Naotaka Fujii

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Brain-machine interfaces (BMIs) employ the electrical activity generated by cortical neurons directly for controlling external devices and have been conceived as a means for restoring human cognitive or sensory-motor functions. The dominant approach in BMI research has been to decode motor variables based on single-unit activity (SUA). Unfortunately, this(More)
A new generalized multilinear regression model, termed the higher order partial least squares (HOPLS), is introduced with the aim to predict a tensor (multiway array) Y from a tensor X through projecting the data onto the latent space and performing regression on the corresponding latent variables. HOPLS differs substantially from other regression models in(More)
Primate neurophysiology has revealed various neural mechanisms at the single-cell level and population level. However, because recording techniques have not been updated for several decades, the types of experimental design that can be applied in the emerging field of social neuroscience are limited, in particular those involving interactions within a(More)
When humans use a tool, it becomes an extension of the hand physically and perceptually. Common introspection might occur in monkeys trained in tool-use, which should depend on brain operations that constantly update and automatically integrate information about the current intrinsic (somatosensory) and the extrinsic (visual) status of the body parts and(More)
Brain–machine interface (BMI) technology captures brain signals to enable control of prosthetic or communication devices with the goal of assisting patients who have limited or no ability to perform voluntary movements. Decoding of inherent information in brain signals to interpret the user’s intention is one of main approaches for developing BMI(More)
Accumulating evidence indicates that the capacity to integrate information in the brain is a prerequisite for consciousness. Integrated Information Theory (IIT) of consciousness provides a mathematical approach to quantifying the information integrated in a system, called integrated information, Φ. Integrated information is defined theoretically as the(More)
Humans show spontaneous synchronization of movements during social interactions; this coordination has been shown to facilitate smooth communication. Although human studies exploring spontaneous synchronization are increasing in number, little is known about this phenomenon in other species. In this study, we examined spontaneous behavioural synchronization(More)
Brain-wide interactions generating complex neural dynamics are considered crucial for emergent cognitive functions. However, the irreducible nature of nonlinear and high-dimensional dynamical interactions challenges conventional reductionist approaches. We introduce a model-free method, based on embedding theorems in nonlinear state-space reconstruction,(More)
Social brain function, which allows us to adapt our behavior to social context, is poorly understood at the single-cell level due largely to technical limitations. But the questions involved are vital: How do neurons recognize and modulate their activity in response to social context? To probe the mechanisms involved, we developed a novel recording(More)
Socially correct behavior requires constant observation of the social environment. Behavior that was appropriate a few seconds ago is not guaranteed to be appropriate now. The brain keeps the eyes focused on the current social space and constantly updates its internal representation of the environment and social context. Monitoring the behavior of others is(More)