New resting-state fMRI related studies at PubMed

The altered intrinsic functional connectivity after acupuncture at shenmen (HT7) in acute sleep deprivation

Fri, 08/12/2022 - 10:00

Front Neurol. 2022 Jul 26;13:947379. doi: 10.3389/fneur.2022.947379. eCollection 2022.


INTRODUCTION: Accumulating evidence has shown that acupuncture could significantly improve the sleep quality and cognitive function of individuals suffering from insufficient sleep. Numerous animal studies have confirmed the effects and mechanisms of acupuncture on acute sleep deprivation (SD). However, the role of acupuncture on individuals after acute SD remains unclear.

METHODS: In the current study, we recruited 30 healthy subjects with regular sleep. All subjects received resting-state fMRI scans during the rested wakefulness (RW) state and after 24 h of total SD. The scan after 24 h of total SD included two resting-state fMRI sessions before and after needling at Shenmen (HT7). Both edge-based and large-scale network FCs were calculated.

RESULTS: The edge-based results showed the suprathreshold edges with abnormal between-network FC involving all paired networks except somatosensory motor network (SMN)-SCN between the SD and RW state, while both decreased and increased between-network FC of edges involving all paired networks except frontoparietal network (FPN)-subcortical network (SCN) between before and after acupuncture at HT7. Compared with the RW state, the large-scale brain network results showed decreased between-network FC in SMN-Default Mode Network (DMN), SMN-FPN, and SMN-ventral attention network (VAN), and increased between-network FC in Dorsal Attention Network (DAN)-VAN, DAN-SMN between the RW state and after 24 h of total SD. After acupuncture at HT7, the large-scale brain network results showed decreased between-network FC in DAN-VAN and increased between-network FC in SMN-VAN.

CONCLUSION: Acupuncture could widely modulate extensive brain networks and reverse the specific between-network FC. The altered FC after acupuncture at HT7 may provide new evidence to interpret neuroimaging mechanisms of the acupuncture effect on acute SD.

PMID:35959405 | PMC:PMC9360611 | DOI:10.3389/fneur.2022.947379

Altered functional connectivity within default mode network after rupture of anterior communicating artery aneurysm

Fri, 08/12/2022 - 10:00

Front Aging Neurosci. 2022 Jul 25;14:905453. doi: 10.3389/fnagi.2022.905453. eCollection 2022.


BACKGROUND: Rupture of anterior communicating artery (ACoA) aneurysm often leads to cognitive impairment, especially memory complaints. The medial superior frontal gyrus (SFGmed), a node of the default mode network (DMN), has been extensively revealed to participate in various cognitive processes. However, the functional connectivity (FC) characteristics of SFGmed and its relationship with cognitive performance remain unknown after the rupture of the ACoA aneurysm.

METHODS: Resting-state functional MRI (fMRI) and cognitive assessment were acquired in 27 eligible patients and 20 controls. Seed-based FC between unilateral SFGmed and the rest of the brain was calculated separately, and then compared their intensity differences between the two groups. Furthermore, we analyzed the correlation between abnormal FC and cognitive function in patients with ruptured ACoA aneurysm.

RESULTS: Cognitive impairment was confirmed in 51.9% of the patients. Compared with the controls, patients suffering from ruptured ACoA aneurysm exhibited a similar FC decline between each side of SFGmed and predominant nodes within DMN, including the precuneus, angular gyrus, cingulate cortex, left hippocampus, left amygdala, left temporal pole (TPO), and left medial orbitofrontal cortex (mOFC). Besides, significantly decreased FC of left SFGmed and left insula, right middle temporal gyrus (MTG), as well as right mOFC, were also found. In addition, only enhanced insular connectivity with right SFGmed was determined, whereas increased FC of the left SFGmed was not observed. Correlation analyses showed that lower total cognitive performance or stronger subjective memory complaints were related to reduced connectivity in the SFGmed and several cortical regions such as the angular gyrus and middle cingulate cortex (MCC).

CONCLUSION: Our results suggest that patients with ruptured ACoA aneurysm exist long-term cognitive impairment and intrinsic hypoconnectivity of cognition-related brain regions within DMN. Deactivation of DMN may be a potential neural mechanism leading to cognitive deficits in these patients.

PMID:35959287 | PMC:PMC9357996 | DOI:10.3389/fnagi.2022.905453

Reconfiguration of Functional Dynamics in Cortico-Thalamo-Cerebellar Circuit in Schizophrenia Following High-Frequency Repeated Transcranial Magnetic Stimulation

Fri, 08/12/2022 - 10:00

Front Hum Neurosci. 2022 Jul 25;16:928315. doi: 10.3389/fnhum.2022.928315. eCollection 2022.


