Increased functional connectivity following ingestion of dried bonito soup.

Soup, including dried bonito broth, is customarily consumed as an umami taste during meals in Japan. Previous functional magnetic resonance imaging (fMRI) studies have investigated neuronal activation following human exposure to carbohydrates and umami substances. However, neuronal activity following ingestion of dried bonito soup has not been investigated. Additionally, recent progress in fMRI has enabled us to investigate the functional connectivity between two anatomically separated regions, such as the default mode network. In this study, we first investigated the altered functional connectivity after ingesting dried bonito soup in healthy volunteers. Functional connectivity in several brain regions, including the connection between the vermis, part of the cerebellum, and bilateral central opercular cortex, was markedly increased after ingesting dried bonito soup, compared to the ingestion of hot water. Physiological scaling showed that satiety was substantially increased by ingesting hot water rather than dried bonito soup. These results indicate that increased functional connectivity reflects the post-ingestive information pathway of dried bonito soup.

Comparison of local activation, functional connectivity, and structural connectivity in the N-back task.

The N-back task is widely used to investigate working memory. Previous functional magnetic resonance imaging (fMRI) studies have shown that local brain activation depends on the difficulty of the N-back task. Recently, changes in functional connectivity and local activation during a task, such as a single-hand movement task, have been reported to give the distinct information. However, previous studies have not investigated functional connectivity changes in the entire brain during N-back tasks. In this study, we compared alterations in functional connectivity and local activation related to the difficulty of the N-back task. Because structural connectivity has been reported to be associated with local activation, we also investigated the relationship between structural connectivity and accuracy in a N-back task using diffusion tensor imaging (DTI). Changes in functional connectivity depend on the difficulty of the N-back task in a manner different from local activation, and the 2-back task is the best method for investigating working memory. This indicates that local activation and functional connectivity reflect different neuronal events during the N-back task. The top 10 structural connectivities associated with accuracy in the 2-back task were locally activated during the 2-back task. Therefore, structural connectivity as well as fMRI will be useful for predicting the accuracy of the 2-back task.

Functional ultrasound reveals effects of MRI acoustic noise on brain function.

Loud acoustic noise from the scanner during functional magnetic resonance imaging (fMRI) can affect functional connectivity (FC) observed in the resting state, but the exact effect of the MRI acoustic noise on resting state FC is not well understood. Functional ultrasound (fUS) is a neuroimaging method that visualizes brain activity based on relative cerebral blood volume (rCBV), a similar neurovascular coupling response to that measured by fMRI, but without the audible acoustic noise. In this study, we investigated the effects of different acoustic noise levels (silent, 80 dB, and 110 dB) on FC by measuring resting state fUS (rsfUS) in awake mice in an environment similar to fMRI measurement. Then, we compared the results to those of resting state fMRI (rsfMRI) conducted using an 11.7 Tesla scanner. RsfUS experiments revealed a significant reduction in FC between the retrosplenial dysgranular and auditory cortexes (0.56 ± 0.07 at silence vs 0.05 ± 0.05 at 110 dB, p=.01) and a significant increase in FC anticorrelation between the infralimbic and motor cortexes (-0.21 ± 0.08 at silence vs -0.47 ± 0.04 at 110 dB, p=.017) as acoustic noise increased from silence to 80 dB and 110 dB, with increased consistency of FC patterns between rsfUS and rsfMRI being found with the louder noise conditions. Event-related auditory stimulation experiments using fUS showed strong positive rCBV changes (16.5% ± 2.9% at 110 dB) in the auditory cortex, and negative rCBV changes (-6.7% ± 0.8% at 110 dB) in the motor cortex, both being constituents of the brain network that was altered by the presence of acoustic noise in the resting state experiments. Anticorrelation between constituent brain regions of the default mode network (such as the infralimbic cortex) and those of task-positive sensorimotor networks (such as the motor cortex) is known to be an important feature of brain network antagonism, and has been studied as a biological marker of brain disfunction and disease. This study suggests that attention should be paid to the acoustic noise level when using rsfMRI to evaluate the anticorrelation between the default mode network and task-positive sensorimotor network.

Increased interhemispheric functional connectivity during non-dominant hand movement in right-handed subjects.

