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The blood–brain barrier (BBB) protects the brain but is also an important obstacle for the effective delivery of therapeutics in Alzheimer’s disease and other neurodegenerative disorders. Transcranial magnetic resonance-guided focused ultrasound (MRgFUS) has been shown to reversibly disrupt the BBB. However, treatment of diffuse regions across the brain along with the effect on Alzheimer’s disease relevant pathology need to be better characterized. This study is an open-labelled single-arm trial (NCT03739905) to investigate the feasibility of modulating BBB permeability in the default mode network and the impact on cognition, amyloid and tau pathology as well as BBB integrity. Nine participants [mean age 70.2 ± 7.2 years, mean Mini-Mental State Examination (MMSE) 21.9] underwent three biweekly procedures with follow-up visits up to 6 months. The BBB permeability of the bilateral hippocampi, anterior cingulate cortex and precuneus was transiently increased without grade 3 or higher adverse events. Participants did not experience worsening trajectory of cognitive decline (ADAS-cog11, MMSE). Whole brain vertex-based analysis of the 18F-florbetaben PET imaging demonstrated clusters of modest SUVR reduction in the right parahippocampal and inferior temporal lobe. However, CSF and blood biomarkers did not demonstrate any amelioration of Alzheimer’s disease pathology (P-tau181, amyloid-β42/40 ratio), nor did it show persistent BBB dysfunction (plasma PDGFRbeta and CSF-to-plasma albumin ratio). This study provides neuroimaging and fluid biomarker data to characterize the safety profile of MRgFUS BBB modulation in neurodegeneration as a potential strategy for enhanced therapeutic delivery.

White matter (WM) injury is frequently observed along with dementia. Positron emission tomography with amyloid-ligands (Aβ-PET) recently gained interest for detecting WM injury. Yet, little is understood about the origin of the altered Aβ-PET signal in WM regions. Here, we investigated the relative contributions of diffusion MRI-based microstructural alterations, including free water and tissue-specific properties, to Aβ-PET in WM and to cognition. We included a unique cohort of 115 participants covering the spectrum of low-to-severe white matter hyperintensity (WMH) burden and cognitively normal to dementia. We applied a bi-tensor diffusion-MRI model that differentiates between (i) the extracellular WM compartment (represented via free water), and (ii) the fiber-specific compartment (via free water-adjusted fractional anisotropy [FA]). We observed that, in regions of WMH, a decrease in Aβ-PET related most closely to higher free water and higher WMH volume. In contrast, in normal-appearing WM, an increase in Aβ-PET related more closely to higher cortical Aβ (together with lower free water-adjusted FA). In relation to cognitive impairment, we observed a closer relationship with higher free water than with either free water-adjusted FA or WM PET. Our findings support free water and Aβ-PET as markers of WM abnormalities in patients with mixed dementia, and contribute to a better understanding of processes giving rise to the WM PET signal.

GBA1 mutation is the most common genetic risk factor for Parkinson's disease (PD). Replacement of the lysosomal enzyme glucocerebrosidase (GCase) slows neurodegeneration in PD models and may be a promising disease-modifying therapy in patients with PD. However, recombinant GCase has limited penetration through the blood-brain barrier (BBB). Microbubble-mediated magnetic resonance-guided focused ultrasound (MRgFUS) can reversibly disrupt the BBB for drug delivery.This open-label phase I study investigated the safety and feasibility of MRgFUS putaminal delivery of intravenous GCase at escalating doses (15 to 30 to 60 IU/kg) every 2 weeks in four patients with PD with GBA1 mutations.BBB permeability was achieved and restored in all patients as quantified by dynamic contrast-enhanced magnetic resonance imaging after treatment. There were no serious adverse events. Two patients developed transient dyskinesia after treatment. Blinded Movement Disorder Society-Unified Parkinson's Disease Rating Scale motor scores off medication decreased by 12% at 6 months from baseline (from 26 ± 9 to 22 ± 6). Standardized uptake value ratio on fluorodeoxyglucose positron emission tomography imaging in the treated putamen reduced from 1.66 ± 0.14 to 1.27 ± 0.08.Results from this study demonstrate the safety and feasibility of MRgFUS GCase delivery in PD and support further investigation of this approach. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

