Evidence map›Paper›PMID 37848285›Full record

ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2023

Distinct Neural Components of Visually Guided Grasping during Planning and Execution.

Lina K Klein, Guido Maiello, Kevin Stubbs, Daria Proklova, Juan Chen, Vivian C Paulun, Jody C Culham, Roland W Fleming

Abstract read
In one paragraph

Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Object and Task Features Influence Visual and Sensorimotor Integration in Grasping Tasks.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  4. Computation on Demand: Action-Specific Representations of Visual Task Features Arise during Distinct Movement Phases.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    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

8 authors.

Lina K KleinDepartment of Experimental Psychology, Justus Liebig University Giessen, 35390 Giessen, Germany.
Guido MaielloSchool of Psychology, University of Southampton, Southampton SO17 1PS, United Kingdom guido_maiello@yahoo.it.ORCID 0000-0001-6625-2583
Kevin StubbsDepartment of Psychology, University of Western Ontario, London, Ontario N6A 5C2, Canada.ORCID 0000-0002-1630-8427
Daria ProklovaDepartment of Psychology, University of Western Ontario, London, Ontario N6A 5C2, Canada.
Juan ChenCenter for the Study of Applied Psychology, Guangdong Key Laboratory of Mental Health and Cognitive Science, and the School of Psychology, South China Normal University, Guangzhou, 510631, China.
Vivian C PaulunMcGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139.ORCID 0000-0003-0211-6106
Jody C CulhamDepartment of Psychology, University of Western Ontario, London, Ontario N6A 5C2, Canada.
Roland W FlemingDepartment of Experimental Psychology, Justus Liebig University Giessen, 35390 Giessen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Selecting suitable grasps on three-dimensional objects is a challenging visuomotor computation, which involves combining information about an object (e.g., its shape, size, and mass) with information about the actor's body (e.g., the optimal grasp aperture and hand posture for comfortable manipulation). Here, we used functional magnetic resonance imaging to investigate brain networks associated with these distinct aspects during grasp planning and execution. Human participants of either sex viewed and then executed preselected grasps on L-shaped objects made of wood and/or brass. By leveraging a computational approach that accurately predicts human grasp locations, we selected grasp points that disentangled the role of multiple grasp-relevant factors, that is, grasp axis, grasp size, and object mass. Representational Similarity Analysis revealed that grasp axis was encoded along dorsal-stream regions during grasp planning. Grasp size was first encoded in ventral stream areas during grasp planning then in premotor regions during grasp execution. Object mass was encoded in ventral stream and (pre)motor regions only during grasp execution. Premotor regions further encoded visual predictions of grasp comfort, whereas the ventral stream encoded grasp comfort during execution, suggesting its involvement in haptic evaluation. These shifts in neural representations thus capture the sensorimotor transformations that allow humans to grasp objects.

Indexed as

BrainPsychomotor PerformanceBrain MappingHandHand StrengthHumansfunctional magnetic resonance imaginggrasp axisgraspinggrasp sizeobject massvisual grasp selection

Identifiers

PMID37848285
PMCPMC10711727

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.