Evidence map›Paper›PMID 34104383›Full record

Articlei-Perception

Unique Neural Activity Patterns Among Lower Order Cortices and Shared Patterns Among Higher Order Cortices During Processing of Similar Shapes With Different Stimulus Types.

Zhen Li, Hiroaki Shigemasu

Abstract read
In one paragraph

Article in i-Perception. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

2 authors.

Zhen LiDepartment of Psychology, The University of Hong Kong, Hong Kong, China; Graduate School of Engineering, Kochi University of Technology, Kochi, Japan.ORCID https://orcid.org/0000-0001-8433-6393
Hiroaki ShigemasuSchool of Information, Kochi University of Technology, Kochi, Japan.ORCID https://orcid.org/0000-0002-6156-0488

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We investigated the neural mechanism of the processing of three-dimensional (3D) shapes defined by disparity and perspective. We measured blood oxygenation level-dependent signals as participants viewed and classified 3D images of convex-concave shapes. According to the cue (disparity or perspective) and element type (random dots or black and white dotted lines), three types of stimuli were used: random dot stereogram, black and white dotted lines with perspective, and black and white dotted lines with binocular disparity. The blood oxygenation level-dependent images were then classified by multivoxel pattern analysis. To identify areas selective to shape, we assessed convex-concave classification accuracy with classifiers trained and tested using signals evoked by the same stimulus type (same cue and element type). To identify cortical regions with similar neural activity patterns regardless of stimulus type, we assessed the convex-concave classification accuracy of transfer classification in which classifiers were trained and tested using different stimulus types (different cues or element types). Classification accuracy using the same stimulus type was high in the early visual areas and subregions of the intraparietal sulcus (IPS), whereas transfer classification accuracy was high in the dorsal subregions of the IPS. These results indicate that the early visual areas process the specific features of stimuli, whereas the IPS regions perform more generalized processing of 3D shapes, independent of a specific stimulus type.

Indexed as

depth cuesfunctional magnetic resonance imagingmultivoxel pattern analysisshape representation

Identifiers

PMID34104383
PMCPMC8161881

What OpenQuestion holds

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LicenceCC BY
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.