INTRODUCTIONIt remains unclear to which extent vascular burden promotes neurodegeneration and cognitive dysfunction in a cohort spanning low-to-severe small vessel disease (SVD) and amyloid-beta pathology.METHODSIn 120 subjects, we investigated 1) whether vascular burden, quantified as total or lobar white matter hyperintensity (WMH) volumes, is associated with different cognitive domains; and 2) whether the total WMH effect on cognition is mediated by amyloid (18F-AV45-PET), glucose metabolism (18F-FDG-PET), and/or cortical atrophy.RESULTSIncreased total WMH volume was associated with poorer performance in all cognitive domains tested, with the strongest effects observed for semantic fluency. These relationships were mediated mainly through cortical atrophy, particularly in the temporal lobe, and to a lesser extent through amyloid and metabolism. WMH volumes differentially impacted cognition depending on lobar location and amyloid status.DISCUSSIONOur study suggests mainly an amyloid-independent pathway in which vascular burden affects cognitive impairment through temporal lobe atrophy.

Emotional states influence bodily physiology, as exemplified in the top-down process by which anxiety causes faster beating of the heart1–3. However, whether an increased heart rate might itself induce anxiety or fear responses is unclear3–8. Physiological theories of emotion, proposed over a century ago, have considered that in general, there could be an important and even dominant flow of information from the body to the brain9. Here, to formally test this idea, we developed a noninvasive optogenetic pacemaker for precise, cell-type-specific control of cardiac rhythms of up to 900 beats per minute in freely moving mice, enabled by a wearable micro-LED harness and the systemic viral delivery of a potent pump-like channelrhodopsin. We found that optically evoked tachycardia potently enhanced anxiety-like behaviour, but crucially only in risky contexts, indicating that both central (brain) and peripheral (body) processes may be involved in the development of emotional states. To identify potential mechanisms, we used whole-brain activity screening and electrophysiology to find brain regions that were activated by imposed cardiac rhythms. We identified the posterior insular cortex as a potential mediator of bottom-up cardiac interoceptive processing, and found that optogenetic inhibition of this brain region attenuated the anxiety-like behaviour that was induced by optical cardiac pacing. Together, these findings reveal that cells of both the body and the brain must be considered together to understand the origins of emotional or affective states. More broadly, our results define a generalizable approach for noninvasive, temporally precise functional investigations of joint organism-wide interactions among targeted cells during behaviour.

Develop and evaluate a deep learning approach to estimate cerebral blood flow (CBF) and arterial transit time (ATT) from multiple post-labeling delay (PLD) ASL MRI.ASL MRI were acquired with 6 PLDs on a 1.5T or 3T GE system in adults with and without cognitive impairment (N = 99). Voxel-level CBF and ATT maps were quantified by training models with distinct convolutional neural network architectures: (1) convolutional neural network (CNN) and (2) U-Net. Models were trained and compared via 5-fold cross validation. Performance was evaluated using mean absolute error (MAE). Model outputs were trained on and compared against a reference ASL model fitting after data cleaning. Minimally processed ASL data served as another benchmark. Model output uncertainty was estimated using Monte Carlo dropout. The better-performing neural network was subsequently re-trained on inputs with missing PLDs to investigate generalizability to different PLD schedules.Relative to the CNN, the U-Net yielded lower MAE on training data. On test data, the U-Net MAE was 8.4 ± 1.4 mL/100 g/min for CBF and 0.22 ± 0.09 s for ATT. A significant association was observed between MAE and Monte Carlo dropout-based uncertainty estimates. Neural network performance remained stable despite systematically reducing the number of input images (i.e., up to 3 missing PLD images). Mean processing time was 10.77 s for the U-Net neural network compared to 10 min 41 s for the reference pipeline.It is feasible to generate CBF and ATT maps from 1.5T and 3T multi-PLD ASL MRI with a fast deep learning image-generation approach.