Schizophrenia is a serious mental illness characterized by a disconnection between brain regions. Transcranial magnetic stimulation is a non-invasive brain intervention technique that can be used as a new and safe treatment option for patients with schizophrenia with drug-refractory symptoms, such as negative symptoms and cognitive impairment. However, the therapeutic effects of transcranial magnetic stimulation remain unclear and would be investigated using non-invasive tools, such as functional connectivity (FC). A longitudinal design was adopted to investigate the alteration in FC dynamics using a dynamic functional connectivity (dFC) approach in patients with schizophrenia following high-frequency repeated transcranial magnetic stimulation (rTMS) with the target at the left dorsolateral prefrontal cortex (DLPFC). Two groups of schizophrenia inpatients were recruited. One group received a 4-week high-frequency rTMS together with antipsychotic drugs (TSZ, n = 27), while the other group only received antipsychotic drugs (DSZ, n = 26). Resting-state functional magnetic resonance imaging (fMRI) and psychiatric symptoms were obtained from the patients with schizophrenia twice at baseline (t1) and after 4-week treatment (t2). The dynamics was evaluated using voxel- and region-wise FC temporal variability resulting from fMRI data. The pattern classification technique was used to verify the clinical application value of FC temporal variability. For the voxel-wise FC temporary variability, the repeated measures ANCOVA analysis showed significant treatment × time interaction effects on the FC temporary variability between the left DLPFC and several regions, including the thalamus, cerebellum, precuneus, and precentral gyrus, which are mainly located within the cortico-thalamo-cerebellar circuit (CTCC). For the ROI-wise FC temporary variability, our results found a significant interaction effect on the FC among CTCC. rTMS intervention led to a reduced FC temporary variability. In addition, higher alteration in FC temporal variability between left DLPFC and right posterior parietal thalamus predicted a higher remission ratio of negative symptom scores, indicating that the decrease of FC temporal variability between the brain regions was associated with the remission of schizophrenia severity. The support vector regression (SVR) results suggested that the baseline pattern of FC temporary variability between the regions in CTCC could predict the efficacy of high-frequency rTMS intervention on negative symptoms in schizophrenia. These findings confirm the potential relationship between the reduction in whole-brain functional dynamics induced by high-frequency rTMS and the improvement in psychiatric scores, suggesting that high-frequency rTMS affects psychiatric symptoms by coordinating the heterogeneity of activity between the brain regions. Future studies would examine the clinical utility of using functional dynamics patterns between specific brain regions as a biomarker to predict the treatment response of high-frequency rTMS.

PMID:35959244 | PMC:PMC9359206 | DOI:10.3389/fnhum.2022.928315

Altered insular functional connectivity correlates to impaired vigilant attention after sleep deprivation: A resting-state functional magnetic resonance imaging study

Fri, 08/12/2022 - 10:00

Front Neurosci. 2022 Jul 26;16:889009. doi: 10.3389/fnins.2022.889009. eCollection 2022.


OBJECTIVES: This study used resting-state functional magnetic resonance imaging (rs-fMRI) scans to assess the dominant effects of 36 h total sleep deprivation (TSD) on vigilant attention and changes in the resting-state network.

MATERIALS AND METHODS: Twenty-two healthy college students were enrolled in this study. Participants underwent two rs-fMRI scans, once in rested wakefulness (RW) and once after 36 h of TSD. We used psychomotor vigilance tasks (PVT) to measure vigilant attention. The region-of-interest to region-of-interest correlation was employed to analyze the relationship within the salience network (SN) and between other networks after 36 h of TSD. Furthermore, Pearson's correlation analysis investigated the relationship between altered insular functional connectivity and PVT performance.

RESULTS: After 36 h of TSD, participants showed significantly decreased vigilant attention. Additionally, TSD induced decreased functional connectivity between the visual and parietal regions, whereas, a significant increase was observed between the anterior cingulate cortex and insula. Moreover, changes in functional connectivity in the anterior cingulate cortex and insula showed a significant positive correlation with the response time to PVT.

CONCLUSION: Our results suggest that 36 h of TSD impaired vigilant visual attention, resulting in slower reaction times. The decrease in visual-parietal functional connectivity may be related to the decrease in the reception of information in the brain. Enhanced functional connectivity of the anterior cingulate cortex with the insula revealed that the brain network compensation occurs mainly in executive function.

PMID:35958999 | PMC:PMC9361853 | DOI:10.3389/fnins.2022.889009

Two-step clustering-based pipeline for big dynamic functional network connectivity data

Fri, 08/12/2022 - 10:00

Front Neurosci. 2022 Jul 25;16:895637. doi: 10.3389/fnins.2022.895637. eCollection 2022.


