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https://www.readbyqxmd.com/read/27920670/two-visual-pathways-in-primates-based-on-sampling-of-space-exploitation-and-exploration-of-visual-information
#1
Bhavin R Sheth, Ryan Young
Evidence is strong that the visual pathway is segregated into two distinct streams-ventral and dorsal. Two proposals theorize that the pathways are segregated in function: The ventral stream processes information about object identity, whereas the dorsal stream, according to one model, processes information about either object location, and according to another, is responsible in executing movements under visual control. The models are influential; however recent experimental evidence challenges them, e.g., the ventral stream is not solely responsible for object recognition; conversely, its function is not strictly limited to object vision; the dorsal stream is not responsible by itself for spatial vision or visuomotor control; conversely, its function extends beyond vision or visuomotor control...
2016: Frontiers in Integrative Neuroscience
https://www.readbyqxmd.com/read/27920466/joint-models-for-multiple-longitudinal-processes-and-time-to-event-outcome
#2
Lili Yang, Menggang Yu, Sujuan Gao
Joint models are statistical tools for estimating the association between time-to-event and longitudinal outcomes. One challenge to the application of joint models is its computational complexity. Common estimation methods for joint models include a two-stage method, Bayesian and maximum-likelihood methods. In this work, we consider joint models of a time-to-event outcome and multiple longitudinal processes and develop a maximum-likelihood estimation method using the expectation-maximization (EM) algorithm...
2016: Journal of Statistical Computation and Simulation
https://www.readbyqxmd.com/read/27919903/high-throughput-screening-and-prediction-models-building-for-novel-hemozoin-inhibitors-using-physicochemical-properties
#3
Nguyen Tien Huy, Pham Lan Chi, Jun Nagai, Tran Ngoc Dang, Evaristus Chibunna Mbanefo, Ali Mahmoud Ahmed, Nguyen Phuoc Long, Le Thi Bich Thoa, Le Phi Hung, Titouna Afaf, Kaeko Kamei, Hiroshi Ueda, Kenji Hirayama
It is essential to continue the search for novel antimalarial drugs due to current spread of resistance against artemisinin by Plasmodium falciparum parasites. In this study, we developed in silico models to predict hemozoin inhibitors as a potential first-step screening for novel antimalarials. The in vitro colorimetric high throughput screening assay of hemozoin formation was used to identify hemozoin inhibitors from 9600 structurally diverse compounds. Physicochemical properties of positive hits and randomly selected compounds were extracted from ChemSpider database; they were used for developing prediction models to predict hemozoin inhibitors using two different approaches, i...
December 5, 2016: Antimicrobial Agents and Chemotherapy
https://www.readbyqxmd.com/read/27919785/a-comparative-assessment-of-preclinical-chemotherapeutic-response-of-tumors-using-quantitative-non-gaussian-diffusion-mri
#4
Junzhong Xu, Ke Li, R Adam Smith, John C Waterton, Ping Zhao, Zhaohua Ding, Mark D Does, H Charles Manning, John C Gore
BACKGROUND: Diffusion-weighted MRI (DWI) signal attenuation is often not mono-exponential (i.e. non-Gaussian diffusion) with stronger diffusion weighting. Several non-Gaussian diffusion models have been developed and may provide new information or higher sensitivity compared with the conventional apparent diffusion coefficient (ADC) method. However the relative merits of these models to detect tumor therapeutic response is not fully clear. METHODS: Conventional ADC, and three widely-used non-Gaussian models, (bi-exponential, stretched exponential, and statistical model), were implemented and compared for assessing SW620 human colon cancer xenografts responding to barasertib, an agent known to induce apoptosis via polyploidy...
