Auditory cues reveal intended movement information in middle frontal gyrus neuronal ensemble activity of a person with tetraplegia.

Intracortical brain-computer interfaces (iBCIs) allow people with paralysis to directly control assistive devices using neural activity associated with the intent to move. Realizing the full potential of iBCIs critically depends on continued progress in understanding how different cortical areas contribute to movement control. Here we present the first comparison between neuronal ensemble recordings from the left middle frontal gyrus (MFG) and precentral gyrus (PCG) of a person with tetraplegia using an iBCI. As expected, PCG was more engaged in selecting and generating intended movements than in earlier perceptual stages of action planning. By contrast, MFG displayed movement-related information during the sensorimotor processing steps preceding the appearance of the action plan in PCG, but only when the actions were instructed using auditory cues. These results describe a previously unreported function for neurons in the human left MFG in auditory processing contributing to motor control.

Regionally specific TSC1 and TSC2 gene expression in tuberous sclerosis complex.

Tuberous sclerosis complex (TSC), a heritable neurodevelopmental disorder, is caused by mutations in the TSC1 or TSC2 genes. To date, there has been little work to elucidate regional TSC1 and TSC2 gene expression within the human brain, how it changes with age, and how it may influence disease. Using a publicly available microarray dataset, we found that TSC1 and TSC2 gene expression was highest within the adult neo-cerebellum and that this pattern of increased cerebellar expression was maintained throughout postnatal development. During mid-gestational fetal development, however, TSC1 and TSC2 expression was highest in the cortical plate. Using a bioinformatics approach to explore protein and genetic interactions, we confirmed extensive connections between TSC1/TSC2 and the other genes that comprise the mammalian target of rapamycin (mTOR) pathway, and show that the mTOR pathway genes with the highest connectivity are also selectively expressed within the cerebellum. Finally, compared to age-matched controls, we found increased cerebellar volumes in pediatric TSC patients without current exposure to antiepileptic drugs. Considered together, these findings suggest that the cerebellum may play a central role in TSC pathogenesis and may contribute to the cognitive impairment, including the high incidence of autism spectrum disorder, observed in the TSC population.

Shared genetic risk between corticobasal degeneration, progressive supranuclear palsy, and frontotemporal dementia.

Corticobasal degeneration (CBD), progressive supranuclear palsy (PSP) and a subset of frontotemporal dementia (FTD) are neurodegenerative disorders characterized by tau inclusions in neurons and glia (tauopathies). Although clinical, pathological and genetic evidence suggests overlapping pathobiology between CBD, PSP, and FTD, the relationship between these disorders is still not well understood. Using summary statistics (odds ratios and p values) from large genome-wide association studies (total n = 14,286 cases and controls) and recently established genetic methods, we investigated the genetic overlap between CBD and PSP and CBD and FTD. We found up to 800-fold enrichment of genetic risk in CBD across different levels of significance for PSP or FTD. In addition to NSF (tagging the MAPT H1 haplotype), we observed that SNPs in or near MOBP, CXCR4, EGFR, and GLDC showed significant genetic overlap between CBD and PSP, whereas only SNPs tagging the MAPT haplotype overlapped between CBD and FTD. The risk alleles of the shared SNPs were associated with expression changes in cis-genes. Evaluating transcriptome levels across adult human brains, we found a unique neuroanatomic gene expression signature for each of the five overlapping gene loci (omnibus ANOVA p < 2.0 × 10-16). Functionally, we found that these shared risk genes were associated with protein interaction and gene co-expression networks and showed enrichment for several neurodevelopmental pathways. Our findings suggest: (1) novel genetic overlap between CBD and PSP beyond the MAPT locus; (2) strong ties between CBD and FTD through the MAPT clade, and (3) unique combinations of overlapping genes that may, in part, influence selective regional or neuronal vulnerability observed in specific tauopathies.

Within-subject template estimation for unbiased longitudinal image analysis.

