Evidence map›Paper›PMID 35153678›Full record

ArticleFrontiers in neural circuits2021

Orientation Invariant Sensorimotor Object Recognition Using Cortical Grid Cells.

Kalvyn Roux, David van den Heever

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neural circuits, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 99% of its field
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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

2 authors at 2 institutions in 2 countries.

Kalvyn RouxBERG, Department of Mechanical and Mechatronic Engineering, Stellenbosch University, Stellenbosch, South Africa.
David van den HeeverBERG, Department of Mechanical and Mechatronic Engineering, Stellenbosch University, Stellenbosch, South Africa.
Mississippi State University · USStellenbosch University · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Grid cells enable efficient modeling of locations and movement through path integration. Recent work suggests that the brain might use similar mechanisms to learn the structure of objects and environments through sensorimotor processing. This work is extended in our network to support sensor orientations relative to learned allocentric object representations. The proposed mechanism enables object representations to be learned through sensorimotor sequences, and inference of these learned object representations from novel sensorimotor sequences produced by rotated objects through path integration. The model proposes that orientation-selective cells are present in each column in the neocortex, and provides a biologically plausible implementation that echoes experimental measurements and fits in with theoretical predictions of previous studies.

Indexed as

Grid CellsNeocortexLearningPattern Recognition, VisualVisual Perceptiongrid cellshierarchical temporal memoryneocortexobject recognitionorientation invariancesensorimotor learning

Identifiers

PMID35153678
PMCPMC8825787
OpenAlexW4210438887

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.