Phasic perfusion dynamics among migraine subtypes: a multimodel arterial spin labeling investigation.

BACKGROUND: Migraine-related perfusion changes are documented but inconsistent across studies due to limited sample size and insufficient phenotyping. The phasic and spatial dynamics across migraine subtypes remains poorly characterized. This study aimed to determine spatiotemporal dynamics of gray matter (GM) perfusion in migraine. METHODS: We prospectively recruited episodic (EM) and chronic migraine (CM) patients, diagnosed with the International Headache Society criteria and healthy controls (HCs) between 2021 and 2023 from the headache center in a tertiary medical center, and adjacent communities. Magnetic resonance (3-tesla) arterial spin labeling (ASL) was conducted for whole brain cerebral blood flow (CBF) in all participants. The voxel-wise and whole brain gray matter (GM) CBF were compared between subgroups. Spatial pattern analysis of CBF and its correlations with headache frequency were investigated regarding different migraine phases and subtypes. Sex- and age-adjusted voxel-wise and whole brain GM comparisons were performed between HCs and different EM and CM phases. Spatial pattern analysis was conducted by CBF clusters with phasic differences and spin permutation test. Correlations between headache frequency and CBF were investigated regarding different EM and CM phases. RESULTS: Totally 344 subjects (172 EM, 120 CM, and 52 HCs) were enrolled. Higher CBF in different anatomical locations was identified in ictal EM and CM. The combined panels of the specific locations with altered CBF in ictal EM on receiver operating characteristic curve analysis demonstrated areas under curve of 0.780 (vs. HCs) and 0.811 (vs. preictal EM). The spatial distribution of ictal-interictal CBF alteration of EM and CM were not correlated with each other (p = 0.665; r = - 0.018). Positive correlations between headache frequency and CBF were noted in ictal EM and CM regarding whole GM and specific anatomical locations. CONCLUSIONS: Patients with migraine exhibited unique spatiotemporal CBF dynamics across different phases and distinct between subtypes. The findings provide neurobiological insights into how selected anatomical structures engage in a migraine attack and adapt to plastic change of repeated attacks along with chronicity.

Association between gray matter regional structural-functional connectivity couplings and visual memory in major depressive disorder.

Alterations in structural-functional (SC-FC) coupling have been linked to major depressive disorder (MDD). A newly developed algorithm for regional-specific SC-FC coupling analysis shows potential in advancing psychiatric research. In this study, we calculated the gray matter regional-specific SC-FC coupling of 114 MDD patients and 131 healthy controls (HCs). The delayed matching to sample (DMS) and Pattern Recognition Memory (PRM) subtests of the computerized Cambridge Neurocognitive Test Automated Battery (CANTAB) were used to evaluate visual memory. We found that the Xgboost model exhibited robust discriminative performance (Area under the ROC curve [95% CI]: 0.75 [0.65 to 0.85], Accuracy [95% CI]: 0.73 [0.63 to 0.84], Sensitivity [95% CI]: 0.65 [0.53 to 0.76], Specificity [95% CI]: 0.82 [0.77 to 0.87]). MDD patients showed lower SC-FC coupling in the left inferior frontal orbital gyrus (IFGorb_L) and the right inferior occipital gyrus (IOG_R) and higher SC-FC coupling in the left superior temporal pole (TPOsup_L) and the right middle temporal pole (TPOmid_R) than HCs. SC-FC coupling of IFGorb_L negatively correlated with current duration of illness (r = -0.26, P = 0.007), IOG_R negatively correlated with HAMD-17 cognitive factor score (r = -0.24, P = 0.011), while TPOsup_L positively correlated with percent correct in PRM delayed task among MDD patients (r = 0.31, P = 0.003). In conclusion, the study suggested that altered regional SC-FC coupling may be involved in MDD pathophysiology and associated with visual memory impairment.

Diffusion tensor imaging and gray matter volumetry to evaluate cerebral remodeling processes after a pure motor stroke: a longitudinal study.

