Evidence map›Paper›PMID 29867412›Full record

ArticleFrontiers in human neuroscience2018

Cortical Power-Density Changes of Different Frequency Bands in Visually Guided Associative Learning: A Human EEG-Study.

András Puszta, Xénia Katona, Balázs Bodosi, Ákos Pertich, Diána Nyujtó, Gábor Braunitzer, Attila Nagy

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Article in Frontiers in human neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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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

7 citing papers in PubMed.

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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

7 authors.

András PusztaSensorimotor Lab, Department of Physiology, Faculty of Medicine, University of Szeged, Szeged, Hungary.
Xénia KatonaSensorimotor Lab, Department of Physiology, Faculty of Medicine, University of Szeged, Szeged, Hungary.
Balázs BodosiSensorimotor Lab, Department of Physiology, Faculty of Medicine, University of Szeged, Szeged, Hungary.
Ákos PertichSensorimotor Lab, Department of Physiology, Faculty of Medicine, University of Szeged, Szeged, Hungary.
Diána NyujtóSensorimotor Lab, Department of Physiology, Faculty of Medicine, University of Szeged, Szeged, Hungary.
Gábor BraunitzerLaboratory for Perception & Cognition and Clinical Neuroscience (LPCCN), National Institute of Psychiatry and Addictions at Nyírő Gyula Hospital, Budapest, Hungary.
Attila NagySensorimotor Lab, Department of Physiology, Faculty of Medicine, University of Szeged, Szeged, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The computer-based Rutgers Acquired Equivalence test (RAET) is a widely used paradigm to test the function of subcortical structures in visual associative learning. The test consists of an acquisition (pair learning) and a test (rule transfer) phase, associated with the function of the basal ganglia and the hippocampi, respectively. Obviously, such a complex task also requires cortical involvement. To investigate the activity of different cortical areas during this test, 64-channel EEG recordings were recorded in 24 healthy volunteers. Fast-Fourier and Morlet wavelet convolution analyses were performed on the recordings. The most robust power changes were observed in the theta (4-7 Hz) and gamma (>30 Hz) frequency bands, in which significant power elevation was observed in the vast majority of the subjects, over the parieto-occipital and temporo-parietal areas during the acquisition phase. The involvement of the frontal areas in the acquisition phase was remarkably weaker. No remarkable cortical power elevations were found in the test phase. In fact, the power of the alpha and beta bands was significantly decreased over the parietooccipital areas. We conclude that the initial acquisition of the image pairs requires strong cortical involvement, but once the pairs have been learned, neither retrieval nor generalization requires strong cortical contribution.

Indexed as

acquired equivalenceassociative learningEEGFFTtime-frequency analysis

Identifiers

PMID29867412
PMCPMC5951962

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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.