Most recent paper

Mov Disord. 2023 Feb 17. doi: 10.1002/mds.29320. Online ahead of print.

ABSTRACT

BACKGROUND: Degeneration of the substantia nigra (SN) may contribute to levodopa-induced dyskinesia (LID) in Parkinson's disease (PD), but the exact characteristics of SN in LID remain unclear.

OBJECTIVE: To further understand the pathogenesis of patients with PD with LID (PD-LID), we explored the structural and functional characteristics of SN in PD-LID using multimodal magnetic resonance imaging (MRI).

METHODS: Twenty-nine patients with PD-LID, 37 patients with PD without LID (PD-nLID), and 28 healthy control subjects underwent T1-weighted MRI, quantitative susceptibility mapping, neuromelanin-sensitive MRI, multishell diffusion MRI, and resting-state functional MRI. Different measures characterizing the SN were obtained using a region of interest-based approach.

RESULTS: Compared with patients with PD-nLID and healthy control subjects, the quantitative susceptibility mapping values of SN pars compacta (SNpc) were significantly higher (P = 0.049 and P = 0.00002), and the neuromelanin contrast-to-noise ratio values in SNpc were significantly lower (P = 0.012 and P = 0.000002) in PD-LID. The intracellular volume fraction of the posterior SN in PD-LID was significantly higher compared with PD-nLID (P = 0.037). Resting-state fMRI indicated that PD-LID in the medication off state showed higher functional connectivity between the SNpc and putamen compared with PD-nLID (P = 0.031), and the functional connectivity changes in PD-LID were positively correlated with Unified Dyskinesia Rating Scale total scores (R = 0.427, P = 0.042).

CONCLUSIONS: Our multimodal imaging findings highlight greater neurodegeneration in SN and the altered nigrostriatal connectivity in PD-LID. These characteristics provide a new perspective into the role of SN in the pathophysiological mechanisms underlying PD-LID. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

PMID:36799459 | DOI:10.1002/mds.29320

Res Sq. 2023 Feb 9:rs.3.rs-2547880. doi: 10.21203/rs.3.rs-2547880/v1. Preprint.

ABSTRACT

Sleep and related disorders could lead to changes in various brain networks, but little is known about the role of amyloid β (Aβ) burden-a key Alzheimer's disease (AD) biomarker-in the relationship between sleep disturbance and altered resting state functional connectivity (rsFC) in older adults. This cross-sectional study examined the association between sleep disturbance, Aβ burden, and rsFC using a large-scale dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Sample included 489 individuals (53.6% cognitively normal, 32.5% mild cognitive impairment, and 13.9% AD) who had completed sleep measures (Neuropsychiatric Inventory), PET Aβ data, and resting-state fMRI scans at baseline. Within and between rsFC of the Salience (SN), the Default Mode (DMN) and the Frontal Parietal network (FPN) were compared between participants with sleep disturbance versus without sleep disturbance. The interaction between Aβ positivity and sleep disturbance was evaluated using linear regressions, controlling for age, diagnosis status, gender, sedatives and hypnotics use, and hypertension. Although no significant main effect of sleep disturbance was found on rsFC, a significant interaction term emerged between sleep disturbance and Aβ burden on rsFC of SN (β=0.11, P=0.006). Specifically, sleep disturbance was associated with SN hyperconnectivity, only with the presence of Aβ burden. Sleep disturbance may lead to altered connectivity in the SN when Aβ is accumulated in the brain. Individuals with AD pathology may be at increased risk for sleep-related aberrant rsFC; therefore, identifying and treating sleep problems in these individuals may help prevent further disease progression.

PMID:36798352 | PMC:PMC9934741 | DOI:10.21203/rs.3.rs-2547880/v1

medRxiv. 2023 Feb 10:2023.02.09.23285713. doi: 10.1101/2023.02.09.23285713. Preprint.

ABSTRACT

BACKGROUND: Neuropathic pain after spinal cord injury (SCI) is notoriously hard to treat. Mechanisms of neuropathic pain are unclear, which makes finding effective treatments challenging. Prior studies have shown that adults with SCI have body awareness deficits. Recent imaging studies, including ours, point to the parietal operculum and insula as key areas for both pain perception and body awareness. Cognitive multisensory rehabilitation (CMR) is a physical therapy approach that helps improve body awareness for pain reduction and sensorimotor recovery. Based on our prior brain imaging work in CMR in stroke, we hypothesized that improving body awareness through restoring parietal operculum network connectivity leads to neuropathic pain relief and improved sensorimotor and daily life function in adults with SCI. Thus, the objectives of this study were to (1) determine baseline differences in resting-state and task-based functional magnetic resonance imaging (fMRI) brain function in adults with SCI compared to healthy controls and (2) identify changes in brain function and behavioral pain and pain-associated outcomes in adults with SCI after CMR.

