Most recent paper

Manifold learning for fMRI time-varying functional connectivity

Thu, 07/27/2023 - 18:00

Front Hum Neurosci. 2023 Jul 11;17:1134012. doi: 10.3389/fnhum.2023.1134012. eCollection 2023.

ABSTRACT

Whole-brain functional connectivity (FC) measured with functional MRI (fMRI) evolves 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 often seek to generate low dimensional representations (e.g., 2D and 3D scatter plots) hoping those will retain important aspects of the data (e.g., relationships to behavior and 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 tvFC data to lie on a low dimensional manifold. Second, we estimate what is the intrinsic dimension (ID; i.e., minimum number of latent dimensions) of tvFC data manifolds. Third, we describe the inner workings of three state-of-the-art MLTs: Laplacian Eigenmaps (LEs), 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 LE 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:37497043 | PMC:PMC10366614 | DOI:10.3389/fnhum.2023.1134012

The impact of HCN4 channels on CNS brain networks as a new target in pain development

Thu, 07/27/2023 - 18:00

Front Netw Physiol. 2023 Jul 10;3:1090502. doi: 10.3389/fnetp.2023.1090502. eCollection 2023.

ABSTRACT

While it is well established that the isoform 2 of the hyperpolarization-activated cyclic nucleotide-gated cation channel (HCN2) plays an important role in the development and maintenance of pain, the role of the closely related HCN4 isoform in the processing of nociceptive signals is not known. HCN4 channels are highly expressed in the thalamus, a region important for stimulus transmission and information processing. We used a brain-specific HCN4-knockout mouse line (HCN4-KO) to explore the role of HCN4 channels in acute nociceptive processing using several behavioral tests as well as a multimodal magnetic resonance imaging (MRI) approach. Functional MRI (fMRI) brain responses were measured during acute peripheral thermal stimulation complemented by resting state (RS) before and after stimulation. The data were analyzed by conventional and graph-theoretical approaches. Finally, high-resolution anatomical brain data were acquired. HCN4-KO animals showed a central thermal, but not a mechanical hypersensitivity in behavioral experiments. The open field analysis showed no significant differences in motor readouts between HCN4-KO and controls but uncovered increased anxiety in the HCN4-KO mice. Thermal stimulus-driven fMRI (s-fMRI) data revealed increased response volumes and response amplitudes for HCN4-KO, most pronounced at lower stimulation temperatures in the subcortical input, the amygdala as well as in limbic/hippocampal regions, and in the cerebellum. These findings could be cross-validated by graph-theoretical analyses. Assessment of short-term RS before and after thermal stimulation revealed that stimulation-related modulations of the functional connectivity only occurred in control animals. This was consistent with the finding that the hippocampus was found to be smaller in HCN4-KO. In summary, the deletion of HCN4 channels impacts on processing of acute nociception, which is remarkably manifested as a thermal hypersensitive phenotype. This was mediated by the key regions hypothalamus, somatosensory cortex, cerebellum and the amygdala. As consequence, HCN4-KO mice were more anxious, and their brain-wide RS functional connectivity could not be modulated by thermal nociceptive stimulation.

PMID:37496803 | PMC:PMC10368246 | DOI:10.3389/fnetp.2023.1090502

Expression of the excitatory opsin ChRERα can be traced longitudinally in rat and nonhuman primate brains with PET imaging

Wed, 07/26/2023 - 18:00

Sci Transl Med. 2023 Jul 26;15(706):eadd1014. doi: 10.1126/scitranslmed.add1014. Epub 2023 Jul 26.

ABSTRACT

Optogenetics is a widely used technology with potential for translational research. A critical component of such applications is the ability to track the location of the transduced opsin in vivo. To address this problem, we engineered an excitatory opsin, ChRERα (hChR2(134R)-V5-ERα-LBD), that could be visualized using positron emission tomography (PET) imaging in a noninvasive, longitudinal, and quantitative manner. ChRERα consists of the prototypical excitatory opsin channelrhodopsin-2 (ChR2) and the ligand-binding domain (LBD) of the human estrogen receptor α (ERα). ChRERα showed conserved ChR2 functionality and high affinity for [18F]16α-fluoroestradiol (FES), an FDA-approved PET radiopharmaceutical. Experiments in rats demonstrated that adeno-associated virus (AAV)-mediated expression of ChRERα enables neural circuit manipulation in vivo and that ChRERα expression could be monitored using FES-PET imaging. In vivo experiments in nonhuman primates (NHPs) confirmed that ChRERα expression could be monitored at the site of AAV injection in the primary motor cortex and in long-range neuronal terminals for up to 80 weeks. The anatomical connectivity map of the primary motor cortex identified by FES-PET imaging of ChRERα expression overlapped with a functional connectivity map identified using resting state fMRI in a separate cohort of NHPs. Overall, our results demonstrate that ChRERα expression can be mapped longitudinally in the mammalian brain using FES-PET imaging and can be used for neural circuit modulation in vivo.

