Search Results (65)

Background/Objectives: The insula is a deep, functionally heterogeneous region involved in various pathological conditions. Repetitive transcranial magnetic stimulation (rTMS) has emerged as a promising therapeutic avenue for neuromodulation, yet very few studies have directly investigated its effects on insular activity. Moreover, empirical evidence of target engagement of this region remains scarce. This study aimed to stimulate the insula with rTMS and assess blood oxygen level-dependent (BOLD) signal modulation using concurrent functional magnetic resonance imaging (fMRI). Methods: Ten participants were recruited, six of whom underwent a single session of 5 Hz high-frequency rTMS over the right insular cortex inside the MRI scanner. Stimulation was delivered using a compatible MRI-B91 TMS coil. Stimulation consisted of 10 trains of 10 s each, with a 50 s interval between trains. Frameless stereotactic neuronavigation ensured precise targeting. Paired t-tests were used to compare the mean BOLD signal obtained between stimulation trains with resting-state fMRI acquired before the rTMS stimulation session. A significant cluster threshold of q < 0.01 (False Discovery Rate; FDR) with a minimum cluster size of 10 voxels was applied. Results: Concurrent rTMS-fMRI revealed the significant modulation of BOLD activity within insular subregions. Increased activity was observed in the anterior, middle, and middle-inferior insula, while decreased activity was identified in the ventral anterior and posterior insula. Additionally, two participants reported transient dysgeusia following stimulation, which provides further evidence of insular modulation. Conclusions: These findings provide preliminary evidence that rTMS can modulate distinct subregions of the insular cortex. The combination of region-specific BOLD responses and stimulation-induced dysgeusia supports the feasibility of using rTMS to modulate insular activity. Full article

Background/Objectives: Fibromyalgia (FM) is a chronic pain condition that includes symptoms of hyperalgesia and has an unknown etiology. This study aimed to further investigate the underlying neural signaling mechanisms and their relation to observed blood oxygenation-level dependent (BOLD) signal increases at the onset of functional magnetic resonance imaging (fMRI) runs. Methods: The possible neural mechanisms were first explored by reviewing the current literature. The second component of this study involved a voxel-by-voxel analysis of BOLD responses in all regions of the brain. The fMRI data were obtained from a previous study of participants with and without fibromyalgia during fMRI runs involving either a noxious heat pain stimulus or no stimulus. Results: The literature review indicates that no single factor can explain the initial BOLD signal rise observed in FM but that there are likely multiple interacting influences. These include physiological dysregulation via mechanisms, such as oxidative stress, mitochondrial dysfunction, and cytokine activity, and may involve the sympathetic nervous system. The analysis of BOLD responses demonstrated that the initial BOLD rises occur specifically in gray matter regions and are largest in regions involved with pain processing, including the right insular cortex and periaqueductal gray region. Moreover, the BOLD rise is significantly larger in people with FM prior to the application of a noxious stimulus. Conclusions: The initial rise in BOLD response demonstrates heightened metabolic demand that is exaggerated in people with FM. It appears to be influenced by cognitive factors such as anticipation and may reflect neural dysregulation, possibly involving autonomic signaling. Full article

Background: Alzheimer’s disease (AD) is a common neurodegenerative disease. Functional magnetic resonance imaging (fMRI) can be used to measure the temporal correlation of blood-oxygen-level-dependent (BOLD) signals in the brain to assess the brain’s intrinsic connectivity and capture dynamic changes in the brain. In this study, our research goal is to investigate how the brain network structure, as measured by resting-state fMRI, differs across distinct physiological states. Method: With the research goal of addressing the limitations of BOLD signal-based brain networks constructed using Pearson correlation coefficients, individual brain networks and community detection are used to study the brain networks based on co-community probability matrices (CCPMs). We used CCPMs and enrichment analysis to compare differences in brain network topological characteristics among three typical brain states. Result: The experimental results indicate that AD patients with increasing disease severity levels will experience the isolation of brain networks and alterations in the topological characteristics of brain networks, such as the Somatomotor Network (SMN), dorsal attention network (DAN), and Default Mode Network (DMN). Conclusion: This work suggests that using different data-driven methods based on CCPMs to study alterations in the topological characteristics of brain networks would provide better information complementarity, which can provide a novel analytical perspective for AD progression and a new direction for the extraction of neuro-biomarkers in the early diagnosis of AD. Full article

