Search

Abstract Background The therapeutic use of intermittent theta burst stimulation (iTBS) delivered to the left dorsolateral prefrontal cortex (LDLPFC) is a relatively new but promising treatment option for depression. There is a need for more knowledge on the mechanisms involved in its antidepressant effects. Methods This is a single-centre, prospective, randomized, double-blind, placebo-controlled trial with two arms, iTBS and sham iTBS. Adult outpatients with unipolar major depressive disorder of at least moderate severity will undergo cognitive assessment with an N-back task (0-back and 2-back), functional and structural magnetic resonance imaging and assessment of depression severity before and after brain stimulation. Neuronavigated iTBS or sham stimulation will be targeted at the LDPFC once a day for 10 consecutive workdays. ITBS will be delivered with the parameters 120% of resting motor threshold, triplet 50 Hz bursts repeated at 5 Hz; 2 s on and 8 s off, 600 pulses per session with a total duration of 3 min 9 s. The severity of depression will be measured with the Montogomery Aasberg Depression Rating Scale and the Beck Depression Inventory – second edition. In the iTBS group relative to sham, we expect significant antidepressant effects and improved N-back performance, associated with increased integrity in white matter tracts functionally connected with the LDLPFC and emotion regulation areas within the rostral anterior cingulate cortices, alongside potential increases in cortical thickness in these regions. On functional imaging, we expect to observe increased brain activity in the LDPFC during the performance of the N-back condition with higher cognitive load (2-back) in the iTBS group relative to sham. Discussion iTBS is a promising, time-efficient, and considered a safe treatment option for depression according to existing evidence. This trial aims to assess the neurocognitive impact of a 2-week, once-daily iTBS compared to sham iTBS, targeting the LDLPFC in depressed adult outpatients. The study investigates the relationships between changes in cerebral measures and cognitive performance on an N-back task in relation to the antidepressant effect following iTBS. This trial delves into the neurocognitive mechanisms of iTBS in depression, potentially offering novel scientific insights into its treatment effects and mechanisms of action. Trial registration ClinicalTrials.gov NCT06534684. Retrospectively registered on August 1st 2024.

Abstract Background New daily persistent headache (NDPH) is a rare primary headache disorder characterized by daily and persistent sudden onset headaches. Specific abnormalities in gray matter and white matter structure are associated with pain, but have not been well studied in NDPH. The objective of this work is to explore the fiber tracts and structural connectivity, which can help reveal unique gray and white matter structural abnormalities in NDPH. Methods The regional radiomics similarity networks were calculated from T1 weighted (T1w) MRI to depict the gray matter structure. The fiber connectivity matrices weighted by diffusion metrics like fractional anisotropy (FA), mean diffusivity (MD) and radial diffusivity (RD) were built, meanwhile the fiber tracts were segmented by anatomically-guided superficial fiber segmentation (Anat-SFSeg) method to explore the white matter structure from diffusion MRI. The considerable different neuroimaging features between NDPH and healthy controls (HC) were extracted from the connectivity and tract-based analyses. Finally, decision tree regression was used to predict the clinical scores (i.e. pain intensity) from the above neuroimaging features. Results T1w and diffusion MRI data were available in 51 participants after quality control: 22 patients with NDPH and 29 HCs. Significantly decreased morphological similarity was found between the right superior frontal gyrus and right hippocampus. The superficial white matter (SWM) showed significantly decreased FA in fiber tracts including the right superficial-frontal, left superficial-occipital, bilateral superficial-occipital-temporal (Sup-OT) and right superficial-temporal, meanwhile significant increased RD was found in the left Sup-OT. For the fiber connectivity, NDPH showed significantly decreased FA in the bilateral basal ganglion and temporal lobe, increased MD in the right frontal lobe, and increased RD in the right frontal lobe and left temporal-occipital lobe. Clinical scores could be predicted dominantly by the above significantly different neuroimaging features through decision tree regression. Conclusions Our research indicates the structural abnormalities of SWM and the neural pathways projected between regions like right hippocampus and left caudate nucleus, along with morphological similarity changes between the right superior frontal gyrus and right hippocampus, constitute the pathological features of NDPH. The decision tree regression demonstrates correlations between these structural changes and clinical scores.

Abstract Chemical exchange saturation transfer (CEST) imaging may provide novel contrast for the diagnosis, prognosis, and monitoring of the progression or treatment of neurological applications. However, the reproducibility of prominent CEST contrasts like amide CEST and nuclear Overhauser enhancement (NOE) CEST must be characterized in healthy brain gray matter (GM) and white matter (GM) prior to clinical implementation. The objective of this study was to characterize the reproducibility of four different CEST contrasts in the healthy human brain. Using a 3T MRI scanner, two 3D CEST scans were acquired in 12 healthy subjects (7 females, mean age (± SD) 26 ± 4 years) approximately 10 days apart. Scan-rescan reproducibility was measured for four contrasts: amine/amide concentration-independent detection (AACID), Amide*, and inverse magnetization transfer ratio (MTRRex) contrast for amide and NOE. Reproducibility was evaluated between- and within-subjects using coefficients of variation (CV) and the percent difference between measurements. AACID and NOE-MTRRex contrasts demonstrated the lowest within-subject CVs (0.8–1.2% and 1.6-2.0%, respectively), between-subject CVs (1.2–2.1% and 3.4–4.2%, respectively), and percent difference (1.2–1.4% and 2.2–2.8%, respectively) for both GM and WM. AACID and NOE-MTRRex contrasts demonstrated the highest reproducibility and represented stable measurements suitable for characterizing changes in brain tissue caused by pathological processes.

Progressive multifocal leukoencephalopathy (PML) is a rare demyelinating disease of the central nervous system (CNS) due to John Cunningham (JC) virus reactivation most often in immunocompromised patients. The brainstem and the anterior corpus callosum are uncommon locations for white matter lesions. We present a case of PML in a 40-year-old female presenting to the emergency department for a tonic seizure with transient postictal confusion. The inpatient workup revealed low cluster of differentiation cell counts (CD3 and CD4), transaminitis, positive drug screen, and abnormal electroencephalogram (EEG). The computed tomogram (CT) of the head and magnetic resonance image (MRI or MR) of the brain showed evidence of subcortical and periventricular white matter lesions in the right hemisphere extending into the brainstem and the left frontal lobe. The hospital course consisted of supportive measures, seizure treatment along with prophylaxis, and human immunodeficiency virus (HIV) management along with prophylactic antibiotics. The patient was discharged with appropriate medications and outpatient referrals. Overall, this case describes some key points. It highlights particular imaging characteristics of PML in the setting of inadequately treated HIV. For example, white matter lesions cross the anterior corpus callosum rather than the splenium, as in the “barbell” sign. In addition, the lesions extend inferiorly along the ipsilateral corticospinal tract into the midbrain and pons. This could be one of the first cases to capture both of these features given the rarity of their concomitant occurrence.

Abstract Aging is the greatest known risk factor for most neurodegenerative diseases. Myelin degeneration is an early pathological indicator of these diseases and a normal part of aging; albeit, to a lesser extent. Despite this, little is known about the contribution of age-related myelin degeneration on neurodegenerative disease. Microglia participate in modulating white matter events from demyelination to remyelination, including regulation of (de)myelination by the microglial innate immune receptor triggering receptor expressed on myeloid cells 2 (TREM2). Here, we demonstrate Trem2-deficiency aggravates and accelerates age-related myelin degeneration in the striatum. We show TREM2 is necessary for remyelination by recruiting reparative glia and mediating signaling that promotes OPC differentiation/maturation. In response to demyelination, TREM2 is required for phagocytosis of large volumes of myelin debris. In addition to lysosomal regulation, we show TREM2 can modify the ER stress response, even prior to overt myelin debris, that prevents lipid accumulation and microglial dysfunction. These data support a role for Trem2-dependent interactions in age-related myelin degeneration and suggest a basis for how early dysfunctional microglia could contribute to disease pathology through insufficent repair, defective phagocytosis, and the ER stress response.

Abstract Parkinson’s disease (PD) is a movement-related neurological condition caused by the death of brain nerve cells that produce dopamine. T1 MR images were obtained from the Parkinson’s Progression Markers Initiative (PPMI) database. Data was collected at baseline, and at 48 months duration. SPM12 software was used to segment gray matter (GM) and white matter (WM) from the MR images. For the classification of PD, CNN and machine learning (ML) classifiers were used to train on the segmented GM and WM. The findings demonstrated that utilizing the segmented GM and WM obtained from MR images at 48 months had a better predictive ability than the data obtainment at the baseline. CNNs did not perform as well as the conventional ML algorithms, especially for the baseline data. This result is most likely due to the smaller dataset available for training the CNNs, as CNNs normally require more data for best performance. Overall, machine learning algorithms were able to distinguish between people with Parkinson’s disease and healthy controls by analyzing GM and WM in brain scans. The classifiers trained at different stages demonstrated varying degrees of accuracy, with the predictive accuracy for the 48-month dataset surpassing that of the baseline data by a significant margin. The accuracy rate for GM was 65.78% at baseline and improved significantly to 92.59% at 48 months. Similarly, the accuracy rate for WM was 60.52% at baseline and improved to 88.89% at 48 months.