December 2, 2016: Magnetic Resonance Imaging
https://www.readbyqxmd.com/read/27919554/quantitative-structure-property-relationships-for-predicting-sorption-of-pharmaceuticals-to-sewage-sludge-during-waste-water-treatment-processes
#5
L Berthod, D C Whitley, G Roberts, A Sharpe, R Greenwood, G A Mills
Understanding the sorption of pharmaceuticals to sewage sludge during waste water treatment processes is important for understanding their environmental fate and in risk assessments. The degree of sorption is defined by the sludge/water partition coefficient (Kd). Experimental Kd values (n=297) for active pharmaceutical ingredients (n=148) in primary and activated sludge were collected from literature. The compounds were classified by their charge at pH7.4 (44 uncharged, 60 positively and 28 negatively charged, and 16 zwitterions)...
December 2, 2016: Science of the Total Environment
https://www.readbyqxmd.com/read/27918908/likelihood-ratio-sequential-sampling-models-of-recognition-memory
#6
Adam F Osth, Simon Dennis, Andrew Heathcote
The mirror effect - a phenomenon whereby a manipulation produces opposite effects on hit and false alarm rates - is benchmark regularity of recognition memory. A likelihood ratio decision process, basing recognition on the relative likelihood that a stimulus is a target or a lure, naturally predicts the mirror effect, and so has been widely adopted in quantitative models of recognition memory. Glanzer, Hilford, and Maloney (2009) demonstrated that likelihood ratio models, assuming Gaussian memory strength, are also capable of explaining regularities observed in receiver-operating characteristics (ROCs), such as greater target than lure variance...
December 2, 2016: Cognitive Psychology
https://www.readbyqxmd.com/read/27918886/computational-principles-and-models-of-multisensory-integration
#7
REVIEW
Chandramouli Chandrasekaran
Combining information from multiple senses creates robust percepts, speeds up responses, enhances learning, and improves detection, discrimination, and recognition. In this review, I discuss computational models and principles that provide insight into how this process of multisensory integration occurs at the behavioral and neural level. My initial focus is on drift-diffusion and Bayesian models that can predict behavior in multisensory contexts. I then highlight how recent neurophysiological and perturbation experiments provide evidence for a distributed redundant network for multisensory integration...
December 2, 2016: Current Opinion in Neurobiology
https://www.readbyqxmd.com/read/27918599/hierarchical-bayesian-inference-for-ion-channel-screening-dose-response-data
#8
Ross H Johnstone, Rémi Bardenet, David J Gavaghan, Gary R Mirams
Dose-response (or 'concentration-effect') relationships commonly occur in biological and pharmacological systems and are well characterised by Hill curves. These curves are described by an equation with two parameters: the inhibitory concentration 50% (IC50); and the Hill coefficient. Typically just the 'best fit' parameter values are reported in the literature. Here we introduce a Python-based software tool, PyHillFit , and describe the underlying Bayesian inference methods that it uses, to infer probability distributions for these parameters as well as the level of experimental observation noise...
2016: Wellcome Open Res
https://www.readbyqxmd.com/read/27918530/a-probabilistic-approach-to-demixing-odors
#9
Agnieszka Grabska-Barwińska, Simon Barthelmé, Jeff Beck, Zachary F Mainen, Alexandre Pouget, Peter E Latham
The olfactory system faces a hard problem: on the basis of noisy information from olfactory receptor neurons (the neurons that transduce chemicals to neural activity), it must figure out which odors are present in the world. Odors almost never occur in isolation, and different odors excite overlapping populations of olfactory receptor neurons, so the central challenge of the olfactory system is to demix its input. Because of noise and the large number of possible odors, demixing is fundamentally a probabilistic inference task...
December 5, 2016: Nature Neuroscience
https://www.readbyqxmd.com/read/27918181/comparing-vector-based-and-bayesian-memory-models-using-large-scale-datasets-user-generated-hashtag-and-tag-prediction-on-twitter-and-stack-overflow
#10
Clayton Stanley, Michael D Byrne
The growth of social media and user-created content on online sites provides unique opportunities to study models of human declarative memory. By framing the task of choosing a hashtag for a tweet and tagging a post on Stack Overflow as a declarative memory retrieval problem, 2 cognitively plausible declarative memory models were applied to millions of posts and tweets and evaluated on how accurately they predict a user's chosen tags. An ACT-R based Bayesian model and a random permutation vector-based model were tested on the large data sets...
