Spatiotemporal bias of the human gaze toward hierarchical visual features during natural scene viewing.

The human gaze is directed at various locations from moment to moment in acquiring information necessary to recognize the external environment at the fine resolution of foveal vision. Previous studies showed that the human gaze is attracted to particular locations in the visual field at a particular time, but it remains unclear what visual features produce such spatiotemporal bias. In this study, we used a deep convolutional neural network model to extract hierarchical visual features from natural scene images and evaluated how much the human gaze is attracted to the visual features in space and time.

Bodily ownership of an independent supernumerary limb: an exploratory study.

Can our brain perceive a sense of ownership towards an independent supernumerary limb; one that can be moved independently of any other limb and provides its own independent movement feedback? Following the rubber-hand illusion experiment, a plethora of studies have shown that the human representation of "self" is very plastic. But previous studies have almost exclusively investigated ownership towards "substitute" artificial limbs, which are controlled by the movements of a real limb and/or limbs from which non-visual sensory feedback is provided on an existing limb. Here, to investigate whether the human brain can own an independent artificial limb, we first developed a novel independent robotic "sixth finger.

Information spreading by a combination of MEG source estimation and multivariate pattern classification.

To understand information representation in human brain activity, it is important to investigate its fine spatial patterns at high temporal resolution. One possible approach is to use source estimation of magnetoencephalography (MEG) signals. Previous studies have mainly quantified accuracy of this technique according to positional deviations and dispersion of estimated sources, but it remains unclear how accurately MEG source estimation restores information content represented by spatial patterns of brain activity.

Multivariate Analysis of Magnetic Resonance Imaging Signals of the Human Brain.

Magnetic resonance imaging (MRI) of the human brain plays an important role in the field of medical imaging as well as basic neuroscience. It measures proton spin relaxation, the time constant of which depends on tissue type, and allows us to visualize anatomical structures in the brain. It can also measure functional signals that depend on the local ratio of oxyhemoglobin to deoxyhemoglobin in the blood, which is believed to reflect the degree of neural activity in the corresponding area.

Inter-subject neural code converter for visual image representation.

Brain activity patterns differ from person to person, even for an identical stimulus. In functional brain mapping studies, it is important to align brain activity patterns between subjects for group statistical analyses. While anatomical templates are widely used for inter-subject alignment in functional magnetic resonance imaging (fMRI) studies, they are not sufficient to identify the mapping between voxel-level functional responses representing specific mental contents.

Modular encoding and decoding models derived from bayesian canonical correlation analysis.

Neural encoding and decoding provide perspectives for understanding neural representations of sensory inputs. Recent functional magnetic resonance imaging (fMRI) studies have succeeded in building prediction models for encoding and decoding numerous stimuli by representing a complex stimulus as a combination of simple elements. While arbitrary visual images were reconstructed using a modular model that combined the outputs of decoder modules for multiscale local image bases (elements), the shapes of the image bases were heuristically determined.

Spike suppression in a local cortical circuit induced by transcranial magnetic stimulation.

Transcranial magnetic stimulation (TMS) noninvasively interferes with human cortical function, and is widely used as an effective technique for probing causal links between neural activity and cognitive function. However, the physiological mechanisms underlying TMS-induced effects on neural activity remain unclear. We examined the mechanism by which TMS disrupts neural activity in a local circuit in early visual cortex using a computational model consisting of conductance-based spiking neurons with excitatory and inhibitory synaptic connections.

Influence of coherence between multiple cortical columns on alpha rhythm: a computational modeling study.

In electroencephalographic (EEG) and magnetoencephalographic (MEG) signals, stimulus-induced amplitude increase and decrease in the alpha rhythm, known as event-related synchronization and desynchronization (ERS/ERD), emerge after a task onset. ERS/ERD is assumed to reflect neural processes relevant to cognitive tasks. Previous studies suggest that several sources of alpha rhythm, each of which can serve as an alpha rhythm generator, exist in the cortex.

Visual image reconstruction from human brain activity using a combination of multiscale local image decoders.

Perceptual experience consists of an enormous number of possible states. Previous fMRI studies have predicted a perceptual state by classifying brain activity into prespecified categories. Constraint-free visual image reconstruction is more challenging, as it is impractical to specify brain activity for all possible images.

A network model of perceptual suppression induced by transcranial magnetic stimulation.

We modeled the inhibitory effects of transcranial magnetic stimulation (TMS) on a neural population. TMS is a noninvasive technique, with high temporal resolution, that can stimulate the brain via a brief magnetic pulse from a coil placed on the scalp. Because of these advantages, TMS is extensively used as a powerful tool in experimental studies of motor, perception, and other functions in humans.

Unconscious adaptation: a new illusion of depth induced by stimulus features without depth.

Here, we show a new illusion of depth induced by psychophysical adaptation to dynamic random-dot stereograms (RDS) that are interocularly anticorrelated (i.e., in which the images for the two eyes have reversed contrast polarity with each other).