Evidence map›Paper›PMID 32783027›Full record

ArticleNeuroscience insights2020

Targeting Subsets of Mammalian Neurons.

Boris V Zemelman

Open access · goldAbstract readComment
In one paragraph

Article in Neuroscience insights, 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
–field-weighted citation impact, top 98% 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

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Boris V ZemelmanCenter for Learning and Memory, Department of Neuroscience, The University of Texas at Austin, Austin, TX, USA.ORCID https://orcid.org/0000-0003-2463-4887
The University of Texas at Austin · US

Funding

Neural ensembles underlying natural tracking behaviorU01NS094330 · NINDS · UNIVERSITY OF TEXAS AT AUSTIN · PI FIETE, ILA R., HUK, ALEXANDER C · 2015 to 2018
$3.2M
An optical-genetic toolbox for reading and writing neural population codes in functional mapsU01NS099720 · NINDS · UNIVERSITY OF TEXAS AT AUSTIN · PI GEISLER, WILSON S, SEIDEMANN, EYAL J · 2016 to 2018
$1.8M
Discovery of functional cell types in the inferior colliculus with combined molecular-genetic and electrophysiological approachesR21DC016169 · NIDCD · UNIVERSITY OF TEXAS AT AUSTIN · PI GOLDING, NACE L, ZEMELMAN, BORIS V · 2017 to 2018
$419k
NIDCD NIH HHS R21 DC016169NINDS NIH HHS U01 NS094330NINDS NIH HHS U01 NS099720
6 · The paper itself

Abstract

Functional dissection of mammalian neuronal circuits depends on accurate targeting of constituent cell classes. Transgenic mice offer precise and predictable access to genetically defined cell populations, but there is the pressing need to target neuronal assemblies in species less amenable to genomic manipulations, such as the primate, which is an important animal model for human perception, cognition, and action. We have developed several virus-based methods for accessing all forebrain inhibitory interneurons as well as the major excitatory and inhibitory neuron subclasses. These methods rely on the wealth of emerging single-cell transcriptome data and harness gene expression variations to refine neuron targeting. Our approach enables nuanced functional studies, including in vivo imaging and manipulation, of the diverse cell populations of the mammalian neocortex, and it represents a timely blueprint for transgenics-independent interrogation of functionally significant cell classes.

Indexed as

adeno-associated viruscell type specificityGenetic targetingnonhuman primatesrodents

Identifiers

PMID32783027
PMCPMC7384116
OpenAlexW3008084107

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.