Evidence map›Paper›PMID 40800898›Full record

ArticleImaging neuroscience (Cambridge, Mass.)2025

Transcriptomic gradients of the human cerebellum.

Leana King, Maedbh King, Zonglei Zhen, Richard B Ivry, Kevin S Weiner

Abstract read
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. The cerebellar components of the human language network.bioRxiv : the preprint server for biology · 2025
    Article
  6. 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

5 authors.

Leana KingDepartment of Neuroscience, University of California, Berkeley, CA, United States.ORCID https://orcid.org/0000-0002-6338-3614
Maedbh KingMcGovern Institute, Massachusetts Institute of Technology, Cambridge, MA, United States.
Zonglei ZhenBeijing Key Laboratory of Applied Experimental Psychology, Beijing Normal University, Beijing, China.
Richard B IvryDepartment of Neuroscience, University of California, Berkeley, CA, United States.
Kevin S WeinerDepartment of Neuroscience, University of California, Berkeley, CA, United States.

Funding

Human Cerebellar Function in Multiple Task DomainsR35NS116883 · NINDS · UNIVERSITY OF CALIFORNIA BERKELEY · PI RICHARD IVRY · 2020 to 2026
$5.3M
NINDS NIH HHS R35 NS116883
6 · The paper itself

Abstract

In the past decade, there has been major interest in understanding the role of transcriptomics in the functional and anatomical layout of the human brain. To date, almost all of the work linking transcriptomics to human brain function and structure has been restricted to the cerebral cortex. The culmination of this work has identified transcriptomics as an important shared principle that can tie together function, structure, and gene expression. However, largely missing from this work is the subcortex-namely the cerebellum. Here, we investigate whether transcriptomics offer a link between function and structure in the human cerebellum, using gene expression data from post-mortem cerebella and multi-modal brain atlases. We find that transcriptomic gradients from a sparse subset of genes align with a macroanatomical, rather than a functional - parcellation of the cerebellum, and the transition of the main gradient occurs at the horizontal fissure for the group, as well as individual cerebella. Conversely, when filtering for cortex-specific genes, there is an alignment with continuous functional gradients of the cerebellum, but not discrete parcellated areas.

Indexed as

cerebellumneuroimagingparcellationtranscriptomics

Identifiers

PMID40800898
PMCPMC12319844

What OpenQuestion holds

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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.