PMID:37494470 | DOI:10.1126/scitranslmed.add1014

Early development of the functional brain network in newborns

Wed, 07/26/2023 - 18:00

Brain Struct Funct. 2023 Jul 26. doi: 10.1007/s00429-023-02681-4. Online ahead of print.

ABSTRACT

During the prenatal period and the first postnatal years, the human brain undergoes rapid growth, which establishes a preliminary infrastructure for the subsequent development of cognition and behavior. To understand the underlying processes of brain functioning and identify potential sources of developmental disorders, it is essential to uncover the developmental rules that govern this critical period. In this study, graph theory modeling and network science analysis were employed to investigate the impact of age, gender, weight, and typical and atypical development on brain development. Local and global topologies of functional connectomes obtained from rs-fMRI data were collected from 421 neonates aged between 31 and 45 postmenstrual weeks who were in natural sleep without any sedation. The results showed that global efficiency, local efficiency, clustering coefficient, and small-worldness increased with age, while modularity and characteristic path length decreased with age. The normalized rich-club coefficient displayed a U-shaped pattern during development. The study also examined the global and local impacts of gender, weight, and group differences between typical and atypical cases. The findings presented some new insights into the maturation of functional brain networks and their relationship with cognitive development and neurodevelopmental disorders.

PMID:37493690 | DOI:10.1007/s00429-023-02681-4

Trait representation of embodied cognition in dancers pivoting on the extended mirror neuron system: a resting-state fMRI study

Wed, 07/26/2023 - 18:00

Front Hum Neurosci. 2023 Jul 10;17:1173993. doi: 10.3389/fnhum.2023.1173993. eCollection 2023.

ABSTRACT

INTRODUCTION: Dance is an art form that integrates the body and mind through movement. Dancers develop exceptional physical and mental abilities that involve various neurocognitive processes linked to embodied cognition. We propose that dancers' primary trait representation is movement-actuated and relies on the extended mirror neuron system (eMNS).

METHODS: A total of 29 dancers and 28 non-dancer controls were recruited. A hierarchical approach of intra-regional and inter-regional functional connectivity (FC) analysis was adopted to probe trait-like neurodynamics within and between regions in the eMNS during rest. Correlation analyses were employed to examine the associations between dance training, creativity, and the FC within and between different brain regions.

RESULTS: Within the eMNS, dancers exhibited increased intra-regional FC in various brain regions compared to non-dancers. These regions include the left inferior frontal gyrus, left ventral premotor cortex, left anterior insula, left posterior cerebellum (crus II), and bilateral basal ganglia (putamen and globus pallidus). Dancers also exhibited greater intrinsic inter-regional FC between the cerebellum and the core/limbic mirror areas within the eMNS. In dancers, there was a negative correlation observed between practice intensity and the intrinsic FC within the eMNS involving the cerebellum and basal ganglia. Additionally, FCs from the basal ganglia to the dorsolateral prefrontal cortex were found to be negatively correlated with originality in dancers.

DISCUSSION: Our results highlight the proficient communication within the cortical-subcortical hierarchy of the eMNS in dancers, linked to the automaticity and cognitive-motor interactions acquired through training. Altered functional couplings in the eMNS can be regarded as a unique neural signature specific to virtuoso dancers, which might predispose them for skilled dancing performance, perception, and creation.

PMID:37492559 | PMC:PMC10364845 | DOI:10.3389/fnhum.2023.1173993

Disrupted network communication predicts mild cognitive impairment in end-stage renal disease: an individualized machine learning study based on resting-state fMRI

Wed, 07/26/2023 - 18:00

Cereb Cortex. 2023 Jul 25:bhad269. doi: 10.1093/cercor/bhad269. Online ahead of print.

