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Cerebral Cortex

Neuroscience · NLM MeSH · updated 2026-10-29 · version 1

Citations verified against PubMedNot yet clinician-reviewed9 referencesApproximately 3 min read

The thin layer of gray matter on the surface of the cerebral hemispheres that develops from the telencephalon and folds into gyri and sulci.

Table of Contents

1. Definition2. Research landscape3. Reading the evidence4. Open-access studies5. Key reviews6. References7. About this article

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 (543 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

The thin layer of gray matter on the surface of the cerebral hemispheres that develops from the telencephalon and folds into gyri and sulci. It reaches its highest development in humans and is responsible for intellectual faculties and higher mental functions.

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: Cerebral Cortices; Cortex, Cerebral; Cortex Cerebri; Cortex Cerebrus; Cortical Plate; Cortical Plates; Plate, Cortical; Allocortex.

Where it fits in the MeSH classification

Broader topics
Cerebrum
Narrower topics
Frontal Lobe; Hippocampus; Insular Cortex; Limbic Lobe; Neocortex; Occipital Lobe; Parietal Lobe; Sensorimotor Cortex; Temporal Lobe
See also
Cerebral Decortication; Electroencephalography; Cortical Spreading Depression

Related concepts

  • Gray Matter
  • Cerebral Hemispheres
  • Telencephalon

Research landscape

PubMed indexes 433,012 records tagged with the MeSH heading “Cerebral Cortex” (counts retrieved 2026-10-29). 71,475 of them (16.5%) were published from 2020 onward, and the busiest period so far is through 1999 with 134,992 records.

Reviews account for 26,927 records (6.2%) and meta-analyses for 1,437. Randomized controlled trials number 5,820 (1.3%) 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.

PubMed records by publication periodthrough 1999: 134,992 records; 2000-2009: 98,853 records; 2010-2019: 127,692 records; 2020 onward: 71,475 records134,992through 199998,8532000-2009127,6922010-201971,4752020 onward
Records in PubMed indexed with this heading, by publication period. Real counts from NCBI E-utilities; the final period covers only part of the current year. Volume reflects how much has been published, not how strong the evidence is.
Show the data
PeriodRecords
through 1999134,992
2000-200998,853
2010-2019127,692
2020 onward71,475
Share of records by publication typeReviews: 6.2 percent; Meta-analyses: 0.3 percent; Randomized controlled trials: 1.3 percentReviews6.2% (26,927)Meta-analyses0.3% (1,437)Randomized controlled trials1.3% (5,820)
Share of all PubMed records on this heading that carry each publication type. Types overlap with other records, so the shares do not sum to 100%.
Publication-type chart data
Publication types among 433,012 PubMed records
TypeRecordsShare
Reviews26,9276.2%
Meta-analyses1,4370.3%
Randomized controlled trials5,8201.3%

Method: PubMed query "Cerebral Cortex"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-29.

Reading the evidence in neuroscience

Neuroscience draws on tools with different strengths: cellular and animal work can manipulate circuits directly, while human imaging and electrophysiology observe the living brain at lower resolution. Small imaging studies are prone to false positives, and findings in animals do not always carry over to people. Clinical neurology and psychiatry rely on trials and cohort studies whose outcomes are often symptom scales. Check the species, the sample size, how the outcome was measured and whether results were replicated.

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 comparison — selected abstracts, not a systematic review
Study / authorsYearSource label / designEurope PMC citationsLicence / source
Neocortical long-range inhibition promotes cortical synchrony and sleep
Ratliff JM, Terral G, Vazquez A, Lutzu S, Manning A, Perez-Catalan N, et al.
2026Research article
Design not recorded in structured metadata
4cc by
PMID 42717094 · DOI · PMC13645642
Single-nucleus atlas of cell-type specific genetic regulation in the human brain
Zeng B, Yang H, N M P, Venkatesh S, Mathur D, Auluck P, et al.
2026Research article
Design not recorded in structured metadata
4cc by
PMID 42778721 · DOI · PMC13649572
Cholinergic-dependent dopamine signals in mouse dorsomedial striatum are regulated by frontal but not sensory cortices
Goldbach HC, Rimondini R, Swanson ES, Shin JH, Authement ME, Anderson LG, et al.
2026Research article
Design not recorded in structured metadata
3cc by
PMID 42711343 · DOI · PMC13554099

Neocortical long-range inhibition promotes cortical synchrony and sleep [1]

Research article Ratliff JM, Terral G, Vazquez A, Lutzu S, Manning A, Perez-Catalan N, et al. · · 2026 · cited 4 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
Sleep and wakefulness are associated with distinct cortical patterns of rhythmic activity1.
Closing excerpt
Together, these findings show that long-range Sst-Chodl inhibitory neurons not only track behavioural state, but can also actively promote synchronized cortical activity and sleep behaviour, highlighting that cortical circuits have a key role in sleep regulation, alongside established subcortical mechanisms.
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 (186 words)