METHODS: Healthy adults underwent a one-time MRI scan and completed questionnaires. We recruited community-dwelling adults with SCI-related neuropathic pain, with complete or incomplete SCI >3 months, and highest neuropathic pain intensity level of >3 on the Numeric Pain Rating Scale (NPRS). Participants with SCI were randomized into two groups, according to a delayed treatment arm phase I randomized controlled trial (RCT): Group A immediately received CMR intervention, 3x/week, 45 min/session, followed by a 6-week and 1-year follow-up. Group B started with a 6-week observation period, then 6 weeks of CMR, and a 1-year follow-up. Highest, average, and lowest neuropathic pain intensity levels were assessed weekly with the NPRS as primary outcome. Other primary outcomes (fMRI resting-state and functional tasks; sensory and motor function with the INSCI AIS exam), as well as secondary outcomes (mood, function, spasms, and other SCI secondary conditions), were assessed at baseline, after the first and second 6-week period. The INSCI AIS exam and questionnaires were repeated at the 1-year follow-up.

FINDINGS: Thirty-six healthy adults and 28 adults with SCI were recruited between September 2020 and August 2021, and of those, 31 healthy adults and 26 adults with SCI were enrolled in the study. All 26 participants with SCI completed the intervention and pre-post assessments. There were no study-related adverse events. Participants were 52±15 years of age, and 1-56 years post-SCI. During the observation period, group B did not show any reductions in neuropathic pain and did not have any changes in sensation or motor function (INSCI ASIA exam). However, both groups experienced a significant reduction in neuropathic pain after the 6-week CMR intervention. Their highest level of neuropathic pain of 7.81±1.33 on the NPRS at baseline was reduced to 2.88±2.92 after 6 weeks of CMR. Their change scores were 4.92±2.92 (large effect size Cohen's d =1.68) for highest neuropathic pain, 4.12±2.23 ( d =1.85) for average neuropathic pain, and 2.31±2.07 ( d =1.00) for lowest neuropathic pain. Nine participants out of 26 were pain-free after the intervention (34.62%). The results of the INSCI AIS testing also showed significant improvements in sensation, muscle strength, and function after 6 weeks of CMR. Their INSCI AIS exam increased by 8.81±5.37 points ( d =1.64) for touch sensation, 7.50±4.89 points ( d =1.53) for pin prick sensation, and 3.87±2.81 ( d =1.38) for lower limb muscle strength. Functional improvements after the intervention included improvements in balance for 17 out of 18 participants with balance problems at baseline; improved transfers for all of them and a returned ability to stand upright with minimal assistance in 12 out of 20 participants who were unable to stand at baseline. Those improvements were maintained at the 1-year follow-up. With regard to brain imaging, we confirmed that the resting-state parietal operculum and insula networks had weaker connections in adults with SCI-related neuropathic pain (n=20) compared to healthy adults (n=28). After CMR, stronger resting-state parietal operculum network connectivity was found in adults with SCI. Also, at baseline, as expected, right toe sensory stimulation elicited less brain activation in adults with SCI (n=22) compared to healthy adults (n=26). However, after CMR, there was increased brain activation in relevant sensorimotor and parietal areas related to pain and mental body representations (i.e., body awareness and visuospatial body maps) during the toe stimulation fMRI task. These brain function improvements aligned with the AIS results of improved touch sensation, including in the feet.

INTERPRETATION: Adults with chronic SCI had significant neuropathic pain relief and functional improvements, attributed to the recovery of sensation and movement after CMR. The results indicate the preliminary efficacy of CMR for restoring function in adults with chronic SCI. CMR is easily implementable in current physical therapy practice. These encouraging impressive results pave the way for larger randomized clinical trials aimed at testing the efficacy of CMR to alleviate neuropathic pain in adults with SCI.

CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04706208.

FUNDING: AIRP2-IND-30: Academic Investment Research Program (AIRP) University of Minnesota School of Medicine. National Center for Advancing Translational Sciences of the National Institutes of Health Award Number UL1TR002494; the Biotechnology Research Center: P41EB015894, the National Institute of Neurological Disorders & Stroke Institutional Center Core Grants to Support Neuroscience Research: P30 NS076408; and theHigh-Performancee Connectome Upgrade for Human 3T MR Scanner: 1S10OD017974.

PMID:36798345 | PMC:PMC9934787 | DOI:10.1101/2023.02.09.23285713

medRxiv. 2023 Feb 8:2023.02.05.23285034. doi: 10.1101/2023.02.05.23285034. Preprint.

