Most recent paper
Effective Connectivity Evaluation of Resting-State Brain Networks in Alzheimer's Disease, Amnestic Mild Cognitive Impairment, and Normal Aging: An Exploratory Study
Brain Sci. 2023 Feb 4;13(2):265. doi: 10.3390/brainsci13020265.
(1) Background: Alzheimer's disease (AD) is a neurodegenerative disease with a high prevalence. Despite the cognitive tests to diagnose AD, there are pitfalls in early diagnosis. Brain deposition of pathological markers of AD can affect the direction and intensity of the signaling. The study of effective connectivity allows the evaluation of intensity flow and signaling pathways in functional regions, even in the early stage, known as amnestic mild cognitive impairment (aMCI). (2) Methods: 16 aMCI, 13 AD, and 14 normal subjects were scanned using resting-state fMRI and T1-weighted protocols. After data pre-processing, the signal of the predefined nodes was extracted, and spectral dynamic causal modeling analysis (spDCM) was constructed. Afterward, the mean and standard deviation of the Jacobin matrix of each subject describing effective connectivity was calculated and compared. (3) Results: The maps of effective connectivity in the brain networks of the three groups were different, and the direction and strength of the causal effect with the progression of the disease showed substantial changes. (4) Conclusions: Impaired information flow in the resting-state networks of the aMCI and AD groups was found versus normal groups. Effective connectivity can serve as a potential marker of Alzheimer's pathophysiology, even in the early stages of the disease.
PMID:36831808 | DOI:10.3390/brainsci13020265
OViTAD: Optimized Vision Transformer to Predict Various Stages of Alzheimer's Disease Using Resting-State fMRI and Structural MRI Data
Brain Sci. 2023 Feb 3;13(2):260. doi: 10.3390/brainsci13020260.
Advances in applied machine learning techniques for neuroimaging have encouraged scientists to implement models to diagnose brain disorders such as Alzheimer's disease at early stages. Predicting the exact stage of Alzheimer's disease is challenging; however, complex deep learning techniques can precisely manage this. While successful, these complex architectures are difficult to interrogate and computationally expensive. Therefore, using novel, simpler architectures with more efficient pattern extraction capabilities, such as transformers, is of interest to neuroscientists. This study introduced an optimized vision transformer architecture to predict the group membership by separating healthy adults, mild cognitive impairment, and Alzheimer's brains within the same age group (>75 years) using resting-state functional (rs-fMRI) and structural magnetic resonance imaging (sMRI) data aggressively preprocessed by our pipeline. Our optimized architecture, known as OViTAD is currently the sole vision transformer-based end-to-end pipeline and outperformed the existing transformer models and most state-of-the-art solutions. Our model achieved F1-scores of 97%±0.0 and 99.55%±0.39 from the testing sets for the rs-fMRI and sMRI modalities in the triple-class prediction experiments. Furthermore, our model reached these performances using 30% fewer parameters than a vanilla transformer. Furthermore, the model was robust and repeatable, producing similar estimates across three runs with random data splits (we reported the averaged evaluation metrics). Finally, to challenge the model, we observed how it handled increasing noise levels by inserting varying numbers of healthy brains into the two dementia groups. Our findings suggest that optimized vision transformers are a promising and exciting new approach for neuroimaging applications, especially for Alzheimer's disease prediction.
PMID:36831803 | DOI:10.3390/brainsci13020260
Neuronal dysfunction in individuals at early stage of schizophrenia, A resting-state fMRI study
Psychiatry Res. 2023 Feb 20;322:115123. doi: 10.1016/j.psychres.2023.115123. Online ahead of print.
Schizophrenia has been associated with abnormal intrinsic brain activity, involving various cognitive impairments. Qualitatively similar abnormalities are seen in individuals at ultra-high risk (UHR) for psychosis. In this study, resting-state fMRI (rs-fMRI) data were collected from 44 drug-naïve first-episode schizophrenia (Dn-FES) patients, 48 UHR individuals, and 40 healthy controls (HCs). The fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo), and functional connectivity (FC), were performed to evaluate resting brain function. A support vector machine (SVM) was applied for classification analysis. Compared to HCs, both clinical groups showed increased fALFF in the central executive network (CEN), decreased ReHo in the ventral visual pathway (VVP) and decreased FC in temporal-sensorimotor regions. Excellent performance was achieved by using fALFF value in distinguishing both FES (sensitivity=83.21%, specificity=80.58%, accuracy=81.37%, p=0.009) and UHR (sensitivity=75.88%, specificity=85.72%, accuracy=80.72%, p<0.001) from HC group. Moreover, the study highlighted the importance of frontal and temporal alteration in the pathogenesis of schizophrenia. However, no fMRI features were observed that could well distinguish Dn-FES from UHR group. To conclude, fALFF in the CEN may provide potential power for identifying individuals at the early stage of schizophrenia and the alteration in the frontal and temporal lobe may be important to these individuals.
