Hemodynamic response to intestinal pH stimulation measured with spectroscopic video imaging.

To investigate the relationship between the gut and skin (gut-skin axis), head skin hemodynamic responses to gut stimulation including the injection of acetic acid in nude mice were measured by spectroscopic video imaging, which was calculated using a modified Beer-Lambert formula. The relationship with blood proteins was also analyzed. The blood volume changes in three mice injected with acetic acid were highly reproducible in the mathematical model equation. Four proteins correlated with blood volume changes were all related to immunity. These results suggest that intestinal pH can alter the blood volume in the skin and induce immune-related responses.

Projection of Damaged Visual and Language Regions on Low Trail Making Test Part-B Performance in Stroke Patients.

Background: The Trail Making Test Part-B (TMT-B) is an attention functional test to investigate cognitive dysfunction. It requires the ability to recognize not only numbers but also letters. We analyzed the relationship between brain lesions in stroke patients and their TMT-B performance. Methods: From the TMT-B, two parameters (score and completion time) were obtained. The subjects were classified into several relevant groups by their scores and completion times through a data-driven analysis (k-means clustering). The score-classified groups were characterized by low (≤10), moderate (10 < score < 25), and high (25) scores. In terms of the completion time, the subjects were classified into four groups. The lesion degree in the brain was calculated for each of the 116 regions classified by automated anatomical labeling (AAL). For each group, brain sites with a significant difference (corrected p < 0.1) between each of the 116 regions were determined by a Wilcoxon Rank-Sum significant difference test. Results: Lesions at the cuneus and the superior occipital gyrus, which are mostly involved in visual processing, were significant (corrected p < 0.1) in the low-score group. Furthermore, the moderate-score group showed more-severe lesion degrees (corrected p < 0.05) in the regions responsible for the linguistic functions, such as the superior temporal gyrus and the supramarginal gyrus. As for the completion times, lesions in the calcarine, the cuneus, and related regions were significant (corrected p < 0.1) in the fastest group as compared to the slowest group. These regions are also involved in visual processing. Conclusion: The TMT-B results revealed that the subjects in the low-score group or the slowest- group mainly had damage in the visual area, whereas the subjects in the moderate-score group mainly had damage in the language area. These results suggest the potential utility of TMT-B performance in the lesion site.

Artificially-reconstructed brain images with stroke lesions from non-imaging data: modeling in categorized patients based on lesion occurrence and sparsity.

Brain imaging is necessary for understanding disease symptoms, including stroke. However, frequent imaging procedures encounter practical limitations. Estimating the brain information (e.g., lesions) without imaging sessions is beneficial for this scenario. Prospective estimating variables are non-imaging data collected from standard tests. Therefore, the current study aims to examine the variable feasibility for modelling lesion locations. Heterogeneous variables were employed in the multivariate logistic regression. Furthermore, patients were categorized (i.e., unsupervised clustering through k-means method) by the charasteristics of lesion occurrence (i.e., ratio between the lesioned and total regions) and sparsity (i.e., density measure of lesion occurrences across regions). Considering those charasteristics in models improved estimation performances. Lesions (116 regions in Automated Anatomical Labeling) were adequately predicted (sensitivity: 80.0-87.5% in median). We confirmed that the usability of models was extendable to different resolution levels in the brain region of interest (e.g., lobes, hemispheres). Patients' charateristics (i.e., occurrence and sparsity) might also be explained by the non-imaging data as well. Advantages of the current approach can be experienced by any patients (i.e., with or without imaging sessions) in any clinical facilities (i.e., with or without imaging instrumentation).

Increased cerebrovascular reactivity in selected brain regions after extracranial-intracranial bypass improves the speed and accuracy of visual cancellation in patients with severe steno-occlusive disease: a preliminary study.

