Most recent paper

Neurol Ther. 2022 Aug 23. doi: 10.1007/s40120-022-00397-x. Online ahead of print.

ABSTRACT

INTRODUCTION: Restless legs syndrome (RLS) is a common non-motor symptom in Parkinson's disease (PD), but its pathogenesis remains unclear. This study aimed to explore the potential neural substrates of RLS in a large sample of patients with PD.

METHODS: A total of 42 patients with PD with RLS and 124 patients with PD without RLS were prospectively recruited at our hospital between February 2019 and October 2020 and underwent structural and resting-state functional magnetic resonance imaging. Differences between the two patient groups were assessed using voxel-based morphometry and functional connectivity analysis. PD duration, Part III of the Movement Disorder Society's Unified Parkinson's Disease Rating Scale (MDS-UPDRS-III) score, and levodopa equivalent daily dose were treated as covariates.

RESULTS: Patients with PD with RLS had significantly larger gray matter volume in the bilateral posterior cingulate cortex than patients with PD without RLS (FDR-adjusted P < 0.05). Compared to patients without RLS, those with RLS had significantly lower functional connectivity between the left central opercular cortex and the bilateral precentral gyri and postcentral gyri (FDR-adjusted P < 0.001).

CONCLUSION: Our study provides the first evidence that in patients with PD, RLS is associated with significantly larger gray matter volume in the posterior cingulate cortex and lower resting-state functional connectivity within the sensorimotor network. Our results may help clarify the pathophysiology of RLS in PD and identify possible therapeutic targets.

PMID:35999489 | DOI:10.1007/s40120-022-00397-x

Addict Behav. 2022 Aug 12;135:107458. doi: 10.1016/j.addbeh.2022.107458. Online ahead of print.

ABSTRACT

BACKGROUND: Adolescent electronic cigarette (e-cigarette) use remains high. Elucidating contributing factors may enhance prevention strategies. Neurobiologically, amygdala-insula resting-state functional connectivity (rsFC) has been linked with aspects of sleep, affect, and substance use (SU). As such, we hypothesized that amygdala's rsFC with the insula would be associated with e-cigarette use via sleep problems and/or depression levels.

METHODS: An adolescent sample (N = 146) completed a rs-fMRI scan at time 1 and self-reports at time 2 (∼15 months later). Given consistent associations between mental health outcomes and the rsFC of the laterobasal amygdala (lbAMY) with the anterior insula, we utilized a seed region (lbAMY) to region of interest (ROI) analysis approach to characterize brain-behavior relationships. Two serial mediation models tested the interrelations between amygdala's rsFC with distinct anterior insula subregions (i.e., ventral insula [vI], dorsal insula [dI]), sleep problems, depression levels, and days of e-cigarette use.

RESULTS: An indirect effect was observed when considering the lbAMY's rsFC with the vI. Greater rsFC predicted more sleep problems, more sleep problems were linked with greater depressive symptoms, and greater depressive symptoms were associated with more e-cigarette use (indirect effect = 0.08, CI [0.01,0.21]). Indicative of a neurobiological dissociation, a similar indirect effect linking these variables was not observed when considering the lbAMY's rsFC with the dI (indirect effect = 0.03, CI [-0.001,0.10]).

CONCLUSIONS: These outcomes highlight functional interactions between the amygdala and insula as a neurobiological contributor to sleep problems, depressive symptoms, and ultimately SU thereby suggesting potential intervention points to reduce teen e-cigarette use.

PMID:35998541 | DOI:10.1016/j.addbeh.2022.107458

CNS Neurosci Ther. 2022 Aug 23. doi: 10.1111/cns.13946. Online ahead of print.

ABSTRACT

AIM: The inferior parietal lobule (IPL) plays important roles in reaching and grasping during hand movements, but how reorganizations of IPL subsystems underlie the paretic hand remains unclear. We aimed to explore whether specific IPL subsystems were disrupted and associated with hand performance after chronic stroke.

