Regional White Matter Integrity Differentiates Between Vascular Dementia and Alzheimer Disease

BACKGROUND AND PURPOSE: Considerable clinical and radiological overlap between vascular dementia (VaD) and Alzheimer disease (AD) often makes the diagnosis difficult. Diffusion-tensor imaging studies showed that fractional anisotropy (FA) could be a useful marker for white matter changes. This study aimed to identify regional FA changes to identify a biomarker that could be used to differentiate VaD from AD. METHODS: T1-weighted and diffusion-tensor imaging scans were obtained in 13 VaD patients, 16 AD patients, and 22 healthy elderly controls. We used tract-based spatial statistics to study regional changes in fractional anisotropy in AD, VaD, and elderly controls. We then used probabilistic tractography to parcel the corpus callosum in 7 regions according to its connectivity with major cerebral cortices using diffusion-tensor imaging data set. We compared the volume and mean FA in each set of transcallosal fibers between groups using ANOVA and then applied a discriminant analysis based on FA and T2-weighted imaging measures. RESULTS: FA reduction in forceps minor was the most significant area of difference between AD and VaD. Segmentation of the corpus callosum using tractography and comparison of FA changes of each segment confirmed the FA changes in transcallosal prefrontal tracts of patients with VaD when compared to AD. The best discriminant model was the combination of transcallosal prefrontal FA and Fazekas score with 87.5% accuracy, 100% specificity, and 93% sensitivity (P<0.0001). CONCLUSIONS: Integrating mean FA in the forceps minor to the Fazekas score provides a useful quantitative marker for differentiating AD from VaD

Statistical Learning for Resting-State fMRI: Successes and Challenges

International audienceIn the absence of external stimuli, fluctuations in cerebral activity can be used to reveal intrinsic structures. Well-conditioned probabilistic models of this so-called resting-state activity are needed to support neuroscientific hypotheses. Exploring two specific descriptions of resting-state fMRI, namely spatial analysis and connectivity graphs, we discuss the progress brought by statistical learning techniques, but also the neuroscientific picture that they paint, and possible modeling pitfalls

Subjective memory complaints are associated with brain activation supporting successful memory encoding

Neuro Imaging Researc

A Novel Sparse Graphical Approach for Multimodal Brain Connectivity Inference

International audienceDespite the clear potential benefits of combining fMRI and diffusion MRI in learning the neural pathways that underlie brain functions, little methodological progress has been made in this direction. In this paper, we propose a novel multimodal integration approach based on sparse Gaussian graphical model for estimating brain connectivity. Casting functional connectivity estimation as a sparse inverse covariance learning problem, we adapt the level of sparse penalization on each connection based on its anatomical capacity for functional interactions. Functional connections with little anatomical support are thus more heavily penalized. For validation, we showed on real data collected from a cohort of 60 subjects that additionally modeling anatomical capacity significantly increases subject consistency in the detected connection patterns. Moreover, we demonstrated that incorporating a connectivity prior learned with our multimodal connectivity estimation approach improves activation detection

Deriving a multi-subject functional-connectivity atlas to inform connectome estimation

MICCAI 2014 preprintInternational audienceThe estimation of functional connectivity structure from functional neuroimaging data is an important step toward understanding the mechanisms of various brain diseases and building relevant biomarkers. Yet, such inferences have to deal with the low signal-to-noise ratio and the paucity of the data. With at our disposal a steadily growing volume of publicly available neuroimaging data, it is however possible to improve the estimation procedures involved in connectome mapping. In this work, we propose a novel learning scheme for functional connectivity based on sparse Gaussian graphical models that aims at minimizing the bias induced by the regularization used in the estimation, by carefully separating the estimation of the model support from the coefficients. Moreover, our strategy makes it possible to include new data with a limited computational cost. We illustrate the physiological relevance of the learned prior, that can be identified as a functional connectivity atlas, based on an experiment on 46 subjects of the Human Connectome Dataset

Glucocorticoids decrease hippocampal and prefrontal activation during declarative memory retrieval in young men.

Multivariate analysis of psychological data - ou

White Matter Hyperintensities and Apolipoprotein E Affect the Association Between Mean Arterial Pressure and Objective and Subjective Cognitive Functioning in Older Adults

Background: White matter hyperintensities (WMH) show a robust relationship with arterial pressure as well as objective and subjective cognitive functioning. In addition, APOE epsilon 4 carriership may influence how arterial pressure affects cognitive functioning.Objective: To determine the role of region-specific WMH burden and APOE epsilon 4 carriership on the relationship between mean arterial pressure (MAP) and cognitive function as well as subjective cognitive decline (SCD).Methods: The sample consisted of 87 cognitively unimpaired middle-aged to older adults aged 50-85. We measured WMH volume for the whole brain, anterior thalamic radiation (ATR), forceps minor, and superior longitudinal fasciculus (SLF). We examined whether WMH burden mediated the relationship between MAP and cognition (i.e., TMT-A score for processing speed; Stroop performance for executive function) as well as SCD (i.e., Frequency of Forgetting (FoF)), and whether APOE epsilon 4 carriership moderated that mediation.Results: WMH burden within SLF mediated the effect of MAP on Stroop performance. Both whole brain and ATR WMH burden mediated the effect of MAP on FoF score. In the MAP-WMH-Stroop relationship, the mediation effect of SLFWMH and the effect of MAP on SLF WMH were significant only in APOE epsilon 4 carriers. In the MAP-WMH-FoF relationship, the effect of MAP on whole brain WMH burden was significant only in epsilon 4 carriers.Conclusion: WMH burden and APOE genotype explain the link between blood pressure and cognitive function and may enable a more accurate assessment of the effect of high blood pressure on cognitive decline and risk for dementia.Neuro Imaging Researc

Loss of 'Small-World' Networks in Alzheimer's Disease: Graph Analysis of fMRI Resting-State Functional Connectivity

Background: Local network connectivity disruptions in Alzheimer's disease patients have been found using graph analysis in BOLD fMRI. Other studies using MEG and cortical thickness measures, however, show more global long distance connectivity changes, both in functional and structural imaging data. The form and role of functional connectivity changes thus remains ambiguous. The current study shows more conclusive data on connectivity changes in early AD using graph analysis on resting-state condition fMRI data. Methodology/Principal Findings: 18 mild AD patients and 21 healthy age-matched control subjects without memory complaints were investigated in resting-state condition with MRI at 1.5 Tesla. Functional coupling between brain regions was calculated on the basis of pair-wise synchronizations between regional time-series. Local (cluster coefficient) and global (path length) network measures were quantitatively defined. Compared to controls, the characteristic path length of AD functional networks is closer to the theoretical values of random networks, while no significant differences were found in cluster coefficient. The whole-brain average synchronization does not differ between Alzheimer and healthy control groups. Post-hoc analysis of the regional synchronization reveals increased AD synchronization involving the frontal cortices and generalized decreases located at the parietal and occipital regions. This effectively translates in a global reduction of functional long-distance links between frontal and caudal brain regions. Conclusions/Significance: We present evidence of AD-induced changes in global brain functional connectivity specifically affecting long-distance connectivity. This finding is highly relevant for it supports the anterior-posterior disconnection theory and its role in AD. Our results can be interpreted as reflecting the randomization of the brain functional networks in AD, further suggesting a loss of global information integration in disease.Neuro Imaging Researc