Background: Alcohol-related brain degeneration (ARBD) is associated with cognitive–motor impairments that can progress to disability and dementia. White matter (WM) is prominently targeted in ARBD due to chronic neurotoxic and degenerative effects on oligodendrocytes and myelin. Early detection and monitoring of WM pathology in ARBD could lead to therapeutic interventions. Objective: This study examines the potential utility of a non-invasive strategy for detecting WM ARBD using exosomes isolated from serum. Comparative analyses were made with paired tissue (Tx) and membrane vesicles (MVs) from the temporal lobe (TL). Methods: Long Evans rats were fed for 8 weeks with isocaloric liquid diets containing 37% or 0% caloric ethanol (n = 8/group). TL-Tx, TL-MVs, and serum exosomes (S-EVs) were used to examine ethanol’s effects on oligodendrocyte glycoprotein, astrocyte, and oxidative stress markers. Results: Ethanol significantly decreased the TL-Tx expression of platelet-derived growth factor receptor alpha (PDGFRA), 2′,3′-cyclic nucleotide 3′ phosphodiesterase (CNPase), proteolipid protein (PLP), myelin oligodendrocyte glycoprotein (MOG), glial fibrillary acidic protein (GFAP), and 8-OHdG, whereas in the TL-MVs, ethanol increased CNPase, PDGFRA, and 8-OHdG, but decreased MOG and GFAP concordantly with TL-Tx. Ethanol modulated the S-EV expression by reducing PLP, nestin, GFAP, and 4-hydroxynonenal (HNE). Conclusion: Chronic ethanol exposures differentially alter the expression of oligodendrocyte/myelin, astrocyte, and oxidative stress markers in the brain, brain MVs, and S-EVs. However, directionally concordant effects across all three compartments were limited. Future studies should advance these efforts by characterizing the relationship between ABRD and molecular pathological changes in brain WM-specific exosomes in serum.

Background: Diffuse astrocytomas preferentially infiltrate eloquent areas affecting the outcome. A preoperative understanding of isocitrate dehydrogenase (IDH) status may offer opportunities for specific targeted therapies impacting treatment management. The aim of this study was to analyze clinical, topographical, radiological in WHO 2 astrocytomas with different IDH status and the long-term patient’s outcome. Methods: A series of confirmed WHO 2 astrocytoma patients (between 2005 and 2015) were retrospectively analyzed. MRI sequences (FLAIR) were used for tumor volume segmentation and to create a frequency map of their locations into the Montreal Neurological Institute (MNI) space. The Brain-Grid (BG) system (standardized radiological tool of intersected lines according to anatomical landmarks) was used as an overlay for infiltration analysis of each tumor. Long-term follow-up was used to perform a survival analysis. Results: Forty patients with confirmed IDH status (26 IDH-mutant, IDHm/14 IDH-wild type, IDHwt) according to WHO 2021 classification were included with a mean follow-up of 7.8 years. IDHm astrocytomas displayed a lower number of BG-voxels (P < 0.05) and were preferentially located in the anterior insular region. IDHwt group displayed a posterior insular and peritrigonal location. IDHwt group displayed a shorter OS compared with IDHm (P < 0.05), with the infiltration of 7 or more BG-voxels as an independent factor predicting a shorter OS. Conclusions: IDHm and IDHwt astrocytomas differed in preferential location, number of BG-voxels and OS at long follow-up time. The number of BG-voxels affected the OS in IDHwt was possibly reflecting higher tumor invasiveness. We encourage the systematic use of alternative observational tools, such as gradient maps and the Brain-Grid analysis, to better detect differences of tumor invasiveness in diffuse low-grade gliomas subtypes.

Objectives: A body of evidence suggests that individuals with diabetes face an elevated susceptibility to developing Alzheimer's disease when compared to the general populace. Prior research has indicated the potential of metformin to confer a protective influence in postponing dementia onset among diabetic patients. Nevertheless, data are scarce regarding the impact of metformin on microstructural alterations. The primary objective of this study is to explore the influence of metformin on white matter microstructural change in non-demented individuals with diabetes.Methods: We entered 113 non-demented diabetic subjects including 77 mild cognitive impairment (MCI), and 36 cognitively healthy individuals from Alzheimer's disease Neuroimaging Initiative (ADNI) which were then categorized as metformin users and non-users. We used the ANCOVA model to measure the association between metformin use and DTI values.Results: Results of the univariate model indicate that metformin users had a higher FA value left hippocampal cingulum (p = 0.003) and right internal capsule (p = 0.004). Moreover, the MD value of the right inferior frontal-occipital fasciculus was lower in those who used metformin compared to those not use it (p = 0.027).Conclusion: Our results revealed that metformin has protective effects on brain microstructural changes in elderly individuals with diabetes who do not exhibit signs of dementia. A comparison of the groups yielded compelling evidence of reduced neurodegeneration among those utilizing metformin.

Objectives: Alzheimer's disease (AD) represents a significant public health challenge, particularly as its prevalence is projected to rise sharply. Aspirin, known for its anti-inflammatory and antiplatelet properties, has been hypothesized to affect AD progression, although findings from observational studies and clinical trials remain inconsistent.Methods: This study utilized data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to investigate the potential association between aspirin use and white matter (WM) microstructural changes in a cohort of 148 mild cognitive impairment (MCI) subjects. Diffusion tensor imaging (DTI) was employed to assess WM integrity, with fractional anisotropy (FA) and diffusivity metrics serving as primary outcomes. Statistical analyses were conducted using ANCOVA, adjusting for age, sex, APOE ε4 genotype, and MMSE score.Results: Aspirin users exhibited significantly higher FA values in the anterior corona radiata and left external capsule, alongside lower axial and radial diffusivity values in the right cingulum, indicating better-preserved WM microstructure compared to non-users.Conclusion: These findings suggest that aspirin may confer neuroprotective effects on WM in early AD, potentially delaying cognitive decline. Further research is warranted to confirm these results and explore the underlying mechanisms. Aspirin is widely prescribed to millions of adults, yet its impact on WM regions in the brain remains largely unclear. Further research is necessary to replicate these findings and to assess whether the effects of aspirin on WM structure could contribute to delaying or preventing cognitive decline.

Abstract Glioma, a predominant type of brain tumor, can be fatal. This necessitates an early diagnosis and effective treatment strategies. Current diagnosis is based on biopsy, prompting the need for non invasive neuroimaging alternatives. Diffusion tensor imaging (DTI) is a promising method for studying the pathophysiological impact of tumors on white matter (WM) tissue. Single-shell DTI studies in brain glioma patients have not accounted for free water (FW) contamination due to tumors. This study aimed to (a) assess the efficacy of a two-compartment DTI model that accounts for FW contamination and (b) identify DTI-based biomarkers to classify low-grade glioma (LGG) and high-grade glioma (HGG) patients. DTI data from 86 patients (LGG n = 39, HGG n = 47) were obtained using a routine clinical imaging protocol. DTI metrics of tumorous regions and normal-appearing white matter (NAWM) were evaluated. Advanced stacked-based ensemble learning was employed to classify LGG and HGG patients using both single- and two-compartment DTI model measures. The DTI metrics of the two-compartment model outperformed those of the standard single-compartment DTI model in terms of sensitivity, specificity, and area under the curve of receiver operating characteristic (AUC-ROC) score in classifying LGG and HGG patients. Four features (out of 16 features), namely fractional anisotropy (FA) of the edema and core region and FA and mean diffusivity of the NAWM region, showed superior performance (sensitivity = 92%, specificity = 90%, and AUC-ROC = 90%) in classifying LGG and HGG. This demonstrates that both tumorous and NAWM regions may be differentially affected in LGG and HGG patients. Our results demonstrate the significance of using a two-compartment DTI model that accounts for FW contamination by improving diagnostic accuracy. This improvement may eventually aid in planning treatment strategies for glioma patients.

Abstract Background This study aimed to investigate the long-term effects of repetitive mild traumatic brain injury (rmTBI) with varying inter-injury intervals by measuring diffusion tensor metrics, including mean diffusivity (MD), fractional anisotropy (FA), and diffusion magnitude (L) and pure anisotropy (q). Methods Eighteen rats were randomly divided into three groups: short-interval rmTBI (n = 6), long-interval rmTBI (n = 6), and sham controls (n = 6). MD, FA, L, and q values were analyzed from longitudinal diffusion tensor imaging at days 50 and 90 after rmTBI. Immunohistochemical staining against neurons, astrocytes, microglia, and myelin was performed. Analysis of variance, Pearson correlation coefficient, and simple linear regression model were used. Results At day 50 post-rmTBI, lower cortical FA and q values were shown in the short-interval group (p ≤ 0.038). In contrast, higher FA and q values were shown for the long-interval group (p ≤ 0.039) in the corpus callosum. In the ipsilesional external capsule and internal capsule, no significant changes were found in FA, while lower L and q values were shown in the short-interval group (p ≤ 0.028) at day 90. The q values in the external capsule and internal capsule were negatively correlated with the number of microglial cells and the total number of astroglial cells (p ≤ 0.035). Conclusion Tensor scalar measurements, such as L and q values, are sensitive to exacerbated chronic injury induced by rmTBI with shorter inter-injury intervals and reflect long-term astrogliosis induced by the cumulative injury. Relevance statement Tensor scalar measurements, including L and q values, are potential DTI metrics for detecting long-term and subtle injury following rmTBI; in particular, q values may be used for quantifying remote white matter (WM) changes following rmTBI. Key Points The alteration of L and q values was demonstrated after chronic repetitive mild traumatic brain injury. Changing q values were observed in the impact site and remote WM. The lower q values in the remote WM were associated with astrogliosis. Graphical Abstract

