Sleep deprivation (SD) is known to be associated with decreased cognitive performance; however, the underlying mechanisms are poorly understood. As interactions between distinct brain regions depend on mental state, functional brain networks established by these connections typically show a reorganization during task. Hence, analysis of functional connectivity (FC) could reveal the task-related change in the examined frontal brain networks. Our objective was to assess the impact of SD on static FC in the prefrontal and motor cortices and find whether changes in FC correlate with changes in neuropsychological scores. Healthy young male individuals (n = 10, 27.6 ± 3.7 years of age) participated in the study. A battery of tests from the Cambridge Neuropsychological Test Automated Battery (CANTAB) and 48 channel functional near-infrared spectroscopy (fNIRS) measurements were performed before and after 24 hr of SD. Network metrics were obtained by graph theoretical analysis using the fNIRS records in resting state and during finger-tapping sessions. During task, SD resulted in a significantly smaller decrease in the number and strength of functional connections (characterizing FC) in the frontal cortex. Changes in the global connection strengths correlated with decreased performance in the paired association learning test. These results indicate a global impact of SD on functional brain networks in the frontal lobes.

Functional near-infrared spectroscopy (fNIRS) is a noninvasive optical brain-imaging technique that detects changes in hemoglobin concentration in the cerebral cortex. fNIRS devices are safe, silent, portable, robust against motion artifacts, and have good temporal resolution. fNIRS is reliable and trustworthy, as well as an alternative and a complement to other brain-imaging modalities, such as electroencephalography or functional magnetic resonance imaging. Given these advantages, fNIRS has become a well-established tool for neuroscience research, used not only for healthy cortical activity but also as a biomarker during clinical assessment in individuals with schizophrenia, major depressive disorder, bipolar disease, epilepsy, Alzheimer's disease, vascular dementia, and cancer screening. Owing to its wide applicability, studies on fNIRS have increased exponentially over the last two decades. In this study, scientific publications indexed in the Web of Science databases were collected and a bibliometric-type methodology was developed. For this purpose, a comprehensive science mapping analysis, including top-ranked authors, journals, institutions, countries, and co-occurring keywords network, was conducted. From a total of 2310 eligible documents, 6028 authors and 531 journals published fNIRS-related papers, Fallgatter published the highest number of articles and was the most cited author. University of Tübingen in Germany has produced the most trending papers since 2000. USA was the most prolific country with the most active institutions, followed by China, Japan, Germany, and South Korea. The results also revealed global trends in emerging areas of research, such as neurodevelopment, aging, and cognitive and emotional assessment.

The gold standard for diagnosing impulsivity relies on clinical interviews, behavioral questionnaires and rating scales which are highly subjective.The aim of this study was to develop a functional near infrared spectroscopy (fNIRS) based classification approach for correct identification of impulsive adolescents. Taking into account the multifaceted nature of impulsivity, we propose that combining informative features from clinical, behavioral and neurophysiological domains might better elucidate the neurobiological distinction underlying symptoms of impulsivity.. Hemodynamic and behavioral information was collected from 38 impulsive adolescents and from 33 non-impulsive adolescents during a Stroop task with concurrent fNIRS recordings. Connectivity-based features were computed from the hemodynamic signals and a neural efficiency metric was computed by fusing the behavioral and connectivity-based features. We tested the efficacy of two commonly used supervised machine-learning methods, namely the support vector machines (SVM) and artificial neural networks (ANN) in discriminating impulsive adolescents from their non-impulsive peers when trained with multi-domain features. Wrapper method was adapted to identify the informative biomarkers in each domain. Classification accuracies of each algorithm were computed after 10 runs of a 10-fold cross-validation procedure, conducted for 7 different combinations of the 3-domain feature set.Both SVM and ANN achieved diagnostic accuracies above 90% when trained with Wrapper-selected clinical, behavioral and fNIRS derived features. SVM performed significantly higher than ANN in terms of the accuracy metric (92.2% and 90.16%, respectively,= 0.005).Preliminary findings show the feasibility and applicability of both machine-learning based methods for correct identification of impulsive adolescents when trained with multi-domain data involving clinical interviews, fNIRS based biomarkers and neuropsychiatric test measures. The proposed automated classification approach holds promise for assisting the clinical practice of diagnosing impulsivity and other psychiatric disorders. Our results also pave the path for a computer-aided diagnosis perspective for rating the severity of impulsivity.

