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https://www.readbyqxmd.com/read/28936158/bayesian-tractography-using-geometric-shape-priors
#1
Xiaoming Dong, Zhengwu Zhang, Anuj Srivastava
The problem of estimating neuronal fiber tracts connecting different brain regions is important for various types of brain studies, including understanding brain functionality and diagnosing cognitive impairments. The popular techniques for tractography are mostly sequential-tracts are grown sequentially following principal directions of local water diffusion profiles. Despite several advancements on this basic idea, the solutions easily get stuck in local solutions, and can't incorporate global shape information...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28915367/breathlessness-and-the-body-neuroimaging-clues-for-the-inferential-leap
#2
Olivia K Faull, Anja Hayen, Kyle T S Pattinson
Breathlessness debilitates millions of people with chronic illness. Mismatch between breathlessness severity and objective disease markers is common and poorly understood. Traditionally, sensory perception was conceptualised as a stimulus-response relationship, although this cannot explain how conditioned symptoms may occur in the absence of physiological signals from the lungs or airways. A Bayesian model is now proposed, in which the brain generates sensations based on expectations learnt from past experiences (priors), which are then checked against incoming afferent signals...
August 9, 2017: Cortex; a Journal Devoted to the Study of the Nervous System and Behavior
https://www.readbyqxmd.com/read/28912425/predictive-models-of-minimal-hepatic-encephalopathy-for-cirrhotic-patients-based-on-large-scale-brain-intrinsic-connectivity-networks
#3
Yun Jiao, Xun-Heng Wang, Rong Chen, Tian-Yu Tang, Xi-Qi Zhu, Gao-Jun Teng
We aimed to find the most representative connectivity patterns for minimal hepatic encephalopathy (MHE) using large-scale intrinsic connectivity networks (ICNs) and machine learning methods. Resting-state fMRI was administered to 33 cirrhotic patients with MHE and 43 cirrhotic patients without MHE (NMHE). The connectivity maps of 20 ICNs for each participant were obtained by dual regression. A Bayesian machine learning technique, called Graphical Model-based Multivariate Analysis, was applied to determine ICN regions that characterized group differences...
September 14, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28890416/bayesian-population-receptive-field-modelling
#4
REVIEW
Peter Zeidman, Edward Harry Silson, Dietrich Samuel Schwarzkopf, Chris Ian Baker, Will Penny
We introduce a probabilistic (Bayesian) framework and associated software toolbox for mapping population receptive fields (pRFs) based on fMRI data. This generic approach is intended to work with stimuli of any dimension and is demonstrated and validated in the context of 2D retinotopic mapping. The framework enables the experimenter to specify generative (encoding) models of fMRI timeseries, in which experimental stimuli enter a pRF model of neural activity, which in turns drives a nonlinear model of neurovascular coupling and Blood Oxygenation Level Dependent (BOLD) response...
September 8, 2017: NeuroImage
https://www.readbyqxmd.com/read/28882000/integrative-deep-models-for-alternative-splicing
#5
Anupama Jha, Matthew R Gazzara, Yoseph Barash
Motivation: Advancements in sequencing technologies have highlighted the role of alternative splicing (AS) in increasing transcriptome complexity. This role of AS, combined with the relation of aberrant splicing to malignant states, motivated two streams of research, experimental and computational. The first involves a myriad of techniques such as RNA-Seq and CLIP-Seq to identify splicing regulators and their putative targets. The second involves probabilistic models, also known as splicing codes, which infer regulatory mechanisms and predict splicing outcome directly from genomic sequence...
July 15, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28874923/noninvasive-brain-stimulation-maladaptive-plasticity-and-bayesian-analysis-in-phantom-limb-pain
#6
REVIEW
Leon Morales-Quezada
Introduction: Phantom limb pain (PLP) is a common and poorly understood pathology of difficult medical control that progressively takes place after amputation occurs. Objective: This article discusses the multifactorial bases of PLP. These bases involve local changes at the stump level, spinal modifications of excitability, deafferentation, and central sensitization, leading to the development of maladaptive plasticity, and consequentially, defective processing of sensory information by associative neural networks...
