Computational models of motor learning have been examined experimentally with human participants ... more Computational models of motor learning have been examined experimentally with human participants using a robotic manipulandum that produces force perturbations on their reach trajectories. Here, we developed a small-scale robotic manipulandum for rodent studies. This device enabled us to conduct the same motor control experiments typically used for human study on rodents in order to examine the neural basis of the computational process of motor control and learning. We present the design of the manipulandum and controller system in addition to kinematic analysis of the link structures. We also confirmed the feasibility of the developed system for rodent studies. GRAPHICAL ABSTRACT
Motor learning is the process of updating motor commands in response to a trajectory error induce... more Motor learning is the process of updating motor commands in response to a trajectory error induced by a perturbation to the body or vision. The brain has a great capability to accelerate learning by increasing the sensitivity of the memory update to the perceived trajectory errors. Conventional theory suggests that the statistics of perturbations or the statistics of the experienced errors induced by the external perturbations determine the learning speeds. However, the potential effect of another type of error perception, a self-generated error as a result of motor command updates (i.e., an aftereffect), on the learning speeds has not been examined yet. In this study, we dissociated the two kinds of errors by controlling the perception of the aftereffect using a channel-force environment. One group experienced errors due to the aftereffect of the learning process, while the other did not. We found that the participants who perceived the aftereffect of the memory updates exhibited a...
Reinforcement learning enables the brain to learn optimal action selection, such as go or not go,... more Reinforcement learning enables the brain to learn optimal action selection, such as go or not go, by forming state-action and action-outcome associations. Does this mechanism also optimize the brain’s willingness to learn, such as learn or not learn? Learning to learn by rewards, i.e., reinforcement meta-learning, is a crucial mechanism for machines to develop flexibility in learning, which is also considered in the brain without empirical examinations. Here, we show that humans learn to learn or not learn to maximize rewards in visuomotor learning tasks. We also show that this regulation of learning is not a motivational bias but is a result of an instrumental, active process, which takes into account the learning-outcome structure. Our results thus demonstrate the existence of reinforcement meta-learning in the human brain. Because motor learning is a process of minimizing sensory errors, our findings uncover an essential mechanism of interaction between reward and error.
The visuomotor transformation during a goal-directed movement may involve a coordinate transforma... more The visuomotor transformation during a goal-directed movement may involve a coordinate transformation from visual 'extrinsic' to muscle-like 'intrinsic' coordinate frames, which might be processed via a multilayer network architecture composed of neural basis functions. This theory suggests that the postural change during a goal-directed movement task alters activity patterns of the neurons in the intermediate layer of the visuomotor transformation that recieves both visual and proprioceptive inputs, and thus influence the multi-voxel pattern of the blood oxygenation level dependent signal. Using a recently developed multi-voxel pattern decoding method, we found extrinsic, intrinsic and intermediate coordinate frames along the visuomotor cortical pathways during a visuomotor control task. The presented results support the hypothesis that, in human, the extrinsic coordinate frame was transformed to the muscle-like frame over the dorsal pathway from the posterior parie...
Functional near-infrared spectroscopy (fNIRS) is a widely utilized neuroimaging tool in fundament... more Functional near-infrared spectroscopy (fNIRS) is a widely utilized neuroimaging tool in fundamental neuroscience research and clinical investigation. Previous research has revealed that task-evoked systemic artifacts mainly originating from the superficial-tissue may preclude the identification of cerebral activation during a given task. We examined the influence of such artifacts on event-related brain activity during a brisk squeezing movement. We estimated task-evoked superficial-tissue hemodynamics from short source–detector distance channels (15 mm) by applying principal component analysis. The estimated superficial-tissue hemodynamics exhibited temporal profiles similar to the canonical cerebral hemodynamic model. Importantly, this task-evoked profile was also observed in data from a block design motor experiment, suggesting a transient increase in superficial-tissue hemodynamics occurs following motor behavior, irrespective of task design. We also confirmed that estimation of...
