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 (452 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
Area of the occipital lobe concerned with the processing of visual information relayed via visual pathways.
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: Cortex, Visual; Extrastriate Cortex; Cortex, Extrastriate; Extrastriate Cortices; Secondary Visual Cortex; Cortex, Secondary Visual; Secondary Visual Cortices; Visual Cortex, Secondary.
Where it fits in the MeSH classification
- Broader topics
- Occipital Lobe; Sensorimotor Cortex
- Narrower topics
- Primary Visual Cortex
Related concepts
- Occipital Lobe
- Visual Pathways
Research landscape
PubMed indexes 30,108 records tagged with the MeSH heading “Visual Cortex” (counts retrieved 2026-10-29). 3,379 of them (11.2%) were published from 2020 onward, and the busiest period so far is through 1999 with 12,635 records.
Reviews account for 2,113 records (7.0%) and meta-analyses for 22. Randomized controlled trials number 202 (0.7%) 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 | 12,635 |
| 2000-2009 | 6,816 |
| 2010-2019 | 7,278 |
| 2020 onward | 3,379 |
Publication-type chart data
| Type | Records | Share |
|---|---|---|
| Reviews | 2,113 | 7.0% |
| Meta-analyses | 22 | 0.1% |
| Randomized controlled trials | 202 | 0.7% |
Method: PubMed query "Visual 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 / authors | Year | Source label / design | Europe PMC citations | Licence / source |
|---|---|---|---|---|
| Rethinking category-selectivity in human visual cortex | 2026 | Review article Design not recorded in structured metadata | 31 | cc0 PMID 40836402 · DOI · PMC12458057 |
| Ultrasound system for precise neuromodulation of human deep brain circuits | 2025 | Research article Design not recorded in structured metadata | 30 | cc by PMID 40913042 · DOI · PMC12413462 |
| The synaptic architecture of layer 5 thick tufted excitatory neurons in mouse visual cortex | 2025 | Research article Design not recorded in structured metadata | 23 | cc by PMID 40721677 · DOI · PMC12321573 |
Rethinking category-selectivity in human visual cortex [1]
Abstract reading summary — source excerpts
- Opening excerpt
- A wealth of studies report evidence that occipitotemporal cortex tessellates into 'category-selective' brain regions that are apparently specialized for representing ecologically important visual stimuli like faces, bodies, scenes, and tools.
- Closing excerpt
- Grounding our thinking in behavioral relevance rather than category-selectivity raises a host of theoretical and empirical issues that we discuss while providing proposals for how existing tools can be harnessed in this light to better understand visual function in occipitotemporal cortex.
- 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)
A wealth of studies report evidence that occipitotemporal cortex tessellates into 'category-selective' brain regions that are apparently specialized for representing ecologically important visual stimuli like faces, bodies, scenes, and tools. Here, we argue that while valuable insights have been gained through the lens of category-selectivity, a more complete view of visual function in occipitotemporal cortex requires centering the behavioral relevance of visual properties in real-world environments rather than stimulus category. Focusing on behavioral relevance challenges a simple mapping between stimulus and visual function in occipitotemporal cortex because the environmental properties relevant to a behavior are visually diverse and how a given property is represented is modulated by our goals. Grounding our thinking in behavioral relevance rather than category-selectivity raises a host of theoretical and empirical issues that we discuss while providing proposals for how existing tools can be harnessed in this light to better understand visual function in occipitotemporal cortex.
Abstract reproduced from the open-access article under the recorded cc0 licence; © the authors. PMID 40836402 · DOI · PMC12458057
Ultrasound system for precise neuromodulation of human deep brain circuits [2]
Abstract reading summary — source excerpts
- Opening excerpt
- We introduce an advanced transcranial ultrasound stimulation (TUS) system for precise deep brain neuromodulation, featuring a 256-element helmet-shaped transducer array (555 kHz), stereotactic positioning, individualised planning, and real-time fMRI monitoring.
- Closing excerpt
- Our findings reveal this system's potential to non-invasively modulate deep brain circuits with unprecedented precision and specificity, offering new avenues for studying brain function and developing targeted therapies for neurological and psychiatric disorders, with transformative potential for both research and clinical applications.