BACKGROUND: Dynamic functional network connectivity (dFNC) estimated from resting-state functional magnetic imaging (rs-fMRI) studies the temporally varying functional integration between brain networks. In a conventional dFNC pipeline, a clustering stage to summarize the connectivity patterns that are transiently but reliably realized over the course of a scanning session. However, identifying the right number of clusters (or states) through a conventional clustering criterion computed by running the algorithm repeatedly over a large range of cluster numbers is time-consuming and requires substantial computational power even for typical dFNC datasets, and the computational demands become prohibitive as datasets become larger and scans longer. Here we developed a new dFNC pipeline based on a two-step clustering approach to analyze large dFNC data without having access to huge computational power.

METHODS: In the proposed dFNC pipeline, we implement two-step clustering. In the first step, we randomly use a sub-sample dFNC data and identify several sets of states at different model orders. In the second step, we aggregate all dFNC states estimated from all iterations in the first step and use this to identify the optimum number of clusters using the elbow criteria. Additionally, we use this new reduced dataset and estimate a final set of states by performing a second kmeans clustering on the aggregated dFNC states from the first k-means clustering. To validate the reproducibility of results in the new pipeline, we analyzed four dFNC datasets from the human connectome project (HCP).

RESULTS: We found that both conventional and proposed dFNC pipelines generate similar brain dFNC states across all four sessions with more than 99% similarity. We found that the conventional dFNC pipeline evaluates the clustering order and finds the final dFNC state in 275 min, while this process takes only 11 min for the proposed dFNC pipeline. In other words, the new pipeline is 25 times faster than the traditional method in finding the optimum number of clusters and finding the final dFNC states. We also found that the new method results in better clustering quality than the conventional approach (p < 0.001). We show that the results are replicated across four different datasets from HCP.

CONCLUSION: We developed a new analytic pipeline that facilitates the analysis of large dFNC datasets without having access to a huge computational power source. We validated the reproducibility of the result across multiple datasets.

PMID:35958983 | PMC:PMC9358255 | DOI:10.3389/fnins.2022.895637

Performances of whole-brain dynamic and static functional connectivity fingerprinting in machine learning-based classification of major depressive disorder

Fri, 08/12/2022 - 10:00

Front Psychiatry. 2022 Jul 26;13:973921. doi: 10.3389/fpsyt.2022.973921. eCollection 2022.


BACKGROUND: Alterations in static and dynamic functional connectivity during resting state have been widely reported in major depressive disorder (MDD). The objective of this study was to compare the performances of whole-brain dynamic and static functional connectivity combined with machine learning approach in differentiating MDD patients from healthy controls at the individual subject level. Given the dynamic nature of brain activity, we hypothesized that dynamic connectivity would outperform static connectivity in the classification.

METHODS: Seventy-one MDD patients and seventy-one well-matched healthy controls underwent resting-state functional magnetic resonance imaging scans. Whole-brain dynamic and static functional connectivity patterns were calculated and utilized as classification features. Linear kernel support vector machine was employed to design the classifier and a leave-one-out cross-validation strategy was used to assess classifier performance.

RESULTS: Experimental results of dynamic functional connectivity-based classification showed that MDD patients could be discriminated from healthy controls with an excellent accuracy of 100% irrespective of whether or not global signal regression (GSR) was performed (permutation test with P < 0.0002). Brain regions with the most discriminating dynamic connectivity were mainly and reliably located within the default mode network, cerebellum, and subcortical network. In contrast, the static functional connectivity-based classifiers exhibited unstable classification performances, i.e., a low accuracy of 38.0% without GSR (P = 0.9926) while a high accuracy of 96.5% with GSR (P < 0.0002); moreover, there was a considerable variability in the distribution of brain regions with static connectivity most informative for classification.

CONCLUSION: These findings suggest the superiority of dynamic functional connectivity in machine learning-based classification of depression, which may be helpful for a better understanding of the neural basis of MDD as well as for the development of effective computer-aided diagnosis tools in clinical settings.

PMID:35958666 | PMC:PMC9360427 | DOI:10.3389/fpsyt.2022.973921

Altered voxel-mirrored homotopic connectivity in right temporal lobe epilepsy as measured using resting-state fMRI and support vector machine analyses

Fri, 08/12/2022 - 10:00

Front Psychiatry. 2022 Jul 26;13:958294. doi: 10.3389/fpsyt.2022.958294. eCollection 2022.