ABSTRACT

Mesial temporal lobe epilepsy (mTLE) is associated with variable dysfunction beyond the temporal lobe. We used functional anomaly mapping (FAM), a multivariate machine learning approach to resting state fMRI analysis to measure subcortical and cortical functional aberrations in patients with mTLE. We also examined the value of individual FAM in lateralizing the hemisphere of seizure onset in mTLE patients. Methods: Patients and controls were selected from an existing imaging and clinical database. After standard preprocessing of resting state fMRI, time-series were extracted from 400 cortical and 32 subcortical regions of interest (ROIs) defined by atlases derived from functional brain organization. Group-level aberrations were measured by contrasting right (RTLE) and left (LTLE) patient groups to controls in a support vector regression models, and tested for statistical reliability using permutation analysis. Individualized functional anomaly maps (FAMs) were generated by contrasting individual patients to the control group. Half of patients were used for training a classification model, and the other half for estimating the accuracy to lateralize mTLE based on individual FAMs. Results: Thirty-two right and 14 left mTLE patients (33 with evidence of hippocampal sclerosis on MRI) and 94 controls were included. At group levels, cortical regions affiliated with limbic and somatomotor networks were prominent in distinguishing RTLE and LTLE from controls. At individual levels, most TLE patients had high anomaly in bilateral mesial temporal and medial parietooccipital default mode regions. A linear support vector machine trained on 50% of patients could accurately lateralize mTLE in remaining patients (median AUC =1.0 [range 0.97-1.0], median accuracy = 96.87% [85.71-100Significance: Functional anomaly mapping confirms widespread aberrations in function, and accurately lateralizes mTLE from resting state fMRI. Future studies will evaluate FAM as a non-invasive localization method in larger datasets, and explore possible correlations with clinical characteristics and disease course.

PMID:36798218 | PMC:PMC9934715 | DOI:10.1101/2023.02.05.23285034

Res Sq. 2023 Feb 9:rs.3.rs-2362961. doi: 10.21203/rs.3.rs-2362961/v1. Preprint.

ABSTRACT

The agonist-antagonist myoneural interface (AMI) is a novel amputation surgery that preserves sensorimotor signaling mechanisms of the central-peripheral nervous systems. Our first neuroimaging study investigating AMI subjects (Srinivasan et al., Sci. Transl. Med. 2020) focused on task-based neural signatures, and showed evidence of proprioceptive feedback to the central nervous system. The study of resting state neural activity helps non-invasively characterize the neural patterns that prime task response. In this first study on resting state fMRI in AMI subjects, we compared resting state functional connectivity in patients with transtibial AMI (n=12) and traditional (n=7) amputations, as well as biologically intact control subjects (n=10). We hypothesized that the AMI surgery will induce functional network reorganization that significantly differs from the traditional amputation surgery and also more closely resembles the neural configuration of controls. We found AMI subjects to have lower connectivity with salience and motor seed regions compared to traditional amputees. Additionally, with connections affected in traditional amputees, AMI subjects exhibited a connectivity pattern more closely resembling controls. Lastly, sensorimotor connectivity in amputee cohorts was significantly associated with phantom sensation (R 2 =0.7, p =0.0008). These findings provide researchers and clinicians with a critical mechanistic understanding of the effects of the AMI surgery on the brain at rest, spearheading future research towards improved prosthetic control and embodiment.

PMID:36798194 | PMC:PMC9934762 | DOI:10.21203/rs.3.rs-2362961/v1

Transl Psychiatry. 2023 Feb 16;13(1):59. doi: 10.1038/s41398-023-02344-2.

ABSTRACT

Both, pharmacological and genome-wide association studies suggest N-methyl-D-aspartate receptor (NMDAR) dysfunction and excitatory/inhibitory (E/I)-imbalance as a major pathophysiological mechanism of schizophrenia. The identification of shared fMRI brain signatures of genetically and pharmacologically induced NMDAR dysfunction may help to define biomarkers for patient stratification. NMDAR-related genetic and pharmacological effects on functional connectivity were investigated by integrating three different datasets: (A) resting state fMRI data from 146 patients with schizophrenia genotyped for the disease-associated genetic variant rs7191183 of GRIN2A (encoding the NMDAR 2 A subunit) as well as 142 healthy controls. (B) Pharmacological effects of the NMDAR antagonist ketamine and the GABA-A receptor agonist midazolam were obtained from a double-blind, crossover pharmaco-fMRI study in 28 healthy participants. (C) Regional gene expression profiles were estimated using a postmortem whole-brain microarray dataset from six healthy donors. A strong resemblance was observed between the effect of the genetic variant in schizophrenia and the ketamine versus midazolam contrast of connectivity suggestive for an associated E/I-imbalance. This similarity became more pronounced for regions with high density of NMDARs, glutamatergic neurons, and parvalbumin-positive interneurons. From a functional perspective, increased connectivity emerged between striato-pallido-thalamic regions and cortical regions of the auditory-sensory-motor network, while decreased connectivity was observed between auditory (superior temporal gyrus) and visual processing regions (lateral occipital cortex, fusiform gyrus, cuneus). Importantly, these imaging phenotypes were associated with the genetic variant, the differential effect of ketamine versus midazolam and schizophrenia (as compared to healthy controls). Moreover, the genetic variant was associated with language-related negative symptomatology which correlated with disturbed connectivity between the left posterior superior temporal gyrus and the superior lateral occipital cortex. Shared genetic and pharmacological functional connectivity profiles were suggestive of E/I-imbalance and associated with schizophrenia. The identified brain signatures may help to stratify patients with a common molecular disease pathway providing a basis for personalized psychiatry.

PMID:36797233 | DOI:10.1038/s41398-023-02344-2

Front Neurol. 2023 Jan 30;13:1105592. doi: 10.3389/fneur.2022.1105592. eCollection 2022.