Background Cerebral small vessel disease is associated with higher ratios of soluble‐epoxide hydrolase derived linoleic acid diols (12,13‐dihydroxyoctadecenoic acid [DiHOME] and 9,10‐DiHOME) to their parent epoxides (12(13)‐epoxyoctadecenoic acid [EpOME] and 9(10)‐EpOME); however, the relationship has not yet been examined in stroke. Methods and Results Participants with mild to moderate small vessel stroke or large vessel stroke were selected based on clinical and imaging criteria. Metabolites were quantified by ultra‐high‐performance liquid chromatography–mass spectrometry. Volumes of stroke, lacunes, white matter hyperintensities, magnetic resonance imaging visible perivascular spaces, and free water diffusion were quantified from structural and diffusion magnetic resonance imaging (3 Tesla). Adjusted linear regression models were used for analysis. Compared with participants with large vessel stroke (n=30), participants with small vessel stroke (n=50) had a higher 12,13‐DiHOME/12(13)‐EpOME ratio (β=0.251, P =0.023). The 12,13‐DiHOME/12(13)‐EpOME ratio was associated with more lacunes (β=0.266, P =0.028) but not with large vessel stroke volumes. Ratios of 12,13‐DiHOME/12(13)‐EpOME and 9,10‐DiHOME/9(10)‐EpOME were associated with greater volumes of white matter hyperintensities (β=0.364, P P P =0.011; β=0.314, P =0.006). In small vessel stroke, the 12,13‐DiHOME/12(13)‐EpOME ratio was associated with higher white matter free water diffusion (β=0.439, P =0.016), which was specific to the temporal lobe in exploratory regional analyses. The 9,10‐DiHOME/9(10)‐EpOME ratio was associated with temporal lobe atrophy (β=−0.277, P =0.031). Conclusions Linoleic acid markers of cytochrome P450/soluble‐epoxide hydrolase activity were associated with small versus large vessel stroke, with small vessel disease markers consistent with blood brain barrier and neurovascular‐glial disruption, and temporal lobe atrophy. The findings may indicate a novel modifiable risk factor for small vessel disease and related neurodegeneration.

Neurological symptoms associated with coronavirus disease 2019 (COVID-19), such as fatigue and smell/taste changes, persist beyond infection. However, little is known of brain physiology in the post-COVID-19 timeframe.To determine whether adults who experienced flu-like symptoms due to COVID-19 would exhibit cerebral blood flow (CBF) alterations in the weeks/months beyond infection, relative to controls who experienced flu-like symptoms but tested negative for COVID-19.Prospective observational.A total of 39 adults who previously self-isolated at home due to COVID-19 (41.9 ± 12.6 years of age, 59% female, 116.5 ± 62.2 days since positive diagnosis) and 11 controls who experienced flu-like symptoms but had a negative COVID-19 diagnosis (41.5 ± 13.4 years of age, 55% female, 112.1 ± 59.5 since negative diagnosis).A 3.0 T; T1-weighted magnetization-prepared rapid gradient and echo-planar turbo gradient-spin echo arterial spin labeling sequences.Arterial spin labeling was used to estimate CBF. A self-reported questionnaire assessed symptoms, including ongoing fatigue. CBF was compared between COVID-19 and control groups and between those with (n = 11) and without self-reported ongoing fatigue (n = 28) within the COVID-19 group.Between-group and within-group comparisons of CBF were performed in a voxel-wise manner, controlling for age and sex, at a family-wise error rate of 0.05.Relative to controls, the COVID-19 group exhibited significantly decreased CBF in subcortical regions including the thalamus, orbitofrontal cortex, and basal ganglia (maximum cluster size = 6012 voxels and maximum t-statistic = 5.21). Within the COVID-19 group, significant CBF differences in occipital and parietal regions were observed between those with and without self-reported on-going fatigue.These cross-sectional data revealed regional CBF decreases in the COVID-19 group, suggesting the relevance of brain physiology in the post-COVID-19 timeframe. This research may help elucidate the heterogeneous symptoms of the post-COVID-19 condition.2.Stage 3.

Deep brain stimulation (DBS) has been investigated for neuropsychiatric disorders. In this phase 1 trial, we treated four posttraumatic stress disorder (PTSD) patients with DBS delivered to the subgenual cingulum and the uncinate fasciculus. In addition to validated clinical scales, patients underwent neuroimaging studies and psychophysiological assessments of fear conditioning, extinction, and recall. We show that the procedure is safe and potentially effective (55% reduction in Clinical Administered PTSD Scale scores). Posttreatment imaging data revealed metabolic activity changes in PTSD neurocircuits. During psychophysiological assessments, patients with PTSD had higher skin conductance responses when tested for recall compared to healthy controls. After DBS, this objectively measured variable was significantly reduced. Last, we found that a ratio between recall of extinguished and nonextinguished conditioned responses had a strong correlation with clinical outcome. As this variable was recorded at baseline, it may comprise a potential biomarker of treatment response.

