Application of functional near-infrared spectroscopy in psychiatry

Identifying neuroimaging biomarkers in major depressive disorder using machine learning algorithms and functional near-infrared spectroscopy (fNIRS) during verbal fluency task

One of the most prevalent psychiatric disorders is major depressive disorder (MDD), which increases the probability of suicidal ideation or untimely demise. Abnormal frontal hemodynamic changes detected by functional near-infrared spectroscopy (fNIRS) during verbal fluency task (VFT) have the potential to be used as an objective indicator for assessing clinical symptoms. However, comprehensive quantitative and objective assessment instruments for individuals who exhibit symptoms suggestive of depression remain undeveloped. Drawing from a total of 467 samples in a large-scale dataset comprising 289 MDD patients and 178 healthy controls, fNIRS measurements were obtained throughout the VFT. To identify unique MDD biomarkers, this research introduced a data representation approach for extracting spatiotemporal features from fNIRS signals, which were subsequently utilized as potential predictors. Machine learning classifiers (e.g., Gradient Boosted Decision Trees (GBDT) and Multilayer Perceptron) were implemented to assess the ability to predict selected features. The mean and standard deviation of the cross-validation indicated that the GBDT model, when combined with the 180-feature pattern, distinguishes patients with MDD from healthy controls in the most effective manner. The accuracy of correct classification for the test set was 0.829 ± 0.053, with an AUC of 0.895 (95 % CI: 0.864-0.925) and a sensitivity of 0.914 ± 0.051. Channels that made the most important contribution to the identification of MDD were identified using Shapley Additive Explanations method, located in the frontopolar area and the dorsolateral prefrontal cortex, as well as pars triangularis Broca's area. Assessment of abnormal prefrontal activity during the VFT in MDD serves as an objectively measurable biomarker that could be utilized to evaluate cognitive deficits and facilitate early screening for MDD. The model suggested in this research could be applied to large-scale case-control fNIRS datasets to detect unique characteristics of MDD and offer clinicians an objective biomarker-based analytical instrument to assist in the evaluation of suspicious cases.

Different activation in dorsolateral prefrontal cortex between anxious depression and non-anxious depression during an autobiographical memory task: A fNIRS study

OBJECTIVE

Using functional near-infrared spectroscopy (fNIRS) previous studies have found that activation differences in the dorsolateral prefrontal cortex (DLPFC) during an autobiographical memory task (AMT) under the condition of different emotional valences may be neurophysiological markers of depression and different depression subtypes. Additionally, compared with non-anxious depression, anxious depression presents abnormal hemodynamic activation in the DLPFC. This study aimed to use fNIRS to investigate hemodynamic activation in the DLPFC of depression patients with and without anxiety during AMT triggered by different emotional valence stimuli.

METHODS

We recruited 194 patients with depression (91 with non-anxious depression, 103 with anxious depression) and 110 healthy controls from Chinese college students. A 53-channel fNIRS was used to detect cerebral hemodynamic differences in the three groups during AMT.

RESULTS

The results showed that: (1) the activation of oxy-Hb in the left DLPFC was significantly higher under positive emotional valence than under negative emotional valence for healthy controls and patients with non-anxious depression, while there was no significant difference between positive and negative emotional valence observed in response to anxious depression; and (2) Oxy-Hb activation under negative emotional valence was significantly higher in the anxious depression group than in the non-anxious depression group.

CONCLUSIONS

This study revealed that the hemodynamic hyperactivation of negative emotional valence in the left DLPFC may be due to the neurophysiological differences between anxious and non-anxious patients with depression.

Discriminative analysis of schizophrenia and major depressive disorder using fNIRS

BACKGROUND

Research into the shared and distinct brain dysfunctions in patients with schizophrenia (SCZ) and major depressive disorder (MDD) has been increasing. However, few studies have explored the application of functional near-infrared spectroscopy (fNIRS) in investigating brain dysfunction and enhancing diagnostic methodologies in these two conditions.

METHODS

A general linear model was used for analysis of brain activation following task-state fNIRS from 131 patients with SCZ, 132 patients with MDD and 130 healthy controls (HCs). Subsequently, seventy-seven time-frequency analysis methods were used to construct new features of fNIRS, followed by the implementation of five machine learning algorithms to develop a differential diagnosis model for the three groups. This model was evaluated by comparing it to both a diagnostic model relying on traditional fNIRS features and assessments made by two psychiatrists.

RESULTS

Brain activation analysis revealed significantly lower activation in Broca's area, the dorsolateral prefrontal cortex, and the middle temporal gyrus for both the SCZ and MDD groups compared to HCs. Additionally, the SCZ group exhibited notably lower activation in the superior temporal gyrus and the subcentral gyrus compared to the MDD group. When distinguishing among the three groups using independent validation datasets, the models utilizing new fNIRS features achieved an accuracy of 85.90 % (AUC = 0.95). In contrast, models based on traditional fNIRS features reached an accuracy of 52.56 % (AUC = 0.66). The accuracies of the two psychiatrists were 42.00 % (AUC = 0.60) and 38.00 % (AUC = 0.50), respectively.

CONCLUSION

This investigation brings to light the shared and distinct neurobiological abnormalities present in SCZ and MDD, offering potential enhancements for extant diagnostic systems.

Multimodal analysis of cortical activation in young male adults with internet gaming disorder: A resting state EEG-fNIRS study

BACKGROUND

Internet gaming disorder (IGD) has become increasingly prevalent worldwide and is recognized as a significant public health concern because of its negative consequences on individuals mental and physical health, social relationships, academic performance and overall well-being. While research on IGD has gained significant momentum in the past decade, the neural substrates underlying this disorder remains unclear. This study aims to investigate resting-state cortical activation in male subjects with IGD using a concurrent functional near infrared spectroscopy (fNIRS) and electroencephalography (EEG) hybrid system.

METHODS

Twenty-two male individuals with IGD (18-23 years old) and twenty-two male healthy, age-matched healthy controls were included in the study. Mean oxygenation of the prefrontal cortex (PFC) and whole head neural activity were measured using fNIRS and EEG respectively, during eyes-open and eyes-closed conditions at the resting state. EEG signals were decomposed into distinct frequency sub-bands with wavelet transform, followed by the analysis of the power spectral density within each band. Mean oxygenation of PFC is measured using a multichannel fNIRS system.

RESULTS

Results revealed that the individuals with IGD had significantly higher beta power in the frontal region compared to the control group. Individuals with IGD showed significantly increased PFC oxygenation compared to healthy controls. Additionally, both frontal beta power and PFC oxygenation were significantly correlated with IGD severity. However, there were no significant correlations observed between oxygenation and beta powers.

CONCLUSION

This study is the first to examine resting-state cortical activation using multimodal EEG-fNIRS system in young adults with IGD. Moreover, it provides an important contribution to the understanding of the underlying neural mechanisms of IGD and offer new insights for the diagnosis and intervention of the disorder using multimodal EEG-fNIRS system. Further studies should aim to replicate the findings of this study using a larger and more culturally diverse sample to support the neurophysiological basis of IGD.

Effects of an online mindfulness-based intervention on brain haemodynamics: a pilot randomized controlled trial using functional near-infrared spectroscopy

Although many neuroimaging studies have evaluated changes in the prefrontal cortex during mindfulness-based interventions, most of these studies were cross-sectional studies of skilled participants or involved pre-post comparisons before and after a single session. While functional near-infrared spectroscopy is a useful tool to capture changes in the hemodynamic response of the prefrontal cortex during continuous mindfulness-based intervention, its ability to detect the accumulated effects of continuous mindfulness-based intervention is currently unclear. We investigated whether a 12-wk online mindfulness-based intervention changed the hemodynamic response of the prefrontal cortex during a verbal fluency task. Eighty-two healthy university students were randomly allocated to a 12-wk online mindfulness-based intervention group or a wait-list control group. The integral values of oxygenated hemoglobin measured using functional near-infrared spectroscopy before and after the intervention were compared to the values in the wait-list group. The intervention condition showed significantly greater functional near-infrared spectroscopy signal activation than the control condition; however, the effect sizes before and after the intervention were small. Thus, continuous mindfulness-based intervention could alter prefrontal cortex function, and functional near-infrared spectroscopy could be useful for measuring the accumulated effects of continuous mindfulness-based interventions. With a better understanding of the association between mindfulness and functional near-infrared spectroscopy signals, functional near-infrared spectroscopy can be used for biofeedback analyses.

A scoping review of functional near-infrared spectroscopy biomarkers in late-life depression: Depressive symptoms, cognitive functioning, and social functioning

Late-life depression is one of the most damaging mental illnesses, disrupting the normal lives of older people by causing chronic illness and cognitive impairment. Patients with late-life depression, accompanied by changes in appetite, insomnia, fatigue and guilt, are more likely to experience irritability, anxiety and somatic symptoms. It increases the risk of suicide and dementia and is a major challenge for the public health systems. The current clinical assessment, identification and effectiveness assessment of late-life depression are primarily based on history taking, mental status examination and scale scoring, which lack subjectivity and precision. Functional near-infrared spectroscopy is a rapidly developing optical imaging technology that objectively reflects the oxygenation of hemoglobin in different cerebral regions during different tasks and assesses the functional status of the cerebral cortex. This article presents a comprehensive review of the assessment of functional near-infrared spectroscopy technology in assessing depressive symptoms, social functioning, and cognitive functioning in patients with late-life depression. The use of functional near-infrared spectroscopy provides greater insight into the neurobiological mechanisms underlying depression and helps to assess these three aspects of functionality in depressed patients. In addition, the study discusses the limitations of previous research and explores potential advances in the field.

