Evidence map›Paper›PMID 28794195›Full record

ArticleJournal of neurophysiology2017

Object comparison in the lateral intraparietal area.

Wei Song Ong, Koorosh Mirpour, James W Bisley

Abstract read
In one paragraph

Article in Journal of neurophysiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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.

Wei Song OngDepartment of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, California.
Koorosh MirpourDepartment of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, California.
James W BisleyDepartment of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, California; jbisley@mednet.ucla.edu.ORCID 0000-0002-2841-0306

Funding

The Neural Mechanisms Underlying the Guidance of Visual AttentionR01EY019273 · NEI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BISLEY, JAMES · 2008 to 2017
$3.4M
NEI NIH HHS R01 EY019273
6 · The paper itself

Abstract

We can search for and locate specific objects in our environment by looking for objects with similar features. Object recognition involves stimulus similarity responses in ventral visual areas and task-related responses in prefrontal cortex. We tested whether neurons in the lateral intraparietal area (LIP) of posterior parietal cortex could form an intermediary representation, collating information from object-specific similarity map representations to allow general decisions about whether a stimulus matches the object being looked for. We hypothesized that responses to stimuli would correlate with how similar they are to a sample stimulus. When animals compared two peripheral stimuli to a sample at their fovea, the response to the matching stimulus was similar, independent of the sample identity, but the response to the nonmatch depended on how similar it was to the sample: the more similar, the greater the response to the nonmatch stimulus. These results could not be explained by task difficulty or confidence. We propose that LIP uses its known mechanistic properties to integrate incoming visual information, including that from the ventral stream about object identity, to create a dynamic representation that is concise, low dimensional, and task relevant and that signifies the choice priorities in mental matching behavior.

Indexed as

Pattern Recognition, VisualAnimalsFovea CentralisMacaca mulattaMaleNeuronsParietal LobeVisual Fieldsdorsal streamobject recognitionparietal cortexvision

Identifiers

PMID28794195
PMCPMC5646194

What OpenQuestion holds

Textmetadata
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.