Background: The detailed extent of neuroinvasion or deleterious brain changes resulting from COVID-19 and their time courses remain to be determined in relation to “long-haul” COVID-19 symptoms. Our objective is to determine whether there are alterations in functional brain imaging measures among people with COVID-19 after hospital discharge or self-isolation. Methods: This paper describes a protocol for NeuroCOVID-19, a longitudinal observational study of adults aged 20–75 years at Sunnybrook Health Sciences Centre in Toronto, Ontario, that began in April 2020. We aim to recruit 240 adults, 60 per group: people who contracted COVID-19 and were admitted to hospital (group 1), people who contracted COVID-19 and self-isolated (group 2), people who experienced influenza-like symptoms at acute presentation but tested negative for COVID-19 and self-isolated (group 3, control) and healthy people (group 4, control). Participants are excluded based on premorbid neurologic or severe psychiatric illness, unstable cardiovascular disease, and magnetic resonance imaging (MRI) contraindications. Initial and 3-month follow-up assessments include multiparametric brain MRI and electroencephalography. Sensation and cognition are assessed alongside neuropsychiatric assessments and symptom self-reports. We will test the data from the initial and follow-up assessments for group differences based on 3 outcome measures: MRI cerebral blood flow, MRI resting state fractional amplitude of low-frequency fluctuation and electroencephalography spectral power. Interpretation: If neurophysiologic alterations are detected in the COVID-19 groups in our NeuroCOVID-19 study, this information could inform future research regarding interventions for long-haul COVID-19. The study results will be disseminated to scientists, clinicians and COVID-19 survivors, as well as the public and private sectors to provide context on how brain measures relate to lingering symptoms.

Background: Neuropsychiatric symptoms (NPS) are a core feature of most neurodegenerative and cerebrovascular diseases. White matter hyperintensities and brain atrophy have been implicated in NPS. We aimed to investigate the relative contribution of white matter hyperintensities and cortical atrophy to NPS in participants across neurodegenerative and cerebrovascular diseases. Methods: 513 participants with one of these conditions, i.e. Alzheimer’s Disease/Mild Cognitive Impairment, Amyotrophic Lateral Sclerosis, Frontotemporal Dementia, Parkinson’s Disease, or Cerebrovascular Disease were included in the study. NPS were assessed using the Neuropsychiatric Inventory – Questionnaire and grouped into hyperactivity, psychotic, affective, and apathy subsyndromes. White matter hyperintensities were quantified using a semi-automatic segmentation technique and FreeSurfer cortical thickness was used to measure regional grey matter atrophy. Results: Although NPS were frequent across the five disease groups, participants with Frontotemporal Dementia had the highest frequency of hyperactivity, apathy, and affective subsyndromes compared to other groups, whilst psychotic subsyndrome was high in both Frontotemporal Dementia and Parkinson’s Disease. Results from univariate and multivariate results showed that various predictors were associated with neuropsychiatric subsyndromes, especially cortical thickness in the inferior frontal, cingulate, and insula regions, sex(female), global cognition, and basal ganglia-thalamus white matter hyperintensities. Conclusions: In participants with neurodegenerative and cerebrovascular diseases, our results suggest that increased cortical atrophy and white matter hyperintensities burden in several cortical-subcortical structures may contribute to the development of NPS. Further studies investigating the mechanisms that determine the progression of NPS in various neurodegenerative and cerebrovascular diseases are needed.