Diagnostic machine learning applications on clinical populations using functional near infrared spectroscopy: a review

Functional near-infrared spectroscopy (fNIRS) and its interaction with machine learning (ML) is a popular research topic for the diagnostic classification of clinical disorders due to the lack of robust and objective biomarkers. This review provides an overview of research on psychiatric diseases by using fNIRS and ML. Article search was carried out and 45 studies were evaluated by considering their sample sizes, used features, ML methodology, and reported accuracy. To our best knowledge, this is the first review that reports diagnostic ML applications using fNIRS. We found that there has been an increasing trend to perform ML applications on fNIRS-based biomarker research since 2010. The most studied populations are schizophrenia (n = 12), attention deficit and hyperactivity disorder (n = 7), and autism spectrum disorder (n = 6) are the most studied populations. There is a significant negative correlation between sample size (>21) and accuracy values. Support vector machine (SVM) and deep learning (DL) approaches were the most popular classifier approaches (SVM = 20) (DL = 10). Eight of these studies recruited a number of participants more than 100 for classification. Concentration changes in oxy-hemoglobin (ΔHbO) based features were used more than concentration changes in deoxy-hemoglobin (ΔHb) based ones and the most popular ΔHbO-based features were mean ΔHbO (n = 11) and ΔHbO-based functional connections (n = 11). Using ML on fNIRS data might be a promising approach to reveal specific biomarkers for diagnostic classification.

Flexible-circuit-based 3-D aware modular optical brain imaging system for high-density measurements in natural settings

Significance

Functional near-infrared spectroscopy (fNIRS) presents an opportunity to study human brains in everyday activities and environments. However, achieving robust measurements under such dynamic condition remains a significant challenge.

Aim

The modular optical brain imaging (MOBI) system is designed to enhance optode-to-scalp coupling and provide real-time probe 3-D shape estimation to improve the use of fNIRS in everyday conditions.

Approach

The MOBI system utilizes a bendable and lightweight modular circuit-board design to enhance probe conformity to head surfaces and comfort for long-term wearability. Combined with automatic module connection recognition, the built-in orientation sensors on each module can be used to estimate optode 3-D positions in real-time to enable advanced tomographic data analysis and motion tracking.

Results

Optical characterization of the MOBI detector reports a noise equivalence power (NEP) of 8.9 and 7.3 pW / H z at 735 nm and 850 nm, respectively, with a dynamic range of 88 dB. The 3-D optode shape acquisition yields an average error of 4.2 mm across 25 optodes in a phantom test compared to positions acquired from a digitizer. Results for initial in vivo validations, including a cuff occlusion and a finger-tapping test, are also provided.

Conclusions

To the best of our knowledge, the MOBI system is the first modular fNIRS system featuring fully flexible circuit boards. The self-organizing module sensor network and automatic 3-D optode position acquisition, combined with lightweight modules (18 g/module) and ergonomic designs, would greatly aid emerging explorations of brain function in naturalistic settings.

Reduced inhibition control ability in children with ADHD due to coexisting learning disorders: an fNIRS study

Introduction

Inhibition control, as the core component of executive function, might play a crucial role in the understanding of attention deficit/hyperactivity disorder (ADHD) and specific learning disorders (SLD). Inhibition control deficits have been observed in children with ADHD or SLD. This study sought to test in a multi-modal fashion (i.e., behavior and plus brain imaging) whether inhibition control abilities would be further deteriorated in the ADHD children due to the comorbidity of SLD.

Method

A total number of 90 children (aged 6-12 years) were recruited, including 30 ADHD, 30 ADHD+SLD (children with the comorbidity of ADHD and SLD), and 30 typically developing (TD) children. For each participant, a 44-channel functional near infrared spectroscopy (fNIRS) equipment was first adopted to capture behavioral and cortical hemodynamic responses during a two-choice Oddball task (a relatively new inhibition control paradigm). Then, 50 metrics were extracted, including 6 behavioral metrics (i.e., OddballACC, baselineACC, totalACC, OddballRT, baselineRT, and totalRT) and 44 beta values in 44 channels based on general linear model. Finally, differences in those 50 metrics among the TD, ADHD, and ADHD+SLD children were analyzed.

Results

Findings showed that: (1) OddballACC (i.e., the response accuracy in deviant stimuli) is the most sensitive metric in identifying the differences between the ADHD and ADHD+SLD children; and (2) The ADHD+SLD children exhibited decreased behavioral response accuracy and brain activation level in some channels (e.g., channel CH35) than both the ADHD and TD children.

Discussion

Findings seem to support that inhibition control abilities would be further decreased in the ADHD children due to the comorbidity of SLD.

Differences in prefrontal cortex activation in Chinese college students with different severities of depressive symptoms: A large sample of functional near-infrared spectroscopy (fNIRS) findings

BACKGROUND

Previous studies proposed that functional near-infrared spectroscopy (fNIRS) can be used to distinguish between not only different severities of depressive symptoms but also different subgroups of depression, such as anxious and non-anxious depression, bipolar and unipolar depression, and melancholia and non-melancholia depression. However, the differences in brain haemodynamic activation between depression subgroups (such as confirmed depression [CD] and suspected depression [SD]) with different symptom severities and the possible correlation between symptom severity and haemodynamic activation in specific brain regions using fNIRS have yet to be clarified.

METHODS

The severity of depression symptoms was classified using the Hospital Anxiety and Depression scale (HADS) and the Mini International Neuropsychiatric Interview by psychiatrists. We recruited 654 patients with depression who had varying severities of depressive symptoms, including 276 with SD and 378 with CD, and 317 with HCs from among Chinese college students. The 53-channel fNIRS was used to detect the cerebral hemodynamic difference of the three groups during the VFT (verbal fluency task).

RESULTS

Compared with the HC, region-specific fNIRS leads indicate CD patients had significant lower haemodynamic activation in three particular prefrontal regions: 1) right dorsolateral prefrontal cortex (DLPFC), 2) bilateral frontopolar cortex (FPC), and 3) right Broca's area (BA). SD vs. HC comparisons revealed only significant lower haemodynamic activation in the right FPC area. Compared to SD patients, CD patients exhibited decreased hemodynamic activation changes in the right DLPFC and the right BA. Correlation analysis established a significant negative correlation between the hemodynamic changes in the bilateral FPC and the severity of depressive symptoms.

CONCLUSIONS

The right DLPFC and right BA are expected to be physiological mechanisms to distinguish depression subgroups (CD, SD) with different symptom severities. The haemodynamic changes in the bilateral FPC was nagatively associated with the symptom severity of depression.

Working and short-term memory in children with ADHD: an examination of prefrontal cortical functioning using functional Near-Infrared Spectroscopy (fNIRS)

Working memory impairments are an oft-reported deficit among children with ADHD, and complementary neuroimaging studies implicate reductions in prefrontal cortex (PFC) structure and function as a neurobiological explanation. Most imaging studies, however, rely on costly, movement-intolerant, and/or invasive methods to examine cortical differences. This is the first study to use a newer neuroimaging tool that overcomes these limitations, functional Near Infrared Spectroscopy (fNIRS), to investigate hypothesized prefrontal differences. Children (aged 8-12) with ADHD (N = 22) and typically developing (N = 18) children completed phonological working memory (PHWM) and short-term memory (PHSTM) tasks. Children with ADHD evinced poorer performance on both tasks, with greater differences observed in PHWM (Hedges' g = 0.67) relative to PHSTM (g = 0.39). fNIRS revealed reduced hemodynamic response among children with ADHD in the dorsolateral PFC while completing the PHWM task, but not within the anterior or posterior PFC. No between-group fNIRS differences were observed during the PHSTM task. Findings suggest that children with ADHD exhibit an inadequate hemodynamic response in a region of the brain that underlies PHWM abilities. The study also highlights the use of fNIRS as a cost-effective, noninvasive neuroimaging technique to localize/quantify neural activation patterns associated with executive functions.

A scoping review of utilization of the verbal fluency task in Chinese and Japanese clinical settings with near-infrared spectroscopy

This review targets the application of the Verbal Fluency Task (VFT) in conjunction with functional near-infrared spectroscopy (fNIRS) for diagnosing psychiatric disorders, specifically in the contexts of China and Japan. These two countries are at the forefront of integrating fNIRS with VFT in clinical psychiatry, often employing this combination as a complementary tool alongside traditional psychiatric examinations. Our study aims to synthesize research findings on the hemodynamic responses elicited by VFT task in clinical settings of the two countries, analyzing variations in task design (phonological versus semantic), stimulus modality (auditory versus visual), and the impact of language typology. The focus on China and Japan is crucial, as it provides insights into the unique applications and adaptations of VFT in these linguistically and culturally distinct environments. By exploring these specific cases, our review underscores the importance of tailoring VFT to fit the linguistic and cultural context, thereby enhancing its validity and utility in cross-cultural psychiatric assessments.