ABSTRACT

OBJECTIVE: Misdiagnosis and missed diagnosis of migraine are common in clinical practice. Currently, the pathophysiological mechanism of migraine is not completely known, and its imaging pathological mechanism has rarely been reported. In this study, functional magnetic resonance imaging (fMRI) technology combined with a support vector machine (SVM) was employed to study the imaging pathological mechanism of migraine to improve the diagnostic accuracy of migraine.

METHODS: We randomly recruited 28 migraine patients from Taihe Hospital. In addition, 27 healthy controls were randomly recruited through advertisements. All patients had undergone the Migraine Disability Assessment (MIDAS), Headache Impact Test - 6 (HIT-6), and 15 min magnetic resonance scanning. We ran DPABI (RRID: SCR_010501) on MATLAB (RRID: SCR_001622) to preprocess the data and used REST (RRID: SCR_009641) to calculate the degree centrality (DC) value of the brain region and SVM (RRID: SCR_010243) to classify the data.

RESULTS: Compared with the healthy controls (HCs), the DC value of bilateral inferior temporal gyrus (ITG) in patients with migraine was significantly lower and that of left ITG showed a positive linear correlation with MIDAS scores. The SVM results showed that the DC value of left ITG has the potential to be a diagnostic biomarker for imaging, with the highest diagnostic accuracy, sensitivity, and specificity for patients with migraine of 81.82, 85.71, and 77.78%, respectively.

CONCLUSION: Our findings demonstrate abnormal DC values in the bilateral ITG among patients with migraine, and the present results provide insights into the neural mechanism of migraines. The abnormal DC values can be used as a potential neuroimaging biomarker for the diagnosis of migraine.

PMID:36793799 | PMC:PMC9922777 | DOI:10.3389/fneur.2022.1105592

Front Neurosci. 2023 Jan 30;16:1073800. doi: 10.3389/fnins.2022.1073800. eCollection 2022.

ABSTRACT

Quality control (QC) is a necessary, but often an under-appreciated, part of FMRI processing. Here we describe procedures for performing QC on acquired or publicly available FMRI datasets using the widely used AFNI software package. This work is part of the Research Topic, "Demonstrating Quality Control (QC) Procedures in fMRI." We used a sequential, hierarchical approach that contained the following major stages: (1) GTKYD (getting to know your data, esp. its basic acquisition properties), (2) APQUANT (examining quantifiable measures, with thresholds), (3) APQUAL (viewing qualitative images, graphs, and other information in systematic HTML reports) and (4) GUI (checking features interactively with a graphical user interface); and for task data, and (5) STIM (checking stimulus event timing statistics). We describe how these are complementary and reinforce each other to help researchers stay close to their data. We processed and evaluated the provided, publicly available resting state data collections (7 groups, 139 total subjects) and task-based data collection (1 group, 30 subjects). As specified within the Topic guidelines, each subject's dataset was placed into one of three categories: Include, exclude or uncertain. The main focus of this paper, however, is the detailed description of QC procedures: How to understand the contents of an FMRI dataset, to check its contents for appropriateness, to verify processing steps, and to examine potential quality issues. Scripts for the processing and analysis are freely available.

PMID:36793774 | PMC:PMC9922690 | DOI:10.3389/fnins.2022.1073800

Front Neurosci. 2023 Jan 30;17:1104886. doi: 10.3389/fnins.2023.1104886. eCollection 2023.

ABSTRACT

Functional MRI studies have achieved promising outcomes in revealing abnormal functional connectivity in Parkinson's disease (PD). The primary sensorimotor area (PSMA) received a large amount of attention because it closely correlates with motor deficits. While functional connectivity represents signaling between PSMA and other brain regions, the metabolic mechanism behind PSMA connectivity has rarely been well established. By introducing hybrid PET/MRI scanning, the current study enrolled 33 advanced PD patients during medication-off condition and 25 age-and-sex-matched healthy controls (HCs), aiming to not only identify the abnormal functional connectome pattern of the PSMA, but also to simultaneously investigate how PSMA functional connectome correlates with glucose metabolism. We calculated degree centrality (DC) and the ratio of standard uptake value (SUVr) using resting state fMRI and 18F-FDG-PET data. A two-sample t-test revealed significantly decreased PSMA DC (PFWE < 0.014) in PD patients. The PSMA DC also correlated negatively with H-Y stage (P = 0.031). We found a widespread reduction of H-Y stage associated (P-values < 0.041) functional connectivity between PSMA and the visual network, attention network, somatomotor network, limbic network, frontoparietal network as well as the default mode network. The PSMA DC correlated positively with FDG-uptake in the HCs (P = 0.039) but not in the PD patients (P > 0.44). In summary, we identified disease severity-dependent PSMA functional connectome which in addition uncoupled with glucose metabolism in PD patients. The current study highlighted the critical role of simultaneous PET/fMRI in revealing the functional-metabolic mechanism in the PSMA of PD patients.

PMID:36793540 | PMC:PMC9922997 | DOI:10.3389/fnins.2023.1104886

Front Neurosci. 2023 Jan 30;17:1098573. doi: 10.3389/fnins.2023.1098573. eCollection 2023.

