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Bayesian Brain

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https://www.readbyqxmd.com/read/28714853/unveiling-the-development-of-intracranial-injury-using-dynamic-brain-eit-an-evaluation-of-current-reconstruction-algorithms
#1
Haoting Li, Rongqing Chen, Canhua Xu, Benyuan Liu, Mengxing Tang, Lin Yang, Xiuzhen Dong, Feng Fu
Dynamic brain EIT is a promising technique for continuous monitoring the development of cerebral injury. While there are many reconstruction algorithms available to brain EIT, there is still a lack of study to compare their performance in the context of dynamic brain monitoring. To address the problem, we develop a framework for evaluating different current algorithms with their ability to correctly identify small intracranial conductivity changes. Firstly, a simulation 3D head phantom with realistic layered structure and impedance distribution were developed...
July 17, 2017: Physiological Measurement
https://www.readbyqxmd.com/read/28702345/hierarchical-disruption-in-the-bayesian-brain-focal-epilepsy-and-brain-networks
#2
Amir Omidvarnia, Mangor Pedersen, Richard E Rosch, Karl J Friston, Graeme D Jackson
In this opinion paper, we describe a combined view of functional and effective brain connectivity along with the free-energy principle for investigating persistent disruptions in brain networks of patients with focal epilepsy. These changes are likely reflected in effective connectivity along the cortical hierarchy and construct the basis of increased local functional connectivity in focal epilepsy. We propose a testable framework based on dynamic causal modelling and functional connectivity analysis with the capacity of explaining commonly observed connectivity changes during interictal periods...
2017: NeuroImage: Clinical
https://www.readbyqxmd.com/read/28688579/replicable-and-coupled-changes-in-innate-and-adaptive-immune-gene-expression-in-two-case-control-studies-of-blood-microarrays-in-major-depressive-disorder
#3
Gwenaël G R Leday, Petra E Vértes, Sylvia Richardson, Jonathan R Greene, Tim Regan, Shahid Khan, Robbie Henderson, Tom C Freeman, Carmine M Pariante, Neil A Harrison, V Hugh Perry, Wayne C Drevets, Gayle M Wittenberg, Edward T Bullmore
BACKGROUND: Peripheral inflammation is often associated with major depressive disorder (MDD), and immunological biomarkers of depression remain a focus of investigation. METHODS: We used microarray data on whole blood from two independent case-control studies of MDD: the GlaxoSmithKline-High-Throughput Disease-specific target Identification Program [GSK-HiTDiP] study (113 patients and 57 healthy control subjects) and the Janssen-Brain Resource Company study (94 patients and 100 control subjects)...
July 6, 2017: Biological Psychiatry
https://www.readbyqxmd.com/read/28663729/estimating-the-information-extracted-by-a-single-spiking-neuron-from-a-continuous-input-time-series
#4
Fleur Zeldenrust, Sicco de Knecht, Wytse J Wadman, Sophie Denève, Boris Gutkin
Understanding the relation between (sensory) stimuli and the activity of neurons (i.e., "the neural code") lies at heart of understanding the computational properties of the brain. However, quantifying the information between a stimulus and a spike train has proven to be challenging. We propose a new (in vitro) method to measure how much information a single neuron transfers from the input it receives to its output spike train. The input is generated by an artificial neural network that responds to a randomly appearing and disappearing "sensory stimulus": the hidden state...
2017: Frontiers in Computational Neuroscience
https://www.readbyqxmd.com/read/28663726/neural-cross-frequency-coupling-functions
#5
Tomislav Stankovski, Valentina Ticcinelli, Peter V E McClintock, Aneta Stefanovska
Although neural interactions are usually characterized only by their coupling strength and directionality, there is often a need to go beyond this by establishing the functional mechanisms of the interaction. We introduce the use of dynamical Bayesian inference for estimation of the coupling functions of neural oscillations in the presence of noise. By grouping the partial functional contributions, the coupling is decomposed into its functional components and its most important characteristics-strength and form-are quantified...
2017: Frontiers in Systems Neuroscience
https://www.readbyqxmd.com/read/28658252/integration-of-individual-and-social-information-for-decision-making-in-groups-of-different-sizes
#6
Seongmin A Park, Sidney Goïame, David A O'Connor, Jean-Claude Dreher
When making judgments in a group, individuals often revise their initial beliefs about the best judgment to make given what others believe. Despite the ubiquity of this phenomenon, we know little about how the brain updates beliefs when integrating personal judgments (individual information) with those of others (social information). Here, we investigated the neurocomputational mechanisms of how we adapt our judgments to those made by groups of different sizes, in the context of jury decisions for a criminal...
June 2017: PLoS Biology
https://www.readbyqxmd.com/read/28649314/hierarchical-cortical-transcriptome-disorganization-in-autism
#7
Michael V Lombardo, Eric Courchesne, Nathan E Lewis, Tiziano Pramparo
BACKGROUND: Autism spectrum disorders (ASD) are etiologically heterogeneous and complex. Functional genomics work has begun to identify a diverse array of dysregulated transcriptomic programs (e.g., synaptic, immune, cell cycle, DNA damage, WNT signaling, cortical patterning and differentiation) potentially involved in ASD brain abnormalities during childhood and adulthood. However, it remains unclear whether such diverse dysregulated pathways are independent of each other or instead reflect coordinated hierarchical systems-level pathology...