Activation changes in patients with post-stroke cognitive impairment receiving intermittent theta burst stimulation: A functional near-infrared spectroscopy study

BACKGROUND

Intermittent theta burst stimulation (iTBS) has demonstrated efficacy in patients with cognitive impairment. However, activation patterns and mechanisms of iTBS for post-stroke cognitive impairment (PSCI) remain insufficiently understood.

OBJECTIVE

To investigate the activation patterns and potential benefits of using iTBS in patients with PSCI.

METHODS

A total of forty-four patients with PSCI were enrolled and divided into an iTBS group (iTBS and cognitive training) or a control group (cognitive training alone). Outcomes were assessed based on the activation in functional near-infrared spectroscopy (fNIRS), as well as Loewenstein Occupational Therapy Cognitive Assessment (LOTCA) and the modified Barthel Index (MBI).

RESULTS

Thirty-eight patients completed the interventions and assessments. Increased cortical activation was observed in the iTBS group after the interventions, including the right superior temporal gyrus (STG), left frontopolar cortex (FPC) and left orbitofrontal cortex (OFC). Both groups showed significant improvements in LOTCA and MBI after the interventions (p < 0.05). Furthermore, the iTBS group augmented superior improvement in the total score of MBI and LOTCA compared to the control group, especially in visuomotor organization and thinking operations (p < 0.05).

CONCLUSION

iTBS altered activation patterns and improved cognitive function in patients with PSCI. The activation induced by iTBS may contribute to the improvement of cognitive function.

Altered resting-state cerebellar-cerebral functional connectivity in patients with panic disorder before and after treatment

The study aimed to investigate the functional connectivity (FC) between the cerebellum and intrinsic cerebral networks in patients with panic disorder (PD), and to observe changes in the cerebellar-cerebral FC following pharmacotherapy. Fifty-four patients with PD and 54 healthy controls (HCs) underwent clinical assessments and functional magnetic resonance imaging scans before and after a 5-week paroxetine treatment. Seed-based cerebellar-cerebral FC was compared between the PD and HC groups, as well as between patients with PD before and after treatment. Additionally, the correlations between FC and clinical features of PD were analyzed. Compared to HCs, patients with PD had altered cerebellar-cerebral FC in the default mode, affective-limbic, and sensorimotor networks. Moreover, a negative correlation between cerebellar-insula disconnection and the severity of depressive symptoms in patients with PD (Pearson correlation, r = -0.424, p = 0.001, Bonferroni corrected) was found. After treatment, most of the enhanced FCs observed in patients with PD at baseline returned to levels similar to those observed in HCs. However, the reduced FC at baseline did not significantly change after treatment. The findings suggest that patients with PD have specific deficits in resting-state cerebellar-cerebral FC and that paroxetine may improve PD by restoring the balance of cerebellar-cerebral FC. These findings emphasize the crucial involvement of cerebellar-cerebral FC in the neuropsychological mechanisms underlying PD and in the potential pharmacological mechanisms of paroxetine for treating PD.

Functional Near-Infrared Spectroscopy of English-Speaking Adults With Attention-Deficit/Hyperactivity Disorder During a Verbal Fluency Task

OBJECTIVE

Functional near-infrared spectroscopy (fNIRS) provides direct and quantitative assessment of cortical hemodynamic response. It has been used to identify neurophysiological alterations in medication-naïve adults with attention-deficit/hyperactivity disorder (ADHD). Hence, this study aimed to distinguish both medication-naïve and medicated adults with ADHD from healthy controls (HC).

METHOD

75 HCs, 75 medication-naïve, and 45 medicated patients took part in this study. fNIRS signals during a verbal fluency task (VFT) were acquired using a 52-channel system and relative oxy-hemoglobin changes in the prefrontal cortex were quantified.

RESULTS

Prefrontal cortex hemodynamic response was lower in patients than HCs (p ≤ ≤.001). Medication-naïve and medicated patients did not differ in hemodynamic response or symptom severity (p > .05). fNIRS measurements were not associated with any clinical variables (p > .05). 75.8% patients and 76% HCs were correctly classified using hemodynamic response.

CONCLUSION

fNIRS may be a potential diagnostic tool for adult ADHD. These findings need to be replicated in larger validation studies.

Deep neural network to differentiate internet gaming disorder from healthy controls during stop-signal task: a multichannel near-infrared spectroscopy study

Internet Gaming Disorder (IGD), as one of worldwide mental health issues, leads to negative effects on physical and mental health and has attracted public attention. Most studies on IGD are based on screening scales and subjective judgments of doctors, without objective quantitative assessment. However, public understanding of internet gaming disorder lacks objectivity. Therefore, the researches on internet gaming disorder still have many limitations. In this paper, a stop-signal task (SST) was designed to assess inhibitory control in patients with IGD based on prefrontal functional near-infrared spectroscopy (fNIRS). According to the scale, the subjects were divided into health and gaming disorder. A total of 40 subjects (24 internet gaming disorders; 16 healthy controls) signals were used for deep learning-based classification. The seven algorithms used for classification and comparison were deep learning algorithms (DL) and machine learning algorithms (ML), with four and three algorithms in each category, respectively. After applying hold-out method, the performance of the model was verified by accuracy. DL models outperformed traditional ML algorithms. Furthermore, the classification accuracy of the two-dimensional convolution neural network (2D-CNN) was 87.5% among all models. This was the highest accuracy out of all models that were tested. The 2D-CNN was able to outperform the other models due to its ability to learn complex patterns in data. This makes it well-suited for image classification tasks. The findings suggested that a 2D-CNN model is an effective approach for predicting internet gaming disorder. The results show that this is a reliable method with high accuracy to identify patients with IGD and demonstrate that the use of fNIRS to facilitate the development of IGD diagnosis has great potential.

In situ fNIRS measurements during cognitive behavioral emotion regulation training in rumination-focused therapy: A randomized-controlled trial

Repetitive negative thinking (RNT), including rumination, plays a key role in various psychopathologies. Although several psychotherapeutic treatments have been developed to reduce RNT, the neural correlates of those specific treatments and of psychotherapy in general are largely unknown. Functional near-infrared spectroscopy (fNIRS) offers the potential to investigate the neural correlates of psychotherapeutic techniques in situ. Therefore, in this study we investigated the efficacy and neural correlates of a fNIRS adapted Mindfulness-based Emotion Regulation Training (MBERT) for the treatment of depressive rumination in 42 subjects with major depressive disorder (MDD) in a cross-over designed randomized controlled trial. Using psychometric measures, subjective ratings and fNIRS, we analyzed in situ changes in depressive symptom severity, ruminative thoughts and cortical activity in the Cognitive Control Network (CCN). Our results show that MBERT is effective in treating depressive symptoms and rumination. On a neural level, we found consistently higher cortical activation during emotion regulation training compared to control trials in the bilateral inferior frontal gyrus (IFG) and dorsolateral prefrontal cortex (DLPFC). Furthermore, cortical oxygenation decreased from session to session in the bilateral DLPFC. The relevance of the results for the psychotherapeutic treatment of MDD as well as further necessary investigations are discussed.

Comprehensive investigations of cerebral hemodynamic responses in CSVD patients with mental disorders: a pilot study

Although a portion of patients with cerebral small vessel disease (CSVD) present mental disorders, there is currently a lack of appropriate technologies to evaluate brain functions that are relevant to neurovascular coupling. Furthermore, there are no established objective criteria for diagnosing and distinguishing CSVD-induced mental disorders and psychiatric diseases. In this study, we report the first comprehensive investigation of the cerebral hemodynamics of CSVD patients who also presented with mental disorders. Two CSVD patients with similar magnetic resonance imaging (MRI) outcomes but with non-identical mental symptoms participated in this study. The patients were instructed to perform the verbal fluency task (VFT), high-level cognition task (HCT), as well as voluntary breath holding (VBH). A functional near-infrared spectroscopy (fNIRS) was used to measure the cerebral oxygenation responses. Additionally, a diffuse correlation spectroscopy (DCS) was used to measure the cerebral blood flow (CBF) responses. Both technologies were also applied to a healthy subject for comparison. The fNIRS results showed that both CSVD patients presented abnormal cerebral oxygenation responses during the VFT, HCT, and VBH tasks. Moreover, the patient with cognition impairment showed fluctuations in CBF during these tasks. In contrast, the patient without cognition impairment mostly presented typical CBF responses during the tasks, which was consistent with the healthy subject. The cognitive impairment in CSVD patients may be due to the decoupling of the neurons from the cerebrovascular, subsequently affecting the autoregulation capacity. The results of the fNIRS and DCS combined provide a comprehensive evaluation of the neurovascular coupling and, hence, offer great potential in diagnosing cerebrovascular or psychiatric diseases.