ABSTRACT

BACKGROUND: Patients with primary dysmenorrhea (PDM) often present with abnormalities other than dysmenorrhea including co-occurrence with other chronic pain conditions and central sensitization. Changes in brain activity in PDM have been demonstrated; however, the results are not consistent. Herein, this study probed into altered intraregional and interregional brain activity in patients with PDM and expounded more findings.

METHODS: A total of 33 patients with PDM and 36 healthy controls (HCs) were recruited and underwent a resting-state functional magnetic resonance imaging scan. Regional homogeneity (ReHo) and mean amplitude of low-frequency fluctuation (mALFF) analysis were applied to compare the difference in intraregional brain activity between the two groups, and the regions with ReHo and mALFF group differences were used as seeds for functional connectivity (FC) analysis to explore the difference of interregional activity. Pearson's correlation analysis was conducted between rs-fMRI data and clinical symptoms in patients with PDM.

RESULTS: Compared with HCs, patients with PDM showed altered intraregional activity in a series of brain regions, including the hippocampus, the temporal pole superior temporal gyrus, the nucleus accumbens, the pregenual anterior cingulate cortex, the cerebellum_8, the middle temporal gyrus, the inferior temporal gyrus, the rolandic operculum, the postcentral gyrus and the middle frontal gyrus (MFG), and altered interregional FC mainly between regions of the mesocorticolimbic pathway and regions associated with sensation and movement. The anxiety symptoms are correlated with the intraregional activity of the right temporal pole superior temporal gyrus and FC between MFG and superior frontal gyrus.

CONCLUSION: Our study showed a more comprehensive method to explore changes in brain activity in PDM. We found that the mesocorticolimbic pathway might play a key role in the chronic transformation of pain in PDM. We, therefore, speculate that the modulation of the mesocorticolimbic pathway may be a potential novel therapeutic mechanism for PDM.

PMID:36793538 | PMC:PMC9922713 | DOI:10.3389/fnins.2023.1098573

BMJ Open. 2023 Feb 15;13(2):e066458. doi: 10.1136/bmjopen-2022-066458.

ABSTRACT

INTRODUCTION: Radiation-induced cognitive decline (RICD) occurs in 50%-90% of adult patients 6 months post-treatment. In patients with low-grade and benign tumours with long expected survival, this is of paramount importance. Despite advances in radiation therapy (RT) treatment delivery, better understanding of structures important for RICD is necessary to improve cognitive outcomes. We hypothesise that RT may affect network topology and microstructural integrity on MRI prior to any gross anatomical or apparent cognitive changes. In this longitudinal cohort study, we aim to determine the effects of RT on brain structural and functional integrity and cognition.

METHODS AND ANALYSIS: This study will enroll patients with benign and low-grade brain tumours receiving partial brain radiotherapy. Patients will receive either hypofractionated (>2 Gy/fraction) or conventionally fractionated (1.8-2 Gy/fraction) RT. All participants will be followed for 12 months, with MRIs conducted pre-RT and 6-month and 12 month post-RT, along with a battery of neurocognitive tests and questionnaires. The study was initiated in late 2018 and will continue enrolling through 2024 with final follow-ups completing in 2025. The neurocognitive battery assesses visual and verbal memory, attention, executive function, processing speed and emotional cognition. MRI protocols incorporate diffusion tensor imaging and resting state fMRI to assess structural connectivity and functional connectivity, respectively. We will estimate the association between radiation dose, imaging metrics and cognitive outcomes.

ETHICS AND DISSEMINATION: This study has been approved by the Research Subjects Review Board at the University of Rochester (STUDY00001512: Cognitive changes in patients receiving partial brain radiation). All results will be published in peer-reviewed journals and at scientific conferences.

TRIAL REGISTRATION NUMBER: ClinicalTrials.gov NCT04390906.

PMID:36792323 | DOI:10.1136/bmjopen-2022-066458

Epilepsy Behav. 2023 Feb 13;140:109100. doi: 10.1016/j.yebeh.2023.109100. Online ahead of print.

ABSTRACT

OBJECTIVE: We aimed to determine whether alterations in spontaneous regional brain activity in those with generalized tonic-clonic seizures (GTCS) and focal to bilateral tonic-clonic seizures (FBTCS) and explore whether the alterations could be used as biomarkers to classify disease subtypes through support vector machine analysis (SVM).

METHODS: The fractional amplitude of low-frequency fluctuations (fALFF) and regional homogeneity (ReHo) from resting-state functional magnetic resonance imaging (rs-fMRI) data were extracted from 57 patients with GTCS, 35 patients with FBTCS, and 50 age-matched and sex-matched normal controls (NCs) using the DPARSF 5.0 toolbox. Between-group comparisons were adjusted for covariates (age, sex, and equipment). Correlation analyses between imaging biomarkers and the frequency or duration of seizure activity were calculated using partial correlations. The differential imaging indicators, age, and sex were considered as the discriminative features in the SVM to evaluate classification performance.

