Evidence map›Paper›PMID 35410342›Full record

ArticleBMC biology2022

High activity and high functional connectivity are mutually exclusive in resting state zebrafish and human brains.

Mahdi Zarei, Dan Xie, Fei Jiang, Adil Bagirov, Bo Huang, Ashish Raj, Srikantan Nagarajan, Su Guo

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Network Mechanisms Underlying the Regional Diversity of Variance and Time Scales of the Brain's Spontaneous Activity Fluctuations.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    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

8 authors.

Mahdi ZareiDepartment of Bioengineering and Therapeutic Sciences, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, USA. Mahdi.Zarei@ucsf.edu.
Dan XieDepartment of Bioengineering and Therapeutic Sciences, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, USA.
Fei JiangDepartment of Epidemiology and Biostatistics, University of California, San Francisco, USA.
Adil BagirovFaculty of Science and Technology, Federation University Australia, Ballarat, Victoria, Australia.
Bo HuangDepartment of Pharmaceutical Chemistry, University of California, San Francisco, USA.
Ashish RajDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, USA.
Srikantan NagarajanDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, USA.
Su GuoDepartment of Bioengineering and Therapeutic Sciences, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, USA. su.guo@ucsf.edu.ORCID 0000-0002-7342-0108

Funding

Mechanisms that drive the variation of aversive behaviorR01GM132500 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GUO, SU · 2019 to 2022
$2.5M
Functional connectivity at cellular resolution in brains with mutations in ASD genesR21MH113961 · NIMH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GUO, SU · 2017 to 2018
$436k
Explore in vivo functional connectivity at cellular resolution in drugged brainsR21DA044007 · NIDA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GUO, SU · 2017 to 2018
$414k
NIDA NIH HHS R21 DA044007NIGMS NIH HHS R01 GM132500NIMH NIH HHS R21 MH113961
6 · The paper itself

Abstract

backgroundThe structural connectivity of neurons in the brain allows active neurons to impact the physiology of target neuron types with which they are functionally connected. While the structural connectome is at the basis of functional connectome, it is the functional connectivity measured through correlations between time series of individual neurophysiological events that underlies behavioral and mental states. However, in light of the diverse neuronal cell types populating the brain and their unique connectivity properties, both neuronal activity and functional connectivity are heterogeneous across the brain, and the nature of their relationship is not clear. Here, we employ brain-wide calcium imaging at cellular resolution in larval zebrafish to understand the principles of resting state functional connectivity.

resultsWe recorded the spontaneous activity of >12,000 neurons in the awake resting state forebrain. By classifying their activity (i.e., variances of ΔF/F across time) and functional connectivity into three levels (high, medium, low), we find that highly active neurons have low functional connections and highly connected neurons are of low activity. This finding holds true when neuronal activity and functional connectivity data are classified into five instead of three levels, and in whole brain spontaneous activity datasets. Moreover, such activity-connectivity relationship is not observed in randomly shuffled, noise-added, or simulated datasets, suggesting that it reflects an intrinsic brain network property. Intriguingly, deploying the same analytical tools on functional magnetic resonance imaging (fMRI) data from the resting state human brain, we uncover a similar relationship between activity (signal variance over time) and functional connectivity, that is, regions of high activity are non-overlapping with those of high connectivity.

conclusionsWe found a mutually exclusive relationship between high activity (signal variance over time) and high functional connectivity of neurons in zebrafish and human brains. These findings reveal a previously unknown and evolutionarily conserved brain organizational principle, which has implications for understanding disease states and designing artificial neuronal networks.

Indexed as

ConnectomeZebrafishAnimalsBrainHumansMagnetic Resonance ImagingNerve NetNeuronsActivity connectivity relationshipAnatomical and functional architecture of the brainFunctional connectomeIntrinsic brain network propertyLight sheet microscopyMachine learningOptimal thresholding valuesSelective-plane illumination microscopy (SPIM)Spontaneous activityWhole brain recording at cellular resolution

Identifiers

PMID35410342
PMCPMC8996543

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Registered trials

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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.