Open access dataset integrating EEG and fNIRS during Stroop tasks

Conflict monitoring and processing are crucial components of the human cognitive system, with significant implications for daily life and the diagnosis of cognitive disorders. The Stroop task, combined with brain function detection technology, has been widely employed as a classical paradigm for investigating conflict processing. However, there remains a lack of public datasets that integrate Electroencephalogram (EEG) and functional Near-infrared Spectroscopy (fNIRS) to simultaneously record brain activity during a Stroop task. We introduce a dual-modality Stroop task dataset incorporating 34-channel EEG (sampling frequency is 1000 Hz) and 20-channel high temporal resolution fNIRS (sampling frequency is 100 Hz) measurements covering the whole frontal cerebral cortex from 21 participants (9 females/12 males, aged 23.0 ± 2.3 years). Event-related potential analysis of EEG recordings and activation analysis of fNIRS recordings were performed to show the significant Stroop effect. We expected that the data provided would be utilized to investigate multimodal data processing algorithms during cognitive processing.

Lateralization difference in functional activity during Stroop tasks: a functional near-infrared spectroscopy and EEG simultaneous study

Introduction

Conflict monitoring and processing is an important part of the human cognitive system, it plays a key role in many studies of cognitive disorders.

Methods

Based on a Chinese word-color match Stroop task, which included incongruent and neutral stimuli, the Electroencephalogram (EEG) and functional Near-infrared Spectroscopy (fNIRS) signals were recorded simultaneously. The Pearson correlation coefficient matrix was calculated to analyze brain connectivity based on EEG signals. Granger Causality (GC) method was employed to analyze the effective connectivity of bilateral frontal lobes. Wavelet Transform Coherence (WTC) was used to analyze the functional connectivity of the bilateral hemisphere and ipsilateral hemisphere.

Results

Results indicated that brain connectivity analysis on EEG signals did not show any significant lateralization, while fNIRS analysis results showed the frontal lobes especially the left frontal lobe play the leading role in dealing with conflict tasks. The human brain shows leftward lateralization while processing the more complicated incongruent stimuli. This is demonstrated by the higher functional connectivity in the left frontal lobe and the information flow from the left frontal lobe to the right frontal lobe.

Discussion

Our findings in brain connectivity during cognitive conflict processing demonstrated that the dual modality method combining EEG and fNIRS is a valuable tool to excavate more information through cognitive and physiological studies.

Subjective feeling of control during fNIRS-based neurofeedback targeting the DL-PFC is related to neural activation determined with short-channel correction

Neurofeedback (NF) training is a promising preventive and therapeutic approach for brain and behavioral impairments, the dorsolateral prefrontal cortex (DL-PFC) being a relevant region of interest. Functional near-infrared spectroscopy (NIRS) has recently been applied in NF training. However, this approach is highly sensitive to extra-cerebral vascularization, which could bias measurements of cortical activity. Here, we examined the feasibility of a NF training targeting the DL-PFC and its specificity by assessing the impact of physiological confounds on NF success via short-channel offline correction under different signal filtering conditions. We also explored whether the individual mental strategies affect the NF success. Thirty volunteers participated in a single 15-trial NF session in which they had to increase the oxy-hemoglobin (HbO2) level of their bilateral DL-PFC. We found that 0.01-0.09 Hz band-pass filtering was more suited than the 0.01-0.2 Hz band-pass filter to highlight brain activation restricted to the NF channels in the DL-PFC. Retaining the 10 out of 15 best trials, we found that 18 participants (60%) managed to control their DL-PFC. This number dropped to 13 (43%) with short-channel correction. Half of the participants reported a positive subjective feeling of control, and the "cheering" strategy appeared to be more effective in men (p<0.05). Our results showed successful DL-PFC fNIRS-NF in a single session and highlighted the value of accounting for extra cortical signals, which can profoundly affect the success and specificity of NF training.

Quantification of identifying cognitive impairment using olfactory-stimulated functional near-infrared spectroscopy with machine learning: a post hoc analysis of a diagnostic trial and validation of an external additional trial

BACKGROUND

We aimed to quantify the identification of mild cognitive impairment and/or Alzheimer's disease using olfactory-stimulated functional near-infrared spectroscopy using machine learning through a post hoc analysis of a previous diagnostic trial and an external additional trial.

METHODS

We conducted two independent, patient-level, single-group, diagnostic interventional trials (original and additional trials) involving elderly volunteers (aged > 60 years) with suspected declining cognitive function. All volunteers were assessed by measuring the oxygenation difference in the orbitofrontal cortex using an open-label olfactory-stimulated functional near-infrared spectroscopy approach, medical interview, amyloid positron emission tomography, brain magnetic resonance imaging, Mini-Mental State Examination, and Seoul Neuropsychological Screening Battery.

RESULTS

In total, 97 (original trial) and 36 (additional trial) elderly volunteers with suspected decline in cognitive function met the eligibility criteria. The statistical model reported classification accuracies of 87.3% in patients with mild cognitive impairment and Alzheimer's disease in internal validation (original trial) but 63.9% in external validation (additional trial). The machine learning algorithm achieved 92.5% accuracy with the internal validation data and 82.5% accuracy with the external validation data. For the diagnosis of mild cognitive impairment, machine learning performed better than statistical methods with internal (86.0% versus 85.2%) and external validation data (85.4% versus 68.8%).

INTERPRETATION

In two independent trials, machine learning models using olfactory-stimulated oxygenation differences in the orbitofrontal cortex were superior in diagnosing mild cognitive impairment and Alzheimer's disease compared to classic statistical models. Our results suggest that the machine learning algorithm is stable across different patient groups and increases generalization and reproducibility.

TRIAL REGISTRATION

Clinical Research Information Service (CRiS) of Republic of Korea; CRIS numbers, KCT0006197 and KCT0007589.

An fNIRS investigation of novel expressed emotion stimulations in schizophrenia

Living in high expressed emotion (EE) environments tends to increase the relapse rate in schizophrenia (SZ). At present, the neural substrates responsible for high EE in SZ remain poorly understood. Functional near-infrared spectroscopy (fNIRS) may be of great use to quantitatively assess cortical hemodynamics and elucidate the pathophysiology of psychiatric disorders. In this study, we designed novel low- (positivity and warmth) and high-EE (criticism, negative emotion, and hostility) stimulations, in the form of audio, to investigate cortical hemodynamics. We used fNIRS to measure hemodynamic signals while participants listened to the recorded audio. Healthy controls (HCs, [Formula: see text]) showed increased hemodynamic activation in the major language centers across EE stimulations, with stronger activation in Wernicke's area during the processing of negative emotional language. Compared to HCs, people with SZ ([Formula: see text]) exhibited smaller hemodynamic activation in the major language centers across EE stimulations. In addition, people with SZ showed weaker or insignificant hemodynamic deactivation in the medial prefrontal cortex. Notably, hemodynamic activation in SZ was found to be negatively correlated with the negative syndrome scale score at high EE. Our findings suggest that the neural mechanisms in SZ are altered and disrupted, especially during negative emotional language processing. This supports the feasibility of using the designed EE stimulations to assess people who are vulnerable to high-EE environments, such as SZ. Furthermore, our findings provide preliminary evidence for future research on functional neuroimaging biomarkers for people with psychiatric disorders.

Altered prefrontal activation during the inhibition of eating responses in women with bulimia nervosa

BACKGROUND

The sense of 'loss of control' (LOC), or a feeling of being unable to stop eating or control what or how much one is eating, is the most salient aspect of binge eating. However, the neural alterations that may contribute to this experience and eating behavior remain poorly understood.

METHODS

We used functional near-infrared spectroscopy (fNIRS) to measure activation in the prefrontal cortices of 23 women with bulimia nervosa (BN) and 23 healthy controls (HC) during two tasks: a novel go/no-go task requiring inhibition of eating responses, and a standard go/no-go task requiring inhibition of button-pressing responses.

RESULTS

Women with BN made more commission errors on both tasks. BN subgroups with the most severe LOC eating (n = 12) and those who felt most strongly that they binge ate during the task (n = 12) showed abnormally reduced bilateral ventromedial prefrontal cortex (vmPFC) and right ventrolateral prefrontal cortex (vlPFC) activation associated with eating-response inhibition. In the entire BN sample, lower eating-task activation in right vlPFC was related to more frequent and severe LOC eating, but no group differences in activation were detected on either task when this full sample was compared with HC. BN severity was unrelated to standard-task activation.

CONCLUSIONS

Results provide initial evidence that diminished PFC activation may directly contribute to more severe eating-specific control deficits in BN. Our findings support vmPFC and vlPFC dysfunction as promising treatment targets, and indicate that eating-specific tasks and fNIRS may be useful tools for identifying neural mechanisms underlying dysregulated eating.