Successful segmentation of the total intracranial vault (ICV) and ventricles is of critical importance when studying neurodegeneration through neuroimaging. We present iCVMapper and VentMapper, robust algorithms that use a convolutional neural network (CNN) to segment the ICV and ventricles from both single and multi-contrast MRI data. Our models were trained on a large dataset from two multi-site studies (N=528 subjects for ICV, N=501 for ventricular segmentation) consisting of older adults with varying degrees of cerebrovascular lesions and atrophy, which pose significant challenges for most segmentation approaches. The models were tested on 238 participants, including subjects with vascular cognitive impairment and high white matter hyperintensity burden. Two of the three test sets came from studies not used in the training dataset. We assessed our algorithms relative to four state-of-the-art ICV extraction methods (MONSTR, BET, Deep Extraction, FreeSurfer), as well as a ventricular segmentation tool (FreeSurfer). Our multi-contrast models outperformed other methods across all evaluation metrics, with average Dice coefficients of 0.98 and 0.94 for ICV and ventricular segmentation respectively. Both models were also the most time efficient, segmenting the structures in orders of magnitude faster than some of the other available methods. Our networks showed an increased accuracy with the use of a conditional random field (CRF) as a post-processing step. We further validated both segmentation models, highlighting their robustness to images with lower resolution and signal-to-noise ratio, compared to tested techniques. The pipeline and models are available at: https://icvmapp3r.readthedocs.io and https://ventmapp3r.readthedocs.io to enable further investigation of the roles of ICV and ventricles in relation to normal aging and neurodegeneration in large multi-site studies.

Background: Recent evidence suggests that the accumulation of iron, specifically ferrous Fe2+, may play a role in the development and progression of neurodegeneration in Alzheimer’s disease (AD) through the production of oxidative stress. Objective: To localize and characterize iron deposition and oxidation state in AD, we analyzed human hippocampal autopsy samples from four subjects with advanced AD that have been previously characterized with correlative MRI-histology. Methods: We perform scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and electron energy loss spectroscopy (EELS) in the higher resolution transmission electron microscope on the surface and cross-sections of specific iron-rich regions of interest. Results: Specific previously analyzed regions were visualized using SEM and confirmed to be iron-rich deposits using EDS. Subsequent analysis using focused ion beam cross-sectioning and SEM characterized the iron deposition throughout the 3-D volumes, confirming the presence of iron throughout the deposits, and in two out of four specimens demonstrating colocalization with zinc. Analysis of traditional histology slides showed the analyzed deposits overlapped both with amyloid and tau deposition. Following higher resolution analysis of a single iron deposit using scanning transmission electron microscope (STEM), we demonstrated the potential of monochromated STEM-EELS to discern the relative oxidation state of iron within a deposit. Conclusion: These findings suggest that iron is present in the AD hippocampus and can be visualized and characterized using combined MRI and EM techniques. An altered relative oxidation state may suggest a direct link between iron and oxidative stress in AD. These methods thus could potentially measure an altered relative oxidation state that could suggest a direct link between iron and oxidative stress in AD. Furthermore, we have demonstrated the ability to analyze metal deposition alongside commonly used histological markers of AD pathology, paving the way for future insights into the molecular interactions between Aβ, tau, iron, and other putative metals, such as zinc.

The long-term consequences of coronavirus disease 2019 (COVID-19) on brain physiology and function are not yet well understood. From the recently described NeuroCOVID-19 study, we examined cerebral blood flow (CBF) in 50 participants recruited to one of two groups: 1) adults who previously self-isolated at home due to COVID-19 (n = 39; 116.5 ± 62.2 days since positive diagnosis), or 2) controls who experienced flu-like symptoms but had a negative COVID-19 diagnosis (n = 11). Participants underwent arterial spin labeling magnetic resonance imaging at 3 T to yield measures of CBF. Voxel-wise analyses of CBF were performed to assess for between-group differences, after controlling for age and sex. Relative to controls, the COVID-19 group exhibited decreased CBF in the thalamus, orbitofrontal cortex, and regions of the basal ganglia. Within the COVID-19 group, CBF differences in occipital and parietal regions were observed between those with (n = 11) and without (n = 28) self-reported on-going fatigue. These results suggest long-term changes in brain physiology in adults across the post-COVID-19 timeframe. Moreover, CBF may aid in understanding the heterogeneous symptoms of the post-COVID-19 condition. Future longitudinal studies are needed to further characterize the consequences of COVID-19 on the brain.

