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Record W2094731623 · doi:10.1167/13.9.783

Complex object representations in the medial temporal lobe: Feature conjunctions and view invariance

2013· article· en· W2094731623 on OpenAlexaff
Jonathan Erez, Rhodri Cusack, Wilfrid S. Kendall, Morgan D. Barense

Bibliographic record

VenueJournal of Vision · 2013
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsWestern UniversityToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsPerirhinal cortexTemporal lobePerceptionPsychologyTemporal cortexInvariant (physics)Artificial intelligencePattern recognition (psychology)Computer scienceVisual ObjectsCognitive psychologyRepresentation (politics)NeuroscienceMathematics

Abstract

fetched live from OpenAlex

The medial temporal lobe (MTL) is known to be vital for memory function. However, recent studies have shown that a specific set of brain structures within the MTL are also important for perception. For example, studies of amnesic patients with damage to MTL structures indicated that these patients performed poorly on perceptual tasks, specifically, when discriminating between items that shared overlapping features. It was suggested that one MTL structure in particular, the perirhinal cortex (PRC), should be considered part of the representational hierarchy in the ventral visual stream (VVS) and is responsible for representing the complex conjunction of features that comprise objects, perhaps at a view-invariant level. In this study we investigated how the different features comprising complex objects are represented throughout the VVS up to and including the MTL, and at what stage the representations become view-invariant. To address these questions, we used multi-voxel pattern analysis (MVPA) of fMRI data, a technique that has gained prominence for its ability to probe the underlying neural representations of visual information. Participants completed a one-back task involving novel objects that were comprised of either one (e.g., A, B, or C), two (e.g., AB, AC, BC), or three features (e.g., ABC) and were presented from one of two possible viewpoints. This allowed us to examine the degree to which neural representation of a pair of objects depended only on the sum of their parts (i.e., A+BC=AB+C), or whether the specific feature conjunctions within objects were encoded. A searchlight analysis using this method indicated that anterior regions of the VVS, including the PRC, coded the complex conjunctions of features comprising the objects, over and above the individual features themselves. Moreover, we found evidence to suggest that the conjunctive representations in PRC were view-invariant. Meeting abstract presented at VSS 2013

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.072
GPT teacher head0.352
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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