Thalamic Matter Research Articles

Anemia, blood cell indices, genetic correlations, and brain structures: A comprehensive analysis of roles in Parkinson's disease risk

IntroductionAnemia may contribute significantly to the onset of Parkinson's disease (PD). Current research on the association between anemia and PD risk is inconclusive, and the relationships between anemia-related blood cell indices and PD incidence require further clarification. This study aims to investigate the relationships between anemia, blood cell indicators, and PD risk using a thorough prospective cohort study. MethodsWe used data from the UK Biobank, a prospective cohort study of 502,649 participants, and ultimately, 365,982 participants were included in the analysis. Cox proportional hazards models were utilized to adjust for confounding factors, aiming to thoroughly explore the associations between anemia and blood cell indices with the risk of incident PD. The interaction between anemia and Polygenic Risk Score (PRS) for PD was also examined. Linear regression and mediation analyses assessed potential mechanisms driven by brain structures, including grey matter volume. ResultsDuring a median follow-up of 14.24 years, 2513 participants were diagnosed with PD. Anemia considerably increased PD risk (hazard ratio [HR] 1.98, 95 % confidence interval [CI]: 1.81–2.18, P < 0.001) after adjustments. Those with high PRS for anemia had an 83 % higher PD incidence compared to low PRS participants. Sensitivity analyses confirmed result robustness. Linear regression showed that anemia correlated with grey matter volumes and most white matter tracts. Furthermore, mediation analyses identified that the volume of grey matter in Thalamus mediates the relationship between anemia and PD risk. ConclusionIn summary, we consider there to be a substantial correlation between anemia and increased PD risk.

Early detection of Parkinson's disease through multimodal features using machine learning approaches

This research establishes a relation between objective biomarkers of Parkinson's disease (PD) based on T1-weighted MRI scans and other clinical biomarkers. It shall aid doctors in identifying the onset and progression of PD among the patients. Voxel-based morphometry has been used for feature extraction from MRI scans. These extracted features are combined with biochemical biomarkers for dataset enrichment. A genetic algorithm is applied to this dataset to remove the redundancies and to obtain an optimal set of features. Subsequently, we used Self-adaptive resource allocation network (SRAN), extreme learning machine (ELM) and support vector machines (SVM) to classify different subjects. It is observed that SRAN classifier gave the best performance when compared with ELM and SVM. Finally, it is found that a variation of grey matter in Thalamus is responsible for PD. The obtained results corroborate the earlier findings from the literature.

Analysis of grey matter in thalamus and basal ganglia based on EEG α3/α2 frequency ratio reveals specific changes in subjects with mild cognitive impairment.

GM (grey matter) changes of thalamus and basal ganglia have been demonstrated to be involved in AD (Alzheimer's disease). Moreover, the increase of a specific EEG (electroencephalogram) marker, α3/α2, have been associated with AD-converters subjects with MCI (mild cognitive impairment). To study the association of prognostic EEG markers with specific GM changes of thalamus and basal ganglia in subjects with MCI to detect biomarkers (morpho-physiological) early predictive of AD and non-AD dementia. Seventy-four adult subjects with MCI underwent EEG recording and high-resolution 3D MRI (three-dimensional magnetic resonance imaging). The α3/α2 ratio was computed for each subject. Three groups were obtained according to increasing tertile values of α3/α2 ratio. GM density differences between groups were investigated using a VBM (voxel-based morphometry) technique. Subjects with higher α3/α2 ratios when compared with subjects with lower and middle α3/α2 ratios showed minor atrophy in the ventral stream of basal ganglia (head of caudate nuclei and accumbens nuclei bilaterally) and of the pulvinar nuclei in the thalamus; The integrated analysis of EEG and morpho-structural markers could be useful in the comprehension of anatomo-physiological underpinning of the MCI entity.

Gray matter structural alterations in obsessive–compulsive disorder: Relationship to neuropsychological functions

Numerous magnetic resonance (MR) studies have examined gray matter structural alterations in patients with obsessive–compulsive disorder (OCD). Few, however, have used automated, highly reliable techniques such as voxel-based morphometry (VBM) to examine the entire brain in contrast to selected regions of interest. Moreover, few studies have examined the functional correlates of gray matter abnormalities in OCD. We used VBM to evaluate regional gray matter differences between 21 OCD patients and 21 age- and sex-matched healthy volunteers. All patients had comprehensive neuropsychological assessments. MR images were normalized to a customized template and segmented using optimized VBM. OCD patients had significantly more gray matter in the left thalamus compared with healthy volunteers. OCD patients without major depression had significantly more gray matter in the thalamus (bilaterally) and left orbitofrontal cortex as well as an unpredicted region of more right dorsolateral prefrontal gray matter, which remained significant after correction for multiple comparisons, compared with healthy volunteers. In the subgroup of patients without depression, greater right hemisphere thalamic and dorsolateral prefrontal gray matter correlated significantly with worse motor functioning and processing speed, respectively. In this subgroup there was also a tendency for more gray matter in the left orbitofrontal cortex and right dorsolateral prefrontal cortex to be associated with greater symptom severity. Our findings provide additional support for the involvement of cortical–striatal–thalamic circuits in the pathophysiology of OCD and preliminary evidence that a defect involving the dorsolateral prefrontal cortex may also be implicated. Moreover, our data suggest that gray matter structural alterations in OCD have neuropsychological correlates, which may be useful in further characterizing structure–function relations in this disorder.

Simulation of reflected light intensity changes during navigation and radio-frequency lesioning in the brain

An electrode with adjacent optical fibers for measurements during navigation and radio frequency lesioning in the brain is modeled for Monte Carlo simulations of light transport in brain tissue. Relative reflected light intensity at 780 nm, I780, from this electrode and probes with identical fiber configuration are simulated using the intensity from native white matter as reference. Models are made of homogeneous native and coagulated gray, thalamus, and white matter as well as blood. Dual layer models, including models with a layer of cerebrospinal fluid between the fibers and the brain tissue, are also made. Simulated I780 was 0.16 for gray matter, 0.67 for coagulate gray matter, 0.36 for thalamus, 0.39 for coagulated thalamus, unity for white matter, 0.70 for coagulated white matter, and 0.24 for blood. Thalamic matter is also found to reflect more light than gray matter and less than white matter in clinical studies. In conclusion, the reflected light intensity can be used to differentiate between gray and white matter during navigation. Furthermore, coagulation of light gray tissue, such as the thalamus, might be difficult to detect using I780, but coagulation in darker gray tissue should result in a rapid increase of I780.