Background and ObjectivesRepeated concussive and sub-concussive impacts in high-contact sports can affect the brain’s microstructure, which can be studied using diffusion MRI. Most prior imaging studies, however, employ a cross-sectional design, do not include low-contact players as controls, or use traditional diffusion tensor imaging without investigating novel tractspecific microstructural metrics.MethodsWe examined brain microstructure in 63 high-contact (American football) and 34 low-contact (volleyball) collegiate athletes with up to 4 years of follow-up (315 total scans) using advanced diffusion MRI, a comprehensive set of multi-compartment models, and automated fiber quantification tools. We investigated diffusion metrics along the length of tracts using nested linear mixed-effects models to ascertain the acute and chronic effects of sub-concussive and concussive impacts, as well as associations between diffusion changes with clinical, behavioral, and sports-related measures.ResultsSignificant longitudinal increases in fractional anisotropy and axonal water fraction were detected in volleyball players, but not in football players, along with decreases in radial and mean diffusivity as well as orientation dispersion index (all findings absolute T-statistic > 3.5, p < .0001). This pattern was present in the callosum forceps minor, left superior longitudinal fasciculus, left thalamic radiation, and right cingulum hippocampus. Longitudinal group differences were more prominent and observed in a larger number of tracts in concussed (previously or in-study) football players (p < .0001), while smaller effects were noted in un-concussed players. An analysis of immediate-post concussion scans in football players demonstrated a transient localized increase in axial diffusivity, mean and radial kurtosis in the left uncinate and right cingulum hippocampus (p < .0001). Finally, football players with high position-based sub-concussive risk demonstrated increased orientation dispersion index over time (p < .0001).DiscussionThe observed longitudinal changes in our volleyball cohort likely reflect normal development in this age range, while the relative attenuation of these effects seen in football, and especially concussed athletes, could possibly reveal diminished myelination, altered axonal calibers, or depressed pruning processes leading to a static, non-decreasing axonal dispersion. This prospective longitudinal study demonstrates significantly divergent tract-specific trajectories of brain microstructure, possibly reflecting a concussive and/or repeated sub-concussive impact-related alteration of normal white matter development in football athletes.

Tau protein neurofibrillary tangles are closely linked to neuronal/synaptic loss and cognitive decline in Alzheimer’s disease and related dementias. Our knowledge of the pattern of neurofibrillary tangle progression in the human brain, critical to the development of imaging biomarkers and interpretation of in vivo imaging studies in Alzheimer’s disease, is based on conventional two-dimensional histology studies that only sample the brain sparsely. To address this limitation, ex vivo MRI and dense serial histological imaging in 18 human medial temporal lobe specimens (age 75.3 ± 11.4 years, range 45 to 93) were used to construct three-dimensional quantitative maps of neurofibrillary tangle burden in the medial temporal lobe at individual and group levels. Group-level maps were obtained in the space of an in vivo brain template, and neurofibrillary tangles were measured in specific anatomical regions defined in this template. Three-dimensional maps of neurofibrillary tangle burden revealed significant variation along the anterior-posterior axis. While early neurofibrillary tangle pathology is thought to be confined to the transentorhinal region, we found similar levels of burden in this region and other medial temporal lobe subregions, including amygdala, temporopolar cortex, and subiculum/cornu ammonis 1 hippocampal subfields. Overall, the three-dimensional maps of neurofibrillary tangle burden presented here provide more complete information about the distribution of this neurodegenerative pathology in the region of the cortex where it first emerges in Alzheimer’s disease, and may help inform the field about the patterns of pathology spread, as well as support development and validation of neuroimaging biomarkers.

Obsessive compulsive disorder (OCD) and major depressive disorder (MDD) are common, often refractory, neuropsychiatric conditions for which new treatment approaches are urgently needed. Magnetic resonance-guided focused ultrasound (MRgFUS) is a novel surgical technique permitting incisionless ablative neurosurgery. We examined the safety profile, clinical response, and imaging correlates of MRgFUS bilateral anterior capsulotomy in patients with refractory obsessive compulsive disorder (OCD, N = 6) and major depressive disorder (MDD, n = 6). There were no serious adverse events. Nonserious adverse events included headaches and pin-site swelling in 7/12 patients. The response rate was 4/6 and 2/6 in the OCD and MDD cohorts respectively. To delineate the white-matter tracts impacted by capsulotomy, a normative diffusion MRI-based structural connectome was used, revealing tracts terminating primarily in the frontal pole, medial thalamus, striatum, and medial-temporal lobe. Positron emission tomography (PET) analysis (nine subjects) revealed widespread decreases in metabolism bilaterally in the cerebral hemispheres at 6 months post treatment, as well as in the right hippocampus, amygdala, and putamen. A pretreatment seed-to-voxel resting-state functional magnetic resonance imaging (rs-fMRI) analysis (12 subjects) revealed three voxel clusters significantly associated with eventual clinical response. MRgFUS capsulotomy appears to be safe, well tolerated, and according to these initial results, may be an important treatment option for patients with refractory OCD and MDD. MRgFUS capsulotomy results in both targeted and widespread changes in neural activity, and neuroimaging may hold potential for the prediction of outcome.

