Evidence map›Paper›PMID 32311583›Full record

ArticleiScience2020

Neural Circuit Mechanism Underlying the Feeding Controlled by Insula-Central Amygdala Pathway.

Calvin Zhang-Molina, Matthew B Schmit, Haijiang Cai

Open access · goldAbstract read
In one paragraph

Article in iScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.6field-weighted citation impact, top 18% 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

13 citing papers in PubMed, 24 citations in OpenAlex.

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  9. Glucagon-Like Peptide-1 Receptors in the Gustatory Cortex Influence Food Intake.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023
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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 at 1 institution in 1 country.

Calvin Zhang-MolinaDepartment of Mathematics, University of Arizona, Tucson, AZ 85721, USA. Electronic address: calvinz@math.arizona.edu.
Matthew B SchmitDepartment of Neuroscience, University of Arizona, Tucson, AZ 85721, USA; Graduate Interdisciplinary Program in Neuroscience, University of Arizona, Tucson, AZ 85721, USA.
Haijiang CaiDepartment of Neuroscience, University of Arizona, Tucson, AZ 85721, USA; Bio5 Institute and Department of Neurology, University of Arizona, Tucson, AZ 85721, USA. Electronic address: haijiangcai@email.arizona.edu.
University of Arizona · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Central nucleus of amygdala (CeA) contains distinct populations of neurons that play opposing roles in feeding. The circuit mechanism of how CeA neurons process information sent from their upstream inputs to regulate feeding is still unclear. Here we show that activation of the neural pathway projecting from insular cortex neurons to the CeA suppresses food intake. Surprisingly, we find that the inputs from insular cortex form excitatory connections with similar strength to all types of CeA neurons. To reconcile this puzzling result, and previous findings, we developed a conductance-based dynamical systems model for the CeA neuronal network. Computer simulations showed that both the intrinsic electrophysiological properties of individual CeA neurons and the overall synaptic organization of the CeA circuit play a functionally significant role in shaping CeA neural dynamics. We successfully identified a specific CeA circuit structure that reproduces the desired circuit output consistent with existing experimentally observed feeding behaviors.

Indexed as

Behavioral NeuroscienceMathematical BiosciencesSystems Neuroscience

Identifiers

PMID32311583
PMCPMC7168768
OpenAlexW3014750347

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.