METHODS: In this cross-sectional study, we recruited 65 patients who had chronic subcortical strokes and 40 healthy controls from China. Each participant underwent the Fugl-Meyer Assessment of Hand and Wrist and resting-state fMRI at baseline. We mainly explored the group differences in resting-state effective connectivity (EC) patterns for six IPL subregions in each hemisphere, and we correlated these EC patterns with paretic hand performance across the whole stroke group and stroke subgroups. Moreover, we used receiver operating characteristic curve analysis to distinguish the stroke subgroups with partially (PPH) and completely (CPH) paretic hands.

RESULTS: Stroke patients exhibited abnormal EC patterns with ipsilesional PFt and bilateral PGa, and five sensorimotor-parietal/two parietal-temporal subsystems were positively or negatively correlated with hand performance. Compared with CPH patients, PPH patients exhibited abnormal EC patterns with the contralesional PFop. The PPH patients had one motor-parietal subsystem, while the CPH patients had one sensorimotor-parietal and three parietal-occipital subsystems that were associated with hand performance. Notably, the EC strength from the contralesional PFop to the ipsilesional superior frontal gyrus could distinguish patients with PPH from patients with CPH.

CONCLUSIONS: The IPL subsystems manifest specific functional reorganization and are associated with hand dysfunction following chronic stroke.

PMID:35996952 | DOI:10.1111/cns.13946

Behav Brain Res. 2022 Aug 19:114058. doi: 10.1016/j.bbr.2022.114058. Online ahead of print.

ABSTRACT

BACKGROUND: The current diagnosis of major depressive disorder (MDD) is mainly based on the patient's self-report and clinical symptoms. Machine learning methods are used to identify MDD using resting-state functional magnetic resonance imaging (rs-fMRI) data. However, due to large site differences in multisite rs-fMRI data and the difficulty of sample collection, most of the current machine learning studies use small sample sizes of rs-fMRI datasets to detect the alterations of functional connectivity (FC) or network attribute (NA), which may affect the reliability of the experimental results.

METHODS: Multisite rs-fMRI data were used to increase the size of the sample, and then we extracted the functional connectivity (FC) and network attribute (NA) features from 1611 rs-fMRI data (832 patients with MDD (MDDs) and 779 healthy controls (HCs)). ComBat algorithm was used to harmonize the data variances caused by the multisite effect, and multivariate linear regression was used to remove age and sex covariates. Two-sample t-test and wrapper-based feature selection methods (support vector machine recursive feature elimination with cross-validation (SVM-RFECV) and LightGBM's "feature_importances_" function) were used to select important features. The Shapley additive explanations (SHAP) method was used to assign the contribution of features to the best classification effect model.

RESULTS: The best result was obtained from the LinearSVM model trained with the 136 important features selected by SVMRFE-CV. In the nested five-fold cross-validation (consisting of an outer and an inner loop of five-fold cross-validation) of 1611 data, the model achieved the accuracy, sensitivity, and specificity of 68.90%, 71.75%, and 65.84%, respectively. The 136 important features were tested in a small dataset and obtained excellent classification results after balancing the ratio between patients with depression and HCs.

CONCLUSIONS: The combined use of FC and NA features is effective for classifying MDDs and HCs. The important FC and NA features extracted from the large sample dataset have some generalization performance and may be used as a reference for the altered brain functional connectivity networks in MDD.

PMID:35995263 | DOI:10.1016/j.bbr.2022.114058

Brain Connect. 2022 Aug 22. doi: 10.1089/brain.2022.0044. Online ahead of print.

ABSTRACT

To date, numerous studies have documented various alterations in resting brain activity in Alzheimer's disease (AD) and other neuropsychiatric diseases. In particular, disease-related alterations of functional connectivity (FC) in the resting state networks (RSN) have been documented. Altered FC in RSN is useful not only for interpreting the phenotype of diseases but also for diagnosing the diseases. More recently, several studies proposed the dynamics of resting-brain activity as a useful marker for detecting altered RSNs related to AD and other diseases. In contrast to previous studies, which focused on FC calculated using an entire fMRI scan (static FC), these newer studies focused the on temporal dynamics of FC within the scan (dynamic FC) to provide more sensitive measures to characterize RSNs. However, despite the increasing popularity of dFC, several studies cautioned that the results obtained in commonly used analyses for dFC require careful interpretation. In this mini-review, we review recent studies exploring alterations of static and dynamic functional connectivity in AD and other neuropsychiatric diseases. We then discuss how to utilize and interpret dFC for studying resting brain activity in diseases.

