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Toshio Inui
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Journal Articles
Publisher: Journals Gateway
Journal of Cognitive Neuroscience (2014) 26 (2): 232–246.
Published: 01 February 2014
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Previous studies have suggested that the posterior parietal cortices and premotor areas are involved in mental image transformation. However, it remains unknown whether these regions really cooperate to realize mental image transformation. In this study, simultaneous EEG and fMRI were performed to clarify the spatio-temporal properties of neural networks engaged in mental image transformation. We adopted a modified version of the mental clock task used by Sack et al. [Sack, A. T., Camprodon, J. A., Pascual-Leone, A., & Goebel, R. The dynamics of interhemispheric compensatory processes in mental imagery. Science, 308, 702–704, 2005; Sack, A. T., Sperling, J. M., Prvulovic, D., Formisano, E., Goebel, R., Di Salle, F., et al. Tracking the mind's image in the brain II: Transcranial magnetic stimulation reveals parietal asymmetry in visuospatial imagery. Neuron, 35, 195–204, 2002]. In the modified mental clock task, participants mentally rotated clock hands from the position initially presented at a learned speed for various durations. Subsequently, they matched the position to the visually presented clock hands. During mental rotation of the clock hands, we observed significant beta EEG suppression with respect to the amount of mental rotation at the right parietal electrode. The beta EEG suppression accompanied activity in the bilateral parietal cortices and left premotor cortex, representing a dynamic cortical network for mental image transformation. These results suggest that motor signals from the premotor area were utilized for mental image transformation in the parietal areas and for updating the imagined clock hands represented in the right posterior parietal cortex.
Journal Articles
Publisher: Journals Gateway
Journal of Cognitive Neuroscience (2012) 24 (1): 171–182.
Published: 01 January 2012
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Visually guided reaching involves the transformation of a spatial position of a target into a body-centered reference frame. Although involvement of the posterior parietal cortex (PPC) has been proposed in this visuomotor transformation, it is unclear whether human PPC uses visual or body-centered coordinates in visually guided movements. We used a delayed visually guided reaching task, together with an fMRI multivoxel pattern analysis, to reveal the reference frame used in the human PPC. In experiments, a target was first presented either to the left or to the right of a fixation point. After a delay period, subjects moved a cursor to the position where the target had previously been displayed using either a normal or a left–right reversed mouse. The activation patterns of normal sessions were first used to train the classifier to predict movement directions. The activity patterns of the reversed sessions were then used as inputs to the decoder to test whether predicted directions correspond to actual movement directions in either visual or body-centered coordinates. When the target was presented before actual movement, the predicted direction in the medial intraparietal cortex was congruent with the actual movement in the body-centered coordinates, although the averaged signal intensities were not significantly different between two movement directions. Our results indicate that the human medial intraparietal cortex uses body-centered coordinates to encode target position or movement directions, which are crucial for visually guided movements.
Journal Articles
Publisher: Journals Gateway
Journal of Cognitive Neuroscience (2007) 19 (11): 1827–1835.
Published: 01 November 2007
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Internal monitoring or state estimation of movements is essential for human motor control to compensate for inherent delays and noise in sensorimotor loops. Two types of internal estimation of movements exist: self-generated movements, and externally generated movements. We used functional magnetic resonance imaging to investigate differences in brain activity for internal monitoring of self- versus externally generated movements during visual occlusion. Participants tracked a sinusoidally moving target with a mouse cursor. On some trials, vision of either target (externally generated) or cursor (self-generated) movement was transiently occluded, during which subjects continued tracking by estimating current position of either the invisible target or cursor on screen. Analysis revealed that both occlusion conditions were associated with increased activity in the presupplementary motor area and decreased activity in the right lateral occipital cortex compared to a control condition with no occlusion. Moreover, the right and left posterior parietal cortex (PPC) showed greater activation during occlusion of target and cursor movements, respectively. This study suggests lateralization of the PPC for internal monitoring of internally versus externally generated movements, fully consistent with previously reported clinical findings.
Journal Articles
Publisher: Journals Gateway
Journal of Cognitive Neuroscience (2006) 18 (12): 2088–2107.
Published: 01 November 2006
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One of the functions of everyday human language is to communicate meaning. Thus, when one hears or reads the sentence, “John gave a book to Mary,” some aspect of an event concerning the transfer of possession of a book from John to Mary is (hopefully) transmitted. One theoretical approach to language referred to as construction grammar emphasizes this link between sentence structure and meaning in the form of grammatical constructions. The objective of the current research is to (1) outline a functional description of grammatical construction processing based on principles of psycholinguistics, (2) develop a model of how these functions can be implemented in human neurophysiology, and then (3) demonstrate the feasibility of the resulting model in processing languages of typologically diverse natures, that is, English, French, and Japanese. In this context, particular interest will be directed toward the processing of novel compositional structure of relative phrases. The simulation results are discussed in the context of recent neurophysiological studies of language processing.