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Modular organization of internal models of tools in the human cerebellum
Open accessAbstract
Human capabilities in manipulating many different tools with dexterity suggest modular neural organization at functional levels, but anatomical modularity underlying the capabilities has yet to be demonstrated. Although modularity in phylogenetically older parts of the cerebellum is well known, comparable modularity in the lateral cerebellum for cognitive functions remains unknown. We investigated these issues by functional MRI (fMRI) based on our previous findings of a cerebellar internal model of a tool. After subjects intensively learned to manipulate two novel tools (the rotated mouse whose cursor appeared at a rotated position, and the velocity mouse whose cursor velocity was proportional to the mouse position), they could easily switch between the two. The lateral and posterior cerebellar activities for the two different tools were spatially segregated, and their overlaps were <10%, even at low statistical thresholds. Activities of the rotated mouse were more anterior and lateral than the velocity mouse activities. These results were consistent with predictions by the MOdular Selection And Identification Controller (MOSAIC) model that multiple internal models compete to partition sensory-motor experiences and their outputs are linearly combined for a particular context.
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“Brain loops might extend beyond the striatum and include, for example, the cerebellum, which – given its remarkably homogenous microarchitecture – has been often assumed to be able to encode a large repertoire of internal (generative) models required to predict and control action and its timing (Caligiore et al., 2013, Imamizu et al., 2003, Miall and Wolpert, 1996, Wolpert et al., 1998).”
From Active Inference, homeostatic regulation and adaptive behavioural control (2015) · cites this paper as Imamizu et al., 2003
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“…– given its remarkably homogenous microarchitecture – has been often assumed to be able to encode a large repertoire of internal (generative) models required to predict and control action and its timing (Caligiore et al., 2013; Imamizu et al., 2003; Miall and Wolpert, 1996; Wolpert et al., 1998).”
Metadata
- Authors
- Imamizu, H., Kuroda, T., Miyauchi, S., Yoshioka, T., & Kawato, M.
- Affiliations
- Advanced Telecommunications Research Institute International (JP)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2003-04-18
- Volume
- 100
- Issue
- 9
- Pages
- 5461-5466
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC154367
- OpenAlex
- W2110514514
- Cited by
- 334
- References
- 38
- Citations by year
- 2026: 4 · 2025: 29 · 2024: 8 · 2023: 7 · 2022: 6 · 2021: 14 · 2020: 10 · 2019: 12 · 2018: 8 · 2017: 13 · 2016: 8 · 2015: 14 · 2014: 18 · 2013: 16 · 2012: 13
- FWCI
- 8.00
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Neurology › Vestibular and auditory disorders
- Keywords
- cerebellum, internal models, tool handling, lateral cerebellum, posterior cerebellum, tool switching, mosaic model, sensorimotor learning, functional segregation
- MeSH terms
- Adult, Animals, Cerebellum, Female, Humans, Magnetic Resonance Imaging, Male, Models, Biological, Regression Analysis, Mice
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