Resting-state Functional Connectivity Strength Research Articles

Altered Large-Scale Resting-State Functional Network Connectivity in Convergence Insufficiency Young Adults Compared With Binocularly Normal Controls.

To investigate the underlying resting-state functional connectivity (RSFC) of symptomatic convergence insufficiency (CI) compared with binocularly normal controls (BNC) using functional magnetic resonance imaging (fMRI) under The Convergence Insufficiency Neuro‑mechanism Adult Population Study (NCT03593031). A total of 101 participants were eligible for this study. After removing datasets with motion artifacts, 49 CI and 47 BNC resting-state functional magnetic resonance imaging datasets were analyzed. CI was diagnosed with the following signs: (1) receded near point of convergence of 6 cm or greater, (2) decreased positive fusional vergence of less than 15∆ or failing Sheard's criteria of twice the near phoria, (3) near phoria of at least 4∆ more exophoric compared with the distance phoria, and (4) symptoms using the Convergence Insufficiency Symptom Survey (score of ≥21). RSFC was assessed using a group-level independent components analysis and dual regression. A behavioral correlation analysis using linear regression method was performed between clinical measures and RSFC using the significant difference between the CI and BNC. On average, a decreased RSFC was observed within the frontoparietal network, default mode network and visual network in patients with CI, compared with the participants with BNC (P < 0.05, corrected for multiple comparisons). The default mode network RSFC strength was significantly correlated with the PFV, near point of convergence, and difference between the horizontal phoria at near compared with far (P < 0.05). Results support altered RSFC in patients with CI compared with participants with BNC and suggest that these differences in underlying neurophysiology may in part be in connection with the differences in optometric visual function used to diagnose CI.

Functional connectivity of salience and affective networks among remitted depressed patients predicts episode recurrence.

Recurrent episodes in major depressive disorder (MDD) are common but the neuroimaging features predictive of recurrence are not established. Participants in the Predictors of Remission in Depression to Individual and Combined Treatments (PReDICT) study who achieved remission after 12 weeks of treatment withcognitive behavior therapy, duloxetine, or escitalopram were prospectively monitored for up to 21 months for recurrence. Neuroimaging markers predictive of recurrence were identified from week 12 functional magnetic resonance imaging scans by analyzing whole-brain resting state functional connectivity (RSFC) using seeds for four brain networks that are altered in MDD. Neuroimaging correlates of established clinical predictors of recurrence, including the magnitude of depressive (Hamilton Depression Rating Scale), anxiety (Hamilton Anxiety Rating Scale) symptom severity at time of remission, and a comorbid anxiety disorder were examined for their similarity to the neuroimaging predictors of recurrence. Of the 344 patients randomized in PReDICT, 61 achieved remission and had usable scans for analysis, 9 of whom experienced recurrence during follow-up. Recurrence was predicted by: 1) increased RSFC between subcallosal cingulate cortex (SCC) and right anterior insula, 2) decreased RSFC between SCC and bilateral primary visual cortex, and 3) decreased RSFC between insula and bilateral caudate. Week 12 depression and anxiety scores were negatively correlated with RSFC strength between executive control and default mode networks, but they were not correlated with the three RSFC patterns predicting recurrence. We conclude that altered RSFC in SCC and anterior insula networks are prospective risk factors associated with MDD recurrence, reflecting additional sources of risk beyond clinical measures.

Human anterior thalamic stimulation evoked cortical potentials align with intrinsic functional connectivity

Characterizing human thalamocortical network is fundamental for understanding a vast array of human behaviors since the thalamus plays a central role in cortico-subcortical communication. Over the past few decades, advances in functional magnetic resonance imaging have allowed for spatial mapping of intrinsic resting-state functional connectivity (RSFC) between both cortical regions and in cortico-subcortical networks. Despite these advances, identifying the electrophysiological basis of human thalamocortical network architecture remains challenging. By leveraging stereoelectroencephalography electrodes temporarily implanted into distributed cortical regions and the anterior nucleus of the thalamus (ANT) of 10 patients with refractory focal epilepsy, we tested whether ANT stimulation evoked cortical potentials align with RSFC from the stimulation site, derived from a normative functional connectome (n = 1000). Our study identifies spatial convergence of ANT stimulation evoked cortical potentials and normative RSFC. Other than connections to the Papez circuit, the ANT was found to be closely connected to several distinct higher-order association cortices, including the precuneus, angular gyrus, dorsal lateral prefrontal cortex, and anterior insula. Remarkably, we found that the spatial distribution and magnitude of cortical-evoked responses to single-pulse electrical stimulation of the ANT aligned with the spatial pattern and strength of normative RSFC of the stimulation site. The present study provides electrophysiological evidence that stimulation evoked electrical activity flows along intrinsic brain networks connected on a thalamocortical level.