Abstract Background Multiple sclerosis (MS) is an irreversible progressive CNS pathology characterized by the loss of myelin (i.e. demyelination). The lack of myelin is followed by a progressive neurodegeneration triggering symptoms as diverse as fatigue, motor, locomotor and sensory impairments and/or bladder, cardiac and respiratory dysfunction. Even though there are more than fourteen approved treatments for reducing MS progression, there are still no cure for the disease. Thus, MS research is a very active field and therefore we count with different experimental animal models for studying mechanisms of demyelination and myelin repair, however, we still lack a preclinical MS model assembling demyelination mechanisms with relevant clinical-like signs. Results Here, by inducing the simultaneous demyelination of both callosal and cerebellar white matter fibers by the double-site injection of lysolecithin (LPC), we were able to reproduce CNS demyelination, astrocyte recruitment and increases levels of proinflammatory cytokines levels along with motor, locomotor and urinary impairment, as well as cardiac and respiratory dysfunction, in the same animal model. Single site LPC-injections either in corpus callosum or cerebellum only, fails in to reproduce such a complete range of MS-like signs. Conclusion We here report that the double-site LPC injections treatment evoke a complex MS-like mice model. We hope that this experimental approach will help to deepen our knowledge about the mechanisms of demyelinated diseases such as MS.

Abstract Background To investigate the association between white matter changes and ventricular expansion in idiopathic normal pressure hydrocephalus (iNPH) based on diffusion spectrum imaging (DSI). Methods We included 32 patients with iNPH who underwent DSI using a 3T MRI scanner. The lateral ventricles were manually segmented, and ventricular volumes were measured. Two methods were utilised in the study: manual region-of-interest (ROI) delineation and tract diffusion profile analysis. General fractional anisotropy (GFA) and fractional anisotropy (FA) were extracted in different white matter regions, including the bilateral internal capsule (anterior and posterior limbs) and corpus callosum (body, genu, and splenium) with manual ROI delineation. The 18 main tracts in the brain of each patient were extracted; the diffusion metrics of 100 equidistant nodes on each fibre were calculated, and Spearman’s correlation coefficient was used to determine the correlation between diffusion measures and ventricular volume of iNPH patients. Results The GFA and FA of all ROI showed no significant correlation with lateral ventricular volume. However, in the tract diffusion profile analysis, lateral ventricular volume was positively correlated with part of the cingulum bundle, left corticospinal tract, and bilateral thalamic radiation posterior, whereas it was negatively correlated with the bilateral cingulum parahippocampal (all p

ContextOlfactory dysfunction (OD) is a common early symptom of Parkinson’s disease (PD). However, OD is not specific to PD, as approximatively 20% of the general population exhibit different forms of OD. To use olfactory measures for early Parkinson screening, it is crucial to distinguish PD-related OD from Non-Parkinsonian OD (NPOD).Objectives and hypothesisThis study aimed to compare the structural changes associated with PD-related OD (n = 15) with NPOD (n = 15), focusing on gray matter volumes and white matter fiber integrity in chemosensory regions. We hypothesized that PD-related OD presents specific structural alterations in these regions.MethodsParticipants underwent a 3 T MRI scan, which included anatomical T1 and diffusion-weighted imaging. Gray and white matter integrity were assessed using both whole-brain analyses (voxel-based morphometry—VBM and tract-based spatial statistics—TBSS, respectively) and localized approaches, including regions of interest and tractography.ResultsPD patients exhibited significantly higher gray matter volume in the left insula using restricted regions-of-interest analyses, while no other significant gray or white matter differences were found between groups.ConclusionStructural imaging of the gray matter, particularly the insula, but not of white matter, differentiates PD-related OD from NPOD.

Background: Arbor vitae cerebelli (tree-like branching white matter of the cerebellum) has a complex spatial configuration that is challenging to assess using conventional morphometric methods. This study proposes a fractal approach to describe and quantify the anatomy of Arbor vitae cerebelli. For this purpose, a new “contour scaling” method for fractal analysis of cerebellar white matter was developed. Material and methods: The cerebella of 100 cadavers (50 male and 50 female) who died from causes unrelated to brain pathology, aged 20–95 years, were examined. Mid-sagittal sections of the cerebellar vermis were studied. The fractal dimension values of the cerebellar white matter were determined using both the developed fractal analysis method and the conventional “box counting” method, along with measurements of non-fractal parameters including cerebellar weight, area and perimeter of the vermis cross-section, perimeter-to-area ratio, and circularity. Results: Considering the cerebellar white matter as a tree-like fractal, it was found to have 7 or 8 primary branches, which subdivide into 10-18 second-iteration branches, 19–38 third-iteration branches, and 34–53 fourth-iteration branches. Females more often had 8 primary branches compared to males, while males had a greater number of branches in the second to fourth iterations. The mean fractal (Hausdorff) dimension was 1.697 (1.721 in males, 1.674 in females, P = 0.01). The fractal dimension correlated most strongly with the perimeter and area of the vermis cross-section and had no significant relationship with age. Conclusion: The fractal (Hausdorff) dimension, determined using the novel “contour scaling” method, quantitatively assesses the degree of branching of the cerebellar white matter. An increase in the absolute size of the cerebellum leads to a higher degree of branching of its white matter and an increase in the number of its constitutive components – white matter branches and folia.

IntroductionPreviously, we showed that omega-3 polyunsaturated fatty acid n-3 (PUFA) supplementation improved the performance of postpartum rats in the shuttle box escape test (SBET).MethodsThe brains of these rats were used in the current study which examined brain cytochrome c oxidase (CCO) activity in white matter bundles and 39 regions spanning sensorimotor, limbic, and cognitive areas to determine the effects of n-3 PUFAs on neural metabolic capacity and network interactions.ResultsWe found that n-3 PUFA supplementation decreased CCO activity in white matter bundles, deep and superficial areas within the inferior colliculus, the anterior and barrel field regions of the primary somatic sensorimotor cortex, the secondary somatic sensorimotor cortex, the lateral, anterior regions of the secondary visual cortex and the ventral posterior nucleus of the thalamus, and the medial nucleus of the amygdala. Structural equation modeling revealed that animals consuming diets without n-3 PUFAs exhibited fewer inter-regional interactions when compared to those fed diets with n-3 PUFAs. Without n-3 PUFAs, inter-regional interactions were observed between the posterior cingulate cortex and amygdala as well as among amygdala subregions. With n-3 PUFAs, more inter-regional interactions were observed, particularly between regions associated with fear memory processing and escape. Correlations between regional CCO activity and SBET behavior were observed in rats lacking dietary n-3 PUFAs but not in those supplemented with these nutrients.DiscussionIn conclusion, consumption of n-3 PUFAs results in reduced CCO activity in white matter bundles and sensorimotor regions, reflecting more efficient neurotransmission, and an increase in inter-regional interactions, facilitating escape from footshock.

ObjectiveMild cognitive impairment (MCI) is a common non-motor manifestation of Parkinson’s disease, commonly referred to as PD-MCI. However, there is a lack of comprehensive data regarding the role of glial cell line-derived neurotrophic factor (GDNF) and cerebral white matter damage in the pathogenesis of PD-MCI. The objective of this study is to investigate the association between alterations in GDNF levels and cerebral white matter damage in individuals diagnosed with PD-MCI, as well as to explore their potential involvement in cognitive progression.MethodsNeuropsychological assessments were conducted on 105 patients with Parkinson’s disease and 45 healthy volunteers to examine various cognitive domains. An enzyme-linked immunosorbent assay (ELISA) was employed to measure serum levels of GDNF. Additionally, all participants underwent 3.0T magnetic resonance imaging (MRI) to acquire diffusion tensor images (DTI), and a voxel-based analysis (VBA) approach was utilized to compare the fractional anisotropy (FA) values of white matter in the brain.ResultsThere was a significant correlation between the right corpus callosum, right cingulate gyrus, and the Digit Span Backward Test (DSB-T) as well as the Trail Making Test A (TMT-A), both of which assess attention and working memory functions. The left internal capsule exhibited a significant correlation with the Trail Making Test B (TMT-B) and the Clock Drawing Test (CDT), which evaluate executive function. Additionally, the right cingulate gyrus showed a significant association with scores on the Auditory Verbal Learning Test-HuaShan (AVLT-H), assessing memory function. Abnormal fiber structures that demonstrated significant correlations with serum GDNF levels included the left internal capsule, left corticospinal tract, right corpus callosum, and right cingulate gyrus.ConclusionThe decrease in serum GDNF levels among PD-MCI patients exhibiting impairments in attention and working memory function was significantly correlated with alterations in the corpus callosum (knee) and posterior cingulate gyrus. Furthermore, the reduction of serum GDNF levels in PD-MCI patients with impaired executive function is associated with changes in the internal capsule (forelimb) projection fibers. Additionally, the decline of serum GDNF levels in PD-MCI patients experiencing memory function impairment is related to alterations in the right cingulate gyrus.