BACKGROUND: Prior reports revealed abnormalities in voxel-mirrored homotopic connectivity (VMHC) when analyzing neuroimaging data from patients with various psychiatric conditions, including temporal lobe epilepsy (TLE). Whether these VHMC changes can be leveraged to aid in the diagnosis of right TLE (rTLE), however, remains to be established. This study was thus developed to examine abnormal VMHC findings associated with rTLE to determine whether these changes can be used to guide rTLE diagnosis.

METHODS: The resultant imaging data of resting-state functional MRI (rs-fMRI) analyses of 59 patients with rTLE and 60 normal control individuals were analyzed using VMHC and support vector machine (SVM) approaches.

RESULTS: Relative to normal controls, patients with rTLE were found to exhibit decreased VMHC values in the bilateral superior and the middle temporal pole (STP and MTP), the bilateral middle and inferior temporal gyri (MTG and ITG), and the bilateral orbital portion of the inferior frontal gyrus (OrbIFG). These patients further exhibited increases in VMHC values in the bilateral precentral gyrus (PreCG), the postcentral gyrus (PoCG), and the supplemental motor area (SMA). The ROC curve of MTG VMHC values showed a great diagnostic efficacy in the diagnosis of rTLE with AUCs, sensitivity, specificity, and optimum cutoff values of 0.819, 0.831, 0.717, and 0.465. These findings highlight the value of the right middle temporal gyrus (rMTG) when differentiating between rTLE and control individuals, with a corresponding SVM analysis yielding respective accuracy, sensitivity, and specificity values of 70.59% (84/119), 78.33% (47/60), and 69.49% (41/59).

CONCLUSION: In summary, patients with rTLE exhibit various forms of abnormal functional connectivity, and SVM analyses support the potential value of abnormal VMHC values as a neuroimaging biomarker that can aid in the diagnosis of this condition.

PMID:35958657 | PMC:PMC9360423 | DOI:10.3389/fpsyt.2022.958294

Resting-state functional magnetic resonance imaging-based identification of altered brain the fractional amplitude of low frequency fluctuation in adolescent major depressive disorder patients undergoing electroconvulsive therapy

Fri, 08/12/2022 - 10:00

Front Psychiatry. 2022 Jul 25;13:972968. doi: 10.3389/fpsyt.2022.972968. eCollection 2022.


PURPOSE: While electroconvulsive therapy (ECT) has been repeatedly been shown to effectively and efficiently treat the major depressive disorder (MDD), the mechanistic basis for such therapeutic efficacy remains to be firmly established. As such, further research exploring the ECT-based treatment of MDD in an adolescent population is warranted.

METHODS: This study included 30 treatment-naïve first-episode MDD patients and 30 healthy control (HC) individuals (aged 12-17 years). All participants were scanned using rs-fMRI, and the 30 MDD patients were scanned again after 2 weeks of the ECT treatment period. Intrinsic local activity in each voxel was assessed based on the fractional amplitude of low frequency fluctuation (fALFF) parameter, with all fALFF analyses being completed using the REST application. Correlations between ECT-related changes in fALFF and clinical parameters were additionally examined.

RESULTS: Relative to HCs, MDD patients exhibited increased fALFF values in the right inferior frontal gyrus (ORBinf), inferior occipital gyrus (IOG), and the left middle frontal gyrus (MFG) at baseline. Following ECT, these patients exhibited significant increases in fALFF values in the right medial superior frontal gyrus (SFGmed), dorsolateral superior frontal gyrus (SFGdor), anterior cingulate, and paracingulate gyrus (ACG), median cingulate and paracingulate gyrus (DCG), and left MFG. MDD patient HAMD scores were negatively correlated with fALFF values when analyzing pre-ECT vs. post-HCT ΔHAMD and fALFF values in the right SFGmed, SFGdor, and the left MFG.

CONCLUSION: These data suggest that ECT induced altered fALFF in some regions of the brain, suggesting that these alterations may serve as a neurobiological indicator of ECT effectiveness in MDD adolescents.

PMID:35958635 | PMC:PMC9357980 | DOI:10.3389/fpsyt.2022.972968

Higher access to screens is related to decreased functional connectivity between neural networks associated with basic attention skills and cognitive control in children

Fri, 08/12/2022 - 10:00

Child Neuropsychol. 2022 Aug 11:1-20. doi: 10.1080/09297049.2022.2110577. Online ahead of print.