PMID:35994384 | DOI:10.1089/brain.2022.0044

Front Hum Neurosci. 2022 Aug 5;16:959523. doi: 10.3389/fnhum.2022.959523. eCollection 2022.

ABSTRACT

AIM: Patients with high myopia (HM) reportedly exhibit changes in functional brain activity, but the mechanism underlying such changes is unclear. This study was conducted to observe differences in dynamic spontaneous brain activity between patients with HM and healthy controls (HCs) via dynamic regional homogeneity (dReHo) analysis.

METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) scans were performed on 82 patients with HM and 59 HCs who were closely matched for age, sex, and weight. The dReHo approach was used to assess local dynamic activity in the human brain. The association between mean dReHo signal values and clinical symptoms in distinct brain areas in patients with HM was determined via correlation analysis.

RESULTS: In the left fusiform gyrus (L-FG), right inferior temporal gyrus (R-ITG), right Rolandic operculum (R-ROL), right postcentral gyrus (R-PoCG), and right precentral gyrus (R-PreCG), dReHo values were significantly greater in patients with HM than in HCs.

CONCLUSION: Patients with HM have distinct functional changes in various brain regions that mainly include the L-FG, R-ITG, R-ROL, R-PoCG, and R-PreCG. These findings constitute important evidence for the roles of brain networks in the pathophysiological mechanisms of HM and may aid in the diagnosis of HM.

PMID:35992950 | PMC:PMC9390771 | DOI:10.3389/fnhum.2022.959523

Front Neurosci. 2022 Aug 3;16:958804. doi: 10.3389/fnins.2022.958804. eCollection 2022.

ABSTRACT

Motor dysfunction is the major sequela of ischemic stroke. Motor recovery after stroke has been shown to be associated with remodeling of large-scale brain networks, both functionally and structurally. Electroacupuncture (EA) is a traditional Chinese medicine application that has frequently been recommended as an alternative therapy for ischemic stroke and is reportedly effective for alleviating motor symptoms in patients. In the present study, the effect of EA on the alterations of functional resting state networks (RSNs) was explored after middle cerebral artery occlusion/reperfusion (MCAO/R) injury using resting-state functional MRI. Rats were randomly assigned to three groups, including the sham group, MCAO/R group and MCAO/R+EA group. The ladder rung walking test was conducted prior to and after modeling to assess behavioral changes. RSNs were identified based on the independent component analysis (ICA) performed on the fMRI data from groups. EA treatment effectively reduced the occurrence of contralateral forelimb foot faults. Furthermore, our results suggested the disrupted function of the whole-brain network following ischemic stroke and the modulatory effect of acupuncture. The sensorimotor network (SMN), interoceptive network (IN), default mode network (DMN) and salience network (SN) were related to the therapeutic effect of EA on stroke recovery. Collectively, our findings confirmed the effect of EA on motor function recovery after cerebral ischemia reperfusion and shed light on the assessment of EA intervention-induced effects on brain networks. This study provides neuroimaging evidence to explain the therapeutic effects of EA in ischemic stroke and will lay the groundwork for further studies.

PMID:35992929 | PMC:PMC9382119 | DOI:10.3389/fnins.2022.958804

Front Neurosci. 2022 Aug 5;16:937245. doi: 10.3389/fnins.2022.937245. eCollection 2022.

ABSTRACT

AIMS: Based on resting-state functional MRI (fMRI), we preliminarily explored brain alterations in asymptomatic patients with vulnerable carotid plaques, but carotid stenosis was < 50%.

METHODS: A total of 58 asymptomatic patients with vulnerable carotid plaques (stenosis <50%) and 38 healthy controls were recruited. Between-group differences in regional homogeneity (ReHo), degree centrality (DC), and functional connectivity (FC) were analyzed. Correlation analysis was performed between the ReHo or DC values in altered brain regions as well as voxel-wise abnormal FC and scores on neuropsychiatric scales, serum interleukin-6 (IL-6), and C-reactive protein (CRP).