Hand preference is one of the behavioral expressions of lateralization in the brain. Previous fMRI studies showed the activation in several regions including the motor cortex and the cerebellum during single-hand movement. However, functional connectivity related to hand preference has not been investigated. Here, we used the generalized psychophysiological interaction (gPPI) approach to investigate the alteration of functional connectivity during single-hand movement from the resting state in right-hand subjects. The functional connectivity in interhemispheric motor-related regions including the supplementary motor area, the precentral gyrus, and the cerebellum was significantly increased during non-dominant hand movement, while functional connectivity was not increased during dominant hand movement. The general linear model (GLM) showed activation in contralateral supplementary motor area, contralateral precentral gyrus, and ipsilateral cerebellum during right- or left-hand movement. These results indicate that a combination of GLM and gPPI analysis can detect the lateralization of hand preference more clearly.

Brain-wide mapping of resting-state networks in mice using high-frame rate functional ultrasound.

Functional ultrasound (fUS) imaging is a method for visualizing deep brain activity based on cerebral blood volume changes coupled with neural activity, while functional MRI (fMRI) relies on the blood-oxygenation-level-dependent signal coupled with neural activity. Low-frequency fluctuations (LFF) of fMRI signals during resting-state can be measured by resting-state fMRI (rsfMRI), which allows functional imaging of the whole brain, and the distributions of resting-state network (RSN) can then be estimated from these fluctuations using independent component analysis (ICA). This procedure provides an important method for studying cognitive and psychophysiological diseases affecting specific brain networks. The distributions of RSNs in the brain-wide area has been reported primarily by rsfMRI. RSNs using rsfMRI are generally computed from the time-course of fMRI signals for more than 5 min. However, a recent dynamic functional connectivity study revealed that RSNs are still not perfectly stable even after 10 min. Importantly, fUS has a higher temporal resolution and stronger correlation with neural activity compared with fMRI. Therefore, we hypothesized that fUS applied during the resting-state for a shorter than 5 min would provide similar RSNs compared to fMRI. High temporal resolution rsfUS data were acquired at 10 Hz in awake mice. The quality of the default mode network (DMN), a well-known RSN, was evaluated using signal-noise separation (SNS) applied to different measurement durations of rsfUS. The results showed that the SNS did not change when the measurement duration was increased to more than 210 s. Next, we measured short-duration rsfUS multi-slice measurements in the brain-wide area. The results showed that rsfUS with the short duration succeeded in detecting RSNs distributed in the brain-wide area consistent with RSNs detected by 11.7-T MRI under awake conditions (medial prefrontal cortex and cingulate cortex in the anterior DMN, retrosplenial cortex and visual cortex in the posterior DMN, somatosensory and motor cortexes in the lateral cortical network, thalamus, dorsal hippocampus, and medial cerebellum), confirming the reliability of the RSNs detected by rsfUS. However, bilateral RSNs located in the secondary somatosensory cortex, ventral hippocampus, auditory cortex, and lateral cerebellum extracted from rsfUS were different from the unilateral RSNs extracted from rsfMRI. These findings indicate the potential of rsfUS as a method for analyzing functional brain networks and should encourage future research to elucidate functional brain networks and their relationships with disease model mice.

Basal ganglia-cortical connectivity underlies self-regulation of brain oscillations in humans.

Brain-computer interfaces provide an artificial link by which the brain can directly interact with the environment. To achieve fine brain-computer interface control, participants must modulate the patterns of the cortical oscillations generated from the motor and somatosensory cortices. However, it remains unclear how humans regulate cortical oscillations, the controllability of which substantially varies across individuals. Here, we performed simultaneous electroencephalography (to assess brain-computer interface control) and functional magnetic resonance imaging (to measure brain activity) in healthy participants. Self-regulation of cortical oscillations induced activity in the basal ganglia-cortical network and the neurofeedback control network. Successful self-regulation correlated with striatal activity in the basal ganglia-cortical network, through which patterns of cortical oscillations were likely modulated. Moreover, basal ganglia-cortical network and neurofeedback control network connectivity correlated with strong and weak self-regulation, respectively. The findings indicate that the basal ganglia-cortical network is important for self-regulation, the understanding of which should help advance brain-computer interface technology.

Neuroanatomical correlates of brain-computer interface performance.

