Personalized functional imaging using fMRI is a paradigm shift in neuroscience but demands extensive data per participant. Functional near-infrared spectroscopy (fNIRS) is a cost-effective alternative, yet its ability to capture individual-specific functional architecture with adequate precision remains unproven. To assess fNIRS for personalized mapping, we charted functional organization in nine individuals using task-based and resting-state fNIRS alongside fMRI. Each participant contributed 11.5 hours of imaging data, including 4 hours of resting-state and 4.2 hours of task-based (motor, working memory, language) fNIRS data, and 3.3 hours of matched fMRI for cross-validation. Results show fNIRS reliably identifies individual-specific resting-state networks, requiring only 20 minutes of data for stable characterization. Additionally, fNIRS captures subject-specfic activation patterns in sensorimotor and higher-order domains, including atypical right-lateralized language dominance. These personalized fNIRS profiles align strongly with fMRI, offering comparable reliability at far lower cost. fNIRS proves a reliable, scalable, and cost-efficient tool for personalized brain mapping.

BACKGROUND:Excessive exposure to sedentary behavior (SB) is associated with cognitive decline and impaired brain health; however, the neurobiological mechanisms underlying this relationship remain unclear. Functional near-infrared spectroscopy (fNIRS) enables real-time monitoring of cerebral hemodynamics in naturalistic settings and offers unique technical advantages for understanding the effects of SB on brain health. Notably, methodological standardization specific to SB research is lacking, limiting cross-study comparisons and evidence synthesis despite established general fNIRS best practices. METHODS:Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically searched PubMed, Scopus, Web of Science, and PsycINFO through February 2026 for studies using fNIRS to assess SB's effects on brain function. Two independent reviewers conducted study selection, data extraction, and bias risk assessment. We systematically extracted and analyzed instrumentation specifications, spatial positioning, data processing pipelines, statistical methods, and quality control measures to identify methodological variations and best practice patterns in current research. RESULTS:From 36,477 initial records, 43 studies encompassing 2751 participants were included. Study types comprised acute (25 studies) and chronic interventions (8 studies) manipulating or monitoring SB patterns as well as cross-sectional studies (10 studies) analyzing the association between SB patterns and fNIRS-related parameters. Substantial heterogeneity was evident for specific methodological aspects, such as the use of diverse fNIRS systems and sampling rates (e.g., spanning 1.81-50.00 Hz), whereas others such as source-detector separation (i.e., 3.0 cm) were relatively homogenous across studies. Critical methodological issues included inadequate reporting of spatial registration and data quality control procedures, inconsistent implementation of multiple comparison corrections, and neglected monitoring of relevant environmental factors and physiological confounds. CONCLUSION:This review provides the first SB-specific standardized methodological framework for fNIRS applications, building on established fNIRS best practices and extending them to address unique challenges of SB research, encompassing 6 core domains: hardware configuration, extended monitoring protocols, data processing, statistical analysis, quality assessment, and SB-specific reporting. Recommendations are systematically classified by evidence level, distinguishing minimum reporting standards applicable across all laboratories from best practices and aspirational approaches for well-resourced settings. Minimum recommendations include reporting optode geometry and placement with sufficient detail for replication and, where feasible, using short-separation regression (or a clearly justified alternative) to mitigate systemic physiological confounds. These recommendations aim to enhance methodological rigor, promote cross-study comparability, and support the long-term goal of identifying SB-related neurobiological biomarkers.

