MEGnet: Automatic ICA-based artifact removal for MEG using spatiotemporal convolutional neural networks.

Magnetoencephalography (MEG) is a functional neuroimaging tool that records the magnetic fields induced by neuronal activity; however, signal from non-neuronal sources can corrupt the data. Eye-blinks, saccades, and cardiac activity are three of the most common sources of non-neuronal artifacts. They can be measured by affixing eye proximal electrodes, as in electrooculography (EOG), and chest electrodes, as in electrocardiography (ECG), however this complicates imaging setup, decreases patient comfort, and can induce further artifacts from movement. This work proposes an EOG- and ECG-free approach to identify eye-blinks, saccades, and cardiac activity signals for automated artifact suppression. The contribution of this work is three-fold. First, using a data driven, multivariate decomposition approach based on Independent Component Analysis (ICA), a highly accurate artifact classifier is constructed as an amalgam of deep 1-D and 2-D Convolutional Neural Networks (CNNs) to automate the identification and removal of ubiquitous whole brain artifacts including eye-blink, saccade, and cardiac artifacts. The specific architecture of this network is optimized through an unbiased, computer-based hyperparameter random search. Second, visualization methods are applied to the learned abstraction to reveal what features the model uses and to bolster user confidence in the model's training and potential for generalization. Finally, the model is trained and tested on both resting-state and task MEG data from 217 subjects, and achieves a new state-of-the-art in artifact detection accuracy of 98.95% including 96.74% sensitivity and 99.34% specificity on the held out test-set. This work automates MEG processing for both clinical and research use, adapts to the acquired acquisition time, and can obviate the need for EOG or ECG electrodes for artifact detection.

Mapping default mode connectivity alterations following a single season of subconcussive impact exposure in youth football.

Repetitive head impact (RHI) exposure in collision sports may contribute to adverse neurological outcomes in former players. In contrast to a concussion, or mild traumatic brain injury, "subconcussive" RHIs represent a more frequent and asymptomatic form of exposure. The neural network-level signatures characterizing subconcussive RHIs in youth collision-sport cohorts such as American Football are not known. Here, we used resting-state functional MRI to examine default mode network (DMN) functional connectivity (FC) following a single football season in youth players (n = 50, ages 8-14) without concussion. Football players demonstrated reduced FC across widespread DMN regions compared with non-collision sport controls at postseason but not preseason. In a subsample from the original cohort (n = 17), players revealed a negative change in FC between preseason and postseason and a positive and compensatory change in FC during the offseason across the majority of DMN regions. Lastly, significant FC changes, including between preseason and postseason and between in- and off-season, were specific to players at the upper end of the head impact frequency distribution. These findings represent initial evidence of network-level FC abnormalities following repetitive, non-concussive RHIs in youth football. Furthermore, the number of subconcussive RHIs proved to be a key factor influencing DMN FC.

Advanced MRI techniques for transcranial high intensity focused ultrasound targeting.

Magnetic resonance guided high intensity focused ultrasound is a novel, non-invasive, image-guided procedure that is able to ablate intracranial tissue with submillimetre precision. It is currently FDA approved for essential tremor and tremor dominant Parkinson's disease. The aim of this update is to review the limitations of current landmark-based targeting techniques of the ventral intermediate nucleus and demonstrate the role of emerging imaging techniques that are relevant for both magnetic resonance guided high intensity focused ultrasound and deep brain stimulation. A significant limitation of standard MRI sequences is that the ventral intermediate nucleus, dentatorubrothalamic tract, and other deep brain nuclei cannot be clearly identified. This paper provides original, annotated images demarcating the ventral intermediate nucleus, dentatorubrothalamic tract, and other deep brain nuclei on advanced MRI sequences such as fast grey matter acquisition T1 inversion recovery, quantitative susceptibility mapping, susceptibility weighted imaging, and diffusion tensor imaging tractography. Additionally, the paper reviews clinical efficacy of targeting with these novel MRI techniques when compared to current established landmark-based targeting techniques. The paper has widespread applicability to both deep brain stimulation and magnetic resonance guided high intensity focused ultrasound.