RESULTS: Both ReHo and DC values on the left superior occipital gyrus (SOG.L) of the asymptomatic vulnerable carotid plaque group reduced, regardless of plaque location (left, right, or bilateral). Functional connections weakened between the SOG.L and right lingual gyrus (LING.R)/right inferior occipital gyrus (IOG.R), right middle frontal gyrus (MFG.R)/orbital part of superior frontal gyrus (ORBsup.R)/orbital part of middle frontal gyrus (ORBmid.R), left precentral gyrus (PreCG.L)/postcentral gyrus (PoCG.L), left supplementary motor area (SMA.L), right paracentral lobule (PCL.R), left precuneus (PCUN.L), and right postcentral gyrus (PoCG.R)/PCL.R. In ReHo-altered brain regions, ReHo values were positively correlated with Hamilton Rating Scale for Depression (HAMD) scores, and the setting region of abnormal ReHo as seed points, voxel-wise FC between the SOG.L and PreCG.L was negatively correlated with CRP.

CONCLUSIONS: Cerebral alterations of neuronal synchronization, activity, and connectivity properties in the asymptomatic vulnerable carotid plaque group were independent of the laterality of vulnerable carotid plaques. Significant relation between ReHo values on the SOG.L and HAMD indicated that even when there were neither clinical symptoms nor lesions on routine MRI, brain function might have changed already at an early stage of carotid atherosclerosis. Inflammation might play a role in linking vulnerable carotid plaques and changes of resting-state functional connectivity.

PMID:35992918 | PMC:PMC9389209 | DOI:10.3389/fnins.2022.937245

Front Neurosci. 2022 Aug 5;16:974940. doi: 10.3389/fnins.2022.974940. eCollection 2022.

ABSTRACT

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is an effective way to stimulate changes in structural and functional plasticity, which is a part of learning and memory. However, to our knowledge, rTMS-induced specific activity and neural plasticity in different brain regions that affect cognition are not fully understood; nor are its mechanisms. Therefore, we aimed to investigate rTMS-induced cognition-related neural plasticity changes and their mechanisms in different brain regions.

METHODS: A total of 30 healthy adult rats were randomly divided into the control group and the rTMS group (n = 15 rats per group). The rats in the control and the rTMS group received either 4 weeks of sham or high-frequency rTMS (HF-rTMS) over the prefrontal cortex (PFC). Cognitive function was detected by Morris water maze. Functional imaging was acquired by resting-state functional magnetic resonance imaging (rs-fMRI) before and after rTMS. The protein expressions of BDNF, TrkB, p-Akt, Akt, NR1, NR2A, and NR2B in the PFC, hippocampus, and primary motor cortex (M1) were detected by Western blot following rTMS.

RESULTS: After 4 weeks of rTMS, the cognitive ability of healthy rats who underwent rTMS showed a small but significant behavioral improvement in spatial episodic learning and memory performance. Compared with the pre-rTMS or the control group, rats in the rTMS group showed increased regional homogeneity (ReHo) in multiple brain regions in the interoceptive/default mode network (DMN) and cortico-striatal-thalamic network, specifically the bilateral PFC, bilateral hippocampus, and the left M1. Western blot analyses showed that rTMS led to a significant increase in the expressions of N-methyl-D-aspartic acid (NMDA) receptors, including NR1, NR2A, and NR2B in the PFC, hippocampus, and M1, as well as an upregulation of BDNF, TrkB, and p-Akt in these three brain regions. In addition, the expression of NR1 in these three brain regions correlated with rTMS-induced cognitive improvement.

CONCLUSION: Overall, these data suggested that HF-rTMS can enhance cognitive performance through modulation of NMDA receptor-dependent brain plasticity.

PMID:35992904 | PMC:PMC9389218 | DOI:10.3389/fnins.2022.974940

Comput Stat Data Anal. 2022 Jul;171:107454. doi: 10.1016/j.csda.2022.107454. Epub 2022 Feb 22.

