Compatible Wearable Transcranial Focused Ultrasound Neuromodulation Array ProbesRF1NS131069 · NINDS · CARNEGIE-MELLON UNIVERSITY · PI HE, BIN · 2023 to 2023
$3.6M
Imaging Epilepsy Sources with Biophysically Constrained Deep Neural NetworksR01NS127849 · NINDS · CARNEGIE-MELLON UNIVERSITY · PI BIN HE · 2023 to 2026
$2.4M
Characterization of in vivo neuronal and inter-neuronal responses to transcranial focused ultrasoundR01NS124564 · NINDS · CARNEGIE-MELLON UNIVERSITY · PI HE, BIN · 2021 to 2021
$2.0M
Characterization of in vivo neuronal and inter-neuronal responses to transcranial focused ultrasoundRF1NS124564 · NINDS · CARNEGIE-MELLON UNIVERSITY · PI HE, BIN · 2025 to 2025
$571k
NINDS NIH HHS R01 NS096761NINDS NIH HHS R01 NS124564NINDS NIH HHS R01 NS127849NINDS NIH HHS RF1 NS124564NINDS NIH HHS RF1 NS131069
6 · The paper itself

Abstract

The complementary strengths of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have driven extensive research into integrating these two noninvasive modalities to better understand the neural mechanisms underlying cognitive, sensory, and motor functions. However, the precise neural patterns associated with motor functions, especially imagined movements, remain unclear. Specifically, the correlations between electrophysiological responses and hemodynamic activations during executed and imagined movements have not been fully elucidated at a whole-brain level. In this study, we employed a unified EEG-informed fMRI approach on concurrent EEG-fMRI data to map hemodynamic changes associated with dynamic EEG temporal features during motor-related brain activities. We localized and differentiated the hemodynamic activations corresponding to continuous EEG temporal dynamics across multiple motor execution and imagery tasks. Validation against conventional block fMRI analysis demonstrated high precision in identifying regions specific to motor activities, underscoring the accuracy of the EEG-driven model. Beyond the expected sensorimotor activations, the integrated analysis revealed supplementary coactivated regions showing significant negative covariation between blood oxygenation level-dependent (BOLD) activities and sensorimotor EEG alpha power, including the cerebellum, frontal, and temporal regions. These findings confirmed both the colocalization of EEG and fMRI activities in sensorimotor regions and a negative covariation between EEG alpha band power and BOLD changes. Moreover, the results provide novel insights into neurovascular coupling during motor execution and imagery on a brain-wide scale, advancing our understanding of the neural dynamics underlying motor functions.

Indexed as

BrainBrain MappingElectroencephalographyImaginationMagnetic Resonance ImagingMotor ActivityNeurovascular CouplingAdultFemaleHumansMaleYoung AdultEEG-informed fMRIMotor executionMotor imageryNeural correlatesSimultaneous EEG-fMRI

Identifiers

PMID40484327
PMCPMC12515077

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.