Robust pCASL perfusion imaging using a 3D Cartesian acquisition with spiral profile reordering (CASPR).

PURPOSE: To improve the robustness of arterial spin-labeled measured perfusion using a novel Cartesian acquisition with spiral profile reordering (CASPR) 3D turbo spin echo (TSE) in the brain and kidneys. METHODS: The CASPR view ordering followed a pseudo-spiral trajectory on a Cartesian grid, by sampling the center of k-space at the beginning of each echo train of a segmented 3D TSE acquisition. With institutional review board approval and written informed consent, 14 normal subjects (9 brain and 5 kidneys) were scanned with pCASL perfusion imaging using 3D CASPR and compared against 3D linear TSE (brain and kidneys), the established 2D EPI and 3D gradient and spin echo perfusion (brain), and 2D single-shot turbo spin-echo perfusion (kidneys). The SNR and the quantitative perfusion values were compared among different acquisitions. RESULTS: 3D CASPR TSE achieved robust perfusion across all slices compared to 3D linear TSE in the brain and kidneys. Compared to 2D EPI, 3D CASPR TSE showed higher SNR across the brain (P < 0.01), and exhibited good agreement (36.4 ± 4.7 and 36.9 ± 5.3 mL/100 g/min with 2D EPI and 3D CASPR, respectively), and with 3D gradient and spin echo (27.9 ± 7.2 mL/100 g/min). Compared to a single slice 2D single-shot turbo spin-echo acquisition, 3D CASPR TSE achieved robust perfusion across the entire kidneys in similar scan time with comparable quantified perfusion values (154.1 ± 74.6 and 151.7 ± 70.6 mL/100 g/min with 2D single-shot turbo spin-echo and 3D CASPR, respectively). CONCLUSION: The CASPR view ordering with 3D TSE achieves robust arterial spin-labeled perfusion in the brain and kidneys because of the sampling of the center of k-space at the beginning of each echo train.

A nonhuman primate model of early Alzheimer's disease pathologic change: Implications for disease pathogenesis.

INTRODUCTION: Nonhuman primates may serve as excellent models of sporadic age-associated brain ß-amyloid deposition and Alzheimer's disease pathologic changes. We examined whether a vervet nonhuman primate model recapitulated pathologic, physiologic, and behavioral features of early Alzheimer's disease. METHODS: Nine middle-aged (mean = 11.2 years) and nine aged (mean = 21.7 years) female vervet/African green monkeys underwent cerebrospinal fluid collection, gait speed measurement, and neuroimaging before neuropathologic assessment. RESULTS: ß-amyloid plaques were identified in all aged vervets and paired helical filament tau immunoreactivity was observed in all animals. Cerebrospinal fluid ß-amyloid42 and gait speed correlated negatively with age and plaque density. Greater plaque and paired helical filament tau burden predicted reduced volumes and CMRg in several brain regions. DISCUSSION: We observed a coordinated set of relationships among neuropathologic, cerebrospinal fluid, imaging, and behavioral modalities consistent with early Alzheimer's disease. Our results support future use of the vervet model to explore disease mechanisms, biomarkers, and novel therapeutic strategies.

Exome Chip Analysis Identifies Low-Frequency and Rare Variants in MRPL38 for White Matter Hyperintensities on Brain Magnetic Resonance Imaging.