ABSTRACT

End-Stage Renal Disease (ESRD) is known to be associated with a range of brain injuries, including cognitive decline. The purpose of this study is to investigate the functional connectivity (FC) of the resting-state networks (RSNs) through resting state functional magnetic resonance imaging (MRI), in order to gain insight into the neuropathological mechanism of ESRD. A total of 48 ESRD patients and 49 healthy controls underwent resting-state functional MRI and neuropsychological tests, for which Independent Components Analysis and graph-theory (GT) analysis were utilized. With the machine learning results, we examined the connections between RSNs abnormalities and neuropsychological test scores. Combining intra/inter network FC differences and GT results, ESRD was optimally distinguished in the testing dataset, with a balanced accuracy of 0.917 and area under curve (AUC) of 0.942. Shapley additive explanations results revealed that the increased functional network connectivity between DMN and left frontoparietal network (LFPN) was the most critical predictor for ESRD associated mild cognitive impairment diagnosis. Moreover, hypoSN (salience network) was positively correlated with Attention scores, while hyperLFPN was negatively correlated with Execution scores, indicating correlations between functional disruption and cognitive impairment measurements in ESRD patients. This study demonstrated that both the loss of FC within the SN and compensatory FC within the lateral frontoparietal network coexist in ESRD. This provides a network basis for understanding the individual brain circuits and offers additional noninvasive evidence to comprehend the brain networks in ESRD.

PMID:37492012 | DOI:10.1093/cercor/bhad269

Brain circuits for maternal sensitivity and pain involving anterior cingulate cortex among mothers receiving buprenorphine treatment for opioid use disorder

Wed, 07/26/2023 - 18:00

J Neuroendocrinol. 2023 Jun 21:e13316. doi: 10.1111/jne.13316. Online ahead of print.

ABSTRACT

Opioid-induced deficits in maternal behaviors are well-characterized in rodent models. Amid the current epidemic of opioid use disorder (OUD), prevalence among pregnant women has risen sharply. Yet, the roles of buprenorphine replacement treatment for OUD (BT/OUD) in the brain functions of postpartum mothers are unclear. Using functional magnetic resonance imaging (fMRI), we have developed an evolutionarily conserved maternal behavior neurocircuit (MBN) model to study human maternal care versus defensive/aggressive behaviors critical to mother-child bonding. The anterior cingulate gyrus (ACC) is not only involved in the MBN for mother-child bonding and attachment, but also part of an opioid sensitive "pain-matrix". The literature suggests that prescription opioids produce physical and emotional "analgesic" effects by disrupting specific resting-state functional connectivity (rs-FC) of ACC to regions related to MBN. Thus, in this longitudinal study, we report findings of overlapping MBN and pain matrix circuits, for mothers with chronic exposure of BT/OUD. A total of 32 mothers were studied with 6 min rs-FC at 1 month (T1) and 4 months postpartum (T2), including seven on BT/OUD and 25 non-BT/OUD mothers as a comparison group. We analyzed rs-FC between the insula, putamen, and the dorsal anterior cingulate cortex (DACC) and rostral ACC (RACC), as the regions of interest that mediate opioid analgesia. BT/OUD mothers, as compared to non-BT/OUD mothers, showed less left insula-RACC rs-FC but greater right putamen-DACC rs-FC at T1, with these between-group differences diminished at T2. Some of these rs-FC results were correlated with the scores of postpartum parental bonding questionnaire. We found time-by-treatment interaction effects on DACC and RACC-dependent rs-FC, potentially identifying brain mechanisms for beneficial effects of BT, normalizing dysfunction of maternal brain and behavior over the first four months postpartum. This study complements recent studies to ascertain how BT/OUD affects maternal behaviors, mother-child bonding, and intersubjectivity and reveals potential MBN/pain-matrix targets for novel interventions.

PMID:37491982 | DOI:10.1111/jne.13316

The neurocognitive impact of loneliness and social networks on social adaptation

Tue, 07/25/2023 - 18:00

Sci Rep. 2023 Jul 25;13(1):12048. doi: 10.1038/s41598-023-38244-0.