August 1, 2017: Medical Acupuncture
https://www.readbyqxmd.com/read/28861338/increased-default-mode-variability-is-related-to-reduced-task-performance-and-is-evident-in-adults-with-adhd
#7
Athanasia M Mowinckel, Dag Alnæs, Mads L Pedersen, Sigurd Ziegler, Mats Fredriksen, Tobias Kaufmann, Edmund Sonuga-Barke, Tor Endestad, Lars T Westlye, Guido Biele
Insufficient suppression and connectivity of the default mode network (DMN) is a potential mediator of cognitive dysfunctions across various disorders, including attention deficit/hyperactivity disorder (ADHD). However, it remains unclear if alterations in sustained DMN suppression, variability and connectivity during prolonged cognitive engagement are implicated in adult ADHD pathophysiology, and to which degree methylphenidate (MPH) remediates any DMN abnormalities. This randomized, double-blinded, placebo-controlled, cross-over clinical trial of MPH (clinicaltrials...
2017: NeuroImage: Clinical
https://www.readbyqxmd.com/read/28854000/multistable-perception-and-the-role-of-frontoparietal-cortex-in-perceptual-inference
#8
Jan Brascamp, Philipp Sterzer, Randolph Blake, Tomas Knapen
A given pattern of optical stimulation can arise from countless possible realworld sources, creating a dilemma for vision: What in the world actually gives rise to the current pattern? This dilemma was pointed out centuries ago by the astronomer and mathematician Ibn al-Haytham and was forcefully restated 150 years ago when von Helmholtz characterized perception as unconscious inference. To buttress his contention, von Helmholtz cited multistable perception: recurring changes in perception despite unchanging sensory input...
August 30, 2017: Annual Review of Psychology
https://www.readbyqxmd.com/read/28843540/pattern-component-modeling-a-flexible-approach-for-understanding-the-representational-structure-of-brain-activity-patterns
#9
REVIEW
Jörn Diedrichsen, Atsushi Yokoi, Spencer A Arbuckle
Representational models specify how complex patterns of neural activity relate to visual stimuli, motor actions, or abstract thoughts. Here we review pattern component modeling (PCM), a practical Bayesian approach for evaluating such models. Similar to encoding models, PCM evaluates the ability of models to predict novel brain activity patterns. In contrast to encoding models, however, the activity of individual voxels across conditions (activity profiles) are not directly fitted. Rather, PCM integrates over all possible activity profiles and computes the marginal likelihood of the data under the activity profile distribution specified by the representational model...
August 24, 2017: NeuroImage
https://www.readbyqxmd.com/read/28841647/probing-the-compartmentalization-of-hiv-1-in-the-central-nervous-system-through-its-neutralization-properties
#10
Karl Stefic, Antoine Chaillon, Mélanie Bouvin-Pley, Alain Moreau, Martine Braibant, Frédéric Bastides, Guillaume Gras, Louis Bernard, Francis Barin
Compartmentalization of HIV-1 has been observed in the cerebrospinal fluid (CSF) of patients at different clinical stages. Considering the low permeability of the blood-brain barrier, we wondered if a reduced selective pressure by neutralizing antibodies (NAb) in the central nervous system (CNS) could favor the evolution of NAb-sensitive viruses in this compartment. Single genome amplification (SGA) was used to sequence full-length HIV-1 envelope variants (453 sequences) from paired CSF and blood plasma samples in 9 subjects infected by HIV variants of various clades and suffering from diverse neurologic disorders...
