Specific Functional Connectivity Research Articles

Functional connectivity of the posterior cingulate cortex in autism spectrum disorder

The purpose of this study was to assess the functional connectivity of the posterior cingulate cortex in autism spectrum disorder (ASD). We used resting-state functional magnetic resonance imaging (rsfMRI) brain scans of adolescents diagnosed with ASD and a neurotypical control group. The Autism Brain Imaging Data Exchange (ABIDE) consortium was utilized to acquire data from the University of Michigan (145 subjects) and data from the New York University (183 subjects). The posterior cingulate cortex showed reduced connectivity with the anterior cingulate cortex for the ASD group compared to the control group. These two brain regions have previously both been linked to ASD symptomology. Specifically, the posterior cingulate cortex has been associated with behavioral control and executive functions, which appear to be responsible for the repetitive and restricted behaviors (RRB) in ASD. Our findings support previous data indicating a neurobiological basis of the disorder, and the specific functional connectivity changes involving the posterior cingulate cortex and anterior cingulate cortex may be a potential neurobiological biomarker for the observed RRBs in ASD.

A longitudinal evaluation of personalized intrinsic network topography and cognitive decline in Parkinson's disease.

Resting state functional magnetic resonance imaging (R-fMRI) offers insight into how synchrony within and between brain networks is altered in disease states. Individual and disease-related variability in intrinsic connectivity networks may influence our interpretation of R-fMRI data. We used a personalized approach designed to account for individual variation in the spatial location of correlation maxima to evaluate R-fMRI differences between Parkinson's disease (PD) patients who showed cognitive decline, those who remained cognitively stable and cognitively stable controls. We compared fMRI data from these participant groups, studied at baseline and 18 months later, using both network-based statistics (NBS) and calculations of mean inter- and intra-network connectivity within pre-defined functional networks. The NBS analysis showed that PD participants who remained cognitively stable showed exclusively (at baseline) or predominantly (at follow-up) increased intra-network connectivity, whereas decliners showed exclusively reduced intra-network and inter- (ventral attention and default mode) connectivity, in comparison with the control group. Evaluation of mean connectivity between all regions of interest (ROIs) within a priori networks showed that decliners had consistently reduced inter-network connectivity for ventral attention, somatomotor, visual and striatal networks and reduced intra-network connectivity for ventral attention network to striatum and cerebellum. These findings suggest that specific functional connectivity covariance patterns differentiate PD cognitive subtypes and may predict cognitive decline. Further, increased intra and inter-network synchrony may support cognitive function in the face of PD-related network disruptions.

Anterior and posterior default mode network functional connectivity and segregation in aging

AbstractBackgroundThe default mode network (DMN) supports memory performance and has been shown to be vulnerable to the effects of aging. The posterior DMN (pDMN) is an early region of amyloid‐β (Aβ) accumulation, which may lead to disrupted communication within/between subnetworks of the DMN. Using resting state functional connectivity (FC), we tested whether communication within and between the pDMN and anterior DMN (aDMN) were altered by aging and Aβ pathology and related to memory performance. We also tested segregation FC between the aDMN and pDMN.MethodData from 27 cognitively normal adults (69.6 years, 59% females) with resting state fMRI (rsfMRI), 18F‐florbetapir (FBP) PET to measure Aβ, and the Rey Auditory Verbal LearningTest (RAVLT) delayed recall to assess memory were analyzed. The rsfMRI data were preprocessed using CONN toolbox. ROI‐to‐ROI FC matrices were constructed for regions included in the aDMN and pDMN. We calculated: (1) the average FC within each network (Zw), (2) average FC between the aDMN and pDMN (Zb), and (3) network segregation [(Zw‐Zb)/Zw] for each DMN network. Global FBP SUVR was calculated as the mean across association cortical regions, and a cutoff of 1.11 was used to determine Aβ positivity. Analyses included the FC variables and their associations with age, Aβ, and memory.ResultOlder age was associated with reduced network segregation of the pDMN (r = ‐0.53, p = 0.004), and a trend level association for reduced within‐pDMN FC (r = ‐0.37, p = 0.057). Global FBP SUVR was not associated with FC or network segregation, and there was no significant difference in FC between Aβ groups (controlling for age). There was a trend‐level association between better memory performance and stronger FC between aDMN and pDMN (r = 0.37, p = 0.066; controlling for age and education).ConclusionResults demonstrated that aging is associated with specific FC disruptions of pDMN, leading to reduced specialization of processing as indexed by network segregation. Moreover, increased communication between DMN subnetworks may support memory in aging. Future analyses in a larger sample will further test the association between Alzheimer’s pathology and functional changes to DMN subnetworks.