ABSTRACT

Independent component analysis (ICA) is an unsupervised learning method popular in functional magnetic resonance imaging (fMRI). Group ICA has been used to search for biomarkers in neurological disorders including autism spectrum disorder and dementia. However, current methods use a principal component analysis (PCA) step that may remove low-variance features. Linear non-Gaussian component analysis (LNGCA) enables simultaneous dimension reduction and feature estimation including low-variance features in single-subject fMRI. A group LNGCA model is proposed to extract group components shared by more than one subject. Unlike group ICA methods, this novel approach also estimates individual (subject-specific) components orthogonal to the group components. To determine the total number of components in each subject, a parametric resampling test is proposed that samples spatially correlated Gaussian noise to match the spatial dependence observed in data. In simulations, estimated group components achieve higher accuracy compared to group ICA. The method is applied to a resting-state fMRI study on autism spectrum disorder in 342 children (252 typically developing, 90 with autism), where the group signals include resting-state networks. The discovered group components appear to exhibit different levels of temporal engagement in autism versus typically developing children, as revealed using group LNGCA. This novel approach to matrix decomposition is a promising direction for feature detection in neuroimaging.

PMID:35992040 | PMC:PMC9390952 | DOI:10.1016/j.csda.2022.107454

Neurosci Insights. 2022 Aug 11;17:26331055221119443. doi: 10.1177/26331055221119443. eCollection 2022.

ABSTRACT

Human functional brain imaging research over the last 2 decades has shown that data from resting-state brain activity can help predict various psychological and pathological variables and brain function during tasks. However, most variables have been attributed to the individual brain. Recently, several studies have aimed to understand interpersonal relationships based on inter-individual similarity or dissimilarity of functional connectome. In this commentary, we introduce the studies that have opened up a new era of interpersonal research using human brain imaging.

PMID:35991809 | PMC:PMC9386479 | DOI:10.1177/26331055221119443

Front Psychiatry. 2022 Aug 5;13:923938. doi: 10.3389/fpsyt.2022.923938. eCollection 2022.

ABSTRACT

Transcranial direct current stimulation (tDCS) is a promising adjuvant treatment for persistent auditory verbal hallucinations (AVH) in Schizophrenia (SZ). Nonetheless, there is considerable inter-patient variability in the treatment response of AVH to tDCS in SZ. Machine-learned models have the potential to predict clinical response to tDCS in SZ. This study aims to examine the feasibility of identifying SZ patients with persistent AVH (SZ-AVH) who will respond to tDCS based on resting-state functional connectivity (rs-FC). Thirty-four SZ-AVH patients underwent resting-state functional MRI at baseline followed by add-on, twice-daily, 20-min sessions with tDCS (conventional/high-definition) for 5 days. A machine learning model was developed to identify tDCS treatment responders based on the rs-FC pattern, using the left superior temporal gyrus (LSTG) as the seed region. Functional connectivity between LSTG and brain regions involved in auditory and sensorimotor processing emerged as the important predictors of the tDCS treatment response. L1-regularized logistic regression model had an overall accuracy of 72.5% in classifying responders vs. non-responders. This model outperformed the state-of-the-art convolutional neural networks (CNN) model-both without (59.41%) and with pre-training (68.82%). It also outperformed the L1-logistic regression model trained with baseline demographic features and clinical scores of SZ patients. This study reports the first evidence that rs-fMRI-derived brain connectivity pattern can predict the clinical response of persistent AVH to add-on tDCS in SZ patients with 72.5% accuracy.

PMID:35990061 | PMC:PMC9388779 | DOI:10.3389/fpsyt.2022.923938

Front Psychiatry. 2022 Aug 3;13:956895. doi: 10.3389/fpsyt.2022.956895. eCollection 2022.

ABSTRACT

BACKGROUND: Inter-hemispheric disconnection is a primary pathological finding in schizophrenia. However, given the inherent complexity of this disease and its development, it remains unclear as to whether associated inter-hemispheric changes play an important role in auditory verbal hallucination (AVH) development. As such, this study was developed to explore inter-hemispheric connectivity in the context of schizophrenia with AVH while excluding positive symptoms and other factors with the potential to confound these results.

METHOD: In total, resting-state functional magnetic resonance imaging (fMRI) was used to assess 42 patients with AVH (APG), 26 without AVH (NPG), and 82 normal control (NC) individuals. Inter-hemispheric connectivity in these subjects was then assessed through the use of voxel-mirrored homotopic connectivity (VMHC) and Pearson correlation analyses.

