Takatsugu Aihara

Internal noise determines external stochastic resonance in visual perception

We provide the first experimental evidence that the internal noise level determines whether external noise can enhance the detectability of a weak signal. We conduct a visual detection experiment in the absence and presence of visual noise. We define three indices of external stochastic resonance effects, consider the spread of the psychometric function without external noise as an internal noise level index, and find that the indices of external stochastic resonance effects negatively correlate with the internal noise level index. Our results suggest that external stochastic resonance depends not only on the external but also on the internal noise level.

Anodal transcranial direct current stimulation of the right anterior temporal lobe did not significantly affect verbal insight

Humans often utilize past experience to solve difficult problems. However, if past experience is insufficient to solve a problem, solvers may reach an impasse. Insight can be valuable for breaking an impasse, enabling the reinterpretation or re-representation of a problem. Previous studies using between-subjects designs have revealed a causal relationship between the anterior temporal lobes (ATLs) and non-verbal insight, by enhancing the right ATL while inhibiting the left ATL using transcranial direct current stimulation (tDCS). In addition, neuroimaging studies have reported a correlation between right ATL activity and verbal insight. Based on these findings, we hypothesized that the right ATL is causally related to both non-verbal and verbal insight. To test this hypothesis, we conducted an experiment with 66 subjects using a within-subjects design, which typically has greater statistical power than a between-subjects design. Subjects participated in tDCS experiments across 2 days, in which they solved both non-verbal and verbal insight problems under active or sham stimulation conditions. To dissociate the effects of right ATL stimulation from those of left ATL stimulation, we used two montage types; anodal tDCS of the right ATL together with cathodal tDCS of the left ATL (stimulating both ATLs) and anodal tDCS of the right ATL with cathodal tDCS of the left cheek (stimulating only the right ATL). The montage used was counterbalanced across subjects. Statistical analyses revealed that, regardless of the montage type, there were no significant differences between the active and sham conditions for either verbal or non-verbal insight, although the finding for non-verbal insight was inconclusive because of a lack of statistical power. These results failed to support previous findings suggesting that the right ATL is the central locus of insight.

Large-scale brain network associated with creative insight: combined voxel-based morphometry and resting-state functional connectivity analyses

Creative insight occurs with an “Aha!” experience when solving a difficult problem. Here, we investigated large-scale networks associated with insight problem solving. We recruited 232 healthy participants aged 21–69 years old. Participants completed a magnetic resonance imaging study (MRI; structural imaging and a 10 min resting-state functional MRI) and an insight test battery (ITB) consisting of written questionnaires (matchstick arithmetic task, remote associates test, and insight problem solving task). To identify the resting-state functional connectivity (RSFC) associated with individual creative insight, we conducted an exploratory voxel-based morphometry (VBM)-constrained RSFC analysis. We identified positive correlations between ITB score and grey matter volume (GMV) in the right insula and middle cingulate cortex/precuneus, and a negative correlation between ITB score and GMV in the left cerebellum crus 1 and right supplementary motor area. We applied seed-based RSFC analysis to whole brain voxels using the seeds obtained from the VBM and identified insight-positive/negative connections, i.e. a positive/negative correlation between the ITB score and individual RSFCs between two brain regions. Insight-specific connections included motor-related regions whereas creative-common connections included a default mode network. Our results indicate that creative insight requires a coupling of multiple networks, such as the default mode, semantic and cerebral-cerebellum networks.

Brain imaging of motor control activity using EEG and a combination of Hierarchical Variational Bayesian method and Sparse Logistic Regression

we observed individual neurons of the mouse brain using hard x-ray Talbottype phase-contrast micro-tomography with 1 m resolution at SPring-8. Furthermore, a nano-resolution hard x-ray Zernike-type phase-contrast microscope revealed nerve fibers and organelles including mitochondria and synapses in the neural tissue. In the near future, we will utilize that information to begin deciphering the wiring diagram of the brain by using the nano-resolution x-ray tomography.

Load-dependent and abnormal lateralization during paretic finger movement: A NIRS-EEG study

They were longer than the onset latency of motor evoked potential after stimulation of the cortical leg area by ca. 5 ms at the shortest. The facilitation disappeared during repetitive voluntary contractions of the thigh muscles, cycling without BB contraction, or stimulation of cortical leg area. Thus, corticospinal excitations to thigh muscles can be induced from the cortical arm area. Their short latencies, together with the short interstimulus interval to observe them, suggest that they are mediated by cervical PNs.

Bayesian adaptive estimation of a psychometric model for stochastic resonance

Only a few softwares are available for neuron tracing and 3D reconstruction based on serial sections, but the costs is rather expensive. We developed a new inexpensive Windows®-based tracing system “NeuroShape”. The conventional bright-field microscope, video camera and digital linear scale are used. A personal computer is linked to the camera and the scale via USB interfaces. Microscopic view is overlaid on a video image captured. Users then trace the neuronal structures specifying XY coordinates by mouse operation and Z coordinate by microscope focusing. Shrinkage correction is also available. The virtual reality modeling language (VRML) is used to obtain 3D view. Final 3D views are shown interactively. We could build the system with few expense and stress the usefulness for exploring the 3D structure of neurons.

Bayesian Adaptive Estimation of Psychometric Functions in Noisy Environments

We propose a new psychometric model incorporating noise as well as stimulus effects, based on recent findings that noise can improve human perception via a mechanism of stochastic resonance (SR). This model assumes that the psychometric function can be regarded as a bivariate function of noise and stimulus intensities. The algorithm of the Ψ Bayesian adaptive estimation method is modified so that it is applicable to our new model. In computer simulations, our new procedure successfully estimates the bivariate psychometric function within a few hundred trials. We also demonstrate several examples in which the procedure is applied to actual psychophysical experiments.