Divergent electroencephalogram resting-state functional network alterations in subgroups of autism spectrum disorder: a symptom-based clustering analysis.

Autism spectrum disorder (ASD) is characterized by etiological and phenotypic heterogeneity. Despite efforts to categorize ASD into subtypes, research on specific functional connectivity changes within ASD subgroups based on clinical presentations is limited. This study proposed a symptom-based clustering approach to identify subgroups of ASD based on multiple clinical rating scales and investigate their distinct Electroencephalogram (EEG) functional connectivity patterns. Eyes-opened resting-state EEG data were collected from 72 children with ASD and 63 typically developing (TD) children. A data-driven clustering approach based on Social Responsiveness Scales-Second Edition and Vinland-3 scores was used to identify subgroups. EEG functional connectivity and topological characteristics in four frequency bands were assessed. Two subgroups were identified: mild ASD (mASD, n = 37) and severe ASD (sASD, n = 35). Compared to TD, mASD showed increased functional connectivity in the beta band, while sASD exhibited decreased connectivity in the alpha band. Significant between-group differences in global and regional topological abnormalities were found in both alpha and beta bands. The proposed symptom-based clustering approach revealed the divergent functional connectivity patterns in the ASD subgroups that was not observed in typical ASD studies. Our study thus provides a new perspective to address the heterogeneity in ASD research.

Intrinsic brain functional connectivity predicts treatment-related motor complications in early Parkinson’s disease patients

BackgroundTreatment-related motor complications may develop progressively over the course of Parkinson’s disease (PD).ObjectiveWe investigated intrinsic brain networks functional connectivity (FC) at baseline in a cohort of early PD patients which successively developed treatment-related motor complications over 4 years.MethodsBaseline MRI images of 88 drug-naïve PD patients and 20 healthy controls were analyzed. After the baseline assessments, all PD patients were prescribed with dopaminergic treatment and yearly clinically re-assessed. At the 4-year follow-up, 36 patients have developed treatment-related motor complications (PD-Compl) whereas 52 had not (PD-no-Compl). Single-subject and group-level independent component analyses were used to investigate FC changes within the major large-scale resting-state networks at baseline. A multivariate Cox regression model was used to explore baseline predictors of treatment-related motor complications at 4-year follow-up.ResultsAt baseline, an increased FC in the right middle frontal gyrus within the frontoparietal network as well as a decreased connectivity in the left cuneus within the default-mode network were detected in PD-Compl compared with PD-no-Compl. PD-Compl patients showed a preserved sensorimotor FC compared to controls. FC differences were found to be independent predictors of treatment-related motor complications over time.ConclusionOur findings demonstrated that specific FC differences may characterize drug-naïve PD patients more prone to develop treatment-related complications. These findings may reflect the presence of an intrinsic vulnerability across frontal and prefrontal circuits, which may be potentially targeted as a future biomarker in clinical trials.

Manipulating ΔFOSB in D1-Type Medium Spiny Neurons of the Nucleus Accumbens Reshapes Whole-Brain Functional Connectivity

