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Koirala N, Manning J, Neumann S, Anderson C, Deroche MLD, Wolfe J, Pugh K, Landi N, Muthuraman M, Gracco VL. The neural characteristics influencing literacy outcome in children with cochlear implants. Brain Commun 2025; 7:fcaf086. [PMID: 40046341 PMCID: PMC11881800 DOI: 10.1093/braincomms/fcaf086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 01/20/2025] [Accepted: 02/19/2025] [Indexed: 03/16/2025] Open
Abstract
Early hearing intervention in children with congenital hearing loss is critical for improving auditory development, speech recognition and both expressive and receptive language, which translates into better educational outcomes and quality of life. In children receiving hearing aids or cochlear implants, both adaptive and potentially maladaptive neural reorganization can mitigate higher-level functions that impact reading. The focus of the present study was to dissect the neural underpinnings of the reading networks in children with cochlear implants and assess how these networks mediate the reading ability in children with cochlear implants. Cortical activity was obtained using naturalistic stimuli from 75 children (50 cochlear implant recipients, aged 7-17, and 25 age-matched children with typical hearing) using functional near-infrared spectroscopy. Assessment of basic reading skill was completed using the Reading Inventory and Scholastic Evaluation. We computed directed functional connectivity of the haemodynamic activity in reading-associated anterior and posterior brain regions using the time-frequency causality estimation method known as temporal partial directed coherence. The influence of the cochlear implant-related clinical measures on reading outcome and the extent to which neural connectivity mediated these effects were examined using structural equation modelling. Our findings reveal that the timing of intervention (e.g. age of first cochlear implants, age of first hearing aid) in children with cochlear implants significantly influenced their reading ability. Furthermore, reading-related processes (word recognition and decoding, vocabulary, morphology and sentence processing) were substantially mediated by the directed functional connectivity within reading-related neural circuits. Notably, the impact of these effects differed across various reading skills. Hearing age, defined as the age at which a participant received adequate access to sound, and age of initial implantation emerged as robust predictors of reading proficiency. The current study is one of the first to identify the influence of neural characteristics on reading outcomes for children with cochlear implants. The findings emphasize the importance of the duration of deafness and early intervention for enhancing outcomes and strengthening neural network connections. However, the neural evidence further suggested that such positive influences cannot fully offset the detrimental impact of early auditory deprivation. Consequently, additional, perhaps more specialized, interventions might be necessary to maximize the benefits of early prosthetic hearing intervention.
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Affiliation(s)
- Nabin Koirala
- Child Study Center, School of Medicine, Yale University, New Haven, CT 06511, USA
- Brain Imaging Research Core, University of Connecticut, Storrs, CT 06269, USA
- Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
| | - Jacy Manning
- Hearts for Hearing Foundation, Oklahoma City, OK 73120, USA
| | - Sara Neumann
- Hearts for Hearing Foundation, Oklahoma City, OK 73120, USA
| | | | - Mickael L D Deroche
- Department of Psychology, Concordia University, Montreal, QC H3G 1M8, Canada
| | - Jace Wolfe
- Oberkotter Foundation, Philadelphia, PA 19102, USA
| | - Kenneth Pugh
- Child Study Center, School of Medicine, Yale University, New Haven, CT 06511, USA
- Department of Psychological Sciences, University of Connecticut, Storrs, CT 06269, USA
| | - Nicole Landi
- Child Study Center, School of Medicine, Yale University, New Haven, CT 06511, USA
- Department of Psychological Sciences, University of Connecticut, Storrs, CT 06269, USA
| | | | - Vincent L Gracco
- Child Study Center, School of Medicine, Yale University, New Haven, CT 06511, USA
- School of Communication Sciences and Disorders, McGill University, Montreal, QC H3A 0G4, Canada
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Wang F, Jamaludin A. Investigating frontoparietal networks and activation in children with mathematics learning difficulties: Cases with different deficit profiles. Eur J Neurosci 2025; 61:e16629. [PMID: 39803862 DOI: 10.1111/ejn.16629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 11/09/2024] [Accepted: 11/15/2024] [Indexed: 05/02/2025]
Abstract
Approximately 15%-20% of school-aged children suffer from mathematics learning difficulties (MLD). Most children with developmental dyscalculia (DD) or MLD also have comorbid cognitive deficits. Recent literature suggests that research should focus on uncovering the neural underpinnings of MLD across more inclusive samples, rather than limiting studies to pure cases of DD or MLD with highly stringent inclusion criteria. Therefore, this study aims to identify neural aberrancies that may be common across multiple MLD cases with different deficit profiles. Nine MLD cases and 45 typically developing (TD) children, all around 7 years old (27 boys), were recruited. Using functional near-infrared spectroscopy (fNIRS), brain data were collected during an approximate resting state and a mathematical computation task (addition). Graph theory was then applied to assess global and nodal network indicators of brain function. When comparing the network indicators and brain activation of the MLD cases to those of TD children, no unified neural aberrancy was found across all cases. However, three MLD cases did show distinct neural aberrancies compared to TD children. The study discusses the implications of these findings, considering both the neural aberrancies in the three MLD cases and the neural similarities found in the other six cases, which were comparable to those of the TD children. This raises important questions about the presence and nature of aberrant neural indicators in MLD across large cohorts and highlights the need for further research in this area.