Characteristics of resting state functional connectivity of motor cortex of high fitness level college students: Experimental evidence from functional near infrared spectroscopy (fNIRS)

AbstractObjectiveThis study inspects difference of resting state functional connectivity (RSFC) of motor cortex between athletes and ordinary college students and the test‐retest reliability of RSFC.MethodsTwenty high fitness level college students (high fitness group) and 20 ordinary college students (control group) were recruited. The motor cortical blood oxygen signals in resting states were monitored by functional near infrared spectroscopy (fNIRS). RSFCs of brain signals were preprocessed and calculated by FC‐NIRS software. RSFC results of test‐retest reliability were evaluated by intra‐class correlation coefficient (ICC).ResultsTotal RSFC (HbO signal) was significantly different between high fitness group (0.62 ± 0.04) and low fitness group (0.81 ± 0.04) (p &lt; .05). Significant differences were found between the groups (HbO signal) in 50 edges among the 190 edges of motor cortex (14 edges after FDR corrected). At three hemoglobin concentrations, mean of group‐level ICC (C, 1) for total RSFC in two groups was 0.40 ± 0.10, whereas the mean of group‐level ICC (C, k) was 0.57 ± 0.11, depicting “fair” reliability. The mean of group‐level ICC (C, 1) of 190 “edges” was 0.88 ± 0.06, whereas mean of ICC (C, k) was 0.94 ± 0.03, exhibiting “excellent” reliability.ConclusionFitness level is the factor causing specific changes in RSFC strength of motor cortex that can be utilized as biomarker for evaluating the fitness level.

Pattern of prefrontal cortical activation and network revealed by task-based and resting-state fNIRS in Parkinson's disease's patients with overactive bladder symptoms.

Overactive bladder (OAB) symptoms are common in Parkinson's disease (PD), and negatively contribute to the quality of life (QoL) of patients. To explore the underlying pathophysiological mechanism, we investigated the correlation between the prefrontal cortex (PFC) function and OAB symptoms in PD patients. One hundred fifty-five idiopathic PD patients were recruited and classified either as PD-OAB or PD-NOAB candidates based on their corresponding OAB symptom scores (OABSS). A linear regression analysis identified a correlative connection of cognitive domains. Then cortical activation during the performance of the verbal fluency test (VFT) and brain connectivity during resting state were conducted by functional near-infrared spectroscopy (fNIRS) for 10 patients in each group to investigate their frontal cortical activation and network pattern. In cognitive function analysis, a higher OABS score was significantly correlated with a lower FAB score, MoCA total score, and sub-scores of visuospatial/executive, attention, and orientation as well. In the fNIRS study, the PD-OAB group exhibited significant activations in 5 channels over the left hemisphere, 4 over the right hemisphere, and 1 in the median during the VFT process. In contrast, only 1 channel over the right hemisphere showed significant activation in the PD-NOAB group. The PD-OAB group revealed hyperactivation, particularly in certain channel in the left dorsolateral prefrontal cortex (DLPFC), compared with PD-NOAB (FDR P < 0.05). In the resting state, there was a significant increase of the resting state functional connectivity (RSFC) strength between the bilateral Broca area, left frontopolar area (FPA-L) and right Broca's area (Broca-R), between the FPA and Broca's area if merging the bilateral regions of interest (ROI), and also between the two hemispheres in the PD-OAB group. The Spearman's correlation confirmed that the OABS scores were positively correlated with RSFC strength between the bilateral Broca area, FPA-L and Broca-R, between the FPA and Broca area if merging the bilateral ROI. In this PD cohort, OAB was related to decreased PFC functions, with particularly hyperactivated left DLPFC during VTF and an enhanced neural connectivity between the two hemispheres in the resting state as observed by fNIRS imaging.