Spontaneous brain activity occurs at rest, as represented by the default mode network. A resting paradigm is suitable for investigating brain function of patients with psychiatric diseases who may have difficulties adhering to goal-oriented tasks. Evidence accumulated in neuroimaging studies using functional magnetic resonance imaging has shown that the resting cerebral blood flow is impaired in psychiatric diseases. Near-infrared spectroscopy (NIRS), a simple neuroimaging modality, is an optimal tool for the resting paradigm, because it can offer a comfortable environment for measurement. Recent NIRS studies have demonstrated some promising data of altered resting activity in the prefrontal cortex of patients with schizophrenia, which may be exploited to develop further applications of NIRS in clinical psychiatry. Based on these findings, we emphasize the benefits of NIRS for assessing the prefrontal pathophysiology during the resting state and some methodological issues to be noted while analyzing cerebral blood flow using NIRS; moreover, we focus on interpreting these changes based on the complex nature of the spontaneous brain activity during resting state.

The purpose of this study was to compare prefrontal cortex (PFC) activity among subjects with differing social anxiety (SA) severity levels to identify a possible biomarker for severe SA. Further, SA is generally under-diagnosed, so we examined if such measurements could be acquired conveniently, non-invasively, and at low cost using a portable near-infrared spectroscopy (NIRS) system. We classified 96 participants into three groups based on Liebowitz Social Anxiety Scale (LSAS) total score: Low SA (LSA, n = 40), Moderate SA (MSA, n = 39), and High SA (HSA, n = 17). We compared the prefrontal hemodynamic responses among LSAS severity groups during a verbal fluency task using a palm-sized NIRS system. The HSA group exhibited a significantly lower hemodynamic response in the left PFC compared to LSA and MSA groups, whereas there was no significant difference between LSA and MSA groups. There was also no significant difference in the right PFC hemodynamic response among groups. Differences in the severity of SA symptoms may be related to the left PFC function. Low PFC activity during specific cognitive tasks may provide a biomarker for distinguishing severe from mild/moderate SA symptoms to guide subsequent therapeutic decisions.

Brain disorders seriously affect life quality. Therefore, non-invasive neuroimaging has received attention to monitoring and early diagnosing neural disorders to prevent their progress to a severe level. This short review briefly describes the current MRI and PET/CT techniques developed for non-invasive neuroimaging and the future direction of optical imaging techniques to achieve higher resolution and specificity using the second near-infrared (NIR-II) region of wavelength with organic molecules.

INTRODUCTION:Neural alterations in limbic and prefrontal circuits in association with self-injurious behavior have been studied primarily in adult borderline personality disorder (BPD). In adolescent patients, research is still sparse. Here, we used resting functional near-infrared spectroscopy (NIRS) to examine oxygenation of the prefrontal cortex (PFC) and its association with symptom severity in adolescents engaging in non-suicidal self-injury (NSSI) and matched healthy controls (HC). METHODS:Adolescents (12-17 years) with recurrent episodes of NSSI (n = 170) and healthy controls (n = 43) performed a low-demanding resting-state vanilla baseline task. Mean oxygenation of the PFC and functional connectivity within the PFC, were measured using an 8-channel functional NIRS system (Octamon, Artinis, The Netherlands). Various clinical variables derived from diagnostic interviews and self-reports were included in statistical analyses to explore potential associations with PFC oxygenation and connectivity. RESULTS:Adolescents with NSSI showed significantly decreased PFC oxygenation compared to HC, as indexed by oxygenated hemoglobin. Lower PFC oxygenation was associated with greater adverse childhood experiences and less health-related quality of life (HRQoL). While there was no evidence for alterations in PFC connectivity in adolescents engaging in NSSI compared to HC, increased PFC connectivity in the full sample was associated with greater adverse childhood experience, greater BPD pathology, greater depression severity and psychological burden in general, as well as lower HRQoL. CONCLUSION:This study is the first to examine PFC oxygenation using NIRS technology in adolescents engaging in NSSI. Overall, results indicate small effects not specific to NSSI. Clinical implications of these findings and recommendations for further research are discussed.

