Non-invasive brain-function imaging by optical topography

Aggregation-and-Attention Network for brain tumor segmentation

BACKGROUND

Glioma is a malignant brain tumor; its location is complex and is difficult to remove surgically. To diagnosis the brain tumor, doctors can precisely diagnose and localize the disease using medical images. However, the computer-assisted diagnosis for the brain tumor diagnosis is still the problem because the rough segmentation of the brain tumor makes the internal grade of the tumor incorrect.

METHODS

In this paper, we proposed an Aggregation-and-Attention Network for brain tumor segmentation. The proposed network takes the U-Net as the backbone, aggregates multi-scale semantic information, and focuses on crucial information to perform brain tumor segmentation. To this end, we proposed an enhanced down-sampling module and Up-Sampling Layer to compensate for the information loss. The multi-scale connection module is to construct the multi-receptive semantic fusion between encoder and decoder. Furthermore, we designed a dual-attention fusion module that can extract and enhance the spatial relationship of magnetic resonance imaging and applied the strategy of deep supervision in different parts of the proposed network.

RESULTS

Experimental results show that the performance of the proposed framework is the best on the BraTS2020 dataset, compared with the-state-of-art networks. The performance of the proposed framework surpasses all the comparison networks, and its average accuracies of the four indexes are 0.860, 0.885, 0.932, and 1.2325, respectively.

CONCLUSIONS

The framework and modules of the proposed framework are scientific and practical, which can extract and aggregate useful semantic information and enhance the ability of glioma segmentation.

Deconvolution of hemodynamic responses along the cortical surface using personalized functional near infrared spectroscopy

In functional near infrared spectroscopy (fNIRS), deconvolution analysis of oxy and deoxy-hemoglobin concentration changes allows estimating specific hemodynamic response functions (HRF) elicited by neuronal activity, taking advantage of the fNIRS excellent temporal resolution. Diffuse optical tomography (DOT) is also becoming the new standard reconstruction procedure as it is more accurate than the modified Beer Lambert law approach at the sensor level. The objective of this study was to assess the relevance of HRF deconvolution after DOT constrained along the cortical surface. We used local personalized fNIRS montages which consists in optimizing the position of fNIRS optodes to ensure maximal sensitivity to subject specific target brain regions. We carefully evaluated the accuracy of deconvolution when applied after DOT, using realistic simulations involving several HRF models at different signal to noise ratio (SNR) levels and on real data related to motor and visual tasks in healthy subjects and from spontaneous pathological activity in one patient with epilepsy. We demonstrated that DOT followed by deconvolution was able to accurately recover a large variability of HRFs over a large range of SNRs. We found good performances of deconvolution analysis for SNR levels usually encountered in our applications and we were able to reconstruct accurately the temporal dynamics of HRFs in real conditions.

Prefrontal cortex activation of return-to-work trainees in remission of mental disorders with depressive symptoms compared to that of healthy controls

The increase in the number of patients with mental disorders with depressive symptoms has become a significant problem. To prevent people developing those disorders and help with the effective recovery, it is important to quantitatively and objectively monitor an individual's mental state. Previous studies have shown the relationship between negative or depressive mood state and human prefrontal cortex (PFC) activation during verbal and spatial working memory tasks based on a near-infrared spectroscopy imaging technique. In this study, we aimed to explore a biomarker of the mental state of people in remission of mental disorders with depressive symptoms using this technique. We obtained the PFC activation of return-to-work (RTW) trainees in remission of those disorders, compared that of healthy controls, and obtained subjective questionnaire scores with the Profile of Mood States. We compared the PFC activation with the questionnaire scores by receiver operating characteristic analysis using a logistic-regression model. The results showed that the PFC activation indicates a healthy state compared to that of the RTW trainees evaluated by area-under-curve analysis. This study demonstrates that our PFC measurement technique will be useful as a quantitative and objective assessment of mental state.