Association of Brain Microstructure and Functional Connectivity With Cognitive Outcomes and Postnatal Growth Among Early School–Aged Children Born With Extremely Low Birth Weight

Postnatal growth may be associated with longitudinal brain development in children born preterm. To compare brain microstructure and functional connectivity strength with cognitive outcomes in association with postnatal growth among early school-aged children born preterm with extremely low birth weight. This single-center cohort study prospectively enrolled 38 children 6 to 8 years of age born preterm with extremely low birth weight: 21 with postnatal growth failure (PGF) and 17 without PGF. Children were enrolled, past records were retrospectively reviewed, and imaging data and cognitive assessments occurred from April 29, 2013, through February 14, 2017. Image processing and statistical analyses were conducted through November 2021. Postnatal growth failure in the early neonatal period. Diffusion tensor images and resting-state functional magnetic resonance images were analyzed. Cognitive skills were tested using the Wechsler Intelligence Scale; executive function was assessed based on a composite score calculated from the synthetic composite of the Children's Color Trails Test, STROOP Color and Word Test, and Wisconsin Card Sorting Test; attention function was evaluated using the Advanced Test of Attention (ATA); and the Hollingshead Four Factor Index of Social Status-Child was estimated. Twenty-one children born preterm with PGF (14 girls [66.7%]), 17 children born preterm without PGF (6 girls [35.3%]), and 44 children born full term (24 girls [54.5%]) were recruited. Attention function was less favorable in children with PGF than those without PGF (mean [SD] ATA score: children with PGF, 63.5 [9.4]; children without PGF, 55.7 [8.0]; P = .008). Significantly lower mean (SD) fractional anisotropy in the forceps major of the corpus callosum (0.498 [0.067] vs 0.558 [0.044] vs 0.570 [0.038]) and higher mean (SD) mean diffusivity in the left superior longitudinal fasciculus-parietal bundle (8.312 [0.318] vs 7.902 [0.455] vs 8.083 [0.393]; originally calculated as millimeter squared per second and rescaled 10 000 times as mean diffusivity × 10 000) were seen among children with PGF compared with children without PGF and controls, respectively. Decreased resting-state functional connectivity strength was observed in the children with PGF. The mean diffusivity of the forceps major of the corpus callosum significantly correlated with the attention measures (r = 0.225; P = .047). Functional connectivity strength between the left superior lateral occipital cortex and both superior parietal lobules correlated with cognitive outcomes of intelligence (right superior parietal lobule, r = 0.262; P = .02; and left superior parietal lobule, r = 0.286; P = .01) and executive function (right superior parietal lobule, r = 0.367; P = .002; and left superior parietal lobule, r = 0.324; P = .007). The ATA score was positively correlated with functional connectivity strength between the precuneus and anterior division of the cingulate gyrus (r = 0.225; P = .048); however, it was negatively correlated with functional connectivity strength between the posterior cingulate gyrus and both superior parietal lobules (the right superior parietal lobule [r = -0.269; P = .02] and the left superior parietal lobule [r = -0.338; P = .002]). This cohort study suggests that the forceps major of the corpus callosum and the superior parietal lobule were vulnerable regions in preterm infants. Preterm birth and suboptimal postnatal growth could have negative associations with brain maturation, including altered microstructure and functional connectivity. Postnatal growth may be associated with differences in long-term neurodevelopment among children born preterm.

Classification and prediction of cognitive performance differences in older age based on brain network patterns using a machine learning approach.

Age-related cognitive decline varies greatly in healthy older adults, which may partly be explained by differences in the functional architecture of brain networks. Resting-state functional connectivity (RSFC) derived network parameters as widely used markers describing this architecture have even been successfully used to support diagnosis of neurodegenerative diseases. The current study aimed at examining whether these parameters may also be useful in classifying and predicting cognitive performance differences in the normally aging brain by using machine learning (ML). Classifiability and predictability of global and domain-specific cognitive performance differences from nodal and network-level RSFC strength measures were examined in healthy older adults from the 1000BRAINS study (age range: 55-85 years). ML performance was systematically evaluated across different analytic choices in a robust cross-validation scheme. Across these analyses, classification performance did not exceed 60% accuracy for global and domain-specific cognition. Prediction performance was equally low with high mean absolute errors (MAEs ≥ 0.75) and low to none explained variance (R2 ≤ 0.07) for different cognitive targets, feature sets, and pipeline configurations. Current results highlight limited potential of functional network parameters to serve as sole biomarker for cognitive aging and emphasize that predicting cognition from functional network patterns may be challenging.

