Brain Functional Connectivity Research Articles

TMS-induced plasticity improving cognitive control in OCD II: Task-based neural predictors of treatment response

ObjectiveRepetitive transcranial magnetic stimulation (rTMS) has the potential to increase the clinical effect of exposure with response prevention (ERP) psychotherapy for obsessive-compulsive disorder (OCD). We investigated the use of task-based functional MRI (tb-fMRI) for predicting clinical outcomes to different rTMS protocols combined with ERP in OCD. Method61 adults with OCD underwent rTMS and ERP and were randomized to different high frequency rTMS conditions: left dorsolateral prefrontal cortex (DLPFC; n=19), left pre-supplementary motor area (preSMA; n=23), and control stimulation at the vertex at low intensity (n=19). The Tower of London task and Stop-Signal Task were used to assess pretreatment activation during planning and inhibitory control, respectively. We adopted a Bayesian region-based approach to test whether clinical improvement can be predicted by tb-fMRI-derived measures of task-related brain activation or functional connectivity between task-relevant regions and the bilateral amygdala. ResultsFor the vertex group, but not the DLPFC/preSMA rTMS conditions, higher activation in several task-relevant regions during planning and response inhibition, and lower error-related activation, corresponded with better short-term clinical improvement. Lower precuneus activation with increased planning taskload correlated with symptom reduction in the DLPFC group. In the preSMA group, higher error-related activation and lower inhibition-related insular-amygdalar connectivity was associated with symptom reduction. ConclusionsPretreatment tb-fMRI-derived measures of activation and connectivity during planning and inhibition-related processes are associated with clinical response for specific rTMS conditions in OCD. Future placebo-controlled trials with larger sample sizes should combine clinical information and neural correlates to improve prediction of clinical outcome.

Aberrant brain structural-functional connectivity coupling associated with cognitive dysfunction in different cerebral small vessel disease burdens.

Emerging evidence suggests that cerebral small vessel disease (CSVD) pathology changes brain structural connectivity (SC) and functional connectivity (FC) networks. Although network-level SC and FC are closely coupled in the healthy population, how SC-FC coupling correlates with neurocognitive outcomes in patients with different CSVD burdens remains largely unknown. Using multimodal MRI, we reconstructed whole-brain SC and FC networks for 54 patients with severe CSVD burden (CSVD-s), 106 patients with mild CSVD burden (CSVD-m), and 79 healthy controls. We then investigated the aberrant SC-FC coupling and functional network topology in CSVD and their correlations with cognitive dysfunction. Compared with controls, the CSVD-m patients showed no significant change in any SC-FC coupling, but the CSVD-s patients exhibited significantly decreased whole-brain (p = 0.014), auditory/motor (p = 0.033), and limbic modular (p = 0.011) SC-FC coupling. For functional network topology, despite no change in global efficiency, CSVD-s patients exhibited significantly reduced nodal efficiency of the bilateral amygdala (p = 0.024 and 0.035) and heschl gyrus (p = 0.001 and 0.005). Notably, for the CSVD-s patients, whole-brain SC-FC coupling showed a significantly positive correlation with MoCA (r = 0.327, p = 0.020) and SDMT (r = 0.373, p = 0.008) scores, limbic/subcortical modular SC-FC coupling showed a negative correlation (r = -0.316, p = 0.025) with SCWT score, and global/local efficiency (r = 0.367, p = 0.009 and r = 0.353, p = 0.012) showed a positive correlation with AVLT score. For the CSVD-m group, whole-brain and auditory/motor modular SC-FC couplings showed significantly positive correlations with SCWT (r = 0.217, p = 0.028 and r = 0.219, p = 0.027) and TMT (r = 0.324, p = 0.001 and r = 0.245, p = 0.013) scores, and global/local efficiency showed positive correlations with AVLT (r = 0.230, p = 0.020 and r = 0.248, p = 0.012) and SDMT (r = 0.263, p = 0.008 and r = 0.263, p = 0.007) scores. Our findings demonstrated that decreased whole-brain and module-dependent SC-FC coupling associated with reduced functional efficiency might underlie more severe burden and worse cognitive decline in CSVD. SC-FC coupling might serve as a more sensitive neuroimaging biomarker of CSVD burden and provided new insights into the pathophysiologic mechanisms of clinical development of CSVD.