Informal Face-to-Face Interaction Improves Mood State Reflected in Prefrontal Cortex Activity

Recent progress with wearable sensors has enabled researchers to capture face-to-face interactions quantitatively and given great insight into human dynamics. One attractive field for applying such sensors is the workplace, where the relationship between the face-to-face behaviors of employees and the productivity of the organization has been investigated. One interesting result of previous studies showed that informal face-to-face interaction among employees, captured by wearable sensors that the employees wore, significantly affects their performance. However, the mechanism behind this relationship has not yet been adequately explained, though experiences at the job scene might qualitatively support the finding. We hypothesized that informal face-to-face interaction improves mood state, which in turn affects the task performance. To test this hypothesis, we evaluated the change of mood state before and after break time for two groups of participants, one that spent their breaks alone and one that spent them with other participants, by administering questionnaires and taking brain activity measurements. Recent neuroimaging studies have suggested a significant relationship between mood state and brain activity. Here, we show that face-to-face interaction during breaks significantly improved mood state, which was measured by Profiles of Mood States (POMS). We also observed that the verbal working memory (WM) task performance of participants who did not have face-to-face interaction during breaks decreased significantly. In this paper, we discuss how the change of mood state was evidenced in the prefrontal cortex (PFC) activity accompanied by WM tasks measured by near-infrared spectroscopy (NIRS).

Optimal optode montage on electroencephalography/functional near-infrared spectroscopy caps dedicated to study epileptic discharges

Functional near-infrared spectroscopy (fNIRS), acquired simultaneously with electroencephalography (EEG), allows the investigation of hemodynamic brain responses to epileptic activity. Because the presumed epileptogenic focus is patient-specific, an appropriate source/detector (SD) montage has to be reconfigured for each patient. The combination of EEG and fNIRS, however, entails several constraints on montages, and finding an optimal arrangement of optodes on the cap is an important issue. We present a method for computing an optimal SD montage on an EEG/fNIRS cap that focuses on one or several specific brain regions; the montage maximizes the spatial sensitivity. We formulate this optimization problem as a linear integer programming problem. The method was evaluated on two EEG/fNIRS caps. We simulated absorbers at different locations on a head model and generated realistic optical density maps on the scalp. We found that the maps of optimal SD montages had spatial resolution properties comparable to those of regular SD arrangements for the whole head with significantly fewer sensors than regular SD arrangements. In addition, we observed that optimal montages yielded improved spatial density of fNIRS measurements over the targeted regions together with an increase in signal-to-noise ratio.

The prefrontal cortex: functional neural development during early childhood

The prefrontal cortex plays an essential role in various cognitive functions, such as planning and reasoning, yet little is known about how such neural mechanisms develop during childhood, particularly in young children. To better understand this issue, the present article reviews the literature on the development of the prefrontal cortex during early childhood, focusing mainly on the changes in structural architecture, neural activity, and cognitive abilities. Neuroanatomically, the prefrontal cortex undergoes considerable maturation during childhood, including a reduction of synaptic and neuronal density, a growth of dendrites, and an increase in white matter volume, thereby forming distributed neural networks appropriate for complex cognitive processing. Concurrently, behavioral performance of various cognitive tasks improves with age, and intercorrelations among performance on each task become weak through development. Furthermore, the correlation between subcategories of intelligence test decreases as general intellectual efficiency increases. In addition, recent neuroimaging findings suggest that the prefrontal cortex is already functional in 4-year olds and becomes organized into focal, fine-tuned systems through later development. The literature reviewed suggests that fractionation of the functional neural systems plays a key role in the development of prefrontal cortex and such fractionating process has already commenced in preschool children.

Ethical considerations of neuroscience research: the perspectives on neuroethics in Japan

Recent technologies and developments in neuroscience have contributed to remarkable scientific discoveries, and have also raised many new philosophical, ethical, legal, and social issues. Research in "neuroethics" has identified various ethical issues, which will be difficult for current biomedical ethics to resolve from both an experimental and a social perspective, such as criminal applications of brain scans, incidental findings during non-clinical brain imaging, and cognitive enhancement. Although American and European neuroscience societies have demonstrated immediate, concrete reactions to these ethical issues, including academic conferences, study programs, and publications, Japanese neuroscientists have so far produced little response. Ethics is tightly linked with one's religion, nationality, culture, and social background, whereas science is tightly linked with the demand, economics, and politics of the society to which individuals belong. Taken together, it is important and necessary for Japanese neuroscientists to consider the ethical problems in Japanese neuroscience. In this paper, we first review the history of neuroethics in the world, and then report the less-developed ethical issues in the Japanese neuroscience community, focusing on neuroimaging and manipulative neuroscience as a first step in discussing how to apply principles in neuroethics to this rapidly progressing field of research.