BACKGROUND:Transcranial photobiomodulation (tPBM), as a novel non-invasive neurostimulation technique, has shown the compelling potential for improving cognitive function in aging population. However, the potential mechanism remains unclear. Neuroimaging studies have found that tPBM-induced physiological changes exist in both targeted and non-targeted brain areas, suggesting the necessity of understanding the modulation mechanism from the perspective of the whole brain level. OBJECTIVE:This randomized, single-blind, sham-controlled crossover study aimed to investigate the hypothesis that tPBM improved working memory in healthy older adults through the mechanism of optimizing the properties of the resting-state functional brain networks. METHODS:A total of 55 right-handed healthy older adults were randomly assigned to sham tPBM session group or active tPBM session group. After a washout interval, they were assigned to the opposite intervention session. Each session included the following: active or sham tPBM application with a 1064-nm laser to the left forehead; before and after, resting-state functional near-infrared spectroscopy (fNIRS) measurements; and the digital n-back task. Differences in accuracy and reaction time of the n-back task, and changes in functional connectivity and graph metrics of the brain networks were investigated and compared between the active and sham tPBM sessions. In addition, correlations between tPBM-induced changes in functional brain networks, and the n-back task were examined. RESULTS:The results showed that compared with the sham tPBM session, the accuracy and reaction time during 3-back task significantly improved in the active tPBM session. In addition, the global efficiency, local efficiency, nodal efficiency, and functional connectivity significantly increased in the active tPBM session, particularly in the frontoparietal areas. Importantly, the altered 3-back accuracy was positively correlated with the changes of functional connectivity and nodal efficiency mainly in left prefrontal cortex in those who had increased 3-back accuracy in the active tPBM session. CONCLUSION:This study suggests that tPBM may serve as an effective tool to improve working memory in older adults through the modulation of resting-state functional brain network properties. Investigations in large-scale samples are needed to further validate the findings of this study.

Auditory exposure plays a crucial role in shaping brain development, but little is known about whether and how an initial lack of auditory exposure might disrupt the development of functional network lateralization. We addressed this issue by acquiring functional near-infrared spectroscopy data from infants aged 3 to 9 months with congenital sensorineural hearing loss (SNHL). The SNHL infants showed efficient small-world characteristics within each hemisphere. However, unlike typically developing controls, who showed an age-related leftward lateralization of network efficiencies, SNHL infants did not exhibit the emergence of hemispheric asymmetry. Intriguingly, lateralization of frontal efficiency was preserved in SNHL infants with mild hearing loss but declined significantly with increasing severity of hearing impairment. These findings suggest that even SNHL infants with some residual hearing experience disruption in the development of functional lateralization. This underscores the importance of providing early auditory access to SNHL infants to support robust functional integration during early development.

Significance:A shared understanding of terminology is essential for clear scientific communication and minimizing misconceptions. This is particularly challenging in rapidly expanding, interdisciplinary domains that utilize functional near-infrared spectroscopy (fNIRS), where researchers come from diverse backgrounds and apply their expertise in fields such as engineering, neuroscience, and psychology. Aim:The fNIRS Glossary Project was established to develop a community-sourced glossary covering key fNIRS terms, including those related to the continuous-wave (CW), frequency-domain (FD), and time-domain (TD) NIRS techniques. Approach:The glossary was collaboratively developed by a diverse group of 76 fNIRS researchers, representing a wide range of career stages (from PhD students to experts) and disciplines. This collaborative process, structured across five phases, ensured the glossary's depth and comprehensiveness. Results:The glossary features over 300 terms categorized into six key domains: analysis, experimental design, hardware, neuroscience, mathematics, and physics. It also includes abbreviations, symbols, synonyms, references, alternative definitions, and figures where relevant. Conclusions:The fNIRS glossary provides a community-sourced resource that facilitates education and effective scientific communication within the fNIRS community and related fields. By lowering barriers to learning and engaging with fNIRS, the glossary is poised to benefit a broad spectrum of researchers, including those with limited access to educational resources.

