Cited by 283Visual perception and processing mechanismsNeural and Behavioral Psychology StudiesFace Recognition and Perception

The DOI matches its Crossref record; 106 of the 109 references it cites were found in a registry or an index; none of the 36 sources its claims cite is checked for support yet.

Evidence Accumulation and the Moment of Recognition: Dissociating Perceptual Recognition Processes Using fMRI

Open access
Ploran, Elisabeth J., Nelson, Steven M., Velanova, Katerina, Donaldson, David I., Petersen, Steven E., Wheeler, Mark E.·2007·The Journal of Neuroscience

Abstract

Decision making can be conceptualized as the culmination of an integrative process in which evidence supporting different response options accumulates gradually over time. We used functional magnetic resonance imaging to investigate brain activity leading up to and during decisions about perceptual object identity. Pictures were revealed gradually and subjects signaled the time of recognition (T R ) with a button press. We examined the time course of T R -dependent activity to determine how brain regions tracked the timing of recognition. In several occipital regions, activity increased primarily as stimulus information increased, suggesting a role in lower-level sensory processing. In inferior temporal, frontal, and parietal regions, a gradual buildup in activity peaking in correspondence with T R suggested that these regions participated in the accumulation of evidence supporting object identity. In medial frontal cortex, anterior insula/frontal operculum, and thalamus, activity remained near baseline until T R , suggesting a relation to the moment of recognition or the decision itself. The findings dissociate neural processes that function in concert during perceptual recognition decisions.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

Using fMRI with gradually revealed pictures, this paper dissociates three neural profiles during perceptual recognition: sensory processors tracking stimulus information, accumulator regions whose activity builds up until recognition, and moment-of-recognition regions active only at the recognition decision. Recognition time (TR) systematically shifted onset/peak timing in accumulator and recognition regions, while sensory regions did not show TR-dependent onset changes.

Key findings

  • Behavioral: Exp1 (n=12) had 620/704 picture trials with recognition during steps 1–7; 564 (91.0%) were verified accurate. Exp2 (n=13) had 985/1148 trials with recognition before VoA; 852 (86.5%) later verified. Most correct recognitions occurred in TR4–7.
  • Cluster analysis of 73 Exp1 ROIs yielded four time-course clusters; the positive cluster contained 32 ROIs, later split by interpolation into sensory (5), accumulator (13), and moment-of-recognition (14) groups.
  • Sensory ROIs (posterior occipital) had onset times that changed little across TR4–7 (mean 5.5, 5.2, 4.8, 5.2 s) and the widest responses (FWHM 15.7, 15.2, 14.6, 15.3 s). Accumulator ROIs (occipital/fusiform, dlPFC, PPL) showed TR-dependent buildup: onset 7.1, 7.0, 8.2, 8.6 s; peak 14.8, 16.5, 18.3, 20.0 s; leading-edge slope decreased 0.13, 0.11, 0.10, 0.10. Moment-of-recognition ROIs (meFG/pre-SMA, ACC, aI/fO, thalamus) had markedly later onsets as TR increased (8.5, 12.0, 13.3, 14.3 s), peaks 14.2, 16.3, 18.3, 20.2 s, and narrowest widths (7.1, 4.8, 5.7, 5.4 s).
  • Statistical tests supported dissociation: onset showed a main effect of TR (F(2.5,73.4)=14.47, p<0.0001) and TR×region interaction (F(5.1,73.4)=10.91, p<0.0001); width differed by region type (F(2,29)=90.48, p<0.0001).

Methods

  • Two fMRI experiments with gradual unmasking of 233 grayscale images over eight revelation steps; participants pressed a button when they recognized the picture (TR) and again at full revelation if earlier recognition was correct (VoA). Exp1 used within-trial jitter; Exp2 removed within-trial jitter and added trials.
  • 31 right-handed native English speakers (18 female, age 19–29) began; 25 were analyzed after exclusions (12 Exp1, 13 Exp2). Imaging used a Siemens Allegra 3T scanner; data were analyzed with voxelwise GLM and repeated-measures ANOVA.
  • Exp1 identified 73 ROIs by comparing TR and VoA activity; Exp2 extracted TR-dependent time courses from those ROIs. Hierarchical cluster analysis (UPGMA; cophenetic r=0.8234) classified time courses, and linear interpolation quantified onset, peak, and FWHM.