ABSTRACT

Social adaptation arises from the interaction between the individual and the social environment. However, little empirical evidence exists regarding the relationship between social contact and social adaptation. We propose that loneliness and social networks are key factors explaining social adaptation. Sixty-four healthy subjects with no history of psychiatric conditions participated in this study. All participants completed self-report questionnaires about loneliness, social network, and social adaptation. On a separate day, subjects underwent a resting state fMRI recording session. A hierarchical regression model on self-report data revealed that loneliness and social network were negatively and positively associated with social adaptation. Functional connectivity (FC) analysis showed that loneliness was associated with decreased FC between the fronto-amygdalar and fronto-parietal regions. In contrast, the social network was positively associated with FC between the fronto-temporo-parietal network. Finally, an integrative path model examined the combined effects of behavioral and brain predictors of social adaptation. The model revealed that social networks mediated the effects of loneliness on social adaptation. Further, loneliness-related abnormal brain FC (previously shown to be associated with difficulties in cognitive control, emotion regulation, and sociocognitive processes) emerged as the strongest predictor of poor social adaptation. Findings offer insights into the brain indicators of social adaptation and highlight the role of social networks as a buffer against the maladaptive effects of loneliness. These findings can inform interventions aimed at minimizing loneliness and promoting social adaptation and are especially relevant due to the high prevalence of loneliness around the globe. These findings also serve the study of social adaptation since they provide potential neurocognitive factors that could influence social adaptation.

PMID:37491346 | DOI:10.1038/s41598-023-38244-0

Altered resting-state cerebellar-cerebral functional connectivity in patients with end-stage renal disease

Tue, 07/25/2023 - 18:00

Ren Fail. 2023 Dec;45(1):2238829. doi: 10.1080/0886022X.2023.2238829.

ABSTRACT

BACKGROUND: End-stage renal disease (ESRD) patients have functional and structural brain abnormalities. The cerebellum also showed varying degrees of damage. However, no studies on cerebellar-cerebral functional connectivity (FC) have been conducted in ESRD patients. This study aimed to investigate the changes in cerebellar-cerebral FC in ESRD patients and its relationship with neuropsychological and clinical indexes.

METHODS: Resting-state functional magnetic resonance imaging and neuropsychological assessment were performed on 37 ESRD patients and 35 control subjects. Seed-based FC analysis was performed to investigate inter-group differences in cerebellar-cerebral FC. In addition, the relations of altered FC with the neuropsychological function and clinical indicators were analyzed in ERSD patients.

RESULTS: ESRD patients exhibited alterations in cerebellar-cerebral FC involving the executive control network, default mode network, and affective-limbic network compared to control subjects (False discovery rate-corrected, p < 0.05). The altered cerebellar-cerebral FC was associated with the Montreal Cognitive Assessment Scale score (p < 0.05), and correlated with serum creatinine and uric acid levels within the ESRD group (p < 0.05).

CONCLUSIONS: The study indicates that cerebellar-cerebral FC is involved in the neural substrates of cognitive impairment in ESRD patients. The findings may provide clinically relevant new neuroimaging biomarkers for the neuropathological mechanisms underlying cognitive impairment of ESRD.

PMID:37488933 | DOI:10.1080/0886022X.2023.2238829

Spontaneous brain microstates correlate with impaired inhibitory control in internet addiction disorder

Mon, 07/24/2023 - 18:00

Psychiatry Res Neuroimaging. 2023 Jul 19;334:111686. doi: 10.1016/j.pscychresns.2023.111686. Online ahead of print.

ABSTRACT

The prevalence of the Internet addiction disorder (IAD) has been on the rise, making it increasingly imperative to explore the neurophysiological markers of it. Using the whole-brain imaging approach of EEG microstate analysis, which treats multichannel EEG recordings as a series of quasi-steady states, similar as the resting-state networks found by fMRI, the present study aimed to investigate the specificity of the IAD in class C of the four canonical microstates. The existing EEG data of 40 participants (N = 20 for each group) was used, and correlation between the time parameters of microstate C and the performance of the Go/NoGo task was analyzed. Results suggested that the duration and coverage of class C were significantly reduced in the IAD group as compared to the healthy control (HC) group. Furthermore, the duration of class C had a significant inverse correlation with Go RTs in the IAD group. These results implied that class C might serve as a neurophysiological marker of IAD, helping to understand the underlying neural mechanism of inhibitory control in IAD.

PMID:37487311 | DOI:10.1016/j.pscychresns.2023.111686

Autism spectrum disorder diagnosis based on deep unrolling-based spatial constraint representation

Mon, 07/24/2023 - 18:00

Med Biol Eng Comput. 2023 Jul 24. doi: 10.1007/s11517-023-02859-2. Online ahead of print.