RESULT: Relative to HC and NPG subjects, APG individuals exhibited a decrease in VMHC in the superior temporal gyrus (STG) extending into Heschl's gyrus, the insula, and the Rolandic operculum as well as in the fusiform gyrus extending into the para-hippocampus (Corrected p < 0.005, cluster size = 52). Among APG individuals, these observed impairments of inter-hemispheric connectivity were negatively correlated with Hoffman auditory hallucination scores.

CONCLUSION: These results support the schizophrenia hemitropic disconnection hypothesis, and provide novel evidence suggesting that there may be a relationship between reductions in inter-hemispheric connectivity in auditory and memory-related networks and the pathogenesis of AVH in patients with schizophrenia following the exclusion of confounding factors from other positive symptoms.

PMID:35990049 | PMC:PMC9381966 | DOI:10.3389/fpsyt.2022.956895

Biol Psychol. 2022 Aug 18:108409. doi: 10.1016/j.biopsycho.2022.108409. Online ahead of print.

ABSTRACT

Previous studies have reported that test anxiety is closely related to unreasonable cognitive patterns and maladaptive emotional responses. However, its underlying brain structural and functional basis has not been thoroughly studied. This study aimed to evaluate the potential difference in local gyration index (LGI) and corresponding resting-state functional connectivity (RSFC) in individuals with high test anxiety (HTA) compared with low test anxiety (LTA). Twenty-six individuals with HTA and 28 individuals with LTA underwent T1-weighted structural and resting-state functional magnetic resonance imaging scans. Using FreeSurfer software, we contrasted the LGI between the HTA and LTA groups using a surface-based general linear model to map group contrasts on a vertex-by-vertex basis. By selecting the cortical regions with significant differences in the LGI analysis as the regions of interest, the seed-based RSFC analysis was further carried out using the Resting-State fMRI Data Analysis Toolkit to examine the differences in the functional connectivity of these cortical regions with the whole brain between the two groups. The results showed that the LGI in several cortical regions of the executive control network (ECN) and the right lateral occipital gyrus was lower in the HTA group than in the LTA group. Furthermore, compared with the LTA group, the HTA group exhibited abnormal RSFC within the ECN, between the ECN and the visual network, and between the ECN and the sensorimotor network. Our findings might provide preliminary evidence for brain morphology and functional alterations in individuals with HTA and contribute to a better understanding of the pathophysiology of TA. DATA STATEMENT: The data that support the findings of this study are available from the corresponding author upon reasonable request after completing a formal data sharing agreement.

PMID:35988834 | DOI:10.1016/j.biopsycho.2022.108409

Nat Commun. 2022 Aug 20;13(1):4899. doi: 10.1038/s41467-022-32592-7.

ABSTRACT

In Alzheimer's disease (AD), younger symptom onset is associated with accelerated disease progression and tau spreading, yet the mechanisms underlying faster disease manifestation are unknown. To address this, we combined resting-state fMRI and longitudinal tau-PET in two independent samples of controls and biomarker-confirmed AD patients (ADNI/BioFINDER, n = 240/57). Consistent across both samples, we found that younger symptomatic AD patients showed stronger tau-PET in globally connected fronto-parietal hubs, i.e., regions that are critical for maintaining cognition in AD. Stronger tau-PET in hubs predicted faster subsequent tau accumulation, suggesting that tau in globally connected regions facilitates connectivity-mediated tau spreading. Further, stronger tau-PET in hubs mediated the association between younger age and faster tau accumulation in symptomatic AD patients, which predicted faster cognitive decline. These independently validated findings suggest that younger AD symptom onset is associated with stronger tau pathology in brain hubs, and accelerated tau spreading throughout connected brain regions and cognitive decline.

PMID:35987901 | DOI:10.1038/s41467-022-32592-7

J Psychiatr Res. 2022 Aug 12;155:33-41. doi: 10.1016/j.jpsychires.2022.07.040. Online ahead of print.

