Aim: Cognitive aging is known to alter reward-guided behaviors that require interactions between the orbitofrontal cortex (OFC) and amygdala. In macaques, OFC, but not amygdala volumes decline with age and correlate with performance on a reward devaluation (RD) task. The present study used diffusion magnetic resonance imaging (dMRI) methods to investigate whether the condition of the white matter associated with amygdala-OFC connectivity changes with age and relates to reward devaluation.
Methods: Diffusion-, T1- and T2-weighted MRIs were acquired from adult and aged bonnet macaques. Using probabilistic tractography, fractional anisotropy (FA) estimates from two separate white matter tracts associated with amygdala-OFC connectivity, the uncinate fasciculus (UF) and amygdalofugal (AF) pathways, were obtained. Performance measures on RD and reversal learning (RL) tasks were also acquired and related to FA indices from each anatomical tract.
Results: Aged monkeys were impaired on both the RD and RL tasks and had lower FA indices in the AF pathway. Higher FA indices from the right hemisphere UF pathway correlated with better performance on an object-based RD task, whereas higher FA indices from the right hemisphere AF were associated with better performance on an object-free version of the task. FA measures from neither tract correlated with RL performance.
Conclusions: These results suggest that the condition of the white matter connecting the amygdala and OFC may impact reward devaluation behaviors. Furthermore, the observation that FA indices from the UF and AF differentially relate to reward devaluation suggests that the amygdala-OFC interactions that occur via these separate tracts are partially independent.
Background: Single-voxel proton magnetic resonance spectroscopy (1H MRS) is a powerful technique for studying in vivo neurochemistry, but has an often-overlooked source of error variance: inconsistent voxel placement between scans. We developed and evaluated an Automated Voxel Placement (AVP) procedure for accurate and reliable 1H MRS voxel prescription. AVP is a suite of Linux-based programs that facilitate automated template-driven single-voxel coregistration.
Methods: Three studies were conducted to evaluate AVP for prescription of one voxel: left dorsolateral prefrontal cortex. First, we evaluated how robust AVP was to 'extreme' subject head positions/angulations within the scanner head coil. Second, subjects (N = 13) were recruited and underwent MR scans. Manual voxel prescription (n = 5) was contrasted with AVP (n = 8). A subset of AVP subjects (n = 4) completed a second scan. Third, ongoing data collection (n = 16; recruited for a separate study) helped evaluate AVP. Voxel placement accuracy was quantified as 3D geometric voxel overlap percentage between each subject's voxel and the template voxel. Reliability was quantified as 3D geometric voxel overlap percentage across subjects at each time point and within subjects who completed two scans.
Results: Results demonstrated that AVP was robust to 'extreme' head positions (97.5% - 97.9% overlap with the template voxel). AVP was significantly more accurate (baseline and follow-up: 96.2% ± 3.0% and 97.6% ± 1.4% overlap) than manual voxel placement (67.7% ± 22.8% overlap; ps<.05). AVP was reliable within- (97.9%) and between-subjects (94.2% and 97.2% overlap; baseline and follow-up; respectively). Finally, ongoing data collection indicates AVP is accurate (96.0%).
Conclusion: These pilot studies demonstrated that AVP was feasible, accurate, and reliable method for automated single voxel coregistration.
Stroke characteristics vary widely between individuals making it difficult to assess the value of stroke rehabilitation interventions. To eliminate inter-subject variability, this study used an N-of-1 randomized, controlled design to explore the efficacy of repetitive transcranial magnetic stimulation (rTMS) in one unique individual with pontine stroke. We hypothesized that five days of active 6-Hz primed, low-frequency rTMS to the contralesional primary motor area (M1), combined with finger movement tracking training, would accomplish greater gains in hand function than sham rTMS combined with tracking training. We assessed hand function (Box and Block test and finger tracking test), cortical activation (laterality index during functional magnetic resonance imaging), and cortical excitability (interhemispheric inhibition testing (IHI) with transcranial magnetic stimulation (TMS)). Diffusion tensor imaging (DTI) assessed the integrity of his corticospinal tracts at baseline. Results showed no improvement in the Box and Block or finger tracking tests, unreliable IHI findings, and no change in laterality index following active rTMS. DTI suggested truncation of the left corticospinal tract (CST) at the pons. His non-dexterous hand movements combined with no elicitable motor evoked potentials with TMS to ipsilesional M1 and his DTI findings lead us to speculate a reticulospinal mechanism for preserving his rudimentary paretic hand control. We conclude that rTMS combined with tracking training was not effective in the absence of CST pathways and that research is needed to confirm markers of reticulospinal function in humans as an alternative to defective CST function.
Background: Radiological assessments of biologically relevant regions in glioblastoma have been associated with genotypic characteristics, implying a potential role in personalized medicine. Here, we assess the reproducibility and association with survival of two volumetric segmentation platforms and explore how methodology could impact subsequent interpretation and analysis.
Methods: Post-contrast T1- and T2-weighted FLAIR MR images of 67 TCGA patients were segmented into five distinct compartments (necrosis, contrast-enhancement, FLAIR, post contrast abnormal, and total abnormal tumor volumes) by two quantitative image segmentation platforms - 3D Slicer and a method based on Velocity AI and FSL. We investigated the internal consistency of each platform by correlation statistics, association with survival, and concordance with consensus neuroradiologist ratings using ordinal logistic regression.
Results: We found high correlations between the two platforms for FLAIR, post contrast abnormal, and total abnormal tumor volumes (spearman's r(67) = 0.952, 0.959, and 0.969 respectively). Only modest agreement was observed for necrosis and contrast-enhancement volumes (r(67) = 0.693 and 0.773 respectively), likely arising from differences in manual and automated segmentation methods of these regions by 3D Slicer and Velocity AI/FSL, respectively. Survival analysis based on AUC revealed significant predictive power of both platforms for the following volumes: contrast-enhancement, post contrast abnormal, and total abnormal tumor volumes. Finally, ordinal logistic regression demonstrated correspondence to manual ratings for several features.
Conclusion: Tumor volume measurements from both volumetric platforms produced highly concordant and reproducible estimates across platforms for general features. As automated or semi-automated volumetric measurements replace manual linear or area measurements, it will become increasingly important to keep in mind that measurement differences between segmentation platforms for more detailed features could influence downstream survival or radio genomic analyses.
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：