An automated, geometry-based method for hippocampal shape and thickness analysis

The hippocampus is one of the most studied neuroanatomical structures due to its involvement in attention, learning, and memory as well as its atrophy in ageing, neurological, and psychiatric diseases. Hippocampal shape changes, however, are complex and cannot be fully characterized by a single summary metric such as hippocampal volume as determined from MR images. In this work, we propose an automated, geometry-based approach for the unfolding, point-wise correspondence, and local analysis of hippocampal shape features such as thickness and curvature. Starting from an automated segmentation of hippocampal subfields, we create a 3D tetrahedral mesh model as well as a 3D intrinsic coordinate system of the hippocampal body. From this coordinate system, we derive local curvature and thickness estimates as well as a 2D sheet for hippocampal unfolding. We evaluate the performance of our algorithm with a series of experiments to quantify neurodegenerative changes in Mild Cognitive Impairment and Alzheimer's disease dementia. We find that hippocampal thickness estimates detect known differences between clinical groups and can determine the location of these effects on the hippocampal sheet. Further, thickness estimates improve classification of clinical groups and cognitively unimpaired controls when added as an additional predictor. Comparable results are obtained with different datasets and segmentation algorithms. Taken together, we replicate canonical findings on hippocampal volume/shape changes in dementia, extend them by gaining insight into their spatial localization on the hippocampal sheet, and provide additional, complementary information beyond traditional measures. We provide a new set of sensitive processing and analysis tools for the analysis of hippocampal geometry that allows comparisons across studies without relying on image registration or requiring manual intervention

Automated Olfactory Bulb Segmentation on High Resolutional T2-Weighted MRI

The neuroimage analysis community has neglected the automated segmentation of the olfactory bulb (OB) despite its crucial role in olfactory function. The lack of an automatic processing method for the OB can be explained by its challenging properties. Nonetheless, recent advances in MRI acquisition techniques and resolution have allowed raters to generate more reliable manual annotations. Furthermore, the high accuracy of deep learning methods for solving semantic segmentation problems provides us with an option to reliably assess even small structures. In this work, we introduce a novel, fast, and fully automated deep learning pipeline to accurately segment OB tissue on sub-millimeter T2-weighted (T2w) whole-brain MR images. To this end, we designed a three-stage pipeline: (1) Localization of a region containing both OBs using FastSurferCNN, (2) Segmentation of OB tissue within the localized region through four independent AttFastSurferCNN - a novel deep learning architecture with a self-attention mechanism to improve modeling of contextual information, and (3) Ensemble of the predicted label maps. The OB pipeline exhibits high performance in terms of boundary delineation, OB localization, and volume estimation across a wide range of ages in 203 participants of the Rhineland Study. Moreover, it also generalizes to scans of an independent dataset never encountered during training, the Human Connectome Project (HCP), with different acquisition parameters and demographics, evaluated in 30 cases at the native 0.7mm HCP resolution, and the default 0.8mm pipeline resolution. We extensively validated our pipeline not only with respect to segmentation accuracy but also to known OB volume effects, where it can sensitively replicate age effects

a combined ecological momentary assessment and fMRI study

Regulation of emotions is necessary for successful attainment of short-term and long-term goals. However, over-regulation may also have its costs. In anorexia nervosa (AN), forgoing food intake despite emaciation and endocrine signals that promote eating is an example of “too much” self-control. Here we investigated whether voluntary emotion regulation in AN patients comes with associated disorder-relevant costs. Thirty-five patients with acute AN and thirty-five age-matched healthy controls (HCs) performed an established emotion regulation paradigm during functional magnetic resonance imaging after an overnight fast. The task required reducing emotions induced by positively valenced pictures via distancing. We calculated a neural regulation score from responses recorded in a reward-related brain region of interest (ventral striatum; VS) by subtracting activation measured on “positive distance” trials from that elicited under the “positive watch” (baseline) condition. Complementing the imaging data, we used ecological momentary assessment (EMA) to probe disorder-related rumination and affect six times/day for 2 weeks following the scanning session. The neural regulation score indicating reduced VS activation during emotion regulation was used as a predictor in hierarchical linear models with EMA measures as outcomes. No group differences in neural activity were found for the main contrasts of the task. However, regulation of VS activity was associated with increased body-related rumination and increased negative affect in AN, but not in HC. In line with this finding, correlational analysis with longitudinal BMI measurements revealed a link between greater VS regulation and poorer treatment outcome after 60 and 90 days. Together, these results identify a neural correlate of altered emotion regulation in AN, which seems to be detrimental to psychological well-being and may interfere with recovery