PMID:36827856 | DOI:10.1016/j.psychres.2023.115123
Interhemispheric parietal cortex connectivity reflects improvement in post-stroke spasticity due to treatment with botulinum toxin-A
J Neurol Sci. 2023 Feb 15;446:120588. doi: 10.1016/j.jns.2023.120588. Online ahead of print.
In post-stroke spasticity (PSS), effective treatment with botulinum neurotoxin (BoNT) is associated with transient decrease in activation of the ipsilesional superior parietal lobule (SPL) and intraparietal sulcus (IPS). We hypothesized that this would be reflected in changes in resting-state functional connectivity (rsFC) of the SPL/IPS. Our aim was therefore to assess rsFC of the ipsilesional SPL/IPS in chronic stroke patients with hemiparesis both with and without PSS and to explore the relationship between SPL/IPS rsFC and PSS severity. To this end, fourteen chronic stroke patients with upper limb weakness and PSS (the PSS group) and 8 patients with comparable weakness but no PSS (the control group) underwent clinical evaluation and 3 fMRI examinations, at baseline (W0) and 4 and 11 weeks after BoNT (W4 and W11, respectively). Seed-based rsFC of the atlas-based SPL and IPS was evaluated using a group×time interaction analysis and a correlation analysis with PSS severity (modified Ashworth scale), integrity of the ipsilesional somatosensory afferent pathway (evoked potential N20 latency), and age. In the PSS group, transient improvement in PSS was associated with increase in rsFC between the ipsilesional IPS and the contralesional SPL at W4. The interhemispheric connectivity was negatively correlated with PSS severity at baseline and with PSS improvement at W4. We propose adaptation of the internal forward model as the putative underlying mechanism and discuss its possible association with increased limb use, diminished spastic dystonia, or improved motor performance, as well as its potential contribution to the clinical effects of BoNT.
PMID:36827809 | DOI:10.1016/j.jns.2023.120588
Dissociable brainstem functional connectivity changes correlate with objective and subjective vigilance decline after total sleep deprivation in healthy male subjects
J Neurosci Res. 2023 Feb 24. doi: 10.1002/jnr.25182. Online ahead of print.
The maintenance of vigilance relies on the activation of the cerebral cortex by the arousal system centered on the brainstem. Previous studies have suggested that both objective and subjective vigilance are susceptible to sleep deprivation. This study aims to explore the alterations in brainstem arousal system functional connectivity (FC) and its involvement in these two types of vigilance decline following total sleep deprivation (TSD). Thirty-seven healthy male subjects underwent two counterbalanced resting-state fMRI scans, once in rested wakefulness (RW) and once after 36 h of TSD. The pontine tegmental area and caudal midbrain (PTA-cMidbrain), the core regions of the brainstem arousal system, were chosen as the seeds for FC analysis. The difference in PTA-cMidbrain FC between RW and TSD conditions was then investigated, as well as its associations with objective vigilance measured by psychomotor vigilance task (PVT) and subjective vigilance measured by Stanford Sleepiness Scale. The sleep-deprived subjects showed increased PTA-cMidbrain FC with the thalamus and cerebellum and decreased PTA-cMidbrain FC with the occipital, parietal, and sensorimotor regions. TSD-induced increases in PVT reaction time were negatively correlated with altered PTA-cMidbrain FC in the dorsolateral prefrontal cortex, extrastriate visual cortex, and precuneus. TSD-induced increases in subjective sleepiness were positively correlated with altered PTA-cMidbrain FC in default mode regions including the medial prefrontal cortex and precuneus. Our results suggest that different brainstem FC patterns underlie the objective and subjective vigilance declines induced by TSD.
PMID:36827444 | DOI:10.1002/jnr.25182
Exploring impaired self-awareness of motor symptoms in Parkinson's disease: Resting-state fMRI correlates and the connection to mindfulness
PLoS One. 2023 Feb 24;18(2):e0279722. doi: 10.1371/journal.pone.0279722. eCollection 2023.
OBJECTIVE: To further explore the phenomenon of impaired self-awareness of motor symptoms in patients with Parkinson's Disease by using an evaluated measurement approach applied in previous studies, while also examining its connection with dispositional mindfulness and possible correlates of functional connectivity.
BACKGROUND: Recently, the phenomenon of impaired self-awareness has been studied more intensively by applying different measurement and imaging methods. Existing literature also points towards a possible connection with mindfulness, which has not been examined in a cross-sectional study. There is no data available concerning correlates of functional connectivity.
METHODS: Non-demented patients with idiopathic Parkinson's Disease without severe depression were tested for impaired self-awareness for motor symptoms following a psychometrically evaluated approach. Mindfulness was measured by applying the German version of the Five Facet Mindfulness Questionnaire. A subset of eligible patients underwent functional MRI scanning. Spearman correlation analyses were performed to examine clinical data. Whole-brain voxelwise regressions between seed-based connectivity and behavioral measures were calculated to identify functional connectivity correlates of impaired self-awareness scores.