Screen-based media has become a prevailing part of children's lives. Different technologies provide limitless access to a wide range of content. This accessibility has immensely increased screen exposure among children, showing that this exposure is associated with decreased cognitive abilities. This study was designed to evaluate how the neurobiological correlates for different sub-components of screen exposure, such as level of access, content, and frequency, are related to different cognitive abilities. Resting-state functional MRI data were collected in 29 native English-speaking children (8-12 years old), in addition to cognitive-behavioral measures. Functional connectivity measures within and between several networks related to cognitive control and attention were calculated [fronto-parietal (FP), cingulo-opercular (CO), dorsal attention (DAN), ventral attention (VAN), salience, default mode (DMN), cerebellar networks]. Sub-components of screen exposure were measured using the Screen-Q questionnaire. Higher access to screens was related to lower functional connectivity between neural networks associated with basic attention skills and cognitive control (i.e., DAN and salience). In addition, higher levels of parent-child interaction during screen exposure were related to increased functional connectivity between networks related to cognitive control and learning (i.e., CO and cerebellar). These findings suggest that screen exposure may reduce the engagement of basic attention and modulation of cognitive control networks and that higher levels of parent-child interaction engage cognitive control networks. An enhanced understanding of these processes can provide an important scientific basis for future educational and medical approaches regarding screen exposure.

PMID:35957604 | DOI:10.1080/09297049.2022.2110577

Altered time-varying local spontaneous brain activity pattern in patients with high myopia: a dynamic amplitude of low-frequency fluctuations study

Thu, 08/11/2022 - 10:00

Neuroradiology. 2022 Aug 12. doi: 10.1007/s00234-022-03033-5. Online ahead of print.


PURPOSE: To investigate the abnormal time-varying local spontaneous brain activity in patients with high myopia (HM) on the basis of the dynamic amplitude of low-frequency fluctuations (dALFF) approach.

METHODS: Age and gender matching were performed based on resting-state functional magnetic resonance imaging data from 86 HM patients and 87 healthy controls (HCs). Local spontaneous brain activities were evaluated using the time-varying dALFF method. Support vector machine combined with the radial basis function kernel was used for pattern classification analysis.

RESULTS: Inter-group comparison between HCs and HM patients has demonstrated that dALFF variability in the left inferior frontal gyrus (orbital part), left lingual gyrus, right anterior cingulate and paracingulate gyri, and right calcarine fissure and surrounding cortex was decreased in HM patients, while increased in the left thalamus, left paracentral lobule, and left inferior parietal (except supramarginal and angular gyri). Pattern classification between HM patients and HCs displayed a classification accuracy of 85.5%.

CONCLUSION: In this study, the findings mentioned above have suggested the association between local brain activities of HM patients and abnormal variability in brain regions performing visual sensorimotor and attentional control functions. Several useful information has been provided to elucidate the mechanism-related alterations of the myopic nervous system. In addition, the significant role of abnormal dALFF variability has been highlighted to achieve an in-depth comprehension of the pathological alterations and neuroimaging mechanisms in the field of HM.

PMID:35953566 | DOI:10.1007/s00234-022-03033-5

Genetic profile for dopamine signaling predicts brain functional reactivity to repetitive transcranial magnetic stimulation

Thu, 08/11/2022 - 10:00

Eur Arch Psychiatry Clin Neurosci. 2022 Aug 11. doi: 10.1007/s00406-022-01436-2. Online ahead of print.


Research integrating molecular and imaging data provides important insights into how the genetic profile associated with dopamine signaling influences inter-individual differences in brain functions. However, the effects of genetic variations in dopamine signaling on the heterogeneity of brain changes induced by repetitive transcranial magnetic stimulation (rTMS) still remain unclear. The current study examined the composite effects of genetic variations in dopamine-related genes on rTMS-induced brain responses in terms of the functional network connectivity and working memory performance. Healthy individuals (n = 30) participated in a randomized, double-blind, sham-controlled study with a crossover design of five consecutive days where active rTMS or sham stimulation sessions were administered over the left dorsolateral prefrontal cortex (DLPFC) of the brain. Participants were mostly women (n = 29) and genotyped for polymorphisms in the catechol-O-methyltransferase and D2 dopamine receptor genes and categorized according to their genetic composite scores: high vs. low dopamine signaling groups. Pre- and post-intervention data of resting-state functional magnetic resonance imaging and working memory performance were obtained from 27 individuals with active rTMS and 30 with sham stimulation sessions. The mean functional connectivity within the resting-state networks centered on the DLPFC increased in the high dopamine signaling group. Working memory performance also improved with rTMS in the high dopamine signaling group compared to that in the low dopamine signaling group. The present results suggest that genetic predisposition to higher dopamine signaling may be a promising neurobiological predictor for rTMS effects on cognitive enhancement.Trial registration: (NCT02932085).

PMID:35951113 | DOI:10.1007/s00406-022-01436-2

Task-based functional connectivity of the Useful Field of View (UFOV) fMRI task

Wed, 08/10/2022 - 10:00

Geroscience. 2022 Aug 11. doi: 10.1007/s11357-022-00632-1. Online ahead of print.