The effect of the change in cerebrovascular reactivity (CVR) in each brain area on cognitive function after extracranial-intracranial bypass (EC-IC bypass) was examined. Eighteen patients who underwent EC-IC bypass for severe unilateral steno-occlusive disease were included. Single-photon emission CT (SPECT) for evaluating CVR and the visual cancellation (VC) task were performed before and after surgery. The accuracy of VC was expressed by the arithmetic mean of the age-matched correct answer rate and the accurate answer rate, and the averages of the time (time score) and accuracy (accuracy score) of the four VC subtests were used. The speed of VC tended to be slower, whereas accuracy was maintained before surgery. The EC-IC bypass improved CVR mainly in the cerebral hemisphere on the surgical side. On bivariate analysis, when CVR increased post-operatively, accuracy improved on both surgical sides, but the time score was faster on the left and slower on the right surgical side. Stepwise multiple regression analysis showed that the number of the brain regions associated with the time score was 5 and that associated with the accuracy score was 4. In the hemodynamically ischemic brain, processing speed might be adjusted so that accuracy would be maintained based on the speed-accuracy trade-off mechanism that may become engaged separately in the left and right cerebral hemispheres when performing VC. When considering the treatment for hemodynamic ischemia, the relationship between CVR change and the speed-accuracy trade-off in each brain region should be considered.

Proposal of layered mental healthcare for mental well-being.

A new concept, 'Layered mental healthcare' for keeping employees mental well-being in the workplace to avoid losses caused by both absenteeism and presenteeism is proposed. A key factor forming the basis of the concept is the biometric measurements over three layers, i.e., behaviour, physiology, and brain layers, for monitoring mental/distress conditions of employees. Here, the necessity of measurements in three layers was validated by the data-driven approach using the preliminary dataset measured in the office environment. Biometric measurements were supported by an activity tracker, a PC logger, and the optical topography; mental/distress conditions were quantified by the brief job stress questionnaire. The biometric features obtained 1 week before the measurement of mental/distress scores were selected for the best regression model. The feature importance of each layer was obtained in the learning process of the best model using the light graded boosting machine and was compared between layers. The ratio of feature importance of behaviour:physiology:brain layers was found to be 4:3:3. The study results suggest the contribution and necessity of the three-layer features in predicting mental/distress scores.

Mental Condition Monitoring Based on Multimodality Biometry.

We have developed a system with multimodality that monitors objective biomarkers for screening the mental distress in the office. A field study using a prototype of the system was performed over four months with 39 volunteers. We obtained PC operation patterns using a PC logger, sleeping time and activity levels using a wrist-band-type activity tracker, and brain activity and behavior data during a working memory task using optical topography. We also administered two standard questionnaires: the Brief Job Stress Questionnaire (BJS) and the Kessler 6 scale (K6). Supervised machine learning and cross validation were performed. The objective variables were mental scores obtained from the questionnaires and the explanatory variables were the biomarkers obtained from the modalities. Multiple linear regression models for mental scores were comprehensively searched and the optimum models were selected from 2,619,785 candidates. Each mental score estimated with each optimum model was well correlated with each mental score obtained with the questionnaire (correlation coefficient = 0.6-0.8) within a 24% of estimation error. Mental scores obtained by means of questionnaires have been in general use in mental health care for a while, so our multimodality system is potentially useful for mental healthcare due to the quantitative agreement on the mental scores estimated with biomarkers and the mental scores obtained with questionnaires.

Lesions in the right Rolandic operculum are associated with self-rating affective and apathetic depressive symptoms for post-stroke patients.

Stroke survivors majorly suffered from post-stroke depression (PSD). The PSD diagnosis is commonly performed based on the clinical cut-off for psychometric inventories. However, we hypothesized that PSD involves spectrum symptoms (e.g., apathy, depression, anxiety, and stress domains) and severity levels. Therefore, instead of using the clinical cut-off, we suggested a data-driven analysis to interpret patient spectrum conditions. The patients' psychological conditions were categorized in an unsupervised manner using the k-means clustering method, and the relationships between psychological conditions and quantitative lesion degrees were evaluated. This study involved one hundred sixty-five patient data; all patients were able to understand and perform self-rating psychological conditions (i.e., no aphasia). Four severity levels-low, low-to-moderate, moderate-to-high, and high-were observed for each combination of two psychological domains. Patients with worse conditions showed the significantly greater lesion degree at the right Rolandic operculum (part of Brodmann area 43). The dissimilarities between stress and other domains were also suggested. Patients with high stress were specifically associated with lesions in the left thalamus. Impaired emotion processing and stress-affected functions have been frequently related to those lesion regions. Those lesions were also robust and localized, suggesting the possibility of an objective for predicting psychological conditions from brain lesions.