2017: Molecular Autism
https://www.readbyqxmd.com/read/28647485/dynamic-network-model-with-continuous-valued-nodes-for-longitudinal-brain-morphometry
#8
Rong Chen, Yuanjie Zheng, Erika Nixon, Edward H Herskovits
Longitudinal brain morphometry probes time-related brain morphometric patterns. We propose a method called dynamic network modeling with continuous valued nodes to generate a dynamic brain network from continuous valued longitudinal morphometric data. The mathematical framework of this method is based on state-space modeling. We use a bootstrap-enhanced least absolute shrinkage operator to solve the network-structure generation problem. In contrast to discrete dynamic Bayesian network modeling, the proposed method enables network generation directly from continuous valued high-dimensional short sequence data, being free from any discretization process...
June 21, 2017: NeuroImage
https://www.readbyqxmd.com/read/28630937/high-precision-neural-decoding-of-complex-movement-trajectories-using-recursive-bayesian-estimation-with-dynamic-movement-primitives
#9
Guy Hotson, Ryan J Smith, Adam G Rouse, Marc H Schieber, Nitish V Thakor, Brock A Wester
Brain-machine interfaces (BMIs) are a rapidly progressing technology with the potential to restore function to victims of severe paralysis via neural control of robotic systems. Great strides have been made in directly mapping a user's cortical activity to control of the individual degrees of freedom of robotic end-effectors. While BMIs have yet to achieve the level of reliability desired for widespread clinical use, environmental sensors (e.g. RGB-D cameras for object detection) and prior knowledge of common movement trajectories hold great potential for improving system performance...
July 2016: IEEE Robotics and Automation Letters
https://www.readbyqxmd.com/read/28630885/bayesian-framework-inspired-no-reference-region-of-interest-quality-measure-for-brain-mri-images
#10
Michael Osadebey, Marius Pedersen, Douglas Arnold, Katrina Wendel-Mitoraj
We describe a postacquisition, attribute-based quality assessment method for brain magnetic resonance imaging (MRI) images. It is based on the application of Bayes theory to the relationship between entropy and image quality attributes. The entropy feature image of a slice is segmented into low- and high-entropy regions. For each entropy region, there are three separate observations of contrast, standard deviation, and sharpness quality attributes. A quality index for a quality attribute is the posterior probability of an entropy region given any corresponding region in a feature image where quality attribute is observed...
April 2017: Journal of Medical Imaging
https://www.readbyqxmd.com/read/28630413/bayesian-inference-of-physiologically-meaningful-parameters-from-body-sway-measurements
#11
A Tietäväinen, M U Gutmann, E Keski-Vakkuri, J Corander, E Hæggström
The control of the human body sway by the central nervous system, muscles, and conscious brain is of interest since body sway carries information about the physiological status of a person. Several models have been proposed to describe body sway in an upright standing position, however, due to the statistical intractability of the more realistic models, no formal parameter inference has previously been conducted and the expressive power of such models for real human subjects remains unknown. Using the latest advances in Bayesian statistical inference for intractable models, we fitted a nonlinear control model to posturographic measurements, and we showed that it can accurately predict the sway characteristics of both simulated and real subjects...
June 19, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28628647/an-efficient-coding-theory-for-a-dynamic-trajectory-predicts-non-uniform-allocation-of-entorhinal-grid-cells-to-modules
#12
Noga Mosheiff, Haggai Agmon, Avraham Moriel, Yoram Burak
Grid cells in the entorhinal cortex encode the position of an animal in its environment with spatially periodic tuning curves with different periodicities. Recent experiments established that these cells are functionally organized in discrete modules with uniform grid spacing. Here we develop a theory for efficient coding of position, which takes into account the temporal statistics of the animal's motion. The theory predicts a sharp decrease of module population sizes with grid spacing, in agreement with the trend seen in the experimental data...
June 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28626019/neural-mechanisms-of-updating-under-reducible-and-irreducible-uncertainty
#13
Kenji Kobayashi, Ming Hsu
Adaptive decision-making depends on agents' ability to make use of environmental signals to reduce uncertainty. However, because there exist multiple types of uncertainty, agents should take into account not only the extent to which signals violate prior expectancy but also whether uncertainty can be reduced in the first place. Here we studied how the human brain of both sexes responds to signals under conditions of reducible and irreducible uncertainty. We show behaviorally that subjects' value updating was sensitivity to the reducibility of uncertainty, and could be quantitative characterized by a Bayesian model where agents ignore expectancy violations that do not update beliefs or values...