Maternal prenatal social disadvantage and neonatal functional connectivity: Associations with psychopathology symptoms at age 12 months.

Recent research has reported effects of socioeconomic status on neurobehavioral development as early as infancy, including positive associations between income and brain structure, functional connectivity, and behavior later in childhood (Ramphal, Whalen, et al., 2020; Triplett et al., 2022). This study extends this literature by investigating the relation of maternal prenatal social disadvantage (PSD) to neonatal amygdala and hippocampus functional connectivity and whether socioeconomic-related alterations in functional connectivity subsequently predict behavior at age 12 months in a large, socioeconomically diverse sample (N = 261 mother-infant dyads). PSD was assessed across gestation; neonatal magnetic resonance imaging was completed within the first weeks of life; and infant internalizing and externalizing symptoms were evaluated using the Infant-Toddler Social and Emotional Assessment at age 12 months. The results showed that PSD was significantly related to neonatal right amygdala and left hippocampus functional connectivity with prefrontal and motor-related regions. Social disadvantage-related right amygdala and left hippocampus functional connectivity with these regions was subsequently related to infant externalizing and internalizing symptoms at age 12 months. Building off an emerging literature exploring prenatal impacts on neonatal functional connectivity, this study further emphasizes the important role of the maternal environment during gestation on infant brain function and its relationship with externalizing and internalizing behavior in the first years of life. The results suggest that the prenatal socioeconomic environment may be a promising target for interventions aimed at improving infant neurobehavioral outcomes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Common and unique brain aging patterns between females and males quantified by large-scale deep learning.

There has been extensive evidence that aging affects human brain function. However, there is no complete picture of what brain functional changes are mostly related to normal aging and how aging affects brain function similarly and differently between males and females. Based on resting-state brain functional connectivity (FC) of 25,582 healthy participants (13,373 females) aged 49-76 years from the UK Biobank project, we employ deep learning with explainable AI to discover primary FCs related to progressive aging and reveal similarity and difference between females and males in brain aging. Using a nested cross-validation scheme, we conduct 4200 deep learning models to classify all paired age groups on the main data for females and males separately and then extract gender-common and gender-specific aging-related FCs. Next, we validate those FCs using additional 21,000 classifiers on the independent data. Our results support that aging results in reduced brain functional interactions for both females and males, primarily relating to the positive connectivity within the same functional domain and the negative connectivity between different functional domains. Regions linked to cognitive control show the most significant age-related changes in both genders. Unique aging effects in males and females mainly involve the interaction between cognitive control and the default mode, vision, auditory, and frontoparietal domains. Results also indicate females exhibit faster brain functional changes than males. Overall, our study provides new evidence about common and unique patterns of brain aging in females and males.

Early screening of post-stroke fall risk: A simultaneous multimodal fNIRs-EMG study.

Stroke is the third-leading cause of death and disability, and poststroke falls (PSF) are common at all stages after stroke and could even lead to injuries or death. Brain information from functional near-infrared spectroscopy (fNIRs) may precede conventional imaging and clinical symptoms but has not been systematically considered in PSF risk prediction. This study investigated the difference in brain activation between stroke patients and healthy subjects, and this study was aimed to explore fNIRs biomarkers for early screening of PSF risk by comparing the brain activation in patients at and not at PSF risk. In this study, we explored the differences in brain activation and connectivity between stroke and healthy subjects by synchronizing the detection of fNIRs and EMG tests during simple (usual sit-to-stand) and difficult tasks (sit-to-stand based on EMG feedback). Thereby further screened for neuroimaging biomarkers for early prediction of PSF risk by comparing brain activation variability in poststroke patients at and not at fall risk during simple and difficult tasks. The area under the ROC curve (AUROC), sensitivity, and specificity were used to compare the diagnostic effect. A total of 40 patients (22 not at and 18 at PSF risk) and 38 healthy subjects were enrolled. As the difficulty of standing task increased, stroke patients compared with healthy subjects further increased the activation of the unaffected side of supplementary motor area (H-SMA) and dorsolateral prefrontal cortex-Brodmann area 46 (H-DLFC-BA46) but were unable to increase functional connectivity (Group*Task: p < 0.05). More importantly, the novel finding showed that hyperactivation of the H-SMA during a simple standing task was a valid fNIRs predictor of PSF risk [AUROC 0.74, p = 0.010, sensitivity 77.8%, specificity 63.6%]. This study provided novel evidence that fNIR-derived biomarkers could early predict PSF risk that can facilitate the widespread use of real-time assessment tools in early screening and rehabilitation. Meanwhile, this study demonstrated that the higher brain activation and inability to increase the brain functional connectivity in stroke patients during difficult task indicated the inefficient use of brain resources.

