ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2023
Cortical Patterns Shift from Sequence Feature Separation during Planning to Integration during Motor Execution.
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. An erratum has been issued. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 16 citations in OpenAlex.
- Pretraining of Embodied Recurrent Networks Bridges the Gap Between Artificial and Cortical Neural Activities.Biomimetics (Basel, Switzerland) · 2026Article
- Article
- Behavioral evidence for the hierarchical execution of sequential movements.Communications psychology · 2026Article
- Motor and Cognitive Sequence Tasks Exhibit Different Ramping Patterns in Parietal and Prefrontal Cortices.Journal of cognitive neuroscience · 2025Article
- Dissociable Causal Roles of Dorsolateral Prefrontal Cortex and Primary Motor Cortex over the Course of Motor Skill Development.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Ramping dissociates motor and cognitive sequences in the parietal and prefrontal cortices.bioRxiv : the preprint server for biology · 2025Article
- Neural Encoding of Direction and Distance across Reference Frames in Visually Guided Reaching.eNeuro · 2024Article
- The Hippocampus Preorders Movements for Skilled Action Sequences.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- De novo sensorimotor learning through reuse of movement components.PLoS computational biology · 2024Article
- Feature Integration in Motor Sequences: Implications for Abstract Task Sequence Studies.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
Corrections and comments
- Commented on by
- Erratum issued
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Performing sequences of movements from memory and adapting them to changing task demands is a hallmark of skilled human behavior, from handwriting to playing a musical instrument. Prior studies showed a fine-grained tuning of cortical primary motor, premotor, and parietal regions to motor sequences: from the low-level specification of individual movements to high-level sequence features, such as sequence order and timing. However, it is not known how tuning in these regions unfolds dynamically across planning and execution. To address this, we trained 24 healthy right-handed human participants (14 females, 10 males) to produce four five-element finger press sequences with a particular finger order and timing structure in a delayed sequence production paradigm entirely from memory. Local cortical fMRI patterns during preparation and production phases were extracted from separate No-Go and Go trials, respectively, to tease out activity related to these perimovement phases. During sequence planning, premotor and parietal areas increased tuning to movement order or timing, regardless of their combinations. In contrast, patterns reflecting the unique integration of sequence features emerged in these regions during execution only, alongside timing-specific tuning in the ventral premotor, supplementary motor, and superior parietal areas. This was in line with the participants' behavioral transfer of trained timing, but not of order to new sequence feature combinations. Our findings suggest a general informational state shift from high-level feature separation to low-level feature integration within cortical regions for movement execution. Recompiling sequence features trial-by-trial during planning may enable flexible last-minute adjustment before movement initiation.
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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.