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Affiliation(s)
- Fengjuan Wang
- National Institute of Education, Nanyang Technological University, Singapore
- School of Physical and Mathematical Sciences (SPMS), Nanyang Technological University, Singapore
| | - Azilawati Jamaludin
- National Institute of Education, Nanyang Technological University, Singapore
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Wang J, Zou Z, Huang H, Zhang Y, He X, Su H, Wang W, Chen Y, Liu Y. Effects of repetitive transcranial magnetic stimulation on prefrontal cortical activation in children with attention deficit hyperactivity disorder: a functional near-infrared spectroscopy study. Front Neurol 2024; 15:1503975. [PMID: 39711791 PMCID: PMC11659132 DOI: 10.3389/fneur.2024.1503975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2024] [Accepted: 11/20/2024] [Indexed: 12/24/2024] Open
Abstract
Background Attention deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder characterized by inattention, impulsivity, and hyperactivity. With the continuous development of neuromodulation technology, Repetitive Transcranial Magnetic Stimulation (rTMS) has emerged as a potential non-invasive treatment for ADHD. However, there is a lack of research on the mechanism of rTMS for ADHD. Functional near infrared spectroscopy (fNIRS) is an optical imaging technique that reflects the brain function by measuring changes in blood oxygen concentration in brain tissue. Consequently, this research utilized fNIRS to examine the impact of rTMS on the core symptoms and prefrontal cortex activation in children with ADHD, which provides a reference for the clinical application of rTMS in the treatment of ADHD. Methods Forty children with ADHD were chosen as research subjects and randomly assigned to two groups: a treatment group (20 subjects) and a control group (20 subjects). The control group received non-pharmacological interventions, whereas the treatment group was administered rTMS in conjunction with non-pharmacological interventions. Clinical symptom improvement was evaluated using SNAP-IV scale scores both before and after treatment. Additionally, fNIRS was utilized to monitor alterations in the relative concentrations of oxyhemoglobin (HbO2) and deoxyhemoglobin (HbR) in the prefrontal cortex during resting state and during the Go/no-go task state, both pre- and post-treatment. Results In conclusion, the study comprised 17 participants in the treatment group and 18 in the control group. Initially, the SNAP-scale scores were comparable between the groups, with no significant differences observed (p > 0.05). Post-treatment, a notable reduction in SNAP-scale scores was evident (p < 0.05), with the treatment group exhibiting a more pronounced decrease (p < 0.05). Following the intervention, both groups demonstrated enhanced Resting-state functional connectivity (RSFC) in the prefrontal cortex, as indicated by a significant increase compared to pre-treatment levels (p < 0.05). Specifically, the treatment group showed superior RSFC in the left dorsolateral prefrontal cortex, right dorsolateral prefrontal cortex, left medial prefrontal cortex, and right medial prefrontal cortex compared to the control group (p < 0.05). However, no significant differences were noted in RSFC of the left and right temporal lobes between the two groups (p > 0.05). In the Go/no-go task, the treatment group recorded higher mean HbO2 concentrations in the aforementioned prefrontal cortical regions compared to the control group (p < 0.05). Conversely, no statistically significant disparities were observed in the left and right temporal lobes of both groups. Conclusion rTMS shows promise as a treatment for ADHD by modulating prefrontal cortical activation. fNIRS provides a valuable method for assessing these effects, offering insights into the neurobiological mechanisms underlying rTMS therapy.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Yun Liu
- Department of Rehabilitation, Kunming Children's Hospital, Kunming Medical University, Kunming, Yunnan, China
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He Y, Wang N, Liu D, Peng H, Yin S, Wang X, Wang Y, Yang Y, Si J. Assessment of residual awareness in patients with disorders of consciousness using functional near-infrared spectroscopy-based connectivity: a pilot study. NEUROPHOTONICS 2024; 11:045013. [PMID: 39668847 PMCID: PMC11635295 DOI: 10.1117/1.nph.11.4.045013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/23/2024] [Revised: 11/20/2024] [Accepted: 11/21/2024] [Indexed: 12/14/2024]
Abstract
Significance The accurate assessment and classification of residual consciousness are crucial for optimizing therapeutic interventions in patients with disorders of consciousness (DOCs). However, there remains an absence of effective and definitive diagnostic methods for DOC in clinical practice. Aim The primary objective was to investigate the feasibility of utilizing resting state functional near-infrared spectroscopy (rs-fNIRS) for evaluating residual consciousness. The secondary objective was to explore the distinguishing characteristics that are more effective in differentiating between the unresponsive wakefulness syndrome (UWS) and the minimally conscious state (MCS) and to identify the machine learning model that offers superior classification accuracy. Approach We utilized rs-fNIRS to evaluate the residual consciousness in patients with DOC. Specifically, rs-fNIRS was used to construct functional brain networks, and graph theory analysis was conducted to quantify the topological differences within these brain networks between MCS and UWS. After that, two classifiers were used to distinguish MCS from UWS. Results The graph theory results showed that the MCS group ( n = 8 ) exhibited significantly higher global efficiency (E g ) and smaller characteristic path length (L p ) than the UWS group ( n = 10 ). The functional connectivity results showed that the correlation within the left occipital cortex (L_OC) was significantly lower in the MCS group than in the UWS group. By using the indicators with significant differences as features for further classification, the accuracy for K -nearest neighbors and linear discriminant analysis classifiers was improved by 0.89 and 0.83, respectively. Conclusions The resting state functional connectivity and graph theory analysis based on fNIRS has the potential to enhance the classification accuracy, providing valuable insights into the diagnosis of patients with DOC.