Seeing the future: Connectome strength and network efficiency in visual network predict individual ability of episodic future thinking

Episodic future thinking (EFT) refers to the critical ability that enables people to construct and pre-experience the vivid mental imagery about future events, which impacts on the decision-making for individuals and group. Although EFT is generally believed to have a visual nature by theorists, little neuroscience evidence has been provided to verify this assumption. Here, by employing the approach of connectome-based predictive modeling (CPM) and graph-theoretical analysis, we analyzed resting-state functional brain image from 191 participants to predict their variability of EFT ability (leave-one-out cross-validation), and validated the results by applying different parcellation schemas and feature selection thresholds. At the connectome strength level, CPM-based analysis revealed that EFT ability could be predicted by the connectome strength of visual network. Besides, at the network level, graph-theoretical analysis showed that EFT ability could be predicted by the network efficiency of visual network. Moreover, these findings were replicated using different parcellation schemas and feature selection thresholds. These results robustly and collectively supported that the visual network might be one of the neural substrates underlying EFT ability from a comprehensive perspective of resting-state functional connectivity strength and the neural network. This study provides indications on how the function of visual network supports EFT ability, and enhances our understanding of the EFT ability from a neural basis perspective.

Moxibustion for primary dysmenorrhea: A resting-state functional magnetic resonance imaging study exploring the alteration of functional connectivity strength and functional connectivity.

IntroductionPrimary dysmenorrhea (PDM) is a common gynecological disease and chronic pain disorder. Moxibustion, a form of traditional Chinese medicine therapy, has proven to be effective for PDM. However, the central mechanisms of PDM and moxibustion for PDM are still unclear. This study aims to explore the potential central mechanism of PDM and clarify the possible mechanism of moxibustion for relieving pain.Materials and methodsA total of 23 PDM patients and 23 matched healthy controls (HCs) were enrolled. For PDM patients, resting-state functional magnetic resonance imaging (rs-fMRI) data were collected pre- and post-moxibustion treatment of 3 consecutive menstrual cycles, respectively. For HCs, rs-fMRI data were collected in the baseline. The resting-state functional connectivity strength (rs-FCS) analysis and the resting-state functional connectivity (rs-FC) analysis based on the region of interest (ROI) were combined to be conducted.ResultsCompared to HCs, PDM patients showed weaker rs-FCS in the left inferior frontal gyrus (IFG). After the moxibustion treatment, rs-FCS in the left IFG was increased with clinical improvement. Then, the left IFG was chosen as ROI, and the rs-FC analysis was conducted. It showed that the left IFG rs-FC in the bilateral anterior cingulate cortex (ACC)/middle cingulate cortex (MCC), the left posterior cingulate cortex (PCC)/precuneus (PCU), and the left parahippocampal gyrus (PHG) decreased after moxibustion treatment, most of which belong to the default mode network (DMN).ConclusionOur results highlight the role of the left IFG and the DMN in PDM. Specifically, the central mechanism of moxibustion for analgesia may be related to modulating the disorders of the reappraisal and processing of pain stimuli through influencing the cognition of pain.

Increased cerebral cortex activation in stroke patients during electrical stimulation of cerebellar fastigial nucleus with functional near-infrared spectroscopy.