BACKGROUND AND OBJECTIVES: Clinical factors are not sufficient to fix a prognosis of recovery after stroke. Pyramidal tract or alternate motor fiber (aMF: reticulo-, rubrospinal pathways and transcallosal fibers) integrity and remodeling processes assessable by diffusion tensor MRI (DTI) and voxel-based morphometry (VBM) may be of interest. The primary objective was to study longitudinal cortical brain changes using VBM and longitudinal corticospinal tract changes using DTI during the first 4 months after lacunar cerebral infarction. The second objective was to determine which changes were correlated to clinical improvement. METHODS: Twenty-one patients with deep brain ischemic infarct with pure motor deficit (NIHSS score ≥ 2) were recruited at Purpan Hospital and included. Motor deficit was measured [Nine peg hole test (NPHT), dynamometer (DYN), Hand-Tapping Test (HTT)], and a 3T MRI scan (VBM and DTI) was performed during the acute and subacute phases. RESULTS: White matter changes: corticospinal fractional anisotropy (FACST) was significantly reduced at follow-up (approximately 4 months) on the lesion side. FAr (FA ratio in affected/unaffected hemispheres) in the corona radiata was correlated to the motor performance at the NPHT, DYN, and HTT at follow-up. The presence of aMFs was not associated with the extent of recovery. Grey matter changes: VBM showed significant increased cortical thickness in the ipsilesional premotor cortex at follow-up. VBM changes in the anterior cingulum positively correlated with improvement in motor measures between baseline and follow-up. DISCUSSION: To our knowledge, this study is original because is a longitudinal study combining VBM and DTI during the first 4 months after stroke in a series of patients selected on pure motor deficit. Our data would suggest that good recovery relies on spared CST fibers, probably from the premotor cortex, rather than on the aMF in this group with mild motor deficit. The present study suggests that VBM and FACST could provide reliable biomarkers of post-stroke atrophy, reorganization, plasticity and recovery. GOV IDENTIFIER: NCT01862172, registered May 24, 2013.

Neural basis of fatigue in post-COVID syndrome and relationships with cognitive complaints and cognition.

The main objective was to evaluate structural and functional connectivity correlates of fatigue in post-COVID syndrome, and to investigate the relationships with an objective measure of mental fatigue and with subjective cognitive complaints. One-hundred and twenty-nine patients were recruited after 14.79 ± 7.17 months. Patients were evaluated with fatigue, neuropsychological, and subjective cognitive complaints assessments. Structural and functional magnetic resonance imaging were acquired, and functional connectivity, white matter diffusivity and grey matter volume were evaluated. Fatigue was present in 86 % of patients, and was highly correlated to subjective cognitive complaints. Fatigue was associated with structural and functional connectivity mostly in frontal areas but also temporal, and cerebellar areas, showing mental fatigue different pattern of functional connectivity correlates compared to physical fatigue. White matter diffusivity correlates were similar in fatigue and subjective cognitive complaints, located in the forceps minor, anterior corona radiata and anterior cingulum. Findings confirm that fatigue in post-COVID syndrome is related to cerebral connectivity patterns, evidencing its brain substrates. Moreover, results highlight the relationship between fatigue and subjective cognitive complaints. These findings point out the relevance of the multidisciplinary assessment of post-COVID syndrome patients with subjective cognitive complaints, in order to unravel the symptomatology beneath the patient's complaints.

Identification of high-functioning autism spectrum disorders based on gray-white matter functional network connectivity.

In the field of autism spectrum disorder (ASD), research on functional connectivity between gray matter and white matter remains under-researched. To address this gap, this study innovatively introduced a nested cross-validation method that integrates gray-white matter functional connectivity with an F-Score algorithm. This method calculates the correlation based on signals extracted from functional magnetic resonance imaging data using gray matter and white matter brain region templates. After applying the method to a New York University Langone Medical Center dataset consisting of 55 individuals with high-functioning ASD and 52 healthy subjects, we achieved a classification accuracy of 72.94%. This study found abnormal functional connectivity, primarily involving the left anterior prefrontal cortex and right superior corona radiata, left retrosplenial cortex and left superior corona radiata, as well as the left ventral anterior cingulate cortex and body of corpus callosum. Besides, we discovered that these abnormal connections are closely related to social impairment and restrictive and repetitive behaviors in ASD. In conclusion, this study provides a gray-white matter functional connectivity perspective for the diagnosis and understanding of ASD.

Functional and structural abnormalities of thalamus in individuals at early stage of schizophrenia.

