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https://www.readbyqxmd.com/read/28774650/rapid-anatomical-brain-imaging-using-spiral-acquisition-and-an-expanded-signal-model
#1
Lars Kasper, Maria Engel, Christoph Barmet, Maximilian Haeberlin, Bertram J Wilm, Benjamin E Dietrich, Thomas Schmid, Simon Gross, David O Brunner, Klaas E Stephan, Klaas P Pruessmann
We report the deployment of spiral acquisition for high-resolution structural imaging at 7T. Long spiral readouts are rendered manageable by an expanded signal model including static off-resonance and B0 dynamics along with k-space trajectories and coil sensitivity maps. Image reconstruction is accomplished by inversion of the signal model using an extension of the iterative non-Cartesian SENSE algorithm. Spiral readouts up to 25 ms are shown to permit whole-brain 2D imaging at 0.5 mm in-plane resolution in less than a minute...
July 31, 2017: NeuroImage
https://www.readbyqxmd.com/read/28767650/the-stochastic-early-reaction-inhibition-and-late-action-seria-model-for-antisaccades
#2
Eduardo A Aponte, Dario Schöbi, Klaas E Stephan, Jakob Heinzle
The antisaccade task is a classic paradigm used to study the voluntary control of eye movements. It requires participants to suppress a reactive eye movement to a visual target and to concurrently initiate a saccade in the opposite direction. Although several models have been proposed to explain error rates and reaction times in this task, no formal model comparison has yet been performed. Here, we describe a Bayesian modeling approach to the antisaccade task that allows us to formally compare different models on the basis of their evidence...
August 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28619481/computational-psychosomatics-and-computational-psychiatry-toward-a-joint-framework-for-differential-diagnosis
#3
REVIEW
Frederike H Petzschner, Lilian A E Weber, Tim Gard, Klaas E Stephan
This article outlines how a core concept from theories of homeostasis and cybernetics, the inference-control loop, may be used to guide differential diagnosis in computational psychiatry and computational psychosomatics. In particular, we discuss 1) how conceptualizing perception and action as inference-control loops yields a joint computational perspective on brain-world and brain-body interactions and 2) how the concrete formulation of this loop as a hierarchical Bayesian model points to key computational quantities that inform a taxonomy of potential disease mechanisms...
May 25, 2017: Biological Psychiatry
https://www.readbyqxmd.com/read/28612049/episodic-tags-enhance-striatal-valuation-signals-during-temporal-discounting-in-pathological-gamblers
#4
Antonius Wiehler, Frederike Hermi Petzschner, Klaas Enno Stephan, Jan Peters
Similar to many addiction disorders, pathological gambling is associated with an increased preference for immediate rewards (steep temporal discounting). In healthy participants, episodic future thinking has been shown to reduce impulsivity during intertemporal choice. Here, we examine for the first time a modulation of temporal discounting via episodic future thinking in a group of pathological gamblers. We investigated a sample of 24 pathological gamblers and 24 matched healthy controls with functional magnetic resonance imaging (fMRI)...
May 2017: ENeuro
https://www.readbyqxmd.com/read/28259780/regression-dcm-for-fmri
#5
Stefan Frässle, Ekaterina I Lomakina, Adeel Razi, Karl J Friston, Joachim M Buhmann, Klaas E Stephan
The development of large-scale network models that infer the effective (directed) connectivity among neuronal populations from neuroimaging data represents a key challenge for computational neuroscience. Dynamic causal models (DCMs) of neuroimaging and electrophysiological data are frequently used for inferring effective connectivity but are presently restricted to small graphs (typically up to 10 regions) in order to keep model inversion computationally feasible. Here, we present a novel variant of DCM for functional magnetic resonance imaging (fMRI) data that is suited to assess effective connectivity in large (whole-brain) networks...