Electrical stimulation of the cerebellar fastigial nucleus (FNS) has been shown to protect animals against cerebral ischemic injury. However, the changes in cortical activation as a response to FNS have not been illustrated in humans. This study aims to detect functional connectivity changes in the brain of stroke patients, and investigate the cortical activation caused by FNS through measuring the oxygenated hemoglobin concentration (HBO) in the cerebral cortex of stroke patients and healthy controls (HCs). This study recruited 20 patients with stroke and 20 HCs with all the following factors matched: age, gender and BMI. The experiment session was made up of the pre-task baseline, FNS task period, and post-task baseline. FNS task period contains 5 blocks, each block encompassing the resting state (30 s) and the FNS state (30 s). HBO signals were acquired by functional near-infrared spectroscopy (fNIRS) from the Prefrontal Cortex (PFC), the Motor Cortex (MC) and the Occipital Cortex (OC) throughout the experiment. The Pearson correlation coefficient was used to calculate the resting-state functional connectivity strength between the two groups, and the general linear model (GLM) was used to calculate the activation of 39 fNIRS channels during FNS in stroke patients and HCs, respectively. The coupling strength of stroke patients were significantly decreased in the following regions: right MC and left MC (t = 4.65, p = 0.0007), right MC and left OC (t = 2.93, p = 0.04), left MC and left OC (t = 2.81, p = 0.04). In stroke patients, the changes in cerebral oxygenated hemoglobin (ΔHBO) among 12 channels (CH) in the bilateral PFC and bilateral MC regions were significantly increased during the FNS state (FDR corrected p < 0.05) compared with the resting state. In HCs, only 1 channel was increased (FDR corrected p < 0.05) in the left PFC during FNS. By using the FNS and fNIRS techniques, the characteristics of functional connectivity were found to decrease in stroke patients. It was also noticed that FNS activates the PFC and MC regions. These findings may help to guide functional rehabilitation in stroke patients.

Potential brain recovery of frontostriatal circuits in heroin users after prolonged abstinence: A preliminary study

Neuroscientists have devoted efforts to explore potential brain recovery after prolonged abstinence in heroin users (HU). However, not much is known about whether frontostriatal circuits can recover after prolonged abstinence in HU. An eight-month longitudinal study was carried out for HU. Two MRI scans were obtained at baseline (HU1) and 8-month follow-up (HU2). The functional and structural connectivities of dorsal and ventral frontostriatal pathways were measured by resting-state functional connectivity (RSFC) and diffusion tensor imaging (DTI). Correlation analyses were employed to reveal the associations between neuroimaging and behavioral changes. Results suggested that relative to healthy controls (HCs), HU1 showed lower fractional anisotropy (FA) in the right dorsolateral prefrontal cortex (DLPFC)-to-caudate tracts and medial orbitofrontal cortex (mOFC)-to-nucleus accumbens (NAc) tracts as well as decreased RSFC in the left mOFC-NAc circuits. Longitudinal results revealed reduced craving and enhanced cognitive control in HU2 compared with HU1. After prolonged abstinence, HU2 showed increased FA values in the right DLPFC-caudate and mOFC-NAc tracts as well as increased RSFC strength in the bilateral mOFC-NAc circuits compared with HU1. In addition, changes in RSFC and FA values in the right mOFC-NAc circuit were negatively correlated with craving score changes. Similarly, negative correlations were also found between changes of RSFC in the bilateral DLPFC-caudate circuits and TMT-A scores. We provided scientific evidence for brain recovery of the dorsal and ventral frontostriatal circuits in HU after prolonged abstinence, and these circuits may be potential neuroimaging biomarkers for cognition and craving changes.

Cortical D1 and D2 dopamine receptor availability modulate methylphenidate-induced changes in brain activity and functional connectivity

Dopamine signaling plays a critical role in shaping brain functional network organization and behavior. Prominent theories suggest the relative expression of D1- to D2-like dopamine receptors shapes excitatory versus inhibitory signaling, with broad consequences for cognition. Yet it remains unknown how the balance between cortical D1R versus D2R signaling coordinates the activity and connectivity of functional networks in the human brain. To address this, we collected three PET scans and two fMRI scans in 36 healthy adults (13 female/23 male; average age 43 ± 12 years), including a baseline D1R PET scan and two sets of D2R PET scans and fMRI scans following administration of either 60 mg oral methylphenidate or placebo (two separate days, blinded, order counterbalanced). The drug challenge allowed us to assess how pharmacologically boosting dopamine levels alters network organization and behavior in association with D1R-D2R ratios across the brain. We found that the relative D1R-D2R ratio was significantly greater in high-level association cortices than in sensorimotor cortices. After stimulation with methylphenidate compared to placebo, brain activity (as indexed by the fractional amplitude of low frequency fluctuations) increased in association cortices and decreased in sensorimotor cortices. Further, within-network resting state functional connectivity strength decreased more in sensorimotor than association cortices following methylphenidate. Finally, in association but not sensorimotor cortices, the relative D1R-D2R ratio (but not the relative availability of D1R or D2R alone) was positively correlated with spatial working memory performance, and negatively correlated with age. Together, these data provide a framework for how dopamine-boosting drugs like methylphenidate alter brain function, whereby regions with relatively higher inhibitory D2R (i.e., sensorimotor cortices) tend to have greater decreases in brain activity and connectivity compared to regions with relatively higher excitatory D1R (i.e., association cortices). They also support the importance of a balanced interaction between D1R and D2R in association cortices for cognitive function and its degradation with aging.