ABSTRACT

The neural correlates of major depressive disorder (MDD) remain disputed. In the absence of reliable biological markers, the dysfunction and interaction of neural networks have been proposed as pathophysiological neural mechanisms in depression. Here, we examined the functional connectivity (FC) of brain networks. 51 healthy volunteers (mean age 33.57 ± 7.80) and 55 individuals diagnosed with MDD (mean age 33.89 ± 11.00) participated by performing a resting-state (rs) fMRI scan. Seed to voxel FC analyses were performed. Compared to healthy control (HC), MDD patients showed higher connectivity between the hippocampus and the anterior cingulate cortex (ACC) and lower connectivity between the insula and the ACC. The MDD group displayed lower connectivity between the inferior parietal lobule (IPL) and the superior frontal gyrus (SFG). The current data replicate previous findings regarding the cortico-limbic network (hippocampus - ACC connection) and the salience network (insula - ACC connection) and provide novel insight into altered rsFC in MDD, in particular involving the hippocampus - ACC and the insula - ACC connection. Furthermore, altered connectivity between the IPL and SFG indicates that the processing in higher cognitive processes such as attention and working memory is affected in MDD. These data further support dysfunctional neuronal networks as an interesting pathophysiological marker in depression.

PMID:35987176 | DOI:10.1016/j.jpsychires.2022.07.040

Mult Scler Relat Disord. 2022 Aug 13;68:104113. doi: 10.1016/j.msard.2022.104113. Online ahead of print.

ABSTRACT

BACKGROUND: Cognitive impairment is one of the common symptoms in patients with neuromyelitis optica spectrum disorder (NMOSD). However, the underlying mechanism remains unclear. Resting-state functional magnetic resonance imaging (rs-fMRI) offers the opportunity to reveal the patterns of brain activity in patients with different cognitive states. Accordingly, this study investigated functional connectivity (FC) abnormalities within and between the main cognitive networks in cognitively impaired (CI) patients with NMOSD and their correlations with cognitive performance.

METHODS: Thirty-four patients with NMOSD and 39 healthy controls (HC) were included. Neuropsychological evaluations and rs-fMRI scanning were performed. Patients were classified as CI (n = 16) or cognitively preserved (CP; n = 18) according to neuropsychological evaluations. Seven components representing six main cognitive networks were selected by group independent component analysis. The differences in inter- and intranetwork FC among CI, CP, and HC groups were assessed. The correlation between FC values and neuropsychological data in NMOSD was calculated.

RESULTS: The CI group showed decreased intranetwork connectivity in the posterior default mode network (pDMN) compared with the HC group (P < 0.05, GRF corrected), and decreased internetwork connectivity between the salience network (SN) and pDMN, and between the SN and right frontoparietal network (rFPN) compared with CP and HC groups. The altered FC values were significantly correlated with cognitive performance in the whole NMOSD group.

CONCLUSION: The disconnection within the pDMN and between the SN and pDMN or rFPN might suggest the neural substrates underlying cognitive impairment in NMOSD.

PMID:35987110 | DOI:10.1016/j.msard.2022.104113

Neurosci Insights. 2022 Aug 13;17:26331055221119441. doi: 10.1177/26331055221119441. eCollection 2022.

ABSTRACT

Resistance training is a promising strategy to promote healthy cognitive aging; however, the brain mechanisms by which resistance training benefits cognition have yet to be determined. Here, we examined the effects of a 12-week resistance training program on resting brain activity and cerebrovascular function in 20 healthy older adults (14 females, mean age 69.1 years). In this single group clinical trial, multimodal 3 T magnetic resonance imaging was performed at 3 time points: baseline (preceding a 12-week control period), pre-intervention, and post-intervention. Along with significant improvements in fluid cognition (d = 1.27), 4 significant voxelwise clusters were identified for decreases in resting brain activity after the intervention (Cerebellum, Right Middle Temporal Gyrus, Left Inferior Parietal Lobule, and Right Inferior Parietal Lobule), but none were identified for changes in resting cerebral blood flow. Using a separate region of interest approach, we provide estimates for improved cerebral blood flow, compared with declines over the initial control period, in regions associated with cognitive impairment, such as hippocampal blood flow (d = 0.40), and posterior cingulate blood flow (d = 0.61). Finally, resistance training had a small countermeasure effect on the age-related progression of white matter lesion volume (rank-biserial = -0.22), a biomarker of cerebrovascular disease. These proof-of-concept data support larger trials to determine whether resistance training can attenuate or even reverse salient neurodegenerative processes.

