Physical exercise habits correlate with gray matter volume of the hippocampus in healthy adult humans.
Ontology highlight
ABSTRACT:
SUBMITTER: Killgore WD
PROVIDER: S-EPMC3860009 | biostudies-other | 2013
REPOSITORIES: biostudies-other
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Project description:Minimal hepatic encephalopathy (MHE) is associated with cognitive alterations and changes in connectivity. We assessed the relationship of the abnormalities of resting-state functional connectivity (rs-FC) and gray matter (GM) volume with different cognitive alterations and biochemical parameters associated to MHE.Thirty-nine cirrhotic patients (26 without and 13 with MHE) and 24 controls were widely cognitive assessed with a battery of psychometric tests. Atrophy was determined using Voxel-Based Morphometry and rs-FC was assessed by independent component analysis. Receiver operating characteristic (ROC) curves was performed to assess the diagnostic utility of rs-FC and GM reduction for the discrimination of patients with and without MHE. Blood ammonia, cGMP, and levels of pro-inflammatory interleukins were measured.MHE patients showed significant decrease of GM volume and lesser degree of rs-FC in different networks related to attention and executive functions as compared to controls and patients without MHE. There is a progressive reduction in rs-FC in the default mode network with the progression of cognitive impairment. MHE patients showed GM reduction in the right frontal lobe, right insula and right cerebellum compared to patients without MHE. Alterations in GM volume and rs-FC correlated with the scores of different cognitive tests.Decreased cognitive performance is associated by reduced rs-FC and GM atrophy in MHE patients. These changes could have predictive value for detecting MHE.
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Project description:BackgroundDespite decades of research, there is continued uncertainty regarding whether autism is associated with a specific profile of gray matter (GM) structure. This inconsistency may stem from the widespread use of voxel-based morphometry (VBM) methods that combine indices of GM density and GM volume. If GM density or volume, but not both, prove different in autism, the traditional VBM approach of combining the two indices may obscure the difference. The present study measures GM density and volume separately to examine whether autism is associated with alterations in GM volume, density, or both.MethodsDifferences in MRI-based GM density and volume were examined in 6-25 year-olds with a diagnosis of autism spectrum disorder (n = 213, 80.8% male, IQ 47-154) and a typically developing (TD) sample (n = 190, 71.6% male, IQ 67-155). High-resolution T1-weighted anatomical images were collected on a single MRI scanner. Regional density and volume were estimated via whole-brain parcellation comprised of 1625 parcels. Parcel-wise analyses were conducted using generalized additive models while controlling the false discovery rate (FDR, q < 0.05). Volume differences in the 68-region Desikan-Killiany atlas derived from Freesurfer were also examined, to establish the generalizability of findings across methods.ResultsNo density differences were observed between the autistic and TD groups, either in individual parcels or whole brain mean density. Increased volume was observed in autism compared to the TD group when controlling for Age, Sex, and IQ, both at the level of the whole brain (total volume) and in 45 parcels (2.8% of total parcels). Parcels with greater volume included inferior, middle, and superior temporal gyrus, inferior and superior frontal gyrus, precuneus, and fusiform gyrus. Converging evidence from a standard Freesurfer pipeline also identified greater volume in a number of overlapping regions.LimitationsThe method for determining "density" is not a direct measure of neuronal density, and this study cannot reveal underlying cellular differences. While this study represents possibly the largest single-site sample of its kind, it is underpowered to detect very small differences.ConclusionsThese results provide compelling evidence that autism is associated with regional GM volumetric differences, which are more prominent than density differences. This underscores the importance of examining volume and density separately, and suggests that direct measures of volume (e.g. region-of-interest or tensor-based morphometry approaches) may be more sensitive to autism-relevant differences in neuroanatomy than concentration/density-based approaches.
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