March 1, 2017: NeuroImage
https://www.readbyqxmd.com/read/28179228/dietary-nitrate-does-not-reduce-oxygen-cost-of-exercise-or-improve-muscle-mitochondrial-function-in-patients-with-mitochondrial-myopathy
#6
Miranda Nabben, Joep P J Schmitz, Jolita Ciapaite, Carlijn M P le Clercq, Natal A van Riel, Harm R Haak, Klaas Nicolay, Irenaeus F M de Coo, Hubert Smeets, Stephan F Praet, Luc J van Loon, Jeanine J Prompers
Muscle weakness and exercise intolerance negatively affect the quality of life of patients with mitochondrial myopathy. Short-term dietary nitrate supplementation has been shown to improve exercise performance and reduce oxygen cost of exercise in healthy humans and trained athletes. We investigated whether 1 wk of dietary inorganic nitrate supplementation decreases the oxygen cost of exercise and improves mitochondrial function in patients with mitochondrial myopathy. Ten patients with mitochondrial myopathy (40 ± 5 yr, maximal whole body oxygen uptake = 21...
May 1, 2017: American Journal of Physiology. Regulatory, Integrative and Comparative Physiology
https://www.readbyqxmd.com/read/28119508/hierarchical-prediction-errors-in-midbrain-and-septum-during-social-learning
#7
Andreea O Diaconescu, Christoph Mathys, Lilian A E Weber, Lars Kasper, Jan Mauer, Klaas E Stephan
Social learning is fundamental to human interactions, yet its computational and physiological mechanisms are not well understood. One prominent open question concerns the role of neuromodulatory transmitters. We combined fMRI, computational modelling and genetics to address this question in two separate samples (N = 35, N = 47). Participants played a game requiring inference on an adviser's intentions whose motivation to help or mislead changed over time. Our analyses suggest that hierarchically structured belief updates about current advice validity and the adviser's trustworthiness, respectively, depend on different neuromodulatory systems...
April 1, 2017: Social Cognitive and Affective Neuroscience
https://www.readbyqxmd.com/read/28077303/analysis-and-correction-of-field-fluctuations-in-fmri-data-using-field-monitoring
#8
Saskia Bollmann, Lars Kasper, S Johanna Vannesjo, Andreea O Diaconescu, Benjamin E Dietrich, Simon Gross, Klaas E Stephan, Klaas P Pruessmann
This work investigates the role of magnetic field fluctuations as a confound in fMRI. In standard fMRI experiments with single-shot EPI acquisition at 3 Tesla the uniform and gradient components of the magnetic field were recorded with NMR field sensors. By principal component analysis it is found that differences of field evolution between the EPI readouts are explainable by few components relating to slow and within-shot field dynamics of hardware and physiological origin. The impact of fluctuating field components is studied by selective data correction and assessment of its influence on image fluctuation and SFNR...
July 1, 2017: NeuroImage
https://www.readbyqxmd.com/read/28011043/prediction-of-individual-differences-from-neuroimaging-data
#9
EDITORIAL
Vince D Calhoun, Stephan M Lawrie, Janaina Mourao-Miranda, Klaas E Stephan
No abstract text is available yet for this article.
January 15, 2017: NeuroImage
https://www.readbyqxmd.com/read/27895566/allostatic-self-efficacy-a-metacognitive-theory-of-dyshomeostasis-induced-fatigue-and-depression
#10
Klaas E Stephan, Zina M Manjaly, Christoph D Mathys, Lilian A E Weber, Saee Paliwal, Tim Gard, Marc Tittgemeyer, Stephen M Fleming, Helene Haker, Anil K Seth, Frederike H Petzschner
This paper outlines a hierarchical Bayesian framework for interoception, homeostatic/allostatic control, and meta-cognition that connects fatigue and depression to the experience of chronic dyshomeostasis. Specifically, viewing interoception as the inversion of a generative model of viscerosensory inputs allows for a formal definition of dyshomeostasis (as chronically enhanced surprise about bodily signals, or, equivalently, low evidence for the brain's model of bodily states) and allostasis (as a change in prior beliefs or predictions which define setpoints for homeostatic reflex arcs)...