BACKGROUND: Thalamic abnormalities in schizophrenia are recognized, alongside cognitive deficits. However, the current findings about these abnormalities during the prodromal period remain relatively few and inconsistent. This study applied multimodal methods to explore the alterations in thalamic function and structure and their relationship with cognitive function in first-episode schizophrenia (FES) patients and ultra-high-risk (UHR) individuals, aiming to affirm the thalamus's role in schizophrenia development and cognitive deficits. METHODS: 75 FES patients, 60 UHR individuals, and 60 healthy controls (HC) were recruited. Among the three groups, gray matter volume (GMV) and functional connectivity (FC) were evaluated to reflect the structural and functional abnormalities in the thalamus. Pearson correlation was used to calculate the association between these abnormalities and cognitive impairments. RESULTS: No significant difference in GMV of the thalamus was found among the abovementioned three groups. Compared with HC individuals, FES patients had decreased thalamocortical FC mostly in the thalamocortical triple network, including the default mode network (DMN), salience network (SN), and executive control network (ECN). UHR individuals had similar but milder dysconnectivity as the FES group. Furthermore, FC between the left thalamus and right putamen was significantly correlated with execution speed and attention in the FES group. CONCLUSIONS: Our findings revealed decreased thalamocortical FC associated with cognitive deficits in FES and UHR subjects. This improves our understanding of the functional alterations in thalamus in prodromal stage of schizophrenia and the related factors of the cognitive impairment of the disease. TRIAL REGISTRATION: ClinicalTrials.govNCT03965598; https://clinicaltrials.gov/ct2/show/NCT03965598.

Altered Resting-State Brain Entropy in Cerebral Small Vessel Disease Patients with Cognitive Impairment.

Objective: Cerebral small vessel disease (CSVD) is a primary vascular disease of cognitive impairment. Previous studies have predominantly focused on brain linear features. However, the nonlinear measure, brain entropy (BEN), has not been elaborated. Thus, this study aims to investigate if BEN abnormalities could manifest in CSVD patients with cognitive impairment. Methods: Thirty-four CSVD patients with cognitive impairment and 37 healthy controls (HCs) were recruited. Analysis of gray matter approximate entropy (ApEn) and sample entropy (SampEn) which are two indices of BEN was calculated. To explore whether BEN can provide unique information, we further performed brain linear methods, namely, amplitude of low frequency fluctuation (ALFF) and regional homogeneity (ReHo), to observe their differences. The ratios of BEN/ALFF and BEN/ReHo which represent the coupling of nonlinear and linear features were introduced. Correlation analysis was conducted between imaging indices and cognition. Subsequently, the linear support vector machine (SVM) was used to assess their discriminative ability. Results: CSVD patients exhibited lower ApEn and SamEn values in sensorimotor areas, which were correlated with worse memory and executive function. In addition, the results of BEN showed little overlap with ALFF and ReHo in brain regions. Correlation analysis also revealed a relationship between the two ratios and cognition. SVM analysis using BEN and its ratios as features achieved an accuracy of 74.64% (sensitivity: 86.49%, specificity: 61.76%, and AUC: 0.82439). Conclusion: Our study reveals that the reduction of sensorimotor system complexity is correlated with cognition. BEN exhibits distinctive characteristics in brain activity. Combining BEN and the ratios can be new biomarkers to diagnose CSVD with cognitive impairment. Impact Statement Cerebral small vessel disease (CSVD) is regarded as the most important vascular disease of cognitive impairment. However, conventional brain imaging fails to adequately elucidate the pathogenesis of cognitive disorder related to CSVD. In this regard, exploring brain entropy (BEN) based on resting-state functional magnetic resonance imaging (rs-fMRI) represents a relatively novel and unexplored approach in the context of CSVD. This approach provides novel insights into the pathogenesis, diagnosis, and rehabilitation of cognitive disorder associated with CSVD.

Prolonged ventricular repolarization associated with mild cognitive impairment and white matter hyperintensities: a cross-sectional study.