PMID:35983377 | PMC:PMC9379950 | DOI:10.1177/26331055221119441

Front Hum Neurosci. 2022 Aug 2;16:889426. doi: 10.3389/fnhum.2022.889426. eCollection 2022.

ABSTRACT

BACKGROUND: Mild cognitive impairment (MCI) is a common neurological disorder. Moxibustion has been shown to be effective in treating MCI, but its therapeutic mechanisms still remain unclear. This study mainly aimed to investigate the modulation effect of moxibustion treatment for patients with MCI by functional magnetic resonance imaging (fMRI).

METHODS: A total of 47 patients with MCI and 30 healthy controls (HCs) participated in resting-state fMRI imaging (rs-fMRI) scans. Patients with MCI were randomly divided into true moxibustion group (TRUE, n = 30) and sham moxibustion group (SHAM, n = 17). The degree centrality (DC) approach was applied to distinguish altered brain functions. Correlation analysis was then performed to examine the relationships between the neuroimaging findings and clinical symptoms.

RESULTS: Compared with HCs, patients with MCI mainly showed decreased DC in the left middle frontal cortex (MFC) and bilateral middle cingulate cortex (MCC). After moxibustion treatment, the SHAM group had no significant DC findings, while TRUE group mainly showed significant increased DC in the bilateral MFC and MCC, as well as decreased DC in the left middle occipital cortex (MOC). Repeated measures analysis of variance (ANOVA) showed significant interactions between the two groups of patients with MCI. In addition, the higher Mini-Mental State Examination (MMSE) score was significantly positively correlated with increased DC in the right MFC and left MCC after moxibustion treatment.

CONCLUSION: Our findings demonstrate that the potential value of moxibustion treatment on MCI, which adds new insights into the popular view that moxibustion treatment may slow cognitive decline in patients with MCI.

PMID:35982690 | PMC:PMC9378775 | DOI:10.3389/fnhum.2022.889426

Neuropsychopharmacology. 2022 Aug 18. doi: 10.1038/s41386-022-01385-3. Online ahead of print.

ABSTRACT

Subtle subjective visual dysfunctions (VisDys) are reported by about 50% of patients with schizophrenia and are suggested to predict psychosis states. Deeper insight into VisDys, particularly in early psychosis states, could foster the understanding of basic disease mechanisms mediating susceptibility to psychosis, and thereby inform preventive interventions. We systematically investigated the relationship between VisDys and core clinical measures across three early phase psychiatric conditions. Second, we used a novel multivariate pattern analysis approach to predict VisDys by resting-state functional connectivity within relevant brain systems. VisDys assessed with the Schizophrenia Proneness Instrument (SPI-A), clinical measures, and resting-state fMRI data were examined in recent-onset psychosis (ROP, n = 147), clinical high-risk states of psychosis (CHR, n = 143), recent-onset depression (ROD, n = 151), and healthy controls (HC, n = 280). Our multivariate pattern analysis approach used pairwise functional connectivity within occipital (ON) and frontoparietal (FPN) networks implicated in visual information processing to predict VisDys. VisDys were reported more often in ROP (50.34%), and CHR (55.94%) than in ROD (16.56%), and HC (4.28%). Higher severity of VisDys was associated with less functional remission in both CHR and ROP, and, in CHR specifically, lower quality of life (Qol), higher depressiveness, and more severe impairment of visuospatial constructability. ON functional connectivity predicted presence of VisDys in ROP (balanced accuracy 60.17%, p = 0.0001) and CHR (67.38%, p = 0.029), while in the combined ROP + CHR sample VisDys were predicted by FPN (61.11%, p = 0.006). These large-sample study findings suggest that VisDys are clinically highly relevant not only in ROP but especially in CHR, being closely related to aspects of functional outcome, depressiveness, and Qol. Findings from multivariate pattern analysis support a model of functional integrity within ON and FPN driving the VisDys phenomenon and being implicated in core disease mechanisms of early psychosis states.

PMID:35982238 | DOI:10.1038/s41386-022-01385-3