Longitudinal image analysis has become increasingly important in clinical studies of normal aging and neurodegenerative disorders. Furthermore, there is a growing appreciation of the potential utility of longitudinally acquired structural images and reliable image processing to evaluate disease modifying therapies. Challenges have been related to the variability that is inherent in the available cross-sectional processing tools, to the introduction of bias in longitudinal processing and to potential over-regularization. In this paper we introduce a novel longitudinal image processing framework, based on unbiased, robust, within-subject template creation, for automatic surface reconstruction and segmentation of brain MRI of arbitrarily many time points. We demonstrate that it is essential to treat all input images exactly the same as removing only interpolation asymmetries is not sufficient to remove processing bias. We successfully reduce variability and avoid over-regularization by initializing the processing in each time point with common information from the subject template. The presented results show a significant increase in precision and discrimination power while preserving the ability to detect large anatomical deviations; as such they hold great potential in clinical applications, e.g. allowing for smaller sample sizes or shorter trials to establish disease specific biomarkers or to quantify drug effects.

The dynamics of cortical and hippocampal atrophy in Alzheimer disease.

OBJECTIVE: To characterize rates of regional Alzheimer disease (AD)-specific brain atrophy across the presymptomatic, mild cognitive impairment, and dementia stages. DESIGN: Multicenter case-control study of neuroimaging, cerebrospinal fluid, and cognitive test score data from the Alzheimer's Disease Neuroimaging Initiative. SETTING: Research centers across the United States and Canada. PATIENTS: We examined a total of 317 participants with baseline cerebrospinal fluid biomarker measurements and 3 T1-weighted magnetic resonance images obtained within 1 year. MAIN OUTCOME MEASURES: We used automated tools to compute annual longitudinal atrophy in the hippocampus and cortical regions targeted in AD. We used Mini-Mental State Examination scores as a measure of cognitive performance. We performed a cross-subject analysis of atrophy rates and acceleration on individuals with an AD-like cerebrospinal fluid molecular profile. RESULTS: In presymptomatic individuals harboring indicators of AD, baseline thickness in AD-vulnerable cortical regions was significantly reduced compared with that of healthy control individuals, but baseline hippocampal volume was not. Across the clinical spectrum, rates of AD-specific cortical thinning increased with decreasing cognitive performance before peaking at approximately the Mini-Mental State Examination score of 21, beyond which rates of thinning started to decline. Annual rates of hippocampal volume loss showed a continuously increasing pattern with decreasing cognitive performance as low as the Mini-Mental State Examination score of 15. Analysis of the second derivative of imaging measurements revealed that AD-specific cortical thinning exhibited early acceleration followed by deceleration. Conversely, hippocampal volume loss exhibited positive acceleration across all study participants. CONCLUSIONS: Alzheimer disease-specific cortical thinning and hippocampal volume loss are consistent with a sigmoidal pattern, with an acceleration phase during the early stages of the disease. Clinical trials should carefully consider the nonlinear behavior of these AD biomarkers.

Selective disruption of the cerebral neocortex in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) and its transitional state mild cognitive impairment (MCI) are characterized by amyloid plaque and tau neurofibrillary tangle (NFT) deposition within the cerebral neocortex and neuronal loss within the hippocampal formation. However, the precise relationship between pathologic changes in neocortical regions and hippocampal atrophy is largely unknown. METHODOLOGY/PRINCIPAL FINDINGS: In this study, combining structural MRI scans and automated image analysis tools with reduced cerebrospinal fluid (CSF) Aß levels, a surrogate for intra-cranial amyloid plaques and elevated CSF phosphorylated tau (p-tau) levels, a surrogate for neocortical NFTs, we examined the relationship between the presence of Alzheimer's pathology, gray matter thickness of select neocortical regions, and hippocampal volume in cognitively normal older participants and individuals with MCI and AD (n = 724). Amongst all 3 groups, only select heteromodal cortical regions significantly correlated with hippocampal volume. Amongst MCI and AD individuals, gray matter thickness of the entorhinal cortex and inferior temporal gyrus significantly predicted longitudinal hippocampal volume loss in both amyloid positive and p-tau positive individuals. Amongst cognitively normal older adults, thinning only within the medial portion of the orbital frontal cortex significantly differentiated amyloid positive from amyloid negative individuals whereas thinning only within the entorhinal cortex significantly discriminated p-tau positive from p-tau negative individuals. CONCLUSIONS/SIGNIFICANCE: Cortical Aß and tau pathology affects gray matter thinning within select neocortical regions and potentially contributes to downstream hippocampal degeneration. Neocortical Alzheimer's pathology is evident even amongst older asymptomatic individuals suggesting the existence of a preclinical phase of dementia.

