Papers by Tsuyoshi Ikegami
Motor contagions refer to implicit effects on one's actions induced by observed actions. Motor co... more Motor contagions refer to implicit effects on one's actions induced by observed actions. Motor contagions are believed to be induced simply by action observation and cause an observer's action to become similar to the action observed. In contrast, here we report a new motor contagion that is induced only when the observation is accompanied by prediction errors-differences between actions one observes and those he/she predicts or expects. In two experiments, one on whole-body baseball pitching and another on simple arm reaching, we show that the observation of the same action induces distinct motor contagions, depending on whether prediction errors are present or not. In the absence of prediction errors, as in previous reports, participants' actions changed to become similar to the observed action, while in the presence of prediction errors, their actions changed to diverge away from it, suggesting distinct effects of action observation and action prediction on human actions.
The question of how humans predict outcomes of observed motor actions by others is a fundamental ... more The question of how humans predict outcomes of observed motor actions by others is a fundamental problem in cognitive and social neuroscience. Previous theoretical studies have suggested that the brain uses parts of the forward model (used to estimate sensory outcomes of self-generated actions) to predict outcomes of observed actions. However, this hypothesis has remained controversial due to the lack of direct experimental evidence. To address this issue, we analyzed the behavior of darts experts in an understanding learning paradigm and utilized computational modeling to examine how outcome prediction of observed actions affected the participants' ability to estimate their own actions. We recruited darts experts because sports experts are known to have an accurate outcome estimation of their own actions as well as prediction of actions observed in others. We first show that learning to predict the outcomes of observed dart throws deteriorates an expert's abilities to both produce his own darts actions and estimate the outcome of his own throws (or self-estimation). Next, we introduce a state-space model to explain the trial-by-trial changes in the darts performance and self-estimation through our experiment. The model-based analysis reveals that the change in an expert's self-estimation is explained only by considering a change in the individual's forward model, showing that an improvement in an expert's ability to predict outcomes of observed actions affects the individual's forward model. These results suggest that parts of the same forward model are utilized in humans to both estimate outcomes of self-generated actions and predict outcomes of observed actions. Significance Statement Do the neural circuits referred to as forward models, which help humans estimate sensory outcomes of self-generated actions, also help them predict the outcome of other's actions? To address this question, we examined the interactions between one's estimation of self-generated actions and the prediction of other's actions. We first show that learning to predict the outcome of observed actions affects one's ability to both produce actions and estimate the outcome of self-generated actions. Next, using a model-based analysis, we show that these affects cannot be explained without a change in one's forward model. Our results suggest the presence of shared mechanisms in the human brain for the estimation of self-generated actions and the prediction of other's actions.
Springer Tracts in Advanced Robotics, 2015
Neuroscience Research, 2011
Neuroscience Research, 2010
Our social skills are critically determined by our ability to understand and appropriately respon... more Our social skills are critically determined by our ability to understand and appropriately respond to actions
performed by others. However despite its obvious importance, the mechanisms enabling action
understanding in humans have remained largely unclear. A popular but controversial belief is that parts of
the motor system contribute to our ability to understand observed actions. Here, using a novel behavioral
paradigm, we investigated this belief by examining a causal relation between action production, and a
component of action understanding - outcome prediction, the ability of a person to predict the outcome of
observed actions. We asked dart experts to watch novice dart throwers and predict the outcome of their
throws. We modulated the feedbacks provided to them, caused a specific improvement in the expert’s ability
to predict watched actions while controlling the other experimental factors, and exhibited that a change
(improvement) in their outcome prediction ability results in a progressive and proportional deterioration in
the expert’s own darts performance. This causal relationship supports involvement of the motor system in
outcome prediction by humans of actions observed in others.
Human dexterity with tools is believed to stem from our ability to incorporate and use tools as p... more Human dexterity with tools is believed to stem from our ability to incorporate and use tools as parts of our body. However tool incorporation, evident as extensions in our body representation and peri-personal space, has been observed predominantly after extended tool exposures and does not explain our immediate motor behaviours when we change tools. Here we utilize two novel experiments to elucidate the presence of additional immediate tool incorporation effects that determine motor planning with tools. Interestingly, tools were observed to immediately induce a trial-by-trial, tool length dependent shortening of the perceived limb lengths, opposite to observations of elongations after extended tool use. Our results thus exhibit that tools induce a dual effect on our body representation; an immediate shortening that critically affects motor planning with a new tool, and the slow elongation, probably a consequence of skill related changes in sensory-motor mappings with the repeated use of the tool.