Assessment of cerebrovascular function is crucial for managing neurological disorders, with cerebral blood flow (CBF) measurement being key. Single photon emission computed tomography (SPECT), a traditional method, uses radiation exposure. Blood oxygenation level-dependent (BOLD) magnetic resonance imaging (MRI) with carbon dioxide (CO₂) is a non-invasive cerebrovascular reactivity (CVR) alternative, but direct SPECT-MRI CO₂ comparisons for MRI’s replacement potential are limited. This study directly compared CVR from SPECT and MRI CO₂ in nine healthy participants. Delay-based MRI (tcMRI) with stimulus timing correction was analyzed alongside conventional MRI. Results showed no significant CVR differences between SPECT and tcMRI (p = 0.688) or SPECT and conventional MRI (p = 0.813), indicating comparable overall CVR. However, tcMRI significantly differed from conventional MRI (p = 0.016) and showed a greater similarity to SPECT. Regionally, the largest CVR differences were observed between tcMRI and conventional MRI, particularly in the cingulate cortex, frontal lobe, and basal ganglia. These discrepancies suggest that tcMRI may capture subtle CVR abnormalities not detected by conventional MRI. The findings support the clinical utility of CO₂-MRI, especially with stimulus timing correction, as a safe, repeatable, and radiation-free alternative to SPECT. In particular, tcMRI may offer advantages for repeated CVR assessments in long-term clinical monitoring. Full article

Background/Objectives: Cerebrovascular reactivity (CVR) and time shift (TS) are vascular-related parameters that reflect cerebral perfusion and may be associated with the risk of developing stroke in patients with asymptomatic carotid artery stenosis (ACAS). We investigated CVR and TS in patients with ACAS using resting-state magnetic resonance imaging based on blood-oxygen-level-dependent contrast (BOLD-MRI). Methods: We included twenty patients with severe unilateral ACAS and twenty age-matched controls. Individual CVR maps were obtained through a voxel-wise regression of the MRI signal, using the global signal filtered in a specific frequency range (0.02–0.04 Hz) as the regressor. A recursive cross-correlation method provided individual TS maps through the BOLD low-frequency fluctuation. CVR and TS values were obtained for the territories irrigated by the main cerebral arteries (anterior, middle, and posterior) separated into proximal, intermediary, and distal regions. Results: Compared to controls, ACAS patients presented reduced CVR and increased TS in the distal parts of the brain vascular territories. Individual CVR and TS values varied more within the patient group than controls. Such individual variability may help identify patients eligible for intervention better than the stenosis grade. Conclusions: CVR and TS may indicate subtle hemodynamic changes and assist in identifying regions at higher risk of neuronal damage or ischemic stroke on an individual basis, aiding in the stratification of patients with ACAS based on their risk of progressing to stroke. Full article

(1) Background: Working memory, which involves temporary storage, information processing, and regulating attention resources, is a fundamental cognitive process and constitutes a significant component of neuroscience research. This study aimed to evaluate brain activation patterns by analyzing functional magnetic resonance imaging (fMRI) time-series data collected during a designed N-back working memory task with varying cognitive demands. (2) Methods: We utilized a novel transformer model, blood oxygen level-dependent transformer (BolT), to extract the activation level features of brain regions in the cognitive process, thereby obtaining the influence weights of regions of interest (ROIs) on the corresponding tasks. (3) Results: Compared with previous studies, our work reached similar conclusions in major brain region performance and provides a more precise analysis for identifying brain activation patterns. For each type of working memory task, we selected the top 5 percent of the most influential ROIs and conducted a comprehensive analysis and discussion. Additionally, we explored the effect of prior knowledge conditions on the performance of different tasks in the same period and the same tasks at different times. (4) Conclusions: The comparison results reflect the brain’s adaptive strategies and dependencies in coping with different levels of cognitive demands and the stability optimization of the brain’s cognitive processing. This study introduces innovative methodologies for understanding brain function and cognitive processes, highlighting the potential of transformer in cognitive neuroscience. Its findings offer new insights into brain activity patterns associated with working memory, contributing to the broader landscape of neuroscience research. Full article