Automated MRI measures predict progression to Alzheimer's disease.

The prediction of individuals with mild cognitive impairment (MCI) destined to develop Alzheimer's disease (AD) is of increasing clinical importance. In this study, using baseline T1-weighted MRI scans of 324 MCI individuals from two cohorts and automated software tools, we employed factor analyses and Cox proportional hazards models to identify a set of neuroanatomic measures that best predicted the time to progress from MCI to AD. For comparison, cerebrospinal fluid (CSF) assessments of cellular pathology and positron emission tomography (PET) measures of metabolic activity were additionally examined. By 3 years follow-up, 60 MCI individuals from the first cohort and 58 MCI individuals from the second cohort had progressed to a diagnosis of AD. Cox models on the first cohort demonstrated significant effects for the medial temporal factor [Hazards Ratio (HR) = 0.43{95% confidence interval (CI), 0.32-0.55}, p < 0.0001], the fronto-parietoccipital factor [HR = 0.59{95% CI, 0.48-0.80}, p < 0.001], and the lateral temporal factor [HR = 0.67 {95% CI, 0.52-0.87}, p < 0.01]. When applied to the second cohort, these Cox models showed significant effects for the medial temporal factor [HR = 0.44 {0.32-0.61}, p < 0.001] and lateral temporal factor [HR = 0.49 {0.38-0.62}, p < 0.001]. In a combined Cox model, consisting of individual CSF, PET, and MRI measures that best predicted disease progression, only the medial temporal factor [HR = 0.53 {95% CI, 0.34-0.81}, p < 0.001] demonstrated a significant effect. These findings illustrate that automated MRI measures of the medial temporal cortex accurately and reliably predict time to disease progression, outperform cellular and metabolic measures as predictors of clinical decline, and can potentially serve as a predictive marker for AD.

Automated MRI measures identify individuals with mild cognitive impairment and Alzheimer's disease.

Mild cognitive impairment can represent a transitional state between normal ageing and Alzheimer's disease. Non-invasive diagnostic methods are needed to identify mild cognitive impairment individuals for early therapeutic interventions. Our objective was to determine whether automated magnetic resonance imaging-based measures could identify mild cognitive impairment individuals with a high degree of accuracy. Baseline volumetric T1-weighted magnetic resonance imaging scans of 313 individuals from two independent cohorts were examined using automated software tools to identify the volume and mean thickness of 34 neuroanatomic regions. The first cohort included 49 older controls and 48 individuals with mild cognitive impairment, while the second cohort included 94 older controls and 57 mild cognitive impairment individuals. Sixty-five patients with probable Alzheimer's disease were also included for comparison. For the discrimination of mild cognitive impairment, entorhinal cortex thickness, hippocampal volume and supramarginal gyrus thickness demonstrated an area under the curve of 0.91 (specificity 94%, sensitivity 74%, positive likelihood ratio 12.12, negative likelihood ratio 0.29) for the first cohort and an area under the curve of 0.95 (specificity 91%, sensitivity 90%, positive likelihood ratio 10.0, negative likelihood ratio 0.11) for the second cohort. For the discrimination of Alzheimer's disease, these three measures demonstrated an area under the curve of 1.0. The three magnetic resonance imaging measures demonstrated significant correlations with clinical and neuropsychological assessments as well as with cerebrospinal fluid levels of tau, hyperphosphorylated tau and abeta 42 proteins. These results demonstrate that automated magnetic resonance imaging measures can serve as an in vivo surrogate for disease severity, underlying neuropathology and as a non-invasive diagnostic method for mild cognitive impairment and Alzheimer's disease.