BACKGROUND:Maintaining cognitive function is integral to a healthy social life in the aged. Although neuropsychological tests and brain imaging methods can assess cognitive dysfunction, these techniques are subjective, psychologically burdensome, and cannot be conducted easily. OBJECTIVE:We sought to develop an objective, low-burden novel cognitive function scale based on functional near-infrared spectroscopy (fNIRS) of hemodynamic changes in the cerebral cortex during daily task performance. METHODS:A total of 63 participants (aged 60-80 years) identified as non-dementia controls (NDC) or with mild cognitive impairment (MCI) were recruited and randomly assigned to training and test data sets. Explanatory variables were hemodynamic responses during low-burden sensory and simple tasks without higher-order brain functioning. RESULTS:A logistic regression analysis of the fNIRS index in NDCs and MCI patients revealed area under the curve, sensitivity, specificity, and holdout results of 0.98, 94%, 88%, and 62% respectively. Correlation between fNIRS index and MCI odds showed positive linearity (R2 = 0.96). CONCLUSION:Positive correlation between the fNIRS index and MCI odds indicated effectiveness of this fNIRS measurement. Although additional experiments are necessary, the fNIRS index representing degree of cognitive decline can be an onsite monitoring tool to assess cognitive status.

BACKGROUND:The TST trial (Treat Stroke to Target) showed the benefit of targeting a low-density lipoprotein cholesterol (LDL-C) concentration of <70 mg/dL in terms of reducing the risk of major cardiovascular events in 2860 patients with ischemic stroke with atherosclerotic stenosis of cerebral vasculature. The impact on carotid atherosclerosis evolution is not known. METHODS:TST-PLUS (Treat Stroke to Target-Plaque Ultrasound Study) included 201 patients assigned to an LDL-C concentration of <70 mg/dL and 212 patients assigned to a target of 100±10 mg/dL. To achieve these goals, investigators used the statin and dosage of their choice and added ezetimibe as needed. Ultrasonographers were certified and carotid ultrasound examinations were performed using M'Ath software at baseline and at 2, 3, and 5 years. All images were uploaded to the Intelligence in Medical Technologies database directly from the carotid ultrasound device. The central core laboratory performed all offline measurements of the intima-media thickness of both common carotid arteries blinded from the randomization arm. The main outcomes were newly diagnosed atherosclerotic plaque on carotid bifurcation or internal carotid artery using the Mannheim consensus definition and between-group comparison of common carotid arteries intima-media thickness change. RESULTS:After a median follow-up of 3.1 years, the achieved LDL-C concentrations were 64 mg/dL (1.64 mmol/L) in the lower-target group and 106 mg/dL (2.72 mmol/L) in the higher-target group. Compared with the higher-target group, patients in the lower-target group had a similar incidence of newly diagnosed carotid plaque: 46/201 (5-year rate, 26.1%) versus 45/212 (5-year rate, 29.7%). The change in common carotid arteries intima-media thickness was -2.69 µm (95% CI, -6.55 to 1.18) in the higher-target group and -10.53 µm (95% CI, -14.21 to -6.85) in the lower-target group, resulting in an absolute between-group difference of -7.84 µm (95% CI, -13.18 to -2.51; =0.004). CONCLUSIONS:In patients with ischemic stroke and atherosclerosis, an LDL-C target of <70 mg/dL (1.8 mmol/L) did not reduce the incidence of new carotid plaques but produced significantly greater regression of carotid atherosclerosis than an LDL-C target of 90 to 110 mg/dL. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01252875.

BACKGROUND:Large blood pressure (BP) variability may contribute to stroke and dementia, but the mechanisms are largely unknown. OBJECTIVES:This study investigated the association of BP variation, considering its magnitude and direction, with the presence and progression of subclinical brain disease in the general population. METHODS:This study included 2,348 participants age ≥55 years from a prospective cohort study. BP was measured at each visit every 3 to 4 years from 1990 onward. Brain magnetic resonance imaging (MRI) was performed at all visits from 2005 onward. The authors primarily assessed variation as the absolute difference in BP divided by the mean over 2 sequential visits for both systolic BP (SBP) and diastolic BP (DBP), and further assessed the direction of the variation. The authors investigated the multivariate-adjusted associations of BP variation with subsequent measurements of MRI markers of cerebral small vessel disease, brain tissue volumes, and white matter microstructural integrity. Longitudinal changes in these markers also were assessed. RESULTS:A large SBP variation (top vs. bottom tertiles), measured on average 7 years preceding brain MRI, was associated with higher odds of having severe white matter hyperintensities (WMH) (odds ratio [OR]: 1.32; 95% confidence interval [CI]: 1.21 to 1.43), lacunes (OR: 1.25; 95% CI: 1.04 to 1.48), and microbleeds (OR: 1.16; 95% CI: 1.03 to 1.31). Similarly, this variation was associated with smaller total brain volume and worse white matter microstructural integrity (all p < 0.001). A large SBP variation was also associated with the progression of WMH (rate ratio [RR]: 1.14; 95% CI: 1.02 to 1.27). Higher burdens of these brain imaging markers were observed with both large rises and falls in SBP. Similar findings were observed for DBP variation. CONCLUSIONS:Elevated BP variation was associated with a wide range of subclinical brain structural changes, including MRI markers of cerebral small vessel disease, smaller brain tissue volumes, and worse white matter microstructural integrity. These subclinical brain changes could be the underlying mechanisms linking BP variation to dementia and stroke.