Background: Working memory (WM) impairments and inattention symptoms are prevalent among adults with attention-deficit/hyperactivity disorder (ADHD). Transcranial photobiomodulation (tPBM) is a promising brain stimulation technique that may enhance cognitive function among adults with ADHD. Objectives: We aimed to explore the effects of tPBM on improving N-back WM and Continuous Performance Test-Identical Pairs (CPT-IP) attention tasks in adults with ADHD, as well as its baseline predictive factors. Methods: Forty-eight adults with ADHD underwent a 7-day tPBM intervention (720 s daily, 1064-nm wavelength, 250 mW/cm2 irradiance). Participants completed the N-back (1-back, 2-back, 3-back) WM, and CPT-IP (cpt-2, cpt-3, cpt-4) attention tasks at baseline (T1), after the first (T2), and seventh (T3) interventions, and during four weekly follow-ups (T4-T7). Safety was assessed using the Treatment Emergent Symptom Scale (TESS). Results: The participants showed significant improvements in the 2-back, 3-back, cpt-3, and cpt-4 tasks (all p < 0.001), with peak effect sizes observed at 2-3 weeks post-intervention (Cohen's d = 0.84-1.26). Lower baseline performance predicted greater improvement. The intervention was well-tolerated; three (6.3%) participants reported mild adverse events (TESS scores ≤2), all of which resolved spontaneously. Conclusions: tPBM is effective and well-tolerated for improving WM and attention in adults with ADHD, suggesting its potential use as a non-pharmacological approach for ADHD management.

The extent to which brain responses are less distinctive across varying cognitive loads in older adults is referred to as neural dedifferentiation. Moment-to-moment brain signal variability, an emerging indicator, reveals not only the adaptability of an individual's brain as an inter-individual trait, but also the allocation of neural resources within an individual due to ever-changing task demands, thus shedding novel insight into the process of neural dedifferentiation. However, how the modulation of intra-individual brain signal variability reflects behavioral differences related to cognitively demanding tasks remains unclear. In this study, we employed functional near-infrared spectroscopy (fNIRS) imaging to capture the variability of brain signals, which was quantified by the standard deviation, during both the resting state and an n-back task (n=1, 2, 3) in 57 healthy older adults. Using multivariate Partial Least Squares (PLS) analysis, we found that fNIRS signal variability increased from the resting state to the task and increased with working memory load in older adults. We further confirmed that greater fNIRS signal variability generally supported faster and more stable response time in the 2- and 3-back conditions. However, the intra-individual level analysis showed that the greater the up-modulation in fNIRS signal variability with cognitive loads, the more its accuracy decreases and mean response time increases, suggesting that a greater intra-individual brain signal variability up-modulation may reflect decreased efficiency in neural information processing. Taken together, our findings offer new insights into the nature of brain signal variability, suggesting that inter- and intra-individual brain signal variability may index distinct theoretical constructs.

Functional near-infrared spectroscopy (fNIRS) imaging offers a promising avenue for measuring brain function in both healthy and diseased cohorts. However, signal quality in fNIRS data frequently encounters challenges, such as low signal-to-noise ratio or substantial motion artifacts in one or multiple measurement channels, impeding the comprehensive exploitation of the data. Developing a valid method to improve the quality of damaged fNIRS signals is crucial, particularly given the extensive use of wearable fNIRS devices in natural settings where noise issues are even more unavoidable. Here, we proposed a generative deep learning approach to recover damaged fNIRS signals in one or more measurement channels. The model captured spatial and temporal variations in the time series of fNIRS data by integrating multiscale convolutional layers, gated recurrent units (GRUs), and linear regression analyses. We trained the model on a resting-state fNIRS dataset from healthy elderly individuals and evaluated its performance in terms of reconstruction accuracy and functional connectivity matrix similarity. Collectively, the proposed model exhbited an excellent performance for the reconstruction of damaged fNIRS time series. In individual channel-level, the model can accurately reconstruct damaged fNIRS time series (mean correlation = 0.80 ± 0.14) while preserving intervariable relationships (correlation = 0.93). In multiple channel-level, the model maintained robust reconstruction accuracy and consistency in terms of functional connectivity. Our findings underscore the potential of generative deep learning techniques in reconstructing damaged fNIRS signals, providing a novel perspective for the efficient utilization of data in clinical diagnosis and brain research.

