Evidence map›Paper›PMID 35210993›Full record

ArticleFrontiers in neural circuits2021

Paired Feed-Forward Excitation With Delayed Inhibition Allows High Frequency Computations Across Brain Regions.

Alexandra S Cao, Stephen D Van Hooser

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
0.2field-weighted citation impact, top 52% 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

2 authors at 1 institution in 1 country.

Alexandra S CaoDepartment of Biology, Brandeis University, Waltham, MA, United States.
Stephen D Van HooserDepartment of Biology, Brandeis University, Waltham, MA, United States.
Brandeis University · US

Funding

Undergraduate and Graduate Training in Computational Neuroscience R90DA033463 · NIDA · BRANDEIS UNIVERSITY · PI MILLER, PAUL · 2011 to 2020
$2.0M
NIDA NIH HHS R90 DA033463
6 · The paper itself

Abstract

The transmission of high frequency temporal information across brain regions is critical to perception, but the mechanisms underlying such transmission remain unclear. Long-range projection patterns across brain areas are often comprised of paired feed-forward excitation followed closely by delayed inhibition, including the thalamic triad synapse, thalamic projections to cortex, and projections within the hippocampus. Previous studies have shown that these joint projections produce a shortened period of depolarization, sharpening the timing window over which the postsynaptic neuron can fire. Here we show that these projections can facilitate the transmission of high frequency computations even at frequencies that are highly filtered by neuronal membranes. This temporal facilitation occurred over a range of synaptic parameter values, including variations in synaptic strength, synaptic time constants, short-term synaptic depression, and the delay between excitation and inhibition. Further, these projections can coordinate computations across multiple network levels, even amid ongoing local activity. We suggest that paired feed-forward excitation and inhibition provide a hybrid signal-carrying both a value and a clock-like trigger-to allow circuits to be responsive to input whenever it arrives.

Indexed as

SynapsesThalamusCerebral CortexHippocampusNeuronsSynaptic Transmissionarea 17cross-network computingLGNpaired feed-forward excitation/inhibition feed-forwardstriate cortextiming

Identifiers

PMID35210993
PMCPMC8862685
OpenAlexW4225555941

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.