RESULTS: A total of 41 patients with Parkinson's Disease were included. 15 patients successfully underwent resting-state fMRI scanning. Up to 88% of patients showed signs of impaired self-awareness. Awareness for hypokinetic movements correlated with total mindfulness values and three facets, while awareness for dyskinetic movements did not. Three significant clusters between scores of impaired self-awareness in general and for dyskinetic movements were identified linking behavioral measures with the functional connectivity of the inferior frontal gyrus, the right insular cortex, the supplementary motor area, and the precentral gyrus among others. Impaired self-awareness for hypokinetic movements did not have any neural correlate.
CONCLUSIONS: Clinical data is comparable with results from previous studies applying the same structured approach to measure impaired self-awareness in Parkinson's Disease. Functional connectivity analyses were conducted for the first time to evaluate neural correlates thereof. This data does not support a connection between impaired self-awareness of motor symptoms and dispositional mindfulness.
PMID:36827321 | DOI:10.1371/journal.pone.0279722
Altered dynamic functional connectivity associates with post-traumatic stress disorder
Brain Imaging Behav. 2023 Feb 24. doi: 10.1007/s11682-023-00760-y. Online ahead of print.
Research has been looking into neural pathophysiology of post-traumatic stress disorder (PTSD) and dynamic functioning connectivity (dFC) applying resting state functional magnetic resonance imaging (rs-fMRI). Previous studies showed that PTSD related impairments are associated with alterations distributed across different brain regions and disorganized functional connectivity, especially in Default Mode Network and the cerebellar area. In this study, we specifically looked into dFC on a whole brain level, and we focused on critical regions such as DMN and cerebellum. To explore the characteristics of dFC among patients with PTSD, we collected rs-fMRI data from 27 PTSD patients and 30 healthy controls. The study also added a control group of 33 trauma-exposed individuals to further look into trauma impact. Utilizing group spatial independent component analysis (ICA), the dynamic properties on whole brain level were detected with sliding time window approach, and k-means clustering. Two reoccurring FC "States" were identified, with connections being more concentrated on a within-network level in one state and more strongly inter-connected in the other state. Abnormalities in dFC were found within DMN, between DMN and cerebellum, and between DMN and visual network for PTSD patients. The findings were in accordance with the study hypothesis that the dFC alterations might point to deficits in emotional modulation and dysfunctional self-referential thought. Abnormalities in dFC among PTSD patients might also be indicators of PTSD symptoms including depression and anxiety, hypervigilance, impaired cognitive functioning and self-referential information processing.
PMID:36826627 | DOI:10.1007/s11682-023-00760-y
Functional correlates of neurological soft signs in heavy cannabis users
Addict Biol. 2023 Mar;28(3):e13270. doi: 10.1111/adb.13270.
Sensorimotor dysfunction has been previously reported in persons with cannabis dependence. Such individuals can exhibit increased levels of neurological soft signs (NSS), particularly involving motor coordination, sensorimotor integration and complex motor task performance. Abnormal NSS levels can also be detected in non-dependent individuals with heavy cannabis use (HCU), yet very little is known about the functional correlates underlying such deficits. Here, we used resting-state functional magnetic resonance imaging (MRI) to investigate associations between NSS and intrinsic neural activity (INA) in HCU (n = 21) and controls (n = 26). Compared with controls, individuals with HCU showed significantly higher NSS across all investigated subdomains. Three of these subdomains, that is, motor coordination, sensorimotor integration and complex motor task behaviour, were associated with specific use-dependent variables, particularly age of onset of cannabis use and current cannabis use. Between-group comparisons of INA revealed lower regional homogeneity (ReHo) in left precentral gyrus, left inferior occipital gyrus, right triangular pat of the inferior frontal gyrus and right precentral gyrus in HCU compared with controls. In addition, HCU showed also higher ReHo in right cerebellum and left postcentral gyrus compared with controls. Complex motor task behaviour in HCU was significantly related to INA in postcentral, inferior frontal and occipital cortices. Our findings indicate abnormal ReHo in HCU in regions associated with sensorimotor, executive control and visuomotor-integration processes. Importantly, we show associations between ReHo, cannabis-use behaviour and execution of complex motor tasks. Given convergent findings in manifest psychotic disorders, this study suggests an HCU endophenotype that may present with a cumulative risk for psychosis.
PMID:36825488 | DOI:10.1111/adb.13270
Identifying body awareness-related brain network changes after Spring Forest Qigong™ practice or P.Volve low-intensity exercise in adults with chronic low back pain: a feasibility Phase I Randomized Clinical Trial
medRxiv. 2023 Feb 14:2023.02.11.23285808. doi: 10.1101/2023.02.11.23285808. Preprint.