Resting Hypoconnectivity of Theoretically Defined Addiction Networks during Early Abstinence Predicts Subsequent Relapse in Alcohol Use Disorder.

Theoretical models of addiction suggest that alterations in addiction domains including incentive salience, negative emotionality, and executive control lead to relapse in alcohol use disorder (AUD). To determine whether the functional organization of neural networks underlying these domains predict subsequent relapse, we generated theoretically defined addiction networks. We collected resting functional magnetic resonance imaging data from 45 individuals with AUD during early abstinence (number of days abstinent M = 25.40, SD = 16.51) and calculated the degree of resting-state functional connectivity (RSFC) within these networks. Regression analyses determined whether the RSFC strength in domain-defined addiction networks measured during early abstinence predicted subsequent relapse (dichotomous or continuous relapse metrics). RSFC within each addiction network measured during early abstinence was significantly lower in those that relapsed (vs. abstained) and predicted subsequent time to relapse. Lower incentive salience RSFC during early abstinence increased the odds of relapsing. Neither RSFC in a control network nor clinical self-report measures predicted relapse. The association between low incentive salience RSFC and faster relapse highlights the need to design timely interventions that enhance RSFC in AUD individuals at risk of relapsing faster.

Simultaneous PET/fMRI Detects Distinctive Alterations in Functional Connectivity and Glucose Metabolism of Precuneus Subregions in Alzheimer's Disease.

As a central hub in the interconnected brain network, the precuneus has been reported showing disrupted functional connectivity and hypometabolism in Alzheimer’s disease (AD). However, as a highly heterogeneous cortical structure, little is known whether individual subregion of the precuneus is uniformly or differentially involved in the progression of AD. To this end, using a hybrid PET/fMRI technique, we compared resting-state functional connectivity strength (FCS) and glucose metabolism in dorsal anterior (DA_pcu), dorsal posterior (DP_pcu) and ventral (V_pcu) subregions of the precuneus among 20 AD patients, 23 mild cognitive impairment (MCI) patients, and 27 matched cognitively normal (CN) subjects. The sub-parcellation of precuneus was performed using a K-means clustering algorithm based on its intra-regional functional connectivity. For the whole precuneus, decreased FCS (p = 0.047) and glucose hypometabolism (p = 0.006) were observed in AD patients compared to CN subjects. For the subregions of the precuneus, decreased FCS was found in DP_pcu of AD patients compared to MCI patients (p = 0.011) and in V_pcu for both MCI (p = 0.006) and AD (p = 0.008) patients compared to CN subjects. Reduced glucose metabolism was found in DP_pcu of AD patients compared to CN subjects (p = 0.038) and in V_pcu of AD patients compared to both MCI patients (p = 0.045) and CN subjects (p < 0.001). For both FCS and glucose metabolism, DA_pcu remained relatively unaffected by AD. Moreover, only in V_pcu, disruptions in FCS (r = 0.498, p = 0.042) and hypometabolism (r = 0.566, p = 0.018) were significantly correlated with the cognitive decline of AD patients. Our results demonstrated a distinctively disrupted functional and metabolic pattern from ventral to dorsal precuneus affected by AD, with V_pcu and DA_pcu being the most vulnerable and conservative subregion, respectively. Findings of this study extend our knowledge on the differential roles of precuneus subregions in AD.

Electroacupuncture enhances resting-state functional connectivity between dorsal caudate and precuneus and decreases associated leptin levels in overweight/obese subjects.