Declines in processing speed performance occur in aging and are a critical marker of functional independence in older adults. Numerous studies suggest that Useful Field of View (UFOV) training may ameliorate cognitive decline in older adults. Despite its efficacy, little is known about the neural correlates of this task. The current study is the first to investigate the coherence of functional connectivity during UFOV task completion. A total of 336 participants completed the UFOV task while undergoing task-based functional magnetic resonance imaging (fMRI). Ten spherical regions of interest (ROIs), selected a priori, were created based on regions with the greatest peak BOLD activation patterns in the UFOV fMRI task and regions that have been shown to significantly relate to UFOV fMRI task performance. We used a weighted ROI-to-ROI connectivity analysis to model task-specific functional connectivity strength between these a priori selected ROIs. We found that our UFOV fMRI network was functionally connected during task performance and was significantly associated to UFOV fMRI task performance. Within-network connectivity of the UFOV fMRI network showed comparable or better predictive power in accounting for UFOV accuracy compared to 7 resting state networks, delineated by Yeo and colleagues. Finally, we demonstrate that the within-network connectivity of UFOV fMRI task accounted for scores on a measure of "near transfer", the Double Decision task, better than the aforementioned resting state networks. Our data elucidate functional connectivity patterns of the UFOV fMRI task. This may assist in future targeted interventions that aim to improve synchronicity within the UFOV fMRI network.

PMID:35948860 | DOI:10.1007/s11357-022-00632-1

Alcohol use disorder-associated structural and functional characteristics of the insula

Wed, 08/10/2022 - 10:00

J Neurosci Res. 2022 Aug 10. doi: 10.1002/jnr.25113. Online ahead of print.


Based on our current understanding of insular regions, effects of chronic alcohol use on the insula may affect the integration of sensory-motor, socio-emotional, and cognitive function. There is no comprehensive understanding about these differences in individuals with alcohol use disorder that accounts for both structural and functional differences related to chronic alcohol use. The purpose of this study was to investigate these variations in both the anterior and posterior insula in persons with alcohol use disorder. We investigated insula gray matter volume, morphometry, white matter structural connectivity, and resting state functional connectivity in 75 participants with alcohol use disorder (females = 27) and 75 age-matched healthy control participants (females = 39). Results indicated structural differences mostly in the anterior regions, while functional connectivity differences were observed in both the anterior and posterior insula in those with alcohol use disorder. Differing connectivity was observed with frontal, parietal, occipital, cingulate, cerebellar, and temporal brain regions. While these results align with prior studies showing differences primarily in anterior insular regions, they also contribute to the existing literature suggesting differences in anterior insular connectivity with brain regions shown to be engaged during higher cognitive and emotional tasks.

PMID:35946335 | DOI:10.1002/jnr.25113

Multimodal multi-center analysis of electroconvulsive therapy effects in depression: Brainwide gray matter increase without functional changes

Tue, 08/09/2022 - 10:00

Brain Stimul. 2022 Aug 6:S1935-861X(22)00171-1. doi: 10.1016/j.brs.2022.07.053. Online ahead of print.


BACKGROUND: Electroconvulsive therapy (ECT) is an effective treatment for severe depression and induces gray matter (GM) increases in the brain. Small-scale studies suggest that ECT also leads to changes in brain functioning, but findings are inconsistent. In this study, we investigated the influence of ECT on changes in both brain structure and function and their relation to clinical improvement using multicenter neuroimaging data from the Global ECT-MRI Research Collaboration (GEMRIC).

METHODS: We analyzed T1-weighted structural magnetic resonance imaging (MRI) and functional resting-state MRI data of 88 individuals (49 male) with depressive episodes before and within one week after ECT. We performed voxel-based morphometry on the structural data and calculated fractional amplitudes of low-frequency fluctuations, regional homogeneity, degree centrality, functional connectomics, and hippocampus connectivity for the functional data in both unimodal and multimodal analyses. Longitudinal effects in the ECT group were compared to repeated measures of healthy controls (n = 27).

RESULTS: Wide-spread increases in GM volume were found in patients following ECT. In contrast, no changes in any of the functional measures were observed, and there were no significant differences in structural or functional changes between ECT responders and non-responders. Multimodal analysis revealed that volume increases in the striatum, supplementary motor area and fusiform gyrus were associated with local changes in brain function.

CONCLUSION: These results confirm wide-spread increases in GM volume, but suggest that this is not accompanied by functional changes or associated with clinical response. Instead, focal changes in brain function appear related to individual differences in brain volume increases.