Stress estimation by the prefrontal cortex asymmetry: Study on fNIRS signals

BACKGROUND

Functional near-infrared spectroscopy (fNIRS) is a non-invasive technique frequently used to measure the brain hemodynamic activity in applications to evaluate affective disorders and stress. Using two wavelengths of light, it is possible to monitor relative changes in the concentrations of oxyhemoglobin and deoxyhemoglobin. Besides, the spatial asymmetry in the prefrontal cortex activity has been correlated with the brain response to stressful situations.

METHODS

We measured prefrontal cortex activity with a NIRS multi-distance device during a baseline period, under stressful conditions (e.g., social stress), and after a recovery phase. We calculated a laterality index for the contaminated brain signal and for the brain signal where we removed the influence of extracerebral hemodynamic activity by using a short channel.

RESULTS

There was a significant right lateralization during stress when using the contaminated signals, consistent with previous investigations, but this significant difference disappeared using the corrected signals. Indeed, exploration of the susceptibility to contamination of the different channels showed non-homogeneous spatial patterns, which would hint at detection of stress from extracerebral activity from the forehead.

LIMITATIONS

There was no recovery phase between the social and the arithmetic stressor, a cumulative effect was not considered.

CONCLUSIONS

Extracerebral hemodynamic activity provided insights into the pertinence of short channel corrections in fNIRS studies dealing with emotions. It is important to consider this issue in clinical applications including modern monitoring systems based on fNIRS technique to assess emotional states in affective disorders.

Identification of autism spectrum disorder based on functional near-infrared spectroscopy using adaptive spatiotemporal graph convolution network

The accurate diagnosis of autism spectrum disorder (ASD) is of great practical significance in clinical practice. The spontaneous hemodynamic fluctuations were collected by functional near-infrared spectroscopy (fNIRS) from the bilateral frontal and temporal cortices of typically developing (TD) children and children with ASD. Since traditional machine learning and deep learning methods cannot make full use of the potential spatial dependence between variable pairs, and require a long time series to diagnose ASD. Therefore, we use adaptive spatiotemporal graph convolution network (ASGCN) and short time series to classify ASD and TD. To capture spatial and temporal features of fNIRS multivariable time series without the pre-defined graph, we combined the improved adaptive graph convolution network (GCN) and gated recurrent units (GRU). We conducted a series of experiments on the fNIRS dataset, and found that only using 2.1 s short time series could achieve high precision classification, with an accuracy of 95.4%. This suggests that our approach may have the potential to detect pathological signals in autism patients within 2.1 s. In different brain regions, the left frontal lobe has the best classification effect, and the abnormalities occur more frequently in left hemisphere and frontal lobe region. Moreover, we also found that there were correlations between multiple channels, which had different degrees of influence on the classification of ASD. From this, we can also generalize to a wider range, there may be potential correlations between different brain regions. This may help to better understand the cortical mechanism of ASD.

Functional near-infrared spectroscopy is a sensitive marker of neurophysiological deficits on executive function tasks in young adults with a history of child abuse

Previous research has shown the utility of imaging measures of neural activity in identifying deficits in cognitive functioning in individuals with a history of child abuse. The purpose of the present study was to measure differences that may exist between individuals who reported physical, emotional, or sexual abuse as children (n = 37) vs. those who did not (n = 47) using Functional Near Infrared Spectroscopy (fNIRS) during the completion of cognitive tasks of executive function. The results showed a significantly higher rate and number of errors of commission on the Conners CPT test in the child abuse group compared to the control group. The analyses also showed a statistically significant decrease in oxyhemoglobin (oxy-Hb) concentration in the left rostral prefrontal cortex in the child abuse group compared to the no-abuse group during the Wisconsin Card Sorting Test (WCST). A similar, albeit non-significant, trend toward decreased oxy-Hb concentration was observed in the child abuse group in the right dorsolateral prefrontal cortex (dlPFC) on the OSPAN and Connors CPT. The results suggest that the latter group may show subtle neurological deficits that persist into adulthood that may not manifest on traditional measures of cognitive function. These findings have implications for the development of remediation and treatment strategies in this population.

Functional near-infrared spectroscopy is a useful tool for multi-perspective psychobiological study of neurophysiological correlates of parenting behaviour

The quality of the relationship between caregiver and child has long-term effects on the cognitive and socio-emotional development of children. A process involved in human parenting is the bio-behavioural synchrony that occurs between the partners in the relationship during interaction. Through interaction, bio-behavioural synchronicity allows the adaptation of the physiological systems of the parent to those of the child and promotes the positive development and modelling of the child's social brain. The role of bio-behavioural synchrony in building social bonds could be investigated using functional near-infrared spectroscopy (fNIRS). In this paper we have (a) highlighted the importance of the quality of the caregiver-child relationship for the child's cognitive and socio-emotional development, as well as the relevance of infantile stimuli in the activation of parenting behaviour; (b) discussed the tools used in the study of the neurophysiological substrates of the parental response; (c) proposed fNIRS as a particularly suitable tool for the study of parental responses; and (d) underlined the need for a multi-systemic psychobiological approach to understand the mechanisms that regulate caregiver-child interactions and their bio-behavioural synchrony. We propose to adopt a multi-system psychobiological approach to the study of parental behaviour and social interaction.

Personality construct as a biomarker in fibromyalgia: A narrative review from an autonomic rehabilitation perspective

BACKGROUND

The heterogeneity of symptoms and ineffective treatment raise questions about the current diagnostic criteria of fibromyalgia (FM). Misdiagnosis of FM often leads to less than efficacious treatment and poor quality of life.

OBJECTIVE

This article reviews relevant evidence-based literature on personality traits in FM patients with an autonomic dysfunction perspective based on a hierarchical model to explain the utility of considering the personality trait in FM diagnosis.

METHODS

A narrative review of articles concerning chronic pain, FM, and personality traits with respect to autonomic dysfunction in FM was conducted after extensive relevant literature searches.

RESULTS

Reports discussing the predisposing factors, including coping styles, anger, suicide risk, a lack of physical activity and social support, in maintaining persistent pain in FM exist. Relationships between pain duration and severity and personality traits like neuroticism and extraversion have been reported. Coexisting clinical manifestations of FM like sleep disorders, anxiety, and intestinal irritability indicate autonomic dysfunction.

CONCLUSIONS

This article lays out a constructive framework for individualized and personalized medicine for the effective rehabilitation of FM patients. The quest to find a definitive diagnosis of FM should include personality biomarkers that might translate into personalized medicine. An individualistic approach may bank upon artificial intelligence algorithms for both diagnostic as well as prognostic purposes in FM.

Atypical frontotemporal cortical activity in first-episode adolescent-onset schizophrenia during verbal fluency task: A functional near-infrared spectroscopy study

Background

Frontotemporal cortex dysfunction has been found to be associated with cognitive impairment in patients with schizophrenia (SCZ). In patients with adolescent-onset SCZ, a more serious type of SCZ with poorer functional outcome, cognitive impairment appeared to occur at an early stage of the disease. However, the characteristics of frontotemporal cortex involvement in adolescent patients with cognitive impairment are still unclear. In the present study, we aimed to illustrate the frontotemporal hemodynamic response during a cognitive task in adolescents with first-episode SCZ.

Methods

Adolescents with first-episode SCZ who were aged 12-17 and demographically matched healthy controls (HCs) were recruited. We used a 48-channel functional near-infrared spectroscopy (fNIRS) system to record the concentration of oxygenated hemoglobin (oxy-Hb) in the participants' frontotemporal area during a verbal fluency task (VFT) and analyzed its correlation with clinical characteristics.

Results

Data from 36 adolescents with SCZ and 38 HCs were included in the analyses. Significant differences were found between patients with SCZ and HCs in 24 channels, mainly covering the dorsolateral prefrontal cortex, superior and middle temporal gyrus and frontopolar area. Adolescents with SCZ showed no increase of oxy-Hb concentration in most channels, while the VFT performance was comparable between the two groups. In SCZ, the intensity of activation was not associated with the severity of symptoms. Finally, receiver operating characteristic analysis indicated that the changes in oxy-Hb concentration could help distinguish the two groups.

Conclusion

Adolescents with first-episode SCZ showed atypical cortical activity in the frontotemporal area during the VFT, and fNIRS features might be more sensitive indicators in cognitive assessment, indicating that the characteristic hemodynamic response pattern might be potential imaging biomarkers for this population.

Hotspots and trends in fNIRS disease research: A bibliometric analysis

Objective

To summarize the general information and hotspots of functional near-infrared spectroscopy (fNIRS)-based clinical disease research over the past 10 years and provide some references for future research.

Methods

The related literature published between 1 January 2011 and 31 January 2022 was retrieved from the Web of Science core database (WoS). Bibliometric visualization analysis of countries/regions, institutions, authors, journals, keywords and references were conducted by using CiteSpace 6.1.R3.

Results

A total of 467 articles were included, and the annual number of articles published over nearly a decade showed an upward trend year-by-year. These articles mainly come from 39 countries/regions and 280 institutions. The representative country and institution were the USA and the University of Tubingen. We identified 266 authors, among which Andreas J Fallgatter and Ann-Christine Ehlis were the influential authors. Neuroimage was the most co-cited journal. The major topics in fNIRS disease research included activation, prefrontal cortex, working memory, cortex, and functional magnetic resonance imaging (fMRI). In recent years, the Frontier topics were executive function, functional connectivity, performance, diagnosis, Alzheimer's disease, children, and adolescents. Based on the burst of co-cited references, gait research has received much attention.

