Definition and research guide
This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.
Content available: 3 complete abstracts (540 words), 9 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.
Definition
A comprehensive map of the physical interconnections of an organism's neural networks. This modular organization of neuronal architecture is believed to underlie disease mechanisms and the biological development of the central nervous system.
Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.
Also known as: Connectomes; Connectomics; Connectomic; Brain Connectomics; Brain Connectomic; Connectomic, Brain; Connectomics, Brain; Connectome Mapping.
Where it fits in the MeSH classification
- Broader topics
- Brain Mapping
Related concepts
Research landscape
PubMed indexes 9,159 records tagged with the MeSH heading “Connectome” (counts retrieved 2026-11-04). 5,620 of them (61.4%) were published from 2020 onward, and the busiest period so far is 2020 onward with 5,620 records.
Reviews account for 717 records (7.8%) and meta-analyses for 100. Randomized controlled trials number 151 (1.6%) as a share of all records on the topic. Randomized trials make up only a small share of this literature, so much of what is known comes from laboratory, observational or descriptive work.
Show the data
| Period | Records |
|---|---|
| through 1999 | 0 |
| 2000-2009 | 1 |
| 2010-2019 | 3,759 |
| 2020 onward | 5,620 |
Publication-type chart data
| Type | Records | Share |
|---|---|---|
| Reviews | 717 | 7.8% |
| Meta-analyses | 100 | 1.1% |
| Randomized controlled trials | 151 | 1.6% |
Method: PubMed query "Connectome"[MeSH Terms] with publication-type and date filters, retrieved 2026-11-04.
Reading the evidence in diagnostics and medical technology
A test or device is judged by how well it detects a condition, how often it gives false alarms or misses cases, and whether using it improves outcomes for people. Accuracy depends on who is tested and how common the condition is, so a test that performs well in a specialist hospital can perform differently in the community. Check the reference standard, the population studied, the sensitivity and specificity and whether results were confirmed in a separate group.
Evidence from open-access studies
These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.
| Study / authors | Year | Source label / design | Europe PMC citations | Licence / source |
|---|---|---|---|---|
| Distributed control circuits across a brain-and-cord connectome | 2026 | Research article Design not recorded in structured metadata | 25 | cc by PMID 42259917 · DOI · PMC13518251 |
| Comparative connectomics of two distantly related nematode species reveals patterns of nervous system evolution | 2025 | Research article Design not recorded in structured metadata | 23 | cc by PMID 40743352 · DOI · PMC12330220 |
| Heterogeneity of brain functional connectivity, transcriptome, and neurotransmitter profiles in major depressive disorder | 2025 | Research article Design not recorded in structured metadata | 11 | cc by PMID 41220307 · DOI · PMC13058663 |
Distributed control circuits across a brain-and-cord connectome [1]
Abstract reading summary — source excerpts
- Opening excerpt
- Just as genomes revolutionized molecular genetics, connectomes (maps of neurons and synapses) are transforming neuroscience.
- Closing excerpt
- These results reveal an architecture that is distributed, parallelized and embodied, reminiscent of distributed control architectures in engineered systems13,14.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (198 words)
Just as genomes revolutionized molecular genetics, connectomes (maps of neurons and synapses) are transforming neuroscience. To date, the only organisms with complete connectomes are worms1-3, sea squirts4 and comb jellies5 (103-104 synapses). By contrast, the fruit fly is more complex (108 synaptic connections), with a brain that supports learning and spatial memory6,7 and an intricate ventral nerve cord analogous to the vertebrate spinal cord8-12. Here we report a densely reconstructed adult fly connectome that unites the brain and ventral nerve cord, and we leverage this resource to investigate principles of neural control. We show that effector neurons (motor neurons, endocrine cells and efferent neurons targeting the viscera) are primarily influenced by sensory neurons in the same body part, forming local feedback loops. These local loops are linked by long-range circuits that involve ascending and descending neurons organized into behaviour-centric modules. Single ascending and descending neurons are often positioned to influence the voluntary movements of multiple body parts, together with the endocrine cells or visceral organs that support those movements. Brain regions involved in learning and navigation supervise these circuits. These results reveal an architecture that is distributed, parallelized and embodied, reminiscent of distributed control architectures in engineered systems13,14.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42259917 · DOI · PMC13518251
Comparative connectomics of two distantly related nematode species reveals patterns of nervous system evolution [2]
Abstract reading summary — source excerpts
- Opening excerpt
- Understanding the evolution of the bilaterian brain requires a detailed exploration of the precise nature of cellular and subcellular differences between related species.
- Closing excerpt
- These multiscale patterns of evolutionary changes show no bias to specific brain regions or neuron types.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (103 words)
Understanding the evolution of the bilaterian brain requires a detailed exploration of the precise nature of cellular and subcellular differences between related species. We undertook an electron micrographic reconstruction of the brain of the predatory nematode Pristionchus pacificus and compared the results with the brain of Caenorhabditis elegans, which diverged at least 100 million years ago. We revealed changes in neuronal cell death, neuronal cell position, axodendritic projection patterns, and synaptic connectivity of homologous neurons that display no obvious changes in overall neurite morphology and projection patterns. These multiscale patterns of evolutionary changes show no bias to specific brain regions or neuron types.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 40743352 · DOI · PMC12330220
Heterogeneity of brain functional connectivity, transcriptome, and neurotransmitter profiles in major depressive disorder [3]
Abstract reading summary — source excerpts
- Opening excerpt
- BackgroundMajor depressive disorder (MDD) is a heterogeneous with underlying mechanisms that are insufficiently studied.