2016: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/27846219/pharmacological-fingerprints-of-contextual-uncertainty
#11
Louise Marshall, Christoph Mathys, Diane Ruge, Archy O de Berker, Peter Dayan, Klaas E Stephan, Sven Bestmann
Successful interaction with the environment requires flexible updating of our beliefs about the world. By estimating the likelihood of future events, it is possible to prepare appropriate actions in advance and execute fast, accurate motor responses. According to theoretical proposals, agents track the variability arising from changing environments by computing various forms of uncertainty. Several neuromodulators have been linked to uncertainty signalling, but comprehensive empirical characterisation of their relative contributions to perceptual belief updating, and to the selection of motor responses, is lacking...
November 2016: PLoS Biology
https://www.readbyqxmd.com/read/27832957/the-physio-toolbox-for-modeling-physiological-noise-in-fmri-data
#12
Lars Kasper, Steffen Bollmann, Andreea O Diaconescu, Chloe Hutton, Jakob Heinzle, Sandra Iglesias, Tobias U Hauser, Miriam Sebold, Zina-Mary Manjaly, Klaas P Pruessmann, Klaas E Stephan
BACKGROUND: Physiological noise is one of the major confounds for fMRI. A common class of correction methods model noise from peripheral measures, such as ECGs or pneumatic belts. However, physiological noise correction has not emerged as a standard preprocessing step for fMRI data yet due to: (1) the varying data quality of physiological recordings, (2) non-standardized peripheral data formats and (3) the lack of full automatization of processing and modeling physiology, required for large-cohort studies...
January 30, 2017: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/27801751/extraintestinal-manifestations-of-pediatric-inflammatory-bowel-disease-prevalence-presentation-and-anti-tnf-treatment
#13
Thomas Greuter, Fabio Bertoldo, Roman Rechner, Alex Straumann, Luc Biedermann, Jonas Zeitz, Benjamin Misselwitz, Michael Scharl, Gerhard Rogler, Ekaterina Safroneeva, Raja A Ali, Christian Braegger, Klaas Heyland, Pascal Mueller, Andreas Nydegger, Laetitia-Marie Petit, Susanne Schibli, Raoul I Furlano, Johannes Spalinger, Michela Schäppi, Samuel Zamora, Florian Froehlich, Denise Herzog, Alain M Schoepfer, Stephan R Vavricka
BACKGROUND: There is a paucity of data on extraintestinal manifestations (EIM) and their treatment in pediatric patients with inflammatory bowel disease (IBD). METHODS: Since 2008, the Pediatric Swiss IBD Cohort Study has collected data on the pediatric IBD population in Switzerland. Data on 329 patients were analyzed retrospectively. RESULTS: 55 patients (16.7%) suffered from 1-4 EIM (39 Crohn's disease, 12 ulcerative colitis and 4 IBD-Unclassified (IBD-U) patients)...
October 31, 2016: Journal of Pediatric Gastroenterology and Nutrition
https://www.readbyqxmd.com/read/27653804/models-of-neuromodulation-for-computational-psychiatry
#14
REVIEW
Sandra Iglesias, Sara Tomiello, Maya Schneebeli, Klaas E Stephan
Psychiatry faces fundamental challenges: based on a syndrome-based nosology, it presently lacks clinical tests to infer on disease processes that cause symptoms of individual patients and must resort to trial-and-error treatment strategies. These challenges have fueled the recent emergence of a novel field-computational psychiatry-that strives for mathematical models of disease processes at physiological and computational (information processing) levels. This review is motivated by one particular goal of computational psychiatry: the development of 'computational assays' that can be applied to behavioral or neuroimaging data from individual patients and support differential diagnosis and guiding patient-specific treatment...