BACKGROUND: Chronic low back pain (cLBP) affects the quality of life of 52 million Americans and leads to an enormous personal and economic burden. A multidisciplinary approach to cLBP management is recommended. Since medication has limited efficacy and there are mounting concerns about opioid addiction, the American College of Physicians and American Pain Society recommend non-pharmacological interventions, such as mind and body approaches (e.g., Qigong, yoga, Tai Chi) before prescribing medications. Of those, Qigong practice might be most accessible given its gentle movements and because it can be performed standing, sitting, or lying down. The three available Qigong studies in adults with cLBP showed that Qigong reduced pain more than waitlist and equally well than exercise. Yet, the duration and/or frequency of Qigong practice were low (<12 weeks or less than 3x/week). The objectives of this study were to investigate the feasibility of practicing Spring Forest Qigong™ or performing P.Volve low intensity exercises 3x/week for 12 weeks, feasibility of recruitment, data collection, delivery of the intervention as intended, as well as identify estimates of efficacy on brain function and behavioral outcomes after Qigong practice or exercise. To our knowledge, this is the first study investigating the feasibility of the potential effect of Qigong on brain function in adults with cLBP.
METHODS: We conducted a feasibility Phase I Randomized Clinical Trial. Of the 36 adults with cLBP recruited between January 2020 and June 2021, 32 were enrolled and randomized to either 12 weeks of remote Spring Forest Qigong™ practice or remote P.Volve low-intensity exercises. Participants practiced at least 3x/week for 41min/session with online videos. Our main outcome measures were the Numeric Pain Rating Scale (highest, average, and lowest cLBP pain intensity levels in the prior week), assessed weekly and fMRI data (resting-state and task-based fMRI tasks: pain imagery, kinesthetic imagery of a Qigong movement, and robot-guided shape discrimination). We compared baseline resting-state connectivity and brain activation during fMRI tasks in adults with cLBP with data from a healthy control group (n=28) acquired in a prior study. Secondary outcomes included measures of function, disability, body awareness, kinesiophobia, balance, self-efficacy, core muscle strength, and ankle proprioceptive acuity with a custom-build device.
RESULTS: Feasibility of the study design and methods was demonstrated with 30 participants completing the study (94% retention) and reporting high satisfaction with the programs; 96% adherence to P.Volve low-intensity exercises, and 128% of the required practice intensity for Spring Forest Qigong™ practice. Both groups saw promising reductions in low back pain (effect sizes Cohen's d =1.01-2.22) and in most other outcomes ( d =0.90-2.33). Markers of ankle proprioception were not significantly elevated in the cLBP group after the interventions. Brain imaging analysis showed weaker parietal operculum and insula network connectivity in adults with cLBP (n=26), compared to data from a healthy control group (n=28). The pain imagery task elicited lower brain activation of insula, parietal operculum, angular gyrus and supramarginal gyrus at baseline in adults with cLBP than in healthy adults. Adults with cLBP had lower precentral gyrus activation than healthy adults for the Qigong movement and robot task at baseline. Pre-post brain function changes showed individual variability: Six (out of 13) participants in the Qigong group showed increased activation in the parietal operculum, angular gyrus, supramarginal gyrus, and precentral gyrus during the Qigong fMRI task.
INTERPRETATION: Our data indicate the feasibility and acceptability of using Spring Forest Qigong™ practice or P.Volve low-intensity exercises for cLBP relief showing promising results in terms of pain relief and associated symptoms. Our brain imaging results indicated brain function improvements after 12 weeks of Qigong practice in some participants, pointing to the need for further investigation in larger studies.
TRIAL REGISTRATION NUMBER: ClinicalTrials.gov : NCT04164225 .
PMID:36824785 | PMC:PMC9949220 | DOI:10.1101/2023.02.11.23285808
Unified Topological Inference for Brain Networks in Temporal Lobe Epilepsy Using the Wasserstein Distance
ArXiv. 2023 Feb 13:arXiv:2302.06673v1. Preprint.
Persistent homology can extract hidden topological signals present in brain networks. Persistent homology summarizes the changes of topological structures over multiple different scales called filtrations. Doing so detect hidden topological signals that persist over multiple scales. However, a key obstacle of applying persistent homology to brain network studies has always been the lack of coherent statistical inference framework. To address this problem, we present a unified topological inference framework based on the Wasserstein distance. Our approach has no explicit models and distributional assumptions. The inference is performed in a completely data driven fashion. The method is applied to the resting-state functional magnetic resonance images (rs-fMRI) of the temporal lobe epilepsy patients collected at two different sites: University of Wisconsin-Madison and the Medical College of Wisconsin. However, the topological method is robust to variations due to sex and acquisition, and thus there is no need to account for sex and site as categorical nuisance covariates. We are able to localize brain regions that contribute the most to topological differences. We made MATLAB package available at https://github.com/laplcebeltrami/dynamicTDA that was used to perform all the analysis in this study.
PMID:36824424 | PMC:PMC9949148
Prediction of STN-DBS for Parkinson's disease by uric acid-related brain function connectivity: A machine learning study based on resting state function MRI
Front Aging Neurosci. 2023 Feb 7;15:1105107. doi: 10.3389/fnagi.2023.1105107. eCollection 2023.