Sleep and wakefulness are associated with distinct cortical patterns of rhythmic activity1. During low-arousal states such as slow-wave sleep, synchronous low-frequency rhythms dominate activity across widespread cortical regions. Although inhibitory neurons are increasingly recognized as key regulators of cortical state2-4, the circuit mechanisms that coordinate synchronized activity across local and distant neocortical networks in vivo remain poorly understood. Here we show in mice that cells co-expressing somatostatin (Sst) and chondrolectin (Chodl)-which constitute a sparse and genetically distinct class of neocortical GABAergic inhibitory neurons-are selectively active during low-arousal states and mostly silent during periods of high arousal. In contrast to most neocortical inhibitory neurons, Sst-Chodl cells, despite being extremely sparse, exert widespread influence across the neocortex, through long-range axons that target multiple regions simultaneously. Selective activation of Sst-Chodl cells is sufficient to promote the multi-region cortical synchronization that is characteristic of low-arousal states and to induce sleep. Together, these findings show that long-range Sst-Chodl inhibitory neurons not only track behavioural state, but can also actively promote synchronized cortical activity and sleep behaviour, highlighting that cortical circuits have a key role in sleep regulation, alongside established subcortical mechanisms.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42717094 · DOI · PMC13645642

Single-nucleus atlas of cell-type specific genetic regulation in the human brain [2]

Research article Zeng B, Yang H, N M P, Venkatesh S, Mathur D, Auluck P, et al. · · 2026 · cited 4 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
Genetic risk variants for common diseases are predominantly located in non-coding regulatory regions and modulate gene expression.
Closing excerpt
This high-resolution atlas provides insight into the cell type-specific regulatory architecture of the human brain, and offers novel mechanistic targets for understanding the genetic basis of neuropsychiatric and neurodegenerative diseases.
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 (207 words)

Genetic risk variants for common diseases are predominantly located in non-coding regulatory regions and modulate gene expression. Although bulk tissue studies have elucidated shared mechanisms of regulatory and disease-associated genetics, the cellular specificity of these mechanisms remains largely unexplored. Here we present a comprehensive, single-nucleus multi-ancestry atlas of genetic regulation of gene expression in the human prefrontal cortex, comprising 5.6 million nuclei from 1,384 donors of diverse ancestries. Through multi-resolution analyses spanning eight major cell classes and 27 subclasses, we identify genetic regulation for 14,258 genes, with 981 showing cell type-specific regulatory effects at the class level and 857 at the subclass level. Colocalization of genetic variants associated with gene regulation and disease traits uncovers novel cell type-specific genes implicated in Alzheimer's disease, schizophrenia and other disorders that were not detectable in bulk tissue analyses. Analysis of dynamic genetic regulation at the single-nucleus level identifies 2,073 genes with regulatory effects that vary across developmental trajectories, inferred from a broad age range of donors. We also uncover 1,655 genes with trans-regulatory effects, revealing distal regulation of gene expression. This high-resolution atlas provides insight into the cell type-specific regulatory architecture of the human brain, and offers novel mechanistic targets for understanding the genetic basis of neuropsychiatric and neurodegenerative diseases.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42778721 · DOI · PMC13649572

Cholinergic-dependent dopamine signals in mouse dorsomedial striatum are regulated by frontal but not sensory cortices [3]

Research article Goldbach HC, Rimondini R, Swanson ES, Shin JH, Authement ME, Anderson LG, et al. · · 2026 · cited 3 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
Everyday decisions depend on associations between sensory stimuli, actions, and outcomes.
Closing excerpt
This work establishes a framework for understanding how cortical circuits shape striatal dopamine to support reinforcement learning.
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 (150 words)

Everyday decisions depend on associations between sensory stimuli, actions, and outcomes. The striatum supports these sensorimotor associations through dopamine-dependent plasticity. Recent work has characterized a local striatal microcircuit in which cholinergic interneurons (CINs) modulate dopamine release via activation of nicotinic receptors on dopamine axons. Here, we show that visual stimuli evoke dopamine in the dorsomedial striatum partly through this cholinergic mechanism. Using anatomical and functional methods to identify the pathways involved, we found that visual and auditory cortices lack connectivity with CINs and were unable to drive cholinergic-dependent dopamine release. Frontal regions, which were activated by visual stimuli, strongly recruited CINs, producing robust dopamine release both ex vivo and in vivo. These findings reveal a fundamental distinction between sensory and frontal corticostriatal inputs, demonstrating that only the latter can evoke cholinergic-dependent dopamine signals. This work establishes a framework for understanding how cortical circuits shape striatal dopamine to support reinforcement learning.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42711343 · DOI · PMC13554099