BackgroundThe transcription factor ΔFOSB, acting in the nucleus accumbens, has been shown to control transcriptional and behavioral responses to opioids and other drugs of abuse. However, circuit-level consequences of ΔFOSB induction on the rest of the brain, which are required for its regulation of complex behavior, remain unknown. MethodsWe used an epigenetic approach in mice to suppress or activate the endogenous Fosb gene and thereby decrease or increase, respectively, levels of ΔFOSB selectively in D1-type medium spiny neurons of the nucleus accumbens and tested whether these modifications affect the organization of functional connectivity (FC) in the brain. We acquired functional magnetic resonance imaging data at rest and in response to a morphine challenge and analyzed both stationary and dynamic FC patterns. ResultsThe 2 manipulations modified brainwide communication markedly and differently. ΔFOSB down- and upregulation had overlapping effects on prefrontal- and retrosplenial cortex–centered networks, but also generated specific FC signatures for epithalamus (habenula) and dopaminergic/serotonergic centers, respectively. Analysis of dynamic FC patterns showed that increasing ΔFOSB essentially altered responsivity to morphine and uncovered striking modifications of the roles of the epithalamus and amygdala in brain communication, particularly upon ΔFOSB downregulation. ConclusionsThese novel findings illustrate how it is possible to link activity of a transcription factor within a single cell type of an identified brain region to consequent changes in circuit function brainwide by use of functional magnetic resonance imaging, and they pave the way for fundamental advances in bridging the gap between transcriptional and brain connectivity mechanisms underlying opioid addiction.

Functional connectivity modifications in monoaminergic circuits occur in fatigued MS patients treated with fampridine and amantadine.

Monoaminergic network dysfunction may have a role in multiple sclerosis (MS) fatigue pathogenesis. To investigate modifications of fatigue severity and resting state (RS) functional connectivity (FC) in monoaminergic networks of 45 fatigued MS patients after different symptomatic treatments. Patients were randomly, blindly assigned to fampridine (n = 15), amantadine (n = 15) or placebo (n = 15) treatment and underwent clinical and 3T-MRI evaluations at baseline (t0) and week 4 (w4), i.e. after four weeks of treatment. Fifteen healthy controls (HC) were enrolled. Dopamine-, noradrenaline- and serotonin-related RS FC was assessed by PET-guided constrained independent component analysis. At t0, MS patients showed widespread monoamine-related RS FC abnormalities. At w4, fatigue scores decreased in all groups (p = range < 0.001-0.002). Concomitantly, fampridine and amantadine patients showed increased insular RS FC in dopamine-related and noradrenaline-related networks (p < 0.001, uncorrected). Amantadine patients also showed increased RS FC of anterior cingulate cortex in dopamine-related and noradrenaline-related networks (p < 0.001, uncorrected). Placebo patients showed increased precuneus/middle cingulate RS FC in the noradrenaline-related network (p < 0.001, uncorrected). In fampridine and placebo patients, just tendencies towards correlations between RS FC and fatigue modifications were found. In MS patients, specific RS FC modifications in PET-guided monoaminergic networks were observed, concomitantly with fatigue improvements following treatment. EudraCT 2010-023678-38.

Brain circuits for maternal sensitivity and pain involving anterior cingulate cortex among mothers receiving buprenorphine treatment for opioid use disorder.

Opioid-induced deficits in maternal behaviors are well-characterized in rodent models. Amid the current epidemic of opioid use disorder (OUD), prevalence among pregnant women has risen sharply. Yet, the roles of buprenorphine replacement treatment for OUD (BT/OUD) in the brain functions of postpartum mothers are unclear. Using functional magnetic resonance imaging (fMRI), we have developed an evolutionarily conserved maternal behavior neurocircuit (MBN) model to study human maternal care versus defensive/aggressive behaviors critical to mother-child bonding. The anterior cingulate gyrus (ACC) is not only involved in the MBN for mother-child bonding and attachment, but also part of an opioid sensitive "pain-matrix". The literature suggests that prescription opioids produce physical and emotional "analgesic" effects by disrupting specific resting-state functional connectivity (rs-FC) of ACC to regions related to MBN. Thus, in this longitudinal study, we report findings of overlapping MBN and pain matrix circuits, for mothers with chronic exposure of BT/OUD. A total of 32 mothers were studied with 6 min rs-FC at 1 month (T1) and 4 months postpartum (T2), including seven on BT/OUD and 25 non-BT/OUD mothers as a comparison group. We analyzed rs-FC between the insula, putamen, and the dorsal anterior cingulate cortex (DACC) and rostral ACC (RACC), as the regions of interest that mediate opioid analgesia. BT/OUD mothers, as compared to non-BT/OUD mothers, showed less left insula-RACC rs-FC but greater right putamen-DACC rs-FC at T1, with these between-group differences diminished at T2. Some of these rs-FC results were correlated with the scores of postpartum parental bonding questionnaire. We found time-by-treatment interaction effects on DACC and RACC-dependent rs-FC, potentially identifying brain mechanisms for beneficial effects of BT, normalizing dysfunction of maternal brain and behavior over the first four months postpartum. This study complements recent studies to ascertain how BT/OUD affects maternal behaviors, mother-child bonding, and intersubjectivity and reveals potential MBN/pain-matrix targets for novel interventions.