INTRODUCTION: Parkinson's disease (PD) is a neurodegenerative disorder characterized by dyskinesia and is closely related to oxidative stress. Uric acid (UA) is a natural antioxidant found in the body. Previous studies have shown that UA has played an important role in the development and development of PD and is an important biomarker. Subthalamic nucleus deep brain stimulation (STN-DBS) is a common treatment for PD.
METHODS: Based on resting state function MRI (rs-fMRI), the relationship between UA-related brain function connectivity (FC) and STN-DBS outcomes in PD patients was studied. We use UA and DC values from different brain regions to build the FC characteristics and then use the SVR model to predict the outcome of the operation.
RESULTS: The results show that PD patients with UA-related FCs are closely related to STN-DBS efficacy and can be used to predict prognosis. A machine learning model based on UA-related FC was successfully developed for PD patients.
DISCUSSION: The two biomarkers, UA and rs-fMRI, were combined to predict the prognosis of STN-DBS in treating PD. Neurosurgeons are provided with effective tools to screen the best candidate and predict the prognosis of the patient.
PMID:36824266 | PMC:PMC9941535 | DOI:10.3389/fnagi.2023.1105107
Identification of the Language Network from Resting-State fMRI in Patients with Brain Tumors: How Accurate Are Experts?
AJNR Am J Neuroradiol. 2023 Feb 23. doi: 10.3174/ajnr.A7806. Online ahead of print.
BACKGROUND AND PURPOSE: Resting-state fMRI helps identify neural networks in presurgical patients who may be limited in their ability to undergo task-fMRI. The purpose of this study was to determine the accuracy of identifying the language network from resting-state-fMRI independent component analysis (ICA) maps.
MATERIALS AND METHODS: Through retrospective analysis, patients who underwent both resting-state-fMRI and task-fMRI were compared by identifying the language network from the resting-state-fMRI data by 3 reviewers. Blinded to task-fMRI maps, these investigators independently reviewed resting-state-fMRI ICA maps to potentially identify the language network. Reviewers ranked up to 3 top choices for the candidate resting-state-fMRI language map. We evaluated associations between the probability of correct identification of the language network and some potential factors.
RESULTS: Patients included 29 men and 14 women with a mean age of 41 years. Reviewer 1 (with 17 years' experience) demonstrated the highest overall accuracy with 72%; reviewers 2 and 3 (with 2 and 7 years' experience, respectively) had a similar percentage of correct responses (50% and 55%). The highest accuracy used ICA50 and the top 3 choices (81%, 65%, and 60% for reviewers 1, 2, and 3, respectively). The lowest accuracy used ICA50, limiting each reviewer to the top choice (58%, 35%, and 42%).
CONCLUSIONS: We demonstrate variability in the accuracy of blinded identification of resting-state-fMRI language networks across reviewers with different years of experience.
PMID:36822828 | DOI:10.3174/ajnr.A7806
Functional-structural large-scale brain networks are correlated with neurocognitive impairment in acute mild traumatic brain injury
Quant Imaging Med Surg. 2023 Feb 1;13(2):631-644. doi: 10.21037/qims-22-450. Epub 2022 Nov 29.
BACKGROUND: This study was conducted to investigate topological changes in large-scale functional connectivity (FC) and structural connectivity (SC) networks in acute mild traumatic brain injury (mTBI) and determine their potential relevance to cognitive impairment.
METHODS: Seventy-one patients with acute mTBI (29 males, 42 females, mean age 43.54 years) from Nanjing First Hospital and 57 matched healthy controls (HC) (33 males, 24 females, mean age 46.16 years) from the local community were recruited in this prospective study. Resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI) were acquired within 14 days (mean 3.29 days) after the onset of mTBI. Then, large-scale FC and SC networks with 116 regions from the automated anatomical labeling (AAL) brain atlas were constructed. Graph theory analysis was used to analyze global and nodal metrics. Finally, correlations were assessed between topological properties and neurocognitive performances evaluated by the Montreal Cognitive Assessment (MoCA). Bonferroni correction was performed out for multiple comparisons in all involved analyses.
RESULTS: Compared with HC, acute mTBI patients had a higher normalized clustering coefficient (γ) for FC (Cohen's d=4.076), and higher γ and small worldness (σ) for SC (Cohen's d=0.390 and Cohen's d=0.395). The mTBI group showed aberrant nodal degree (Dc), nodal efficiency (Ne), and nodal local efficiency (Nloc) for FC and aberrant Dc, nodal betweenness (Bc), nodal clustering coefficient (NCp) and Ne for SC mainly in the frontal and temporal, cerebellum, and subcortical areas. Acute mTBI patients also had higher functional-structural coupling strength at both the group and individual levels (Cohen's d=0.415). These aberrant global and nodal topological properties at functional and structural levels were associated with attention, orientation, memory, and naming performances (all P<0.05).
CONCLUSIONS: Our findings suggested that large-scale FC and SC network changes, higher correlation between FC and SC and cognitive impairment can be detected in the acute stage of mTBI. These network aberrances may be a compensatory mechanism for cognitive impairment in acute mTBI patients.