ABSTRACT

Accurate diagnosis of autism spectrum disorder (ASD) is crucial for effective treatment and prognosis. Functional brain networks (FBNs) constructed from functional magnetic resonance imaging (fMRI) have become a popular tool for ASD diagnosis. However, existing model-driven approaches used to construct FBNs lack the ability to capture potential non-linear relationships between data and labels. Moreover, most existing studies treat the FBNs construction and disease classification as separate steps, leading to large inter-subject variability in the estimated FBNs and reducing the statistical power of subsequent group comparison. To address these limitations, we propose a new approach to FBNs construction called the deep unrolling-based spatial constraint representation (DUSCR) model and integrate it with a convolutional classifier to create an end-to-end framework for ASD recognition. Specifically, the model spatial constraint representation (SCR) is solved using a proximal gradient descent algorithm, and we unroll it into deep networks using the deep unrolling algorithm. Classification is then performed using a convolutional prototype learning model. We evaluated the effectiveness of the proposed method on the ABIDE I dataset and observed a significant improvement in model performance and classification accuracy. The resting state fMRI images are preprocessed into time series data and 3D coordinates of each region of interest. The data are fed into the DUSCR model, a model for building functional brain networks using deep learning instead of traditional models, that we propose, and then the outputs are fed into the convolutional classifier with prototype learning to determine whether the patient has ASD disease.

PMID:37486440 | DOI:10.1007/s11517-023-02859-2

Use of a Foot-Induced Digitally Controlled Resistance Device for Functional Magnetic Resonance Imaging Evaluation in Patients with Foot Paresis

Mon, 07/24/2023 - 18:00

J Vis Exp. 2023 Jul 7;(197). doi: 10.3791/64613.

ABSTRACT

Neurological deficits from a stroke can result in long-term motor disabilities, including those that affect walking gait. However, extensive rehabilitation following stroke is typically time limited. Establishing predictive biomarkers to identify patients who may meaningfully benefit from additional physical therapy and demonstrate improvement is important to improve the patients' quality of life. Detection of neuroplastic remodeling of the affected region and changes in the activity patterns excited while performing suitable motor tasks could have valuable implications for chronic stroke recovery. This protocol describes the use of a digitally controlled, magnetic resonance-compatible foot-induced robotic device (MR_COFID) to present a personalized foot-motor task involving trajectory following to stroke-affected subjects with gait impairment during functional magnetic resonance imaging (fMRI). In the task, foot flexion is performed against bi-directional resistive forces, which are tuned to the subject's strength in both the dorsiflexion and plantar flexion directions, while following a visual metronome. fMRI non-invasively uses endogenous deoxyhemoglobin as a contrast agent to detect blood oxygenation level-dependent (BOLD) changes between the active and resting periods during testing. Repeated periodic testing can detect therapy-related changes in excitation patterns during task performance. The use of this technique provides data to identify and measure biomarkers that may indicate the likelihood of an individual benefitting from rehabilitation beyond that which is currently provided to stroke patients.

PMID:37486119 | DOI:10.3791/64613

Development and validation of a multimodal neuroimaging biomarker for electroconvulsive therapy outcome in depression: a multicenter machine learning analysis

Mon, 07/24/2023 - 18:00

Psychol Med. 2023 Jul 24:1-12. doi: 10.1017/S0033291723002040. Online ahead of print.

ABSTRACT

BACKGROUND: Electroconvulsive therapy (ECT) is the most effective intervention for patients with treatment resistant depression. A clinical decision support tool could guide patient selection to improve the overall response rate and avoid ineffective treatments with adverse effects. Initial small-scale, monocenter studies indicate that both structural magnetic resonance imaging (sMRI) and functional MRI (fMRI) biomarkers may predict ECT outcome, but it is not known whether those results can generalize to data from other centers. The objective of this study was to develop and validate neuroimaging biomarkers for ECT outcome in a multicenter setting.

METHODS: Multimodal data (i.e. clinical, sMRI and resting-state fMRI) were collected from seven centers of the Global ECT-MRI Research Collaboration (GEMRIC). We used data from 189 depressed patients to evaluate which data modalities or combinations thereof could provide the best predictions for treatment remission (HAM-D score ⩽7) using a support vector machine classifier.

RESULTS: Remission classification using a combination of gray matter volume and functional connectivity led to good performing models with average 0.82-0.83 area under the curve (AUC) when trained and tested on samples coming from the three largest centers (N = 109), and remained acceptable when validated using leave-one-site-out cross-validation (0.70-0.73 AUC).