Prolonged ventricular repolarization has been associated with cardiovascular disease. We sought to investigate the association of prolonged ventricular repolarization with mild cognitive impairment (MCI) and the potential underlying neuropathological mechanisms in older adults. This cross-sectional study included 4328 dementia-free participants (age ≥ 65 years; 56.8% female) in the baseline examination of the Multidomain INterventions to delay dementia and Disability in rural China; of these, 989 undertook structural brain magnetic resonance imaging (MRI) scans. QT, QTc, JT, JTc, and QRS intervals were derived from 12-lead electrocardiograph. MCI, amnestic MCI (aMCI), and non-amnestic MCI (naMCI) were defined following the Petersen's criteria. Volumes of gray matter (GM), white matter, cerebrospinal fluid, total white matter hyperintensities (WMH), periventricular WMH (PWMH), and deep WMH (DWMH) were automatically estimated. Data were analyzed using logistic and general linear regression models. Prolonged QT, QTc, JT, and JTc intervals were significantly associated with an increased likelihood of MCI and aMCI, but not naMCI (p < 0.05). In the MRI subsample, QT, QTc, JT, and JTc intervals were significantly associated with larger total WMH and PWMH volumes (p < 0.05), but not with DWMH volume. Statistical interactions were detected, such that prolonged QT and JT intervals were significantly associated with reduced GM volume only among participants with coronary heart disease or without APOE ε4 allele (p < 0.05). Prolonged ventricular repolarization is associated with MCI and cerebral microvascular lesions in a general population of older adults. This underlies the importance of cognitive assessments and brain MRI examination among older adults with prolonged QT interval.

Brain structural and functional abnormalities in affective network are associated with anxious depression.

BACKGROUND: Anxious depression (AD) is a common subtype of major depressive disorder (MDD). Neuroimaging studies of AD have revealed inconsistent and heterogeneous brain alterations with the use of single-model methods. Therefore, it is necessary to explore the pathogenesis of AD using multi-model imaging analyses to obtain more homogeneous and robust results. METHODS: One hundred and eighty-two patients with MDD and 64 matched healthy controls (HCs) were recruited. Voxel-based morphometry (VBM) was used to estimate the gray matter volume (GMV) of all subjects. The GMV differences between the AD and non-anxious depression (NAD) participants were used as regions of interest (ROIs) for subsequent resting state functional connectivity (rs-FC) analyses. Correlation analysis was used to evaluate the associations between clinical symptoms and abnormal function in specific brain areas. RESULTS: Decreased GMV in the medial frontal gyrus (MFG) and the superior frontal gyrus (SFG) was observed in the AD group compared to the NAD group. Taking the MFG and SFG as ROIs, the rs-FC analysis revealed decreased FC between the left SFG and left temporal pole and between the left SFG and right MFG in the AD group compared to the NAD group. Finally, the FC between the left SFG and left temporal pole was negatively correlated with HAMD-17 scores in the AD group. CONCLUSION: By combining the GMV and rs-FC models, this study revealed that structural and functional disruption of the affective network may be an important pathophysiology underlying AD. The structural impairment may serve as the foundation of the functional impairment.

COVID-19 is associated with changes in brain function and structure: A multimodal meta-analysis of neuroimaging studies.

The actual role of coronavirus disease 2019 (COVID-19) in brain damage has been increasingly reported, necessitating a meta-analysis to collate and summarize the inconsistent findings from functional imaging and voxel-based morphometry (VBM) studies. A comprehensive voxel-wise meta-analysis of the whole brain was conducted to identify alterations in functional activity and gray matter volume (GMV) between COVID-19 patients and healthy controls (HCs) by using Seed-based d Mapping software. We included 15 functional imaging studies (484 patients with COVID-19, 534 HCs) and 9 VBM studies (449 patients with COVID-19, 388 HCs) in the analysis. Overall, patients with COVID-19 exhibited decreased functional activity in the right superior temporal gyrus (STG) (extending to the right middle and inferior temporal gyrus, insula, and temporal pole [TP]), left insula, right orbitofrontal cortex (OFC) (extending to the right olfactory cortex), and left cerebellum compared to HCs. For VBM, patients with COVID-19, relative to HCs, showed decreased GMV in the bilateral anterior cingulate cortex/medial prefrontal cortex (extending to the bilateral OFC), and left cerebellum, and increased GMV in the bilateral amygdala (extending to the bilateral hippocampus, STG, TP, MTG, and right striatum). Moreover, overlapping analysis revealed that patients with COVID-19 exhibited both decreased functional activity and increased GMV in the right TP (extending to the right STG). The multimodal meta-analysis suggests that brain changes of function and structure in the temporal lobe, OFC and cerebellum, and functional or structural alterations in the insula and the limbic system in COVID-19. These findings contribute to a better understanding of the pathophysiology of brain alterations in COVID-19. SIGNIFICANCE STATEMENT: This first large-scale multimodal meta-analysis collates existing neuroimaging studies and provides voxel-wise functional and structural whole-brain abnormalities in COVID-19. Findings of this meta-analysis provide valuable insights into the dynamic brain changes (from infection to recovery) and offer further explanations for the pathophysiological basis of brain alterations in COVID-19.

