Evidence map›Paper›PMID 33831009›Full record

ArticlePLoS computational biology2021

Inhibitory neurons exhibit high controlling ability in the cortical microconnectome.

Motoki Kajiwara, Ritsuki Nomura, Felix Goetze, Masanori Kawabata, Yoshikazu Isomura, Tatsuya Akutsu, Masanori Shimono

Abstract read
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
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

17 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Neural network embedding of functional microconnectome.Network neuroscience (Cambridge, Mass.) · 2025
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. High-resolution analysis of bound CaLife science alliance · 2024
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Common Microscale and Macroscale Principles of Connectivity in the Human Brain.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2022
    Article
  16. Article
  17. Article
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

7 authors.

Motoki KajiwaraGraduate Schools of Medicine, Kyoto University, Kyoto, Japan.
Ritsuki NomuraGraduate Schools of Medicine, Kyoto University, Kyoto, Japan.
Felix GoetzeDepartment of Physics and Center for Complex Systems, National Central University, Taiwan, Republic of China.ORCID 0000-0002-8129-4658
Masanori KawabataDepartment of Physiology and Cell Biology, Tokyo Medical and Dental University, Tokyo, Japan.ORCID 0000-0002-3499-9786
Yoshikazu IsomuraDepartment of Physiology and Cell Biology, Tokyo Medical and Dental University, Tokyo, Japan.
Tatsuya AkutsuBioinformatics Center, Institute for Chemical Research, Kyoto University, Kyoto, Japan.ORCID 0000-0001-9763-797X
Masanori ShimonoGraduate Schools of Medicine, Kyoto University, Kyoto, Japan.ORCID 0000-0003-3549-7697

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The brain is a network system in which excitatory and inhibitory neurons keep activity balanced in the highly non-random connectivity pattern of the microconnectome. It is well known that the relative percentage of inhibitory neurons is much smaller than excitatory neurons in the cortex. So, in general, how inhibitory neurons can keep the balance with the surrounding excitatory neurons is an important question. There is much accumulated knowledge about this fundamental question. This study quantitatively evaluated the relatively higher functional contribution of inhibitory neurons in terms of not only properties of individual neurons, such as firing rate, but also in terms of topological mechanisms and controlling ability on other excitatory neurons. We combined simultaneous electrical recording (~2.5 hours) of ~1000 neurons in vitro, and quantitative evaluation of neuronal interactions including excitatory-inhibitory categorization. This study accurately defined recording brain anatomical targets, such as brain regions and cortical layers, by inter-referring MRI and immunostaining recordings. The interaction networks enabled us to quantify topological influence of individual neurons, in terms of controlling ability to other neurons. Especially, the result indicated that highly influential inhibitory neurons show higher controlling ability of other neurons than excitatory neurons, and are relatively often distributed in deeper layers of the cortex. Furthermore, the neurons having high controlling ability are more effectively limited in number than central nodes of k-cores, and these neurons also participate in more clustered motifs. In summary, this study suggested that the high controlling ability of inhibitory neurons is a key mechanism to keep balance with a large number of other excitatory neurons beyond simple higher firing rate. Application of the selection method of limited important neurons would be also applicable for the ability to effectively and selectively stimulate E/I imbalanced disease states.

Indexed as

ConnectomeAction PotentialsAnimalsCerebral CortexFemaleInhibitory Postsynaptic PotentialsMagnetic Resonance ImagingMiceMice, Inbred C57BLNeurons

Identifiers

PMID33831009
PMCPMC8031186

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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.