Conclusion

This study conducted a comprehensive, objective, and visual analysis of publications, and revealed the status of relevant studies, hot topics, and trends concerning fNIRS disease research from 2011 to 2022. It is hoped that this work would help researchers to identify new perspectives on potential collaborators, important topics, and research Frontiers.

The fNIRS evaluation of frontal and temporal lobe cortical activation in Chinese first-episode medication-naïve and recurrent depression during a verbal fluency task

Background

Functional near-infrared spectroscopy (fNIRS) identifies neurophysiological differences between psychiatric disorders by assessing cortical hemodynamic function. Few trials have studied differences in brain functional activity between first-episode medication-naïve depression patients (FMD) and recurrent major depression (RMD). We aimed to determine the differences between FMD and RMD in oxygenated hemoglobin concentration ([oxy-Hb]), and to investigate the correlation between frontotemporal cortex activation and clinical symptoms.

Methods

We recruited 40 patients with FMD, 53 with RMD, and 38 healthy controls (HCs) from May 2021 to April 2022. Symptom severity was assessed with the 24-item Hamilton Depression Rating Scale (HAM-D) and the Hamilton Anxiety Rating Scale (HAM-A). A 52-channel fNIRS measured changes in [oxy-Hb] during VFT performance.

Results

Both patient groups performed poorly during the VFT task compared with HC (FDR p < 0.05), but there was no significant difference between the two patient groups. Analysis of variance showed that mean [oxy-Hb] activation was lower in both the frontal and temporal lobes in the MDD group compared with HCs (FDR p < 0.05). Additionally, patients with RMD had a significantly lower hemodynamic response in the right dorsolateral prefrontal cortex (DLPFC) and dorsal frontal pole cortex (DFPC) than patients with FMD (FDR p < 0.05). No significant correlation was found between changes in mean [oxy-Hb] and either medical history or clinical symptoms (FDR p < 0.05).

Conclusion

The presence of different neurofunctional activity in some of the same brain regions in FMD and RMD patients implied a link between the level of complexity activation in frontal regions and the stage of MDD. Cognitive impairment may already be present at the beginning of an MDD episode.

Clinical trial registration

www.chictr.org.cn, identifier ChiCTR2100043432.

Current opinions on the present and future use of functional near-infrared spectroscopy in psychiatry

Functional near-infrared spectroscopy (fNIRS) is an optical imaging technique for assessing human brain activity by noninvasively measuring the fluctuation of cerebral oxygenated- and deoxygenated-hemoglobin concentrations associated with neuronal activity. Owing to its superior mobility, low cost, and good tolerance for motion, the past few decades have witnessed a rapid increase in the research and clinical use of fNIRS in a variety of psychiatric disorders. In this perspective article, we first briefly summarize the state-of-the-art concerning fNIRS research in psychiatry. In particular, we highlight the diverse applications of fNIRS in psychiatric research, the advanced development of fNIRS instruments, and novel fNIRS study designs for exploring brain activity associated with psychiatric disorders. We then discuss some of the open challenges and share our perspectives on the future of fNIRS in psychiatric research and clinical practice. We conclude that fNIRS holds promise for becoming a useful tool in clinical psychiatric settings with respect to developing closed-loop systems and improving individualized treatments and diagnostics.

Novel diagnostic tools for identifying cognitive impairment using olfactory-stimulated functional near-infrared spectroscopy: patient-level, single-group, diagnostic trial

Introduction

Basic studies suggest that olfactory dysfunction and functional near-infrared spectroscopy (fNIRS) can be used as tools for the diagnosis of mild cognitive impairment (MCI); however, real-world evidence is lacking. We investigated the potential diagnostic efficacy of olfactory-stimulated fNIRS for early detection of MCI and/or Alzheimer disease (AD).

Methods

We conducted a patient-level, single-group, diagnostic interventional trial involving elderly volunteers (age >60 years) suspected of declining cognitive function. Patients received open-label olfactory-stimulated fNIRS for measurement of oxygenation difference in the orbitofrontal cortex. All participants underwent amyloid PET, MRI, Mini-Mental State Examination (MMSE), and Seoul Neuropsychological Screening Battery (SNSB).

Results

Of 97 subjects, 28 (28.9%) were cognitively normal, 32 (33.0%) had preclinical AD, 21 (21.6%) had MCI, and 16 (16.5%) had AD. Olfactory-stimulated oxygenation differences in the orbitofrontal cortex were associated with cognitive impairment; the association was more pronounced with cognitive severity. Olfactory-stimulated oxygenation difference was associated with MMSE (adjusted β [aβ] 1.001; 95% CI 0.540−1.463), SNSB language and related function (aβ, 1.218; 95% CI, 0.020−2.417), SNSB memory (aβ, 1.963; 95% CI, 0.841−3.084), SNSB frontal/executive function (aβ, 1.715; 95% CI, 0.401−3.029) scores, standard uptake value ratio from amyloid PET (aβ, −10.083; 95% CI, −19.063 to −1.103), and hippocampal volume from MRI (aβ, 0.002; 95% CI, 0.001−0.004). Olfactory-stimulated oxygenation difference in the orbitofrontal cortex was superior in diagnosing MCI and AD (AUC, 0.909; 95% CI, 0.848−0.971), compared to amyloid PET (AUC, 0.793; 95% CI, 0.694−0.893) or MRI (AUC, 0.758; 95% CI, 0.644−0.871).

Discussion

Our trial showed that olfactory-stimulated oxygenation differences in the orbitofrontal cortex detected by fNIRS were associated with cognitive impairment and cognitive-related objectives. This novel approach may be a potential diagnostic tool for patients with MCI and/or AD.

Trial registration

CRIS number, KCT0006197.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-00978-w.

Cerebral oxygen saturation in the prefrontal cortex during electroconvulsive therapy and its relation with the postictal reorientation time

The therapeutic effect of Electroconvulsive Therapy (ECT) has been attributed to generalised seizure. Although patients are well oxygenated prior to and during treatment, critics have associated ECT with brain tissue hypoxemia. In this study, the regional oxygen saturation (rSO₂) was measured continuously during ECT in the prefrontal cortex (PFC) of both hemispheres using 2-channel Near Infrared Spectroscopy (NIRS). Additionally, the postictal reorientation time (PRT) was determined and related to the rSO₂ course. We evaluated 72 ECT treatments in 22 adult patients who were treated for a therapy-resistant depressive syndrome. The therapy was performed according to our standard clinical procedures deploying right unilateral (RUL) and left anterior versus right temporal (LART) electrode placements. According to our results, the rSO₂ courses showed an increase during hyperventilation, a sharp drop immediately after the stimulus, and a long recovery period with values far exceeding the baseline. In 55,6% of treatments the rSO₂ course stayed above the baseline. In the others, the drop fell below it for an average of 12.6 s. According to a cardio surgical standard no signs of hypoxemia occurred during ECT treatments. The rSO₂ drop at seizure onset was the only parameter of the oxygen course related to the PRT in the multivariate analysis and might therefore be a characteristic feature of the seizure. It could reflect its physiological intensity and thereby be involved in the mechanism of action of ECT. NIRS seems to be an interesting non-invasive tool for monitoring and studying ECT.

Hemodynamic analysis of the frontal cortex using multi-task fNIRS in major depressive disorder

BACKGROUND

Appropriate task selection is the key to fNIRS-based major depressive disorder (MDD) diagnosis and treatment; however, there exists no unified rule for task selection, which limits its clinical application.

METHODS

Four tasks were employed to investigate the hemodynamic characteristics of MDD during motor, emotional, cognitive, and combinational tasks. A total of 69 subjects were studied: 50 with MDD and 19 healthy controls. The integral value of oxy-hemoglobin and the asymmetric characteristics of the bilateral frontal lobe were used to demonstrate the hemodynamic changes in MDD during different tasks. A detailed analysis and comparison among different tasks were conducted.

RESULTS

Compared with deoxy-hemoglobin (deoxy-Hb), oxy-Hb was more significant to differentiate between MDD subjects and healthy controls. In subjects with MDD, lower activation of the frontal lobe and smaller integral values of oxy-Hb were observed. In most task paradigms, MDD subjects and healthy controls exhibited diametrically opposite left-right frontal asymmetry. For the integral value of oxy-Hb and the asymmetric characteristics of the bilateral frontal lobe, the differences between MDD subjects and healthy controls under the combinational task were more significant than that under the single tasks.

LIMITATIONS

Brain fatigue patterns over time and their effect on the hemodynamic analysis of MDD should be studied further.

CONCLUSIONS

The difference in hemodynamic characteristics between MDD subjects and healthy controls is closely related to the choice of task, and the combinational task showed better discrimination than the single tasks. It provides guidance for the appropriate task design for MDD in clinics.