PMID:36819289 | PMC:PMC9929413 | DOI:10.21037/qims-22-450
Changes in brain structure and related functional connectivity during menstruation in women with primary dysmenorrhea
Quant Imaging Med Surg. 2023 Feb 1;13(2):1071-1082. doi: 10.21037/qims-22-683. Epub 2022 Dec 19.
BACKGROUND: Neuroimaging studies have identified altered brain structures and functions in women with primary dysmenorrhea (PDM). However, previous studies focused on either structural or functional changes in specific brain regions rather than combining structural and functional analysis. Therefore, this prospective cross-sectional study aimed to investigate the changes in whole brain structure, and functional variation along with structural abnormalities in women with PDM during menstruation.
METHODS: In all, 31 patients with PDM (PTs) and 31 healthy controls (HCs) were recruited. Voxel-based morphometry (VBM) and surface-based morphometry (SBM) analyses were applied to investigate structural changes based on high-resolution T1-weighted magnetic resonance images. Functional connectivity (FC) analysis was performed to evaluate functional variations related to the brain regions that showed structural group differences. Pearson correlation analysis was performed to assess the relationship between neuroimaging changes and clinical measures.
RESULTS: Compared to HCs, PTs had reduced gray matter volume (GMV) in the right superior temporal gyrus (STG) and reduced thickness in the bilateral orbitofrontal cortex (OFC), left postcentral gyrus (PoCG), and left superior occipital gyrus (SOG). Among these areas, the STG and PoCG are responsible for altered resting-state FC patterns in PTs. Results showed decreased FC between the STG and the left cerebellar posterior lobe (poCb), the right dorsolateral prefrontal cortex (DLPFC), and the left precentral gyrus (PrCG). Results also showed decreased FC between the PoCG and the right precuneus and the right DLPFC. We also found greater FCs between the PoCG and the bilateral poCb, the left middle temporal gyrus (MTG), and the left angular gyrus. In addition, the FCs between the STG and poCb, and DLPFC in PTs were positively correlated with history and Cox menstrual symptom scale (CMSS) scores, respectively, while the FCs between STG and PrCG were negatively correlated with the onset age of PDM.
CONCLUSIONS: Our research found structural abnormalities and related FC changes in several brain regions that were mainly involved in the emotional and sensory aspects of menstrual pain in PDM. These findings could help us understand the occurrence of PDM from a neuroimaging perspective.
PMID:36819245 | PMC:PMC9929379 | DOI:10.21037/qims-22-683
Inter-rater reliability of functional MRI data quality control assessments: A standardised protocol and practical guide using pyfMRIqc
Front Neurosci. 2023 Feb 3;17:1070413. doi: 10.3389/fnins.2023.1070413. eCollection 2023.
Quality control is a critical step in the processing and analysis of functional magnetic resonance imaging data. Its purpose is to remove problematic data that could otherwise lead to downstream errors in the analysis and reporting of results. The manual inspection of data can be a laborious and error-prone process that is susceptible to human error. The development of automated tools aims to mitigate these issues. One such tool is pyfMRIqc, which we previously developed as a user-friendly method for assessing data quality. Yet, these methods still generate output that requires subjective interpretations about whether the quality of a given dataset meets an acceptable standard for further analysis. Here we present a quality control protocol using pyfMRIqc and assess the inter-rater reliability of four independent raters using this protocol for data from the fMRI Open QC project (https://osf.io/qaesm/). Data were classified by raters as either "include," "uncertain," or "exclude." There was moderate to substantial agreement between raters for "include" and "exclude," but little to no agreement for "uncertain." In most cases only a single rater used the "uncertain" classification for a given participant's data, with the remaining raters showing agreement for "include"/"exclude" decisions in all but one case. We suggest several approaches to increase rater agreement and reduce disagreement for "uncertain" cases, aiding classification consistency.
PMID:36816136 | PMC:PMC9936142 | DOI:10.3389/fnins.2023.1070413
Exploration of static functional connectivity and dynamic functional connectivity alterations in the primary visual cortex among patients with high myopia <em>via</em> seed-based functional connectivity analysis
Front Neurosci. 2023 Feb 2;17:1126262. doi: 10.3389/fnins.2023.1126262. eCollection 2023.
AIM: This study was conducted to explore differences in static functional connectivity (sFC) and dynamic functional connectivity (dFC) alteration patterns in the primary visual area (V1) among high myopia (HM) patients and healthy controls (HCs) via seed-based functional connectivity (FC) analysis.
METHODS: Resting-state functional magnetic resonance imaging (fMRI) scans were performed on 82 HM patients and 59 HCs who were closely matched for age, sex, and weight. Seed-based FC analysis was performed to identify alterations in the sFC and dFC patterns of the V1 in HM patients and HCs. Associations between mean sFC and dFC signal values and clinical symptoms in distinct brain areas among HM patients were identified via correlation analysis. Static and dynamic changes in brain activity in HM patients were investigated by assessments of sFC and dFC via calculation of the total time series mean and sliding-window analysis.