RESULTS: The patients with GTCS showed lower fALFF values (voxel p < 0.001, cluster p < 0.05, Gaussian random field corrected, GRF corrected) in the right postcentral gyrus and precentral gyrus and lower ReHo values (GRF corrected) in the middle temporal gyrus than the NCs. The patients with FBTCS showed higher fALFF (GRF corrected) values in the right postcentral and precentral gyrus and higher ReHo (GRF corrected) values in the right postcentral gyrus. Both fALFF (GRF corrected) and ReHo (GRF corrected) values were lower in the right postcentral gyrus and precentral gyrus in the GTCS group than in the FBTCS group. In patients with FBTCS, fALFF values in the right postcentral and precentral gyrus were positively correlated with duration (r = 0.655, p = 0.008, Bonferroni corrected) in the low-duration group, and ReHo values in the right postcentral gyrus were positively correlated with frequency (r = 0.486, p = 0.022, uncorrected) in the low-frequency group. SVM results showed receiver operating characteristic curves of 0.89, 0.87, and 0.76 for the classification between GTCS and NC, between FBTCS and NC, and GTCS and FBTCS, respectively.

SIGNIFICANCE: This study detected alterations in fALFF and ReHo in the postcentral gyrus and precentral gyrus in patients with GTCS and FBTCS, which might contribute to understanding the pathogenesis, disease classification, and clinical targeted therapy.

PMID:36791632 | DOI:10.1016/j.yebeh.2023.109100

bioRxiv. 2023 Jan 16:2023.01.14.523992. doi: 10.1101/2023.01.14.523992. Preprint.

ABSTRACT

Whole-brain functional connectivity ( FC ) measured with functional MRI (fMRI) evolve over time in meaningful ways at temporal scales going from years (e.g., development) to seconds (e.g., within-scan time-varying FC ( tvFC )). Yet, our ability to explore tvFC is severely constrained by its large dimensionality (several thousands). To overcome this difficulty, researchers seek to generate low dimensional representations (e.g., 2D and 3D scatter plots) expected to retain its most informative aspects (e.g., relationships to behavior, disease progression). Limited prior empirical work suggests that manifold learning techniques ( MLTs )-namely those seeking to infer a low dimensional non-linear surface (i.e., the manifold) where most of the data lies-are good candidates for accomplishing this task. Here we explore this possibility in detail. First, we discuss why one should expect tv FC data to lie on a low dimensional manifold. Second, we estimate what is the intrinsic dimension (i.e., minimum number of latent dimensions; ID ) of tvFC data manifolds. Third, we describe the inner workings of three state-of-the-art MLTs : Laplacian Eigenmaps ( LE ), T-distributed Stochastic Neighbor Embedding ( T-SNE ), and Uniform Manifold Approximation and Projection ( UMAP ). For each method, we empirically evaluate its ability to generate neuro-biologically meaningful representations of tvFC data, as well as their robustness against hyper-parameter selection. Our results show that tvFC data has an ID that ranges between 4 and 26, and that ID varies significantly between rest and task states. We also show how all three methods can effectively capture subject identity and task being performed: UMAP and T-SNE can capture these two levels of detail concurrently, but L E could only capture one at a time. We observed substantial variability in embedding quality across MLTs , and within- MLT as a function of hyper-parameter selection. To help alleviate this issue, we provide heuristics that can inform future studies. Finally, we also demonstrate the importance of feature normalization when combining data across subjects and the role that temporal autocorrelation plays in the application of MLTs to tvFC data. Overall, we conclude that while MLTs can be useful to generate summary views of labeled tvFC data, their application to unlabeled data such as resting-state remains challenging.

PMID:36789436 | PMC:PMC9928030 | DOI:10.1101/2023.01.14.523992

J Neurosci. 2023 Feb 13:JN-RM-1601-22. doi: 10.1523/JNEUROSCI.1601-22.2023. Online ahead of print.

ABSTRACT

Recent evidence suggests that, in the absence of any task, spontaneous brain activity patterns and connectivity in the visual and motor cortex code for natural stimuli and actions, respectively. These "resting-state" activity patterns may underlie the maintenance and consolidation (replay) of information states coding for ecological stimuli and behaviors. In this study, we examine whether replay patterns occur in resting state activity in association cortex grouped into high-order cognitive networks not directly processing sensory inputs or motor outputs. Fifteen participants (7 females) performed four hand movements during a functional MRI (fMRI) study. Three movements were ecological. The fourth movement as control was less ecological. Before and after the task scans, we acquired resting-state fMRI scans. The analysis examined whether multi-vertex task activation patterns for the four movements computed at the cortical surface in different brain networks resembled spontaneous activity patterns measured at rest. For each movement, we computed a vector of r values indicating the strength of the similarity between the mean task activation pattern and frame-by-frame resting state patterns. We computed a cumulative distribution function of r-squared values and used the 90th percentile cut-off value for comparison. In the dorsal attention network, resting-state patterns were more likely to match task patterns for the ecological movements than the control movement. In contrast, rest-task pattern correlation was more likely for less ecological movement in the ventral attention network. These findings show that spontaneous activity patterns in human attention networks code for hand movements.Significance Statement:Functional magnetic resonance imaging (fMRI) indirectly measures neural activity non-invasively. Resting state (spontaneous) fMRI signals measured in the absence of any task resemble signals evoked by task performance both in topography and inter-regional (functional) connectivity. However, the function of spontaneous brain activity is unknown. We recently showed that spatial activity patterns evoked by visual and motor tasks in visual and motor cortex, respectively, occur at rest in the absence of any stimulus or response. Here we show that activity patterns related to hand movements replay at rest in frontoparietal regions of the human attention system.These findings show that spontaneous activity in the human cortex may mediate the maintenance and consolidation of information states coding for ecological stimuli and behaviors.