Four-Class Classification of Neuropsychiatric Disorders by Use of Functional Near-Infrared Spectroscopy Derived Biomarkers

Diagnosis of most neuropsychiatric disorders relies on subjective measures, which makes the reliability of final clinical decisions questionable. The aim of this study was to propose a machine learning-based classification approach for objective diagnosis of three disorders of neuropsychiatric or neurological origin with functional near-infrared spectroscopy (fNIRS) derived biomarkers. Thirteen healthy adolescents and sixty-seven patients who were clinically diagnosed with migraine, obsessive compulsive disorder, or schizophrenia performed a Stroop task, while prefrontal cortex hemodynamics were monitored with fNIRS. Hemodynamic and cognitive features were extracted for training three supervised learning algorithms (naïve bayes (NB), linear discriminant analysis (LDA), and support vector machines (SVM)). The performance of each algorithm in correctly predicting the class of each participant across the four classes was tested with ten runs of a ten-fold cross-validation procedure. All algorithms achieved four-class classification performances with accuracies above 81% and specificities above 94%. SVM had the highest performance in terms of accuracy (85.1 ± 1.77%), sensitivity (84 ± 1.7%), specificity (95 ± 0.5%), precision (86 ± 1.6%), and F1-score (85 ± 1.7%). fNIRS-derived features have no subjective report bias when used for automated classification purposes. The presented methodology might have significant potential for assisting in the objective diagnosis of neuropsychiatric disorders associated with frontal lobe dysfunction.

Effects of aging on functional connectivity in a neurodegenerative risk cohort: resting state versus task measurement using near-infrared spectroscopy

Changes in functional brain organization are considered to be particularly sensitive to age-related effects and may precede structural cognitive decline. Recent research focuses on aging processes determined by resting state (RS) functional connectivity (FC), but little is known about differences in FC during RS and cognitive task conditions in elderly participants. The purpose of this study is to compare FC within and between the cognitive control (CCN) and dorsal attention network (DAN) at RS and during a cognitive task using functional near-infrared spectroscopy (fNIRS). In a matched, neurodegenerative high-risk cohort comprising early (n = 98; 50–65 y) and late (n = 98; 65–85 y) elder subjects, FC was measured at RS and during performance of the Trail Making Test (TMT) via fNIRS. Both, under RS and task conditions our results revealed a main effect for age, characterized by reduced FC for late elder subjects within the left inferior frontal gyrus. During performance of the TMT, negative correlations of age and FC were confirmed in various regions of the CCN and DAN. For the whole sample, FC of within-region connections was elevated, while FC between regions was decreased at RS. The results confirm a reorganization of functional brain connectivity with increasing age and cognitive demands.

An Approach to Neuroimaging Interpersonal Interactions in Mental Health Interventions

BACKGROUND

Conventional paradigms in clinical neuroscience tend to be constrained in terms of ecological validity, raising several challenges to studying the mechanisms mediating treatments and outcomes in clinical settings. Addressing these issues requires real-world neuroimaging techniques that are capable of continuously collecting data during free-flowing interpersonal interactions and that allow for experimental designs that are representative of the clinical situations in which they occur.

METHODS

In this work, we developed a paradigm that fractionates the major components of human-to-human verbal interactions occurring in clinical situations and used functional near-infrared spectroscopy to assess the brain systems underlying clinician-client discourse (N = 30).

RESULTS

Cross-brain neural coupling between people was significantly greater during clinical interactions compared with everyday life verbal communication, particularly between the prefrontal cortex (e.g., inferior frontal gyrus) and inferior parietal lobule (e.g., supramarginal gyrus). The clinical tasks revealed extensive increases in activity across the prefrontal cortex, especially in the rostral prefrontal cortex (area 10), during periods in which participants were required to silently reason about the dysfunctional cognitions of the other person.

CONCLUSIONS

This work demonstrates a novel experimental approach to investigating the neural underpinnings of interpersonal interactions that typically occur in clinical settings, and its findings support the idea that particular prefrontal systems might be critical to cultivating mental health.

A Decrease in Hemodynamic Response in the Right Postcentral Cortex Is Associated With Treatment-Resistant Auditory Verbal Hallucinations in Schizophrenia: An NIRS Study

Background

Treatment-resistant auditory verbal hallucinations (TRAVHs) might cause an increased risk of violence, suicide, and hospitalization in patients with schizophrenia (SCZ). Although neuroimaging studies have identified the neural correlation to the symptom of AVH, functional brain activity that correlates particularly in patients with TRAVH remains limited. Functional near-infrared spectroscopy (fNIRS) is a portable and suitable measurement, particularly in exploring brain activation during related tasks. Hence, our researchers aimed to explore the differences in the cerebral hemodynamic function in SCZ-TRAVH, patients with schizophrenia without AVH (SCZ-nAVH), and healthy controls (HCs), to examine neural abnormalities associated more specifically with TRAVH.

Methods

A 52-channel functional near-infrared spectroscopy system was used to monitor hemodynamic changes in patients with SCZ-TRAVH (n = 38), patients with SCZ-nAVH (n = 35), and HC (n = 30) during a verbal fluency task (VFT). VFT performance, clinical history, and symptom severity were also noted. The original fNIRS data were analyzed using MATLAB to obtain the β values (the brain cortical activity response during the VFT task period); these were used to calculate Δβ (VFT β minus baseline β), which represents the degree of change in oxygenated hemoglobin caused by VFT task.

Result

Our results showed that there were significant differences in Δβ values among the three groups at 26 channels (ch4, ch13-15, 18, 22, ch25–29, 32, ch35–39, ch43–51, F = 1.70 to 19.10, p < 0.043, FDR-corrected) distributed over the prefrontal–temporal cortical regions. The further pairwise comparisons showed that the Δβ values of 24 channels (ch13–15, 18, 22, 25, ch26–29, ch35–39, ch43–49, ch50–51) were significantly lower in the SCZ group (SCZ-TRAVH and/or SCZ-nAVH) than in the HC group (p < 0.026, FDR-corrected). Additionally, the abnormal activation in the ch22 of right postcentral gyrus was correlated, in turn, with severity of TRAVH.

Conclusion

Our findings indicate that specific regions of the prefrontal cortex may be associated with TRAVH, which may have implications for early intervention for psychosis.

Frontal cortical activation during emotional and non-emotional verbal fluency tests

There has been growing recognition of the utility of combining the verbal fluency test and functional near-infrared spectroscopy (fNIRS) to assess brain functioning and to screen for psychiatric disorders. Recently, an emotional analogue of the semantic fluency test (SFT) has been developed that taps partly different processes from conventional verbal fluency tests. Nevertheless, neural processing during the emotional SFT remains elusive. Here, fNIRS was used to compare frontal cortical activation during emotional and non-emotional SFTs. The goal was to determine whether the emotional SFT activated overlapping yet distinct frontal cortical regions compared with the conventional, non-emotional SFT. Forty-three healthy young adults performed the emotional and non-emotional SFTs while hemodynamic changes in the bilateral frontopolar, dorsomedial, dorsolateral, ventrolateral, and posterolateral frontal cortices were measured by fNIRS. There were significant increases in oxyhemoglobin concentration and significant decreases in deoxyhemoglobin concentration (i.e., activation) in frontopolar, dorsolateral, and ventrolateral frontal regions during both the non-emotional and emotional SFTs. Also, complementary analyses conducted on changes in the two chromophores using classical and Bayesian hypothesis testing suggested that comparable frontal cortical regions were activated while performing the two tests. This similarity in activation occurred in a context where non-emotional and emotional SFT performances exhibited differential relationships with the overall level of negative mood symptoms. In conclusion, frontal cortical activation during the emotional SFT is similar to that during the conventional, non-emotional SFT. Given that there is evidence for discriminant validity for the emotional SFT, the neural mechanisms underlying the uniqueness of this test warrant further investigation.

Prefrontal Activation During Effortful Processing Differentiates Memory Abilities in Adults with Memory Complaints

Background: Identifying individuals at increased risks for developing Alzheimer’s disease (AD) is crucial for early intervention. Memory complaints are associated with brain abnormalities characteristic of AD in cognitively normal older people. However, the utility of memory complaints for predicting mild cognitive impairment (MCI) or AD onset remains controversial, likely due to the heterogeneous nature of this construct. Objective: We investigated whether prefrontal oxygenation changes measured by functional near-infrared spectroscopy (fNIRS) during an arduous cognitive task, previously shown to be associated with the AD syndrome, could differentiate memory abilities among individuals with memory complaints. Episodic memory performance was adopted as a proxy for MCI/AD risks since it has been shown to predict AD progression across stages. Methods: Thirty-six adults self-reporting memory complaints in the absence of memory impairment completed a verbal list learning test and underwent a digit n-back paradigm with an easy (0-back) and a difficult (2-back) condition. K-means clustering was applied to empirically derive memory complaint subgroups based on fNIRS-based prefrontal oxygenation changes during the effortful 2-back task. Results: Cluster analysis revealed two subgroups characterized by high (n = 12) and low (n = 24) bilateral prefrontal activation during the 2-back but not a 0-back task. The low activation group was significantly less accurate across the n-back task and recalled significantly fewer words on the verbal memory test compared to the high activation group. Conclusion: fNIRS may have the potential to differentiate verbal memory abilities in individuals with self-reported memory complaints.