BackgroundFunctional magnetic resonance imaging (fMRI) is widely used to depict neural activity and understand human brain function. Studies show that functional networks in gray matter undergo complex transformations from neonatal age to childhood, supporting rapid cognitive development. However, white matter functional networks, given the much weaker fMRI signal, have not been characterized until recently, and changes in white matter functional networks in the developing brain remain unclear.PurposeAims to examine and compare white matter functional networks in neonates and 8-year-old children.MethodsWe acquired resting-state fMRI data on 69 full-term healthy neonates and 38 healthy 8-year-old children using a same imaging protocol and studied their brain white matter functional networks using a similar pipeline. First, we utilized the ICA method to extract white matter functional networks. Next, we analyzed the characteristics of the white matter functional networks from both time-domain and frequency-domain perspectives, specifically, intra-network functional connectivity (intra-network FC), inter-network functional connectivity (inter-network FC), and fractional amplitude of low-frequency fluctuation (fALFF). Finally, the differences in the above functional networks’ characteristics between the two groups were evaluated. As a supplemental measure and to confirm with literature findings on gray matter functional network changes in the developing brain, we also studied and reported functional networks in gray matter.ResultsWhite matter functional networks in the developing brain can be depicted for both the neonates and the 8-year-old children. White matter intra-network FC within the optic radiations, corticospinal tract, and anterior corona radiata was lower in 8-year-old children compared to neonates (p

ObjectiveTo examine the impact of 40Hz gamma stimulation on the preservation of the corpus callosum, a critical structure for interhemispheric connectivity, in people with mild cognitive impairment or Alzheimer's disease.MethodsOVERTURE (NCT03556280) participants were randomized 2:1 (Active:Sham) to receive daily, 1-h, 40Hz gamma sensory stimulation or sham treatment for 6 months. Structural magnetic resonance imaging data were analyzed to assess changes in corpus callosum area (N = 50; 33 for active, 17 for sham). Bayesian linear mixed-effects modeling was used to assess differences in longitudinal changes of corpus callosum area between the two treatment groups.ResultsAll observed differences in corpus callosum area favored the active treatment group. Differences were observed in the total corpus callosum area (2.28 ± 0.87%, p < 0.02) and its subregions, including genu/rostrum (2.36 ± 0.90%, p < 0.02), anterior-body (2.64 ± 1.26%, p < 0.04), mid-body (2.79 ± 1.18%, p < 0.03), posterior-body (2.87 ± 1.41%, p < 0.05), and splenium (1.58 ± 0.73%, p < 0.04). Total corpus callosum area and some of the sub-regional differences, such as genu/rostrum and splenium, were observed as early as 3 months after commencement of treatment.InterpretationThe structural magnetic resonance imaging results from the OVERTURE Phase 2 study suggest that 6 months of non-invasive 40Hz stimulation reduces the rate of atrophy of the corpus callosum in individuals with Alzheimer's disease. The preservation of structural integrity in the corpus callosum, crucial for interhemispheric communication and cognitive function, may be achievable through this non-invasive approach, potentially providing a promising disease-modifying alternative in Alzheimer's disease management.

ObjectiveMild Cognitive Impairment (MCI) is a recognized precursor to Alzheimer’s Disease (AD), presenting a significant risk of progression. Early detection and intervention in MCI can potentially slow disease advancement, offering substantial clinical benefits. This study employed radiomics and machine learning methodologies to distinguish between MCI and Normal Cognition (NC) groups.MethodsThe study included 172 MCI patients and 183 healthy controls from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database, all of whom had 3D-T1 weighted MRI structural images. The cerebellar gray and white matter were segmented automatically using volBrain software, and radiomic features were extracted and screened through Pyradiomics. The screened features were then input into various machine learning models, including Random Forest (RF), Logistic Regression (LR), eXtreme Gradient Boosting (XGBoost), Support Vector Machines (SVM), K Nearest Neighbors (KNN), Extra Trees, Light Gradient Boosting Machine (LightGBM), and Multilayer Perceptron (MLP). Each model was optimized for penalty parameters through 5-fold cross-validation to construct radiomic models. The DeLong test was used to evaluate the performance of different models.ResultsThe LightGBM model, which utilizes a combination of cerebellar gray and white matter features (comprising eight gray matter and eight white matter features), emerges as the most effective model for radiomics feature analysis. The model demonstrates an Area Under the Curve (AUC) of 0.863 for the training set and 0.776 for the test set.ConclusionRadiomic features based on the cerebellar gray and white matter, combined with machine learning, can objectively diagnose MCI, which provides significant clinical value for assisted diagnosis.

Previously institutionalized adolescents show increased risk for psychopathology, though placement into high-quality foster care can partially mitigate this risk. White matter (WM) structure is associated with early institutional rearing and psychopathology in youth. Here we investigate associations between WM structure and psychopathology in previously institutionalized youth. Adolescent psychopathology data were collected using the MacArthur Health and Behavior Questionnaire. Participants underwent diffusion MRI, and data were processed using fixel-based analyses. General linear models investigated interactions between institutionalization groups and psychopathology on fixel metrics. Supplementary analyses also examined the main effects of psychopathology and institutionalization group on fixel metrics. Ever–Institutionalized children included 41 randomized to foster care (Mage=16.6), and 40 to care-as-usual (Mage=16.7)). In addition, 33 participants without a history of institutionalization were included as a reference group (Mage=16.9). Ever–Institutionalized adolescents displayed altered general psychopathology–fixel associations within the cerebellar peduncles, inferior longitudinal fasciculi, corticospinal tract, and corpus callosum, and altered externalizing–fixel associations within the cingulum and fornix. Our findings indicate brain–behavior associations reported in the literature may not be generalizable to all populations. Previously institutionalized youth may develop differential brain development, which in turn leads to altered neural correlates of psychopathology that are still apparent in adolescence.

Abstract Although white matter (WM) accounts for nearly half of adult brain, its wiring diagram is largely unknown. Here, an approach is developed to construct WM networks by estimating interregional morphological similarity based on structural magnetic resonance imaging. It is found that morphological WM networks showed nontrivial topology, presented good‐to‐excellent test‐retest reliability, accounted for phenotypic interindividual differences in cognition, and are under genetic control. Through integration with multimodal and multiscale data, it is further showed that morphological WM networks are able to predict the patterns of hamodynamic coherence, metabolic synchronization, gene co‐expression, and chemoarchitectonic covariance, and associated with structural connectivity. Moreover, the prediction followed WM functional connectomic hierarchy for the hamodynamic coherence, is related to genes enriched in the forebrain neuron development and differentiation for the gene co‐expression, and is associated with serotonergic system‐related receptors and transporters for the chemoarchitectonic covariance. Finally, applying this approach to multiple sclerosis and neuromyelitis optica spectrum disorders, it is found that both diseases exhibited morphological dysconnectivity, which are correlated with clinical variables of patients and are able to diagnose and differentiate the diseases. Altogether, these findings indicate that morphological WM networks provide a reliable and biologically meaningful means to explore WM architecture in health and disease.

Normal aging, though lacking widespread neurodegeneration, is nevertheless characterized by cognitive impairment in learning, memory, and executive function. The aged brain is spared from neuron loss, but white matter is lost and damage to myelin sheaths accumulates. This myelin damage is strongly associated with cognitive impairment. Although the cause of the myelin damage is not known, microglia dysregulation is a likely contributor. Immunologic proteins interact with microglial receptors to modulate microglia-mediated phagocytosis, which mediates myelin damage clearance and turn-over. Two such proteins, “eat me” signal C1q and “don’t eat me” signal CD47, act in opposition with microglia. Both C1q and CD47 have been implicated in Multiple Sclerosis, a demyelinating disease, but whether they play a role in age-related myelin pathology is currently unknown. The present study investigates C1q and CD47 in relation to age-related myelin degeneration using multilabel immunofluorescence, RNAscope, and confocal microscopy in the cingulum bundle of male and female rhesus monkeys across the lifespan. Our findings showed significant age-related elevation in C1q localized to myelin basic protein, and this increase is associated with more severe cognitive impairment. In contrast, CD47 localization to myelin decreased in middle age and oligodendrocyte expression of CD47 RNA decreased with age. Lastly, microglia reactivity increased with age in association with the changes in C1q and CD47. Together, these results suggest disruption in the balance of “eat me” and “don’t eat me” signals during normal aging, biasing microglia toward increased reactivity and phagocytosis of myelin, resulting in cognitive deficits.

Background: Age is one of the major risk factors for Alzheimer's disease (AD) which is considered the most common adult-onset dementia. There is little information about age-related changes during brain dementia. Methods: This study observed age-related variations in the brain throughout adulthood in magnetic resonance imaging (MRI) of the AD and healthy brains. The Open Access Series of Imaging Studies (OASIS) is used as a database. The method consists of design and develop a computer approach based on artificial intelligence (AI) to segment white matter (WM) from the MRI. Then, the number of pixels within the segmented white matter (WM) of the brain was calculated. Correlation was used to investigate age relation with WM changes in the normal and AD brain. Results: The WM change with aging was more correlated in AD group (rAD = −0.505, p-value = 0.0007) than control group (rControl = −0.357, p-value = 0.0001). Conclusion: Higher correlation of WM pixel counts with age in AD group approved that AD is characterized by the relevant involvement of the WM and age. Our approach gained additional information on the quantitative pathological changes associated with the AD as the most common brain disorder of the elderly.