Common and unique alterations of functional connectivity in major depressive disorder and bipolar disorder.

Major depressive disorder (MDD) and bipolar disorder (BD) are considered whole-brain disorders with some common clinical and neurobiological features. It is important to investigate neural mechanisms to distinguish between the two disorders. However, few studies have explored the functional dysconnectivity between the two disorders from the whole brain level. In this study, 117 patients with MDD, 65 patients with BD, and 116 healthy controls completed resting-state functional magnetic resonance imaging (R-fMRI) scans. Both edge-based network construction and large-scale network analyses were applied. Results found that both the BD and MDD groups showed decreased FC in the whole brain network. The shared aberrant network across patients involves the visual network (VN), sensorimotor network (SMN), dorsal attention network (DAN), and ventral attention network (VAN), which is related to the processing of external stimuli. The default mode network (DMN) and the limbic network (LN) abnormalities were only found in patients with MDD. Furthermore, results showed the highest decrease in edges of patients with MDD in between-network FC in SMN-VN, whereas in VAN-VN of patients with BD. Our findings indicated that both MDD and BD are extensive abnormal brain network diseases, mainly aberrant in those brain networks correlated to the processing of external stimuli, especially the attention network. Specific altered functional connectivity also was found in MDD and BD groups, respectively. These results may provide possible trait markers to distinguish the two disorders.

Brain dysconnectivity with heart failure.

Structural brain damage associated with heart failure is well described; however, little is known about associated changes in various specific brain functions that bear immediate clinical relevance. A satisfactory pathophysiological link between heart failure and decline in cognitive function is still missing. In the present study, we aim to detect functional correlates of heart failure in terms of alterations in functional brain connectivity (quantified by functional magnetic resonance imaging) related to cognitive performance assessed by neuropsychological testing. Eighty patients were post hoc grouped into subjects with and without coronary artery disease. The coronary artery disease patients were further grouped as presenting with or without heart failure according to the guidelines of the European Society of Cardiology. On the basis of resting-state functional magnetic resonance imaging, brain connectivity was investigated using network centrality as well as seed-based correlation. Statistical analysis aimed at specifying centrality group differences and potential correlations between centrality and heart failure-related measures including left ventricular ejection fraction and serum concentrations of N-terminal fragment of the pro-hormone brain-type natriuretic peptide. The resulting correlation maps were then analysed using a flexible factorial model with the factors 'heart failure' and 'cognitive performance'. Our core findings are: (i) A statistically significant network centrality decrease was found to be associated with heart failure primarily in the precuneus, i.e. we show a positive correlation between centrality and left ventricular ejection fraction as well as a negative correlation between centrality and N-terminal fragment of the pro-hormone brain-type natriuretic peptide. (ii) Seed-based correlation analysis showed a significant interaction between heart failure and cognitive performance related to a significant decrease of precuneus connectivity to other brain regions. We obtained these results by different analysis approaches indicating the robustness of the findings we report here. Our results suggest that the precuneus is a brain region involved in connectivity decline in patients with heart failure, possibly primarily or already at an early stage. Current models of Alzheimer's disease-having pathophysiological risk factors in common with cerebrovascular disorders-also consider reduced precuneus connectivity as a marker of brain degeneration. Consequently, we propose that heart failure and Alzheimer's disease exhibit partly overlapping pathophysiological paths or have common endpoints associated with a more or less severe decrease in brain connectivity. This is further supported by specific functional connectivity alterations between the precuneus and widely distributed cortical regions, particularly in patients showing reduced cognitive performance.