Background and Purpose- White matter hyperintensities (WMH) on brain magnetic resonance imaging are typical signs of cerebral small vessel disease and may indicate various preclinical, age-related neurological disorders, such as stroke. Though WMH are highly heritable, known common variants explain a small proportion of the WMH variance. The contribution of low-frequency/rare coding variants to WMH burden has not been explored. Methods- In the discovery sample we recruited 20 719 stroke/dementia-free adults from 13 population-based cohort studies within the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, among which 17 790 were of European ancestry and 2929 of African ancestry. We genotyped these participants at ≈250 000 mostly exonic variants with Illumina HumanExome BeadChip arrays. We performed ethnicity-specific linear regression on rank-normalized WMH in each study separately, which were then combined in meta-analyses to test for association with single variants and genes aggregating the effects of putatively functional low-frequency/rare variants. We then sought replication of the top findings in 1192 adults (European ancestry) with whole exome/genome sequencing data from 2 independent studies. Results- At 17q25, we confirmed the association of multiple common variants in TRIM65, FBF1, and ACOX1 ( P<6×10-7). We also identified a novel association with 2 low-frequency nonsynonymous variants in MRPL38 (lead, rs34136221; PEA=4.5×10-8) partially independent of known common signal ( PEA(conditional)=1.4×10-3). We further identified a locus at 2q33 containing common variants in NBEAL1, CARF, and WDR12 (lead, rs2351524; Pall=1.9×10-10). Although our novel findings were not replicated because of limited power and possible differences in study design, meta-analysis of the discovery and replication samples yielded stronger association for the 2 low-frequency MRPL38 variants ( Prs34136221=2.8×10-8). Conclusions- Both common and low-frequency/rare functional variants influence WMH. Larger replication and experimental follow-up are essential to confirm our findings and uncover the biological causal mechanisms of age-related WMH.

Microstructural correlates of 3D steady-state inhomogeneous magnetization transfer (ihMT) in the human brain white matter assessed by myelin water imaging and diffusion tensor imaging.

PURPOSE: To compare the recently introduced inhomogeneous magnetization transfer (ihMT) technique with more established MRI techniques including myelin water imaging (MWI) and diffusion tensor imaging (DTI), and to evaluate the microstructural attributes correlating with this new contrast method in the human brain white matter. METHODS: Eight adult healthy volunteers underwent T1 -weighted, ihMT, MWI, and DTI imaging on a 3T human scanner. The ihMT ratio (ihMTR), myelin water fraction (MWF), fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity (AD), and mean diffusivity (MD) values were calculated from different white matter tracts. The angle ( θ ) between the directions of the principal eigenvector, as measured by DTI, and the main magnetic field was calculated for all voxels from various fiber tracts. The ihMTR was correlated with MWF and DTI metrics. RESULTS: A strong correlation was found between ihMTR and MWF (ρ = 0.77, P < 0.0001). This was followed by moderate to weak correlations between ihMTR and DTI metrics: RD (ρ = -0.30, P < 0.0001), FA (ρ = 0.20, P < 0.0001), MD (ρ = -0.19, P < 0.0001), AD (ρ = 0.02, P < 0.0001). A strong correlation was found between ihMTR and θ (ρ = -0.541, P < 0.0001). CONCLUSION: The strong correlation with myelin water imaging and its low coefficient of variation suggest that ihMT has the potential to become a new structural imaging marker of myelin. The substantial orientational dependence of ihMT should be taken into account when evaluating and quantitatively interpreting ihMT results.

Blood-based bioenergetic profiling is related to differences in brain morphology in African Americans with Type 2 diabetes.

Blood-based bioenergetic profiling has promising applications as a minimally invasive biomarker of systemic bioenergetic capacity. In the present study, we examined peripheral blood mononuclear cell (PBMC) mitochondrial function and brain morphology in a cohort of African Americans with long-standing Type 2 diabetes. Key parameters of PBMC respiration were correlated with white matter, gray matter, and total intracranial volumes. Our analyses indicate that these relationships are primarily driven by the relationship of systemic bioenergetic capacity with total intracranial volume, suggesting that systemic differences in mitochondrial function may play a role in overall brain morphology.

Associations of Early Kidney Disease With Brain Magnetic Resonance Imaging and Cognitive Function in African Americans With Type 2 Diabetes Mellitus.