2013 6th International IEEE/EMBS Conference on Neural Engineering (NER), 2013
ABSTRACT Measuring discrete-trial motor-related brain activity using functional near-infrared spe... more ABSTRACT Measuring discrete-trial motor-related brain activity using functional near-infrared spectroscopy (fNIRS) is considered difficult. This is because its spatial resolution is much lower than that of functional magnetic resonance imaging (fMRI), and its signals include non-motion-related artifacts. To detect changes in hemoglobin induced by movements, most fNIRS studies have used a block design in which a subject conducts a set of repetitive movements for over a few seconds. Changes in hemoglobin induced by the series of movements are accumulated. Here, we address whether fNIRS can detect a phasic change induced by a discrete ballistic movement using an event-related design similar to those often adopted in fMRI experiments. To detect only event-related brain activity and to reduce the effect of artifacts, we adopted a general linear model whose design matrix contains data from the short transmitter-receiver distance channels that are considered components of artifacts. As a result, high event-related activity was detected in the contralateral sensorimotor cortex. We also compared the topographic functional map produced by fNIRS with the map given by an event-related fMRI experiment in which the same subjects performed exactly the same task. Both maps showed activity in equivalent areas, and the similarity was significant. We conclude that fNIRS affords the opportunity to explore motor-related brain activity even for discrete ballistic movements.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2012
Recently there has been an increase in the number of stroke patients with motor paralysis. Approp... more Recently there has been an increase in the number of stroke patients with motor paralysis. Appropriate re-afferent sensory feedback synchronized with a voluntary motor intention would be effective for promoting neural plasticity in the stroke rehabilitation. Therefore, BCI technology is considered to be a promising approach in the neuro-rehabilitation. To estimate human motor intention, an event-related desynchronization (ERD), a feature of electroencephalogram (EEG) evoked by motor execution or motor imagery is usually used. However, there exists various factors that affect ERD production, and its neural mechanism is still an open question. As a preliminary stage, we evaluate mutual effects of intrinsic (voluntary motor imagery) and extrinsic (visual and somatosensory stimuli) factors on the ERD production. Experimental results indicate that these three factors are not always additively interacting with each other and affecting the ERD production.
ABSTRACT Background: Children with autism exhibit motor dysfunctions including poor coordination ... more ABSTRACT Background: Children with autism exhibit motor dysfunctions including poor coordination and difficulty with performing/imitating skilled gestures. One of the crucial steps in motor learning is for the brain to form internal models: a mapping between motor commands and the expected visual and proprioceptive sensory feedback. These internal models are the basis for which the brain understands actions of others. However, it is not clear yet how the neural mechanism of internal model is disordered in the autistic brain. Objectives: In order to understand a mechanism of the motor disorder in the autistic brain, we examined the differences of the neural representation of internal model between high functioning children with autism (HFA) and typically developing children (TD). If the internal model is a mapping between motor commands and visual sensory feedback, the skill generalizes in Cartesian coordinates; whereas, if it were formed on proprioceptive space, the memory would generalize in the intrinsic coordinates of joints and muscles. The objective of the study was to quantify the property of the generalization of learning of internal model by examining how the learned motor memory could transfer to generalize across arm posture. Methods: HFA and TD children performed a reaching task that involved learning an internal model of a novel tool (a robotic arm). Subjects were trained to reach to the forward direction in left workspace while holding a robotic arm; the robotic arm produced a curl force field so that subjects had to learn to adapt their movements to hit the target. Learning was then tested in the left, as well as the right, workspace using a channel that clamped the trajectory error so that the force that the subject produced to compensate the applied force was measured. Generalization of learning to the right workspace was assessed using two directions: one required production of the identical movement in Cartesian (visually-based) coordinates and the other required the movement to be produced in joint coordinates. Results: Both HFA and TD adapted to the force similarly (F(1,408)=0.892, p=0.3543). We found the learning generalized in joint coordinates for both HFA and TD. This supports the results in our previous study, which suggests that an internal model relies on an association between proprioception and muscle forces. The new finding here is that HFA generalized in joint coordinates to significantly larger extent than TD (F(1,408)=8.91, p=0.0064). Conclusions: More generalization in joint coordinates implies that in learning an internal model of self generated action, the HFA brain builds a stronger than normal association between motor commands and proprioceptive feedback. Because the action perception involves information transformation between the visual feedback and the motor command, the larger than normal reliance on proprioception may explain deficits in action perception in HFA. Furthermore, because the brain of autistic children shows an overgrowth of localized white matter connections, it is possible that this abnormally strong association between motor commands and proprioception in HFA is a correlate of this anatomical feature.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2014
While motor imagery has been known as a powerful tool for neuro-rehabilitation in stroke patients... more While motor imagery has been known as a powerful tool for neuro-rehabilitation in stroke patients, whether this technique is also effective for other brain disorders is unclear. For instance, patients with Parkinson's disease or attention-deficit hyperactivity disorder who are impaired at real motor switching may benefit therapeutically from training that consists of switching their imagined motor movements, and eventually recover from the dysfunction. However, despite its importance little is known about exactly how switching mental images of one's actions is processed in the brain. Therefore, we set out to clarify this issue by measuring brain activity reflected in electroencephalograms as subjects switched an imagined hand rotation from one hand to the other during a motor-imagery task. By comparing electroencephalogram signals from repeated mental imaging of hand movements, we found a switch-specific decrease in the beta-band activity in parietal and frontal regions arou...