Depression is the result of a complex interaction of social, psychological and physiological elements. Research into the brain disorders of patients suffering from depression can help doctors to understand the pathogenesis of depression and facilitate its diagnosis and treatment. Functional near-infrared spectroscopy (fNIRS) is a non-invasive approach to the detection of brain functions and activities. In this paper, a comprehensive fNIRS-based depression-processing architecture, including the layers of source, feature and model, is first established to guide the deep modeling for fNIRS. In view of the complexity of depression, we propose a methodology in the time and frequency domains for feature extraction and deep neural networks for depression recognition combined with current research. It is found that compared to non-depression people, patients with depression have a weaker encephalic area connectivity and lower level of activation in the prefrontal lobe during brain activity. Finally, based on raw data, manual features and channel correlations, the AlexNet model shows the best performance, especially in terms of the correlation features and presents an accuracy rate of 0.90 and a precision rate of 0.91, which is higher than ResNet18 and machine-learning algorithms on other data. Therefore, the correlation of brain regions can effectively recognize depression (from cases of non-depression), making it significant for the recognition of brain functions in the clinical diagnosis and treatment of depression.

Near-infrared spectroscopy (NIRS) is a functional neuroimaging modality that has advantages in clinical usage. Previous functional magnetic resonance imaging (fMRI) studies have found that the resting-state functional connectivity (RSFC) of the default mode network (DMN) is increased, while the RSFC of the cognitive control network (CCN) is reduced in patients with major depressive disorder (MDD) compared with healthy controls. This study tested whether the NIRS-based RSFC measurements can detect the abnormalities in RSFC that have been associated with MDD in previous fMRI studies. We measured 8 min of resting-state brain activity in 34 individuals with MDD and 78 age- and gender-matched healthy controls using a whole-head NIRS system. We applied a previously established partial correlation analysis for estimating RSFCs between the 17 cortical regions. We found that MDD patients had a lower RSFC between the left dorsolateral prefrontal cortex and the parietal lobe that comprise the CCN, and a higher RSFC between the right orbitofrontal cortex and ventrolateral prefrontal cortex, compared to those in healthy controls. The RSFC strength of the left CCN was negatively correlated with the severity of depressive symptoms and the dose of antipsychotic medication and positively correlated with the level of social functioning. The results of this study suggest that NIRS-based measurements of RSFCs have potential clinical applications.

OBJECTIVE:Patients with major depressive disorder tend to exhibit poorer decision-making capacity than the general population, but neurobiological evidence is lacking. Functional near-infrared spectroscopy monitors changes in oxy-haemoglobin concentration in the cerebral cortex. It may provide an objective assessment of neurophysiological responses during decision-making processes. Thus, this study investigated the effect of major depressive disorder diagnosis and severity on prefrontal cortex activity during the Iowa gambling task. METHODS:Right-handed healthy controls ( = 25) and patients with major depressive disorder ( = 25) were matched for age, gender, ethnicity and years of education in this cross-sectional study. Functional near-infrared spectroscopy signals and the responses made during a computerised Iowa gambling task were recorded. In addition, demographics, clinical history and symptom severity were noted. RESULTS:Compared to healthy controls, patients with major depressive disorder had reduced haemodynamic response in several cortical regions of the frontal lobe (Hedge's range from 0.71 to 1.52; values range from ⩽0.001 to 0.041). Among patients, mean oxy-haemoglobin declined with major depressive disorder severity in the right orbitofrontal cortex (Pearson's  = -0.423;  = 0.024). CONCLUSION:Haemodynamic dysfunction of the prefrontal cortex during decision-making processes is associated with major depressive disorder diagnosis and severity. These neurophysiological alterations may have a role in the decision-making capacity of patients with major depressive disorder.