Atypical Dynamic-Connectivity Recruitment in Attention-Deficit/Hyperactivity Disorder Children: An Insight Into Task-Based Dynamic Connectivity Through an fNIRS Study.

Connectivity between brain regions has been redefined beyond a stationary state. Even when a person is in a resting state, brain connectivity dynamically shifts. However, shifted brain connectivity under externally evoked stimulus is still little understood. The current study, therefore, focuses on task-based dynamic functional-connectivity (FC) analysis of brain signals measured by functional near-infrared spectroscopy (fNIRS). We hypothesize that a stimulus may influence not only brain connectivity but also the occurrence probabilities of task-related and task-irrelevant connectivity states. fNIRS measurement (of the prefrontal-to-inferior parietal lobes) was conducted on 21 typically developing (TD) and 21 age-matched attention-deficit/hyperactivity disorder (ADHD) children performing an inhibitory control task, namely, the Go/No-Go (GNG) task. It has been reported that ADHD children lack inhibitory control; differences between TD and ADHD children in terms of task-based dynamic FC were also evaluated. Four connectivity states were found to occur during the temporal task course. Two dominant connectivity states (states 1 and 2) are characterized by strong connectivities within the frontoparietal network (occurrence probabilities of 40%-56% and 26%-29%), and presumptively interpreted as task-related states. A connectivity state (state 3) shows strong connectivities in the bilateral medial frontal-to-parietal cortices (occurrence probability of 7-15%). The strong connectivities were found at the overlapped regions related the default mode network (DMN). Another connectivity state (state 4) visualizes strong connectivities in all measured regions (occurrence probability of 10%-16%). A global effect coming from cerebral vascular may highly influence this connectivity state. During the GNG stimulus interval, the ADHD children tended to show decreased occurrence probability of the dominant connectivity state and increased occurrence probability of other connectivity states (states 3 and 4). Bringing a new perspective to explain neuropathophysiology, these findings suggest atypical dynamic network recruitment to accommodate task demands in ADHD children.

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.

Denoising of neuronal signal from mixed systemic low-frequency oscillation using peripheral measurement as noise regressor in near-infrared imaging.

Functional near-infrared spectroscopy (fNIRS) is a noninvasive functional imaging technique measuring hemodynamic changes including oxygenated ( O 2 Hb ) and deoxygenated (HHb) hemoglobin. Low frequency (LF; 0.01 to 0.15 Hz) band is commonly analyzed in fNIRS to represent neuronal activation. However, systemic physiological artifacts (i.e., nonneuronal) likely occur also in overlapping frequency bands. We measured peripheral photoplethysmogram (PPG) signal concurrently with fNIRS (at prefrontal region) to extract the low-frequency oscillations (LFOs) as systemic noise regressors. We investigated three main points in this study: (1) the relationship between prefrontal fNIRS and peripheral PPG signals; (2) the denoising potential using these peripheral LFOs, and (3) the innovative ways to avoid the false-positive result in fNIRS studies. We employed spatial working memory (WM) and control tasks (e.g., resting state) to illustrate these points. Our results showed: (1) correlation between signals from prefrontal fNIRS and peripheral PPG is region-dependent. The high correlation with peripheral ear signal (i.e., O 2 Hb ) occurred mainly in frontopolar regions in both spatial WM and control tasks. This may indicate the finding of task-dependent effect even in peripheral signals. We also found that the PPG recording at the ear has a high correlation with prefrontal fNIRS signal than the finger signals. (2) The systemic noise was reduced by 25% to 34% on average across regions, with a maximum of 39% to 58% in the highly correlated frontopolar region, by using these peripheral LFOs as noise regressors. (3) By performing the control tasks, we confirmed that the statistically significant activation was observed in the spatial WM task, not in the controls. This suggested that systemic (and any other) noises unlikely violated the major statistical inference. (4) Lastly, by denoising using the task-related signals, the significant activation of region-of-interest was still observed suggesting the manifest task-evoked response in the spatial WM task.