December 2016: Psychological Methods
https://www.readbyqxmd.com/read/27917260/integrative-bayesian-analysis-of-neuroimaging-genetic-data-through-hierarchical-dimension-reduction
#11
S Azadeh, B P Hobbs, L Ma, D A Nielsen, F G Moeller, V Baladandayuthapani
Advances in neuromedicine have emerged from endeavors to elucidate the distinct genetic factors that influence the changes in brain structure that underlie various neurological conditions. We present a framework for examining the extent to which genetic factors impact imaging phenotypes described by voxel-wise measurements organized into collections of functionally relevant regions of interest (ROIs) that span the entire brain. Statistically, the integration of neuroimaging and genetic data is challenging. Because genetic variants are expected to impact different regions of the brain, an appropriate method of inference must simultaneously account for spatial dependence and model uncertainty...
April 2016: Proceedings of the IEEE International Symposium on Biomedical Imaging: from Nano to Macro
https://www.readbyqxmd.com/read/27917138/neural-elements-for-predictive-coding
#12
REVIEW
Stewart Shipp
Predictive coding theories of sensory brain function interpret the hierarchical construction of the cerebral cortex as a Bayesian, generative model capable of predicting the sensory data consistent with any given percept. Predictions are fed backward in the hierarchy and reciprocated by prediction error in the forward direction, acting to modify the representation of the outside world at increasing levels of abstraction, and so to optimize the nature of perception over a series of iterations. This accounts for many 'illusory' instances of perception where what is seen (heard, etc...
2016: Frontiers in Psychology
https://www.readbyqxmd.com/read/27917005/distinct-respiratory-responses-of-soils-to-complex-organic-substrate-are%C3%A2-governed-predominantly-by-soil-architecture-and-its-microbial-community
#13
F C Fraser, L C Todman, R Corstanje, L K Deeks, J A Harris, M Pawlett, A P Whitmore, K Ritz
Factors governing the turnover of organic matter (OM) added to soils, including substrate quality, climate, environment and biology, are well known, but their relative importance has been difficult to ascertain due to the interconnected nature of the soil system. This has made their inclusion in mechanistic models of OM turnover or nutrient cycling difficult despite the potential power of these models to unravel complex interactions. Using high temporal-resolution respirometery (6 min measurement intervals), we monitored the respiratory response of 67 soils sampled from across England and Wales over a 5 day period following the addition of a complex organic substrate (green barley powder)...
December 2016: Soil Biology & Biochemistry
https://www.readbyqxmd.com/read/27916020/the-role-of-symptomatic-presentation-in-influenza-a-transmission-risk
#14
R Wardell, K Prem, B J Cowling, A R Cook
Computer models can be useful in planning interventions against novel strains of influenza. However such models sometimes make unsubstantiated assumptions about the relative infectivity of asymptomatic and symptomatic cases, or conversely assume there is no impact at all. Using household-level data from known-index studies of virologically confirmed influenza A infection, the relationship between an individual's infectiousness and their symptoms was quantified using a discrete-generation transmission model and Bayesian Markov chain Monte Carlo methods...
December 5, 2016: Epidemiology and Infection
https://www.readbyqxmd.com/read/27915121/predicting-individual-brain-functional-connectivity-using-a-bayesian-hierarchical-model
#15
Tian Dai, Ying Guo
Network-oriented analysis of functional magnetic resonance imaging (fMRI), especially resting-state fMRI, has revealed important association between abnormal connectivity and brain disorders such as schizophrenia, major depression and Alzheimer's disease. Imaging-based brain connectivity measures have become a useful tool for investigating the pathophysiology, progression and treatment response of psychiatric disorders and neurodegenerative diseases. Recent studies have started to explore the possibility of using functional neuroimaging to help predict disease progression and guide treatment selection for individual patients...