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Affiliation(s)
- Yifang He
- Beijing Information Science and Technology University, School of Instrumentation Science and Opto-Electronics Engineering, Beijing, China
| | - Nan Wang
- Capital Medical University, Beijing Tiantan Hospital, Department of Neurosurgery, Beijing, China
- Chinese Academy of Medical Sciences and Peking Union Medical College, Peking Union Medical College Hospital, Department of Neurosurgery, Beijing, China
| | - Dongsheng Liu
- Tianjin Medical University, Clinical College of Neurology, Neurosurgery and Neurorehabilitation, Tianjin, China
- Tianjin Huanhu Hospital, Department of Neurosurgery, Tianjin, China
- Aviation General Hospital, Department of Neurosurgery, Beijing, China
| | - Hao Peng
- Beijing Information Science and Technology University, School of Instrumentation Science and Opto-Electronics Engineering, Beijing, China
| | - Shaoya Yin
- Tianjin Medical University, Clinical College of Neurology, Neurosurgery and Neurorehabilitation, Tianjin, China
- Tianjin Huanhu Hospital, Department of Neurosurgery, Tianjin, China
- Tianjin Huanhu Hospital, Tianjin Neurosurgical Institute, Tianjin Key Laboratory of Cerebral Vascular and Neurodegenerative Diseases, Tianjin, China
| | | | - Yong Wang
- Aviation General Hospital, Beijing, China
| | - Yi Yang
- Capital Medical University, Beijing Tiantan Hospital, Department of Neurosurgery, Beijing, China
- Beijing Institute of Brain Disorders, Beijing, China
| | - Juanning Si
- Beijing Information Science and Technology University, School of Instrumentation Science and Opto-Electronics Engineering, Beijing, China
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Mızrak HG, Dikmen M, Hanoğlu L, Şakul BU. Investigation of hemispheric asymmetry in Alzheimer's disease patients during resting state revealed BY fNIRS. Sci Rep 2024; 14:13454. [PMID: 38862632 PMCID: PMC11166983 DOI: 10.1038/s41598-024-62281-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Accepted: 05/15/2024] [Indexed: 06/13/2024] Open
Abstract
Alzheimer's disease (AD) is characterized by the gradual deterioration of brain structures and changes in hemispheric asymmetry. Meanwhile, healthy aging is associated with a decrease in functional hemispheric asymmetry. In this study, functional connectivity analysis was used to compare the functional hemispheric asymmetry in eyes-open resting-state fNIRS data of 16 healthy elderly controls (mean age: 60.4 years, MMSE (Mini-Mental State Examination): 27.3 ± 2.52) and 14 Alzheimer's patients (mean age: 73.8 years, MMSE: 22 ± 4.32). Increased interhemispheric functional connectivity was found in the premotor cortex, supplementary motor cortex, primary motor cortex, inferior parietal cortex, primary somatosensory cortex, and supramarginal gyrus in the control group compared to the AD group. The study revealed that the control group had stronger interhemispheric connectivity, leading to a more significant decrease in hemispheric asymmetry than the AD group. The results show that there is a difference in interhemispheric functional connections at rest between the Alzheimer's group and the control group, suggesting that functional hemispheric asymmetry continues in Alzheimer's patients.
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Affiliation(s)
- Hazel Gül Mızrak
- Department of Anatomy, School of Medicine, Istanbul Medipol University, Istanbul, Turkey
| | - Merve Dikmen
- Regenerative and Restorative Medicine Research Center (REMER), Research Institute for Health Sciences and Technologies (SABITA), Istanbul Medipol University, Istanbul, Turkey.
- Program of Electroneurophysiology, Vocational School of Health Services, Istanbul Medipol University, Istanbul, Turkey.
| | - Lütfü Hanoğlu
- Regenerative and Restorative Medicine Research Center (REMER), Research Institute for Health Sciences and Technologies (SABITA), Istanbul Medipol University, Istanbul, Turkey
- Department of Neurology, Istanbul Medipol University Training and Research Hospital, Istanbul, Turkey
| | - Bayram Ufuk Şakul
- Department of Anatomy, School of Medicine, Istanbul Medipol University, Istanbul, Turkey
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Wang W, Li H, Wang Y, Liu L, Qian Q. Changes in effective connectivity during the visual-motor integration tasks: a preliminary f-NIRS study. BEHAVIORAL AND BRAIN FUNCTIONS : BBF 2024; 20:4. [PMID: 38468270 DOI: 10.1186/s12993-024-00232-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 03/05/2024] [Indexed: 03/13/2024]
Abstract
BACKGROUND Visual-motor integration (VMI) is an essential skill in daily life. The present study aimed to use functional near-infrared spectroscopy (fNIRS) technology to explore the effective connectivity (EC) changes among brain regions during VMI activities of varying difficulty levels. METHODS A total of 17 healthy participants were recruited for the study. Continuous Performance Test (CPT), Behavior Rating Inventory of Executive Function-Adult Version (BRIEF-A), and Beery VMI test were used to evaluate attention performance, executive function, and VMI performance. Granger causality analysis was performed for the VMI task data to obtain the EC matrix for all participants. One-way ANOVA analysis was used to identify VMI load-dependent EC values among different task difficulty levels from brain network and channel perspectives, and partial correlation analysis was used to explore the relationship between VMI load-dependent EC values and behavioral performance. RESULTS We found that the EC values of dorsal attention network (DAN) → default mode network (DMN), DAN → ventral attention network (VAN), DAN → frontoparietal network (FPN), and DAN → somatomotor network (SMN) in the complex condition were higher than those in the simple and moderate conditions. Further channel analyses indicated that the EC values of the right superior parietal lobule (SPL) → right superior frontal gyrus (SFG), right middle occipital gyrus (MOG) → left SFG, and right MOG → right postcentral gyrus (PCG) in the complex condition were higher than those in the simple and moderate conditions. Subsequent partial correlation analysis revealed that the EC values from DAN to DMN, VAN, and SMN were positively correlated with executive function and VMI performance. Furthermore, the EC values of right MOG → left SFG and right MOG → right PCG were positively correlated with attention performance. CONCLUSIONS The DAN is actively involved during the VMI task and thus may play a critical role in VMI processes, in which two key brain regions (right SPL, right MOG) may contribute to the EC changes in response to increasing VMI load. Meanwhile, bilateral SFG and right PCG may also be closely related to the VMI performance.
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Affiliation(s)
- Wenchen Wang
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Haimei Li
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Yufeng Wang
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Lu Liu
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, 100191, China.
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China.
| | - Qiujin Qian
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, 100191, China.
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China.