Electroacupuncture (EA) is a safe and effective method for treating obesity. However, how it modulates reward-related brain activity/functional connectivity and gut hormones remains unclear. We employed resting-state functional magnetic resonance imaging (RS-fMRI) and resting-state functional connectivity (RSFC) to investigate EA induced changes in resting-state activity and RSFC in reward-related regions and its association with gut hormones in overweight/obese subjects who received real (n = 20) and Sham (n = 15) stimulation. Results showed reduced leptin levels was positively correlated with reduced body mass index (BMI) and negatively correlated with increased cognitive-control as measured with Three-Factor-Eating-Questionnaire (TFEQ). Significant time effects on RSFC between dorsal caudate (DC) and precuneus were due to significant increased RSFC strength in both EA and Sham groups. In addition, increased RSFC of DC-precuneus was negatively correlated with reduced BMI and leptin levels in the EA group. Mediation analysis showed that the relationship between increased DC-precuneus RSFC strength and reduced BMI was mediated by reduced leptin levels. These findings reflect the association between EA-induced brain reward-related RSFC and leptin levels, and decreased leptin levels mediated altered DC-precuneus RSFC strength and consequent weight-loss, suggesting the potential role of EA in reducing weight and appetite.

Abnormality of Resting-State Functional Connectivity in Major Depressive Disorder: A Study With Whole-Head Near-Infrared Spectroscopy.

Near-infrared spectroscopy (NIRS) is a functional neuroimaging modality that has advantages in clinical usage. Previous functional magnetic resonance imaging (fMRI) studies have found that the resting-state functional connectivity (RSFC) of the default mode network (DMN) is increased, while the RSFC of the cognitive control network (CCN) is reduced in patients with major depressive disorder (MDD) compared with healthy controls. This study tested whether the NIRS-based RSFC measurements can detect the abnormalities in RSFC that have been associated with MDD in previous fMRI studies. We measured 8 min of resting-state brain activity in 34 individuals with MDD and 78 age- and gender-matched healthy controls using a whole-head NIRS system. We applied a previously established partial correlation analysis for estimating RSFCs between the 17 cortical regions. We found that MDD patients had a lower RSFC between the left dorsolateral prefrontal cortex and the parietal lobe that comprise the CCN, and a higher RSFC between the right orbitofrontal cortex and ventrolateral prefrontal cortex, compared to those in healthy controls. The RSFC strength of the left CCN was negatively correlated with the severity of depressive symptoms and the dose of antipsychotic medication and positively correlated with the level of social functioning. The results of this study suggest that NIRS-based measurements of RSFCs have potential clinical applications.

Novel Neuroimaging Biomarker for Sleep Quality in Insomnia Disorder: A Hypothalamus Resting State Study.

Despite striking progress in the understanding of the neurobiology of insomnia disorder (ID), about 40% of ID patients do not reach sustained remission with the primary treatments. It is necessary to reveal novel neuroimaging biomarkers for sleep quality in ID. The hypothalamus has a central role in sleep-wake regulation by communicating with different brain regions. However, the functional implications of hypothalamus circuitry with other brain areas remains largely unknown in ID. It may be speculated that dysfunctional circuitry in the hypothalamus is involved in the pathogenesis of ID. Thus, we investigated the different network organizations of the bilateral hypothalamus during the resting-state between 26 ID patients and 28 healthy controls (HC). Correlation analysis has been carried out to link the neuroimaging findings and Pittsburgh sleep quality index (PSQI) scores. Group comparisons reveal that the resting-state functional connectivity (RSFC) between the left hypothalamic region and a few other brain regions, including the medial prefrontal cortex (mPFC) and pallidum, are significantly higher in ID compared with HC. The right inferior temporal cortex showed reduced RSFC with the left hypothalamus. No significantly different RSFC between ID and HC was detected for the right hypothalamus. Positive correlations with PSQI scores were observed for RSFC strength between the left hypothalamus and bilateral mPFC (left: r = 0.2985, p = 0.0393; right: r = 0.3723, p = 0.0056). Similarly, the RSFC strength between the right hypothalamus and bilateral mPFC (left: r = 0.3980, p = 0.0029; right: r = 0.2972, p = 0.0291) also showed significant positive correlations with PSQI scores. In conclusion, we reveal a novel neuroimaging biomarker for sleep quality, i.e., the RSFC strength of the hypothalamus-mPFC pathway. Consistent with the hyperarousal model of ID, our results shed new insights into the implications of the hyper-connection within hypothalamus circuits in the pathology of the ID.

Impulsivity in heroin-dependent individuals: structural and functional abnormalities within frontostriatal circuits.