May 2017: Wiley Interdisciplinary Reviews. Cognitive Science
https://www.readbyqxmd.com/read/27450778/the-dysconnection-hypothesis-2016
#15
REVIEW
Karl Friston, Harriet R Brown, Jakob Siemerkus, Klaas E Stephan
Twenty years have passed since the dysconnection hypothesis was first proposed (Friston and Frith, 1995; Weinberger, 1993). In that time, neuroscience has witnessed tremendous advances: we now live in a world of non-invasive neuroanatomy, computational neuroimaging and the Bayesian brain. The genomics era has come and gone. Connectomics and large-scale neuroinformatics initiatives are emerging everywhere. So where is the dysconnection hypothesis now? This article considers how the notion of schizophrenia as a dysconnection syndrome has developed - and how it has been enriched by recent advances in clinical neuroscience...
October 2016: Schizophrenia Research
https://www.readbyqxmd.com/read/27378955/can-bayesian-theories-of-autism-spectrum-disorder-help-improve-clinical-practice
#16
Helene Haker, Maya Schneebeli, Klaas Enno Stephan
Diagnosis and individualized treatment of autism spectrum disorder (ASD) represent major problems for contemporary psychiatry. Tackling these problems requires guidance by a pathophysiological theory. In this paper, we consider recent theories that re-conceptualize ASD from a "Bayesian brain" perspective, which posit that the core abnormality of ASD resides in perceptual aberrations due to a disbalance in the precision of prediction errors (sensory noise) relative to the precision of predictions (prior beliefs)...
2016: Frontiers in Psychiatry
https://www.readbyqxmd.com/read/27343221/bayesian-inference-dysconnectivity-and-neuromodulation-in-schizophrenia
#17
Klaas E Stephan, Andreea O Diaconescu, Sandra Iglesias
No abstract text is available yet for this article.
July 2016: Brain: a Journal of Neurology
https://www.readbyqxmd.com/read/27303285/learning-what-to-see-in-a-changing-world
#18
Katharina Schmack, Veith Weilnhammer, Jakob Heinzle, Klaas E Stephan, Philipp Sterzer
Visual perception is strongly shaped by expectations, but it is poorly understood how such perceptual expectations are learned in our dynamic sensory environment. Here, we applied a Bayesian framework to investigate whether perceptual expectations are continuously updated from different aspects of ongoing experience. In two experiments, human observers performed an associative learning task in which rapidly changing expectations about the appearance of ambiguous stimuli were induced. We found that perception of ambiguous stimuli was biased by both learned associations and previous perceptual outcomes...
2016: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/27179179/inflammation-biomarkers-and-mortality-prediction-in-patients-with-type-2-diabetes-zodiac-27
#19
Gijs W D Landman, Nanne Kleefstra, Klaas H Groenier, Stephan J L Bakker, Geert H Groeneveld, Henk J G Bilo, Kornelis J J van Hateren
BACKGROUND: C-reactive protein (CRP), procalcitonin (PCT) and pro-adrenomedullin (MR-proADM) are inflammation markers associated with long-term mortality risk. We compared the associations and predictive capacities of CRP, PCT and MR-proADM with cardiovascular and all-cause mortality in patients with type 2 diabetes. METHODS: This study included primary care treated patients with type 2 diabetes participating in the ZODIAC cohort study. A total of 1005 out of 1688 patients (60%) had complete baseline variables...
July 2016: Atherosclerosis
https://www.readbyqxmd.com/read/27141854/a-hierarchical-model-for-integrating-unsupervised-generative-embedding-and-empirical-bayes
#20
Sudhir Raman, Lorenz Deserno, Florian Schlagenhauf, Klaas Enno Stephan
BACKGROUND: Generative models of neuroimaging data, such as dynamic causal models (DCMs), are commonly used for inferring effective connectivity from individual subject data. Recently introduced "generative embedding" approaches have used DCM-based connectivity parameters for supervised classification of individual patients or to find unknown subgroups in heterogeneous groups using unsupervised clustering methods. NEW METHOD: We present a novel framework which combines DCMs with finite mixture models into a single hierarchical model...
August 30, 2016: Journal of Neuroscience Methods
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