White matter, a densely packed collection of myelinated axons, plays an essential part in neural networks. With high spatial resolution and deep penetration, multi-photon microscopy (MPM) is promising for white matter imaging in animal models in vivo. The third harmonic generation (THG) signal can be generated from white matter, but the bottom part of the white matter layer generates weak THG due to its high scattering. Here, we demonstrate an in vivo labeling and imaging technology, capable of visualizing the white matter layer in the mouse brain, combining fluorescence labeling with MitoTracker Red and three-photon fluorescence (3PF) microscopy excited at the 1700 nm window. 3PF signals are several times higher than THG signals, resulting in deeper imaging of the white matter layer with the former. Our results indicate that 3PF microscopy is a promising technology for white matter imaging in the deep brain in vivo.

Background: Offspring of parents with severe mental illness (e.g., bipolar disorder or schizophrenia) are at elevated risk of developing psychiatric illness owing to both genetic predisposition and increased burden of environmental stress. Emerging evidence indicates a disruption of brain network connectivity in young offspring of patients with bipolar disorder and schizophrenia, but the age trajectories of these brain networks in this high-familial-risk population remain to be elucidated. Methods: A total of 271 T1-weighted and diffusion-weighted scans were obtained from 174 offspring of at least 1 parent diagnosed with bipolar disorder (n = 74) or schizophrenia (n = 51) and offspring of parents without severe mental illness (n = 49). The age range was 8 to 23 years; 97 offspring underwent 2 scans. Anatomical brain networks were reconstructed into structural connectivity matrices. Network analysis was performed to investigate anatomical brain connectivity. Results: Offspring of parents with schizophrenia had differential trajectories of connectivity strength and clustering compared with offspring of parents with bipolar disorder and parents without severe mental illness, of global efficiency compared with offspring of parents without severe mental illness, and of local connectivity compared with offspring of parents with bipolar disorder. Conclusions: The findings of this study suggest that familial high risk of schizophrenia is related to deviations in age trajectories of global structural connectome properties and local connectivity strength.

Abstract Background Exploring the relationship between oxygen supply and myelin damage would benefit from a simultaneous quantification of myelin and cerebral blood flow (CBF) in the brain’s white matter (WM). To validate an analytical method for quantifying both CBF and myelin content in the WM using dynamic [11C]PiB positron emission tomography (PET). Methods A test-retest study was performed on eight healthy subjects who underwent two consecutive dynamic [11 C]PiB-PET scans. Three quantitative approaches were compared: simplified reference tissue model 2 (SRTM2), LOGAN graphical model, and standardized uptake value ratio (SUVR). The sensitivity of methods to the size of the region of interest was explored by simulating lesion masks obtained from 36 subjects with multiple sclerosis. Reproducibility was assessed using the relative difference and interclass correlation coefficient. Repeated measures correlations were used to test for cross-correlations between metrics. Results Among the CBF measures, the relative delivery (R1) of the simplified reference tissue model 2 (SRTM2) displayed the best reproducibility in the white matter, with a strong influence of the size of regions analyzed, the test-retest variability being below 10% for regions above 68 mm3 in the supratentorial white matter. [11C]PiB PET-derived proxies of CBF demonstrated lower perfusion of white matter compared to grey matter with an overall ratio equal to 1.71 ± 0.09 when the SRTM2-R1 was employed. Tissue binding in the white matter was well estimated by the Logan graphical model through estimation of the distribution volume ratio (LOGAN-DVR) and SRTM2 distribution volume ratio (SRTM2-DVR), with test-retest variability being below 10% for regions exceeding 106 mm3 for LOGAN-DVR and 300 mm3 for SRTM2-DVR. SRTM2-DVR provided a better contrast between white matter and grey matter. The interhemispheric variability was also dependent on the size of the region analyzed, being below 10% for regions above 103 mm3 for SRTM2-R1 and above 110 mm3 for LOGAN-DVR. Whereas the 1 to 8-minute standardized uptake value ratio (SUVR1-8) showed an intermediary reproducibility for CBF assessment, SUVR0-2 for perfusion or SUVR50-70 for tissue binding showed poor reproducibility and correlated only mildly with SRTM2-R1 and LOGAN-DVR estimations respectively. Conclusions [11C]PiB PET imaging can simultaneously quantify perfusion and myelin content in WM diseases associated with focal lesions. For longitudinal studies, SRTM2-R1 and DVR should be preferred over SUVR for the assessment of regional CBF and myelin content, respectively. Trial registration European Union Clinical Trials Register EUDRACT; EudraCT Number: 2008-004174-40; Date: 2009-03-06; https//www.clinicaltrialsregister.eu ; number 2008-004174-40.

Abstract Human brain experimental models recapitulating age- and disease-related characteristics are lacking. There is urgent need for human-specific tools that model the complex molecular and cellular interplay between different cell types to assess underlying disease mechanisms and test therapies. Here we present an adapted ex vivo organotypic slice culture method using human post-mortem brain tissue cultured at an air-liquid interface to also study brain white matter. We assessed whether these human post-mortem brain slices recapitulate the in vivo neuropathology and if they are suitable for pathophysiological, experimental and pre-clinical treatment development purposes, specifically regarding leukodystrophies. Human post-mortem brain tissue and cerebrospinal fluid were obtained from control, psychiatric and leukodystrophy donors. Slices were cultured up to six weeks, in culture medium with or without human cerebrospinal fluid. Human post-mortem organotypic brain slice cultures remained viable for at least six weeks ex vivo and maintained tissue structure and diversity of (neural) cell types. Supplementation with cerebrospinal fluid could improve slice recovery. Patient-derived organotypic slice cultures recapitulated and maintained known in vivo neuropathology. The cultures also showed physiologic multicellular responses to lysolecithin-induced demyelination ex vivo, indicating their suitability to study intrinsic repair mechanisms upon injury. The slice cultures were applicable for various experimental studies, as multi-electrode neuronal recordings. Finally, the cultures showed successful cell-type dependent transduction with gene therapy vectors. These human post-mortem organotypic brain slice cultures represent an adapted ex vivo model suitable for multifaceted studies of brain disease mechanisms, boosting translation from human ex vivo to in vivo. This model also allows for assessing potential treatment options, including gene therapy applications. Human post-mortem brain slice cultures are thus a valuable tool in preclinical research to study the pathomechanisms of a wide variety of brain diseases in living human tissue.

Abstract Background This study explores the impact of noise-induced hearing loss (NIHL) on the microstructural integrity of white matter tracts in the brain, focusing on areas involved in speech processing. While the primary impact of hearing loss occurs in the inner ear, these changes can extend to the central auditory pathways and have broader effects on brain function. Our research aimed to uncover the neural mechanisms underlying hearing loss-related deficits in speech perception and cognition among NIHL patients. Methods The study included two groups: nine bilateral NIHL patients and nine individuals with normal hearing. Advanced diffusion tensor imaging techniques were employed to assess changes in the white matter tracts. Regions of interest (ROIs), including the auditory cortex, cingulum, arcuate fasciculus, and longitudinal fasciculus, were examined. Fractional anisotropy (FA) values from these ROIs were extracted for analysis. Results Our findings indicated significant reductions in FA values in NIHL patients, particularly in the left cingulum, right cingulum, and left inferior longitudinal fasciculus. Notably, no significant changes were observed in the auditory cortex, arcuate fasciculus, superior longitudinal fasciculus, middle longitudinal fasciculus, and right inferior longitudinal fasciculus, suggesting differential impacts of NIHL on various white matter tracts. Conclusions The study's findings highlight the importance of considering association fibres related to speech processing in treating NIHL, as the broader neural network beyond primary auditory structures is significantly impacted. This research contributes to understanding the neurological impact of NIHL and underscores the need for comprehensive approaches in addressing this condition.

Abstract Objective This study aimed to identify features of white matter network attributes based on diffusion tensor imaging (DTI) that might lead to progression from mild cognitive impairment (MCI) and construct a comprehensive model based on these features for predicting the population at high risk of progression to Alzheimer’s disease (AD) in MCI patients. Methods This study enrolled 121 MCI patients from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Among them, 36 progressed to AD after four years of follow-up. A brain network was constructed for each patient based on white matter fiber tracts, and network attribute features were extracted. White matter network features were downscaled, and white matter markers were constructed using an integrated downscaling approach, followed by forming an integrated model with clinical features and performance evaluation. Results APOE4 and ADAS scores were used as independent predictors and combined with white matter network markers to construct a comprehensive model. The diagnostic efficacy of the comprehensive model was 0.924 and 0.919, sensitivity was 0.864 and 0.900, and specificity was 0.871 and 0.815 in the training and test groups, respectively. The Delong test showed significant differences (P 0.05) between the combined model and white matter network biomarkers. Conclusions A comprehensive model constructed based on white matter network markers can identify MCI patients at high risk of progression to AD and provide an adjunct biomarker helpful in early AD detection.