Significance:Functional near-infrared spectroscopy (fNIRS) has been widely used to assess brain functional networks due to its superior ecological validity. Generally, fNIRS signals are sensitive to motion artifacts (MA), which can be removed by various MA correction algorithms. Yet, fNIRS signals may also undergo varying degrees of distortion due to MA correction, leading to notable alternation in functional connectivity (FC) analysis results. Aim:We aimed to investigate the effect of different MA correction algorithms on the performance of brain FC and topology analyses. Approach:We evaluated various MA correction algorithms on simulated and experimental datasets, including principal component analysis, spline interpolation, correlation-based signal improvement, Kalman filtering, wavelet filtering, and temporal derivative distribution repair (TDDR). The mean FC of each pre-defined network, receiver operating characteristic (ROC), and graph theory metrics were investigated to assess the performance of different algorithms. Results:Although most algorithms did not differ significantly from each other, the TDDR and wavelet filtering turned out to be the most effective methods for FC and topological analysis, as evidenced by their superior denoising ability, the best ROC, and an enhanced ability to recover the original FC pattern. Conclusions:The findings of our study elucidate the varying impact of MA correction algorithms on brain FC analysis, which could serve as a reference for choosing the most appropriate method for future FC research. As guidance, we recommend using TDDR or wavelet filtering to minimize the impact of MA correction in brain network analysis.

This study investigates neural processes in infant speech processing, with a focus on left frontal brain regions and hemispheric lateralization in Mandarin-speaking infants' acquisition of native tonal categories. We tested 2- to 6-month-old Mandarin learners to explore age-related improvements in tone discrimination, the role of inferior frontal regions in abstract speech category representation, and left hemisphere lateralization during tone processing. Using a block design, we presented four Mandarin tones via [ta] and measured oxygenated hemoglobin concentration with functional near-infrared spectroscopy. Results showed age-related improvements in tone discrimination, greater involvement of frontal regions in older infants indicating abstract tonal representation development and increased bilateral activation mirroring native adult Mandarin speakers. These findings contribute to our broader understanding of the relationship between native speech acquisition and infant brain development during the critical period of early language learning.

A large body of evidence suggests that brain signal complexity (BSC) may be an important indicator of healthy brain functioning or alternately, a harbinger of disease and dysfunction. However, despite recent progress our current understanding of how BSC emerges and evolves in large-scale networks, and the factors that shape these dynamics, remains limited. Here, we utilized resting-state functional near-infrared spectroscopy (rs-fNIRS) to capture and characterize the nature and time course of BSC dynamics within large-scale functional networks in 107 healthy participants ranging from 6-13 years of age. Age-dependent increases in spontaneous BSC were observed predominantly in higher-order association areas including the default mode (DMN) and attentional (ATN) networks. Our results also revealed asymmetrical developmental patterns in BSC that were specific to the dorsal and ventral ATN networks, with the former showing a left-lateralized and the latter demonstrating a right-lateralized increase in BSC. These age-dependent laterality shifts appeared to be more pronounced in females compared to males. Lastly, using a machine-learning model, we showed that BSC is a reliable predictor of chronological age. Higher-order association networks such as the DMN and dorsal ATN demonstrated the most robust prognostic power for predicting ages of previously unseen individuals. Taken together, our findings offer new insights into the spatiotemporal patterns of BSC dynamics in large-scale intrinsic networks that evolve over the course of childhood and adolescence, suggesting that a network-based measure of BSC represents a promising approach for tracking normative brain development and may potentially aid in the early detection of atypical developmental trajectories.

Auditory exposure plays crucial roles in shaping healthy brain development and generating lateralization of functional network organization. However, little is known about whether and how an initial lack of auditory exposure in early infancy may disrupt development of functional network lateralization. We addressed this issue by recruiting 55 infants with congenital sensorineural hearing loss (SNHL) and 60 typically developing (TD) controls. Resting-state fNIRS imaging data were acquired to construct hemispheric cerebral networks, and graph theory was applied to quantify the topological characteristics of hemispheric networks. The infants with SNHL exhibited efficient small-world characteristic within each hemispheric network, however, the lateralization of functional network efficiency was substantially disrupted. Compared with TD infants with significantly increased network efficiency lateralized toward left hemisphere with age, the SNHL infants did not exhibit the emergence and development of such cerebral lateralization. Furthermore, the increased leftward asymmetry in nodal efficiency with age was found in TD but not in SNHL infants. Interestingly, the degree of hearing loss had no correlation with lateralization strength in the SNHL group. These results suggest that SNHL infants exhibited disrupted development of cortical lateralization in functional network organization, and highlight the importance of auditory stimulation-promoted multisensory functional integration in early infancy.