RESULTS: In the left anterior cingulate gyrus (L-ACG)/left superior parietal gyrus (L-SPG) and left V1, sFC values were significantly greater in HM patients than in HCs. In the L-ACG and right V1, sFC values were also significantly greater in HM patients than in HCs [two-tailed, voxel-level P < 0.01, Gaussian random field (GRF) correction, cluster-level P < 0.05]. In the left calcarine cortex (L-CAL) and left V1, dFC values were significantly lower in HM patients than in HCs. In the right lingual gyrus (R-LING) and right V1, dFC values were also significantly lower in HM patients than in HCs (two-tailed, voxel-level P < 0.01, GRF correction, cluster-level P < 0.05).
CONCLUSION: Patients with HM exhibited significantly disturbed FC between the V1 and various brain regions, including L-ACG, L-SPG, L-CAL, and R-LING. This disturbance suggests that patients with HM could exhibit impaired cognitive and emotional processing functions, top-down control of visual attention, and visual information processing functions. HM patients and HCs could be distinguished from each other with high accuracy using sFC and dFC variabilities. These findings may help to identify the neural mechanism of decreased visual performance in HM patients.
PMID:36816124 | PMC:PMC9932907 | DOI:10.3389/fnins.2023.1126262
From study abroad to study at home: Spontaneous neuronal activity predicts depressive symptoms in overseas students during the COVID-19 pandemic
Front Neurosci. 2023 Feb 3;17:1078119. doi: 10.3389/fnins.2023.1078119. eCollection 2023.
The objective of this study was to evaluate symptoms of depression and anxiety as well as changes in spontaneous neuronal activity in college students studying abroad during the coronavirus 2019 (COVID-19) pandemic. We examined functional brain changes using resting-state functional magnetic resonance imaging (fMRI), the amplitude of low-frequency fluctuations (ALFF), and regional homogeneity (ReHo) in overseas students with enforced isolation due to the COVID-19 pandemic. Additionally, emotional assessments were administered to determine the severity of depression and anxiety. The questionnaire results showed that anxiety and depressive symptoms differed between overseas students (i.e., those attending an overseas college virtually) and local students (i.e., those attending a local college in person). The fMRI data revealed higher ALFF values in the bilateral superior medial frontal gyrus, bilateral pre-central gyrus, left insula, and left superior temporal gyrus as well as lower ALFF values in the bilateral paracentral lobule (supplementary motor area) in overseas students. Moreover, ReHo analysis also revealed significant differences between overseas students and local students. Compared with local students, overseas students showed significantly increased ReHo in the right inferior frontal and superior temporal gyri and decreased ReHo in the bilateral paracentral lobule, bilateral superior medial frontal gyrus (supplementary motor area), and bilateral pre-central gyrus. In addition, in overseas students, altered ReHo in the cluster including the left superior and medial frontal gyri, pre-central gyrus, and paracentral lobule was significantly positively correlated with Self-Rating Depression Scale scores. Thus, spontaneous brain activity in overseas students changed during the COVID-19 pandemic. This change in brain function might be related to depression and anxiety symptoms. These results suggest that mental health services are needed to decrease the risk of anxiety and depression among college students studying abroad during the COVID-19 pandemic.
PMID:36816115 | PMC:PMC9936146 | DOI:10.3389/fnins.2023.1078119
Remodeling of the brain correlates with gait instability in cervical spondylotic myelopathy
Front Neurosci. 2023 Feb 2;17:1087945. doi: 10.3389/fnins.2023.1087945. eCollection 2023.
INTRODUCTION: Cervical spondylotic myelopathy (CSM) is a common form of non-traumatic spinal cord injury (SCI) and usually leads to remodeling of the brain and spinal cord. In CSM with gait instability, the remodeling of the brain and cervical spinal cord is unclear. We attempted to explore the remodeling of these patients' brains and spinal cords, as well as the relationship between the remodeling of the brain and spinal cord and gait instability.
METHODS: According to the CSM patients' gait, we divided patients into two groups: normal gait patients (nPT) and abnormal gait patients (aPT). Voxel-wise z-score transformation amplitude of low-frequency fluctuations (zALFF) and resting-state functional connectivity (rs-FC) were performed for estimating brain changes. Cross-sectional area (CSA) and fractional anisotropy (FA) of the spinal cord were computed by Spinal cord toolbox. Correlations of these measures and the modified Japanese Orthopedic Association (mJOA) score were analyzed.
RESULTS: We found that the zALFF of caudate nucleus in aPT was higher than that in healthy controls (HC) and lower than that in nPT. The zALFF of the right postcentral gyrus and paracentral lobule in HC was higher than those of aPT and nPT. Compared with the nPT, the aPT showed increased functional connectivity between the caudate nucleus and left angular gyrus, bilateral precuneus and bilateral posterior cingulate cortex (PCC), which constitute a vital section of the default mode network (DMN). No significantly different FA values or CSA of spinal tracts at the C2 level were observed between the HC, nPT and aPT groups. In CSM, the right paracentral lobule's zALFF was negatively correlated with the FA value of fasciculus gracilis (FCG), and the right caudate zALFF was positively correlated with the FA value of the fasciculus cuneatus (FCC). The results showed that the functional connectivity between the right caudate nucleus and DMN was negatively correlated with the CSA of the lateral corticospinal tract (CST).