2017: PloS One
https://www.readbyqxmd.com/read/28838469/the-unpredictive-brain-under-threat-a-neurocomputational-account-of-anxious-hypervigilance
#11
Brian R Cornwell, Marta I Garrido, Cassie Overstreet, Daniel S Pine, Christian Grillon
BACKGROUND: Anxious hypervigilance is marked by sensitized sensory-perceptual processes and attentional biases to potential danger cues in the environment. How this is realized at the neurocomputational level is unknown but could clarify the brain mechanisms disrupted in psychiatric conditions such as posttraumatic stress disorder. Predictive coding, instantiated by dynamic causal models, provides a promising framework to ground these state-related changes in the dynamic interactions of reciprocally connected brain areas...
September 15, 2017: Biological Psychiatry
https://www.readbyqxmd.com/read/28834873/a-bayesian-network-meta-analysis-of-whole-brain-radiotherapy-and-stereotactic-radiotherapy-for-brain-metastasis
#12
Xi Yuan, Wen-Jie Liu, Bing Li, Ze-Tian Shen, Jun-Shu Shen, Xi-Xu Zhu
This study was conducted to compare the effects of whole brain radiotherapy (WBRT) and stereotactic radiotherapy (SRS) in treatment of brain metastasis.A systematical retrieval in PubMed and Embase databases was performed for relative literatures on the effects of WBRT and SRS in treatment of brain metastasis. A Bayesian network meta-analysis was performed by using the ADDIS software. The effect sizes included odds ratio (OR) and 95% confidence interval (CI). A random effects model was used for the pooled analysis for all the outcome measures, including 1-year distant control rate, 1-year local control rate, 1-year survival rate, and complication...
August 2017: Medicine (Baltimore)
https://www.readbyqxmd.com/read/28822751/using-multi-level-bayesian-lesion-symptom-mapping-to-probe-the-body-part-specificity-of-gesture-imitation-skills
#13
Elisabeth I S Achilles, Peter H Weiss, Gereon R Fink, Ellen Binder, Cathy J Price, Thomas M H Hope
Past attempts to identify the neural substrates of hand and finger imitation skills in the left hemisphere of the brain have yielded inconsistent results. Here, we analyse those associations in a large sample of 257 left hemisphere stroke patients. By introducing novel Bayesian methods, we characterise lesion symptom associations at three levels: the voxel-level, the single-region level (using anatomically defined regions), and the region-pair level. The results are inconsistent across those three levels and we argue that each level of analysis makes assumptions which constrain the results it can produce...
August 16, 2017: NeuroImage
https://www.readbyqxmd.com/read/28822294/does-reconsolidation-occur-in-natural-settings-memory-reconsolidation-and-anxiety-disorders
#14
REVIEW
Rodrigo S Fernández, María E Pedreira, Mariano M Boccia
In normal settings, our brain is able to update its stored representations in content, strength, and/or expectations by the memory reconsolidation process. Thus, a reactivated memory enters in a transient labile state (destabilization) followed by a re-stabilization phase in order to persist (memory reconsolidation). Cognitive neuroscience and its insight into psychiatric problems attributed a close relationship between memory (formation, maintenance, and utilization) and several mental disorders. In this framework, the reconsolidation process could be not only the mechanism for maintenance of some psychopathologies, but also open a novel therapeutic window...
August 10, 2017: Clinical Psychology Review
https://www.readbyqxmd.com/read/28814635/perception-of-the-dynamic-visual-vertical-during-sinusoidal-linear-motion
#15
Antonella Pomante, Luc P J Selen, W Pieter Medendorp
The vestibular system provides information for spatial orientation. However, this information is ambiguous: because the otoliths sense the gravito-inertial force, they cannot distinguish gravitational and inertial components. As a consequence, prolonged linear acceleration of the head can be interpreted as tilt, referred to as the somatogravic effect. Previous modeling work suggests that the brain disambiguates the otolith signal according to the rules of Bayesian inference, combining noisy canal cues with the a priori assumption that prolonged linear accelerations are unlikely...