The impairment of executive functions (EFs) in attention-deficit/hyperactivity disorder (ADHD) might vary from one individual to another, indicating high heterogeneity. Comorbidity may contribute to this heterogeneity. Disruptive behavior disorders (DBD), including oppositional defiant disorder (ODD) and conduct disorder (CD), is the most common comorbidity in ADHD. Although many studies suggest that ADHD with CD (ADHDCD+) and ADHD with ODD (ADHDODD+) should be treated differently, little research has attempted to separate these two disorders when studying the EFs and brain imaging of ADHD with DBD (ADHDDBD+). Thus, based on our ongoing research in ADHD, we have now recruited a large sample size of medication-naïve children to obtain estimates of neurocognitive function and functional brain networks. We found no EF impairment in ADHDCD+ patients compared with healthy controls (HCs). Correlation analysis showed that more severe CD symptoms were associated with better EFs. The mediation analysis revealed that the relationship between CD symptoms and inhibition function was mediated by the functional connectivity (FC) of SMN(L) - DMN(R) in the younger group. The study suggested that ADHDCD+ and ADHDODD+ are different in their EF impairment. The comorbidity of CD may not worsen the impairments and might even improve EF performance within ADHD individuals.

It has been proved that unilateral hearing loss (UHL) can cause functional connectivity alterations in adults. However, the mechanism of the human brain coping with the challenge of unilateral hearing deprivation at very early developmental phases remains poorly understood. Here, we performed a resting-state functional near-infrared spectroscopy (fNIRS) study on 3- to 10-month-old infants with varying degrees of unilateral hearing loss to investigate the effect of unilateral auditory deprivation in infants. Using network-based statistics, increased functional connectivity was observed in single-sided deafness (SSD) compared with normal hearing infants, and the right middle temporal gyrus was the most involved nodes. In addition, changes in cortical function in infants were related to the degree of hearing loss, with significantly increased functional connectivity in infants with severe to profound unilateral hearing loss compared with the ones with mild to moderate. Moreover, more significant cortical functional recombination changes were found in right-SSD than in left-SSD infants. For the first time, our study provides evidence for the effects of unilateral hearing deprivation on the early cortical development of the human brain, which would also act as a reference for intervention decisions in children with unilateral hearing loss in clinical settings.

This study aimed to investigate the effects of the Mindful Parenting Program (MPP) on the executive function and brain function of parents of children with attention-deficit/hyperactivity disorder (ADHD). One hundred thirteen parents of children with ADHD were randomly assigned to the 8-week MPP or the Treatment as Usual waitlist control group (TAU). The stroop test, spatial working memory test, and Behavior Rating Inventory of Executive Function-Adult Version (BRIEF-A) were administered at baseline and postintervention. In addition, the time-by-group interaction of the participants was measured with functional near-infrared spectroscopy (fNIRS). The effects of the MPP on the executive function and functional connectivity (FC) of the brain were evaluated with repeated measures analysis of variance. For executive function, there was a significant time-by-group interaction effect on BRIEF-Initiation (F=4.42, p=0.038, Cohen’s d=0.19) and BRIEF-Shift scores (F=4.01, p=0.048, Cohen’s d=0.23). Only 16 participants in the MPP group and 15 in the TAU waitlist control were included for fNIRS analysis. Compared with those in the TAU waitlist control group, the MPP group had increased FC in the right default mode network (DMN-R), and left frontoparietal network (FPN-L), DMN-R-left ventral attention network (VAN-L), DMN-R-left visual network (VN-L), VAN-L-right ventral attention network (VAN-R), VAN-L, and left visual network (VN-L). In contrast to the MPP group, the TAU waitlist control group had decreased FC in the left sensorimotor network (SMN-L)-VN-L. The improvements in BRIEF-Shift scores were correlated with VN(L)-SMN(L). However, no results were significant after false discovery rate correction, a statistical method to control for multiple comparisons. The MPP appears to have beneficial effects on the executive function and brain function of parents of children with ADHD. However, these findings need to be confirmed in further studies. https://www.chictr.org.cn ; ChiCTR1800019215 (registered in 2018/08/31)