CONCLUSIONS: These results show that multimodal neuroimaging data can be used to predict remission with ECT for individual patients across different treatment centers, despite significant variability in clinical characteristics across centers. Future development of a clinical decision support tool applying these biomarkers may be feasible.

PMID:37485692 | DOI:10.1017/S0033291723002040

Short-term blood pressure variability is inversely related to regional amplitude of low frequency fluctuations in older and younger adults

Mon, 07/24/2023 - 18:00

Aging Brain. 2023 Jul 11;4:100085. doi: 10.1016/j.nbas.2023.100085. eCollection 2023.

ABSTRACT

Blood pressure variability (BPV), independent of mean blood pressure levels, is associated with cerebrovascular disease burden on MRI and postmortem evaluation. However, less is known about relationships with markers of cerebrovascular dysfunction, such as diminished spontaneous brain activity as measured by the amplitude of low frequency fluctuations (ALFF), especially in brain regions with vascular and neuronal vulnerability in aging. We investigated the relationship between short-term BPV and concurrent regional ALFF from resting state fMRI in a sample of community-dwelling older adults (n = 44) and healthy younger adults (n = 49). In older adults, elevated systolic BPV was associated with lower ALFF in widespread medial temporal regions and the anterior cingulate cortex. Higher systolic BPV in younger adults was also related to lower ALFF in the medial temporal lobe, albeit in fewer subregions, and the amygdala. There were no significant associations between systolic BPV and ALFF across the right/left whole brain or in the insular cortex in either group. Findings suggest a possible regional vulnerability to cerebrovascular dysfunction and short-term fluctuations in blood pressure. BPV may be an understudied risk factor for cerebrovascular changes in aging.

PMID:37485296 | PMC:PMC10362312 | DOI:10.1016/j.nbas.2023.100085

Machine learning for detecting Wilson's disease by amplitude of low-frequency fluctuation

Mon, 07/24/2023 - 18:00

Heliyon. 2023 Jul 7;9(7):e18087. doi: 10.1016/j.heliyon.2023.e18087. eCollection 2023 Jul.

ABSTRACT

Wilson's disease (WD) is a genetic disorder with the A7P7B gene mutations. It is difficult to diagnose in clinic. The purpose of this study was to confirm whether amplitude of low-frequency fluctuations (ALFF) is one of the potential biomarkers for the diagnosis of WD. The study enrolled 30 healthy controls (HCs) and 37 WD patients (WDs) to obtain their resting-state functional magnetic resonance imaging (rs-fMRI) data. ALFF was obtained through preprocessing of the rs-fMRI data. To distinguish between patients with WDs and HCs, four clusters with abnormal ALFF-z values were identified through between-group comparisons. Based on these clusters, three machine learning models were developed, including Random Forest (RF), Support Vector Machine (SVM), and Logistic Regression (LR). Abnormal ALFF z-values were also combined with volume information, clinical variables, and imaging features to develop machine learning models. There were 4 clusters where the ALFF z-values of the WDs were significantly higher than that of the HCs. Cluster1 was in the cerebellar region, Cluster2 was in the left caudate nucleus, Cluster3 was in the bilateral thalamus, and Cluster4 was in the right caudate nucleus. In the training set and test set, the models trained with Cluster2, Cluster3, and Cluster4 achieved area of curve (AUC) greater than 0.80. In the Delong test, only the AUC values of models trained with Cluster4 exhibited statistical significance. The AUC values of the Logit model (P = 0.04) and RF model (P = 0.04) were significantly higher than those of the SVM model. In the test set, the LR model and RF model trained with Cluster3 had high specificity, sensitivity, and accuracy. By conducting the Delong test, we discovered that there was no statistically significant inter-group difference in AUC values between the model that integrates multi-modal information and the model before fusion. The LR models trained with multimodal information and Cluster 4, as well as the LR and RF models trained with multimodal information and Cluster 3, have demonstrated high accuracy, specificity, and sensitivity. Overall, these findings suggest that using ALFF based on the thalamus or caudate nucleus as markers can effectively differentiate between WDs and HCs. The fusion of multimodal information did not significantly improve the classification performance of the models before fusion.