Temporo-Spatial Dynamics of Event-Related EEG Beta Activity during the Initial Contingent Negative Variation

In the electroencephalogram (EEG), early anticipatory processes are accompanied by a slow negative potential, the initial contingent negative variation (iCNV), occurring between 500 and 1500 ms after cue onset over prefrontal cortical regions in tasks with cue-target intervals of about 3 s or longer. However, the temporal sequence of the distributed cortical activity contributing to iCNV generation remains unclear. During iCNV generation, selectively enhanced low-beta activity has been reported. Here we studied the temporal order of activation foci in cortical regions assumed to underlie iCNV generation using source reconstruction of low-beta (13–18 Hz) activity. During the iCNV, elicited by a cued simple reaction-time task, low-beta power peaked first (750 ms after cue onset) in anterior frontal and limbic regions and last (140 ms later) in posterior areas. This activity occurred 3300 ms before target onset and provides evidence for the temporally ordered involvement of both cognitive-control and motor-preparation processes already at early stages during the preparation for speeded action

Ophthalmology

PURPOSE: To investigate systemic and ocular determinants of peripapillary retinal nerve fiber layer thickness (pRNFLT) in the European population. DESIGN: Cross-sectional meta-analysis. PARTICIPANTS: A total of 16 084 European adults from 8 cohort studies (mean age range, 56.9+/-12.3-82.1+/-4.2 years) of the European Eye Epidemiology (E3) consortium. METHODS: We examined associations with pRNFLT measured by spectral-domain OCT in each study using multivariable linear regression and pooled results using random effects meta-analysis. MAIN OUTCOME MEASURES: Determinants of pRNFLT. RESULTS: Mean pRNFLT ranged from 86.8+/-21.4 mum in the Rotterdam Study I to 104.7+/-12.5 mum in the Rotterdam Study III. We found the following factors to be associated with reduced pRNFLT: Older age (beta = -0.38 mum/year; 95% confidence interval [CI], -0.57 to -0.18), higher intraocular pressure (IOP) (beta = -0.36 mum/mmHg; 95% CI, -0.56 to -0.15), visual impairment (beta = -5.50 mum; 95% CI, -9.37 to -1.64), and history of systemic hypertension (beta = -0.54 mum; 95% CI, -1.01 to -0.07) and stroke (beta = -1.94 mum; 95% CI, -3.17 to -0.72). A suggestive, albeit nonsignificant, association was observed for dementia (beta = -3.11 mum; 95% CI, -6.22 to 0.01). Higher pRNFLT was associated with more hyperopic spherical equivalent (beta = 1.39 mum/diopter; 95% CI, 1.19-1.59) and smoking (beta = 1.53 mum; 95% CI, 1.00-2.06 for current smokers compared with never-smokers). CONCLUSIONS: In addition to previously described determinants such as age and refraction, we found that systemic vascular and neurovascular diseases were associated with reduced pRNFLT. These may be of clinical relevance, especially in glaucoma monitoring of patients with newly occurring vascular comorbidities

Instructions matter: a comparison of baseline conditions for cognitive emotion regulation paradigms