PMID:35944604 | DOI:10.1016/j.brs.2022.07.053

Hippocampal Functional Connectivity in Parkinson's Disease

Tue, 08/09/2022 - 10:00

Neurodegener Dis. 2022 Aug 9. doi: 10.1159/000526377. Online ahead of print.


BACKGROUND: While the hippocampus is not part of the nigrostriatal dopaminergic pathway, influence of Parkinson's Disease (PD) to the hippocampus has been consistently implicated. However, it is not clear how the hippocampal changes contribute to the pathology of PD.

OBJECTIVES: We aimed to elucidate the physiological changes of the hippocampus in its orchestration with the rest of the brain.

METHODS: Using the resting state fMRI data from Parkinson's Progression Markers Initiative (PPMI), functional connectivity of the hippocampus was analyzed in 93 individuals with PD and 18 individuals without PD.

RESULTS: A whole brain voxel-wise analysis showed that the bilateral paracingulate gyri were less connected to the hippocampus in the PD group compared to the control group. The hippocampus-paracingulate dysconnectivity did not show association with cognitive indices.

CONCLUSIONS: The hippocampus in PD shows dysconnectivity to the paracingulate gyri.

PMID:35944512 | DOI:10.1159/000526377

Contrasting the amygdala activity and functional connectivity profile between antidepressant-free participants with major depressive disorder and healthy controls: A systematic review of comparative fMRI studies

Tue, 08/09/2022 - 10:00

Psychiatry Res Neuroimaging. 2022 Jul 22;325:111517. doi: 10.1016/j.pscychresns.2022.111517. Online ahead of print.


Functional neuroimaging research suggests that the amygdala is implicated in the pathophysiology of major depressive disorder (MDD). This systematic review aimed to identify consistently reported amygdala activity and functional connectivity (FC) abnormalities in antidepressant-free participants with MDD as compared to healthy controls at baseline (i.e., before treatment initiation or experimental manipulation). A search for relevant published studies and registered clinical trials was conducted through OVID (MEDLINE, PsycINFO, and Embase) and with an end date of March 7th, 2022. Fifty published studies and two registered clinical trials were included in this review. Participants with MDD frequently exhibited amygdala hyperactivity in response to negative stimuli, abnormal event-related amygdala-anterior cingulate cortex (ACC) FC, and abnormal resting-state amygdala FC with the insula and the prefrontal, temporal, and parietal cortices. Decreased resting-state FC was consistently found between the amygdala and the orbitofrontal cortex, striatum, cerebellum, and middle/inferior frontal gyri. Due to the limited number of studies examining resting-state amygdala activity and FC with specific subregions of interest, including those within the ACC, further investigation is warranted.

PMID:35944425 | DOI:10.1016/j.pscychresns.2022.111517

Altered dynamic functional connectivity of striatal-cortical circuits in Juvenile Myoclonic Epilepsy

Tue, 08/09/2022 - 10:00

Seizure. 2022 Jul 2;101:103-108. doi: 10.1016/j.seizure.2022.07.002. Online ahead of print.


OBJECTIVE: To investigate whether the dynamic functional connectivity (dFC) of striatal-cortical circuits changes in juvenile myoclonic epilepsy (JME).

METHODS: The resting-state EEG-fMRI and the sliding-window approach were adopted to explore the dynamic striatal-cortical circuitry in thirty JME patients compared with 30 well-matched health controls (HCs). Six pairs of striatal seeds were selected as regions of interests. The correlation analysis was performed to reveal the relationship between the altered dFC variability and clinical variables in JME group.

RESULTS: JME patients exhibited increased dFC variability mainly involved in fronto-striatal and striatal-thalamic networks; decreased dFC variability between striatum subdivisions and default mode network (DMN) regions compared with HCs (p<0.05, GRF corrected). In addition, the hypervariability between left ventral-rostral putamen and left medial superior frontal gyrus was positively (r= 0.493, p=0.008) correlated with the mean frequency score of myoclonic seizures in JME group.

CONCLUSION: JME presented altered dFC variability in striatal-cortical circuits. The pattern of altered circuits showed increased variability in fronto-striatal and striatal-thalamic networks and decreased variability in striatal-DMN. These results provide novel information about the dynamic neural striatal-cortical circuitry of JME.

PMID:35944422 | DOI:10.1016/j.seizure.2022.07.002

Comparison of resting state and task-based functional MRI in preoperative mapping in patients with brain gliomas

Tue, 08/09/2022 - 10:00

Zh Vopr Neirokhir Im N N Burdenko. 2022;86(4):33-40. doi: 10.17116/neiro20228604133.


OBJECTIVE: To analyze and compare the results of cerebral cortex mapping with task-based (tb-fMRI) and resting-state functional MRI in patients with glioma of eloquent cortical areas.