PMID:37483763 | PMC:PMC10362133 | DOI:10.1016/j.heliyon.2023.e18087

Altered functional connectivity of the thalamus in patients with insomnia disorder after transcutaneous auricular vagus nerve stimulation therapy

Mon, 07/24/2023 - 18:00

Front Neurol. 2023 Jul 6;14:1164869. doi: 10.3389/fneur.2023.1164869. eCollection 2023.

ABSTRACT

The pathogenesis of insomnia is related to the dysfunction of the thalamus. Transcutaneous auricular vagus nerve stimulation (taVNS) has proved to be effective in treating insomnia. However, whether taVNS alleviates insomnia through modulating thalamus-related functional connectivity remains unclear. To elucidate the instant modulating effects of taVNS on the resting state functional connectivity (RSFC) of the thalamus, 20 patients with insomnia disorder were recruited to receive taVNS treatment and their resting state functional magnetic resonance imaging (fMRI) data were collected immediately before and after stimulation. The fMRI data were compared with 20 age- and gender-matched healthy subjects who received no stimulation and had RSFC fMRI data collected once. RSFC analyses of the thalamus were performed in both groups. In addition to assessing the group differences between ID patients and healthy controls regarding the RSFC of the thalamus, we examined the taVNS-induced changes of RSFC of the thalamus in ID patients. Before taVNS treatment, the ID patients showed increased RSFC of the thalamus with the right insula and inferior frontal gyrus than healthy controls. After taVNS treatment, the RSFC between the thalamus and the right angular gyrus, left anterior cingulate gyrus, and precuneus were significantly decreased in patients. This study provides insights into the instant brain effects involving the thalamus-related functional connectivity of taVNS performed on insomnia disorder patients.

PMID:37483453 | PMC:PMC10357469 | DOI:10.3389/fneur.2023.1164869

Connectivity reveals homology between the visual systems of the human and macaque brains

Fri, 07/21/2023 - 18:00

Front Neurosci. 2023 Jul 5;17:1207340. doi: 10.3389/fnins.2023.1207340. eCollection 2023.

ABSTRACT

The visual systems of humans and nonhuman primates share many similarities in both anatomical and functional organization. Understanding the homology and differences between the two systems can provide important insights into the neural basis of visual perception and cognition. This research aims to investigate the homology between human and macaque visual systems based on connectivity, using diffusion tensor imaging and resting-state functional magnetic resonance imaging to construct structural and functional connectivity fingerprints of the visual systems in humans and macaques, and quantitatively analyze the connectivity patterns. By integrating multimodal magnetic resonance imaging, this research explored the homology and differences between the two systems. The results showed that 9 brain regions in the macaque visual system formed highly homologous mapping relationships with 11 brain regions in the human visual system, and the related brain regions between the two species showed highly structure homologous, with their functional organization being essentially conserved across species. Finally, this research generated a homology information map of the visual system for humans and macaques, providing a new perspective for subsequent cross-species analysis.

PMID:37476839 | PMC:PMC10354265 | DOI:10.3389/fnins.2023.1207340

Time of day dependent longitudinal changes in resting-state fMRI

Fri, 07/21/2023 - 18:00

Front Neurol. 2023 Jul 5;14:1166200. doi: 10.3389/fneur.2023.1166200. eCollection 2023.

ABSTRACT

Longitudinal studies have become more common in the past years due to their superiority over cross-sectional samples. In light of the ongoing replication crisis, the factors that may introduce variability in resting-state networks have been widely debated. This publication aimed to address the potential sources of variability, namely, time of day, sex, and age, in longitudinal studies within individual resting-state fMRI data. DCM was used to analyze the fMRI time series, extracting EC connectivity measures and parameters that define the BOLD signal. In addition, a two-way ANOVA was used to assess the change in EC and parameters that define the BOLD signal between data collection waves. The results indicate that time of day and gender have significant model evidence for the parameters that define the BOLD signal but not EC. From the ANOVA analysis, findings indicate that there was a significant change in the two nodes of the DMN and their connections with the fronto-parietal network. Overall, these findings suggest that in addition to age and gender, which are commonly accounted for in the fMRI data collection, studies should note the time of day, possibly treating it as a covariate in longitudinal samples.

PMID:37475742 | PMC:PMC10354550 | DOI:10.3389/fneur.2023.1166200

Abnormal regional spontaneous neural activity and functional connectivity in thyroid-associated ophthalmopathy patients with different activity: a resting-state fMRI study

Fri, 07/21/2023 - 18:00

Front Neurol. 2023 Jul 5;14:1199251. doi: 10.3389/fneur.2023.1199251. eCollection 2023.

