Biology subjects

Fonov, V. S.

Publications and source records attributed to Fonov, V. S..

4 recordsLinked to original sources

bioRxiv2023

Nucleus basalis of Meynert degeneration signals earliest stage of Alzheimer's disease progression

The Nucleus Basalis of Meynert (NbM) is the main source of cholinergic projection to the entorhinal cortex (EC) and hippocampus (HC), where acetylcholine plays a key role in their function. Both cholinergic cells of NbM and their receptive targets in the EC and HC show sensitivity to neurofibrillary degeneration during the early stages of Alzheimers disease. Precise delineation of the NbM region on T1w scans is challenging due to limited spatial resolution and contrast. Using deformation-based morphometry (DBM), we sought to quantify NbM degeneration along the Alzheimers disease trajectory and confirm recent studies suggesting that NbM degeneration happens before degeneration in the EC or HC. MRI scans of 1447 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI1, 2 and GO) were up-sampled to 0.5 mm voxel-size in each direction (0.125 mm3) before non-linear registration to an ADNI-based unbiased symmetric average MRI template. A subgroup of 677 amyloid-positive participants were chosen for volume time course analysis where the resulting deformation fields were used to compute a high-resolution Jacobian determinant map for each participant as a proxy for local volume change within NbM, EC, and HC masks. Scores of volume change were corrected for age and sex and z-scored using normative data from cognitively healthy amyloid-negative (CN-) participants (n = 219). Two-sample t-tests were then used to compare the baseline differences between NbM, EC, and HC for amyloid-positive cognitively normal controls (CN+), amyloid-positive early mild cognitive impairment (eMCI), and amyloid-positive late mild cognitive impairment (lMCI). Longitudinal linear mixed-effect models were used to compare trajectories of volume change after realigning all participants into a common timeline based on their cognitive decline. Results showed a significant cross-sectional difference at baseline between CN+ and eMCI, and eMCI and lMCI for both left and right Z-scored NbM volumes. There was no difference in z-scored EC and HC volumes between CN+ and eMCI groups but results from eMCI and lMCI differed significantly in these regions. Longitudinal analysis, with a focus on the early disease stages showed the earliest deviation from the CN- trajectory in the NbM and HC in the subject-specific time realigned data. Contrary to the notion that Alzheimers disease originates in EC, we found that NbM volume changes earlier in the disease trajectory than EC or HC. Converging evidence from cross-sectional and longitudinal models suggest that the NbM may be a focal target of early AD progression, which is often obscured by normal age-related decline.

bioinformatics↗

bioRxiv2021

Increased Brain Volumetric Measurement Precision from Multi-Site 3D T1-weighted 3T Magnetic Resonance Imaging by Correcting Geometric Distortions

Magnetic resonance imaging (MRI) scanner-specific geometric distortions may contribute to scanner induced variability and decrease volumetric measurement precision for multi-site studies. The purpose of this study was to determine whether geometric distortion correction increases the precision of brain volumetric measurements in a multi-site multi-scanner study. Geometric distortion variation was quantified over a one-year period at 10 sites using the distortion fields estimated from monthly 3D T1-weighted MRI geometrical phantom scans. The variability of volume and distance measurements were quantified using synthetic volumes and a standard quantitative MRI (qMRI) phantom. The effects of geometric distortion corrections on MRI derived volumetric measurements of the human brain were assessed in two subjects scanned on each of the 10 MRI scanners and in 150 subjects with cerebrovascaular disease (CVD) acquired across imaging sites. Geometric distortions were found to vary substantially between different MRI scanners but were relatively stable on each scanner over a one-year interval. Geometric distortions varied spatially, increasing in severity with distance from the magnet isocenter. In measurements made with the qMRI phantom, the geometric distortion correction decreased the standard deviation of volumetric assessments by 35% and distance measurements by 42%. The average coefficient of variance decreased by 16% in gray matter and white matter volume estimates in the two subjects scanned on the 10 MRI scanners. Geometric distortion correction using an up-to-date correction field is recommended to increase precision in volumetric measurements made from MRI images.

bioengineering↗

bioRxiv2019

A sub+ cortical fMRI-based surface parcellation

Both the cortex and the subcortical structures are organized into a large number of distinct areas reflecting functional and cytoarchitectonic differences. Mapping these areas is of fundamental importance to neuroscience. A central obstacle to this task is the inaccuracy associated with mapping results from individuals into a common space. The vast individual differences in morphology pose a serious problem for volumetric registration. Surface-based approaches fare substantially better, but have thus far been used only for cortical parcellation. We extend this surface-based approach to include also the subcortical deep gray-matter structures. Using the life-span data from the Enhanced Nathan Klein Institute - Rockland Sample, comprised of data from 590 individuals from 6 to 85 years of age, we generate a functional parcellation of both the cortical and subcortical surfaces. To assess this extended parcellation, we show that our extended functional parcellation provides greater homogeneity of functional connectivity patterns than do arbitrary parcellations matching in the number and size of parcels. We also show that our subcortical parcels align with known subnuclei. Further, we show that this parcellation is appropriate for use with data from other modalities; we generate cortical and subcortical white/gray contrast measures for this same dataset, and draw on the fact that areal differences are evident in the relation of white/gray contrast to age, to sex, to brain volume, and to interactions of these terms; we show that our extended functional parcellation provides an improved fit to the complexity of the life-span changes in the white/gray contrast data compared to arbitrary parcellations matching in the number and size of parcels. We provide our extended functional parcellation for the use of the neuroimaging community.

neuroscience↗

bioRxiv2019

Cortical and subcortical T1 white/gray contrast, chronological age, and cognitive performance

The maturational schedule of typical brain development is tightly constrained; deviations from it are associated with cognitive atypicalities, and are potentially predictive of developmental disorders. Previously, we have shown that the white/gray contrast at the inner border of the cortex is a good predictor of chronological age, and is sensitive to aspects of brain development that reflect cognitive performance. Here we extend that work to include the contrast at the white/gray border of subcortical structures. We show that cortical and subcortical contrast together yield better age-predictions than any non-kernel-based method based on a single image-type, and that the residuals of the improved predictions provide new insight into unevenness in cognitive performance. We demonstrate the improvement in age predictions in two large datasets: the NIH Pediatric Data, with 831 scans of typically developing individuals between 4 and 22 years of age; and the Pediatric Imaging, Neurocognition, and Genetics data, with 909 scans of individuals in a similar age-range. Assessment of the relation of the residuals of these age predictions to verbal and performance IQ revealed correlations in opposing directions, and a principal component analysis of the residuals of the model that best fit the contrast data produced components related to either performance IQ or verbal IQ. Performance IQ was associated with the first principle component, reflecting increased cortical contrast, broadly, with almost no subcortical presence; verbal IQ was associated with the second principle component, reflecting reduced contrast in the basal ganglia and increased contrast in the bilateral arcuate fasciculi.

neuroscience↗