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).

Tutorial on platform for optical topography analysis tools.

Optical topography/functional near-infrared spectroscopy (OT/fNIRS) is a functional imaging technique that noninvasively measures cerebral hemoglobin concentration changes caused by neural activities. The fNIRS method has been extensively implemented to understand the brain activity in many applications, such as neurodisorder diagnosis and treatment, cognitive psychology, and psychiatric status evaluation. To assist users in analyzing fNIRS data with various application purposes, we developed a software called platform for optical topography analysis tools (POTATo). We explain how to handle and analyze fNIRS data in the POTATo package and systematically describe domain preparation, temporal preprocessing, functional signal extraction, statistical analysis, and data/result visualization for a practical example of working memory tasks. This example is expected to give clear insight in analyzing data using POTATo. The results specifically show the activated dorsolateral prefrontal cortex is consistent with previous studies. This emphasizes analysis robustness, which is required for validating decent preprocessing and functional signal interpretation. POTATo also provides a self-developed plug-in feature allowing users to create their own functions and incorporate them with established POTATo functions. With this feature, we continuously encourage users to improve fNIRS analysis methods. We also address the complications and resolving opportunities in signal analysis.

Concurrent fNIRS-fMRI measurement to validate a method for separating deep and shallow fNIRS signals by using multidistance optodes.

It has been reported that a functional near-infrared spectroscopy (fNIRS) signal can be contaminated by extracerebral contributions. Many algorithms using multidistance separations to address this issue have been proposed, but their spatial separation performance has rarely been validated with simultaneous measurements of fNIRS and functional magnetic resonance imaging (fMRI). We previously proposed a method for discriminating between deep and shallow contributions in fNIRS signals, referred to as the multidistance independent component analysis (MD-ICA) method. In this study, to validate the MD-ICA method from the spatial aspect, multidistance fNIRS, fMRI, and laser-Doppler-flowmetry signals were simultaneously obtained for 12 healthy adult males during three tasks. The fNIRS signal was separated into deep and shallow signals by using the MD-ICA method, and the correlation between the waveforms of the separated fNIRS signals and the gray matter blood oxygenation level-dependent signals was analyzed. A three-way analysis of variance ([Formula: see text]) indicated that the main effect of fNIRS signal depth on the correlation is significant [[Formula: see text], [Formula: see text]]. This result indicates that the MD-ICA method successfully separates fNIRS signals into spatially deep and shallow signals, and the accuracy and reliability of the fNIRS signal will be improved with the method.

Quantitative evaluation of deep and shallow tissue layers' contribution to fNIRS signal using multi-distance optodes and independent component analysis.