Diagnostic identification of chronic insomnia using ALFF and FC features of resting-state functional MRI and logistic regression approach

This study investigated whether the amplitude of low-frequency fluctuation (ALFF) and functional connectivity (FC) features could be used as potentially neurological markers to identify chronic insomnia (CI) using resting-state functional MRI and machine learning method logistic regression (LR). This study included 49 CI patients and 47 healthy controls (HC). Voxel-wise features, including the amplitude of low-frequency fluctuations (ALFF) and functional connectivity (FC), were extracted from resting-state functional magnetic resonance brain images. Then, we divided the data into two independent cohorts for training (44 CI patients and 42 HC patients), and independent validation (5 CI patients and 5 HC patients) by using logistic regression. The model was evaluated using 20 rounds of fivefold cross‑validation for training. In particular, a two-sample t-test (GRF corrected, p-voxel < 0.001, p-cluster < 0.05) was used for feature selection during the model training. Finally, single‑shot testing of the final model was performed on the independent validation cohort. A correlation analysis (Bonferroni correction, p < 0.05/4) was also conducted to determine whether the features contributing to the prediction were correlated with clinical characteristics, including the Insomnia Severity Index (ISI), Pittsburgh sleep quality index (PSQI), self-rating anxiety scale (SAS), and self-rating depression scale (SDS). Results showed that resting-state features had a discrimination accuracy of 86.40%, with a sensitivity of 93.00% and specificity of 79.80%. The area under the curve (AUC) was 0.89 (all {P}_{mathrm{permutation}}< 0.001). The ALFF and FC features showed significant differences between the CI patients and HC. The regions contributing to the prediction mainly included the anterior cingulate, prefrontal cortex, orbital part of the frontal lobe, angular gyrus, cingulate gyrus, praecuneus, parietal lobe, temporal gyrus, superior temporal gyrus, and middle temporal gyrus. Furthermore, some specific functional connectivity among related regions was positively correlated with the ISI, and also negatively related to the SDS in correlation analysis. Our current study suggested that ALFF and FC in the regions contributing to diagnostic identification might serve as potential neuromarkers for CI.

Increased functional connectivity patterns in mild Alzheimer's disease: A rsfMRI study.

Alzheimer's disease (AD) is the most common age-related neurodegenerative disorder. In view of our rapidly aging population, there is an urgent need to identify Alzheimer's disease (AD) at an early stage. A potential way to do so is by assessing the functional connectivity (FC), i.e., the statistical dependency between two or more brain regions, through novel analysis techniques. In the present study, we assessed the static and dynamic FC using different approaches. A resting state (rs)fMRI dataset from the Alzheimer's disease neuroimaging initiative (ADNI) was used (n = 128). The blood-oxygen-level-dependent (BOLD) signals from 116 regions of 4 groups of participants, i.e., healthy controls (HC; n = 35), early mild cognitive impairment (EMCI; n = 29), late mild cognitive impairment (LMCI; n = 30), and Alzheimer's disease (AD; n = 34) were extracted and analyzed. FC and dynamic FC were extracted using Pearson's correlation, sliding-windows correlation analysis (SWA), and the point process analysis (PPA). Additionally, graph theory measures to explore network segregation and integration were computed. Our results showed a longer characteristic path length and a decreased degree of EMCI in comparison to the other groups. Additionally, an increased FC in several regions in LMCI and AD in contrast to HC and EMCI was detected. These results suggest a maladaptive short-term mechanism to maintain cognition. The increased pattern of FC in several regions in LMCI and AD is observable in all the analyses; however, the PPA enabled us to reduce the computational demands and offered new specific dynamic FC findings.

Alterations of degree centrality and functional connectivity in classic trigeminal neuralgia.