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Su WC, Colacot R, Ahmed N, Nguyen T, George T, Gandjbakhche A. The use of functional near-infrared spectroscopy in tracking neurodevelopmental trajectories in infants and children with or without developmental disorders: a systematic review. Front Psychiatry 2023; 14:1210000. [PMID: 37779610 PMCID: PMC10536152 DOI: 10.3389/fpsyt.2023.1210000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 08/24/2023] [Indexed: 10/03/2023] Open
Abstract
Understanding the neurodevelopmental trajectories of infants and children is essential for the early identification of neurodevelopmental disorders, elucidating the neural mechanisms underlying the disorders, and predicting developmental outcomes. Functional Near-Infrared Spectroscopy (fNIRS) is an infant-friendly neuroimaging tool that enables the monitoring of cerebral hemodynamic responses from the neonatal period. Due to its advantages, fNIRS is a promising tool for studying neurodevelopmental trajectories. Although many researchers have used fNIRS to study neural development in infants/children and have reported important findings, there is a lack of synthesized evidence for using fNIRS to track neurodevelopmental trajectories in infants and children. The current systematic review summarized 84 original fNIRS studies and showed a general trend of age-related increase in network integration and segregation, interhemispheric connectivity, leftward asymmetry, and differences in phase oscillation during resting-state. Moreover, typically developing infants and children showed a developmental trend of more localized and differentiated activation when processing visual, auditory, and tactile information, suggesting more mature and specialized sensory networks. Later in life, children switched from recruiting bilateral auditory to a left-lateralized language circuit when processing social auditory and language information and showed increased prefrontal activation during executive functioning tasks. The developmental trajectories are different in children with developmental disorders, with infants at risk for autism spectrum disorder showing initial overconnectivity followed by underconnectivity during resting-state; and children with attention-deficit/hyperactivity disorders showing lower prefrontal cortex activation during executive functioning tasks compared to their typically developing peers throughout childhood. The current systematic review supports the use of fNIRS in tracking the neurodevelopmental trajectories in children. More longitudinal studies are needed to validate the neurodevelopmental trajectories and explore the use of these neurobiomarkers for the early identification of developmental disorders and in tracking the effects of interventions.
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Affiliation(s)
| | | | | | | | | | - Amir Gandjbakhche
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, United States
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Iester C, Biggio M, Cutini S, Brigadoi S, Papaxanthis C, Brichetto G, Bove M, Bonzano L. Time-of-day influences resting-state functional cortical connectivity. Front Neurosci 2023; 17:1192674. [PMID: 37325041 PMCID: PMC10264597 DOI: 10.3389/fnins.2023.1192674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 05/12/2023] [Indexed: 06/17/2023] Open
Abstract
Time-of-day is rarely considered during experimental protocols investigating motor behavior and neural activity. The goal of this work was to investigate differences in functional cortical connectivity at rest linked to the time of the day using functional Near-Infrared Spectroscopy (fNIRS). Since resting-state brain is shown to be a succession of cognitive, emotional, perceptual, and motor processes that can be both conscious and nonconscious, we studied self-generated thought with the goal to help in understanding brain dynamics. We used the New-York Cognition Questionnaire (NYC-Q) for retrospective introspection to explore a possible relationship between the ongoing experience and the brain at resting-state to gather information about the overall ongoing experience of subjects. We found differences in resting-state functional connectivity in the inter-hemispheric parietal cortices, which was significantly greater in the morning than in the afternoon, whilst the intra-hemispheric fronto-parietal functional connectivity was significantly greater in the afternoon than in the morning. When we administered the NYC-Q we found that the score of the question 27 ("during RS acquisition my thoughts were like a television program or film") was significantly greater in the afternoon with respect to the morning. High scores in question 27 point to a form of thought based on imagery. It is conceivable to think that the unique relationship found between NYC-Q question 27 and the fronto-parietal functional connectivity might be related to a mental imagery process during resting-state in the afternoon.
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Affiliation(s)
- Costanza Iester
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy
| | - Monica Biggio
- Department of Experimental Medicine, Section of Human Physiology, University of Genoa, Genoa, Italy
| | - Simone Cutini
- Department of Developmental and Social Psychology, University of Padova, Padua, Italy
| | - Sabrina Brigadoi
- Department of Developmental and Social Psychology, University of Padova, Padua, Italy
| | - Charalambos Papaxanthis
- INSERM UMR1093-CAPS, Université Bourgogne Franche-Comté, UFR des Sciences du Sport, Dijon, France
| | - Giampaolo Brichetto
- Italian Multiple Sclerosis Foundation, Scientific Research Area, Genoa, Italy
| | - Marco Bove
- Department of Experimental Medicine, Section of Human Physiology, University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Laura Bonzano
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
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Paranawithana I, Mao D, McKay CM, Wong YT. Connections between spatially distant primary language regions strengthen with age during infancy, as revealed by resting-state fNIRS. J Neural Eng 2023; 20. [PMID: 36763991 DOI: 10.1088/1741-2552/acbb2d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 02/10/2023] [Indexed: 02/12/2023]
Abstract
Objective.Hearing is an important sensory function that plays a key role in how children learn to speak and develop language skills. Although previous neuroimaging studies have established that much of brain network maturation happens in early childhood, our understanding of the developmental trajectory of language areas is still very limited. We hypothesized that typical development trajectory of language areas in early childhood could be established by analyzing the changes of functional connectivity in normal hearing infants at different ages using functional near-infrared spectroscopy.Approach.Resting-state data were recorded from two bilateral temporal and prefrontal regions associated with language processing by measuring the relative changes of oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbR) concentrations. Connectivity was calculated using magnitude-squared coherence of channel pairs located in (a) inter-hemispheric homologous and (b) intra-hemispheric brain regions to assess connectivity between homologous regions across hemispheres and two regions of interest in the same hemisphere, respectively.Main results.A linear regression model fitted to the age vs coherence of inter-hemispheric homologous test group revealed a significant coefficient of determination for both HbO (R2= 0.216,p= 0.0169) and HbR (R2= 0.206,p= 0.0198). A significant coefficient of determination was also found for intra-hemispheric test group for HbO (R2= 0.237,p= 0.0117) but not for HbR (R2= 0.111,p= 0.0956).Significance.The findings from HbO data suggest that both inter-hemispheric homologous and intra-hemispheric connectivity between primary language regions significantly strengthen with age in the first year of life. Mapping out the developmental trajectory of primary language areas of normal hearing infants as measured by functional connectivity could potentially allow us to better understand the altered connectivity and its effects on language delays in infants with hearing impairments.