(1) Background: Functional magnetic resonance imaging (fMRI) utilizing multi-echo gradient echo-planar imaging (ME-GE-EPI) has demonstrated higher sensitivity and stability compared to utilizing single-echo gradient echo-planar imaging (SE-GE-EPI). The direct derivation of T₂* maps from fitting multi-echo data enables accurate recording of dynamic functional changes in the brain, exhibiting higher sensitivity than echo combination maps. However, the widely employed voxel-wise log-linear fitting is susceptible to inevitable noise accumulation during image acquisition. (2) Methods: This work introduced a synthetic data-driven deep learning (SD-DL) method to obtain T₂* maps for multi-echo (ME) fMRI analysis. (3) Results: The experimental results showed the efficient enhancement of the temporal signal-to-noise ratio (tSNR), improved task-based blood oxygen level-dependent (BOLD) percentage signal change, and enhanced performance in multi-echo independent component analysis (MEICA) using the proposed method. (4) Conclusion: T₂* maps derived from ME-fMRI data using the proposed SD-DL method exhibit enhanced BOLD sensitivity in comparison to T₂* maps derived from the LLF method. Full article

Revascularization surgery for the symptomatic hemisphere with hemodynamic impairment is effective for Moyamoya vasculopathy patients. However, careful patient selection is crucial and ideally supported by advanced quantitative hemodynamic imaging. Recently, blood oxygenation level-dependent cerebrovascular reactivity (BOLD-CVR) and quantitative magnetic resonance angiography with non-invasive optimal vessel analysis (qMRA-NOVA) have gained prominence in assessing these patients. This study aims to present the results of BOLD-CVR and qMRA-NOVA imaging along with the changes in cerebral hemodynamics and flow status following flow augmentation with superficial temporal artery–middle cerebral artery (STA-MCA) bypass in our Moyamoya vasculopathy patient cohort. Symptomatic patients with Moyamoya vasculopathy treated at the Clinical Neuroscience Center of the University Hospital Zurich who underwent hemodynamic and flow imaging (BOLD-CVR and qMRA-NOVA) before and after bypass were included in the analysis. Reduced hemispheric volume flow rates, as well as impaired BOLD-CVR, were measured in all 12 patients with Moyamoya vasculopathy before STA-MCA bypass surgery. Following the surgical procedure, post-operative BOLD-CVR demonstrated a non-significant increase in BOLD-CVR values within the revascularized, symptomatic middle cerebral artery territory and cerebral hemisphere. The results of the statistical tests should be viewed as indicative due to the small sample size. Additionally, post-operative qMRA-NOVA revealed a significant improvement in the hemispheric volume flow rate of the affected hemisphere due to the additional bypass flow rate. Our findings affirm the presence of hemodynamic and flow impairments in the symptomatic hemisphere of the Moyamoya vasculopathy patients. Bypass surgery proves effective in improving both BOLD-CVR impairment and the hemispheric volume flow rate in our patient cohort. Full article

Purpose: To explore the Oxford classification and prognostic risk stratification of the non-invasive evaluation of immunoglobulin A nephropathy (IgAN) or immunoglobulin A vasculitis with nephritis (IgAVN) in children using multiparametric magnetic resonance imaging (MRI). Materials and Methods: Forty-four children diagnosed with IgAN or IgAVN were included. Patients with 80-month risk scores >10% were categorized as the high-risk group, while others constituted the low-risk group. The T2* and apparent diffusion coefficient (ADC) values of the renal cortex and medulla were measured. Clinical and pathological parameters were also assessed. Univariate and multivariate logistic regression analyses were performed to identify the indicators associated with the high-risk group. Receiver operating characteristic (ROC) curves were drawn and the areas under the curve (AUCs) were calculated to evaluate the diagnostic performance variables for differentiating the high-risk group from the low-risk group. Results: Only the T2*Cortex and mean arterial pressure (MAP) were independently reliable in both the univariate and multivariate analyses. The AUCs for differentiating the high-risk group from the low-risk group of T2*Cortex, MAP, and their combination model were 0.907, 0.881, and 0.947, respectively. Conclusions: Multiparametric MRI parameters, especially T2* values, could be used as new biomarkers to provide a new dimension in chronic kidney disease-related research and could play an important role in the non-invasive prognosis of children with IgAN or IgAVN. Full article