Recent neuroimaging studies have indicated a wide range of structural and regional functional alterations in patients with classic trigeminal neuralgia (CTN). However, few studies have focused on the intrinsic functional characteristics of network organization in the whole brain. Therefore, the present study aimed to characterize the potential intrinsic dysconnectivity pattern of the whole brain functional networks at the voxel level using the degree centrality (DC) analysis in CTN patients. Thirty-four patients with CTN and twenty-nine well-matched healthy controls (HCs) participated in this study. All subjects underwent resting-state functional magnetic resonance imaging (rs-MRI) examination and clinical and neuropsychologic assessments. DC is a graph theory-based measurement that represents the overall functional connectivity (FC) numbers between one voxel and other brain voxels. We first investigated brain regions exhibiting abnormal DC, and further identified their perturbation on FC with other brain regions using a seed-based FC analysis in patients with CTN. In addition, correlation analyses were performed to evaluate the relationship between the abnormal DC value and clinical variables in CTN patients. Compared with the HCs, the patients with CTN exhibited significantly greater DC values in the right pallidum and right putamen, and lower DC values in the right lingual gyrus, right calcarine sulcus, left paracentral lobule, and left midcingulate cortex. A further seed-based FC analysis revealed that the right lingual gyrus showed decreased FC within the visual network and with other core brain networks, including the sensorimotor network, default mode network, and salience network, relative to HCs. Additionally, the left midcingulate cortex exhibited decreased FC within the middle cingulate cortex and the visual network in CTN patients. Moreover, the DC value in the left midcingulate cortex was negatively correlated with the illness duration. The present study shows that CTN patients exhibited specific functional connectivity network alterations in the basal ganglia, visual network, and salience network, which may reflect the aberrant neural network communication in pain processing and modulation. These findings may provide novel insight for understanding the mechanisms of pain chronicity in CTN patients.

Mental imagery content is associated with disease severity and specific brain functional connectivity changes in patients with Parkinson's disease.

Mental imagery is the mental re-creation of perceptual experiences, events and scenarios, and motor acts. In our previous study, we assessed whether motor imagery (MI) training combined with functional magnetic resonance imaging-based neurofeedback could improve the motor function of nondemented subjects with mild Parkinson's disease (PD) (N = 22). We used visual imagery (VI) (e.g., of scenes or events, but not of self-movements) training without neurofeedback for the control group (N = 22). Notably, both groups showed significant and comparable improvement in motor function after four weeks of daily imagery practice. In this study, we further examined the neural correlates of the motor enhancement as a result of the VI training by analyzing the self-reported VI content during daily practice and relating its quality to the functional connectivity characteristics of the same subjects. We demonstrated that the VI practice encompassed multisensory, spatial, affective, and executive processes all of which are also important for motor function in real life. Subjects with worse global disease severity also showed poorer quality of the VI content. Finally, the quality of the VI content showed significant positive correlations with the functional connectivity changes during the VI tasks in brain areas supporting visuospatial and sensorimotor processes. Our findings suggest that mental imagery training combining VI and MI may enhance motor function in patients with mild PD, and more broadly, underline the importance of incorporating self-reports of thoughts and experiences in neuroimaging studies that examine the brain mechanisms of complex cognitive processes especially in neuropsychiatric patient populations.

Specific and common functional connectivity deficits in drug-free generalized anxiety disorder and panic disorder: A data-driven analysis

Evidence of comparing neural network differences between anxiety disorder subtypes is limited, while it is crucial to reveal the pathogenesis of anxiety disorders. The present study aimed to investigate specific and common resting-state functional connectivity (FC) networks in generalized anxiety disorder (GAD), panic disorder (PD), and healthy controls (HC). We employed the gRAICAR algorithm to decompose the resting-state fMRI into independent components and align the components across 61 subjects (22 GAD, 18 PD and 21 HC). The default mode network and precuneus network exhibited GAD-specific aberrance, the anterior default mode network showed atypicality specific to PD, and the right fronto-parietal network showed aberrance common to GAD and PD. Between GAD-specific networks, FC between bilateral dorsolateral prefrontal cortex (DLPFC) was positively correlated with interoceptive sensitivity. In the common network, altered FCs between DLPFC and angular gyrus, and between orbitofrontal cortex and precuneus, were positively correlated with anxiety severity and interoceptive sensitivity. The pathological mechanism of PD could closely relate to the dysfunction of prefrontal cortex, while GAD could involve more extensive brain areas, which may be related to fear generalization.