November 30, 2016: NeuroImage
https://www.readbyqxmd.com/read/27914929/structured-additive-distributional-regression-for-analyzing-landings-per-unit-effort-in-fisheries-research
#16
Valeria Mamouridis, Nadja Klein, Thomas Kneib, Carmen Cadarso Suarez, Francesc Maynou
We analysed the landings per unit effort (LPUE) from the Barcelona trawl fleet targeting the red shrimp (Aristeus antennatus) using novel Bayesian structured additive distributional regression to gain a better understanding of the dynamics and determinants of variation in LPUE. The data set, covering a time span of 17 years, includes fleet-dependent variables (e.g. the number of trips performed by vessels), temporal variables (inter- and intra-annual variability) and environmental variables (the North Atlantic Oscillation index)...
November 30, 2016: Mathematical Biosciences
https://www.readbyqxmd.com/read/27914307/a-multivariate-random-parameters-tobit-model-for-analyzing-highway-crash-rates-by-injury-severity
#17
Qiang Zeng, Huiying Wen, Helai Huang, Xin Pei, S C Wong
In this study, a multivariate random-parameters Tobit model is proposed for the analysis of crash rates by injury severity. In the model, both correlation across injury severity and unobserved heterogeneity across road-segment observations are accommodated. The proposed model is compared with a multivariate (fixed-parameters) Tobit model in the Bayesian context, by using a crash dataset collected from the Traffic Information System of Hong Kong. The dataset contains crash, road geometric and traffic information on 224 directional road segments for a five-year period (2002-2006)...
November 30, 2016: Accident; Analysis and Prevention
https://www.readbyqxmd.com/read/27914207/demographic-history-of-the-trace-metal-hyperaccumulator-noccaea-caerulescens-j-presl-and-c-presl-f-k-mey-in-western-europe
#18
Cédric Gonneau, Nausicaa Noret, Cécile Godé, Hélène Frérot, Catherine Sirguey, Thibault Sterckeman, Maxime Pauwels
Noccaea caerulescens (Brassicaceae) is a major pseudometallophyte model for the investigation of the genetics and evolution of metal hyperaccumulation in plants. We studied the population genetics and demographic history of this species to advance the understanding of among-population differences in metal hyperaccumulation and tolerance abilities. Sampling of seven to 30 plants was carried out in 62 sites in Western Europe. Genotyping was done using a combination of new chloroplast and nuclear neutral markers...
December 3, 2016: Molecular Ecology
https://www.readbyqxmd.com/read/27913961/prediction-of-postoperative-clinical-recovery-of-drop-foot-attributable-to-lumbar-degenerative-diseases-via-a-bayesian-network
#19
Shota Takenaka, Hiroyuki Aono
BACKGROUND: Drop foot resulting from degenerative lumbar diseases can impair activities of daily living. Therefore, predictors of recovery of this symptom have been investigated using univariate or/and multivariate analyses. However, the conclusions have been somewhat controversial. Bayesian network models, which are graphic and intuitive to the clinician, may facilitate understanding of the prognosis of drop foot resulting from degenerative lumbar diseases. QUESTIONS/PURPOSES: (1) To show a layered correlation among predictors of recovery from drop foot resulting from degenerative lumbar diseases; and (2) to develop support tools for clinical decisions to treat drop foot resulting from lumbar degenerative diseases...
December 2, 2016: Clinical Orthopaedics and related Research
https://www.readbyqxmd.com/read/27913729/qsea-modelling-of-genome-wide-dna-methylation-from-sequencing-enrichment-experiments
#20
Matthias Lienhard, Sabrina Grasse, Jana Rolff, Steffen Frese, Uwe Schirmer, Michael Becker, Stefan Börno, Bernd Timmermann, Lukas Chavez, Holger Sültmann, Gunda Leschber, Iduna Fichtner, Michal R Schweiger, Ralf Herwig
Genome-wide enrichment of methylated DNA followed by sequencing (MeDIP-seq) offers a reasonable compromise between experimental costs and genomic coverage. However, the computational analysis of these experiments is complex, and quantification of the enrichment signals in terms of absolute levels of methylation requires specific transformation. In this work, we present QSEA, Quantitative Sequence Enrichment Analysis, a comprehensive workflow for the modelling and subsequent quantification of MeDIP-seq data...
December 1, 2016: Nucleic Acids Research
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