Transcranial photobiomodulation (tPBM) is an emerging non-invasive light-based neuromodulation technique that shows promising potential for improving working memory (WM) performance in older adults. However, the neurophysiological mechanisms associated with tPBM that underlie the improvement of WM and the persistence of such improvement have not been investigated. Sixty-one healthy older adults were recruited to receive a baseline sham stimulation, followed by one-week active tPBM (12 min daily, 1064-nm laser, 250 mW/cm2) and three-week follow-ups. N-back WM task was conducted on post-stimulation of the baseline, the first (Day 1) and seventh (Day 7) days of the active treatment, and at the follow-ups. During the task, functional near-infrared spectroscopy (fNIRS) imaging was employed to record the cortical hemodynamic changes. Brain activations during the active and follow-up sessions were compared with the baseline to determine how tPBM had changed cortical hemodynamic activity and how long these changes persisted. We found that tPBM stimulation on Day 1 induced significantly decreased activation in the right hemisphere during the 3-back. The decreased activation expanded from only the right hemisphere on Day 1 to both hemispheres on Day 7. The decreased activation persisted for one week in the right supramarginal gyrus and the left angular gyrus and two weeks in the left somatosensory association cortex. These activation changes were accompanied by significantly improved task accuracy during the N-back. These findings provide important evidence for understanding neural mechanisms underlying cognitive enhancement after tPBM.

Background Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. Many previous studies have shown that the comorbid status of disruptive behaviour disorders (DBD) was a predictor for ADHD persistence into adulthood. However, the brain mechanisms underlying such a relationship remain unclear. Thus, we aim to investigate whether the brain functional alteration in adults with ADHD could also be detected in children with ADHD co-occurring with disruptive behaviours from both quantitative and categorical dimensions. Methods A total of 172 children with ADHD (cADHD), 98 adults with ADHD (aADHD), 77 healthy control children (cHC) and 40 healthy control adults (aHC) were recruited. The whole-brain spontaneous fluctuations in brain activity of each participant were recorded using functional near-infrared spectroscopy (fNIRS), and the functional connectivities (FCs) were calculated. We first compared the FC differences between aADHD and aHC. Then, for the regions with significantly abnormal FCs in aADHD, we further compared these features between cADHD and cHC. In addition, the correlation between these FCs and the conduct disorder (CD)/oppositional defiant disorder (ODD) symptoms were analysed in cADHD. Moreover, to render the results readily interpretable, we compared the FC differences among ADHD(CD-), subthreshold ADHD(CD+) and cHC groups, and among ADHD(ODD-), ADHD(ODD+) and cHC groups. Finally, we repeated the above analysis after controlling for other comorbidities and core symptoms to diminish the potential confounding effects. Results We found that compared with aHC, aADHD showed significantly increased FCs in the VN, DMN, SMN, and DAN. The aforementioned abnormal FCs were also detected in cADHD, however, in an opposite orientation. Notably, these abnormal FCs were positively correlated with CD symptoms. Finally, the subthreshold ADHD(CD+) group even exhibited a tendency of adult-like increased FCs compared with the cHC. The results held after controlling for other comorbidities and core symptoms. Conclusion This study provides functional neuroimaging evidence that CD might be a risk factor for ADHD persistence into adulthood. Our work highlights the importance of differentiating ADHD(CD+) from ADHD and inspiring further understanding of brain development in ADHD.