DISCUSSION: The activation of the caudate nucleus and the strengthening functional connectivity between the caudate nucleus and DMN were associated with gait instability in CSM patients. Correlations between spinal cord and brain function might be related to the clinical symptoms in CSM.
PMID:36816111 | PMC:PMC9932596 | DOI:10.3389/fnins.2023.1087945
Frequency-Dependent Alterations in the Amplitude of Low-Frequency Fluctuations in Patients with Acute Pericoronitis: A Resting-State fMRI Study
J Pain Res. 2023 Feb 15;16:501-511. doi: 10.2147/JPR.S397523. eCollection 2023.
BACKGROUND: Acute pericoronitis (AP) is a common cause of odontogenic toothache. Pain significantly affects the structure and function of the brain, but alterations in spontaneous brain activity in patients with AP are unclear.
PURPOSE: To apply the amplitude of low-frequency fluctuations (ALFF) method in resting-state functional magnetic resonance imaging to investigate altered spontaneous brain activity characteristics in patients with AP in different frequency bands (typical, slow-4, and slow-5 bands) and assess their correlation with clinical scores.
PATIENTS AND METHODS: Thirty-four right-handed patients with AP and 31 healthy controls (HC), matched for age, sex, education, and right-handedness, were enrolled. All subjects underwent resting-state functional magnetic resonance imaging. DPABI software was used for data preprocessing and extracting the ALFF values in different frequency bands. Subsequently, differences in ALFF values in the three bands were compared between the two groups. Correlation between ALFF values in the differential brain regions and clinical scores was assessed.
RESULTS: In the typical band, ALFF values were higher in the left insula, left superior occipital gyrus, left inferior parietal lobule, left posterior cerebellar lobule, and right postcentral gyrus in the AP than in the HC group. In the slow-4 band, ALFF values in the left superior occipital gyrus, right superior occipital gyrus, and right middle occipital gyrus were higher, and those in the right cingulate gyrus and right superior temporal gyrus were lower in the AP than in the HC group. In the slow-5 band, the ALFF values in the left insula and left superior occipital gyrus were higher in the AP than in the HC group. The ALFF values of the typical bands in the left insula, left inferior parietal lobule, and right postcentral gyrus correlated negatively, those of the slow-4 band in the right middle occipital gyrus correlated positively, and those of the slow-5 band in the left insula correlated negatively with the visual analogue scale score in the AP group.
CONCLUSION: Our results suggested that the intrinsic brain activity of AP patients was abnormal and frequency-dependent. This provides new insights to explore the neurophysiological mechanisms of AP.
PMID:36815124 | PMC:PMC9939792 | DOI:10.2147/JPR.S397523
Topological network properties of resting-state functional connectivity patterns are associated with metal mixture exposure in adolescents
Front Neurosci. 2023 Feb 6;17:1098441. doi: 10.3389/fnins.2023.1098441. eCollection 2023.
INTRODUCTION: Adolescent exposure to neurotoxic metals adversely impacts cognitive, motor, and behavioral development. Few studies have addressed the underlying brain mechanisms of these metal-associated developmental outcomes. Furthermore, metal exposure occurs as a mixture, yet previous studies most often consider impacts of each metal individually. In this cross-sectional study, we investigated the relationship between exposure to neurotoxic metals and topological brain metrics in adolescents.
METHODS: In 193 participants (53% females, ages: 15-25 years) enrolled in the Public Health Impact of Metals Exposure (PHIME) study, we measured concentrations of four metals (manganese, lead, copper, and chromium) in multiple biological media (blood, urine, hair, and saliva) and acquired resting-state functional magnetic resonance imaging scans. Using graph theory metrics, we computed global and local efficiency (global:GE; local:LE) in 111 brain areas (Harvard Oxford Atlas). We used weighted quantile sum (WQS) regression models to examine association between metal mixtures and each graph metric (GE or LE), adjusted for sex and age.
RESULTS: We observed significant negative associations between the metal mixture and GE and LE [βGE = -0.076, 95% CI (-0.122, -0.031); βLE= -0.051, 95% CI (-0.095, -0.006)]. Lead and chromium measured in blood contributed most to this association for GE, while chromium measured in hair contributed the most for LE.
DISCUSSION: Our results suggest that exposure to this metal mixture during adolescence reduces the efficiency of integrating information in brain networks at both local and global levels, informing potential neural mechanisms underlying the developmental toxicity of metals. Results further suggest these associations are due to combined joint effects to different metals, rather than to a single metal.
PMID:36814793 | PMC:PMC9939635 | DOI:10.3389/fnins.2023.1098441