Graph Convolutional Neural Network Based Emotion Recognition with Brain Functional Connectivity Network

Graph Convolutional Neural Network Based Emotion Recognition with Brain Functional Connectivity Network

Exploring age-related functional brain changes during audio-visual integration tasks in early to mid-adulthood

The seamless integration of visual and auditory information is a fundamental aspect of human cognition. Although age-related functional changes in Audio-Visual Integration (AVI) have been extensively explored in the past, thorough studies across various age groups remain insufficient. Previous studies have provided valuable insights into age-related AVI using EEG-based sensor data. However, these studies have been limited in their ability to capture spatial information related to brain source activation and their connectivity. To address these gaps, our study conducted a comprehensive audio-visual integration task with a specific focus on assessing the brain maturation effects in various age groups, particularly in early-mid adulthood. We presented visual, auditory, and audio-visual stimuli and recorded EEG data from Young (18–25 years), Transition (26–33 years), and Middle (34–50 years) age cohort healthy participants. We utilized source-based features for the classification of these age groups. We aimed to understand how aging affects brain activation and functional connectivity among hubs during audio-visual tasks. Our findings unveiled diminished levels of brain activation among middle-aged individuals, which escalate when exposed to AVI stimuli. Lower frequency bands showed substantial changes with increasing age during AVI. Our results demonstrated that implementing the k-means elbow method during the AVI task successfully categorized brain regions into five distinct brain networks. Additionally, we observed increased functional connectivity in middle age, particularly in the frontal, temporal, and occipital regions. These results highlight the compensatory neural mechanisms involved in aging during cognitive tasks.

Transient alteration of Awareness triggered by direct electrical stimulation of the brain

BackgroundAwareness is a state of consciousness that enables a subject to interact with the environment. Transient alteration of awareness (AA) is a disabling sign of many types of epileptic seizures. The brain mechanisms of awareness and its alteration are not well known. Objective/HypothesisTransient and isolated AA induced by electrical brain stimulation during a stereoelectroencephalography (SEEG) recording represents an ideal model for studying the associated modifications of functional connectivity and locating the hubs of awareness networks. MethodsWe investigated the SEEG signals-based brain functional connectivity (FC) changes vs background occurring during AA triggered by three thalamic and two insular stimulations in three patients explored by SEEG in the frame of presurgical evaluation for focal drug-resistant epilepsy. The results were compared to the stimulations of the same sites that did not induce clinical changes (negative stimulations). ResultsWe observed decreased node strength in the pulvinar, insula, and parietal associative cortices during the thalamic and insular stimulations that induced AA. The link strengths characterizing functional coupling between the thalamus and the insular, prefrontal, temporal, or parietal associative cortices were also decreased. In contrast, there was an increased synchronization between the precuneus and the temporal lateral cortex. These FC changes were absent during the negative stimulations. ConclusionOur study highlights the role of the pulvinar, insular, and parietal hubs in maintaining the awareness networks and paves the way for invasive or non-invasive neuromodulation protocols to reduce AA manifestations during epileptic seizures.

Painful stimulation increases functional connectivity between supplementary motor area and thalamus in patients with small fibre neuropathy.