Motor memory is updated to generate ideal movements in a novel environment. When the environment ... more Motor memory is updated to generate ideal movements in a novel environment. When the environment changes every trial randomly, how does the brain incorporate this uncertainty into motor memory? To investigate how the brain adapts to an uncertain environment, we considered a reach adaptation protocol where individuals practiced moving in a force field where a noise was injected. After they had adapted, we measured the trial-to-trial variability in the temporal profiles of the produced hand force. We found that the motor variability was significantly magnified by the adaptation to the random force field. Temporal profiles of the motor variance were significantly dissociable between two different types of random force fields experienced. A model-based analysis suggests that the variability is generated by noise in the gains of the internal model. It further suggests that the trial-to-trial motor variability magnified by the adaptation in a random force field is generated by the uncertainty of the internal model formed in the brain as a result of the adaptation.
Computational models of motor learning have been examined experimentally with human participants ... more Computational models of motor learning have been examined experimentally with human participants using a robotic manipulandum that produces force perturbations on their reach trajectories. Here, we developed a small-scale robotic manipulandum for rodent studies. This device enabled us to conduct the same motor control experiments typically used for human study on rodents in order to examine the neural basis of the computational process of motor control and learning. We present the design of the manipulandum and controller system in addition to kinematic analysis of the link structures. We also confirmed the feasibility of the developed system for rodent studies. GRAPHICAL ABSTRACT
Motor learning is the process of updating motor commands in response to a trajectory error induce... more Motor learning is the process of updating motor commands in response to a trajectory error induced by a perturbation to the body or vision. The brain has a great capability to accelerate learning by increasing the sensitivity of the memory update to the perceived trajectory errors. Conventional theory suggests that the statistics of perturbations or the statistics of the experienced errors induced by the external perturbations determine the learning speeds. However, the potential effect of another type of error perception, a self-generated error as a result of motor command updates (i.e., an aftereffect), on the learning speeds has not been examined yet. In this study, we dissociated the two kinds of errors by controlling the perception of the aftereffect using a channel-force environment. One group experienced errors due to the aftereffect of the learning process, while the other did not. We found that the participants who perceived the aftereffect of the memory updates exhibited a...
Reinforcement learning enables the brain to learn optimal action selection, such as go or not go,... more Reinforcement learning enables the brain to learn optimal action selection, such as go or not go, by forming state-action and action-outcome associations. Does this mechanism also optimize the brain’s willingness to learn, such as learn or not learn? Learning to learn by rewards, i.e., reinforcement meta-learning, is a crucial mechanism for machines to develop flexibility in learning, which is also considered in the brain without empirical examinations. Here, we show that humans learn to learn or not learn to maximize rewards in visuomotor learning tasks. We also show that this regulation of learning is not a motivational bias but is a result of an instrumental, active process, which takes into account the learning-outcome structure. Our results thus demonstrate the existence of reinforcement meta-learning in the human brain. Because motor learning is a process of minimizing sensory errors, our findings uncover an essential mechanism of interaction between reward and error.
