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 (568 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
Imaging techniques used to colocalize sites of brain functions or physiological activity with brain structures.
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: Mapping, Brain; Brain Electrical Activity Mapping; Topographic Brain Mapping; Brain Mapping, Topographic; Mapping, Topographic Brain; Functional Cerebral Localization; Functional Cerebral Localizations.
Where it fits in the MeSH classification
- Broader topics
- Functional Neuroimaging
- Narrower topics
- Connectome
Research landscape
PubMed indexes 115,046 records tagged with the MeSH heading “Brain Mapping” (counts retrieved 2026-11-04). 23,154 of them (20.1%) were published from 2020 onward, and the busiest period so far is 2010-2019 with 43,491 records.
Reviews account for 9,382 records (8.2%) and meta-analyses for 1,195. Randomized controlled trials number 1,730 (1.5%) 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 | 21,440 |
| 2000-2009 | 26,961 |
| 2010-2019 | 43,491 |
| 2020 onward | 23,154 |
Publication-type chart data
| Type | Records | Share |
|---|---|---|
| Reviews | 9,382 | 8.2% |
| Meta-analyses | 1,195 | 1.0% |
| Randomized controlled trials | 1,730 | 1.5% |
Method: PubMed query "Brain Mapping"[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 |
|---|---|---|---|---|
| Organization of circuits linking descending input to motor output in the Drosophila Male Adult Nerve Cord connectome | 2026 | Research article Design not recorded in structured metadata | 35 | cc by PMID 42474298 · DOI · PMC13384506 |
| 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 |
| Investigating the methodological foundation of lesion network mapping | 2026 | Research article Design not recorded in structured metadata | 22 | cc by PMID 41540261 · DOI · PMC13156034 |
Organization of circuits linking descending input to motor output in the Drosophila Male Adult Nerve Cord connectome [1]
Abstract reading summary — source excerpts
- Opening excerpt
- In most animals, a small number of descending neurons (DNs) connect the brain to circuits and motor neurons (MNs) in the nerve cord.
- Closing excerpt
- Our analyses generate hypotheses for future functional experiments and empowers others to investigate these and other circuits of the VNC in richer mechanistic detail.
- 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 (199 words)
In most animals, a small number of descending neurons (DNs) connect the brain to circuits and motor neurons (MNs) in the nerve cord. To understand how brain signals generate behavior, it is critical to understand the organization of the neural pathways linking DNs to MNs. In companion papers, we introduced a densely reconstructed connectome of the Drosophila Male Adult Nerve Cord (MANC; Takemura et al., 2024), including cell types and developmental lineages (Marin et al., 2024), which provides complete connectivity of the ventral nerve cord (VNC) at synaptic resolution. Here, we present a first look at the organization of the networks connecting DNs to MNs. We first proofread and curated all DNs and MNs, then systematically matched their morphology to light microscopy data. We report both broad organizational patterns of the entire network and fine-scale analysis of selected circuits of interest. We discover that direct DN-MN connections are infrequent and identify neuron communities putatively linked to control of different motor systems, including walking, flight steering and power generation, and coordinated action of wings and legs. Our analyses generate hypotheses for future functional experiments and empowers others to investigate these and other circuits of the VNC in richer mechanistic detail.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42474298 · DOI · PMC13384506
Distributed control circuits across a brain-and-cord connectome [2]
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
Investigating the methodological foundation of lesion network mapping [3]
Abstract reading summary — source excerpts
- Opening excerpt
- Lesion network mapping (LNM) is a neuroimaging framework that uses normative functional connectivity (FC) data to link heterogeneous brain lesions and functional alterations to brain networks implicated in neurological and psychiatric conditions.
- Closing excerpt
- Our work may aid the development of a new generation of network-mapping methods from first principles.
- 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 (171 words)
Lesion network mapping (LNM) is a neuroimaging framework that uses normative functional connectivity (FC) data to link heterogeneous brain lesions and functional alterations to brain networks implicated in neurological and psychiatric conditions. However, many of the networks identified by LNM and related methods appear to be highly similar across diverse conditions such as addiction, depression, psychosis and epilepsy. To understand this similarity, we re-examined the data from multiple LNM studies and assessed the methodological roots of the method. Our findings reveal a foundational limitation: at its core, LNM involves a repetitive sampling of one and the same FC matrix. As a result, it systematically maps sets of local brain changes-whether they are patient lesions, magnetic resonance imaging-derived alterations, synthetic or random-onto the same nonspecific properties of the used FC data, producing highly similar networks across conditions. This central limitation cautions the use of LNM as a method for studying distinct biological networks underlying brain disorders. Our work may aid the development of a new generation of network-mapping methods from first principles.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 41540261 · DOI · PMC13156034
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 Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies [4]
- Research article Functional imaging of brain responses to pain. A review and meta-analysis (2000) [5]
- Research article Cognitive reappraisal of emotion: a meta-analysis of human neuroimaging studies [6]
- Research article Social cognition and the brain: a meta-analysis [7]
- Research article Functional anatomy of execution, mental simulation, observation, and verb generation of actions: a meta-analysis [8]
- Research article Impact of intraoperative stimulation brain mapping on glioma surgery outcome: a meta-analysis [9]
References
- Cheong HSJ, Eichler K, Stürner T, Asinof SK, Champion AS, Marin EC, et al.. Organization of circuits linking descending input to motor output in the Drosophila Male Adult Nerve Cord connectome. . 2026. PMID 42474298 · DOI · PMC13384506
- 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
- van den Heuvel MP, Libedinsky I, Quiroz Monnens S, Repple J, Sommer I, Cocchi L. Investigating the methodological foundation of lesion network mapping. . 2026. PMID 41540261 · DOI · PMC13156034
- Binder JR, Desai RH, Graves WW, Conant LL. Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cereb Cortex. 2009. PMID 19329570 · DOI · PMC2774390
- Peyron R, Laurent B, García-Larrea L. Functional imaging of brain responses to pain. A review and meta-analysis (2000). Neurophysiol Clin. 2000. PMID 11126640 · DOI
- Buhle JT, Silvers JA, Wager TD, Lopez R, Onyemekwu C, Kober H, et al.. Cognitive reappraisal of emotion: a meta-analysis of human neuroimaging studies. Cereb Cortex. 2014. PMID 23765157 · DOI · PMC4193464
- Van Overwalle F. Social cognition and the brain: a meta-analysis. Hum Brain Mapp. 2009. PMID 18381770 · DOI · PMC6870808
- Grèzes J, Decety J. Functional anatomy of execution, mental simulation, observation, and verb generation of actions: a meta-analysis. Hum Brain Mapp. 2001. PMID 11198101 · DOI · PMC6872039
- De Witt Hamer PC, Robles SG, Zwinderman AH, Duffau H, Berger MS. Impact of intraoperative stimulation brain mapping on glioma surgery outcome: a meta-analysis. J Clin Oncol. 2012. PMID 22529254 · 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.