The lead symptom of small fibre neuropathy (SFN) is neuropathic pain. Recent functional magnetic resonance imaging (fMRI) studies have indicated central changes in SFN patients of different etiologies. However, less is known about brain functional connectivity during acute pain processing in idiopathic SFN. We conducted fMRI with thermal heat pain application (left volar forearm) in 32 idiopathic SFN patients and 31 healthy controls. We performed functional connectivity analyses with right supplementary motor area (SMA), left insula, and left caudate nucleus (CN) as seed regions, respectively. Since pathogenic gain-of-function variants in voltage gated sodium channels (Nav) have been linked to SFN pathophysiology, explorative connectivity analyses were performed in a homogenous subsample of patients carrying rare heterozygous missense variants. For right SMA, we found significantly higher connectivity with the right thalamus in SFN patients compared to controls. This connectivity correlated significantly with intraepidermal nerve fibre density, suggesting a link between peripheral and central pain processing. We found significantly reduced connections between right SMA and right middle frontal gyrus in patients with Nav variants. Likewise, connectivity between left CN and right frontal pole was decreased. Aberrant functional connectivity in SFN is in line with previous research on other chronic pain syndromes. Functional connectivity changes may be linked to SFN, highlighting the need to determine if they result from peripheral changes causing abnormal somatosensory processing. This understanding may be crucial for assessing their impact on painful symptoms and therapy response. We found increased functional connectivity between SMA and thalamus during painful stimulation in patients with idiopathic SFN. Connectivity correlated significantly with intraepidermal nerve fibre density, suggesting a link between peripheral and central pain processing. Our findings emphasize the importance of investigating functional connectivity changes as a potential feature of SFN.

Risk factor patterns define social anxiety subtypes in adolescents with brain and clinical feature differences.

Social anxiety disorder (SAD) is one of the most common psychiatric disorders in adolescents. The heterogeneity of both symptoms and etiology is an essential source of difficulties in the treatment and prevention of SAD. The study aimed to identify subtypes of adolescent SAD based on etiology-related phenotype dimensions and examine symptom and brain associations of the subtypes. We used a deeply phenotyped sample (47 phenotype subscales from 13 measures) of adolescents with SAD (n = 196) and healthy controls (n = 109) to extract etiology-relevant risk factors, based on which we identified subtypes of SAD. We compared the subtypes on clinical characteristics and brain morphometrics and functional connectivity, and examined subtype-specific links between risk factors, brain aberrance, and clinical characteristics. We identified six etiology-relevant risk factors and two subtypes of adolescent SAD. One subtype showed mainly elevated negative emotionality trait and coping style and diminished positive emotionality trait and coping style, while the other additionally had significantly high environmental risk factors, more severe impairments in social functioning, and significant abnormalities in brain structure and function. There were subtype-specific links between the risk factor profiles, brain aberrance, and clinical characteristics. The finding suggests two etiology-based subtypes of adolescent SAD, providing novel insights to the diversity of pathological pathways and precise intervention strategies.

Uncovering the correlation between neurotransmitter-specific functional connectivity and multidimensional anxiety in a non-clinical cohort.

Research on anxiety faces challenges due to the wide range of symptoms, making it difficult to determine if different aspects of anxiety are linked to distinct neurobiological processes. Both alterations in functional brain connectivity (FC) and monoaminergic neurotransmitter systems are implicated as potential neural bases of anxiety. We aimed to investigate whole-brain FC involving monoaminergic nuclei and its association with anxiety dimensions in 178 non-clinical participants. Nine anxiety-related scales were used, encompassing trait and state anxiety scores, along with measures of cost-probability, hypervigilance, reward-punishment sensitivity, uncertainty, and trait worry. Resting-state functional magnetic resonance imaging data were acquired, focusing on seven brainstem regions representing serotonergic, dopaminergic, and noradrenergic nuclei, with their FC patterns voxel-wise correlated with the scales. All models underwent family-wise-error correction for multiple comparisons. We observed intriguing relationships: trait and state anxiety scores exhibited opposing correlations in FC between the dorsal raphe nucleus and the paracingulate gyrus. Additionally, we identified shared neural correlates, such as a negative correlation between the locus coeruleus and the frontal pole. This connection was significantly associated with scores on measures of probability, hypervigilance, reward sensitivity, and trait worry. These findings underscore the intricate interplay between anxiety dimensions and subcortico-cortical FC patterns, shedding light on the underlying neural mechanisms governing anxiety.

The Involvement of the Ventral Tegmental Area in the Electroacupuncture Alleviation of Anxiety-Like Behaviors Induced by Chronic Restraint Stress in Mice.