Multiple cognition associated multimodal brain networks in major depressive disorder.

Major depressive disorder frequently leads to cognitive impairments, significantly affecting patients' quality of life. However, the neurobiological mechanisms underlying cognitive deficits remain unclear. This study aimed to explore multimodal imaging biomarkers associated with cognitive function in major depressive disorder. Five cognitive scores (sustained attention, visual recognition memory, pattern recognition memory, executive function, and working memory) were used as references to guide the fusion of gray matter volume and amplitude of the low frequency fluctuation. Social function was assessed after 2 yr. Linear regression analysis was performed to identify brain features that were associated with social function of patients with major depressive disorder. Finally, we included 131 major depressive disorder and 145 healthy controls. A multimodal frontal-insula-occipital network associated with sustained attention was found to be associated with social functioning in major depressive disorders. Analysis across different cognitive domains revealed that gray matter volume exhibited greater sensitivity to differences, while amplitude of the low frequency fluctuation consistently decreased in the right temporal-occipital-hippocampus circuit. The consistent functional changes across the 5 cognitive domains were related to symptom severity. Overall, these findings provide insights into biomarkers associated with multiple cognitive domains in major depressive disorder. These results may contribute to the development of effective treatment targeting cognitive deficits and social function.

Associations of Cerebral Blood Flow Patterns With Gray and White Matter Structure in Patients With Temporal Lobe Epilepsy.

BACKGROUND AND OBJECTIVES: Neuroimaging studies in patients with temporal lobe epilepsy (TLE) show widespread brain network alterations beyond the mesiotemporal lobe. Despite the critical role of the cerebrovascular system in maintaining whole-brain structure and function, changes in cerebral blood flow (CBF) remain incompletely understood in the disease. Here, we studied whole-brain perfusion and vascular network alterations in TLE and assessed its associations with gray and white matter compromises and various clinical variables. METHODS: We included individuals with and without pharmaco-resistant TLE who underwent multimodal 3T MRI, including arterial spin labelling, structural, and diffusion-weighted imaging. Using surface-based MRI mapping, we generated individualized cortico-subcortical profiles of perfusion, morphology, and microstructure. Linear models compared regional CBF in patients with controls and related alterations to morphological and microstructural metrics. We further probed interregional vascular networks in TLE, using graph theoretical CBF covariance analysis. The effects of disease duration were explored to better understand the progressive changes in perfusion. We assessed the utility of perfusion in separating patients with TLE from controls using supervised machine learning. RESULTS: Compared with control participants (n = 38; mean ± SD age 34.8 ± 9.3 years; 20 females), patients with TLE (n = 24; mean ± SD age 35.8 ± 10.6 years; 12 females) showed widespread CBF reductions predominantly in fronto-temporal regions (Cohen d -0.69, 95% CI -1.21 to -0.16), consistent in a subgroup of patients who remained seizure-free after surgical resection of the seizure focus. Parallel structural profiling and network-based models showed that cerebral hypoperfusion may be partially constrained by gray and white matter changes (8.11% reduction in Cohen d) and topologically segregated from whole-brain perfusion networks (area under the curve -0.17, p < 0.05). Negative effects of progressive disease duration further targeted regional CBF profiles in patients (r = -0.54, 95% CI -0.77 to -0.16). Perfusion-derived classifiers discriminated patients from controls with high accuracy (71% [70%-82%]). Findings were robust when controlling for several methodological confounds. DISCUSSION: Our multimodal findings provide insights into vascular contributions to TLE pathophysiology affecting and extending beyond mesiotemporal structures and highlight their clinical potential in epilepsy diagnosis. As our work was cross-sectional and based on a single site, it motivates future longitudinal studies to confirm progressive effects, ideally in a multicentric setting.

Bulimia nervosa selectively reshapes the structure and intrinsic function of anterior insula subregions associated with cognition-emotion integration.

