Evidence map›Paper›PMID 32165416›Full record

ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2020

Neural Circuit Dynamics for Sensory Detection.

Sruti Mallik, Srinath Nizampatnam, Anirban Nandi, Debajit Saha, Baranidharan Raman, ShiNung Ching

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2020. 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 62% 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, 2 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

6 authors at 3 institutions in 1 country.

Sruti MallikDepartment of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, Missouri 63130.
Srinath NizampatnamDepartment of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, Missouri 63130.
Anirban NandiAllen Institute of Brain Science, Seattle, Washington 98109.
Debajit SahaDepartment of Biomedical Engineering, Michigan State University, East Lansing, Michigan 48824.
Baranidharan RamanDepartment of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130.ORCID 0000-0002-7866-155X
ShiNung ChingDepartment of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, Missouri 63130 shinung@wustl.edu.ORCID 0000-0003-4063-7068
Washington University in St. Louis · USAllen Institute · USMichigan State University · US

Funding

Wellcome Trust
6 · The paper itself

Abstract

We consider the question of how sensory networks enable the detection of sensory stimuli in a combinatorial coding space. We are specifically interested in the olfactory system, wherein recent experimental studies have reported the existence of rich, enigmatic response patterns associated with stimulus onset and offset. This study aims to identify the functional relevance of such response patterns (i.e., what benefits does such neural activity provide in the context of detecting stimuli in a natural environment). We study this problem through the lens of normative, optimization-based modeling. Here, we define the notion of a low-dimensional latent representation of stimulus identity, which is generated through action of the sensory network. The objective of our optimization framework is to ensure high-fidelity tracking of a nominal representation in this latent space in an energy-efficient manner. It turns out that the optimal motifs emerging from this framework possess morphologic similarity with prototypical onset and offset responses observed

Indexed as

Models, NeurologicalAction PotentialsAnimalsFemaleGrasshoppersMaleNerve NetNeuronsOlfactory Pathways

Identifiers

PMID32165416
PMCPMC7178907
OpenAlexW3012448560

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.