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Although a limb's motion appears to be similar across unimanual and bimanual movements, here we demonstrate partial, but not complete, transfer of learning across these behavioral contexts, hidden learning that remains intact (but invisible) until the original context is again encountered, and the ability to associate two conflicting force fields(More)
Rapid sequential taps delivered first to one location and then to another on the skin create the somatosensory illusion that the tapping is occurring at intermediate locations between the actual stimulus sites, as if a small rabbit were hopping along the skin from the first site to the second (called the "cutaneous rabbit"). Previous behavioral studies have(More)
We can adapt movements to a novel dynamic environment (e.g., tool use, microgravity, and perturbation) by acquiring an internal model of the dynamics. Although multiple environments can be learned simultaneously if each environment is experienced with different limb movement kinematics, it is controversial as to whether multiple internal models for a(More)
Bimanual action requires the neural controller (internal model) for each arm to predictively compensate for mechanical interactions resulting from movement of both that arm and its counterpart on the opposite side of the body. Here, we demonstrate that the brain may accomplish this by constructing the internal model with primitives multiplicatively encoding(More)
A sensorimotor control task often requires an accurate estimation of the timing of the arrival of an external target (e.g., when hitting a pitched ball). Conventional studies of human timing processes have ignored the stochastic features of target timing: e.g., the speed of the pitched ball is not generally constant, but is variable. Interestingly, based on(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(More)
Multi-limb motor skills, such as swimming and rowing, often involve isolated practice of each limb (unimanual) followed by practice with both limbs together (bimanual). We recently demonstrated that learning a novel load during unimanual reaching is partially, but not completely transferred to the same limb during bimanual reaching (and vice versa),(More)
Computational theory of motor control suggests that the brain continuously monitors motor commands, to predict their sensory consequences before actual sensory feedback becomes available. Such prediction error is a driving force of motor learning, and therefore appropriate associations between motor commands and delayed sensory feedback signals are crucial.(More)
Diverse features of motor learning have been reported by numerous studies, but no single theoretical framework concurrently accounts for these features. Here, we propose a model for motor learning to explain these features in a unified way by extending a motor primitive framework. The model assumes that the recruitment pattern of motor primitives is(More)
We propose a generalized method to estimate waveforms common across trials from electroencephalographic (EEG) data. From single/multi-channel EEGs, the proposed method estimates the number of waveforms common across trials, their delays in individual trials, and all of the waveforms. After verifying the performance of this method by a number of simulation(More)