Evidence map›Paper›PMID 29494213›Full record

ReviewAnnual review of biomedical engineering2018

Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics.

Bin He, Abbas Sohrabpour, Emery Brown, Zhongming Liu

Abstract readReview
In one paragraph

Review in Annual review of biomedical engineering, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 115 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
115citing papers in PubMed, 1 pooled it
–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

115 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Tracking electrophysiological signatures of Alzheimer's disease: a systematic review of multimodal studies.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Pooled it
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  17. Mapping epileptogenic brain using a unified spatial-temporal-spectral source imaging framework.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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55 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Bin HeDepartment of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA; email: bhe1@andrew.cmu.edu.
Abbas SohrabpourDepartment of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota 55455, USA.
Emery BrownInstitute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
Zhongming LiuWeldon School of Biomedical Engineering, School of Electrical and Computer Engineering, and Purdue Institute of Integrative Neuroscience, Purdue University, West Lafayette, Indiana 47906, USA.

Funding

Cannabinoid-based therapy and approaches to quantify pain in sickle cell diseaseU01HL117664 · NHLBI · UNIVERSITY OF MINNESOTA · PI GUPTA, KALPNA · 2013 to 2018
$9.6M
Electrophysiological Source Imaging of Partial EpilepsyR01NS096761 · NINDS · UNIVERSITY OF MINNESOTA · PI HE, BIN · 2016 to 2025
$3.6M
Electrophysiological source imaging guided transcranial focused ultrasoundRF1MH114233 · NIMH · UNIVERSITY OF MINNESOTA · PI HE, BIN · 2017 to 2017
$2.4M
Multimodal Hyperspectral Imaging of Brain Activity and ConnectivityR01MH104402 · NIMH · PURDUE UNIVERSITY · PI LIU, ZHONGMING · 2014 to 2018
$2.3M
Mind-body awareness training and brain-computer interfaceR01AT009263 · NCCIH · UNIVERSITY OF MINNESOTA · PI HE, BIN · 2016 to 2020
$2.0M
Integrative Training Program in NeuroimagingT32EB008389 · NIBIB · UNIVERSITY OF MINNESOTA · PI CHEN, WEI · 2008 to 2019
$1.4M
Spatio-temporal Dynamic Imaging of Seizure SourcesR01EB021027 · NIBIB · UNIVERSITY OF MINNESOTA · PI HE, BIN · 2016 to 2020
$1.3M
CRCNS: Spatiotemporal imaging study of the mechanisms of binocular rivalryR01EY023101 · NEI · UNIVERSITY OF MINNESOTA · PI HE, BIN · 2012 to 2014
$1.1M
NCCIH NIH HHS R01 AT009263NEI NIH HHS R01 EY023101NHLBI NIH HHS U01 HL117664NIBIB NIH HHS R01 EB021027NIBIB NIH HHS T32 EB008389NIMH NIH HHS R01 MH104402NIMH NIH HHS RF1 MH114233NINDS NIH HHS R01 NS096761
6 · The paper itself

Abstract

Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.

Indexed as

AlgorithmsAnimalsBayes TheoremBrainElectroencephalographyElectrophysiologyHumansMagnetic Resonance ImagingMagnetoencephalographyNeurosciencesSignal Processing, Computer-AssistedSoftwareEEGelectrophysiological source imagingfunctional connectivityinverse problemMEGsource localization

Identifiers

PMID29494213
PMCPMC7941524

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.