The Global Neuronal Workspace (GNW) hypothesis states that the visual percept is available to conscious awareness only if recurrent long-distance interactions among distributed brain regions activate neural circuitry extending from the posterior areas to prefrontal regions above a certain excitation threshold. To directly test this hypothesis, we trained 14 human participants to increase blood oxygenation level-dependent (BOLD) signals with real-time functional magnetic resonance imaging (rtfMRI)-based neurofeedback simultaneously in four specific regions of the occipital, temporal, insular and prefrontal parts of the brain. Specifically, we hypothesized that the up-regulation of the mean BOLD activity in the posterior–frontal brain regions lowers the perceptual threshold for visual stimuli, while down-regulation raises the threshold. Our results showed that participants could perform up-regulation (Wilcoxon test, session 1: p = 0.022; session 4: p = 0.041) of the posterior–frontal brain activity, but not down-regulation. Furthermore, the up-regulation training led to a significant reduction in the visual perceptual threshold, but no substantial change in perceptual threshold was observed after the down-regulation training. These findings show that the up-regulation of the posterior–frontal regions improves the perceptual discrimination of the stimuli. However, further questions as to whether the posterior–frontal regions can be down-regulated at all, and whether down-regulation raises the perceptual threshold, remain unanswered. Full article

Objective: Functional magnetic resonance imaging (fMRI) has been applied to assess the microstructure of the kidney. However, it is not clear whether fMRI could be used in the field of kidney injury in patients with Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV). Methods: This study included 20 patients with AAV. Diffusion kurtosis imaging (DKI) and blood oxygen level-dependent (BOLD) scanning of the kidneys were performed in AAV patients and healthy controls. The mean kurtosis (MK), mean diffusivity (MD), and fractional anisotropy (FA) parameters of DKI, the R2* parameter of BOLD, and clinical data were further analyzed. Results: In AAV patients, the cortex exhibited lower MD but higher R2* values compared to the healthy controls. Medullary MK values were elevated in AAV patients. Renal medullary MK values showed a positive correlation with serum creatinine levels and negative correlations with hemoglobin levels and estimated glomerular filtration rate. To assess renal injury in AAV patients, AUC values for MK, MD, FA, and R2* in the cortex were 0.66, 0.67, 0.57, and 0.55, respectively, and those in the medulla were 0.81, 0.77, 0.61, and 0.53, respectively. Conclusions: Significant differences in DKI and BOLD MRI parameters were observed between AAV patients with kidney injuries and the healthy controls. The medullary MK value in DKI may be a noninvasive marker for assessing the severity of kidney injury in AAV patients. Full article

To date, there are almost no investigations addressing functional connectivity (FC) in patients with brain metastases (BM). In this retrospective study, we investigate the influence of BM on hemodynamic brain signals derived from functional magnetic resonance imaging (fMRI) and FC. Motor-fMRI data of 29 patients with BM and 29 matched healthy controls were analyzed to assess percent signal changes (PSC) in the ROIs motor cortex, premotor cortex, and supplementary motor cortex and FC in the sensorimotor, default mode, and salience networks using Statistical Parametric Mapping (SPM12) and marsbar and CONN toolboxes. In the PSC analysis, an attenuation of the BOLD signal in the metastases-affected hemisphere compared to the contralateral hemisphere was significant only in the supplementary motor cortex during hand movement. In the FC analysis, we found alterations in patients’ FC compared to controls in all examined networks, also in the hemisphere contralateral to the metastasis. This indicates a qualitative attenuation of the BOLD signal in the affected hemisphere and also that FC is altered by the presence of BM, similarly to what is known for primary brain tumors. This transformation is not only visible in the infiltrated hemisphere, but also in the contralateral one, suggesting an influence of BM beyond local damage. Full article