June 16, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28619481/computational-psychosomatics-and-computational-psychiatry-toward-a-joint-framework-for-differential-diagnosis
#14
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/28615342/supramodal-representation-of-temporal-priors-calibrates-interval-timing
#15
Huihui Zhang, Xiaolin Zhou
Human timing behaviors are consistent with Bayesian inference, according to which both previous knowledge (prior) and current sensory information determine final responses. However, it is unclear whether the brain represents temporal priors exclusively for individual modalities or in a supramodal manner when temporal information comes from different modalities at different times. Here we asked participants to reproduce time intervals in either a unisensory or a multisensory context. In unisensory tasks, sample intervals drawn from a uniform distribution were presented in a single visual or auditory modality...
June 14, 2017: Journal of Neurophysiology
https://www.readbyqxmd.com/read/28608396/information-criteria-for-firth-s-penalized-partial-likelihood-approach-in-cox-regression-models
#16
Kengo Nagashima, Yasunori Sato
In the estimation of Cox regression models, maximum partial likelihood estimates might be infinite in a monotone likelihood setting, where partial likelihood converges to a finite value and parameter estimates converge to infinite values. To address monotone likelihood, previous studies have applied Firth's bias correction method to Cox regression models. However, while the model selection criteria for Firth's penalized partial likelihood approach have not yet been studied, a heuristic AIC-type information criterion can be used in a statistical package...
June 12, 2017: Statistics in Medicine
https://www.readbyqxmd.com/read/28605510/phase-i-study-of-oral-sonidegib-lde225-in-pediatric-brain-and-solid-tumors-and-a-phase-ii-study-in-children-and-adults-with-relapsed-medulloblastoma
#17
Mark W Kieran, Julia Chisholm, Michela Casanova, Alba A Brandes, Isabelle Aerts, Eric Bouffet, Simon Bailey, Sarah Leary, Tobey J MacDonald, Francoise Mechinaud, Kenneth J Cohen, Riccardo Riccardi, Warren Mason, Darren Hargrave, Stacey Kalambakas, Priya Deshpande, Feng Tai, Eunju Hurh, Birgit Geoerger
Background.: Sonidegib (LDE225) is a potent, selective Hedgehog (Hh) inhibitor of SMOOTHENED. This study explored the safety and pharmacokinetics (PK) of sonidegib in children with relapsed/recurrent tumors followed by a phase II trial in pediatric and adult patients with relapsed medulloblastoma (MB) to assess tumor response. Methods.: Pediatric patients aged ≥1-<18 years were included according to a Bayesian design starting at 372mg/m2 of continuous once daily oral sonidegib...
June 9, 2017: Neuro-oncology
https://www.readbyqxmd.com/read/28602997/neural-mechanisms-underlying-valence-inferences-to-sound-the-role-of-the-right-angular-gyrus
#18
Fernando Bravo, Ian Cross, Sarah Hawkins, Nadia Gonzalez, Jorge Docampo, Claudio Bruno, Emmanuel Andreas Stamatakis
We frequently infer others' intentions based on non-verbal auditory cues. Although the brain underpinnings of social cognition have been extensively studied, no empirical work has yet examined the impact of musical structure manipulation on the neural processing of emotional valence during mental state inferences. We used a novel sound-based theory-of-mind paradigm in which participants categorized stimuli of different sensory dissonance level in terms of positive/negative valence. Whilst consistent with previous studies which propose facilitated encoding of consonances, our results demonstrated that distinct levels of consonance/dissonance elicited differential influences on the right angular gyrus, an area implicated in mental state attribution and attention reorienting processes...
June 8, 2017: Neuropsychologia
https://www.readbyqxmd.com/read/28595489/a-brain-model-of-disturbed-self-appraisal-in-depression
#19
Christopher G Davey, Michael Breakspear, Jesus Pujol, Ben J Harrison
OBJECTIVE: A disturbed sense of self is a core feature of depression. The medial prefrontal cortex, which has a central role in self-appraisal processes, is often implicated in the illness, although it remains unclear how functional alterations of the region contribute to the observed disturbances. The aim of this study was to clarify the role of the medial prefrontal cortex in self-appraisal processes in depression. METHOD: The authors applied a recently developed dynamic network model of self-directed cognition to functional MRI data from 71 adolescents and young adults with moderate to severe major depressive disorder, none of whom were being treated with medication, and 88 healthy control participants...
June 9, 2017: American Journal of Psychiatry
https://www.readbyqxmd.com/read/28592689/control-of-the-strength-of-visual-motor-transmission-as-the-mechanism-of-rapid-adaptation-of-priors-for-bayesian-inference-in-smooth-pursuit-eye-movements
#20
Timothy Darlington, Stefanie Tokiyama, Stephen G Lisberger
Bayesian inference provides a cogent account of how the brain combines sensory information with "priors" based on past experience to guide many behaviors, including smooth pursuit eye movements. We now demonstrate very rapid adaptation of the pursuit system's priors for target direction and speed. We go on to leverage that adaptation to outline possible neural mechanisms that could cause pursuit to show features consistent with Bayesian inference. Adaptation of the prior causes changes in the eye speed and direction at the initiation of pursuit...
June 7, 2017: Journal of Neurophysiology
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