PMID:36788030 | DOI:10.1523/JNEUROSCI.1601-22.2023

J Cogn Psychother. 2023 Feb 1;37(1):82-101. doi: 10.1891/JCPSY-D-21-00006. Epub 2022 Jun 3.

ABSTRACT

Cognitive behavioral therapy for insomnia (CBT-I) is the gold-standard non-pharmacological treatment for insomnia, a complex disorder that comprises psychological, behavioral, and physiological components. This systematic literature review aimed to evaluate a growing body of exploratory studies that have examined CBT-I treatment effects using neuroimaging assessment. Nine studies met current review selection criteria, of which six studies compared insomnia groups with good sleepers, waitlist, and/or control groups. CBT-I administration varied in treatment length and duration across the studies, as did neuroimaging assessment, which included task-based and resting-state functional magnetic resonance imaging (fMRI), and structural magnetic resonance imaging (MRI). Functional connectivity abnormalities were observed in participants, including reduced engagement in task-related brain regions and apparent difficulties in regulating default mode brain areas that appeared to reverse following CBT-I treatment. Taken together, the neuroimaging results complement behavioral measures of treatment efficacy, indicating support for the effectiveness of CBT-I treatment in the recovery of brain function and structure.

PMID:36787999 | DOI:10.1891/JCPSY-D-21-00006

Biofactors. 2023 Feb 13. doi: 10.1002/biof.1933. Online ahead of print.

ABSTRACT

Despite numerous research showing the association between brain network abnormalities and autism spectrum disorder (ASD), contrasting findings have been reported from broad functional underconnectivity to broad overconnectivity. Thus, the significance of rich-hub organizations in the brain functional connectome of individuals with ASD remains largely unknown. High-quality data subset of ASD (n = 45) and healthy controls (HC; n = 47) children (7-15 years old) were retrieved from the ABIDE data set, and rich-club organization and network-based statistic (NBS) were assessed from resting-state functional magnetic resonance imaging (rs-fMRI). The rich-club organization functional network (normalized rich-club coefficients >1) was observed in all subjects under a range of thresholds. Compared with HC, ASD patients had higher degree of feeder connections and lower degree of local connections (degree of feeder connections: ASD = 259.20 ± 32.97, HC = 244.98 ± 30.09, p = 0.041; degree of local connections: ASD = 664.02 ± 39.19, HC = 679.89 ± 34.05, p = 0.033) but had similar in rich-club connections. Further, nonparametric NBS analysis showed the presence of abnormal connectivity in the functional network of ASD individuals. Our findings indicated that local connection might be more vulnerable, and feeder connection may compensate for its disruption in ASD, enhancing our understanding on the mechanism of functional connectome dysfunction in ASD.

PMID:36785880 | DOI:10.1002/biof.1933

Mol Psychiatry. 2023 Feb 13. doi: 10.1038/s41380-023-01974-8. Online ahead of print.

ABSTRACT

BACKGROUND: Over the past few decades, neuroimaging research in Bipolar Disorder (BD) has identified neural differences underlying cognitive and emotional processing. However, substantial clinical and methodological heterogeneity present across neuroimaging experiments potentially hinders the identification of consistent neural biomarkers of BD. This meta-analysis aims to comprehensively reassess brain activation and connectivity in BD in order to identify replicable differences that converge across and within resting-state, cognitive, and emotional neuroimaging experiments.

METHODS: Neuroimaging experiments (using fMRI, PET, or arterial spin labeling) reporting whole-brain results in adults with BD and controls published from December 1999-June 18, 2019 were identified via PubMed search. Coordinates showing significant activation and/or connectivity differences between BD participants and controls during resting-state, emotional, or cognitive tasks were extracted. Four parallel, independent meta-analyses were calculated using the revised activation likelihood estimation algorithm: all experiment types, all resting-state experiments, all cognitive experiments, and all emotional experiments. To confirm reliability of identified clusters, two different meta-analytic significance tests were employed.

RESULTS: 205 published studies yielding 506 individual neuroimaging experiments (150 resting-state, 134 cognitive, 222 emotional) comprising 5745 BD and 8023 control participants were included. Five regions survived both significance tests. Individuals with BD showed functional differences in the right posterior cingulate cortex during resting-state experiments, the left amygdala during emotional experiments, including those using a mixed (positive/negative) valence manipulation, and the left superior and right inferior parietal lobules during cognitive experiments, while hyperactivating the left medial orbitofrontal cortex during cognitive experiments. Across all experiments, there was convergence in the right caudate extending to the ventral striatum, surviving only one significance test.