Objectives: Several studies have reported altered cerebrospinal fluid (CSF) concentrations of presynaptic proteins, such as growth-associated protein 43 (GAP-43) in Alzheimer's disease (AD) patients. Given the potential predictive role of CSF GAP-43 for AD, the current study aimed to investigate the relationship between CSF GAP-43 levels and DTI-detected microstructural changes in the white matter (WM).Methods: Data from three groups of participants including 39 control normals (CN), 138 MCI, and 39 AD subjects were obtained from the Alzheimer’s disease Neuroimaging Initiative (ADNI). Linear regression was used to the association of CSF-GAP43 and DTI values (including MD, RD, AxD, and FA) in the brain.Results: We found a significant association between CSF-GAP43 and FA (p-value = 0.011). Also, a negative association was found between CSF-GAP43 concentration and AD, MD, and RD values in MCI (p-value = 0.013, p-value = 0.004, p-value = 0.017). The regression models also revealed a positive association between CSF-GAP43 and FA value in AD subjects (p-value = 0.028). Furthermore, increased CSF-GAP43 level was associated with lower AD, MD, and RD values in brain WM of AD patients (p-value = 0.022, p-value = 0.033, p-value = 0.041).Conclusion: Our study provides a better understanding of the link between CSF GAP-43 and WM changes in patients with MCI and AD. Our findings support the application of CSF GAP-43 as an effective biomarker for monitoring individuals at high risk of AD in the early stages.

Objective(s): During aging, cerebral structures undergo changes due to oxidative stress. The consumption of some plants seems to improve neurological health. For example, rosemary extract (RE) which is widely used as a flavoring food has anti-inflammatory and anti-oxidant activities. Therefore, we aimed to study the effect of RE on the changes related to the aging process in the prefrontal cortex (PFC).Materials and Methods: Twenty-four male Wistar rats including young and old were purchased. Each group was divided into two subgroups: vehicle and rosemary (old vehicle (OV), old rosemary (OR), young vehicle (YV), and young rosemary (YR) groups). Then, we examined the number of intact neurons, myelin base protein (MBP), white matter (WM), levels of malondialdehyde (MDA), and glutathione peroxidase (GPx) in the PFC. Results: The results showed that in the old vehicle rats compared to the young group without treatment, except for the MDA level (which increased), other variables significantly decreased (P≤0.05). Additionally, RE consumption demonstrated a significant elevation of WMA, MBP intensity, number of intact neurons, and GPx activity level, while MDA levels significantly reduced in the treated old rats compared to the old vehicle group (P≤0.05). However, there was no significant difference between the OR and YV groups (P≥0.05). Conclusion: Overall, it seems that RE can protect and improve aging damages in the PFC due to its anti-oxidant properties. So, the use of RE can be a suitable strategy to prevent aging complications in the brain.

Different diseases occur in the brain. For instance, hereditary and progressive diseases affect and degenerate the white matter. Although addressing, diagnosing, and treating complex abnormalities in the brain is challenging, different strategies have been presented with significant advances in medical research. With state-of-art developments in artificial intelligence, new techniques are being applied to brain magnetic resonance images. Deep learning has been recently used for the segmentation and classification of brain images. In this study, we classified normal and pathological brain images using pretrained deep models through transfer learning. The EfficientNet-B5 model reached the highest accuracy of 98.39% on real data, 91.96% on augmented data, and 100%on pathological data. To verify the reliability of the model, fivefold cross-validation and a two-tier cross-test were applied. The results suggest that the proposed method performs reasonably on the classification of brain magnetic resonance images.

Objectives: Cerebral small vessel disease is a chronic, progressive disorder of arterioles, capillaries, and small veins supplying the brain’s white matter and deep structures of gray matter. The latest evidence seems to suggest that chronic oral infections such as periodontitis contribute to cerebral small vessel disease progression. This study evaluated the relationship between periodontal disease and brain white matter hyperintensities. Methods: Forty-three hypertensive patients, aged between 38-82, without previous cardiovascular events, of which 42% were female and 50% diabetic, were evaluated. An association between mean probing depth, mean attachment level, bleeding on probing, total periodontal inflamed surface area, and white matter hyperintensities diagnosed by magnetic resonance was studied. A significance level (α) of 0.05 was considered, and Pearson’s chi-square and Mann–Whitney tests were applied. Results: Data analysis revealed an inverse correlation between mean probing depth, bleeding on probing, total periodontal inflamed surface area, and white matter hyperintensities. A positive correlation was found between mean attachment level and white matter hyperintensities. Conclusions: In our study and within our sample, lower values of mean probing depth, bleeding on probing, and total periodontal inflamed surface area were associated with more white matter hyperintensities. Contrarily, mean attachment level was positively associated with white matter hyperintensities.

Abstract Interactions between extracellular matrix (ECM) proteins and β1 integrins play an essential role maintaining vascular integrity in the brain, particularly under vascular remodeling conditions. As blood vessels in the spinal cord are reported to have distinct properties from those in the brain, here we examined the impact of β1 integrin inhibition on spinal cord vascular integrity, both under normoxic conditions, when blood vessels are stable, and during exposure to chronic mild hypoxia (CMH), when extensive vascular remodeling occurs. We found that a function-blocking β1 integrin antibody triggered a small degree of vascular disruption in the spinal cord under normoxic conditions, but under hypoxic conditions, it greatly enhanced (20-fold) vascular disruption, preferentially in spinal cord white matter (WM). This resulted in elevated microglial activation as well as marked loss of myelin integrity and reduced density of oligodendroglial cells. To understand why vascular breakdown is localized to WM, we compared expression levels of major BBB components of WM and grey matter (GM) blood vessels, but this revealed no obvious differences. Interestingly however, hypoxyprobe staining demonstrated that the most severe levels of spinal cord hypoxia induced by CMH occurred in the WM. Analysis of brain tissue revealed a similar preferential vulnerability of WM tracts to show vascular disruption under these conditions. Taken together, these findings demonstrate an essential role for β1 integrins in maintaining vascular integrity in the spinal cord, and unexpectedly, reveal a novel and fundamental difference between WM and GM blood vessels in their dependence on β1 integrin function during hypoxic exposure. Our data support the concept that the preferential WM vulnerability described may be less a result of intrinsic differences in vascular barrier properties between WM and GM, and more a consequence of differences in vascular density and architecture.

Abstract Background Mutations in the β-glucocerebrosidase (GBA1) gene do cause the lysosomal storage Gaucher disease (GD) and are among the most frequent genetic risk factors for Parkinson’s disease (PD). So far, studies on both neuronopathic GD and PD primarily focused on neuronal manifestations, besides the evaluation of microglial and astrocyte implication. White matter alterations were described in the central nervous system of paediatric type 1 GD patients and were suggested to sustain or even play a role in the PD process, although the contribution of oligodendrocytes has been so far scarcely investigated. Methods We exploited a system to study the induction of central myelination in vitro, consisting of Oli-neu cells treated with dibutyryl-cAMP, in order to evaluate the expression levels and function of β-glucocerebrosidase during oligodendrocyte differentiation. Conduritol-B-epoxide, a β-glucocerebrosidase irreversible inhibitor was used to dissect the impact of β-glucocerebrosidase inactivation in the process of myelination, lysosomal degradation and α-synuclein accumulation in vitro. Moreover, to study the role of β-glucocerebrosidase in the white matter in vivo, we developed a novel mouse transgenic line in which β-glucocerebrosidase function is abolished in myelinating glia, by crossing the Cnp1-cre mouse line with a line bearing loxP sequences flanking Gba1 exons 9–11, encoding for β-glucocerebrosidase catalytic domain. Immunofluorescence, western blot and lipidomic analyses were performed in brain samples from wild-type and knockout animals in order to assess the impact of genetic inactivation of β-glucocerebrosidase on myelination and on the onset of early neurodegenerative hallmarks, together with differentiation analysis in primary oligodendrocyte cultures. Results Here we show that β-glucocerebrosidase inactivation in oligodendrocytes induces lysosomal dysfunction and inhibits myelination in vitro. Moreover, oligodendrocyte-specific β-glucocerebrosidase loss-of-function was sufficient to induce in vivo demyelination and early neurodegenerative hallmarks, including axonal degeneration, α-synuclein accumulation and astrogliosis, together with brain lipid dyshomeostasis and functional impairment. Conclusions Our study sheds light on the contribution of oligodendrocytes in GBA1-related diseases and supports the need for better characterizing oligodendrocytes as actors playing a role in neurodegenerative diseases, also pointing at them as potential novel targets to set a brake to disease progression.

This paper describes a novel nonparametric model for modeling diffusion MRI signals in q-space. In q-space, the diffusion MRI signal is measured for a sequence of diffusion sensitivities (b-values) and diffusion directions (b-vectors). We propose a Poly-RBF model, which employs a bidirectional framework with polynomial bases to model the signal along the b-value direction and Gaussian radial bases across the b-vectors. The model can accommodate sparse data on b-values and moderately dense data on b-vectors. The utility of Poly-RBF is inspected for two applications: (1) prediction of the dMRI signal, and (2) harmonization of dMRI data collected under different acquisition protocols with different scanners. Our results indicate that the proposed Poly-RBF model can more accurately predict the unmeasured diffusion signal than its competitors such as the Gaussian process model in the FSL’s Eddy tool. Applying it to harmonizing the diffusion signal can significantly improve the reproducibility of derived white matter microstructure measures.