BACKGROUND: Relationships between early kidney disease, neurocognitive function, and brain anatomy are poorly defined in African Americans with type 2 diabetes mellitus (T2DM). STUDY DESIGN: Cross-sectional associations were assessed between cerebral anatomy and cognitive performance with estimated glomerular filtration rate (eGFR) and urine albumin-creatinine ratio (UACR) in African Americans with T2DM. SETTING & PARTICIPANTS: African Americans with cognitive testing and cerebral magnetic resonance imaging (MRI) in the African American-Diabetes Heart Study Memory in Diabetes (AA-DHS MIND; n=512; 480 with MRI) and Action to Control Cardiovascular Risk in Diabetes (ACCORD) MIND (n=484; 104 with MRI) studies. PREDICTORS: eGFR (CKD-EPI creatinine equation), spot UACR. MEASUREMENTS: MRI-based cerebral white matter volume (WMV), gray matter volume (GMV), and white matter lesion volume; cognitive performance (Mini-Mental State Examination, Digit Symbol Coding, Stroop Test, and Rey Auditory Verbal Learning Test). Multivariable models adjusted for age, sex, body mass index, scanner, intracranial volume, education, diabetes duration, hemoglobin A1c concentration, low-density lipoprotein cholesterol concentration, smoking, hypertension, and cardiovascular disease were used to test for associations between kidney phenotypes and the brain in each study; a meta-analysis was performed. RESULTS: Mean participant age was 60.1±7.9 (SD) years; diabetes duration, 12.1±7.7 years; hemoglobin A1c concentration, 8.3%±1.7%; eGFR, 88.7±21.6mL/min/1.73m2; and UACR, 119.2±336.4mg/g. In the fully adjusted meta-analysis, higher GMV associated with lower UACR (P<0.05), with a trend toward association with higher eGFR. Higher white matter lesion volume was associated with higher UACR (P<0.05) and lower eGFR (P<0.001). WMV was not associated with either kidney parameter. Higher UACR was associated with lower Digit Symbol Coding performance (P<0.001) and a trend toward association with higher Stroop interference; eGFR was not associated with cognitive tests. LIMITATIONS: Cross-sectional; single UACR measurement. CONCLUSIONS: In African Americans with T2DM, mildly high UACR and mildly low eGFR were associated with smaller GMV and increased white matter lesion volume. UACR was associated with poorer processing speed and working memory.

APOL1 renal-risk variants associate with reduced cerebral white matter lesion volume and increased gray matter volume.

To assess apolipoprotein L1 gene (APOL1) renal-risk-variant effects on the brain, magnetic resonance imaging (MRI)-based cerebral volumes and cognitive function were assessed in 517 African American-Diabetes Heart Study (AA-DHS) Memory IN Diabetes (MIND) and 2568 hypertensive African American Systolic Blood Pressure Intervention Trial (SPRINT) participants without diabetes. Within these cohorts, 483 and 197 had cerebral MRI, respectively. AA-DHS participants were characterized as follows: 60.9% female, mean age of 58.6 years, diabetes duration 13.1 years, estimated glomerular filtration rate of 88.2 ml/min/1.73 m(2), and a median spot urine albumin to creatinine ratio of 10.0 mg/g. In additive genetic models adjusting for age, sex, ancestry, scanner, intracranial volume, body mass index, hemoglobin A1c, statins, nephropathy, smoking, hypertension, and cardiovascular disease, APOL1 renal-risk-variants were positively associated with gray matter volume (ß = 3.4 × 10(-3)) and negatively associated with white matter lesion volume (ß = -0.303) (an indicator of cerebral small vessel disease) and cerebrospinal fluid volume (ß= -30707) (all significant), but not with white matter volume or cognitive function. Significant associations corresponding to adjusted effect sizes (ß/SE) were observed with gray matter volume (0.16) and white matter lesion volume (-0.208), but not with cerebrospinal fluid volume (-0.251). Meta-analysis results with SPRINT Memory and Cognition in Decreased Hypertension (MIND) participants who had cerebral MRI were confirmatory. Thus, APOL1 renal-risk-variants are associated with larger gray matter volume and lower white matter lesion volume suggesting lower intracranial small vessel disease.

Subconcussive Head Impact Exposure and White Matter Tract Changes over a Single Season of Youth Football.