The visuomotor transformation during a goal-directed movement may involve a coordinate transforma... more The visuomotor transformation during a goal-directed movement may involve a coordinate transformation from visual 'extrinsic' to muscle-like 'intrinsic' coordinate frames, which might be processed via a multilayer network architecture composed of neural basis functions. This theory suggests that the postural change during a goal-directed movement task alters activity patterns of the neurons in the intermediate layer of the visuomotor transformation that recieves both visual and proprioceptive inputs, and thus influence the multi-voxel pattern of the blood oxygenation level dependent signal. Using a recently developed multi-voxel pattern decoding method, we found extrinsic, intrinsic and intermediate coordinate frames along the visuomotor cortical pathways during a visuomotor control task. The presented results support the hypothesis that, in human, the extrinsic coordinate frame was transformed to the muscle-like frame over the dorsal pathway from the posterior parie...
Functional near-infrared spectroscopy (fNIRS) is a widely utilized neuroimaging tool in fundament... more Functional near-infrared spectroscopy (fNIRS) is a widely utilized neuroimaging tool in fundamental neuroscience research and clinical investigation. Previous research has revealed that task-evoked systemic artifacts mainly originating from the superficial-tissue may preclude the identification of cerebral activation during a given task. We examined the influence of such artifacts on event-related brain activity during a brisk squeezing movement. We estimated task-evoked superficial-tissue hemodynamics from short source–detector distance channels (15 mm) by applying principal component analysis. The estimated superficial-tissue hemodynamics exhibited temporal profiles similar to the canonical cerebral hemodynamic model. Importantly, this task-evoked profile was also observed in data from a block design motor experiment, suggesting a transient increase in superficial-tissue hemodynamics occurs following motor behavior, irrespective of task design. We also confirmed that estimation of...
2013 6th International IEEE/EMBS Conference on Neural Engineering (NER), 2013
ABSTRACT Measuring discrete-trial motor-related brain activity using functional near-infrared spe... more ABSTRACT Measuring discrete-trial motor-related brain activity using functional near-infrared spectroscopy (fNIRS) is considered difficult. This is because its spatial resolution is much lower than that of functional magnetic resonance imaging (fMRI), and its signals include non-motion-related artifacts. To detect changes in hemoglobin induced by movements, most fNIRS studies have used a block design in which a subject conducts a set of repetitive movements for over a few seconds. Changes in hemoglobin induced by the series of movements are accumulated. Here, we address whether fNIRS can detect a phasic change induced by a discrete ballistic movement using an event-related design similar to those often adopted in fMRI experiments. To detect only event-related brain activity and to reduce the effect of artifacts, we adopted a general linear model whose design matrix contains data from the short transmitter-receiver distance channels that are considered components of artifacts. As a result, high event-related activity was detected in the contralateral sensorimotor cortex. We also compared the topographic functional map produced by fNIRS with the map given by an event-related fMRI experiment in which the same subjects performed exactly the same task. Both maps showed activity in equivalent areas, and the similarity was significant. We conclude that fNIRS affords the opportunity to explore motor-related brain activity even for discrete ballistic movements.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2012
Recently there has been an increase in the number of stroke patients with motor paralysis. Approp... more Recently there has been an increase in the number of stroke patients with motor paralysis. Appropriate re-afferent sensory feedback synchronized with a voluntary motor intention would be effective for promoting neural plasticity in the stroke rehabilitation. Therefore, BCI technology is considered to be a promising approach in the neuro-rehabilitation. To estimate human motor intention, an event-related desynchronization (ERD), a feature of electroencephalogram (EEG) evoked by motor execution or motor imagery is usually used. However, there exists various factors that affect ERD production, and its neural mechanism is still an open question. As a preliminary stage, we evaluate mutual effects of intrinsic (voluntary motor imagery) and extrinsic (visual and somatosensory stimuli) factors on the ERD production. Experimental results indicate that these three factors are not always additively interacting with each other and affecting the ERD production.