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Affiliation(s)
- Ishara Paranawithana
- Department of Electrical and Computer Systems Engineering, Monash University, Clayton, VIC 3800, Australia.,The Bionics Institute, East Melbourne, VIC 3002, Australia
| | - Darren Mao
- The Bionics Institute, East Melbourne, VIC 3002, Australia.,Department of Medical Bionics, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Colette M McKay
- The Bionics Institute, East Melbourne, VIC 3002, Australia.,Department of Medical Bionics, The University of Melbourne, Parkville, VIC 3010, Australia
| | - Yan T Wong
- Department of Electrical and Computer Systems Engineering, Monash University, Clayton, VIC 3800, Australia.,Department of Physiology and the Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
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Li H, Fu X, Lu L, Guo H, Yang W, Guo K, Huang Z. Upper limb intelligent feedback robot training significantly activates the cerebral cortex and promotes the functional connectivity of the cerebral cortex in patients with stroke: A functional near-infrared spectroscopy study. Front Neurol 2023; 14:1042254. [PMID: 36814999 PMCID: PMC9939650 DOI: 10.3389/fneur.2023.1042254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 01/11/2023] [Indexed: 02/09/2023] Open
Abstract
Background Upper limb intelligence robots are widely used to improve the upper limb function of patients with stroke, but the treatment mechanism is still not clear. In this study, functional near-infrared spectroscopy (fNIRS) was used to evaluate the concentration changes of oxygenated hemoglobin (oxy-Hb) and deoxyhemoglobin (deoxy-Hb) in different brain regions and functional connectivity (FC) of the cerebral cortex in patients with stroke. Method Twenty post-stroke patients with upper limb dysfunction were included in the study. They all received three different types of shoulder joint training, namely, active intelligent feedback robot training (ACT), upper limb suspension training (SUS), and passive intelligent feedback robot training (PAS). During the training, activation of the cerebral cortex was detected by fNIRS to obtain the concentration changes of hemoglobin and FC of the cerebral cortex. The fNIRS signals were recorded over eight ROIs: bilateral prefrontal cortices (PFC), bilateral primary motor cortices (M1), bilateral primary somatosensory cortices (S1), and bilateral premotor and supplementary motor cortices (PM). For easy comparison, we defined the right hemisphere as the ipsilesional hemisphere and flipped the lesional right hemisphere in the Nirspark. Result Compared with the other two groups, stronger cerebral cortex activation was observed during ACT. One-way repeated measures ANOVA revealed significant differences in mean oxy-Hb changes among conditions in the four ROIs: contralesional PFC [F(2, 48) = 6,798, p < 0.01], ipsilesional M1 [F(2, 48) = 6.733, p < 0.01], ipsilesional S1 [F(2, 48) = 4,392, p < 0.05], and ipsilesional PM [F(2, 48) = 3.658, p < 0.05]. Oxy-Hb responses in the contralesional PFC region were stronger during ACT than during SUS (p < 0.01) and PAS (p < 0.05). Cortical activation in the ipsilesional M1 was significantly greater during ACT than during SUS (p < 0.01) and PAS (p < 0.05). Oxy-Hb responses in the ipsilesional S1 (p < 0.05) and ipsilesional PM (p < 0.05) were significantly higher during ACT than during PAS, and there is no significant difference in mean deoxy-Hb changes among conditions. Compared with SUS, the FC increased during ACT, which was characterized by the enhanced function of the ipsilesional cortex (p < 0.05), and there was no significant difference in FC between the ACT and PAS. Conclusion The study found that cortical activation during ACT was higher in the contralesional PFC, and ipsilesional M1 than during SUS, and showed tighter cortical FC between the cortices. The activation of the cerebral cortex of ACT was significantly higher than that of PAS, but there was no significant difference in FC. Our research helps to understand the difference in cerebral cortex activation between upper limb intelligent feedback robot rehabilitation and other rehabilitation training and provides an objective basis for the further application of upper limb intelligent feedback robots in the field of stroke rehabilitation.
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Affiliation(s)
- Hao Li
- Guangzhou Panyu Central Hospital, Guangzhou, China,Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Xuefeng Fu
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Lijun Lu
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Hua Guo
- Guangzhou Panyu Central Hospital, Guangzhou, China,Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Wen Yang
- Guangzhou Panyu Central Hospital, Guangzhou, China
| | - Kaifeng Guo
- Guangzhou Panyu Central Hospital, Guangzhou, China
| | - Zhen Huang
- Guangzhou Panyu Central Hospital, Guangzhou, China,*Correspondence: Zhen Huang ✉
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11
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Liang Z, Wang Y, Tian H, Gu Y, Arimitsu T, Takahashi T, Minagawa Y, Niu H, Tong Y. Spatial complexity method for tracking brain development and degeneration using functional near-infrared spectroscopy. BIOMEDICAL OPTICS EXPRESS 2022; 13:1718-1736. [PMID: 35414994 PMCID: PMC8973163 DOI: 10.1364/boe.449341] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 02/07/2022] [Accepted: 02/16/2022] [Indexed: 06/14/2023]
Abstract
Brain complexity analysis using functional near-infrared spectroscopy (fNIRS) has attracted attention as a biomarker for evaluating brain development and degeneration processes. However, most methods have focused on the temporal scale without capturing the spatial complexity. In this study, we propose a spatial time-delay entropy (STDE) method as the spatial complexity measure based on the time-delay measure between two oxy-hemoglobin (Δ[HbO]) or two deoxy-hemoglobin (Δ[Hb]) oscillations within the 0.01-0.1 Hz frequency band. To do this, we analyze fNIRS signals recorded from infants in their sleeping state, children, adults, and healthy seniors in their resting states. We also evaluate the effects of various noise to STDE calculations and STDE's performance in distinguishing various developmental age groups. Lastly, we compare the results with the normalized global spatial complexity (NGSC) and sample entropy (SampEn) measures. Among these measures, STDEHbO (STDE based on Δ[HbO] oscillations) performs best. The STDE value increases with age throughout childhood (p < 0.001), and then decreases in adults and healthy seniors in the 0.01-0.1 Hz frequency band. This trajectory correlates with cerebrovascular development and degeneration. These findings demonstrate that STDE can be used as a new tool for tracking cerebrovascular development and degeneration across a lifespan based on the fNIRS resting-state measurements.