To quantify the effect of absorption changes in the deep tissue (cerebral) and shallow tissue (scalp, skin) layers on functional near-infrared spectroscopy (fNIRS) signals, a method using multi-distance (MD) optodes and independent component analysis (ICA), referred to as the MD-ICA method, is proposed. In previous studies, when the signal from the shallow tissue layer (shallow signal) needs to be eliminated, it was often assumed that the shallow signal had no correlation with the signal from the deep tissue layer (deep signal). In this study, no relationship between the waveforms of deep and shallow signals is assumed, and instead, it is assumed that both signals are linear combinations of multiple signal sources, which allows the inclusion of a "shared component" (such as systemic signals) that is contained in both layers. The method also assumes that the partial optical path length of the shallow layer does not change, whereas that of the deep layer linearly increases along with the increase of the source-detector (S-D) distance. Deep- and shallow-layer contribution ratios of each independent component (IC) are calculated using the dependence of the weight of each IC on the S-D distance. Reconstruction of deep- and shallow-layer signals are performed by the sum of ICs weighted by the deep and shallow contribution ratio. Experimental validation of the principle of this technique was conducted using a dynamic phantom with two absorbing layers. Results showed that our method is effective for evaluating deep-layer contributions even if there are high correlations between deep and shallow signals. Next, we applied the method to fNIRS signals obtained on a human head with 5-, 15-, and 30-mm S-D distances during a verbal fluency task, a verbal working memory task (prefrontal area), a finger tapping task (motor area), and a tetrametric visual checker-board task (occipital area) and then estimated the deep-layer contribution ratio. To evaluate the signal separation performance of our method, we used the correlation coefficients of a laser-Doppler flowmetry (LDF) signal and a nearest 5-mm S-D distance channel signal with the shallow signal. We demonstrated that the shallow signals have a higher temporal correlation with the LDF signals and with the 5-mm S-D distance channel than the deep signals. These results show the MD-ICA method can discriminate between deep and shallow signals.

A NIRS-fMRI investigation of prefrontal cortex activity during a working memory task.

Near-infrared spectroscopy (NIRS) is commonly used for studying human brain function. However, several studies have shown that superficial hemodynamic changes such as skin blood flow can affect the prefrontal NIRS hemoglobin (Hb) signals. To examine the criterion-related validity of prefrontal NIRS-Hb signals, we focused on the functional signals during a working memory (WM) task and investigated their similarity with blood-oxygen-level-dependent (BOLD) signals simultaneously measured by functional magnetic resonance imaging (fMRI). We also measured the skin blood flow with a laser Doppler flowmeter (LDF) at the same time to examine the effect of superficial hemodynamic changes on the NIRS-Hb signals. Correlation analysis demonstrated that temporal changes in the prefrontal NIRS-Hb signals in the activation area were significantly correlated with the BOLD signals in the gray matter rather than those in the soft tissue or the LDF signals. While care must be taken when comparing the NIRS-Hb signal with the extracranial BOLD or LDF signals, these results suggest that the NIRS-Hb signal mainly reflects hemodynamic changes in the gray matter. Moreover, the amplitudes of the task-related responses of the NIRS-Hb signals were significantly correlated with the BOLD signals in the gray matter across participants, which means participants with a stronger NIRS-Hb response showed a stronger BOLD response. These results thus provide supportive evidence that NIRS can be used to measure hemodynamic signals originating from prefrontal cortex activation.

Dynamic phantom with two stage-driven absorbers for mimicking hemoglobin changes in superficial and deep tissues.

In near-infrared spectroscopy (NIRS) for monitoring brain activity and cerebral functional connectivity, the effect of superficial tissue on NIRS signals needs to be considered. Although some methods for determining the effect of scalp and brain have been proposed, direct validation of the methods has been difficult because the actual absorption changes cannot be known. In response to this problem, we developed a dynamic phantom that mimics hemoglobin changes in superficial and deep tissues, thus allowing us to experimentally validate the methods. Two absorber layers are independently driven with two one-axis automatic stages. We can use the phantom to design any type of waveform (e.g., brain activity or systemic fluctuation) of absorption change, which can then be reproducibly measured. To determine the effectiveness of the phantom, we used it for a multiple source-detector distance measurement. We also investigated the performance of a subtraction method with a short-distance regressor. The most accurate lower-layer change was obtained when a shortest-distance channel was used. Furthermore, when an independent component analysis was applied to the same data, the extracted components were in good agreement with the actual signals. These results demonstrate that the proposed phantom can be used for evaluating methods of discriminating the effects of superficial tissue.

Optical scanning system for light-absorption measurement of deep biological tissue.