Multiple Sclerosis (MS) is an autoimmune condition leading to the degeneration of brain tissue, occurring when the immune system attacks the myelin sheath surrounding axons of white brain matter thereby disrupting brain signals. This study aimed to evaluate how MS lesions alter stress distribution through grey and white brain matter with lesions (active, chronic, and inactive). A linear viscoelastic model represents the tissue-scale dynamic deformation and time dependency of brain tissue. A Prony series expansion was used to model viscous effects including stress relaxation. An elastic modulus, within the viscoelastic model, was either reduced by 11 % for active lesions, or increased by 35 % increase for inactive lesions. These material properties were then implemented to model healthy tissue, active, chronically inflamed, and inactive lesions. Finite element analysis enabled stress evaluation in response to a peak cyclic displacement of 0.5 mm (1 % strain) with the healthy model acting as a control model. Chronic lesions had the largest effect on stress induced, in terms of high (171 Pa) and low stress (108 Pa). Inactive lesions induced an increase in stress of 11 Pa with areas of low stress (105 Pa). Active lesions caused the least deviation in peak induced stress (7 Pa). In conclusion, a hierarchy in stress induced across the lesion types has been found, from highest to lowest: chronic, inactive and active, with potential implications for lesion progression. In conclusion, MS lesions within brain tissue should model lesions, avoid assuming homogeneity during degeneration, and should distinguish between active and passive lesions.

IntroductionIn past work we demonstrated different patterns of white matter (WM) plasticity in females versus males associated with learning a lab-based unilateral motor skill. However, this work was completed in neurologically intact older adults. The current manuscript sought to replicate and expand upon these WM findings in two ways: (1) we investigated biological sex differences in neurologically intact young adults, and (2) participants learned a dynamic full-body balance task.Methods24 participants (14 female, 10 male) participated in the balance training intervention, and 28 were matched controls (16 female, 12 male). Correlational tractography was used to analyze changes in WM from pre- to post-training.ResultsBoth females and males demonstrated skill acquisition, yet there were significant differences in measures of WM between females and males. These data support a growing body of evidence suggesting that females exhibit increased WM neuroplasticity changes relative to males despite comparable changes in motor behavior (e.g., balance).DiscussionThe biological sex differences reported here may represent an important factor to consider in both basic research (e.g., collapsing across females and males) as well as future clinical studies of neuroplasticity associated with motor function (e.g., tailored rehabilitation approaches).

Diffusion-weighted imaging (DWI) is the primary method to investigate macro- and microstructure of neural white matter in vivo. DWI can be used to identify and characterize individual-specific white matter bundles, enabling precise analyses on hypothesis-driven connections in the brain and bridging the relationships between brain structure, function, and behavior. However, cortical endpoints of bundles may span larger areas than what a researcher is interested in, challenging presumptions that bundles are specifically tied to certain brain functions. Functional MRI (fMRI) can be integrated to further refine bundles such that they are restricted to functionally-defined cortical regions. Analyzing properties of these Functional Sub-Bundles (FSuB) increases precision and interpretability of results when studying neural connections supporting specific tasks. Several parameters of DWI and fMRI analyses, ranging from data acquisition to processing, can impact the efficacy of integrating functional and diffusion MRI. Here, we discuss the applications of the FSuB approach, suggest best practices for acquiring and processing neuroimaging data towards this end, and introduce the FSuB-Extractor, a flexible open-source software for creating FSuBs. We demonstrate our processing code and the FSuB-Extractor on an openly-available dataset, the Natural Scenes Dataset.

Several previous studies reported reduced leftward lateralization in blind participants’ samples compared to the sighted population. The origins of this difference remain unknown. Here, we tested whether functional lateralization is connected with the structural characteristics of white matter tracts [corpus callosum (CC), uncinate fasciculus (UF), and superior longitudinal fasciculus (SLF)], as suggested by previous studies conducted in the typical sighted population. Twenty-three blind and 21 sighted adult participants were tested during fMRI with a semantic decision paradigm presented both auditorily and in the modality appropriate for reading (tactually for the blind and visually for the sighted). Lateralization indices (LI) were calculated based on the activations. The fractional anisotropy (FA) measure was extracted from the white matter tracts of interest. Correlation analyses testing the relationship between FA and LI were conducted. The reduced leftward lateralization of both speech processing and reading-related activations was replicated. Nevertheless, the relationship between the structural integrity of the CC and LI and between the asymmetry of the intrahemispheric tracts and LI was not confirmed, possibly due to the lack of power. The sources of the reduced lateralization of the language network in the sensory-deprived population remain unknown. Further studies should account for environmental variables (e.g., the frequency of contact with written language) and the complexity of the factors that may influence the functional lateralization of the human brain.

Background Elevated blood viscosity (BV), a critical determinant in blood rheology, is a contributing factor in cerebrovascular diseases. The specific influence of BV on small vessel disease burden remains unexplored. This study aims to examine the relationship between BV and regional white matter hyperintensity (WMH) volume in patients with acute ischemic stroke. Methods and Results We enrolled a cohort of 302 patients with acute ischemic stroke or transient ischemic attack who were admitted to a hospital within 7 days of symptom onset in this study. We measured whole BV using a scanning capillary‐tube viscometer and categorized systolic blood viscosity into 3 groups based on established references. We quantified and normalized WMH volumes using automated localization and segmentation software by NEUROPHET Inc. We performed multivariable logistic regression analysis to assess the correlation between systolic BV and WMH. The mean subject age was 66.7±13.4 years, and 38.7% (n=117) of the participants were female. Among a total of 302 patients, patients with higher deep WMH volume (T3) were typically older and had an atrial fibrillation, strokes of cardioembolic or undetermined cause, elevated levels of C‐reactive protein, diastolic blood viscosity and systolic BV. A multivariable adjustment revealed a significant association between high systolic BV and increased deep‐WMH volume (odds ratio [OR], 2.636 [95% CI, 1.225–5.673]). Conclusions Elevated systolic BV is more likely to be associated with deep WMH volume in patients with acute ischemic stroke or transient ischemic attack. These findings reveal novel therapeutic strategies focusing on blood rheology to enhance cerebral microcirculation in stroke management.

IntroductionPost-acute COVID syndrome (PACS) is a growing concern, given its impact on mental health and quality of life. However, its effects on cerebral white matter remain poorly understood, particularly in non-hospitalized cohorts. The goals of this cross-sectional, observational study were to examine (1) whether PACS was associated with distinct alterations in white matter microstructure, compared to symptom-matched non-COVID viral infection; and (2) whether microstructural alterations correlated with indices of post-COVID emotional health.MethodsData were collected for 54 symptomatic individuals who tested positive for COVID-19 (mean age 41 ± 12 yrs., 36 female) and 14 controls who tested negative for COVID-19 (mean age 41 ± 14 yrs., 8 female), with both groups assessed an average of 4–5 months after COVID testing. Diffusion magnetic resonance imaging data were collected, and emotional health was assessed via the NIH emotion toolbox, with summary scores indexing social satisfaction, well-being and negative affect.ResultsDespite similar symptoms, the COVID-19 group had reduced mean and axial diffusivity, along with increased mean kurtosis and neurite dispersion, in deep white matter. After adjusting for social satisfaction, higher levels of negative affect in the COVID-19 group were also correlated with increased mean kurtosis and reduced free water in white matter.DiscussionThese results provide preliminary evidence that indices of white matter microstructure distinguish PACS from symptomatic non-COVID infection. Moreover, white matter effects seen in PACS correlate with the severity of emotional sequelae, providing novel insights into this highly prevalent disorder.

Human brain gray matter (GM) has usually been clustered into multiple functional networks. The white matter (WM) fiber bundles are known to interconnect these networks simultaneously, engaging in numerous cognitive functions. However, the exact interconnections between GM and WM are still unclear, whether functional signals in WM rewires GM community organization remains to be explored. In this study, we divided brain functional connections into three types by using edge-centric method, including intra-GM, intra-WM and GM-WM connections, and calculated the edge community evaluation indexes for quantifying GM community engagement. The results showed that the involvement of WM significantly enhanced community entropy in the heteromodal system, while the sensory-attention system remained barely changed. In addition, delta community entropy showed a significant correlation with clinical cognitive scale. Our results suggested that WM rewired GM community organization, enhancing the community engagement of brain regions in the heteromodal system. This involvement was observed to be disrupted in disease groups. Our study revealed that considering the functional signals of GM and WM simultaneously could better understand the brain's functional organization.