Patterns of Neural Functional Connectivity in Infants at Familial Risk of Developmental Dyslexia

Developmental dyslexia is a heritable learning disability affecting 7% to 10% of the general population and can have detrimental impacts on mental health and vocational potential. Individuals with dyslexia show altered functional organization of the language and reading neural networks; however, it remains unknown how early in life these neural network alterations might emerge. To determine whether the early emergence of large-scale neural functional connectivity (FC) underlying long-term language and reading development is altered in infants with a familial history of dyslexia (FHD). This cohort study included infants recruited at Boston Children's Hospital between May 2011 and February 2019. Participants underwent structural and resting-state functional magnetic resonance imaging in the Department of Radiology at Boston Children's Hospital. Infants with FHD were matched with infants without FHD based on age and sex. Data were analyzed from April 2019 to June 2021. FHD was defined as having at least 1 first-degree relative with a dyslexia diagnosis or documented reading difficulties. Whole-brain FC patterns associated with 20 predefined cerebral regions important for long-term language and reading development were computed for each infant. Multivariate pattern analyses were applied to identify specific FC patterns that differentiated between infants with vs without FHD. For classification performance estimates, 99% CIs were calculated as the classification accuracy minus chance level. A total of 98 infants (mean [SD] age, 8.5 [2.3] months; 51 [52.0%] girls) were analyzed, including 35 infants with FHD and 63 infants without FHD. Multivariate pattern analyses identified distinct FC patterns between infants with vs without FHD in the left fusiform gyrus (classification accuracy, 0.55 [99% CI, 0.046-0.062]; corrected P < .001; Cohen d = 0.76). Connections linking left fusiform gyrus to regions in the frontal and parietal language and attention networks were among the paths with the highest contributions to the classification performance. These findings suggest that on the group level, FHD was associated with an early onset of atypical FC of regions important for subsequent word form recognition during reading acquisition. Longitudinal studies linking the atypical functional network and school-age reading abilities will be essential to further elucidate the ontogenetic mechanisms underlying the development of dyslexia.

Effect of cerebellum stimulation on cognitive recovery in patients with Alzheimer disease: A randomized clinical trial

IntroductionEvidence indicates that the cerebellum is involved in cognitive processing. However, the specific mechanisms through which the cerebellum repetitive transcranial magnetic stimulation (rTMS) contributes to the cognitive state are unclear. MethodsIn the current randomized, double-blind, sham-controlled trial, 27 patients with Alzheimer's disease (AD) were randomly allotted to one of the two groups: rTMS-real or rTMS-sham. We investigated the efficacy of a four-week treatment of bilateral cerebellum rTMS to promote cognitive recovery and alter specific cerebello-cerebral functional connectivity. ResultsThe cerebellum rTMS significantly improves multi-domain cognitive functions, directly associated with the observed intrinsic functional connectivity between the cerebellum nodes and the dorsolateral prefrontal cortex (DLPFC), medial frontal cortex, and the cingulate cortex in the real rTMS group. In contrast, the sham stimulation showed no significant impact on the clinical improvements and the cerebello-cerebral connectivity. ConclusionOur results depict that 5 Hz rTMS of the bilateral cerebellum is a promising, non-invasive treatment of cognitive dysfunction in AD patients. This cognitive improvement is accompanied by brain connectivity modulation and is consistent with the pathophysiological brain disconnection model in AD patients.

Altered brain functional network dynamics in classic trigeminal neuralgia: a resting-state functional magnetic resonance imaging study

