Lesliemose2201

The regions of T2 and T2* mismatch from MRI, neuromelanin pigments from histology, and elevated iron signals from mass spectrometry were spatially overlapped for a normal postmortem brain. In preliminary in vivo studies, a similar, linear T2 and T2* mismatch region was observed in the dorsal area of the substantia nigra in eight normal subjects; this mismatch was significantly obscured in eight Parkinson's disease patients. The length of the dorsal linear mismatch line based on the T2*-T2 mask was significantly shorter in the Parkinson's disease patients compared to normal controls; this result was corroborated by reduced striatal uptake of [18F] FP-CIT dopamine transporters assessed by positron emission tomography scans. In conclusion, the measurement of T2 and T2* mismatch could serve as a complementary imaging biomarker to visualize the dorsal region of the substantia nigra pars compacta, which contains large amounts of neuromelanin. Functional magnetic resonance imaging provides rich spatio-temporal data of human brain activity during task and rest. Many recent efforts have focussed on characterising dynamics of brain activity. One notable instance is co-activation pattern (CAP) analysis, a frame-wise analytical approach that disentangles the different functional brain networks interacting with a user-defined seed region. While promising applications in various clinical settings have been demonstrated, there is not yet any centralised, publicly accessible resource to facilitate the deployment of the technique. Here, we release a working version of TbCAPs, a new toolbox for CAP analysis, which includes all steps of the analytical pipeline, introduces new methodological developments that build on already existing concepts, and enables a facilitated inspection of CAPs and resulting metrics of brain dynamics. The toolbox is available on a public academic repository at https//c4science.ch/source/CAP_Toolbox.git. In addition, to illustrate the feasibility and usefulness of our pipeline, we describe an application to the study of human cognition. CAPs are constructed from resting-state fMRI using as seed the right dorsolateral prefrontal cortex, and, in a separate sample, we successfully predict a behavioural measure of continuous attentional performance from the metrics of CAP dynamics (R ​= ​0.59). In everyday behavior, we perform numerous goal-directed manual tasks that contain a sequence of actions. However, knowledge is limited regarding developmental aspects of predictive control mechanisms in such tasks, particularly with regard to brain activations supporting sequential manual actions in children. We investigated these issues in typically developing children at early adolescence (11-14 years) compared with previously collected data from adults. While lying in a magnetic resonance imaging (MRI) scanner, the participants steered a cursor on a computer screen towards sequentially presented targets using a hand-held manipulandum. The next target was either revealed after completion of the ongoing target (one-target condition), in which case forthcoming movements could not be planned ahead, or displayed in advance (two-target condition), which allowed the use of a predictive control strategy. The adults completed more targets in the two- than one-target condition, displaying an efficient predictive control strategy. The children, in contrast, completed fewer targets in the two- than one-target condition, and difficulties implementing a predictive strategy were found due to a limited capacity to inhibit premature movements. 5'-N-Ethylcarboxamidoadenosine Brain areas with increased activation in children, compared with the adults, included prefrontal and posterior parietal regions, suggesting an increased demand for higher-level cognitive processing in the children due to inhibitory challenges. Thus, regarding predictive mechanisms during sequential manual tasks, crucial development likely occurs beyond early adolescence. This is at a later age than what has previously been reported from other manual tasks, suggesting that predictive phase transitions are difficult to master. How are outliers in an otherwise homogeneous object ensemble represented by our visual system? Are outliers ignored because they are the minority? Or do outliers alter our perception of an otherwise homogeneous ensemble? We have previously demonstrated ensemble representation in human anterior-medial ventral visual cortex (overlapping the scene-selective parahippocampal place area; PPA). In this study we investigated how outliers impact object-ensemble representation in this human brain region as well as visual representation throughout posterior brain regions. We presented a homogeneous ensemble followed by an ensemble containing either identical elements or a majority of identical elements with a few outliers. Human participants ignored the outliers and made a same/different judgment between the two ensembles. In PPA, fMRI adaptation was observed when the outliers in the second ensemble matched the items in the first, even though the majority of the elements in the second ensemble were distinct from those in the first; conversely, release from fMRI adaptation was observed when the outliers in the second ensemble were distinct from the items in the first, even though the majority of the elements in the second ensemble were identical to those in the first. A similarly robust outlier effect was also found in other brain regions, including a shape-processing region in lateral occipital cortex (LO) and task-processing fronto-parietal regions. These brain regions likely work in concert to flag the presence of outliers during visual perception and then weigh the outliers appropriately in subsequent behavioral decisions. To our knowledge, this is the first time the neural