Evidence map›Paper›PMID 28549921›Full record

ArticleVision research2017

Two representations of a high-dimensional perceptual space.

Jonathan D Victor, Syed M Rizvi, Mary M Conte

Abstract read
In one paragraph

Article in Vision research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Perceptual thresholds for differences in CT noise texture.Journal of medical imaging (Bellingham, Wash.) · 2024
    Article
  3. The Geometry of Low- and High-Level Perceptual Spaces.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    Article
  4. Discrimination of textures with spatial correlations and multiple gray levels.Journal of the Optical Society of America. A, Optics, image science, and vision · 2023
    Article
  5. Article
  6. Article
  7. Article
  8. 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

3 authors.

Jonathan D VictorFeil Family Brain and Mind Research Institute, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, United States. Electronic address: jdvicto@med.cornell.edu.
Syed M RizviFeil Family Brain and Mind Research Institute, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, United States.
Mary M ConteFeil Family Brain and Mind Research Institute, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, United States.

Funding

CENTRAL PROCESSING OF VISUAL INFORMATIONR01EY007977 · NEI · WEILL MEDICAL COLL OF CORNELL UNIV · PI Jonathan D Victor · 1989 to 2026
$9.0M
NEI NIH HHS R01 EY007977
6 · The paper itself

Abstract

A perceptual space is a mental workspace of points in a sensory domain that supports similarity and difference judgments and enables further processing such as classification and naming. Perceptual spaces are present across sensory modalities; examples include colors, faces, auditory textures, and odors. Color is perhaps the best-studied perceptual space, but it is atypical in two respects. First, the dimensions of color space are directly linked to the three cone absorption spectra, but the dimensions of generic perceptual spaces are not as readily traceable to single-neuron properties. Second, generic perceptual spaces have more than three dimensions. This is important because representing each distinguishable point in a high-dimensional space by a separate neuron or population is unwieldy; combinatorial strategies may be needed to overcome this hurdle. To study the representation of a complex perceptual space, we focused on a well-characterized 10-dimensional domain of visual textures. Within this domain, we determine perceptual distances in a threshold task (segmentation) and a suprathreshold task (border salience comparison). In N=4 human observers, we find both quantitative and qualitative differences between these sets of measurements. Quantitatively, observers' segmentation thresholds were inconsistent with their uncertainty determined from border salience comparisons. Qualitatively, segmentation thresholds suggested that distances are determined by a coordinate representation with Euclidean geometry. Border salience comparisons, in contrast, indicated a global curvature of the space, and that distances are determined by activity patterns across broadly tuned elements. Thus, our results indicate two representations of this perceptual space, and suggest that they use differing combinatorial strategies. SIGNIFICANCE STATEMENT: To move from sensory signals to decisions and actions, the brain carries out a sequence of transformations. An important stage in this process is the construction of a "perceptual space" - an internal workspace of sensory information that captures similarities and differences, and enables further processing, such as classification and naming. Perceptual spaces for color, faces, visual and haptic textures and shapes, sounds, and odors (among others) are known to exist. How such spaces are represented is at present unknown. Here, using visual textures as a model, we investigate this. Psychophysical measurements suggest roles for two combinatorial strategies: one based on projections onto coordinate-like axes, and one based on patterns of activity across broadly tuned elements scattered throughout the space.

Indexed as

AdultFemaleHumansMaleMiddle AgedModels, NeurologicalPattern Recognition, VisualPsychophysicsSpace PerceptionVisual PerceptionYoung AdultBorder salienceIntermediate visionLocal featuresMultipoint correlationsVisual textures

Identifiers

PMID28549921
PMCPMC6002902

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Registered trials

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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.