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Affiliation(s)
- Zhenhu Liang
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
- Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Qinhuangdao 066004, China
| | - Yuxi Wang
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
- Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Qinhuangdao 066004, China
| | - Hao Tian
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
- Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, Qinhuangdao 066004, China
| | - Yue Gu
- Key Laboratory of Computer Vision and System (Ministry of Education), School of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300384, China
| | - Takeshi Arimitsu
- Department of Pediatrics, Keio University School of Medicine, Tokyo, Japan
| | - Takao Takahashi
- Department of Pediatrics, Keio University School of Medicine, Tokyo, Japan
| | - Yasuyo Minagawa
- Department of Psychology, Faculty of Letters, Keio University, Tokyo, Japan
| | - Haijing Niu
- Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Yunjie Tong
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA
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12
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Jia G, Liu G, Niu H. Hemispheric Lateralization of Visuospatial Attention Is Independent of Language Production on Right-Handers: Evidence From Functional Near-Infrared Spectroscopy. Front Neurol 2022; 12:784821. [PMID: 35095729 PMCID: PMC8795708 DOI: 10.3389/fneur.2021.784821] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 12/22/2021] [Indexed: 11/13/2022] Open
Abstract
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.
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Affiliation(s)
| | | | - Haijing Niu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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13
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Ding K, Wang H, Li C, Liu F, Yu D. Decreased Right Prefrontal Synchronization Strength and Asymmetry During Joint Attention in the Left-Behind Children: A Functional Near-Infrared Spectroscopy Study. Front Physiol 2021; 12:759788. [PMID: 34867465 PMCID: PMC8634881 DOI: 10.3389/fphys.2021.759788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 10/11/2021] [Indexed: 11/24/2022] Open
Abstract
Although there are millions of left-behind children in China, the researches on brain structure and functions in left-behind children are not sufficient at the brain imaging level. This study aimed to explore whether there is decreased prefrontal synchronization during joint attention in left-behind children. Sixty children (65.12 ± 6.54 months, 29 males) with 34 left-behind children were recruited. The functional near-infrared spectroscopy (fNIRS) imaging data from the prefrontal cortex during joint attention, as well as behavioral measures (associated with family income, intelligence, language, and social-emotional abilities), were collected. Results verified that brain imaging data and behavioral measures are correlative and support that left-behind children have deficits in social-emotional abilities. More importantly, left-behind children showed decreased synchronization strength and asymmetry in the right middle frontal gyrus during joint attention. The findings suggest that decreased right prefrontal synchronization strength and asymmetry during joint attention might be vulnerability factors in the development of left-behind children.
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Affiliation(s)
- Keya Ding
- Key Laboratory of Child Development and Learning Science, Research Center for Learning Science, Southeast University, Nanjing, China.,School of Biological Science and Medical Engineering, Southeast University, Nanjing, China
| | - Hongan Wang
- Key Laboratory of Child Development and Learning Science, Research Center for Learning Science, Southeast University, Nanjing, China.,School of Biological Science and Medical Engineering, Southeast University, Nanjing, China
| | - Chuanjiang Li
- Hangzhou College of Early Childhood Teachers' Education, Zhejiang Normal University, Hangzhou, China
| | - Fulin Liu
- Key Laboratory of Child Development and Learning Science, Research Center for Learning Science, Southeast University, Nanjing, China.,School of Biological Science and Medical Engineering, Southeast University, Nanjing, China
| | - Dongchuan Yu
- Key Laboratory of Child Development and Learning Science, Research Center for Learning Science, Southeast University, Nanjing, China.,School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.,Department of Child Development and Behavior, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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14
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Veréb D, Kovács MA, Kocsis K, Tóth E, Bozsik B, Király A, Kincses B, Faragó P, Fricska-Nagy Z, Bencsik K, Klivényi P, Kincses ZT, Szabó N. Functional Connectivity Lateralisation Shift of Resting State Networks is Linked to Visuospatial Memory and White Matter Microstructure in Relapsing-Remitting Multiple Sclerosis. Brain Topogr 2021; 35:268-275. [PMID: 34807323 PMCID: PMC8860794 DOI: 10.1007/s10548-021-00881-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 11/05/2021] [Indexed: 11/28/2022]
Abstract
Laterality patterns of resting state networks (RSN) change in various neuropsychiatric conditions. Multiple sclerosis (MS) causes neuro-cognitive symptoms involving dysfunctional large-scale brain networks. Yet, whether healthy laterality patterns of RSNs are maintained in MS and whether altered laterality patterns explain disease symptoms has not been explicitly investigated. We analysed functional MRI and diffusion tensor imaging data from 24 relapsing–remitting MS patients and 25 healthy participants. We performed group-level independent component analysis and used dual regression to estimate individual versions of well-established RSNs. Voxelwise laterality indices were calculated for each RSN. Group differences were assessed via a general linear model-based approach. The relationship between functional laterality and white matter microstructural asymmetry was assessed using Tract-Based Spatial Statistics. Spearman’s correlation was calculated between laterality indices and Brief International Cognitive Assessment for Multiple Sclerosis scores. Functional laterality of the dorsal attention network showed a significant leftward shift in the MS group in the posterior intraparietal sulcus (p < 0.033). Default-mode network laterality showed a significant leftward shift in the MS group in the angular gyrus (p < 0.005). Diminished dorsal attention network laterality was associated with increased fractional anisotropy asymmetry in the superior longitudinal fasciculus (p < 0.02). In the default-mode network, leftward laterality of the angular gyrus was associated with higher BVMT-R scores (R = − 0.52, p < 0.023). Our results confirm previous descriptions of RSN dysfunction in relapsing–remitting MS and show that altered functional connectivity lateralisation patterns of RSNs might contibute to cognitive performance and structural remodellation even in patients with mild clinical symptoms.