High levels of impulsivity are a risk factor for the initiation of heroin use and a core behavioral characteristic of heroin dependence. Impulsivity also contributes to the maintenance of drug use and hinders effective therapy. Here we sought to identify neuroimaging markers of impulsivity in heroin-dependent individuals (HDI), with a focus on the nucleus accumbens (NAc), a key region implicated in impulsivity and drug addiction generally. Volume and resting-state functional connectivity (RSFC) differences of the bilateral NAc were investigated between 21 HDI and 21 age-, gender-, nicotine-, alcohol-matched healthy controls (HC). The neuroimaging results were then correlated with the Barratt Impulsivity Scales (BIS-11). Higher motor impulsivity (t = 2.347, p = 0.0253) and larger right NAc volume (F (1,38) = 4.719, p = 0.036) was observed in HDI. The right NAc volume was positively correlated with BIS total (r = 0.6196, p = 0.0239) /motor (r = 0.5921, p = 0.0330) scores in HC and BIS motor (r = 0.5145, p = 0.0170) score in HDI. A negative correlation was found between RSFC of the right NAc-bilateral superior frontal gyrus (SFG) and motor impulsivity in HDI (left: r=-0.6537, p = 0.0013; right: r=-0.6167, p = 0.0029) and HC (left: r=-0.6490,p = 0.0164; right: r=-0.6993, p = 0.0078). We aimed to reveal novel multimodality neuroimaging biomarkers of the higher impulsivity in HDI by focusing on the NAc and corresponding functional circuits. Higher motor impulsivity was observed in HDI. Furthermore, the volume of the right NAc and the RSFC strength of right NAc-SFG could be neuroimaging biomarkers for the severity of impulsivity in HDI. These potential biomarkers could be a target for novel treatments in HDI.

Habenula and left angular gyrus circuit contributes to response of electroconvulsive therapy in major depressive disorder.

The habenula (Hb), one of the hottest structures in depression, has been widely demonstrated to be involved in the neurobiology of depression. Although the structural and functional abnormalities of Hb have been reported in major depressive disorders (MDD) patients, the role of Hb in treatment response in MDD remains unclear. In this study, resting-state functional connectivity (RSFC) and Granger causality analysis (GCA) were performed to investigate the intrinsic and causal changes of Hb in MDD after ECT. Moreover, support vector classification was applied to find out whether the changed functional and causal connections of Hb can effectively distinguish the MDD patients from healthy controls. The RSFC and GCA identified increased RSFC strength between bilateral Hb and left angular gyrus (AG), decreased causal connectivity strength from left AG to left Hb, from right Hb to left AG, and bidirectional interactions between left and right Hb in MDD patients after ECT. The changed causal connectivities from left AG to left Hb, and from right Hb to left AG were correlated with the changed depression symptoms and impaired delay memory recall performances. Furthermore, the functional and causal connectivities between left AG and bilateral Hb could serve as a biomarker to differentiate MDD from HCs. These results provided new evidence for the importance of Hb in depression and revealed that the interactions between Hb and left AG contribute to ECT response in MDD. Our findings will facilitate the future treatment of depression with the target of Hb in MDD and other brain disorders.

Correlates of intelligence via resting-state functional connectivity of the amygdala in healthy adults

Intelligence is a form of advanced cognition that includes reasoning, problem solving, pattern recognition, and establishing relationships among items. The amygdala plays an important role in cognitive processing, but the relationship between amygdalar function and intelligence has rarely been explored directly. Here, we investigated the relationship between resting-state functional connectivity (RSFC) of the amygdala and intelligence test performance in a large sample of healthy adults (N = 197). We found that two pairs of RSFCs were significantly increased in the high IQ group compared with that of the general IQ group. One of these RSFCs consisted of the right amygdala and the right superior parietal lobule, whereas the other RSFC consisted of the right amygdala and the left middle cingulum. In addition, we found that the brain regions in which the strength of RSFC significantly correlated with full IQ (FIQ) were mainly distributed in the parietal and limbic lobes. What’s more, a further mediation analysis indicated that the functional connectivity of the right amygdala and the right superior parietal lobule significantly mediated the correlation between comprehension and object assembly, whereas the functional connectivity of the right amygdala and the left middle cingulum mediated the association between similarities and digit symbol. These findings suggest that amygdalar RSFC may reflect individual differences in intelligence and mediate specific relationships among different intellectual abilities.