Metabolic/neurodegenerative encephalopathies encompass a wide list of conditions that share similar clinical and magnetic resonance imaging (MRI) characteristics, challenging the diagnostic process and resulting in numerous tests performed in order to reach a definitive diagnosis. The aims of this multicentric, retrospective and descriptive study are: (I) to describe the MRI features of dogs and cats with metabolic/neurodegenerative encephalopathies; (II) to attempt an MRI recognition pattern classifying these conditions according to the involvement of grey matter, white matter or both; and (III) to correlate the MRI findings with previous literature. A total of 100 cases were recruited, comprising 81 dogs and 19 cats. These included hepatic encephalopathy (20 dogs and three cats), myelinolysis (five dogs), intoxications (seven dogs and one cat), thiamine deficiency (two dogs and seven cats), hypertensive encephalopathy (three dogs and two cats), neuronal ceroid lipofuscinosis (11 dogs and one cat), gangliosidosis (three dogs and two cats), fucosidosis (one dog), L-2-hydroxyglutaric aciduria (13 dogs and one cat), Lafora disease (11 dogs), spongiform leukoencephalomyelopathy (one dog) and cerebellar cortical degeneration (four dogs and two cats). None of the hepatic encephalopathies showed the previously described T1-weighted hyperintensity of the lentiform nuclei. Instead, there was involvement of the cerebellar nuclei (8/23), which is a feature not previously described. Dogs with myelinolysis showed novel involvement of a specific white matter structure, the superior longitudinal fasciculus (5/5). Thiamine deficiency affected numerous deep grey nuclei with novel involvement of the oculomotor nuclei (3/9), thalamic nuclei, subthalamus and cerebellar nuclei (1/9). Cats with hypertensive encephalopathy had a more extensive distribution of the white matter changes when compared to dogs, extending from the parietal and occipital lobes into the frontal lobes with associated mass effect and increased brain volume. Lysosomal storage disease showed white matter involvement only, with neuronal ceroid lipofuscinosis characterised by severe brain atrophy when compared to gangliosidosis and fucosidosis. All patients with L-2-hydroxyglutaric aciduria had a characteristic T2-weighted hyperintense swelling of the cerebral and cerebellar cortical grey matter, resulting in increased brain volume. Lafora disease cases showed either normal brain morphology (5/11) or mild brain atrophy (6/11). Dogs with cerebellar cortical degeneration had more marked cerebellar atrophy when compared to cats. This study shows the important role of MRI in distinguishing different metabolic/neurodegenerative encephalopathies according to specific imaging characteristics.

Ibogaine is a psychedelic alkaloid being investigated as a possible treatment for opioid use disorder. Ibogaine has a multi-receptor profile with affinities for mu and kappa opioid as well as NMDA receptors amongst others. Due to the sparsity of research into ibogaine's effects on white matter integrity and given the growing evidence that opioid use disorder is characterized by white matter pathology, we set out to investigate ibogaine's effects on two markers of myelination, 2′, 3′-cyclic nucleotide 3′-phosphodiesterase (CNP) and myelin basic protein (MBP). Fifty Sprague Dawley rats were randomly assigned to five experimental groups of n = 10; (1) a saline control group received daily saline injections for 10 days, (2) a morphine control group received escalating morphine doses from 5 to 15 mg/kg over 10 days, (3) an ibogaine control group that received 10 days of saline followed by 50 mg/kg ibogaine hydrochloride, (4) a combination morphine and ibogaine group 1 that received the escalating morphine regime followed by 50 mg/kg ibogaine hydrochloride and (5) a second combination morphine and ibogaine group 2 which followed the same morphine and ibogaine regimen yet was terminated 72 h after administration compared to 24 h in the other groups. White matter from the internal capsule was dissected and qPCR and western blotting determined protein and gene expression of CNP and MBP. Morphine upregulated CNPase whereas ibogaine alone had no effect on CNP mRNA or protein expression. However, ibogaine administration following repeated morphine administration had an immediate effect by increasing CNP mRNA expression. This effect diminished after 72 h and resulted in a highly significant upregulation of CNPase protein at 72 h post administration. Ibogaine administration alone significantly upregulated protein expression yet downregulated MBP mRNA expression. Ibogaine administration following repeated morphine administration significantly upregulated MBP mRNA expression which increased at 72 h post administration resulting in a highly significant upregulation of MBP protein expression at 72 h post administration. These findings indicate that ibogaine is able to upregulate genes and proteins involved in the process of remyelination following opioid use and highlights an important mechanism of action of ibogaine's ability to treat substance use disorders.

Background: During the course of adulthood and aging, white matter (WM) structure and organization are characterized by slow degradation processes such as demyelination and shrinkage. An acceleration of such aging processes has been linked to the development of a range of diseases. Thus, an accurate description of healthy brain maturation, particularly in terms of WM features, is fundamental to the understanding of aging. Methods: We used longitudinal diffusion magnetic resonance imaging to provide an overview of WM changes at different spatial and temporal scales in the UK Biobank (UKB) (n = 2678; agescan 1 = 62.38 ± 7.23 years; agescan 2 = 64.81 ± 7.1 years). To examine the genetic overlap between WM structure and common clinical conditions, we tested the associations between WM structure and polygenic risk scores for the most common neurodegenerative disorder, Alzheimer’s disease, and common psychiatric disorders (unipolar and bipolar depression, anxiety, obsessive-compulsive disorder, autism, schizophrenia, attention-deficit/hyperactivity disorder) in longitudinal (n = 2329) and cross-sectional (n = 31,056) UKB validation data. Results: Our findings indicate spatially distributed WM changes across the brain, as well as distributed associations of polygenic risk scores with WM. Importantly, brain longitudinal changes reflected genetic risk for disorder development better than the utilized cross-sectional measures, with regional differences giving more specific insights into gene-brain change associations than global averages. Conclusions: We extend recent findings by providing a detailed overview of WM microstructure degeneration on different spatial levels, helping to understand fundamental brain aging processes. Further longitudinal research is warranted to examine aging-related gene-brain associations.

IntroductionBrain medical image segmentation is a critical task in medical image processing, playing a significant role in the prediction and diagnosis of diseases such as stroke, Alzheimer's disease, and brain tumors. However, substantial distribution discrepancies among datasets from different sources arise due to the large inter-site discrepancy among different scanners, imaging protocols, and populations. This leads to cross-domain problems in practical applications. In recent years, numerous studies have been conducted to address the cross-domain problem in brain image segmentation.MethodsThis review adheres to the standards of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for data processing and analysis. We retrieved relevant papers from PubMed, Web of Science, and IEEE databases from January 2018 to December 2023, extracting information about the medical domain, imaging modalities, methods for addressing cross-domain issues, experimental designs, and datasets from the selected papers. Moreover, we compared the performance of methods in stroke lesion segmentation, white matter segmentation and brain tumor segmentation.ResultsA total of 71 studies were included and analyzed in this review. The methods for tackling the cross-domain problem include Transfer Learning, Normalization, Unsupervised Learning, Transformer models, and Convolutional Neural Networks (CNNs). On the ATLAS dataset, domain-adaptive methods showed an overall improvement of ~3 percent in stroke lesion segmentation tasks compared to non-adaptive methods. However, given the diversity of datasets and experimental methodologies in current studies based on the methods for white matter segmentation tasks in MICCAI 2017 and those for brain tumor segmentation tasks in BraTS, it is challenging to intuitively compare the strengths and weaknesses of these methods.ConclusionAlthough various techniques have been applied to address the cross-domain problem in brain image segmentation, there is currently a lack of unified dataset collections and experimental standards. For instance, many studies are still based on n-fold cross-validation, while methods directly based on cross-validation across sites or datasets are relatively scarce. Furthermore, due to the diverse types of medical images in the field of brain segmentation, it is not straightforward to make simple and intuitive comparisons of performance. These challenges need to be addressed in future research.

IntroductionSensorineural hearing loss (SNHL) can arise from a diverse range of congenital and acquired factors. Detecting it early is pivotal for nurturing speech, language, and cognitive development in children with SNHL. In our study, we utilized synthetic magnetic resonance imaging (SyMRI) to assess alterations in both gray and white matter within the brains of children affected by SNHL.MethodsThe study encompassed both children diagnosed with SNHL and a control group of children with normal hearing {1.5-month-olds (n = 52) and 3-month-olds (n = 78)}. Participants were categorized based on their auditory brainstem response (ABR) threshold, delineated into normal, mild, moderate, and severe subgroups.Clinical parameters were included and assessed the correlation with SNHL. Quantitative analysis of brain morphology was conducted using SyMRI scans, yielding data on brain segmentation and relaxation time.Through both univariate and multivariate analyses, independent factors predictive of SNHL were identified. The efficacy of the prediction model was evaluated using receiver operating characteristic (ROC) curves, with visualization facilitated through the utilization of a nomogram. It's important to note that due to the constraints of our research, we worked with a relatively small sample size.ResultsNeonatal hyperbilirubinemia (NH) and children with inner ear malformation (IEM) were associated with the onset of SNHL both at 1.5 and 3-month groups. At 3-month group, the moderate and severe subgroups exhibited elevated quantitative T1 values in the inferior colliculus (IC), lateral lemniscus (LL), and middle cerebellar peduncle (MCP) compared to the normal group. Additionally, WMV, WMF, MYF, and MYV were significantly reduced relative to the normal group. Additionally, SNHL-children with IEM had high T1 values in IC, and LL and reduced WMV, WMF, MYV and MYF values as compared with SNHL-children without IEM at 3-month group. LL-T1 and WMF were independent risk factors associated with SNHL. Consequently, a prediction model was devised based on LL-T1 and WMF. ROC for training set, validation set and external set were 0.865, 0.806, and 0.736, respectively.ConclusionThe integration of T1 quantitative values and brain volume segmentation offers a valuable tool for tracking brain development in children affected by SNHL and assessing the progression of the condition's severity.