Evidence map›Paper›PMID 29566355›Full record

ArticleNeural computation2018

Predictive Coding in Area V4: Dynamic Shape Discrimination under Partial Occlusion.

Hannah Choi, Anitha Pasupathy, Eric Shea-Brown

Abstract read
In one paragraph

Article in Neural computation, 2018. 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
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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.

Hannah ChoiDepartment of Applied Mathematics and UW Institute for Neuroengineering, University of Washington, Seattle, WA 98195, U.S.A. hannahch@uw.edu.
Anitha PasupathyDepartment of Biological Structure, Washington National Primate Research Center, and UW Institute for Neuroengineering, University of Washington, Seattle, WA 98195, U.S.A. pasupat@uw.edu.
Eric Shea-BrownDepartment of Applied Mathematics, UW Institute for Neuroengineering, and UW Center for Computational Neuroscience, University of Washington, Seattle, WA 98195, and Allen Institute for Brain Science, Seattle, WA 98109, U.S.A. etsb@uw.edu.

Funding

Washington National Primate Research CenterP51OD010425 · OD · UNIVERSITY OF WASHINGTON · PI Mari Ostendorf · 2012 to 2026
$201.8M
YILMA SIV VACCINIA VACCINE TRIALP51RR000166 · NCRR · UNIVERSITY OF WASHINGTON · PI HU, SHIU-LOK · 1985 to 2011
$161.1M
Vision Research CoreP30EY001730 · NEI · UNIVERSITY OF WASHINGTON · PI MAUREEN E NEITZ · 1985 to 2026
$23.5M
The role of area V4 in the perception and recognition of visual objectsR01EY018839 · NEI · UNIVERSITY OF WASHINGTON · PI Anitha Pasupathy · 2009 to 2026
$9.0M
NCRR NIH HHS P51 RR000166NEI NIH HHS P30 EY001730NEI NIH HHS R01 EY018839NIH HHS P51 OD010425
6 · The paper itself

Abstract

The primate visual system has an exquisite ability to discriminate partially occluded shapes. Recent electrophysiological recordings suggest that response dynamics in intermediate visual cortical area V4, shaped by feedback from prefrontal cortex (PFC), may play a key role. To probe the algorithms that may underlie these findings, we build and test a model of V4 and PFC interactions based on a hierarchical predictive coding framework. We propose that probabilistic inference occurs in two steps. Initially, V4 responses are driven solely by bottom-up sensory input and are thus strongly influenced by the level of occlusion. After a delay, V4 responses combine both feedforward input and feedback signals from the PFC; the latter reflect predictions made by PFC about the visual stimulus underlying V4 activity. We find that this model captures key features of V4 and PFC dynamics observed in experiments. Specifically, PFC responses are strongest for occluded stimuli and delayed responses in V4 are less sensitive to occlusion, supporting our hypothesis that the feedback signals from PFC underlie robust discrimination of occluded shapes. Thus, our study proposes that area V4 and PFC participate in hierarchical inference, with feedback signals encoding top-down predictions about occluded shapes.

Indexed as

Nonlinear DynamicsAction PotentialsAlgorithmsAnimalsDiscrimination LearningMacaca mulattaModels, NeurologicalNeuronsPhotic StimulationPrefrontal CortexProbabilityVisual CortexVisual PathwaysVisual Perception

Identifiers

PMID29566355
PMCPMC5930045

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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.