ArticleCommunications biology2024
Human local field potentials in motor and non-motor brain areas encode upcoming movement direction.
Article in Communications biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed, 11 citations in OpenAlex.
- Direction selectivity in naturalistic action observation: distributed representations across the action observation network.Brain structure & function · 2026Article
- An evolutionary conserved neural mechanism for interpersonal coordination in primates.Science advances · 2026Article
- Dynamics of oscillatory power support the integration of perceptual and mnemonic information within the premotor cortex.Nature communications · 2026Article
- Inferring Arm Movement Direction from EEG Signals Using Explainable Deep Learning.Sensors (Basel, Switzerland) · 2026Article
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Authors and funding
9 authors at 6 institutions in 3 countries.
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Abstract
Limb movement direction can be inferred from local field potentials in motor cortex during movement execution. Yet, it remains unclear to what extent intended hand movements can be predicted from brain activity recorded during movement planning. Here, we set out to probe the directional-tuning of oscillatory features during motor planning and execution, using a machine learning framework on multi-site local field potentials (LFPs) in humans. We recorded intracranial EEG data from implanted epilepsy patients as they performed a four-direction delayed center-out motor task. Fronto-parietal LFP low-frequency power predicted hand-movement direction during planning while execution was largely mediated by higher frequency power and low-frequency phase in motor areas. By contrast, Phase-Amplitude Coupling showed uniform modulations across directions. Finally, multivariate classification led to an increase in overall decoding accuracy (>80%). The novel insights revealed here extend our understanding of the role of neural oscillations in encoding motor plans.
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Registered trials
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.