mechanisms involved in outlier processing have been systematically documented in the human brain. Such an outlier effect could well provide the neural basis mediating our perceptual experience in situations like "one bad apple spoils the whole bushel". Segmentation of brain lesions from magnetic resonance images (MRI) is an important step for disease diagnosis, surgical planning, radiotherapy and chemotherapy. However, due to noise, motion, and partial volume effects, automated segmentation of lesions from MRI is still a challenging task. In this paper, we propose a two-stage supervised learning framework for automatic brain lesion segmentation. Specifically, in the first stage, intensity-based statistical features, template-based asymmetric features, and GMM-based tissue probability maps are used to train the initial random forest classifier. Next, the dense conditional random field optimizes the probability maps from the initial random forest classifier and derives the whole tumor regions referred as the region of interest (ROI). In the second stage, the optimized probability maps are further intergraded with features from the intensity-based statistical features and template-based asymmetric features to train subsequent random forest, focusing on classifecting the reliability and interpretability of our framework. The naturalistic viewing of a video clip enables participants to obtain more information from the clip compared to conventional viewing of a static image. Because changing the field-of-view (FoV) allows new visual information to be obtained, we were motivated to investigate whether naturalistic viewing with varying FoV based on active eye movement can enhance the viewing experience of natural stimuli, such as those found in a video clip with a 360° FoV in an MRI scanner. To this end, we developed a novel naturalistic viewing paradigm based on real-time eye-gaze tracking while participants were watching a 360° panoramic video during fMRI acquisition. The gaze position of the participants was recorded using an eye-tracking computer and then transmitted to a stimulus presentation computer via a TCP/IP connection. The identified gaze position was then used to alter the participants' FoV of the video clip in real-time, so the participants could change their FoV to fully explore the 360° video clip (referred to in ime. Our method of utilizing the MRI environment can be further extended to other environments such as electroencephalography and behavioral research. It would also be feasible to apply our method to virtual reality and/or augmented reality systems to maximize user experience based on their eye movement. Functional brain organization in transgender persons remains unclear. Our aims were to investigate global and regional connectivity differences within functional networks in transwomen and transmen with early-in-life onset gender incongruence; and to test the consistency of two available hypotheses that attempted to explain gender variants (i) a neurodevelopmental cortical hypothesis that suggests the existence of different brain phenotypes based on structural MRI data and genes polymorphisms of sex hormone receptors; (ii) a functional-based hypothesis in relation to regions involved in the own body perception. T2*-weighted images in a 3-T MRI were obtained from 29 transmen and 17 transwomen as well as 22 cisgender women and 19 cisgender men. Resting-state independent component analysis, seed-to-seed functional network and graph theory analyses were performed. Transmen, transwomen, and cisgender women had decreased connectivity compared with cisgender men in superior parietal regions, as part of the salience (SN) and the executive control (ECN) networks. Transmen also had weaker connectivity compared with cisgender men between intra-SN regions and weaker inter-network connectivity between regions of the SN, the default mode network (DMN), the ECN and the sensorimotor network. Transwomen had lower small-worldness, modularity and clustering coefficient than cisgender men. There were no differences among transmen, transwomen, and ciswomen. Together these results underline the importance of the SN interacting with DMN, ECN, and sensorimotor networks in transmen, involving regions of the entire brain with a frontal predominance. Reduced global connectivity graph-theoretical measures were a characteristic of transwomen. It is proposed that the interaction between networks is a keystone in building a gendered self. Finally, our findings suggest that both proposed hypotheses are complementary in explaining brain differences between gender variants. PURPOSE Melanoma brain metastases (MBM) occur in ∼50% of melanoma patients. Although both radiation therapy (RT) and immune checkpoint inhibitor (ICI) are used alone or in combination for MBM treatment, the role of this combination and how these treatments could best be sequenced remains unclear. METHODS AND MATERIALS We conducted a retrospective analysis of patients with resected MBM who underwent treatment with RT, ICI, or a combination of RT and ICI. Among the latter, we specifically investigated the differential gene expression via RNA-sequencing between patients who received RT first then ICI (RT → ICI) versus ICI first then RT (ICI → RT). We used a glycoprotein-transduced syngeneic melanoma mouse model for validation experiments. RESULTS We found that for patients with resected MBM, a combination of RT and ICI confers superior survival compared with RT alone. Specifically, we found that RT → ICI was superior compared with ICI → RT. Transcriptome analysis of resected MBM revealed that the RT → ICI cohort demonstrated deregulation of genes involved in apoptotic signaling and key modulators of inflammation that are most implicated in nuclear factor kappa-light-chain-enhancer of activated B cells signaling.