Evidence map›Paper›PMID 35782087›Full record

SynthesisFrontiers in computational neuroscience2022

Recent Trends in Non-invasive Neural Recording Based Brain-to-Brain Synchrony Analysis on Multidisciplinary Human Interactions for Understanding Brain Dynamics: A Systematic Review.

Tahnia Nazneen, Iffath Binta Islam, Md Sakibur Rahman Sajal, Wasifa Jamal, M Ashraful Amin, Ravi Vaidyanathan, Tom Chau, Khondaker A Mamun

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in computational neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Trial
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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

8 authors.

Tahnia NazneenAdvanced Intelligent Multidisciplinary Systems Lab, Institute of Advanced Research, United International University, Dhaka, Bangladesh.
Iffath Binta IslamAdvanced Intelligent Multidisciplinary Systems Lab, Institute of Advanced Research, United International University, Dhaka, Bangladesh.
Md Sakibur Rahman SajalAdvanced Intelligent Multidisciplinary Systems Lab, Institute of Advanced Research, United International University, Dhaka, Bangladesh.
Wasifa JamalBrainCo Inc., Somerville, MA, United States.
M Ashraful AminDepartment of Computer Science and Engineering, Independent University, Dhaka, Bangladesh.
Ravi VaidyanathanDepartment of Mechanical Engineering, Imperial College London, London, United Kingdom.
Tom ChauInstitute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada.
Khondaker A MamunAdvanced Intelligent Multidisciplinary Systems Lab, Institute of Advanced Research, United International University, Dhaka, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study of brain-to-brain synchrony has a burgeoning application in the brain-computer interface (BCI) research, offering valuable insights into the neural underpinnings of interacting human brains using numerous neural recording technologies. The area allows exploring the commonality of brain dynamics by evaluating the neural synchronization among a group of people performing a specified task. The growing number of publications on brain-to-brain synchrony inspired the authors to conduct a systematic review using the PRISMA protocol so that future researchers can get a comprehensive understanding of the paradigms, methodologies, translational algorithms, and challenges in the area of brain-to-brain synchrony research. This review has gone through a systematic search with a specified search string and selected some articles based on pre-specified eligibility criteria. The findings from the review revealed that most of the articles have followed the social psychology paradigm, while 36% of the selected studies have an application in cognitive neuroscience. The most applied approach to determine neural connectivity is a coherence measure utilizing phase-locking value (PLV) in the EEG studies, followed by wavelet transform coherence (WTC) in all of the fNIRS studies. While most of the experiments have control experiments as a part of their setup, a small number implemented algorithmic control, and only one study had interventional or a stimulus-induced control experiment to limit spurious synchronization. Hence, to the best of the authors' knowledge, this systematic review solely contributes to critically evaluating the scopes and technological advances of brain-to-brain synchrony to allow this discipline to produce more effective research outcomes in the remote future.

Indexed as

behavioral cognitionbrain dynamicsbrain-to-brain synchronyinterbrain synchronyneurosciencepsychologysynchrony measure

Identifiers

PMID35782087
PMCPMC9245014

What OpenQuestion holds

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LicenceCC BY
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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.