Evidence map›Paper›PMID 30850689›Full record

ArticleScientific reports2019

Intrinsic timescales of sensory integration for motion perception.

Woochul Choi, Se-Bum Paik

Abstract read
In one paragraph

Article in Scientific reports, 2019. 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
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.

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

2 authors.

Woochul ChoiDepartment of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.ORCID 0000-0002-9937-1404
Se-Bum PaikDepartment of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea. sbpaik@kaist.ac.kr.ORCID 0000-0002-4078-305X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A subject-specific process of perceptual decision making is of importance to how the brain translates its interpretation of sensory information into behavior. In particular, a number of studies reported substantial variation across the observers' decision behavior, which may reflect different profiles of evidence accumulated by each individual. However, a detailed profile of perceptual integration has not yet been verified from human behavioral data. To address the issue, we precisely measured the time course of sensory integration, as the "sensory integration kernel" of subjects, using a coherence-varying motion discrimination task. We found that each subject has a distinct profile of sensory integration. We observed that kernel size (maximum sensory integration interval) is consistent within subjects, independent of external stimuli conditions. The observed kernel could accurately predict subject-specific perceptual behaviors and explain the inter-individual variation of observed behaviors. Surprisingly, the performance of most subjects did not improve in proportion to increased duration of the stimulus, but was maximized when the stimulus duration matched their kernel size. We also found that the observed kernel size was strongly correlated with the subject-specific perceptual characteristics for illusory motion. Our results suggest that perceptual decisions arise from intrinsic decision dynamics, and on individual timescales of sensory integration.

Indexed as

AdultBrainDecision MakingDiscrimination, PsychologicalFemaleHumansMaleMotionMotion PerceptionPhotic StimulationReaction TimeSensationSensory Receptor CellsYoung Adult

Identifiers

PMID30850689
PMCPMC6408463

What OpenQuestion holds

Textmetadata
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.