- Closing excerpt
- The two subtypes had both shared and distinct genetic mechanisms and neurotransmitter receptor/transporter profiles, suggesting potential clinical implications for this heterogeneous disorder.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (239 words)
BackgroundMajor depressive disorder (MDD) is a heterogeneous with underlying mechanisms that are insufficiently studied. We aimed to identify functional connectivity (FC)-based subtypes of MDD and investigate their biological mechanisms.MethodsConsensus clustering of FC patterns was applied to a population of 829 MDD patients from the REST-Meta-MDD database, with validity assessed across multiple dimensions, including atlas replication, cross-validated classification, and drug-naïve subgroup analysis. Regression models were used to quantify FC alterations in each MDD subgroup compared with 770 healthy controls, and to analyze spatial associations between FC alterations and publicly available gene transcriptomic and neurotransmitter receptor/transporter density databases.ResultsTwo stable MDD subtypes emerged: hypoconnectivity (n = 527) and hyperconnectivity (n = 299), which had both shared and distinct regions with remarkable FC alterations (i.e. epicenters) in the default mode network.There were several common enriched genes (e.g. axon/brain development, synaptic transmission/organization, etc.) related to FC alterations in both subtypes. However, glial cell and neuronal differentiation genes were specifically enriched in the hypoconnectivity and hyperconnectivity subtypes, respectively.Both subtypes showed spatial associations between FC alterations and serotonin receptor/transporter density. In the hypoconnectivity subtype, FC alterations correlated with GABA and acetylcholine receptor densities, while norepinephrine transporter and glutamate receptor densities were linked to the hyperconnectivity subtype.ConclusionsOur findings suggested the presence of two neuroimaging subtypes of MDD characterized by hypoconnectivity or hyperconnectivity, demonstrating robust reproducibility. The two subtypes had both shared and distinct genetic mechanisms and neurotransmitter receptor/transporter profiles, suggesting potential clinical implications for this heterogeneous disorder.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 41220307 · DOI · PMC13058663
Key reviews and meta-analyses
The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.
- Research article The WU-Minn Human Connectome Project: an overview [4]
- Research article A connectome and analysis of the adult Drosophila central brain [5]
- Research article Linking Structure and Function in Macroscale Brain Networks [6]
- Research article What Is the Test-Retest Reliability of Common Task-Functional MRI Measures? New Empirical Evidence and a Meta-Analysis [7]
- Research article Mapping Symptoms to Brain Networks with the Human Connectome [8]
- Research article The dynamic pain connectome [9]
Full-text reviews on EvidenceLib
Open-access review articles about this topic, reproduced in full with authors, licence and references.
The nonhuman primate neuroimaging and neuroanatomy project
Takuya Hayashi, Yujie Hou, Matthew F Glasser et al. · NeuroImage 2021 · CC BY 4.0
References
- Bates AS, Phelps JS, Kim M, Yang HH, Matsliah A, Ajabi Z, et al.. Distributed control circuits across a brain-and-cord connectome. . 2026. PMID 42259917 · DOI · PMC13518251
- Cook SJ, Kalinski CA, Loer CM, Memar N, Majeed M, Stephen SR, et al.. Comparative connectomics of two distantly related nematode species reveals patterns of nervous system evolution. . 2025. PMID 40743352 · DOI · PMC12330220
- Li Q, Li H, Long F, Chen Y, Wang Y, Yang B, et al.. Heterogeneity of brain functional connectivity, transcriptome, and neurotransmitter profiles in major depressive disorder. . 2025. PMID 41220307 · DOI · PMC13058663
- Van Essen DC, Smith SM, Barch DM, Behrens TE, Yacoub E, Ugurbil K, et al.. The WU-Minn Human Connectome Project: an overview. Neuroimage. 2013. PMID 23684880 · DOI · PMC3724347
- Scheffer LK, Xu CS, Januszewski M, Lu Z, Takemura SY, Hayworth KJ, et al.. A connectome and analysis of the adult Drosophila central brain. Elife. 2020. PMID 32880371 · DOI · PMC7546738
- Suárez LE, Markello RD, Betzel RF, Misic B. Linking Structure and Function in Macroscale Brain Networks. Trends Cogn Sci. 2020. PMID 32160567 · DOI
- Elliott ML, Knodt AR, Ireland D, Morris ML, Poulton R, Ramrakha S, et al.. What Is the Test-Retest Reliability of Common Task-Functional MRI Measures? New Empirical Evidence and a Meta-Analysis. Psychol Sci. 2020. PMID 32489141 · DOI · PMC7370246
- Fox MD. Mapping Symptoms to Brain Networks with the Human Connectome. N Engl J Med. 2018. PMID 30575457 · DOI
- Kucyi A, Davis KD. The dynamic pain connectome. Trends Neurosci. 2015. PMID 25541287 · DOI
About this article
- Sources
- NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
- Verification
- Every reference was resolved against PubMed on 2026-11-04; title, year and DOI matched.
- Review state
- automated source verified; no human expert review has been recorded yet.
- Version
- 1, last updated 2026-11-04.
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Evidence strength
EvidenceHelix's computed view of the study designs behind this topic: how common meta-analyses, randomized trials and reviews are, how recent the literature is, and a plain-language reading. It describes the design mix of the literature. It is not a quality appraisal of any study, and it is not medical advice.