BACKGROUND: Existing evidence suggests that anterior insula plays a crucial role in cognitive control and emotional regulation and is implicated in the onset and maintenance of bulimia nervosa (BN). However, it remains unclear how structural and functional abnormalities in specific subregions of anterior insula contribute to BN. METHODS: In this study, we analyzed structural MRI and resting-state functional MRI data from 54 BN patients and 56 healthy controls (HCs). We conducted voxel-based morphometry, amplitude of low frequency fluctuation (conventional band: 0.01-0.08 Hz, slow-5: 0.01-0.027 Hz) and seed-based whole-brain functional connectivity (FC) analysis of the anterior insula subregions for both groups. Additionally, we investigated the correlation between neuroimaging findings and clinical characteristics in the BN group. RESULTS: Our findings revealed that BN patients exhibited reduced gray matter volume in the right dorsal anterior insula (dAI) and bilateral ventral anterior insula (vAI) and demonstrated decreased ALFF in slow-5 band of bilateral dAI. The BN group also showed increased FC between bilateral dAI and precuneus or right superior frontal gyri which significantly correlated with the severity of BN or its key symptom. In addition, the decreased FC between bilateral vAI and anterior cingulate and paracingulate gyri and/or median cingulate and paracingulate gyri were both significantly correlated with the severity and its restrained eating behavior. CONCLUSIONS: Our findings further indicate that the functional separation of anterior insula subregions may underlie the pathophysiology of BN. Notably, the vAI associated with emotional processing may serve as a promising neuroimaging biomarker which could inform therapeutic strategy.

The functional and structural alterations in brain regions related to the fear network model in panic disorder: A resting-state fMRI and T1-weighted imaging study.

Abnormal functional connectivity (FC) within the fear network model (FNM) has been identified in panic disorder (PD) patients, but the specific local structural and functional properties, as well as effective connectivity (EC), remain poorly understood in PD. The purpose of this study was to investigate the structural and functional patterns of the FNM in PD. Magnetic resonance imaging data were collected from 33 PD patients and 35 healthy controls (HCs). Gray matter volume (GMV), degree centrality (DC), regional homogeneity (ReHo), and amplitude of low-frequency fluctuation (ALFF) were used to identify the structural and functional characteristics of brain regions within the FNM in PD. Subsequently, FC and EC of abnormal regions, based on local structural and functional features, and their correlation with clinical features were further examined. PD patients exhibited preserved GMV, ReHo, and ALFF in the brain regions of the FNM compared with HCs. However, increased DC in the bilateral amygdala was observed in PD patients. The amygdala and its subnuclei exhibited altered EC with rolandic operculum, insula, medial superior frontal gyrus, supramarginal gyrus, opercular part of inferior frontal gyrus, and superior temporal gyrus. Additionally, Hamilton Anxiety Scale score was positively correlated with EC from left lateral nuclei (dorsal portion) of amygdala to right rolandic operculum and left superior temporal gyrus. Our findings revealed a reorganized functional network in PD involving brain regions regulating exteroceptive-interoceptive signals, mood, and somatic symptoms. These results enhance our understanding of the neurobiological underpinnings of PD, suggesting potential biomarkers for diagnosis and targets for therapeutic intervention.

The interplay between insomnia symptoms and Alzheimer's disease across three main brain networks.

STUDY OBJECTIVES: Insomnia symptoms are prevalent along the trajectory of Alzheimer's disease (AD), but the neurobiological underpinning of their interaction is poorly understood. Here, we assessed structural and functional brain measures within and between the default mode network (DMN), salience network, and central executive network (CEN). METHODS: We selected 320 participants from the ADNI database and divided them by their diagnosis: cognitively normal (CN), Mild Cognitive Impairment (MCI), and AD, with and without self-reported insomnia symptoms. We measured the gray matter volume (GMV), structural covariance (SC), degrees centrality (DC), and functional connectivity (FC), testing the effect and interaction of insomnia symptoms and diagnosis on each index. Subsequently, we performed a within-group linear regression across each network and ROI. Finally, we correlated observed abnormalities with changes in cognitive and affective scores. RESULTS: Insomnia symptoms were associated with FC alterations across all groups. The AD group also demonstrated an interaction between insomnia and diagnosis. Within-group analyses revealed that in CN and MCI, insomnia symptoms were characterized by within-network hyperconnectivity, while in AD, within- and between-network hypoconnectivity was ubiquitous. SC and GMV alterations were nonsignificant in the presence of insomnia symptoms, and DC indices only showed network-level alterations in the CEN of AD individuals. Abnormal FC within and between DMN and CEN hubs was additionally associated with reduced cognitive function across all groups, and increased depressive symptoms in AD. CONCLUSIONS: We conclude that patients with clinical AD present with a unique pattern of insomnia-related functional alterations, highlighting the profound interaction between both conditions.