August 16, 2017: Journal of Neurophysiology
https://www.readbyqxmd.com/read/28809668/tractography-based-score-for-learning-effective-connectivity-from-multimodal-imaging-data-using-dynamic-bayesian-networks
#16
Shilpa Dang, Santanu Chaudhury, Brejesh Lall, Prasun K Roy
OBJECTIVE: Effective connectivity (EC) is the methodology for determining functional-integration among the functionally-active segregated regions of the brain. By definition [1] EC is "the causal influence exerted by one neuronal group on another" which is constrained by anatomical connectivity (AC) (axonal connections). AC is necessary for EC but does not fully determine it, because synaptic communication occurs dynamically in a context-dependent fashion. Although there is a vast emerging evidence of structure-function relationship using multimodal imaging studies, till date only a few studies have done joint modelling of the two modalities: functional MRI (fMRI) and Diffusion Tensor Imaging (DTI)...
August 10, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28801251/modeling-correlated-noise-is-necessary-to-decode-uncertainty
#17
REVIEW
R S van Bergen, J F M Jehee
Brain decoding algorithms form an important part of the arsenal of analysis tools available to neuroscientists, allowing for a more detailed study of the kind of information represented in patterns of cortical activity. While most current decoding algorithms focus on estimating a single, most likely stimulus from the pattern of noisy fMRI responses, the presence of noise causes this estimate to be uncertain. This uncertainty in stimulus estimates is a potentially highly relevant aspect of cortical stimulus processing, and features prominently in Bayesian or probabilistic models of neural coding...
August 8, 2017: NeuroImage
https://www.readbyqxmd.com/read/28782681/a-bayesian-spatial-model-for-neuroimaging-data-based-on-biologically-informed-basis-functions
#18
Ismael Huertas, Marianne Oldehinkel, Erik S B van Oort, David Garcia-Solis, Pablo Mir, Christian F Beckmann, Andre F Marquand
The dominant approach to neuroimaging data analysis employs the voxel as the unit of computation. While convenient, voxels lack biological meaning and their size is arbitrarily determined by the resolution of the image. Here, we propose a multivariate spatial model in which neuroimaging data are characterised as a linearly weighted combination of multiscale basis functions which map onto underlying brain nuclei or networks or nuclei. In this model, the elementary building blocks are derived to reflect the functional anatomy of the brain during the resting state...
August 4, 2017: NeuroImage
https://www.readbyqxmd.com/read/28777721/infinite-von-mises-fisher-mixture-modeling-of-whole-brain-fmri-data
#19
Rasmus E Røge, Kristoffer H Madsen, Mikkel N Schmidt, Morten Mørup
Cluster analysis of functional magnetic resonance imaging (fMRI) data is often performed using gaussian mixture models, but when the time series are standardized such that the data reside on a hypersphere, this modeling assumption is questionable. The consequences of ignoring the underlying spherical manifold are rarely analyzed, in part due to the computational challenges imposed by directional statistics. In this letter, we discuss a Bayesian von Mises-Fisher (vMF) mixture model for data on the unit hypersphere and present an efficient inference procedure based on collapsed Markov chain Monte Carlo sampling...
October 2017: Neural Computation
https://www.readbyqxmd.com/read/28774437/new-approach-to-detect-and-classify-stroke-in-skull-ct-images-via-analysis-of-brain-tissue-densities
#20
Pedro P Rebouças Filho, Róger Moura Sarmento, Gabriel Bandeira Holanda, Daniel de Alencar Lima
BACKGROUND AND OBJECTIVE: Cerebral vascular accident (CVA), also known as stroke, is an important health problem worldwide and it affects 16 million people worldwide every year. About 30% of those that have a stroke die and 40% remain with serious physical limitations. However, recovery in the damaged region is possible if treatment is performed immediately. In the case of a stroke, Computed Tomography (CT) is the most appropriate technique to confirm the occurrence and to investigate its extent and severity...
September 2017: Computer Methods and Programs in Biomedicine
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