Yokoyama, H. — Page 2 | Search bioRxiv

bioRxiv2019

Detecting task-dependent modulation of spatiotemporal module via tensor decomposition: application to kinematics and EMG data for walking and running at various speed

How the central nervous system (CNS) controls many joints and muscles is a fundamental question in motor neuroscience and related research areas. An attractive hypothesis is the module hypothesis: the CNS controls groups of joints or muscles (i.e., spatial modules) while providing time-varying motor commands (i.e., temporal modules) to the spatial modules rather than controlling each joint or muscle separately. Another fundamental question is how the CNS generates numerous repertories of movement patterns. One hypothesis is that the CNS modulates the spatial and/or temporal modules depending on the required tasks. It is thus essential to quantify the spatial module, the temporal module, and the task-dependent modulation of those modules. Although previous methods attempted to quantify these aspects, they considered the modulation in only the spatial or temporal module. These limitations were possibly due to the constraints inherent to conventional methods for quantifying the spatial and temporal modules. Here, we demonstrate the effectiveness of tensor decomposition in quantifying the spatial module, the temporal module, and the task-dependent modulation of these modules without such limitations. We further demonstrate that the tensor decomposition provides a new perspective on the task-dependent modulation of spatiotemporal modules: in switching from walking to running, the CNS modulates the peak timing in the temporal module while recruiting proximal muscles in the corresponding spatial module.\n\nAuthor summaryThere are at least two fundamental questions in motor neuroscience and related research areas: 1) how does the central nervous system (CNS) control many joints and muscles and 2) how does the CNS generate numerous repertories of movement patterns. One possible answer to question 1) is that the CNS controls groups of joints or muscles (i.e., spatial modules) while providing time-varying motor commands (i.e., temporal modules) to the spatial modules rather than controlling each joint or muscle separately. One possible answer to question 2) is that the CNS modulates the spatial and/or temporal module depending on the required tasks. It is thus essential to quantify the spatial module, the temporal module, and the task-dependent modulation of those modules. Here, we demonstrate the effectiveness of tensor decomposition in quantifying the modules and those task-dependent modulations while overcoming the shortcomings inherent to previous methods. We further show that the tensor decomposition provides a new perspective on how the CNS switches between walking and running. The CNS modulated the peak timing in the temporal module while recruiting proximal muscles in the corresponding spatial module.

neuroscience↗

bioRxiv2018

Cortical control of locomotor muscle activity through muscle synergies in humans: a neural decoding study

Walking movements are orchestrated by the activation of a large number of muscles. The control of numerous muscles during walking is believed to be simplified by flexible activation of groups of muscles called muscle synergies. Although significant corticomuscular connectivity during walking has been reported, the level at which the cortex controls locomotor muscle activity (i.e., muscle synergy or individual muscle level) remains unclear. Here, we examined cortical involvement in muscle control during walking by brain decoding of the activation of muscle synergies and individual muscles from electroencephalographic (EEG) signals using linear decoder models. First, we demonstrated that activation of locomotor muscle synergies was decoded from slow cortical waves with significant accuracy. In addition, we found that decoding accuracy for muscle synergy activation was greater than that for individual muscle activation and that decoding of individual muscle activation was based on muscle synergy-related cortical information. Taken together, these results provide indirect evidence that the cerebral cortex hierarchically controls multiple muscles through a few muscle synergies during walking. Our findings extend the current understanding of the role of the cortex in muscular control during walking and could accelerate the development of effective brain-machine interfaces for people with locomotor disabilities.

neuroscience↗

bioRxiv2017

Cellomics approach for high-throughput functional annotation of Caenorhabditis elegans neural network

Even in Caenorhabditis elegans, which has only 302 neurons, relationships between behaviors and neural networks are not easily elucidated. In this study, we proposed a novel cellomics approach enabling high-throughput and comprehensive exploration of the functions of a single neuron or a subset of neurons in a complex neural network on a particular behavior. To realize this, we combined optogenetics and Brainbow technologies. Using these technologies, we established a C. elegans library where opsin is labeled in a randomized pattern. Behavioral analysis on this library under light illumination enabled high-throughput annotation of neurons affecting target behaviors. We applied this approach to the egg-laying behavior of C. elegans and succeeded in high-throughput confirmation that hermaphrodite-specific neurons play an important role in the egg-laying behavior. This cellomics approach will lead to the accumulation of neurophysiological and behavioral data of the C. elegans neural network, which is necessary for constructing neuroanatomically grounded models of behavior.

neuroscience↗