End-stage renal disease accompanied by mild cognitive impairment: A study and analysis of trimodal brain network fusion.

The function and structure of brain networks (BN) may undergo changes in patients with end-stage renal disease (ESRD), particularly in those accompanied by mild cognitive impairment (ESRDaMCI). Many existing methods for fusing BN focus on extracting interaction features between pairs of network nodes from each mode and combining them. This approach overlooks the correlation between different modal features during feature extraction and the potentially valuable information that may exist between more than two brain regions. To address this issue, we propose a model using a multi-head self-attention mechanism to fuse brain functional networks, white matter structural networks, and gray matter structural networks, which results in the construction of brain fusion networks (FBN). Initially, three networks are constructed: the brain function network, the white matter structure network, and the individual-based gray matter structure network. The multi-head self-attention mechanism is then applied to fuse the three types of networks, generating attention weights that are transformed into an optimized model. The optimized model introduces hypergraph popular regular term and L1 norm regular term, leading to the formation of FBN. Finally, FBN is employed in the diagnosis and prediction of ESRDaMCI to evaluate its classification performance and investigate the correlation between discriminative brain regions and cognitive dysfunction. Experimental results demonstrate that the optimal classification accuracy achieved is 92.80%, which is at least 3.63% higher than the accuracy attained using other methods. This outcome confirms the effectiveness of our proposed method. Additionally, the identification of brain regions significantly associated with scores on the Montreal cognitive assessment scale may shed light on the underlying pathogenesis of ESRDaMCI.

Cerebral Gray Matter May Not Explain Sleep Slow-Wave Characteristics after Severe Brain Injury.

Sleep slow waves are the hallmark of deeper non-rapid eye movement sleep. It is generally assumed that gray matter properties predict slow-wave density, morphology, and spectral power in healthy adults. Here, we tested the association between gray matter volume (GMV) and slow-wave characteristics in 27 patients with moderate-to-severe traumatic brain injury (TBI, 32.0 ± 12.2 years old, eight women) and compared that with 32 healthy controls (29.2 ± 11.5 years old, nine women). Participants underwent overnight polysomnography and cerebral MRI with a 3 Tesla scanner. A whole-brain voxel-wise analysis was performed to compare GMV between groups. Slow-wave density, morphology, and spectral power (0.4-6 Hz) were computed, and GMV was extracted from the thalamus, cingulate, insula, precuneus, and orbitofrontal cortex to test the relationship between slow waves and gray matter in regions implicated in the generation and/or propagation of slow waves. Compared with controls, TBI patients had significantly lower frontal and temporal GMV and exhibited a subtle decrease in slow-wave frequency. Moreover, higher GMV in the orbitofrontal cortex, insula, cingulate cortex, and precuneus was associated with higher slow-wave frequency and slope, but only in healthy controls. Higher orbitofrontal GMV was also associated with higher slow-wave density in healthy participants. While we observed the expected associations between GMV and slow-wave characteristics in healthy controls, no such associations were observed in the TBI group despite lower GMV. This finding challenges the presumed role of GMV in slow-wave generation and morphology.

Distinct grey and white matter changes are associated with the phenomenology of visual hallucinations in Lewy Body Disease.

