Evidence map›Paper›PMID 37126607›Full record

ArticleHuman brain mapping2023

Hierarchical categorization learning is associated with representational changes in the dorsal striatum and posterior frontal and parietal cortex.

Sebastian M Frank, Marvin R Maechler, Sergey V Fogelson, Peter U Tse

Open access · goldAbstract read
In one paragraph

Article in Human brain mapping, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
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

5 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. The how and why for multiple forms of hippocampal LTP.Frontiers in synaptic neuroscience · 2026
    Review
  3. Article
  4. Emergence of Categorical Representations in Parietal and Ventromedial Prefrontal Cortex across Extended Training.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  5. 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

4 authors at 2 institutions in 2 countries.

Sebastian M FrankInstitute for Experimental Psychology, University of Regensburg, Regensburg, Germany.ORCID 0000-0002-7028-8754
Marvin R MaechlerDepartment of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, USA.ORCID 0000-0002-2847-3083
Sergey V FogelsonDepartment of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, USA.
Peter U TseDepartment of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, USA.
Dartmouth College · USUniversity of Regensburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Learning and recognition can be improved by sorting novel items into categories and subcategories. Such hierarchical categorization is easy when it can be performed according to learned rules (e.g., "if car, then automatic or stick shift" or "if boat, then motor or sail"). Here, we present results showing that human participants acquire categorization rules for new visual hierarchies rapidly, and that, as they do, corresponding hierarchical representations of the categorized stimuli emerge in patterns of neural activation in the dorsal striatum and in posterior frontal and parietal cortex. Participants learned to categorize novel visual objects into a hierarchy with superordinate and subordinate levels based on the objects' shape features, without having been told the categorization rules for doing so. On each trial, participants were asked to report the category and subcategory of the object, after which they received feedback about the correctness of their categorization responses. Participants trained over the course of a one-hour-long session while their brain activation was measured using functional magnetic resonance imaging. Over the course of training, significant hierarchy learning took place as participants discovered the nested categorization rules, as evidenced by the occurrence of a learning trial, after which performance suddenly increased. This learning was associated with increased representational strength of the newly acquired hierarchical rules in a corticostriatal network including the posterior frontal and parietal cortex and the dorsal striatum. We also found evidence suggesting that reinforcement learning in the dorsal striatum contributed to hierarchical rule learning.

Indexed as

Brain MappingParietal LobeBrainHumansLearningMagnetic Resonance ImagingReinforcement, Psychologycategorization learningcorticostriatal loopsdorsal striatumfMRIfrontal cortexhierarchical decision treeshierarchical rule learningintraparietal sulcusreinforcement learningrepresentational similarity analysis

Identifiers

PMID37126607
PMCPMC10203792
OpenAlexW4367625682

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.