Understanding how the brain learns motor skills remains a very challenging task. To elucidate the... more Understanding how the brain learns motor skills remains a very challenging task. To elucidate the neural mechanism underlying motor learning, we assessed brain activation changes on a trial-by-trial basis during learning of a multi-joint discrete motor task (kendama task). We used multi-channel near-infrared spectroscopy (NIRS) while simultaneously measuring upper limb movement changes by using a 3D motion capture system. Fourteen right-handed participants performed the task using their right upper limb while sitting a chair. The task involved tossing a ball connected by a string to the kendama stick (picking up movement) and catching the ball in the cup attached to the stick (catching movement). Participants performed a trial every 20 s for 90 trials. We measured the hemodynamic responses [oxygenated hemoglobin (oxy-Hb) and deoxygenated hemoglobin (deoxy-Hb) signals] around the predicted location of the sensorimotor cortices on both hemispheres. Analysis of the NIRS data revealed that the magnitudes of the event-related oxy-Hb responses to each trial decreased significantly as learning progressed. Analysis of movement data revealed that integrated upper limb muscle torques decreased significantly only for the picking up movements as learning progressed, irrespective of the outcome of the trials. In contrast, dispersion of the movement patterns decreased significantly only for the catching movements in the unsuccessful trials. Furthermore, we found significant positive correlations between the changes in the magnitudes of the oxy-Hb responses and those of the integrated upper limb muscle torques during learning. Our results suggest that the decrease in cortical activation in the sensorimotor cortex reflects changes in motor commands during learning of a multi-joint discrete movement.
As long as we only focus on kinematics, rhythmic movement appears to be a concatenation of discre... more As long as we only focus on kinematics, rhythmic movement appears to be a concatenation of discrete movements or discrete movement appears to be a truncated rhythmic movement. However, whether or not the neural control processes of discrete and rhythmic movements are distinct has not yet been clearly understood. Here, we address this issue by examining the motor learning transfer between these two types of movements testing the hypothesis that distinct neural control processes should lead to distinct motor learning and transfer. First, we found that the adaptation to an altered visuomotor condition was almost fully transferred from the discrete out-and-back movements to the rhythmic out-and-back movements; however, the transfer from the rhythmic to discrete movements was very small. Second, every time a new set of rhythmic movements was started, a considerable amount of movement error reappeared in the first and the following several cycles although the error converged to a small level by the end of each set. Last, we observed that when the discrete movement training was performed with intertrial intervals longer than 4 s, a significantly larger error appeared, specifically for the second and third cycles of the subsequent rhythmic movements, despite a seemingly full transfer to the first cycle. These results provide strong behavioral evidence that different neuronal control processes are involved in the two types of movements and that discrete control processes contribute to the generation of the first cycle of the rhythmic movement.
Movement error is a driving force behind motor learning. For motor learning with discrete movemen... more Movement error is a driving force behind motor learning. For motor learning with discrete movements, such as point-to-point reaching, it is believed that the brain uses error information of the immediately preceding movement only. However, in the case of continuous and repetitive movements (i.e., rhythmic movements), there is a ceaseless inflow of performance information. Thus, an accurate temporal association of the motor commands with the resultant movement errors is not necessarily guaranteed. We investigated how the brain overcomes this challenging situation. Human participants adapted rhythmic movements between two targets to visuomotor rotations, the amplitudes of which changed randomly from cycle to cycle (the duration of one cycle was ∼400 ms). A system identification technique revealed that the motor adaptation was affected not just by the preceding movement error, but also by a history of errors from the previous cycles. Error information obtained from more than one previous cycle tended to increase, rather than decrease, movement error. This result led to a counterintuitive prediction: providing visual error feedback for only a fraction of cycles should enhance visuomotor adaptation. As predicted, we observed that motor adaptation to a constant visual rotation (30°) was significantly enhanced by providing visual feedback once every fourth or fifth cycle rather than for every cycle. These results suggest that the brain requires a specific processing time to modify the motor command, based on the error information, and so is unable to deal appropriately with the overwhelming flow of error information generated during rhythmic movements.
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Papers by Tsuyoshi Ikegami
performed by others. However despite its obvious importance, the mechanisms enabling action
understanding in humans have remained largely unclear. A popular but controversial belief is that parts of
the motor system contribute to our ability to understand observed actions. Here, using a novel behavioral
paradigm, we investigated this belief by examining a causal relation between action production, and a
component of action understanding - outcome prediction, the ability of a person to predict the outcome of
observed actions. We asked dart experts to watch novice dart throwers and predict the outcome of their
throws. We modulated the feedbacks provided to them, caused a specific improvement in the expert’s ability
to predict watched actions while controlling the other experimental factors, and exhibited that a change
(improvement) in their outcome prediction ability results in a progressive and proportional deterioration in
the expert’s own darts performance. This causal relationship supports involvement of the motor system in
outcome prediction by humans of actions observed in others.
performed by others. However despite its obvious importance, the mechanisms enabling action
understanding in humans have remained largely unclear. A popular but controversial belief is that parts of
the motor system contribute to our ability to understand observed actions. Here, using a novel behavioral
paradigm, we investigated this belief by examining a causal relation between action production, and a
component of action understanding - outcome prediction, the ability of a person to predict the outcome of
observed actions. We asked dart experts to watch novice dart throwers and predict the outcome of their
throws. We modulated the feedbacks provided to them, caused a specific improvement in the expert’s ability
to predict watched actions while controlling the other experimental factors, and exhibited that a change
(improvement) in their outcome prediction ability results in a progressive and proportional deterioration in
the expert’s own darts performance. This causal relationship supports involvement of the motor system in
outcome prediction by humans of actions observed in others.