ABSTRACT Background: Children with autism exhibit motor dysfunctions including poor coordination ... more ABSTRACT Background: Children with autism exhibit motor dysfunctions including poor coordination and difficulty with performing/imitating skilled gestures. One of the crucial steps in motor learning is for the brain to form internal models: a mapping between motor commands and the expected visual and proprioceptive sensory feedback. These internal models are the basis for which the brain understands actions of others. However, it is not clear yet how the neural mechanism of internal model is disordered in the autistic brain. Objectives: In order to understand a mechanism of the motor disorder in the autistic brain, we examined the differences of the neural representation of internal model between high functioning children with autism (HFA) and typically developing children (TD). If the internal model is a mapping between motor commands and visual sensory feedback, the skill generalizes in Cartesian coordinates; whereas, if it were formed on proprioceptive space, the memory would generalize in the intrinsic coordinates of joints and muscles. The objective of the study was to quantify the property of the generalization of learning of internal model by examining how the learned motor memory could transfer to generalize across arm posture. Methods: HFA and TD children performed a reaching task that involved learning an internal model of a novel tool (a robotic arm). Subjects were trained to reach to the forward direction in left workspace while holding a robotic arm; the robotic arm produced a curl force field so that subjects had to learn to adapt their movements to hit the target. Learning was then tested in the left, as well as the right, workspace using a channel that clamped the trajectory error so that the force that the subject produced to compensate the applied force was measured. Generalization of learning to the right workspace was assessed using two directions: one required production of the identical movement in Cartesian (visually-based) coordinates and the other required the movement to be produced in joint coordinates. Results: Both HFA and TD adapted to the force similarly (F(1,408)=0.892, p=0.3543). We found the learning generalized in joint coordinates for both HFA and TD. This supports the results in our previous study, which suggests that an internal model relies on an association between proprioception and muscle forces. The new finding here is that HFA generalized in joint coordinates to significantly larger extent than TD (F(1,408)=8.91, p=0.0064). Conclusions: More generalization in joint coordinates implies that in learning an internal model of self generated action, the HFA brain builds a stronger than normal association between motor commands and proprioceptive feedback. Because the action perception involves information transformation between the visual feedback and the motor command, the larger than normal reliance on proprioception may explain deficits in action perception in HFA. Furthermore, because the brain of autistic children shows an overgrowth of localized white matter connections, it is possible that this abnormally strong association between motor commands and proprioception in HFA is a correlate of this anatomical feature.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2014
While motor imagery has been known as a powerful tool for neuro-rehabilitation in stroke patients... more While motor imagery has been known as a powerful tool for neuro-rehabilitation in stroke patients, whether this technique is also effective for other brain disorders is unclear. For instance, patients with Parkinson's disease or attention-deficit hyperactivity disorder who are impaired at real motor switching may benefit therapeutically from training that consists of switching their imagined motor movements, and eventually recover from the dysfunction. However, despite its importance little is known about exactly how switching mental images of one's actions is processed in the brain. Therefore, we set out to clarify this issue by measuring brain activity reflected in electroencephalograms as subjects switched an imagined hand rotation from one hand to the other during a motor-imagery task. By comparing electroencephalogram signals from repeated mental imaging of hand movements, we found a switch-specific decrease in the beta-band activity in parietal and frontal regions arou...
Motor memory is updated to generate ideal movements in a novel environment. When the environment ... more Motor memory is updated to generate ideal movements in a novel environment. When the environment changes every trial randomly, how does the brain incorporate this uncertainty into motor memory? To investigate how the brain adapts to an uncertain environment, we considered a reach adaptation protocol where individuals practiced moving in a force field where a noise was injected. After they had adapted, we measured the trial-to-trial variability in the temporal profiles of the produced hand force. We found that the motor variability was significantly magnified by the adaptation to the random force field. Temporal profiles of the motor variance were significantly dissociable between two different types of random force fields experienced. A model-based analysis suggests that the variability is generated by noise in the gains of the internal model. It further suggests that the trial-to-trial motor variability magnified by the adaptation in a random force field is generated by the uncertainty of the internal model formed in the brain as a result of the adaptation.
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