MATERIAL AND METHODS: There were 55 patients (24 men and 31 women aged 24 - 74 years, median 39) with glial tumors. In 26 patients, the tumor was located in motor areas. Twenty-nine patients had lesions of Broca and Wernicke's areas. All patients underwent preoperative tb-fMRI and rs-fMRI. Then, resection of tumor was carried out in all cases.

RESULTS: Comparison of fMRI and rs-fMRI activation maps was assessed by calculating the Dice coefficient for inclusive speech and motor cortex masks and exclusive masks without brainstem, cerebellum, subcortical nuclei. Inclusive Dice coefficient for motor cortex ranged from 0.11 to 0.50, for speech cortex - from 0.006 to 0.240 (p<0.05). In case of exclusive masks, this value ranged from 0.15 to 0.55 for motor cortex and from 0.004 to 0.205 for speech cortex (p<0.05).

CONCLUSION: When comparing the results of cortical mapping in patients with glial tumors, the use of hemispheric exclusive and inclusive masks did not significantly increase activation maps matching. Probably, low degree of correspondence was associated with different genesis of activations, as well as with high variability of speech cortex.

PMID:35942835 | DOI:10.17116/neiro20228604133

Machine learning for resting state fMRI-based preoperative mapping: comparison with task-based fMRI and direct cortical stimulation

Tue, 08/09/2022 - 10:00

Zh Vopr Neirokhir Im N N Burdenko. 2022;86(4):25-32. doi: 10.17116/neiro20228604125.


OBJECTIVE: To develop a system for preoperative prediction of individual activations of motor and speech areas in patients with brain gliomas using resting state fMRI (rsfMRI), task-based fMRI (tb-fMRI), direct cortical stimulation and machine learning methods.

MATERIAL AND METHODS: Thirty-three patients with gliomas (19 females and 14 males aged 19 - 540) underwent DCS-assisted resection of tumor (19 ones with lesion of motor zones and 14 patients with lesions of speech areas). Awake craniotomy was performed in 14 cases. Preoperative mapping was performed according to special MRI protocol (T1, tb-fMRI, rs-fMRI).

Machine learning system was built on open source data from The Human Connectome Project. MR data of 200 healthy subjects from this database were used for system pre-training. Further, this system was trained on the data of our patients with gliomas.

RESULTS: In DCS, we obtained 332 stimulations including 173 with positive response. According to comparison of functional activations between rs-fMRI and tb-fMRI, there were more positive DCS responses predicted by rs-fMRI (132 vs 112). Non-response stimulation sites (negative) prevailed in tb-fMRI activations (69 vs 44).

CONCLUSION: The developed method with machine learning based on resting state fMRI showed greater sensitivity compared to classical task-based fMRI after verification with DCS: 0.72 versus 0.66 (p<0.05) for identifying the speech zones and 0.79 versus 0.62 (p<0.05) for motor areas.

PMID:35942834 | DOI:10.17116/neiro20228604125

Functional Connectivity Disturbances of the Locus Coeruleus in Chronic Insomnia Disorder

Tue, 08/09/2022 - 10:00

Nat Sci Sleep. 2022 Aug 2;14:1341-1350. doi: 10.2147/NSS.S366234. eCollection 2022.


INTRODUCTION: In recent years, people have gained a profound understanding of chronic insomnia disorder (CID), but the pathophysiological mechanism of CID is still unclear. There is some evidence that the locus coeruleus (LC) is involved in the regulation of wakefulness in CID, but there have been few studies using brain functional imaging. The purpose of this study was to evaluate the resting-state functional connectivity (FC) between the LC and other brain voxels in CID and whether these abnormal FC are involved in the regulation of wakefulness.

METHODS: A total of 49 patients with chronic insomnia disorder and 47 healthy controls (HC) matched for gender, age, and education were examined with rs-fMRI in this study. The LC was selected as the region of interest, and then seed-based analysis was conducted on the LC and other voxels to obtain the brain regions with abnormal FC. The correlation between the FC value of the abnormal connection area and the clinical scale score was analyzed.

RESULTS: Compared with the HC, the FC between the LC and right precuneus, right posterior cingulate cortex, left middle temporal gyrus, left calcarine, and right superior orbitofrontal cortex was significantly enhanced (p < 0.05, FDR correction), and the functional connectivity signal value between the locus coeruleus and left middle temporal gyrus was positively correlated with the Self-Rating Depression Scale (p = 0.021).

CONCLUSION: The abnormal FC between the LC and multiple brain regions may contribute to a better understanding of the neurobiological mechanism of CID.

PMID:35942365 | PMC:PMC9356738 | DOI:10.2147/NSS.S366234