Theory of Mind (ToM) deficits interfere in social cognitive functioning in schizophrenia (SCZ) and are increasingly recognized to do so in bipolar disorder (BD), however their clinical and neurobiological correlates remain unclear. This study represents the first direct comparison of subjects with SCZ (N = 26), BD (N = 26) and healthy controls (N = 33) in cortical activity during the Reading the Mind in the Eyes Task (RMET) using functional Near Infrared Spectroscopy (fNIRS) with the control condition (CC) involving gender identification via the same stimuli. The three groups were compared with a comprehensive ToM battery and assessed in terms of the relationship of ToM performance with clinical symptoms, insight and functioning. The controls scored higher than the SCZ and BD groups in ToM assessments, with SCZ group showing the worse performance in terms of meta-representation and empathy. The SCZ group ToM scores inversely correlated with negative symptom severity and positively correlated with insight; BD group ToM scores negatively correlated with subclinical mania symptoms and projected functioning. Cortical activity was higher during the ToM condition compared to the CC in the pre-motor and supplementary-motor cortices, middle and superior temporal gyri, and the primary somatosensory cortex. Group x Condition interaction was detected whereby activity was higher during the ToM condition among controls with no detected difference between SCZ and BD groups. The results suggest that ToM is represented similarly in cortical activity in SCZ and BD compared to healthy controls pointing to possible neurobiological convergence of SCZ and BD in underlying impairments of social cognition.

BACKGROUND:Functional near-infrared spectroscopy (fNIRS) is an emerging neuroimaging modality that provides a direct and quantitative assessment of cortical haemodynamic response during a cognitive task. It may be used to identify neurophysiological differences between psychiatric disorders with overlapping symptoms, such as bipolar disorder (BD) and borderline personality disorder (BPD). Hence, this preliminary study aimed to compare the cerebral haemodynamic function of healthy controls (HC), patients with BD and patients with BPD. METHODS:Twenty-seven participants (9 HCs, 9 patients with BD and 9 patients with BPD) matched for age, gender, ethnicity and education were recruited. Relative oxy-haemoglobin and deoxy-haemoglobin changes in the frontotemporal cortex was monitored with a 52-channel fNIRS system during a verbal fluency task (VFT). VFT performance, clinical history and symptom severity were also noted. RESULTS:Compared to HCs, both patient groups had lower mean oxy-haemoglobin in the frontotemporal cortex during the VFT. Moreover, mean oxy-haemoglobin in the left inferior frontal region is markedly lower in patients with BPD compared to patients with BD. Task performance, clinical history and symptom severity were not associated with mean oxy-haemoglobin levels. CONCLUSIONS:Prefrontal cortex activity is disrupted in patients with BD and BPD, but it is more extensive in BPD. These results provide further neurophysiological evidence for the separation of BPD from the bipolar spectrum. fNIRS could be a potential tool for assessing the frontal lobe function of patients who present with symptoms that are common to BD and BPD.

OBJECTIVES:In Denmark, 25% of hospital admissions with stroke are recurrent strokes. With thrombolytic treatment, more patients survive with only minor disability. This promising development should be followed up by intensive secondary prevention. Hypertension is the most important target. We aimed at testing the hypotheses that early follow-up in a preventive clinic would result in (a) a higher proportion of patients with blood pressure at target and (b) time to stroke recurrence, myocardial infarction, and death would be longer in the intervention group compared to controls. MATERIALS AND METHODS:Eligible patients admitted to the stroke unit of Herlev Hospital were randomized shortly before discharge to intervention or control group. Of 78 included participants, data from 73 were available for follow-up 9 months after inclusion. Patients in the intervention group were seen in the clinic within 1 week. In case of hypertension, treatment was initiated or supplied with a new drug. We used individual targets for blood pressure according to diagnosis of stroke and patients' comorbidity. Patients in the intervention group had a median of five visits to the preventive clinic. RESULTS:In the intervention group, blood pressure was treated to target in 25 patients (69%) versus 14 (38%) in the control group (p = .007). Median time to first event was 44 months (4-49) in the intervention group and 19 months (4-37) in controls (p = .316). CONCLUSIONS:Treatment of hypertension to individual targets after stroke is feasible. It may postpone recurrent stroke and death in stroke survivors.