- 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 (133 words)
We introduce an advanced transcranial ultrasound stimulation (TUS) system for precise deep brain neuromodulation, featuring a 256-element helmet-shaped transducer array (555 kHz), stereotactic positioning, individualised planning, and real-time fMRI monitoring. Experiments demonstrated selective modulation of the lateral geniculate nucleus (LGN) and connected visual cortex regions. Participants showed significantly increased visual cortex activity during concurrent TUS and visual stimulation, with high cross-individual reproducibility. A theta-burst TUS protocol produced robust neuromodulatory effects, decreasing visual cortex activity for at least 40 min post-stimulation. Control experiments confirmed these effects were specific to the targeted LGN. Our findings reveal this system's potential to non-invasively modulate deep brain circuits with unprecedented precision and specificity, offering new avenues for studying brain function and developing targeted therapies for neurological and psychiatric disorders, with transformative potential for both research and clinical applications.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 40913042 · DOI · PMC12413462
The synaptic architecture of layer 5 thick tufted excitatory neurons in mouse visual cortex [3]
Abstract reading summary — source excerpts
- Opening excerpt
- Despite significant progress in characterizing neocortical cell types, a complete understanding of the synaptic connections of individual excitatory cells remains elusive.
- Closing excerpt
- This is achieved using a publicly available, automated approach for synapse recognition and automated cell typing, offering a framework for exploring the connectivity of other 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 (169 words)
Despite significant progress in characterizing neocortical cell types, a complete understanding of the synaptic connections of individual excitatory cells remains elusive. This study investigates the connectivity of mouse visual cortex thick tufted layer 5 pyramidal cells, also known as extratelencephalic neurons (L5-ETns), using a 1 mm3 publicly available electron microscopy dataset. The analysis reveals that, in their immediate vicinity, L5-ETns primarily establish connections with a group of inhibitory cell types, which, in turn, specifically target the L5-ETns back. The most common excitatory targets of L5-ETns are layer 5 intertelencephalic neurons (L5-ITns) and layer 6 (L6) pyramidal cells, whereas synapses with other L5-ETns are less common. When L5-ETns extend their axons to other cortical regions, they tend to connect more with excitatory cells. Our results highlight a circuit motif where a subclass of excitatory cells forms a subcircuit with specific inhibitory cell types. This is achieved using a publicly available, automated approach for synapse recognition and automated cell typing, offering a framework for exploring the connectivity of other neuron types.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 40721677 · DOI · PMC12321573
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 A new neural framework for visuospatial processing [4]
- Research article Development and plasticity of the primary visual cortex [5]
- Research article Large-scale brain systems in ADHD: beyond the prefrontal-striatal model [6]
- Research article The human imagination: the cognitive neuroscience of visual mental imagery [7]
- Research article Evidence for a Third Visual Pathway Specialized for Social Perception [8]
- Research article Imaging retinotopic maps in the human brain [9]
References
- Ritchie JB, Wardle SG, Vaziri-Pashkam M, Kravitz DJ, Baker CI. Rethinking category-selectivity in human visual cortex. . 2026. PMID 40836402 · DOI · PMC12458057
- Martin E, Roberts M, Grigoras IF, Wright O, Nandi T, Rieger SW, et al.. Ultrasound system for precise neuromodulation of human deep brain circuits. . 2025. PMID 40913042 · DOI · PMC12413462
- Bodor AL, Schneider-Mizell CM, Zhang C, Elabbady L, Mallen A, Bergeson A, et al.. The synaptic architecture of layer 5 thick tufted excitatory neurons in mouse visual cortex. . 2025. PMID 40721677 · DOI · PMC12321573
- Kravitz DJ, Saleem KS, Baker CI, Mishkin M. A new neural framework for visuospatial processing. Nat Rev Neurosci. 2011. PMID 21415848 · DOI · PMC3388718
- Espinosa JS, Stryker MP. Development and plasticity of the primary visual cortex. Neuron. 2012. PMID 22841309 · DOI · PMC3612584
- Castellanos FX, Proal E. Large-scale brain systems in ADHD: beyond the prefrontal-striatal model. Trends Cogn Sci. 2012. PMID 22169776 · DOI · PMC3272832
- Pearson J. The human imagination: the cognitive neuroscience of visual mental imagery. Nat Rev Neurosci. 2019. PMID 31384033 · DOI
- Pitcher D, Ungerleider LG. Evidence for a Third Visual Pathway Specialized for Social Perception. Trends Cogn Sci. 2021. PMID 33334693 · DOI · PMC7811363
- Wandell BA, Winawer J. Imaging retinotopic maps in the human brain. Vision Res. 2011. PMID 20692278 · DOI · PMC3030662
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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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.