It is well-established that visuospatial attention is mainly lateralized to the right hemisphere, whereas language production is mainly left-lateralized. However, there is a significant controversy regarding how these two kinds of lateralization interact with each other. The present research used functional near-infrared spectroscopy (fNIRS) to examine whether visuospatial attention is indeed right-lateralized, whereas language production is left-lateralized, and more importantly, whether the extent of lateralization in the visuospatial task is correlated with that in the task involving language. Specifically, fifty-two healthy right-handed participants participated in this study. Multiple-channel fNIRS technique was utilized to record the cerebral hemodynamic changes when participants were engaged in naming objects depicted in pictures (the picture naming task) or judging whether a presented line was bisected correctly (the landmark task). The degree of hemispheric lateralization was quantified according to the activation difference between the left and right hemispheres. We found that the picture-naming task predominantly activated the inferior frontal gyrus (IFG) of the left hemisphere. In contrast, the landmark task predominantly activated the inferior parietal sulcus (IPS) and superior parietal lobule (SPL) of the right hemisphere. The quantitative calculation of the laterality index also showed a left-lateralized distribution for the picture-naming task and a right-lateralized distribution for the landmark task. Intriguingly, the correlation analysis revealed no significant correlation between the laterality indices of these two tasks. Our findings support the independent hypothesis, suggesting that different cognitive tasks may engender lateralized processing in the brain, but these lateralized activities may be independent of each other. Meanwhile, we stress the importance of handedness in understanding the relationship between functional asymmetries. Methodologically, we demonstrated the effectiveness of using the multichannel fNIRS technique to investigate the hemispheric specialization of different cognitive tasks and their lateralization relations between different tasks. Our findings and methods may have important implications for future research to explore lateralization-related issues in individuals with neural pathologies.

BACKGROUND A minimum spanning tree (MST) is a unique efficient network comprising the necessary connections needed to connect all regions in a network while retaining the lowest possible cost of connection weight. OBJECTIVE This study aimed to utilize functional near-infrared spectroscopy (fNIRS) to analyze brain activity in different regions and then construct MST-based regions to characterize the brain topologies of participants with Alzheimer's disease (AD), mild cognitive impairment (MCI), and normal controls (NC). METHODS A 46 channel fNIRS setup was used on all participants, with correlation being calculated for each channel pair. An MST was constructed from the resulting correlation matrix, from which graph theory measures were calculated. The average number of connections within a lobe in the left versus right hemisphere was calculated to identify which lobes displayed and abnormal amount of connectivity. RESULTS Compared to those in the MCI group, the AD group showed a less integrated network structure, with a higher characteristic path length, but lower leaf fraction, maximum degree, and degree divergence. The AD group also showed a higher number of connections in the frontal lobe within the left hemisphere and a lower number between hemispheric frontal lobes as compared to MCI. CONCLUSION These results indicate a deviation in network structure and connectivity within patient groups that is consistent with the theory of dysconnectivity for AD. Additionally, the AD group showed strong correlations between the Hamilton depression rating scale and different graph metrics, suggesting a link between network organization and the recurrence of depression in AD.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by behavioral features that appear early in life. Although studies have shown that atypical brain functional and structural connectivity are associated with these behavioral traits, the occurrence and initial alterations of brain networks have not been fully investigated. The current study aimed to map early brain network efficiency and information transferring in infants at elevated likelihood (EL) compared to infants at typical likelihood (TL) for ASD in the first year of life. This study used a resting-state functional near-infrared spectroscopy (fNIRS) approach to obtain the length and strength of functional connections in the frontal and temporal areas in 45 5-month-old and 38 10-month-old infants. Modular organization and small-world properties were detected in both EL and TL infants at 5 and 10 months. In 5-month-old EL infants, local and nodal efficiency were significantly greater than age-matched TL infants, indicating overgrown local connections. Furthermore, we used a support vector machine (SVM) model to classify infants with or without EL based on the obtained global properties of the network, achieving an accuracy of 77.6%. These results suggest that infants with EL for ASD exhibit inefficiencies in the organization of brain networks during the first year of life.