Purpose To examine the effects of subconcussive impacts resulting from a single season of youth (age range, 8-13 years) football on changes in specific white matter (WM) tracts as detected with diffusion-tensor imaging in the absence of clinically diagnosed concussions. Materials and Methods Head impact data were recorded by using the Head Impact Telemetry system and quantified as the combined-probability risk-weighted cumulative exposure (RWECP). Twenty-five male participants were evaluated for seasonal fractional anisotropy (FA) changes in specific WM tracts: the inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus, and superior longitudinal fasciculus (SLF). Fiber tracts were segmented into a central core and two fiber terminals. The relationship between seasonal FA change in the whole fiber, central core, and the fiber terminals with RWECP was also investigated. Linear regression analysis was conducted to determine the association between RWECP and change in fiber tract FA during the season. Results There were statistically significant linear relationships between RWEcp and decreased FA in the whole (R2 = 0.433; P = .003), core (R2 = 0.3649; P = .007), and terminals (R2 = 0.5666; P < .001) of left IFOF. A trend toward statistical significance (P = .08) in right SLF was observed. A statistically significant correlation between decrease in FA of the right SLF terminal and RWECP was also observed (R2 = 0.2893; P = .028). Conclusion This study found a statistically significant relationship between head impact exposure and change of FA fractional anisotropy value of whole, core, and terminals of left IFOF and right SLF's terminals where WM and gray matter intersect, in the absence of a clinically diagnosed concussion. © RSNA, 2016.

Evaluation of morphological changes in the adult skull with age and sex.

The morphology of the brain and skull are important in the evaluation of the aging human; however, little is known about how the skull may change with age. The objective of this study was to evaluate the morphological changes of the adult skull using three-dimensional geometric morphometric analysis of thousands of landmarks with the focus on anatomic regions that may be correlated with brain atrophy and head injury. Computed tomography data were collected between ages 20 and 100. Each scan was segmented using thresholding techniques. An atlas image of a 50th percentile skull was registered to each subject scan by computing a series of rigid, affine, and non-linear transformations between atlas space and subject space. Landmarks on the atlas skull were transformed to each subject and partitioned into the inner and outer cranial vault and the cranial fossae. A generalized Procrustes analysis was completed for the landmark sets. The coordinate locations describing the shape of each region were regressed with age to generate a model predicting the landmark location with age. Permutation testing was performed to assess significant changes with age. For the males, all anatomic regions reveal significant changes in shape with age except for the posterior cranial fossa. For the females, only the middle cranial fossa and anterior cranial fossa were found to change significantly in shape. Results of this study are important for understanding the adult skull and how shape changes may pertain to brain atrophy, aging, and injury.

Relationships between Cognitive Performance, Neuroimaging and Vascular Disease: The DHS-MIND Study.

BACKGROUND: Type 2 diabetes mellitus increases the risk of cognitive decline and dementia, and elevated burdens of vascular disease are hypothesized to contribute to this risk. These relationships were examined in the Diabetes Heart Study-MIND using a battery of cognitive tests, neuroimaging measures and subclinical cardiovascular disease (CVD) burden assessed by coronary artery calcified (CAC) plaque. We hypothesized that CAC would attenuate the association between neuroimaging measures and cognition performance. METHODS: Associations were examined using marginal models in this family-based cohort of 572 European Americans from 263 families. All models were adjusted for age, gender, education, type 2 diabetes and hypertension, with some neuroimaging measures additionally adjusted for intracranial volume. RESULTS: Higher total brain volume was associated with better performance on the Digit Symbol Substitution Task and Semantic Fluency (both p ≤ 7.0 × 10(-4)). Higher gray matter volume was associated with better performance on the Modified Mini-Mental State Examination and Semantic Fluency (both p ≤ 9.0 × 10(-4)). Adjusting for CAC caused minimal changes to the results. CONCLUSIONS: Relationships exist between neuroimaging measures and cognitive performance in a type 2 diabetes-enriched European American cohort. Associations were minimally attenuated after adjusting for subclinical CVD. Additional work is needed to understand how subclinical CVD burden interacts with other factors and impacts relationships between neuroimaging and cognitive testing measures.

Structural and functional assessment of the brain in European Americans with mild-to-moderate kidney disease: Diabetes Heart Study-MIND.