The choice of a meaningful baseline condition is a crucial issue for each experimental design. In the case of cognitive emotion regulation, it is common to either let participants passively view emotional stimuli without any further specific instructions or to instruct them to actively attend to and permit any arising emotions, and to contrast one of these baseline conditions with a regulation condition. While the “view” strategy can be assumed to allow for a more spontaneous emotional response, the “permit” strategy may result in a more pronounced affective and cognitive response. As these conceptual differences may be associated with differences both in subjective emotional experience and neural activation, we compared these two common control conditions within a single functional magnetic resonance imaging (fMRI) experiment, during which participants were instructed to either passively view a set of unpleasant and neutral pictures or to actively permit any emotions arising in response to the unpleasant pictures. Trial-by-trial ratings confirmed that participants perceived the unpleasant pictures as more arousing than the neutral pictures, but also indicated higher subjective arousal during the “permit negative” as compared to the “view negative” and “view neutral” conditions. While both the “permit negative” and “view negative” conditions led to increased activation of the bilateral amygdala when contrasted with the passive viewing of neutral pictures, activation in the left amygdala was increased in response to the “permit” instruction as compared to the “view” instruction for unpleasant pictures. The increase in amygdala activation in both the “permit” and “view” conditions renders both strategies as suitable baseline conditions for studies of cognitive emotion regulation. Conceptual and activation differences, however, indicate that these two variants are not exchangeable and should be chosen depending on the experimental context

An automated, geometry-based method for hippocampal shape and thickness analysis

The hippocampus is one of the most studied neuroanatomical structures due to its involvement in attention, learning, and memory as well as its atrophy in ageing, neurological, and psychiatric diseases. Hippocampal shape changes, however, are complex and cannot be fully characterized by a single summary metric such as hippocampal volume as determined from MR images. In this work, we propose an automated, geometry-based approach for the unfolding, point-wise correspondence, and local analysis of hippocampal shape features such as thickness and curvature. Starting from an automated segmentation of hippocampal subfields, we create a 3D tetrahedral mesh model as well as a 3D intrinsic coordinate system of the hippocampal body. From this coordinate system, we derive local curvature and thickness estimates as well as a 2D sheet for hippocampal unfolding. We evaluate the performance of our algorithm with a series of experiments to quantify neurodegenerative changes in Mild Cognitive Impairment and Alzheimer's disease dementia. We find that hippocampal thickness estimates detect known differences between clinical groups and can determine the location of these effects on the hippocampal sheet. Further, thickness estimates improve classification of clinical groups and cognitively unimpaired controls when added as an additional predictor. Comparable results are obtained with different datasets and segmentation algorithms. Taken together, we replicate canonical findings on hippocampal volume/shape changes in dementia, extend them by gaining insight into their spatial localization on the hippocampal sheet, and provide additional, complementary information beyond traditional measures. We provide a new set of sensitive processing and analysis tools for the analysis of hippocampal geometry that allows comparisons across studies without relying on image registration or requiring manual intervention

A Functional MRI Paradigm for Efficient Mapping of Memory Encoding Across Sensory Conditions

We introduce a new and time-efficient memory-encoding paradigm for functional magnetic resonance imaging (fMRI). This paradigm is optimized for mapping multiple contrasts using a mixed design, using auditory (environmental/vocal) and visual (scene/face) stimuli. We demonstrate that the paradigm evokes robust neuronal activity in typical sensory and memory networks. We were able to detect auditory and visual sensory-specific encoding activities in auditory and visual cortices. Also, we detected stimulus-selective activation in environmental-, voice-, scene-, and face-selective brain regions (parahippocampal place and fusiform face area). A subsequent recognition task allowed the detection of sensory-specific encoding success activity (ESA) in both auditory and visual cortices, as well as sensory-unspecific positive ESA in the hippocampus. Further, sensory-unspecific negative ESA was observed in the precuneus. Among others, the parallel mixed design enabled sustained and transient activity comparison in contrast to rest blocks. Sustained and transient activations showed great overlap in most sensory brain regions, whereas several regions, typically associated with the default-mode network, showed transient rather than sustained deactivation. We also show that the use of a parallel mixed model had relatively little influence on positive or negative ESA. Together, these results demonstrate a feasible, versatile, and brief memory-encoding task, which includes multiple sensory stimuli to guarantee a comprehensive measurement. This task is especially suitable for large-scale clinical or population studies, which aim to test task-evoked sensory-specific and sensory-unspecific memory-encoding performance as well as broad sensory activity across the life span within a very limited time frame