ABSTRACT

PURPOSE: We aimed to evaluate the spontaneous neuronal activity and functional connectivity pattern variations using resting-state functional magnetic resonance imaging (rs-fMRI) measures, such as amplitude of low-frequency fluctuation (ALFF), fractional amplitude of low-frequency fluctuation (fALFF), and functional connectivity (FC), in patients with thyroid-associated ophthalmopathy (TAO).

METHOD: A total of 24 active TAO patients, 26 inactive TAO patients, and 27 matched healthy controls (HCs) were included. First, ALFF and fALFF were used to detect local neural activity changes, the MRI data were analyzed, and regions with group differences were taken as seeds. Second, FC analysis was performed to explore the altered connection between seeds and other brain regions. A correlation analysis was performed to assess the relationship between functional brain activity and clinical indices and neuropsychiatric behaviors.

RESULTS: Compared to HCs, both active and inactive TAO patients exhibited significantly lower ALFF values in the right calcarine (Calcarine_R) and left postcentral gyrus (Postcentral_L). Active TAO patients also showed significantly higher ALFF values in the left caudate nucleus (Caudate_L) and increased fALFF values in the superior lobe of the right cerebellum (Cerebelum_Crus1_R). Moreover, both active and inactive TAO patients demonstrated decreased FC within the left postcentral gyrus (Postcentral_L) compared to HCs. Additionally, active TAO patients exhibited lower FC compared to inactive TAO patients. The ALFF values in the Calcarine_R of active TAO patients positively correlated with disease duration (r = 0.5892, p = 0.0049) and the Hamilton Anxiety Rating Scale (HARS; r = 0.5377, p = 0.0119). Furthermore, the ALFF value in the Calcarine_R of inactive TAO patients negatively correlated with visual functioning (r = -0.5449, p = 0.0072), while the ALFF values in the Caudate_L of active TAO patients positively correlated with visual functioning (r = 0.6496, p = 0.0014).

CONCLUSION: We found that the Caudate_L and Cerebelum_Crus1_R related to motor control and coordination in active TAO patients exhibit significant compensatory mechanisms; whereas, the Calcarine_R and Postcentral_L related to visual and somatosensory cortices show varying degrees of impairment. Our findings complement the functional neural mechanism of TAO.

PMID:37475733 | PMC:PMC10354644 | DOI:10.3389/fneur.2023.1199251

Functional magnetic resonance imaging study during resting state and visual oddball task in mild cognitive impairment

Fri, 07/21/2023 - 18:00

CNS Neurosci Ther. 2023 Jul 20. doi: 10.1111/cns.14371. Online ahead of print.

ABSTRACT

BACKGROUND: Amnestic mild cognitive impairment (aMCI) is a transitional state between normal aging and dementia, and identifying early biomarkers is crucial for disease detection and intervention. Functional magnetic resonance imaging (fMRI) has the potential to identify changes in neural activity in MCI.

METHODS: We investigated neural activity changes in the visual network of the aMCI patients (n:20) and healthy persons (n:17) using resting-state fMRI and visual oddball task fMRI. We used independent component analysis to identify regions of interest and compared the activity between groups using a false discovery rate correction.

RESULTS: Resting-state fMRI revealed increased activity in the areas that have functional connectivity with the visual network, including the right superior and inferior lateral occipital cortex, the right angular gyrus and the temporo-occipital part of the right middle temporal gyrus (p-FDR = 0.008) and decreased activity in the bilateral thalamus and caudate nuclei, which are part of the frontoparietal network in the aMCI group (p-FDR = 0.002). In the visual oddball task fMRI, decreased activity was found in the right frontal pole, the right frontal orbital cortex, the left superior parietal lobule, the right postcentral gyrus, the right posterior part of the supramarginal gyrus, the right superior part of the lateral occipital cortex, and the right angular gyrus in the aMCI group.

CONCLUSION: Our results suggest the alterations in the visual network are present in aMCI patients, both during resting-state and task-based fMRI. These changes may represent early biomarkers of aMCI and highlight the importance of assessing visual processing in cognitive impairment. However, future studies with larger sample sizes and longitudinal designs are needed to confirm these findings.

PMID:37475197 | DOI:10.1111/cns.14371

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