Limitations

  • Stated: the authors could not perform trial-level analyses, so findings are too broad to test different accumulator models; the degree to which TR-dependent buildup reflects evidence accumulation per se is unclear and could be a byproduct of information processing.
  • Stated: the precise functional relationship between accumulator and moment-of-recognition regions is unknown, including whether decisions arise from accumulators or from regions active at the moment of recognition.
  • Evident from text: sample size after exclusions was modest (25 analyzed), some ROIs showed atypical or late responses possibly related to VoA rather than TR, and bottom-up stimulus-specific differences may have influenced recognition times.

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Integrity signals

Registry

Crossref · 10.1523/jneurosci.3522-07.2007

Cites

106 of 106 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

0 of 36 cited sources checked · 0 supported · 0 flagged

Show all 80 claims

  • Probably not a substantial claim. 27
  • It may state two separate claims as one. 18
  • The quote only partly states this claim. 1
42 of 42
  • The authors state this as an assumption.

    The data values between any two time points are adequately approximated by a linear fit between those two points.

    “Linear interpolation provided a straightforward procedure to quantify time course parameters across a variety of different types of response profile, while making the simple assumption that the data values between any two time points are adequately approximated by a linear fit between those two points.”
  • The paper relies on this without support.

    The time of recognition (TR) button press provides an estimate of the time of recognition.

    “This response provided an estimate of the time of recognition (T R ).”
  • The paper relies on this without support.

    The moment of recognition is a discrete event.

    “Because the moment of recognition is a discrete event, responses should occur transiently at T R (Fig. 2c).”
  • The paper relies on this without support.

    Accumulation and recognition are inherently associated with TR.

    “For example, because accumulation and recognition are inherently associated with T R , the time to peak activity for both should shift in time as a function of T R .”
  • The paper relies on this without support.

    Evidence gathering is a prolonged process.

    “Second, because evidence gathering is a prolonged process, time courses associated with accumulation should be more extended in time (i.e., greater width), albeit showing narrower widths than regions related to visual processing.”
  • The authors state this as an assumption.

    Accumulation has a role in integrating information over time.

    “First, because of a hypothetical role in integrating information over time, BOLD responses associated with accumulation should increase as soon as information related to a decision becomes available (e.g., earlier onset) (Fig. 2b).”
  • The paper relies on this without support.

    The time at which subjects press the button (TR) corresponds to the moment of perceptual recognition.

    “Subjects pressed a button when they could identify the picture with a reasonable degree of confidence, and again at VoA if earlier recognition had been correct.”
7 of 7

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Parahippocampal ROI is labeled left in the text and right in the table

    Minor

    The description of the seven-ROI late-positive cluster places its parahippocampal ROI on the left, whereas the corresponding Table 2 entry labels it right.

  • Response-hand counts do not match the Exp1 sample

    Minor

    The response-hand groups total 13 participants, but the paper says the analysis used Exp1 data, for which it reports 12 participants.

2 of 2

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Metadata

Authors
Ploran, E. J., Nelson, S. M., Velanova, K., Donaldson, D. I., Petersen, S. E., & Wheeler, M. E.
Affiliations
  • University of Pittsburgh (US)
  • University of Stirling (GB)
  • Washington University in St. Louis (US)
Venue
The Journal of Neuroscience
Published
2007-10-31
Volume
27
Issue
44
Pages
11912-11924
ISSN
  • 0270-6474 (ISSN-L)
  • 1529-2401
OpenAlex
W2088702666
Cited by
282
References
109
Citations by year
2026: 8 · 2025: 7 · 2024: 7 · 2023: 7 · 2022: 13 · 2021: 10 · 2020: 7 · 2019: 14 · 2018: 15 · 2017: 14 · 2016: 17 · 2015: 25 · 2014: 26 · 2013: 24 · 2012: 23
FWCI
8.48
Type
journal article
Language
en
Open access
Locations
  • Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • Stirling Online Research Repository (University of Stirling) (submittedVersion, public-domain)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
Keywords
perceptual identification, evidence accumulation, decision-making, object identity, visual object recognition, inferior temporal cortex, frontal cortex, parietal cortex, medial frontal cortex, anterior insula, frontal operculum, thalamus, occipital cortex
MeSH terms
Adult, Analysis of Variance, Brain Mapping, Decision Making, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Neuropsychological Tests, Oxygen, Pattern Recognition, Visual, Photic Stimulation, Psychomotor Performance, Reaction Time, Time Factors, Visual Cortex, Cluster Analysis, Linear Models

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