87 research outputs found
Random walk with barriers: Diffusion restricted by permeable membranes
Restrictions to molecular motion by barriers (membranes) are ubiquitous in
biological tissues, porous media and composite materials. A major challenge is
to characterize the microstructure of a material or an organism
nondestructively using a bulk transport measurement. Here we demonstrate how
the long-range structural correlations introduced by permeable membranes give
rise to distinct features of transport. We consider Brownian motion restricted
by randomly placed and oriented permeable membranes and focus on the
disorder-averaged diffusion propagator using a scattering approach. The
renormalization group solution reveals a scaling behavior of the diffusion
coefficient for large times, with a characteristically slow inverse square root
time dependence. The predicted time dependence of the diffusion coefficient
agrees well with Monte Carlo simulations in two dimensions. Our results can be
used to identify permeable membranes as restrictions to transport in disordered
materials and in biological tissues, and to quantify their permeability and
surface area.Comment: 8 pages, 3 figures; origin of dispersion clarified, refs adde
Bias in MRI Measurements of Apparent Diffusion Coefficient and Kurtosis: Implications for Choice of Maximum Diffusion Encoding
Tissue water diffusion is non-Gaussian and the expressions used to calculate diffusion parameters are approximations which introduce systematic errors dependent on the maximum diffusion encoding, diffusion time, etc. This study aimed at characterizing biases in estimates of both apparent diffusion coefficient and kurtosis, and determines their dependence on these parameters. Similar to the approach of several previous studies, Taylor expansion of the diffusion signal was used to calculate biases. Predicted errors were compared with data from one volunteer. Predicted errors agreed well with the measured errors and also the published diffusion tensor imaging measurements. The equations derived predict biases in measured diffusion parameters and explain much of the discrepancy between measurements obtained with different acquisition protocols. The equations may also be used to choose appropriate diffusion encoding for diffusion weighted, tensor, and kurtosis imaging
The Human Connectome Project's neuroimaging approach
Noninvasive human neuroimaging has yielded many discoveries about the brain. Numerous methodological advances have also occurred, though inertia has slowed their adoption. This paper presents an integrated approach to data acquisition, analysis and sharing that builds upon recent advances, particularly from the Human Connectome Project (HCP). The 'HCP-style' paradigm has seven core tenets: (i) collect multimodal imaging data from many subjects; (ii) acquire data at high spatial and temporal resolution; (iii) preprocess data to minimize distortions, blurring and temporal artifacts; (iv) represent data using the natural geometry of cortical and subcortical structures; (v) accurately align corresponding brain areas across subjects and studies; (vi) analyze data using neurobiologically accurate brain parcellations; and (vii) share published data via user-friendly databases. We illustrate the HCP-style paradigm using existing HCP data sets and provide guidance for future research. Widespread adoption of this paradigm should accelerate progress in understanding the brain in health and disease
Studying neuroanatomy using MRI
The study of neuroanatomy using imaging enables key insights into how our brains function, are shaped by genes and environment, and change with development, aging, and disease. Developments in MRI acquisition, image processing, and data modelling have been key to these advances. However, MRI provides an indirect measurement of the biological signals we aim to investigate. Thus, artifacts and key questions of correct interpretation can confound the readouts provided by anatomical MRI. In this review we provide an overview of the methods for measuring macro- and mesoscopic structure and inferring microstructural properties; we also describe key artefacts and confounds that can lead to incorrect conclusions. Ultimately, we believe that, though methods need to improve and caution is required in its interpretation, structural MRI continues to have great promise in furthering our understanding of how the brain works
The presence of two rare genomic syndromes, 1q21 deletion and Xq28 duplication, segregating independently in a family with intellectual disability
Obstructive Sleep Apnea Severity Affects Amyloid Burden in Cognitively Normal Elderly. A Longitudinal Study
Rationale: Recent evidence suggests that obstructive sleep apnea (OSA) may be a risk factor for developing mild cognitive impairment and Alzheimer’s disease. However, how sleep apnea affects longitudinal risk for Alzheimer’s disease is less well understood.
Objectives: To test the hypothesis that there is an association between severity of OSA and longitudinal increase in amyloid burden in cognitively normal elderly.
Methods: Data were derived from a 2-year prospective longitudinal study that sampled community-dwelling healthy cognitively normal elderly. Subjects were healthy volunteers between the ages of 55 and 90, were nondepressed, and had a consensus clinical diagnosis of cognitively normal. Cerebrospinal fluid amyloid β was measured using ELISA. Subjects received Pittsburgh compound B positron emission tomography scans following standardized procedures. Monitoring of OSA was completed using a home sleep recording device.
Measurements and Main Results: We found that severity of OSA indices (AHIall [F1,88 = 4.26; P < 0.05] and AHI4% [F1,87 = 4.36; P < 0.05]) were associated with annual rate of change of cerebrospinal fluid amyloid β42 using linear regression after adjusting for age, sex, body mass index, and apolipoprotein E4 status. AHIall and AHI4% were not associated with increases in ADPiB-mask (Alzheimer’s disease vulnerable regions of interest Pittsburg compound B positron emission tomography mask) most likely because of the small sample size, although there was a trend for AHIall (F1,28 = 2.96, P = 0.09; and F1,28 = 2.32, not significant, respectively).
Conclusions: In a sample of cognitively normal elderly, OSA was associated with markers of increased amyloid burden over the 2-year follow-up. Sleep fragmentation and/or intermittent hypoxia from OSA are likely candidate mechanisms. If confirmed, clinical interventions for OSA may be useful in preventing amyloid build-up in cognitively normal elderly
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