Visual hallucinations in Lewy body disease (LBD) can be differentiated based on phenomenology into minor phenomena (MVH) and complex hallucinations (CVH). MVH include a variety of phenomena, such as illusions, presence and passage hallucinations occurring at early stages of LBD. The neural mechanisms of visual hallucinations are largely unknown. The hodotopic model posits that the hallucination state is due to abnormal activity in specialized visual areas, that occurs in the context of wider network connectivity alterations and that phenomenology of VH, including content and temporal characteristics, may help identify brain regions underpinning these phenomena. Here we investigated both the topological and hodological neural basis of visual hallucinations integrating grey and white matter imaging analyses. We studied LBD patients with VH and age matched healthy controls (HC). VH were assessed using a North-East-Visual-Hallucinations-Interview that captures phenomenological detail. Then we applied voxel-based morphometry and tract based spatial statistics approaches to identify grey and white matter changes. First, we compared LBD patients and HC. We found a reduced grey matter volume and a widespread damage of white tracts in LBD compared to HC. Then we tested the association between CVH and MVH and grey and white matter indices. We found that CVH duration was associated with decreased grey matter volume in the fusiform gyrus suggesting that LBD neurodegeneration-related abnormal activity in this area is responsible for CVH. An unexpected finding was that MVH severity was associated with a greater integrity of white matter tracts, specifically those connecting dorsal, ventral attention networks and visual areas. Our results suggest that networks underlying MVH need to be partly intact and functional for MVH experiences to occur, while CVH occur when cortical areas are damaged. The findings support the hodotopic view and the hypothesis that MVH and CVH relate to different neural mechanisms, with wider implications for the treatment of these symptoms in a clinical context.

Structural and functional neural patterns among sub-threshold bulimia nervosa: Abnormalities in dorsolateral prefrontal cortex and orbitofrontal cortex.

BACKGROUND: Disordered eating behaviors are prevalent among youngsters and highly associated with dysfunction in neurocognitive systems. We aimed to identify the potential changes in individuals with bulimia symptoms (sub-BN) to generate insights to understand developmental pathophysiology of bulimia nervosa. METHODS: We investigated group differences in terms of degree centrality (DC) and gray matter volume (GMV) among 145 undergraduates with bulimia symptoms and 140 matched control undergraduates, with the secondary analysis of the whole brain connectivity in these regions of interest showing differences in static functional connectivity (FC). RESULTS: The sub-BN group exhibited abnormalities of the right dorsolateral prefrontal cortex and right orbitofrontal cortex in both GMV and DC, and displayed decreased FC between these regions and the precuneus. We also observed that sub-BN presented with reduced FC between the calcarine and superior temporal gyrus, middle temporal gyrus and inferior parietal gyrus. Additionally, brain-behavioral associations suggest a distinct relationship between these FCs and psychopathological symptoms in sub-BN group. CONCLUSIONS: Our study demonstrated that individuals with bulimia symptoms present with aberrant neural patterns that mainly involved in cognitive control and reward processing, as well as attentional and self-referential processing, which could provide important insights into the pathology of BN.

Amygdala structural and functional reorganization as an indicator of affective dysfunction in patients with tinnitus.

The aim of this study was to systematically investigate structural and functional alterations in amygdala subregions using multimodal magnetic resonance imaging (MRI) in patients with tinnitus with or without affective dysfunction. Sixty patients with persistent tinnitus and 40 healthy controls (HCs) were recruited. Based on a questionnaire assessment, 26 and 34 patients were categorized into the tinnitus patients with affective dysfunction (TPAD) and tinnitus patients without affective dysfunction (TPWAD) groups, respectively. MRI-based measurements of gray matter volume, fractional anisotropy (FA), fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo), degree centrality (DC), and functional connectivity (FC) were conducted within 14 amygdala subregions for intergroup comparisons. Associations between the MRI properties and clinical characteristics were estimated via partial correlation analyses. Compared with that of the HCs, the TPAD and TPWAD groups exhibited significant structural and functional changes, including white matter integrity (WMI), fALFF, ReHo, DC, and FC alterations, with more pronounced WMI changes in the TPAD group, predominantly within the left auxiliary basal or basomedial nucleus (AB/BM), right central nucleus, right lateral nuclei (dorsal portion), and left lateral nuclei (ventral portion containing basolateral portions). Moreover, the TPAD group exhibited decreased FC between the left AB/BM and left middle occipital gyrus and right superior frontal gyrus (SFG), left basal nucleus and right SFG, and right lateral nuclei (intermediate portion) and right SFG. In combination, these amygdalar alterations exhibited a sensitivity of 65.4% and specificity of 96.9% in predicting affective dysfunction in patients with tinnitus. Although similar structural and functional amygdala remodeling were observed in the TPAD and TPWAD groups, the changes were more pronounced in the TPAD group. These changes mainly involved alterations in functionality and white matter microstructure in various amygdala subregions; in combination, these changes could serve as an imaging-based predictor of emotional disorders in patients with tinnitus.