Trait rumination and social anxiety separately influence stress-induced rumination and hemodynamic responses

We aimed to investigate stress-reactive rumination in response to social stress and its association with social anxiety and trait rumination. From previous investigations we know that people with a certain vulnerability to rumination show increased stress-reactive rumination. However, up to date the possible influence of social anxiety on this relationship is still unclear. Therefore, we reanalyzed the data of two of our previous studies assessing healthy low and high trait ruminators and depressed patients performing the Trier Social Stress Test (TSST). We measured cortical oxygenation using functional Near-Infrared Spectroscopy (fNIRS) as well as different behavioral outcome measures (subjective stress levels, negative affect, state rumination). On a behavioral level, we found an influence of both, social anxiety and trait rumination, on state rumination, even when correcting for the other factor, respectively, implying two potentially independent factors of influence. On a neural level, we observed reduced activation in brain regions of the cognitive control network (CCN) for higher social anxiety and trait rumination, which might be a result of reduced cognitive and attentional control. Results indicate a specific role of social anxiety, at least on a behavioral level, and therefore implicate a crucial factor to be considered in the treatment of depression.

Characteristics of frontal activity relevant to cognitive function in bipolar depression: an fNIRS study

Memory shortness, verbal influence, and disturbed attention are a few of the cognitive dysfunctions reported by individuals of bipolar disorder in depression phase (BD-D). As neuroimaging modalities can investigate such responses, therefore neuroimaging methods can be used to assist the diagnosis of bipolar disorder (BD). Functional near-infrared spectroscopy (fNIRS) is a neural imaging method that is proved to be prominent in the diagnosis of psychiatric disorders. It is the desired method because of its feasible setup, high resolution in time, and its partial resistance to head movements. This study aims to investigate the brain activity in subjects of BD-D during cognitive tasks compared to the healthy controls. A decreased activation level is expected in individuals of BD-D as compared to the healthy controls. This study aims to find new methods and experimental paradigms to assist in the diagnosis of bipolar depression. Participants of BD-D and healthy controls (HC) performed four cognitive tasks including verbal fluency task (VFT), symbol working memory task (symbol check), attention task (spotter) and multiple cognitive task (code break). fNIRS was used to measure levels of oxy-hemoglobin (HbO) representing the brain activity. The generalized linear model (GLM) method was used to estimate the hemodynamic response related to the task. The wavelet transform coherence (WTC) method was used to calculate the intra-hemispheric functional connectivity. We also analyzed the correlation between hemodynamic response and scores of psychiatric disorders. Results showed decreased levels of HbO in BD-D groups compared to the HC, indicating lower activity, during the tasks except for spotter. The difference between BD-D and HC was significant during VFT, symbol check and code break. Group difference during symbol working memory was significant both in brain activity and connectivity. Meanwhile, the individual brain activity during working memory is more related to the illness degree. Lower activity in BD-D reflects unspecific dysfunctions. Compared with other cognitive tasks, the single-trial symbol-check task may be more suitable to help the diagnosis of bipolar depression.

MOCA: a systematic toolbox for designing and assessing modular functional near-infrared brain imaging probes

Significance

The expansion of functional near-infrared spectroscopy (fNIRS) systems toward broader utilities has led to the emergence of modular fNIRS systems composed of repeating optical source/detector modules. Compared to conventional fNIRS systems, modular fNIRS systems are more compact and flexible, making wearable and long-term monitoring possible. However, the large number of design parameters makes understanding their impact on a probe's performance a daunting task.

Aim

We aim to create a systematic software platform to facilitate the design, characterization, and comparison of modular fNIRS probes.

Approach

Our software-modular optode configuration analyzer (MOCA)-implements semi-automatic algorithms that assist in tessellating user-specified regions-of-interest, in interconnecting modules of various shapes, and in quantitatively comparing probe performance using metrics, such as spatial channel distributions and average brain sensitivity of the resulting probes. There is also support for limited parameter sweeping capabilities.

Results

Through several examples, we show that users can use MOCA to design and optimize modular fNIRS probes, study trade-offs between several module shapes, improve brain sensitivity in probes via module re-orientation, and enhance probe performance via adjusting module spatial layouts.

Conclusion

Despite its simplicity, our modular probe design platform offers a framework to describe and quantitatively assess probes made by modules, opening a new door for the growing fNIRS user community to approach the challenging problem of module- and probe-parameter selection and fine-tuning.

Functional near-infrared spectroscopy as a potential objective evaluation technique in neurocognitive disorders after traumatic brain injury

Most patients with neurocognitive disorders after traumatic brain injury (TBI) show executive dysfunction, in which the pre-frontal cortex (PFC) plays an important role. However, less objective evaluation technique could be used to assess the executive dysfunction in these patients. Functional near-infrared spectroscopy (fNIRS), which is a non-invasive technique, has been widely used in the study of psychiatric disorders, cognitive dysfunction, etc. The present study aimed to explore whether fNIRS could be a technique to assess the damage degree of executive function in patients with neurocognitive disorders after TBI by using the Stroop and N-back tasks in PFC areas. We enrolled 37 patients with neurocognitive disorders after TBI and 60 healthy controls. A 22-channel fNIRS device was used to record HbO during Stroop, 1-back and 2-back tasks. The results showed that patients made significantly more errors and had longer response times than healthy controls. There were statistically significant differences in HbO level variation in bilateral frontopolar, bilateral inferior frontal gyrus and left middle temporal gyrus during Stroop color word consistency tasks and in left frontopolar during Stroop color word inconsistency tasks. During 2-back tasks, there were also statistically significant differences in HbO level variation in bilateral frontopolar, bilateral inferior frontal gyrus, bilateral dorsolateral pre-frontal cortex. According to brain activation maps, the patients exhibited lower but more widespread activation during the 2-back and Stroop color word consistency tasks. The fNIRS could identify executive dysfunction in patients with neurocognitive disorders after TBI by detecting HbO levels, which suggested that fNIRS could be a potential objective evaluation technique in neurocognitive disorders after TBI.

Functional near-infrared spectroscopy during the verbal fluency task of English-Speaking adults with mood disorders: A preliminary study

Functional near-infrared spectroscopy (fNIRS) provides a direct and objective assessment of cerebral cortex function. It may be used to determine neurophysiological differences between psychiatric disorders with overlapping symptoms, such as major depressive disorder (MDD) and bipolar disorder (BD). Therefore, this preliminary study aimed to compare fNIRS signals during the verbal fluency task (VFT) of English-speaking healthy controls (HC), patients with MDD and patients with BD. Fifteen HCs, 15 patients with MDD and 15 patients with BD were recruited. Groups were matched for age, gender, ethnicity and education. Relative oxy-haemoglobin and deoxy-haemoglobin changes in the frontotemporal cortex was monitored with a 52-channel fNIRS system. Integral values of the frontal and temporal regions were derived as a measure cortical haemodynamic response magnitude. Both patient groups had lower frontal and temporal region integral values than HCs, and patients with MDD had lower frontal region integral value than patients with BD. Moreover, patients could be differentiated from HCs using the frontal and temporal integral values, and patient groups could be differentiated using the frontal region integral values. VFT performance, clinical history and symptom severity were not associated with integral values. These results suggest that prefrontal cortex haemodynamic dysfunction occurs in mood disorders, and it is more extensive in MDD than BD. The fNIRS-VFT paradigm may be a potential tool for differentiating MDD from BD in clinical settings, and these findings need to be verified in a larger sample of English-speaking patients with mood disorders.

Prefrontal cortex alterations in major depressive disorder, generalized anxiety disorder and their comorbidity during a verbal fluency task assessed by multi-channel near-infrared spectroscopy

Major depressive disorder (MDD) and generalized anxiety disorder (GAD) are frequently comorbid with each other, and both associated with substantial cognitive impairments; however, it is still unclear whether their impairments are neurobiologically similar or distinct. This study aims to investigate the cognitive functions of the prefrontal cortex (PFC) in patients with MDD and GAD during the verbal fluency task (VFT) using functional near-infrared spectroscopy (fNIRS). Fifty-two patients with MDD, fifty-one patients with GAD, fifty-two patients with the comorbidity of MDD and GAD (CMG), and forty-seven healthy controls (HC) participated in the study. Significant hypoactivation in the left ventrolateral and the left dorsolateral PFC was common in all patient groups when compared to HCs, suggesting a shared etiology. Furthermore,  MDD patients showed significant hypoactivation at the right frontal pole cortex (FPoC) when compared to HCs and significant hypoactivation at the middle FPoC when compared to the CMG patients. Our work is the first fNIRS study to reveal the shared and unique neurobiological profiles of MDD, GAD and their comorbidity under the same standard experimentation condition, suggesting fNIRS holds promise as an adjutant to assist clinical diagnosis.