Emotional stress is a significant environmental risk factor for various mental health disabilities, such as anxiety. Electroacupuncture (EA) has been demonstrated to have pronounced anxiolytic effects. However, the neural mechanisms underlying these effects and their contribution to behavioral deficits remain poorly understood. Here, we addressed these issues using a classical mouse anxiety model induced by chronic restraint stress (CRS).Anxiety-like behaviors were evaluated with the open field test and elevated plus maze. Neuronal activation in various brain regions was marked using c-Fos, followed by calculations of interregional correlation to characterize a network that became functionally active following EA at the HT7 acupoint (EA-HT7). We selected the hub regions and further investigated their functions and connections in regulating anxiety-like behaviors by using a combination of chemogenetic manipulations and behavioral testing. CRS exposure induced anxiety-like behaviors. Interestingly, EA-HT7 mitigated these behavioral abnormalities. The c-Fos expression in 30 brain areas revealed a vital brain network for acupuncture responsiveness in naïve mice. Neural activity in the NAcSh (nucleus accumbens shell), BNST (bed nucleus of the stria terminalis), VMH (Ventromedial Hypothalamus), ARC (arcuate nucleus), dDG (dorsal dentate gyrus), and VTA (ventral tegmental area) was significantly altered following acupuncture. Notably, both c-Fos immunostaining and brain functional connectivity analysis revealed the significant activation of VTA following EA-HT7. Interestingly, blocking the VTA eliminated the anxiolytic effects of EA-HT7, whereas chemogenetic activation of the VTA replicated the therapeutic effects of EA-HT7. EA-HT7 has demonstrated benefits in treating anxiety and enhances brain functional connectivity. The VTA is functionally associated with the anxiolytic effects of EA-HT7.

Comorbidity of concussion and depression alters brain functional connectivity in collegiate student-athletes

Depression and concussion are highly prevalent neuropsychological disorders that often occur simultaneously. However, due to the high degree of symptom overlap between the two events, including but not limited to headache, sleep disturbances, appetite changes, fatigue, and difficulty concentrating, they may be treated in isolation. Thus, clinical awareness of additive symptom load may be missed. This study measures neuropsychological and electroencephalography (EEG) alpha band coherence differences in collegiate student-athletes with history of comorbid depression and concussion, in comparison to those with a single morbidity and healthy controls (HC). 35 collegiate athletes completed neuropsychological screenings and EEG measures. Participants were grouped by concussion and depression history. Differences in alpha band coherence were calculated using two-way ANOVA with post hoc correction for multiple comparisons. Comorbid participants scored significantly worse on neuropsychological screening, BDI-FS, and PCSS than those with a single morbidity and HC. Two-way ANOVA by group revealed significant main effects of alpha band coherence for concussion, depression, and their interaction term. Post-hoc analysis showed that comorbid participants had more abnormal alpha band coherence than single morbidity, when compared to HC. Comorbidity of concussion and depression increased symptom reporting and revealed more altered alpha band coherence than single morbidity, compared to HC. The abnormalities of the comorbid group exclusively showed decreased alpha band coherence in comparison to healthy controls. The comorbidity of depression and SRC has a compounding effect on depression symptoms, post-concussion symptoms, and brain functional connectivity. This research demonstrates a promising objective measure in comorbid individuals, previously only measured via subjective symptom reporting.

Topological properties of white matter network in first untreated children and adolescents with obsessive-compulsive disorder

Objective: To investigate the topological properties of the white matter network in the drug-naive first-episode children and adolescent with obsessive-compulsive disorder (OCD). Methods: This study was a case-control study. First-episode OCD childhren and adolescents(OCD group) who were treated in the outpatient or inpatient department of the Second Affiliated Hospital of Xinxiang Medical University from July 2018 to October 2023 were collected as the research subjects. Healthy controls (control group)matched by gender, age and education level were used as controls. Deterministic tractography technique was used to construct the whole brain white matter structural network, and graph theory analysis method was used to analyze the topological attributes of the whole brain white matter structure network in OCD children and adolescents. A network-based statistical method was used to examine the inter-group differences in the functional connectivity strength of the whole brain network. Results: Finally, 31 cases were included in the obsessive-compulsive disorder group, including 22 males and 9 females, with an age of (13.5±1.6) years; There were 34 cases in the control group, including 22 males and 12 females, with an age of (12.7±1.4) years. The global efficiency and local efficiency of the OCD group (0.62±0.03, 0.70±0.07) were significantly higher than those of the control group (0.50±0.06, 0.54±0.21) [both P<0.01, false discovery rate(FDR)correction]; while the characteristic path length (1.77±0.08) was significantly smaller than that of the control group (2.10±0.23) (P<0.01, FDR correction).The centrality comparison of nodal betweenness centrality showed that in the OCD group, the connections were enhanced in the left lateral orbitofrontal gyrus, right dorsal agranular insula, left dorsal granular insula, right granular insula, right posterior central gyrus main area of parietal lobe, left ventral granular insula, granular insula, left ventral granulosa, left granular insula, and left dorsal agranular insula [all P<0.001, family wise error (FWE) correction], while the connection of right thalamic was weakened (P<0.001, FWE correction), There were sub-networks characterized by significantly enhanced connection strength of relevant nodes in subcortical, visual network, and default mode network (P<0.05, permutation test 5 000 times). Conclusions: The topological properties of the brain's functional network in children and adolescents with OCD exhibit abnormalities, indicating an immature state of brain functional connectivity.

