Evidence map›Paper›PMID 35280282›Full record

ArticleFrontiers in neurology2022

Weighted Blind Source Separation Can Decompose the Frequency Mismatch Response by Deviant Concatenation: An MEG Study.

Teppei Matsubara, Steven Stufflebeam, Sheraz Khan, Jyrki Ahveninen, Matti Hämäläinen, Yoshinobu Goto, Toshihiko Maekawa, Shozo Tobimatsu, Kuniharu Kishida

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 98% of its field
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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

9 authors at 6 institutions in 2 countries.

Teppei MatsubaraAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States.
Steven StufflebeamAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States.
Sheraz KhanAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States.
Jyrki AhveninenAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States.
Matti HämäläinenAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States.
Yoshinobu GotoDepartment of Physiology, School of Medicine, International University of Health and Welfare, Narita, Japan.
Toshihiko MaekawaDepartment of Psychiatry, Amekudai Hospital, Naha, Japan.
Shozo TobimatsuDepartment of Orthoptics, Faculty of Medicine, Fukuoka International University of Health and Welfare, Fukuoka, Japan.
Kuniharu KishidaGifu University, Gifu, Japan.
Harvard University · USAthinoula A. Martinos Center for Biomedical Imaging · USFukuoka International University · JPGifu University · JPInternational University of Health and Welfare · JPNaha City Hospital · JP

Funding

Mapping the intrinsic functional organization of auditory cortex in individual subjects using 7T MRIR01DC017991 · NIDCD · MASSACHUSETTS GENERAL HOSPITAL · PI AHVENINEN, JYRKI · 2019 to 2023
$4.0M
Decoding parametric attributes of auditory working memories from human brain activityR01DC016915 · NIDCD · MASSACHUSETTS GENERAL HOSPITAL · PI AHVENINEN, JYRKI · 2018 to 2022
$3.0M
Non-invasive measures of multisensory cortical feedforward and feedback influencesR01DC016765 · NIDCD · MASSACHUSETTS GENERAL HOSPITAL · PI AHLFORS, SEPPO PENTTI, AHVENINEN, JYRKI · 2018 to 2022
$2.7M
NIDCD NIH HHS R01 DC016765NIDCD NIH HHS R01 DC016915NIDCD NIH HHS R01 DC017991
6 · The paper itself

Abstract

The mismatch response (MMR) is thought to be a neurophysiological measure of novel auditory detection that could serve as a translational biomarker of various neurological diseases. When recorded with electroencephalography (EEG) or magnetoencephalography (MEG), the MMR is traditionally extracted by subtracting the event-related potential/field (ERP/ERF) elicited in response to "deviant" sounds that occur randomly within a train of repetitive "standard" sounds. However, there are several problems with such a subtraction, which include increased noise and the neural adaptation problem. On the basis of the original theory underlying MMR (i.e., the memory-comparison process), the MMR should be present only in deviant epochs. Therefore, we proposed a novel method called weighted-

Indexed as

blind source separation (BSS)deviant concatenationindependent component analysis (ICA)magnetoencephalography (MEG)mismatch response (MMR)time-delayed correlationT/k (fractional) type of decorrelation methodweighted blind source separation

Identifiers

PMID35280282
PMCPMC8916481
OpenAlexW4214718216

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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.