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Affiliation(s)
- Dániel Veréb
- Department of Radiology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary.,Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Márton Attila Kovács
- Department of Radiology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Krisztián Kocsis
- Department of Radiology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Eszter Tóth
- Department of Radiology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Bence Bozsik
- Department of Radiology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - András Király
- Department of Radiology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Bálint Kincses
- Department of Psychiatry, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary.,Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany
| | - Péter Faragó
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Zsanett Fricska-Nagy
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Krisztina Bencsik
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Péter Klivényi
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
| | - Zsigmond Tamás Kincses
- Neuroimaging Research Group, Department of Radiology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Semmelweis u. 6, 6725, Hungary.
| | - Nikoletta Szabó
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Szeged, Hungary
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15
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Akın A. fNIRS-derived neurocognitive ratio as a biomarker for neuropsychiatric diseases. NEUROPHOTONICS 2021; 8:035008. [PMID: 34604439 PMCID: PMC8482313 DOI: 10.1117/1.nph.8.3.035008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 09/16/2021] [Indexed: 05/03/2023]
Abstract
Significance: Clinical use of fNIRS-derived features has always suffered low sensitivity and specificity due to signal contamination from background systemic physiological fluctuations. We provide an algorithm to extract cognition-related features by eliminating the effect of background signal contamination, hence improving the classification accuracy. Aim: The aim in this study is to investigate the classification accuracy of an fNIRS-derived biomarker based on global efficiency (GE). To this end, fNIRS data were collected during a computerized Stroop task from healthy controls and patients with migraine, obsessive compulsive disorder, and schizophrenia. Approach: Functional connectivity (FC) maps were computed from [HbO] time series data for neutral (N), congruent (C), and incongruent (I) stimuli using the partial correlation approach. Reconstruction of FC matrices with optimal choice of principal components yielded two independent networks: cognitive mode network (CM) and default mode network (DM). Results: GE values computed for each FC matrix after applying principal component analysis (PCA) yielded strong statistical significance leading to a higher specificity and accuracy. A new index, neurocognitive ratio (NCR), was computed by multiplying the cognitive quotients (CQ) and ratio of GE of CM to GE of DM. When mean values of NCR ( N C R ¯ ) over all stimuli were computed, they showed high sensitivity (100%), specificity (95.5%), and accuracy (96.3%) for all subjects groups. Conclusions: N C R ¯ can reliable be used as a biomarker to improve the classification of healthy to neuropsychiatric patients.
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Affiliation(s)
- Ata Akın
- Acibadem University, Department of Medical Engineering, Ataşehir, Istanbul, Turkey
- Address all correspondence to Ata Akn,
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16
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Cai L, Nitta T, Yokota S, Obata T, Okada E, Kawaguchi H. Targeting brain regions of interest in functional near-infrared spectroscopy-Scalp-cortex correlation using subject-specific light propagation models. Hum Brain Mapp 2021; 42:1969-1986. [PMID: 33621388 PMCID: PMC8046049 DOI: 10.1002/hbm.25367] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 12/05/2020] [Accepted: 01/31/2021] [Indexed: 11/11/2022] Open
Abstract
Targeting specific brain regions of interest by the accurate positioning of optodes (emission and detection probes) on the scalp remains a challenge for functional near‐infrared spectroscopy (fNIRS). Since fNIRS data does not provide any anatomical information on the brain cortex, establishing the scalp‐cortex correlation (SCC) between emission‐detection probe pairs on the scalp and the underlying brain regions in fNIRS measurements is extremely important. A conventional SCC is obtained by a geometrical point‐to‐point manner and ignores the effect of light scattering in the head tissue that occurs in actual fNIRS measurements. Here, we developed a sensitivity‐based matching (SBM) method that incorporated the broad spatial sensitivity of the probe pair due to light scattering into the SCC for fNIRS. The SCC was analyzed between head surface fiducial points determined by the international 10–10 system and automated anatomical labeling brain regions for 45 subject‐specific head models. The performance of the SBM method was compared with that of three conventional geometrical matching (GM) methods. We reveal that the light scattering and individual anatomical differences in the head affect the SCC, which indicates that the SBM method is compulsory to obtain the precise SCC. The SBM method enables us to evaluate the activity of cortical regions that are overlooked in the SCC obtained by conventional GM methods. Together, the SBM method could be a promising approach to guide fNIRS users in designing their probe arrangements and in explaining their measurement data.
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Affiliation(s)
- Lin Cai
- Department of Electronics and Electrical Engineering, Keio University, Yokohama, Japan
| | - Tomonori Nitta
- Department of Electronics and Electrical Engineering, Keio University, Yokohama, Japan
| | - Sho Yokota
- Department of Electronics and Electrical Engineering, Keio University, Yokohama, Japan
| | - Takayuki Obata
- Department of Molecular Imaging and Theranostics, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Eiji Okada
- Department of Electronics and Electrical Engineering, Keio University, Yokohama, Japan
| | - Hiroshi Kawaguchi
- Department of Electronics and Electrical Engineering, Keio University, Yokohama, Japan.,Department of Molecular Imaging and Theranostics, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan.,Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology, Ibaraki, Japan
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17
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Cao W, Zhu H, Li Y, Wang Y, Bai W, Lao U, Zhang Y, Ji Y, He S, Zou X. The Development of Brain Network in Males with Autism Spectrum Disorders from Childhood to Adolescence: Evidence from fNIRS Study. Brain Sci 2021; 11:120. [PMID: 33477412 PMCID: PMC7830916 DOI: 10.3390/brainsci11010120] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 01/12/2021] [Accepted: 01/15/2021] [Indexed: 11/16/2022] Open
Abstract
In the current study, functional near-infrared spectroscopy (fNIRS) was used to collect resting-state signals from 77 males with autism spectrum disorders (ASD, age: 6~16.25) and 40 typically developing (TD) males (age: 6~16.58) in the theory-of-mind (ToM) network. The graph theory analysis was used to obtain the brain network properties in ToM network, and the multiple regression analysis demonstrated that males with ASD showed a comparable global network topology, and a similar age-related decrease in the medial prefrontal cortex area (mPFC) compared to TD individuals. Nevertheless, participants with ASD showed U-shaped trajectories of nodal metrics of right temporo-parietal junction (TPJ), and an age-related decrease in the left middle frontal gyrus (MFG), while trajectories of TD participants were opposite. The nodal metrics of the right TPJ was negatively associated with the social deficits of ASD, while the nodal metrics of the left MFG was negatively associated with the communication deficits of ASD. Current findings suggested a distinct developmental trajectory of the ToM network in males with ASD from childhood to adolescence.