Construction and analysis of brain metabolic network in temporal lobe epilepsy patients based on 18F-FDG PET

The establishment of brain metabolic network is based on 18fluoro-deoxyglucose positron emission computed tomography ( 18F-FDG PET) analysis, which reflect the brain functional network connectivity in normal physiological state or disease state. It is now applied to basic and clinical brain functional network research. In this paper, we constructed a metabolic network for the cerebral cortex firstly according to 18F-FDG PET image data from patients with temporal lobe epilepsy (TLE).Then, a statistical analysis to the network properties of patients with left or right TLE and controls was performed. It is shown that the connectivity of the brain metabolic network is weakened in patients with TLE, the topology of the network is changed and the transmission efficiency of the network is reduced, which means the brain metabolic network connectivity is extensively impaired in patients with TLE. It is confirmed that the brain metabolic network analysis based on 18F-FDG PET can provide a new perspective for the diagnose and therapy of epilepsy by utilizing PET images.

Investigating changes of functional brain networks in major depressive disorder by graph theoretical analysis of resting-state fMRI

BackgroundMajor Depressive Disorder (MDD), as a chronic mental disorder, causes changes in mood, thoughts, and behavior. The pathophysiology of the disorder and its treatment are still unknown. One of the most notable changes observed in patients with MDD through fMRI is abnormal functional brain connectivity. MethodsPreprocessed data from 60 MDD patients and 60 normal controls (NCs) were selected, which has been performed using the DPARSF toolbox. The whole-brain functional networks and topologies were extracted using graph theory-based methods. A two-sample, two-tailed t-test was used to compare the topological features of functional brain networks between the MDD and NCs groups using the DPABI-Net/Statistical Analysis toolbox. ResultsThe obtained results showed a decrease in both global and local efficiency in MDD patients compared to NCs, and specifically, MDD patients showed significantly higher path length values. Acceptable p-values were obtained with a small sample size and less computational volume compared to the other studies on large datasets. At the node level, MDD patients showed decreased and relatively decreased node degrees in the sensorimotor network (SMN) and the dorsal attention network (DAN), respectively, as well as decreased node efficiency in the SMN, default mode network (DMN), and DAN. Also, MDD patients showed slightly decreased node efficiency in the visual networks (VN) and the ventral attention network (VAN), which were reported after FDR correction with Q < 0.05. LimitationsAll participants were Chinese. ConclusionsCollectively, increased path length, decreased global and local efficiency, and also decreased nodal degree and efficiency in the SMN, DAN, DAN, VN, and VAN were found in patients compared to NCs.

Disrupted brain functional connectivity as early signature in cognitively healthy individuals with pathological CSF amyloid/tau