CONCLUSIONS: Our findings indicate reproducible localization of prefrontal, parietal, and limbic differences distinguishing BD from control participants that are condition-dependent, despite heterogeneity, and point towards a framework for identifying reproducible differences in BD that may guide diagnosis and treatment.

PMID:36782061 | DOI:10.1038/s41380-023-01974-8

J Affect Disord. 2023 Feb 11:S0165-0327(23)00122-2. doi: 10.1016/j.jad.2023.01.104. Online ahead of print.

ABSTRACT

BACKGROUND: Functional connectome studies have revealed widespread connectivity alterations in major depressive disorder (MDD). However, the low frequency bandpass filtering (0.01-0.08 Hz or 0.01-0.1 Hz) in most studies have impeded our understanding on whether and how these alterations are affected by frequency of interest.

METHODS: Here, we performed frequency-resolved (0.01-0.06 Hz, 0.06-0.16 Hz and 0.16-0.24 Hz) connectome analyses using a large-sample resting-state functional MRI dataset of 1002 MDD patients and 924 healthy controls from seven independent centers.

RESULTS: We reported significant frequency-dependent connectome alterations in MDD in left inferior parietal, inferior temporal, precentral, and fusiform cortices and bilateral precuneus. These frequency-dependent connectome alterations are mainly derived by abnormalities of medium- and long-distance connections and are brain network-dependent. Moreover, the connectome alteration of left precuneus in high frequency band (0.16-0.24 Hz) is significantly associated with illness duration.

LIMITATIONS: Multisite harmonization model only removed linear site effects. Neurobiological underpinning of alterations in higher frequency (0.16-0.24 Hz) should be further examined by combining fMRI data with respiration, heartbeat and blood flow recordings in future studies.

CONCLUSIONS: These results highlight the frequency-dependency of connectome alterations in MDD and the benefit of examining connectome alteration in MDD under a wider frequency band.

PMID:36781144 | DOI:10.1016/j.jad.2023.01.104

Behav Brain Res. 2023 Feb 11:114344. doi: 10.1016/j.bbr.2023.114344. Online ahead of print.

ABSTRACT

Several studies with resting-state magnetic resonance imaging (rs-fMRI) have examined functional impairments and plasticity within language network in patients with post-stroke aphasia (PSA). However, there is still ubiquitous inconsistency across these studies, partly due to restricted to very small sample size and the absence of validation with follow-up data. In the current study, we aimed at providing relatively strong evidence to support functional impairments and its reorganization in PSA. Here, the amplitude of low frequency fluctuations (ALFF) and functional connectivity were used to assess functional alterations of PSA with moderate sample size at baseline (thirty-five PSA patients and thirty-five healthy controls). Functional abnormalities at baseline were observed whether improved among sixteen follow-up patients. Compared with controls, PSA at baseline presented decreased ALFF in the left inferior frontal gyrus (IFG) and decreased functional connectivity of the left IFG with the bilateral supplementary motor area (SMA) and right superior temporal gyrus (STG). The decreased ALFF in IFG, decreased IFG-SMA and IFG-STG connectivity were enhanced among follow-up patients and was synchronized with language-performance improvement. Our results revealed reduced intrinsic neural activity and inter-connections within language network in PSA, which would be normalized synchronously as the improvement of language performance.

PMID:36781021 | DOI:10.1016/j.bbr.2023.114344

bioRxiv. 2023 Jan 31:2023.01.29.526110. doi: 10.1101/2023.01.29.526110. Preprint.

ABSTRACT

Resting state functional magnetic resonance imaging (rs-fMRI) dynamic functional network connectivity (dFNC) analysis has illuminated brain network interactions across many neuropsychiatric disorders. A common analysis approach involves using hard clustering methods to identify transitory states of brain activity, and in response to this, other methods have been developed to quantify the importance of specific dFNC interactions to identified states. Some of these methods involve perturbing individual features and examining the number of samples that switch states. However, only a minority of samples switch states. As such, these methods actually identify the importance of dFNC features to the clustering of a subset of samples rather than the overall clustering. In this study, we present a novel approach that more capably identifies the importance of each feature to the overall clustering. Our approach uses fuzzy clustering to output probabilities of each sample belonging to states and then measures their Kullback-Leibler divergence after perturbation. We show the viability of our approach in the context of schizophrenia (SZ) default mode network analysis, identifying significant differences in state dynamics between individuals with SZ and healthy controls. We further compare our approach with an existing approach, showing that it captures the effects of perturbation upon most samples. We also find that interactions between the posterior cingulate cortex (PCC) and the anterior cingulate cortex and the PCC and precuneus are important across methods. We expect that our novel explainable clustering approach will enable further progress in rs-fMRI analysis and to other clustering applications.

PMID:36778353 | PMC:PMC9915490 | DOI:10.1101/2023.01.29.526110