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Affiliation(s)
- Wei Cao
- Centre for Optical and Electromagnetic Research, South China Academy of Advanced Optoelectronics, South China Normal University (SCNU), Guangzhou 510006, China;
| | - Huilin Zhu
- Child Development & Behavior Center, Third Affiliated Hospital of SUN YAT-SEN University, No.2693, Kaichuang revenue, Lingnan Campuses, Guangzhou 510080, China; (H.Z.); (Y.L.); (Y.W.); (W.B.); (U.L.); (Y.Z.); (Y.J.)
| | - Yan Li
- Child Development & Behavior Center, Third Affiliated Hospital of SUN YAT-SEN University, No.2693, Kaichuang revenue, Lingnan Campuses, Guangzhou 510080, China; (H.Z.); (Y.L.); (Y.W.); (W.B.); (U.L.); (Y.Z.); (Y.J.)
| | - Yu Wang
- Child Development & Behavior Center, Third Affiliated Hospital of SUN YAT-SEN University, No.2693, Kaichuang revenue, Lingnan Campuses, Guangzhou 510080, China; (H.Z.); (Y.L.); (Y.W.); (W.B.); (U.L.); (Y.Z.); (Y.J.)
| | - Wuxia Bai
- Child Development & Behavior Center, Third Affiliated Hospital of SUN YAT-SEN University, No.2693, Kaichuang revenue, Lingnan Campuses, Guangzhou 510080, China; (H.Z.); (Y.L.); (Y.W.); (W.B.); (U.L.); (Y.Z.); (Y.J.)
| | - Uchong Lao
- Child Development & Behavior Center, Third Affiliated Hospital of SUN YAT-SEN University, No.2693, Kaichuang revenue, Lingnan Campuses, Guangzhou 510080, China; (H.Z.); (Y.L.); (Y.W.); (W.B.); (U.L.); (Y.Z.); (Y.J.)
| | - Yingying Zhang
- Child Development & Behavior Center, Third Affiliated Hospital of SUN YAT-SEN University, No.2693, Kaichuang revenue, Lingnan Campuses, Guangzhou 510080, China; (H.Z.); (Y.L.); (Y.W.); (W.B.); (U.L.); (Y.Z.); (Y.J.)
| | - Yan Ji
- Child Development & Behavior Center, Third Affiliated Hospital of SUN YAT-SEN University, No.2693, Kaichuang revenue, Lingnan Campuses, Guangzhou 510080, China; (H.Z.); (Y.L.); (Y.W.); (W.B.); (U.L.); (Y.Z.); (Y.J.)
| | - Sailing He
- Centre for Optical and Electromagnetic Research, South China Academy of Advanced Optoelectronics, South China Normal University (SCNU), Guangzhou 510006, China;
| | - Xiaobing Zou
- Child Development & Behavior Center, Third Affiliated Hospital of SUN YAT-SEN University, No.2693, Kaichuang revenue, Lingnan Campuses, Guangzhou 510080, China; (H.Z.); (Y.L.); (Y.W.); (W.B.); (U.L.); (Y.Z.); (Y.J.)
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18
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Hu Z, Liu G, Dong Q, Niu H. Applications of Resting-State fNIRS in the Developing Brain: A Review From the Connectome Perspective. Front Neurosci 2020; 14:476. [PMID: 32581671 PMCID: PMC7284109 DOI: 10.3389/fnins.2020.00476] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Accepted: 04/16/2020] [Indexed: 12/21/2022] Open
Abstract
Early brain development from infancy through childhood is closely related to the development of cognition and behavior in later life. Human brain connectome is a novel framework for describing topological organization of the developing brain. Resting-state functional near-infrared spectroscopy (fNIRS), with a natural scanning environment, low cost, and high portability, is considered as an emerging imaging technique and has shown valuable potential in exploring brain network architecture and its changes during the development. Here, we review the recent advances involving typical and atypical development of the brain connectome from neonates to children using resting-state fNIRS imaging. This review highlights that the combination of brain connectome and resting-state fNIRS imaging offers a promising framework for understanding human brain development.
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Affiliation(s)
- Zhishan Hu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Guangfang Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Haijing Niu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
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19
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Wang M, Hu Z, Liu L, Li H, Qian Q, Niu H. Disrupted functional brain connectivity networks in children with attention-deficit/hyperactivity disorder: evidence from resting-state functional near-infrared spectroscopy. NEUROPHOTONICS 2020; 7:015012. [PMID: 32206679 PMCID: PMC7064804 DOI: 10.1117/1.nph.7.1.015012] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2019] [Accepted: 02/20/2020] [Indexed: 05/19/2023]
Abstract
Significance: Attention-deficit/hyperactivity disorder (ADHD) is the most common psychological disease in childhood. Currently, widely used neuroimaging techniques require complete body confinement and motionlessness and thus are extremely hard for brain scanning of ADHD children. Aim: We present resting-state functional near-infrared spectroscopy (fNIRS) as an imaging technique to record spontaneous brain activity in children with ADHD. Approach: The brain functional connectivity was calculated, and the graph theoretical analysis was further applied to investigate alterations in the global and regional properties of the brain network in the patients. In addition, the relationship between brain network features and core symptoms was examined. Results: ADHD patients exhibited significant decreases in both functional connectivity and global network efficiency. Meanwhile, the nodal efficiency in children with ADHD was also found to be altered, e.g., increase in the visual and dorsal attention networks and decrease in somatomotor and default mode networks, compared to the healthy controls. More importantly, the disrupted functional connectivity and nodal efficiency significantly correlated with dimensional ADHD scores. Conclusions: We clearly demonstrate the feasibility and potential of fNIRS-based connectome technique in ADHD or other neurological diseases in the future.
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Affiliation(s)
- Mengjing Wang
- Beijing Normal University, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China
| | - Zhishan Hu
- Beijing Normal University, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China
| | - Lu Liu
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, China
- Peking University Sixth Hospital, National Clinical Research Center for Mental Disorders, Beijing, China
- Peking University, National Health Commission Key Laboratory of Mental Health, Beijing, China
| | - Haimei Li
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, China
- Peking University Sixth Hospital, National Clinical Research Center for Mental Disorders, Beijing, China
- Peking University, National Health Commission Key Laboratory of Mental Health, Beijing, China
| | - Qiujin Qian
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, China
- Peking University Sixth Hospital, National Clinical Research Center for Mental Disorders, Beijing, China
- Peking University, National Health Commission Key Laboratory of Mental Health, Beijing, China
| | - Haijing Niu
- Beijing Normal University, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China
- Beijing Normal University, Center of Social Welfare Studies, Beijing, China
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