BACKGROUND: Advanced chronic kidney disease (CKD) is associated with altered cerebral structure and function. Relationships between mild-to-moderate CKD and brain morphology and cognitive performance were evaluated in European Americans (EAs). METHODS: A total of 478 EAs with estimated glomerular filtration rate (eGFR) >45 mL/min/1.73 m(2) and urine albumin:creatinine ratio (UACR) < 300 mg/g, most with type 2 diabetes (T2D), were included. Measures of total intracranial volume (TICV), cerebrospinal fluid volume, total white matter volume (TWMV), total gray matter volume (TGMV), total white matter lesion volume (TWMLV), hippocampal white matter volume (HWMV) and hippocampal gray matter volume (HGMV) were obtained with magnetic resonance imaging. Cognitive testing included memory (Rey Auditory Visual Learning Test), global cognition (Modified Mini-Mental State Examination) and executive function (Stroop Task, Semantic Fluency, Digit Symbol Substitution Test). Associations with CKD were assessed using log-transformed eGFR and UACR, adjusted for age, sex, body mass index, smoking, hemoglobin A1c, blood pressure, diabetes duration, cardiovascular disease and education. RESULTS: Participants were 55.2% female, 78.2% had T2D; mean ± SD age 67.6 ± 9.0 years, T2D duration 16.4 ± 6.5 years, eGFR 92.0 ± 22.3 mL/min/1.73 m(2) and UACR 23.8 ± 39.6 mg/g. In adjusted models, eGFR was negatively associated with TICV only in participants with T2D [parameter estimate (ß): -72.2, P = 0.002]. In non-diabetic participants, inverse relationships were observed between eGFR and HGMV (ß: -1.0, P = 0.03) and UACR and normalized TWMLV (ß: -0.2, P = 0.03). Kidney function and albuminuria did not correlate with cognitive testing. CONCLUSIONS: In EAs with mild CKD enriched for T2D, brain structure and cognitive performance were generally not impacted. Longitudinal studies are necessary to determine when cerebral structural changes and cognitive dysfunction develop with progressive CKD in EAs.

Graph theoretical analysis of resting-state MEG data: Identifying interhemispheric connectivity and the default mode.

Interhemispheric connectivity with resting state MEG has been elusive, and demonstration of the default mode network (DMN) yet more challenging. Recent seed-based MEG analyses have shown interhemispheric connectivity using power envelope correlations. The purpose of this study is to compare graph theoretic maps of brain connectivity generated using MEG with and without signal leakage correction to evaluate for the presence of interhemispheric connectivity. Eight minutes of resting state eyes-open MEG data were obtained in 22 normal male subjects enrolled in an IRB-approved study (ages 16-18). Data were processed using an in-house automated MEG processing pipeline and projected into standard (MNI) source space at 7mm resolution using a scalar beamformer. Mean beta-band amplitude was sampled at 2.5second epochs from the source space time series. Leakage correction was performed in the time domain of the source space beam formed signal prior to amplitude transformation. Graph theoretic voxel-wise source space correlation connectivity analysis was performed for leakage corrected and uncorrected data. Degree maps were thresholded across subjects for the top 20% of connected nodes to identify hubs. Additional degree maps for sensory, visual, motor, and temporal regions were generated to identify interhemispheric connectivity using laterality indices. Hubs for the uncorrected MEG networks were predominantly symmetric and midline, bearing some resemblance to fMRI networks. These included the cingulate cortex, bilateral inferior frontal lobes, bilateral hippocampal formations and bilateral cerebellar hemispheres. These uncorrected networks however, demonstrated little to no interhemispheric connectivity using the ROI-based degree maps. Leakage corrected MEG data identified the DMN, with hubs in the posterior cingulate and biparietal areas. These corrected networks demonstrated robust interhemispheric connectivity for the ROI-based degree maps. Graph theoretic analysis of MEG resting state data without signal leakage correction can demonstrate symmetric networks with some resemblance to fMRI networks. These networks however, are an artifact of high local correlation from signal leakage and lack interhemispheric connectivity. Following signal leakage correction, MEG hubs emerge in the DMN, with strong interhemispheric connectivity.

Rapid-onset dystonia-parkinsonism associated with the I758S mutation of the ATP1A3 gene: a neuropathologic and neuroanatomical study of four siblings.

