Evidence map›Paper›PMID 35813505›Full record

ArticleFrontiers in cellular neuroscience2022

Understanding Categorical Learning in Neural Circuits Through the Primary Olfactory Cortex.

Tor Stensola, Hanne Stensola

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cellular neuroscience, 2022. 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
0.1field-weighted citation impact, top 59% 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, 1 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 1 institution in 1 country.

Tor StensolaDynamical Systems Neuroscience Collaboratory, Faculty of Health and Sports Sciences, University of Agder, Kristiansand, Norway.
Hanne StensolaDynamical Systems Neuroscience Collaboratory, Faculty of Health and Sports Sciences, University of Agder, Kristiansand, Norway.
University of Agder · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Knowing which elements in the environment are associated with various opportunities and dangers is advantageous. A major role of mammalian sensory systems is to provide information about the identity of such elements which can then be used for adaptive action planning by the animal. Identity-tuned sensory representations are categorical, invariant to nuances in the sensory stream and depend on associative learning. Although categorical representations are well documented across several sensory modalities, these tend to situate synaptically far from the sensory organs which reduces experimenter control over input-output transformations. The formation of such representations is a fundamental neural computation that remains poorly understood. Odor representations in the primary olfactory cortex have several characteristics that qualify them as categorical and identity-tuned, situated only two synapses away from the sensory epithelium. The formation of categorical representations is likely critically dependent on-and dynamically controlled by-recurrent circuitry within the primary olfactory cortex itself. Experiments suggest that the concerted activity of several neuromodulatory systems plays a decisive role in shaping categorical learning through complex interactions with recurrent activity and plasticity in primary olfactory cortex circuits. In this perspective we discuss missing pieces of the categorical learning puzzle, and why several features of olfaction make it an attractive model system for this challenge.

Indexed as

categorical learningcortical dynamicsmodulatory systemsnoveltyolfaction

Identifiers

PMID35813505
PMCPMC9263292
OpenAlexW4283458820

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.