The thalamus is a key brain hub that is globally connected to many cortical regions. Previous work highlights thalamic contributions to multiple cognitive functions, but few studies have measured thalamic volume changes or cognitive correlates. This study investigates associations between thalamic volumes and post-stroke cognitive function.Participants with non-thalamic brain infarcts (3-42 months) underwent MRI and cognitive testing. Focal infarcts and thalami were traced manually. In cases with bilateral infarcts, the side of the primary infarct volume defined the hemisphere involved. Brain parcellation and volumetrics were extracted using a standardized and previously validated neuroimaging pipeline. Age and gender-matched healthy controls provided normal comparative thalamic volumes. Thalamic atrophy was considered when the volume exceeded 2 standard deviations greater than the controls.Thalamic volumes ipsilateral to the infarct in stroke patients (n=55) were smaller than left (4.4 ± 1.4 vs. 5.4 ± 0.5 cc, p0.001) and right (4.4 ± 1.4 vs. 5.5 ± 0.6 cc, p0.001) thalamic volumes in the controls. After controlling for head-size and global brain atrophy, infarct volume independently correlated with ipsilateral thalamic volume (β= -0.069, p=0.024). Left thalamic atrophy correlated significantly with poorer cognitive performance (β = 4.177, p = 0.008), after controlling for demographics and infarct volumes.Our results suggest that the remote effect of infarction on ipsilateral thalamic volume is associated with global post-stroke cognitive impairment.

3D histology, slice-based connectivity atlases, and diffusion MRI are common techniques to map brain wiring. While there are many modality-specific tools to process these data, there is a lack of integration across modalities. We develop an automated resource that combines histologically cleared volumes with connectivity atlases and MRI, enabling the analysis of histological features across multiple fiber tracts and networks, and their correlation with in-vivo biomarkers. We apply our pipeline in a murine stroke model, demonstrating not only strong correspondence between MRI abnormalities and CLARITY-tissue staining, but also uncovering acute cellular effects in areas connected to the ischemic core. We provide improved maps of connectivity by quantifying projection terminals from CLARITY viral injections, and integrate diffusion MRI with CLARITY viral tracing to compare connectivity maps across scales. Finally, we demonstrate tract-level histological changes of stroke through this multimodal integration. This resource can propel investigations of network alterations underlying neurological disorders., Many approaches exist to process data from individual imaging modalities, but integrating them is challenging. The authors develop an automated resource that enables co-registered network- and tract-level analysis of macroscopic in-vivo imaging and microscopic imaging of cleared tissue.

White matter hyperintensities (WMHs) are frequently observed on structural neuroimaging of elderly populations and are associated with cognitive decline and increased risk of dementia. Many existing WMH segmentation algorithms produce suboptimal results in populations with vascular lesions or brain atrophy, or require parameter tuning and are computationally expensive. Additionally, most algorithms do not generate a confidence estimate of segmentation quality, limiting their interpretation. MRI-based segmentation methods are often sensitive to acquisition protocols, scanners, noise-level, and image contrast, failing to generalize to other populations and out-of-distribution datasets. Given these concerns, we propose a novel Bayesian 3D convolutional neural network with a U-Net architecture that automatically segments WMH, provides uncertainty estimates of the segmentation output for quality control, and is robust to changes in acquisition protocols. We also provide a second model to differentiate deep and periventricular WMH. Four hundred thirty-two subjects were recruited to train the CNNs from four multisite imaging studies. A separate test set of 158 subjects was used for evaluation, including an unseen multisite study. We compared our model to two established state-of-the-art techniques (BIANCA and DeepMedic), highlighting its accuracy and efficiency. Our Bayesian 3D U-Net achieved the highest Dice similarity coefficient of 0.89 ± 0.08 and the lowest modified Hausdorff distance of 2.98 ± 4.40 mm. We further validated our models highlighting their robustness on "clinical adversarial cases" simulating data with low signal-to-noise ratio, low resolution, and different contrast (stemming from MRI sequences with different parameters). Our pipeline and models are available at: https://hypermapp3r.readthedocs.io.