ArticleFrontiers in computational neuroscience2013
Compositionality in neural control: an interdisciplinary study of scribbling movements in primates.
Article in Frontiers in computational neuroscience, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- The Compositional Encoding of Hand-Eye Coordinated Movements for Single Neurons in the Posterior Parietal Cortex.bioRxiv : the preprint server for biology · 2026Article
- The relationship between speed and curvature differs in autistic and non-autistic tracing movements.Scientific reports · 2026Article
- Neural representation of action symbols in primate frontal cortex.bioRxiv : the preprint server for biology · 2025Article
- Biological kinematics: a detailed review of the velocity-curvature power law calculation.Experimental brain research · 2025Review
- Quantifying spontaneous infant movements using state-space models.Scientific reports · 2024Article
- The speed-curvature power law of movements: a reappraisal.Experimental brain research · 2018Article
- Analysis of complex neural circuits with nonlinear multidimensional hidden state models.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- Motor primitives--new data and future questions.Current opinion in neurobiology · 2015Review
- Editorial: Modularity in motor control: from muscle synergies to cognitive action representation.Frontiers in computational neuroscience · 2015Article
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Authors and funding
6 authors.
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Abstract
This article discusses the compositional structure of hand movements by analyzing and modeling neural and behavioral data obtained from experiments where a monkey (Macaca fascicularis) performed scribbling movements induced by a search task. Using geometrically based approaches to movement segmentation, it is shown that the hand trajectories are composed of elementary segments that are primarily parabolic in shape. The segments could be categorized into a small number of classes on the basis of decreasing intra-class variance over the course of training. A separate classification of the neural data employing a hidden Markov model showed a coincidence of the neural states with the behavioral categories. An additional analysis of both types of data by a data mining method provided evidence that the neural activity patterns underlying the behavioral primitives were formed by sets of specific and precise spike patterns. A geometric description of the movement trajectories, together with precise neural timing data indicates a compositional variant of a realistic synfire chain model. This model reproduces the typical shapes and temporal properties of the trajectories; hence the structure and composition of the primitives may reflect meaningful behavior.
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