BackgroundAccumulating studies have indicated a wide range of brain alterations with respect to the structure and function of classic trigeminal neuralgia (CTN). Given the dynamic nature of pain experience, the exploration of temporal fluctuations in interregional activity covariance may enhance the understanding of pain processes in the brain. The present study aimed to characterize the temporal features of functional connectivity (FC) states as well as topological alteration in CTN.MethodsResting-state functional magnetic resonance imaging and three-dimensional T1-weighted images were obtained from 41 CTN patients and 43 matched healthy controls (HCs). After group independent component analysis, sliding window based dynamic functional network connectivity (dFNC) analysis was applied to investigate specific FC states and related temporal properties. Then, the dynamics of the whole brain topological organization were estimated by calculating the coefficient of variation of graph-theoretical properties. Further correlation analyses were performed between all these measurements and clinical data.ResultsTwo distinct states were identified. Of these, the state 2, characterized by complicated coupling between default mode network (DMN) and cognitive control network (CC) and tight connections within DMN, was expressed more in CTN patients and presented as increased fractional windows and dwell time. Moreover, patients switched less frequently between states than HCs. Regarding the dynamic topological analysis, disruptions in global graph-theoretical properties (including network efficiency and small-worldness) were observed in patients, coupled with decreased variability in nodal efficiency of anterior cingulate cortex (ACC) in the salience network (SN) and the thalamus and caudate nucleus in the subcortical network (SC). The variation of topological properties showed negative correlation with disease duration and attack frequency.ConclusionsThe present study indicated disrupted flexibility of brain topological organization under persistent noxious stimulation and further highlighted the important role of “dynamic pain connectome” regions (including DMN/CC/SN) in the pathophysiology of CTN from the temporal fluctuation aspect. Additionally, the findings provided supplementary evidence for current knowledge about the aberrant cortical-subcortical interaction in pain development.

Abnormal Cerebral Blood Flow and Functional Connectivity Strength in Subjects With White Matter Hyperintensities.

White matter hyperintensities (WMHs) are common neuroimaging findings in the aging population and are associated with various clinical symptoms, especially cognitive impairment. Abnormal global cerebral blood flow (CBF) and specific functional connections have been reported in subjects with higher WMH loads. Nevertheless, the comprehensive functional mechanisms underlying WMH are yet to be established. In this study, by combining resting-state functional magnetic resonance imaging and arterial spin labeling, we investigated the neurovascular dysfunction in subjects with WMH in CBF, functional connectivity strength (FCS), and CBF–FCS coupling. The whole-brain alterations of all these measures were explored among non-dementia subjects with different WMH loads using a fine-grained Human Brainnetome Atlas. In addition, exploratory mediation analyses were conducted to further determine the relationships between these neuroimaging indicators, WMH load, and cognition. The results showed that subjects with higher WMH loads displayed decreased CBF and FCS mainly in regions involving the cognitive- and emotional-related brain networks, including the default mode network, salience network, and central executive network. Notably, subjects with higher WMH loads also showed an abnormal regional CBF–FCS coupling in several regions of the thalamus, posterior cingulate cortex, and parahippocampal gyrus involving the default mode network. Furthermore, regional CBF in the right inferior temporal gyrus and right dorsal caudate may mediate the relationship between WMH load and cognition in WMH subjects. These findings indicated characteristic changes in cerebral blood supply, brain activity, and neurovascular coupling in regions involving specific brain networks with the development of WMH, providing further information on pathophysiology underpinnings of the WMH and related cognitive impairment.

Characterization of specific spatial functional connectivity difference in depression during sleep.

Depression is a common mental illness and a large number of researchers have been still devoted to exploring effective biomarkers for the identification of depression. Few researches have been conducted on functional connectivity (FC) during sleep in depression. In this paper, a novel depression characterization is proposed using specific spatial FC features of sleep electroencephalography (EEG). Overnight polysomnography recordings were obtained from 26 healthy individuals and 25 patients with depression. The weighted phase lag indexes (WPLIs) of four frequency bands and five sleep periods were obtained from 16 EEG channels. The high discriminative connections extracted via feature evaluation and the cross-within variation (CW)-the spatial feature constructed to characterize the different performances in inter- and intra-hemispheric FC based on WPLIs, were utilized to classify patients and normal controls. The results showed that enhanced average FC and spatial differences, higher inter-hemispheric FC and lower intra-hemispheric FC, were found in patients. Furthermore, abnormalities in the inter-hemispheric connections of the temporal lobe in the theta band should be important indicators of depression. Finally, both CW and high discriminative WPLI features performed well in depression screening and CW was more specific for characterizing abnormal cortical EEG performance of depression. Our work investigated and characterized the abnormalities in sleep cortical activity in patients with depression, and may provide potential biomarkers for assisting with depression identification and new insights into the understanding of pathological mechanisms in depression.