Rapid-onset dystonia-parkinsonism (RDP) is a movement disorder associated with mutations in the ATP1A3 gene. Signs and symptoms of RDP commonly occur in adolescence or early adulthood and can be triggered by physical or psychological stress. Mutations in ATP1A3 are also associated with alternating hemiplegia of childhood (AHC). The neuropathologic substrate of these conditions is unknown. The central nervous system of four siblings, three affected by RDP and one asymptomatic, all carrying the I758S mutation in the ATP1A3 gene, was analyzed. This neuropathologic study is the first carried out in ATP1A3 mutation carriers, whether affected by RDP or AHC. Symptoms began in the third decade of life for two subjects and in the fifth for another. The present investigation aimed at identifying, in mutation carriers, anatomical areas potentially affected and contributing to RDP pathogenesis. Comorbid conditions, including cerebrovascular disease and Alzheimer disease, were evident in all subjects. We evaluated areas that may be relevant to RDP separately from those affected by the comorbid conditions. Anatomical areas identified as potential targets of I758S mutation were globus pallidus, subthalamic nucleus, red nucleus, inferior olivary nucleus, cerebellar Purkinje and granule cell layers, and dentate nucleus. Involvement of subcortical white matter tracts was also evident. Furthermore, in the spinal cord, a loss of dorsal column fibers was noted. This study has identified RDP-associated pathology in neuronal populations, which are part of complex motor and sensory loops. Their involvement would cause an interruption of cerebral and cerebellar connections which are essential for maintenance of motor control.

Kidney disease and cognitive function: African American-diabetes heart study MIND.

AIMS: Albuminuria and reduced estimated glomerular filtration rate (eGFR) are linked with poorer cognitive performance in European-ancestry populations with advanced nephropathy; relationships in African Americans (AAs) with type 2 diabetes (T2D) are less clear. Tests of cognitive performance, urine albumin:creatinine ratio (UACR), and CKD-EPI eGFR were performed in unrelated AAs with T2D to determine relationships. METHODS: Cross-sectional analysis of 263 unrelated AAs with T2D recruited in the African American-Diabetes Heart Study (AA-DHS) MIND. Global cognitive function (mini-mental state exam [3MSE] and Montreal Cognitive Assessment [MoCA]), memory (Rey Auditory Verbal Learning Test [RAVLT]), executive function (Stroop, verbal fluency for animals, and Digit Symbol Copy [DSC]), UACR, and eGFR were determined. Relationships between cognitive tests and renal parameters were assessed using multivariate models, adjusted for age, gender, body mass index, hemoglobin A1c, level of education, hypertension, and LDL cholesterol. RESULTS: Participants had a mean ± SD age of 60.2 ± 9.7 years, 62.7% were female, T2D duration was 14.3 ± 8.9 years, eGFR 86.0 ± 23.2 ml/min/1.73 m(2), and UACR 155.8 ± 542.1 (median 8.1) mg/g. In adjusted models, higher UACR was associated with worse 3MSE (p = 0.014), MoCA (p = 0.0089), DSC (p = 0.0004), Stroop performance time (p = 0.003), Stroop errors (p = 0.032), and Stroop interference (p = 0.026). Higher eGFR was associated with better performance on DSC (p = 0.0071). CONCLUSIONS: In AAs with T2D, albuminuria and eGFR were associated with cognitive function, even in mild kidney disease. These data stress the need for interventions to prevent cognitive decline well before the late stages of kidney disease.

Simultaneous MEG and EEG source imaging of electrophysiological activity in response to acute transcranial photobiomodulation.

Introduction: Transcranial photobiomodulation (tPBM) is a non-invasive neuromodulation technique that improves human cognition. The effects of tPBM of the right forehead on neurophysiological activity have been previously investigated using EEG in sensor space. However, the spatial resolution of these studies is limited. Magnetoencephalography (MEG) is known to facilitate a higher spatial resolution of brain source images. This study aimed to image post-tPBM effects in brain space based on both MEG and EEG measurements across the entire human brain. Methods: MEG and EEG scans were concurrently acquired for 6 min before and after 8-min of tPBM delivered using a 1,064-nm laser on the right forehead of 25 healthy participants. Group-level changes in both the MEG and EEG power spectral density with respect to the baseline (pre-tPBM) were quantified and averaged within each frequency band in the sensor space. Constrained modeling was used to generate MEG and EEG source images of post-tPBM, followed by cluster-based permutation analysis for family wise error correction (p < 0.05). Results: The 8-min tPBM enabled significant increases in alpha (8-12 Hz) and beta (13-30 Hz) powers across multiple cortical regions, as confirmed by MEG and EEG source images. Moreover, tPBM-enhanced oscillations in the beta band were located not only near the stimulation site but also in remote cerebral regions, including the frontal, parietal, and occipital regions, particularly on the ipsilateral side. Discussion: MEG and EEG results shown in this study demonstrated that tPBM modulates neurophysiological activity locally and in distant cortical areas. The EEG topographies reported in this study were consistent with previous observations. This study is the first to present MEG and EEG evidence of the electrophysiological effects of tPBM in the brain space, supporting the potential utility of tPBM in treating neurological diseases through the modulation of brain oscillations.