A noncontact near-infrared scanning system for multi-distance absorption measurement of deep biological tissue was developed. An 808-nm laser, whose focal point on the surface of biological tissue is controlled by a galvano scanner, is used as a light source. A phosphor is placed at a detection focal point on the tissue surface. The light that propagates through tissue and exits from the tissue surface beneath the phosphor excites the phosphor. The fluorescence emitted from the phosphor is detected by an avalanche photodiode. The system is used to measure 20 points on tissue surface at which source-detector (S-D) distances are 7-45 mm (with 2-mm intervals). Neither the light source nor the detector contacts the tissue surface. The system was validated by using it to measure the absorption change of an absorber (which is embedded in a deep layer of a tissue-simulating phantom) while the surface-layer thickness of the phantom was changed from 1 to 12 mm. It was demonstrated that both the relative absorption change of the absorber and the absolute thickness of the surface layer can be estimated from the measured optical-density change (ΔOD) and the dependence of ΔOD on S-D distance, respectively.

Synchronous activity of two people's prefrontal cortices during a cooperative task measured by simultaneous near-infrared spectroscopy.

The brain activity during cooperation as a form of social process is studied. We investigate the relationship between coinstantaneous brain-activation signals of multiple participants and their cooperative-task performance. A wearable near-infrared spectroscopy (NIRS) system is used for simultaneously measuring the brain activities of two participants. Each pair of participants perform a cooperative task, and their relative changes in cerebral blood are measured with the NIRS system. As for the task, the participants are told to count 10 s in their mind after an auditory cue and press a button. They are also told to adjust the timing of their button presses to make them as synchronized as possible. Certain information, namely, the "intertime interval" between the two button presses of each participant pair and which of the participants was the faster, is fed back to the participants by a beep sound after each trial. When the spatiotemporal covariance between the activation patterns of the prefrontal cortices of each participant is higher, the intertime interval between their button-press times was shorter. This result suggests that the synchronized activation patterns of the two participants' brains are associated with their performance when they interact in a cooperative task.

Noninvasive imaging of prefrontal activation during attention-demanding tasks performed while walking using a wearable optical topography system.

Optical topography (OT) based on near-infrared spectroscopy is a noninvasive technique for mapping the relative concentration changes in oxygenated and deoxygenated hemoglobin (oxy- and deoxy-Hb, respectively) in the human cerebral cortex. In our previous study, we developed a small and light wearable optical topography (WOT) system that covers the entire forehead for monitoring prefrontal activation. In the present study, we examine whether the WOT system is applicable to OT measurement while walking, which has been difficult with conventional OT systems. We conduct OT measurements while subjects perform an attention-demanding (AD) task of balancing a ping-pong ball on a small card while walking. The measured time course and power spectra of the relative concentration changes in oxy- and deoxy-Hb show that the step-related changes in the oxy- and deoxy-Hb signals are negligible compared to the task-related changes. Statistical assessment of the task-related changes in the oxy-Hb signals show that the dorsolateral prefrontal cortex and rostral prefrontal area are significantly activated during the AD task. These results suggest that our functional imaging technique with the WOT system is applicable to OT measurement while walking, and will be a powerful tool for evaluating brain activation in a natural environment.

Development of wearable optical topography system for mapping the prefrontal cortex activation.

Optical topography (OT) based on near infrared spectroscopy is effective for measuring changes in the concentrations of oxygenated hemoglobin (oxy-Hb) and deoxygenated hemoglobin (deoxy-Hb) in the brain. It can be used to investigate brain functions of subjects of all ages because it is noninvasive and less constraining for subjects. Conventional OT systems use optical fibers to irradiate the scalp and detect light transmitted through the tissue in the human head, but optical fibers limit the subject's head position, so some small systems have been developed without using optical fibers. These systems, however, have a small number of measurement channels. We developed a prototype of a small, light, and wearable OT system that covers the entire forehead. We measured changes in the concentrations of oxy-Hb and deoxy-Hb in the prefrontal cortex while a subject performed a word fluency task. The results show typical changes in oxy-Hb and deoxy-Hb during the task and suggest that the prototype of our system can be used to investigate functions in the prefrontal cortex.