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder. Functional magnetic resonance imaging (fMRI) can be used to measure the temporal correlation of blood-oxygen-level-dependent (BOLD) signals in the brain to assess the brain’s intrinsic connectivity and capture dynamic changes in the brain. In this study, the hidden Markov model (HMM) and dynamic graph (DG) theory are used to study the spatial-temporal characteristics and dynamics of brain networks based on dynamic functional connectivity (DFC). By using HMM, we identified three typical brain states for ASD and healthy control (HC). Furthermore, we explored the correlation between HMM time-varying properties and clinical autism scale scores. Differences in brain topological characteristics and dynamics between ASD and HC were compared by DG analysis. The experimental results indicate that ASD is more inclined to enter a strongly connected HMM brain state, leading to the isolation of brain networks and alterations in the topological characteristics of brain networks, such as default mode network (DMN), ventral attention network (VAN), and visual network (VN). This work suggests that using different data-driven methods based on DFC to study brain network dynamics would have better information complementarity, which can provide a new direction for the extraction of neuro-biomarkers in the early diagnosis of ASD. Full article

Background: A fundamental grasp of the variability observed in healthy individuals holds paramount importance in the investigation of neuropsychiatric conditions characterized by sex-related phenotypic distinctions. Functional magnetic resonance imaging (fMRI) serves as a meaningful tool for discerning these differences. Among deep learning models, graph neural networks (GNNs) are particularly well-suited for analyzing brain networks derived from fMRI blood oxygen level-dependent (BOLD) signals, enabling the effective exploration of sex differences during adolescence. Method: In the present study, we introduce a multi-modal graph isomorphism network (MGIN) designed to elucidate sex-based disparities using fMRI task-related data. Our approach amalgamates brain networks obtained from multiple scans of the same individual, thereby enhancing predictive capabilities and feature identification. The MGIN model adeptly pinpoints crucial subnetworks both within and between multi-task fMRI datasets. Moreover, it offers interpretability through the utilization of GNNExplainer, which identifies pivotal sub-network graph structures contributing significantly to sex group classification. Results: Our findings indicate that the MGIN model outperforms competing models in terms of classification accuracy, underscoring the benefits of combining two fMRI paradigms. Additionally, our model discerns the most significant sex-related functional networks, encompassing the default mode network (DMN), visual (VIS) network, cognitive (CNG) network, frontal (FRNT) network, salience (SAL) network, subcortical (SUB) network, and sensorimotor (SM) network associated with hand and mouth movements. Remarkably, the MGIN model achieves superior sex classification accuracy when juxtaposed with other state-of-the-art algorithms, yielding a noteworthy 81.67% improvement in classification accuracy. Conclusion: Our model’s superiority emanates from its capacity to consolidate data from multiple scans of subjects within a proven interpretable framework. Beyond its classification prowess, our model guides our comprehension of neurodevelopment during adolescence by identifying critical subnetworks of functional connectivity. Full article

Fibromyalgia syndrome (FM) is a chronic pain condition that affects a significant portion of the population; yet, this condition is still poorly understood. Prior research has suggested that individuals with FM display a heightened sensitivity to pain and signs of autonomic dysfunction. Recent advances in functional MRI analysis methods to model blood-oxygenation-level-dependent (BOLD) responses across networks of regions, and structural and physiological modeling (SAPM) have shown the potential to provide more detailed information about altered neural activity than was previously possible. Therefore, this study aimed to apply novel analysis methods to investigate altered neural processes underlying pain sensitivity in FM in functional magnetic resonance imaging (fMRI) data from the brainstem and spinal cord. Prior fMRI studies have shown evidence of functional differences in fibromyalgia (FM) within brain regions associated with pain’s motivational aspects, as well as differences in neural activity related to pain regulation, arousal, and autonomic homeostatic regulation within the brainstem and spinal cord regions. We, therefore, hypothesized that nociceptive processing is altered in FM compared to healthy controls (HCs) in the brainstem and spinal cord areas linked to autonomic function and descending pain regulation, including the parabrachial nuclei (PBN) and nucleus tractus solitarius (NTS). We expected that new details of this altered neural signaling would be revealed with SAPM. The results provide new evidence of altered neural signaling in FM related to arousal and autonomic homeostatic regulation. This further advances our understanding of the altered neural processing that occurs in women with FM. Full article