Brain-computer interfaces (BCIs) offer a potential means to replace or restore lost motor function. However, BCI performance varies considerably between users, the reasons for which are poorly understood. Here we investigated the relationship between sensorimotor rhythm (SMR)-based BCI performance and brain structure. Participants were instructed to control a computer cursor using right- and left-hand motor imagery, which primarily modulated their left- and right-hemispheric SMR powers, respectively. Although most participants were able to control the BCI with success rates significantly above chance level even at the first encounter, they also showed substantial inter-individual variability in BCI success rate. Participants also underwent T1-weighted three-dimensional structural magnetic resonance imaging (MRI). The MRI data were subjected to voxel-based morphometry using BCI success rate as an independent variable. We found that BCI performance correlated with gray matter volume of the supplementary motor area, supplementary somatosensory area, and dorsal premotor cortex. We suggest that SMR-based BCI performance is associated with development of non-primary somatosensory and motor areas. Advancing our understanding of BCI performance in relation to its neuroanatomical correlates may lead to better customization of BCIs based on individual brain structure.

Larger right posterior parietal volume in action video game experts: a behavioral and voxel-based morphometry (VBM) study.

Recent studies suggest that action video game players exhibit superior performance in visuospatial cognitive tasks compared with non-game players. However, the neural basis underlying this visuospatial cognitive performance advantage remains largely unknown. The present human behavioral and imaging study compared gray matter volume in action video game experts and non-experts using structural magnetic resonance imaging and voxel-based morphometry analysis. The results revealed significantly larger gray matter volume in the right posterior parietal cortex in experts compared with non-experts. Furthermore, the larger gray matter volume in the right posterior parietal cortex significantly correlated with individual performance in a visual working memory task in experts. These results suggest that differences in brain structure may be linked to extensive video game play, leading to superior visuospatial cognitive performance in action video game experts.

Lateralization of activity in the parietal cortex predicts the effectiveness of bilateral transcranial direct current stimulation on performance of a mental calculation task.

Transcranial direct current stimulation (tDCS) is a non-invasive technique that moderates cognitive and motor function. The effects of tDCS on cognitive and motor tasks vary among individuals. However, the source of the inter-individual variability remains unknown. The purpose of the present study was to examine whether the effect of bilateral tDCS on the performance of mental calculations differs among individuals according to the functional lateralization of parietal activity observed during a mental calculation task. Sixteen healthy subjects (11 males and five females, aged 20-23 years) participated. Laterality of parietal activity during a mental calculation task was evaluated using functional magnetic resonance imaging. Subjects also performed the mental calculation task pre-, during-, 30 min post-, and 60 min post-tDCS. Bilateral tDCS with the anode over the left parietal cortex and the cathode over the right parietal cortex shortened response times of the mental calculation task in subjects with left-hemispheric parietal lateralization, but not in subjects with bilateral parietal activation. This indicates that inter-individual variability in laterality of brain activity might be an important factor underlying the effect of bilateral tDCS. In conclusion, bilateral tDCS over the parietal cortex enhanced the performance of mental calculations in subjects with left-hemispheric parietal lateralization.

Voxel- and atlas-based analysis of diffusion tensor imaging may reveal focal axonal injuries in mild traumatic brain injury -- comparison with diffuse axonal injury.

BACKGROUND: The diagnosis and management of mild traumatic brain injury (MTBI) continue to be subjects of debate, with varying opinions regarding the extent to which tissue-based impairments versus the impacts of other stressors cause ongoing disability. Detecting areas of the brain with abnormalities that can explain symptoms and behavior in patients with MTBI is important in order to confirm the diagnosis of MTBI. METHODS: In this study, we calculated diffusion maps from results of diffusion tensor imaging (DTI) performed in an apparently healthy control group. We then compared these maps with those of patients with MTBI (MTBI group) or diffuse axonal injury (DAI group). All diffusion maps were normalized to the International Consortium for Brain Mapping atlas for atlas-based analysis and were segmented and normalized by the Diffeomorphic Anatomical Registration Through Exponentiated Lie tool in SPM8 to reduce misregistration. RESULTS: All diffusion measures in the DAI group were lower than in the control group. There were significant differences in the body and splenium of the corpus callosum, fornix and right cerebral peduncle in the DAI group compared with the control group (P<.001). The MTBI group had higher axial diffusivity than the control group in the right corticospinal tract, left medial lemniscus, left inferior cerebellar peduncle, bilateral anterior limb of the internal capsule, right anterior corona radiata, bilateral cingulum (cingulate gyrus) and left superior frontooccipital fasciculus (P<.05). CONCLUSIONS: Voxel- and atlas-based analysis of DTI might suggest that patients with MTBI have focal axonal injury and that the pathophysiology is significantly different from that of DAI. These findings will help in the diagnosis of patients with MTBI.