Alterations in functional connectivity (FC) have been observed in individuals with Alzheimer’s disease (AD) with elevated amyloid (Aβ) and tau. However, it is not yet known whether directed FC is already influenced by Aβ and tau load in cognitively healthy (CH) individuals. A 21-channel electroencephalogram (EEG) was used from 46 CHs classified based on cerebrospinal fluid (CSF) Aβ tau ratio: pathological (CH-PAT) or normal (CH-NAT). Directed FC was estimated with Partial Directed Coherence in frontal, temporal, parietal, central, and occipital regions. We also examined the correlations between directed FC and various functional metrics, including neuropsychology, cognitive reserve, MRI volumetrics, and heart rate variability between both groups. Compared to CH-NATs, the CH-PATs showed decreased FC from the temporal regions, indicating a loss of relative functional importance of the temporal regions. In addition, frontal regions showed enhanced FC in the CH-PATs compared to CH-NATs, suggesting neural compensation for the damage caused by the pathology. Moreover, CH-PATs showed greater FC in the frontal and occipital regions than CH-NATs. Our findings provide a useful and non-invasive method for EEG-based analysis to identify alterations in brain connectivity in CHs with a pathological versus normal CSF Aβ/tau.

Identifying developmental changes in functional brain connectivity associated with cognitive functioning in children and adolescents with ADHD

Youth diagnosed with Attention-Deficit/Hyperactivity Disorder (ADHD) often show deficits in various measures of higher-level cognition, such as, executive functioning. Poorer cognitive functioning in children with ADHD has been associated with differences in functional connectivity across the brain. However, little is known about the developmental changes to the brain’s functional properties linked to different cognitive abilities in this cohort. To characterize these changes, we analyzed fMRI data (ADHD = 373, NT = 106) collected while youth between the ages of 6 and 16 watched a short movie-clip. We applied machine learning models to identify patterns of network connectivity in response to movie-watching that differentially predict cognitive abilities in our cohort. Using out-of-sample cross validation, our models successfully predicted IQ, visual spatial, verbal comprehension, and fluid reasoning in children (ages 6 – 11), but not in adolescents with ADHD (ages 12–16). Connections with the default mode, memory retrieval, and dorsal attention were driving prediction during early and middle childhood, but connections with the somatomotor, cingulo-opercular, and frontoparietal networks were more important in middle childhood. This work demonstrated that machine learning approaches can identify distinct functional connectivity profiles associated with cognitive abilities at different developmental stages in children and adolescents with ADHD.

Decline in Sensory Integration in Old Age and Its Related Functional Brain Connectivity Correlates Observed during a Virtual Reality Task.

Sensory integration is an essential human function whose decline impacts quality of life, particularly in older adults. Herein, we propose an arm-reaching task based on a virtual reality head-mounted display system to assess sensory integration in daily life, and we examined whether reaching task performance was associated with resting-state functional connectivity (rsFC) between the brain regions involved in sensory integration. We hypothesized that declining sensory integration would affect performance during a reaching task with multiple cognitive loads. Using a task in which a young/middle-aged group showed only small individual differences, older adults showed large individual differences in the gap angle between the reaching hand and the target position, which was used to assess sensory integration function. Additionally, rsfMRI data were used to identify correlations between rsFC and performance in older adults, showing that performance was correlated with connectivity between the primary motor area and the left inferior temporal gyrus and temporo-occipital region. Connectivity between areas is related to visuomotor integration; thus, the results suggest the involvement of visuomotor integration in the decline of sensory integration function and the validity of the gap angle during this VR reaching task as an index of functional decline.

A multimodal approach for fostering knowledge transfer in engineering design activity: an eye-tracking and fNIRS study

Knowledge transfer in engineering design activity involves effectively applying prior practical experience in novel contexts. While related works fostering knowledge transfer focus on educational practices and experience generalisation, recent advancements enable us to analyze its complex cognitive processes using neuroimaging technology. This paper proposes a multimodal approach for facilitating knowledge transfer in engineering design, utilising functional near-infrared spectroscopy (fNIRS) and eye-tracking technologies based on neurocognitive profiling. We conducted knowledge transfer experiments using mixed and extended design tasks. Meanwhile, The analysis focused on gaze duration, gaze counts, brain region activation levels, functional connectivity, and effective connectivity of the participants. Finally, we employed stepwise linear regression to identify significant and potential associated factors of knowledge transfer. By combining eye-tracking predictors and brain network predictors, a multivariate linear discriminant analysis (LDA) significantly differentiated between participants in near-transferred and far-transferred states, achieving an accuracy of 91.16% using leave-one-out cross-validation. The ‘basic-supplementary-target task’ method effectively improved the knowledge transfer performance by 27.6%. Our findings demonstrate the efficacy of the proposed multimodal approach in facilitating knowledge transfer in engineering design activities.