CoChat
Sign Up
Cited by 963Visual perception and processing mechanismsFace Recognition and PerceptionMemory and Neural Mechanisms

Shape representation in the inferior temporal cortex of monkeys

Open access
Logothetis, Nikos K., Pauls, Jon, Poggio, Tomaso·1995·Current Biology
DOI 10.1016/s0960-9822(95)00108-4
Open this paper in CoChat — free accountOpen PDF

Abstract

Background The inferior temporal cortex (IT) of the monkey has long been known to play an essential role in visual object recognition. Damage to this area results in severe deficits in perceptual learning and object recognition, without significantly affecting basic visual capacities. Consistent with these ablation studies is the discovery of IT neurons that respond to complex two-dimensional visual patterns, or objects such as faces or body parts. What is the role of these neurons in object recognition? Is such a complex configurational selectivity specific to biologically meaningful objects, or does it develop as a result of extensive exposure to any objects whose identification relies on subtle shape differences? If so, would IT neurons respond selectively to recently learned views of features of novel objects? The present study addresses this question by using combined psychophysical and electrophysiological experiments, in which monkeys learned to classify and recognize computer-generated three-dimensional objects.Results A population of IT neurons was found that responded selectively to views of previously unfamiliar objects. The cells discharged maximally to one view of an object, and their response declined gradually as the object was rotated away from this preferred view. No selective responses were ever encountered for views that the animal systematically failed to recognize. Most neurons also exhibited orientation-dependent responses during view-plane rotations. Some neurons were found to be tuned around two views of the same object, and a very small number of cells responded in a view-invariant manner. For the five different objects that were used extensively during the training of the animals, and for which behavioral performance became view-independent, multiple cells were found that were tuned around different views of the same object. A number of view-selective units showed response invariance for changes in the size of the object or the position of its image within the parafovea.Conclusion Our results suggest that IT neurons can develop a complex receptive field organization as a consequence of extensive training in the discrimination and recognition of objects. None of these objects had any prior meaning for the animal, nor did they resemble anything familiar in the monkey's environment. Simple geometric features did not appear to account for the neurons' selective responses. These findings support the idea that a population of neurons--each tuned to a different object aspect, and each showing a certain degree of invariance to image transformations--may, as an ensemble, encode at least some types of complex three-dimensional objects. In such a system, several neurons may be active for any given vantage point, with a single unit acting like a blurred template for a limited neighborhood of a single view.

Integrity signals

Registry

Crossref · 10.1016/s0960-9822(95)00108-4

Cites

40 of 40 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

  • IT neurons are able to learn new arbitrary shapes and arbitrary pairings of stimuli.

    “IT neurons are able to learn new arbitrary shapes (Logothetis et al., 1995), and arbitrary pairings of stimuli (Sakai and Miyashita, 1991), which might be an analogue of learning letters and of linking arbitrarily related upper- and lowercase letters.”

    From Specialization within the ventral stream: the case for the visual word form area (2004) · cites this paper as Logothetis et al., 1995

  • From V1 to IT, there is an increase in invariance to position and scale and, in parallel, an increase in the size of the receptive fields and in the complexity of the optimal stimuli for the neurons.

    “From V1 to IT, there is an increase in invariance to position and scale (1, 2, 4-6) and in parallel, an increase in the size of the receptive fields (2, 4) as well as in the complexity of the optimal stimuli for the neurons (2, 3, 7).”

    From A feedforward architecture accounts for rapid categorization (2007) · cites this paper as [6]

  • Plasticity and learning are probably present at all stages and certainly at the level of IT and PFC.

    “Finally, plasticity and learning are probably present at all stages and certainly at the level of IT (6) and PFC.”

    From A feedforward architecture accounts for rapid categorization (2007) · cites this paper as [6]

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Logothetis, N. K., Pauls, J., & Poggio, T.
Affiliations
  • Baylor College of Medicine (US)
  • Massachusetts Institute of Technology (US)
Corresponding author
Poggio, Tomaso
ORCID
Venue
Current Biology
Publisher
Elsevier BV
Published
1995-05
Volume
5
Issue
5
Pages
552-563
ISSN
0960-9822 (ISSN-L)
DOI
10.1016/s0960-9822(95)00108-4
OpenAlex
W2142756981
Cited by
963
References
40
Citations by year
2026: 7 · 2025: 17 · 2024: 15 · 2023: 11 · 2022: 11 · 2021: 24 · 2020: 18 · 2019: 33 · 2018: 20 · 2017: 19 · 2016: 36 · 2015: 24 · 2014: 48 · 2013: 35 · 2012: 39
FWCI
12.54
Type
journal article
Language
en
Open access
Licence
Locations
  • Current Biology (publishedVersion)
  • PubMed (publishedVersion)
  • MPG.PuRe (Max Planck Society) (submittedVersion)
Funders
  • National Institutes of Health (5r01ey010089-03)
  • National Eye Institute (1R01EY10089-01)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
Keywords
inferior temporal cortex, object recognition, shape representation, perceptual learning, orientation selectivity, viewpoint invariance, receptive field organization, visual object classification
MeSH terms
Animals, Form Perception, Image Processing, Computer-Assisted, Macaca mulatta, Neurons, Temporal Lobe

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review