Magnetoencephalography (MEG) Data Processing in Epilepsy Patients with Implanted Responsive Neurostimulation (RNS) Devices.

Drug-resistant epilepsy (DRE) is often treated with surgery or neuromodulation. Specifically, responsive neurostimulation (RNS) is a widely used therapy that is programmed to detect abnormal brain activity and intervene with tailored stimulation. Despite the success of RNS, some patients require further interventions. However, having an RNS device in situ is a hindrance to the performance of neuroimaging techniques. Magnetoencephalography (MEG), a non-invasive neurophysiologic and functional imaging technique, aids epilepsy assessment and surgery planning. MEG performed post-RNS is complicated by signal distortions. This study proposes an independent component analysis (ICA)-based approach to enhance MEG signal quality, facilitating improved assessment for epilepsy patients with implanted RNS devices. Three epilepsy patients, two with RNS implants and one without, underwent MEG scans. Preprocessing included temporal signal space separation (tSSS) and an automated ICA-based approach with MNE-Python. Power spectral density (PSD) and signal-to-noise ratio (SNR) were analyzed, and MEG dipole analysis was conducted using single equivalent current dipole (SECD) modeling. The ICA-based noise removal preprocessing method substantially improved the signal-to-noise ratio (SNR) for MEG data from epilepsy patients with implanted RNS devices. Qualitative assessment confirmed enhanced signal readability and improved MEG dipole analysis. ICA-based processing markedly enhanced MEG data quality in RNS patients, emphasizing its clinical relevance.

Synthesizing Contrast-Enhanced MR Images from Noncontrast MR Images Using Deep Learning.

BACKGROUND AND PURPOSE: Recent developments in deep learning methods offer a potential solution to the need for alternative imaging methods due to concerns about the toxicity of gadolinium-based contrast agents. The purpose of the study was to synthesize virtual gadolinium contrast-enhanced T1-weighted MR images from noncontrast multiparametric MR images in patients with primary brain tumors by using deep learning. MATERIALS AND METHODS: We trained and validated a deep learning network by using MR images from 335 subjects in the Brain Tumor Segmentation Challenge 2019 training data set. A held out set of 125 subjects from the Brain Tumor Segmentation Challenge 2019 validation data set was used to test the generalization of the model. A residual inception DenseNet network, called T1c-ET, was developed and trained to simultaneously synthesize virtual contrast-enhanced T1-weighted (vT1c) images and segment the enhancing portions of the tumor. Three expert neuroradiologists independently scored the synthesized vT1c images by using a 3-point Likert scale, evaluating image quality and contrast enhancement against ground truth T1c images (1 = poor, 2 = good, 3 = excellent). RESULTS: The synthesized vT1c images achieved structural similarity index, peak signal-to-noise ratio, and normalized mean square error scores of 0.91, 64.35, and 0.03, respectively. There was moderate interobserver agreement between the 3 raters, regarding the algorithm's performance in predicting contrast enhancement, with a Fleiss kappa value of 0.61. Our model was able to accurately predict contrast enhancement in 88.8% of the cases (scores of 2 to 3 on the 3-point scale). CONCLUSIONS: We developed a novel deep learning architecture to synthesize virtual postcontrast enhancement by using only conventional noncontrast brain MR images. Our results demonstrate the potential of deep learning methods to reduce the need for gadolinium contrast in the evaluation of primary brain tumors.