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 Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions [4]
    Howard DM, Adams MJ, Clarke TK, Hafferty JD, Gibson J, Shirali M, et al. · Nat Neurosci · 2019 · cited 2,265 times (Europe PMC)
  • Research article The genetic architecture of the human cerebral cortex [5]
    Grasby KL, Jahanshad N, Painter JN, Colodro-Conde L, Bralten J, Hibar DP, et al. · Science · 2020 · cited 719 times (Europe PMC)
  • Research article Rumination and the default mode network: Meta-analysis of brain imaging studies and implications for depression [6]
    Zhou HX, Chen X, Shen YQ, Li L, Chen NX, Zhu ZC, et al. · Neuroimage · 2020 · cited 512 times (Europe PMC)
  • Research article Effect of aerobic exercise on hippocampal volume in humans: A systematic review and meta-analysis [7]
    Firth J, Stubbs B, Vancampfort D, Schuch F, Lagopoulos J, Rosenbaum S, et al. · Neuroimage · 2018 · cited 389 times (Europe PMC)
  • Research article An atlas of cortical circular RNA expression in Alzheimer disease brains demonstrates clinical and pathological associations [8]
    Dube U, Del-Aguila JL, Li Z, Budde JP, Jiang S, Hsu S, et al. · Nat Neurosci · 2019 · cited 301 times (Europe PMC)
  • Research article Novel genetic loci associated with hippocampal volume [9]
    Hibar DP, Adams HHH, Jahanshad N, Chauhan G, Stein JL, Hofer E, et al. · Nat Commun · 2017 · cited 248 times (Europe PMC)

References

  1. Ratliff JM, Terral G, Vazquez A, Lutzu S, Manning A, Perez-Catalan N, et al.. Neocortical long-range inhibition promotes cortical synchrony and sleep. . 2026. PMID 42717094 · DOI · PMC13645642
  2. Zeng B, Yang H, N M P, Venkatesh S, Mathur D, Auluck P, et al.. Single-nucleus atlas of cell-type specific genetic regulation in the human brain. . 2026. PMID 42778721 · DOI · PMC13649572
  3. Goldbach HC, Rimondini R, Swanson ES, Shin JH, Authement ME, Anderson LG, et al.. Cholinergic-dependent dopamine signals in mouse dorsomedial striatum are regulated by frontal but not sensory cortices. . 2026. PMID 42711343 · DOI · PMC13554099
  4. Howard DM, Adams MJ, Clarke TK, Hafferty JD, Gibson J, Shirali M, et al.. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat Neurosci. 2019. PMID 30718901 · DOI · PMC6522363
  5. Grasby KL, Jahanshad N, Painter JN, Colodro-Conde L, Bralten J, Hibar DP, et al.. The genetic architecture of the human cerebral cortex. Science. 2020. PMID 32193296 · DOI · PMC7295264
  6. Zhou HX, Chen X, Shen YQ, Li L, Chen NX, Zhu ZC, et al.. Rumination and the default mode network: Meta-analysis of brain imaging studies and implications for depression. Neuroimage. 2020. PMID 31655111 · DOI
  7. Firth J, Stubbs B, Vancampfort D, Schuch F, Lagopoulos J, Rosenbaum S, et al.. Effect of aerobic exercise on hippocampal volume in humans: A systematic review and meta-analysis. Neuroimage. 2018. PMID 29113943 · DOI
  8. Dube U, Del-Aguila JL, Li Z, Budde JP, Jiang S, Hsu S, et al.. An atlas of cortical circular RNA expression in Alzheimer disease brains demonstrates clinical and pathological associations. Nat Neurosci. 2019. PMID 31591557 · DOI · PMC6858549
  9. Hibar DP, Adams HHH, Jahanshad N, Chauhan G, Stein JL, Hofer E, et al.. Novel genetic loci associated with hippocampal volume. Nat Commun. 2017. PMID 28098162 · DOI · PMC5253632

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 2026-10-31; title, year and DOI matched.
Review state
automated source verified; no human expert review has been recorded yet.
Version
1, last updated 2026-10-29.

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Related research topics

  • Brain StemNeuroscience
  • NeocortexNeuroscience
  • ThalamusNeuroscience
  • HippocampusNeuroscience
  • Dorsolateral Prefrontal CortexNeuroscience
  • Somatosensory CortexNeuroscience

All 110 articles in Neuroscience →

At a glance

433,012
PubMed records on this heading
17%
published since 2020
26,927
review articles
5,820
randomized trials
9
verified references below

Counts come from PubMed on 2026-10-29; they show how much has been written, not how strong the evidence is.

Related topics See all →

  • Brain StemNeuroscience
  • NeocortexNeuroscience
  • ThalamusNeuroscience
  • HippocampusNeuroscience
  • Dorsolateral Prefrontal CortexNeuroscience

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