keyword
MENU ▼
Read by QxMD icon Read
search

Learning networks

keyword
https://www.readbyqxmd.com/read/27926446/how-motivation-and-reward-learning-modulate-selective-attention
#1
A Bourgeois, L Chelazzi, P Vuilleumier
Motivational stimuli such as rewards elicit adaptive responses and influence various cognitive functions. Notably, increasing evidence suggests that stimuli with particular motivational values can strongly shape perception and attention. These effects resemble both selective top-down and stimulus-driven attentional orienting, as they depend on internal states but arise without conscious will, yet they seem to reflect attentional systems that are functionally and anatomically distinct from those classically associated with frontoparietal cortical networks in the brain...
2016: Progress in Brain Research
https://www.readbyqxmd.com/read/27925199/dopamine-dependent-effects-on-basal-and-glutamate-stimulated-network-dynamics-in-cultured-hippocampal-neurons
#2
Yan Li, Xin Chen, Rhonda Dzakpasu, Katherine Conant
Oscillatory activity occurs in cortical and hippocampal networks with specific frequency ranges thought to be critical to working memory, attention, differentiation of neuronal precursors, and memory trace replay. Synchronized activity within relatively large neuronal populations is influenced by firing and bursting frequency within individual cells, and the latter is modulated by changes in intrinsic membrane excitability and synaptic transmission. Published work suggests that dopamine (DA), a potent modulator of learning and memory, acts on dopamine receptor 1-like dopamine receptors (D1Rs) to influence the phosphorylation and trafficking of glutamate receptor subunits, along with long-term potentiation (LTP) of excitatory synaptic transmission in striatum and prefrontal cortex...
December 7, 2016: Journal of Neurochemistry
https://www.readbyqxmd.com/read/27924352/-prerequisites-skills-and-productivity-of-young-academic-urologists-in-germany
#3
H Borgmann, J Bründl, J Huber, C Ruf, U Schagdarsurgengin, B Wullich, J Salem
BACKGROUND: To safeguard scientific and clinical progress, German urology requires properly trained junior scientists. Before initiating or continuing actions aiming at quality improvement an analysis of the status quo is necessary. OBJECTIVE: To assess the conditions to pursue research, research skills and research output of junior scientists in urology in Germany. MATERIAL UND METHODS: A 16-item online questionnaire was sent to 95 junior scientists in urology within the research network GeSRU Academics...
December 6, 2016: Der Urologe. Ausg. A
https://www.readbyqxmd.com/read/27923731/social-modulation-of-cognition-lessons-from-rhesus-macaques-relevant-to-education
#4
REVIEW
Elisabetta Monfardini, Amélie J Reynaud, Jérôme Prado, Martine Meunier
Any animal, human or non-human, lives in a world where there are others like itself. Individuals' behaviors are thus inevitably influenced by others, and cognition is no exception. Long acknowledged in psychology, social modulations of cognition have been neglected in cognitive neuroscience. Yet, infusing this classic topic in psychology with brain science methodologies could yield valuable educational insights. In recent studies, we used a non-human primate model, the rhesus macaque, to identify social influences representing ancient biases rooted in evolution, and neuroimaging to shed light on underlying mechanisms...
December 3, 2016: Neuroscience and Biobehavioral Reviews
https://www.readbyqxmd.com/read/27923588/autophagy-and-akt-creb-signalling-play-an-important-role-in-the-neuroprotective-effect-of-nimodipine-in-a-rat-model-of-vascular-dementia
#5
Ming Hu, Zhijuan Liu, Peiyuan Lv, Hebo Wang, Yifei Zhu, Qianqian Qi, Jing Xu
The Akt/CREB signalling pathway is involved in neuronal survival and protection. Autophagy is also likely to be involved in survival mechanisms. Nimodipine is an L-type calcium channel antagonist that reduces excessive calcium influx during pathological conditions (contributing to its neuroprotective properties). However, the potential role of nimodipine in autophagic and Akt/CREB signalling is not well understood. In addition, little is known about the relationship between autophagic and Akt/CREB signalling...
December 3, 2016: Behavioural Brain Research
https://www.readbyqxmd.com/read/27923202/structure-based-optimization-of-salt-bridge-network-across-the-complex-interface-of-ptpn4-pdz-domain-with-its-peptide-ligands-in-neuroglioma
#6
Xian Xiao, Qiang-Hua He, Li-Yan Yu, Song-Qing Wang, Yang Li, Hua Yang, Ai-Hua Zhang, Xiao-Hong Ma, Yu-Jie Peng, Bing Chen
The PTP non-receptor type 4 (PTPN4) is an important regulator protein in learning, spatial memory and cerebellar synaptic plasticity; targeting the PDZ domain of PTPN4 has become as attractive therapeutic strategy for human neuroglioma. Here, we systematically examined the complex crystal structures of PTPN4 PDZ domain with its known peptide ligands; a number of charged amino acid residues were identified in these ligands and in the peptide-binding pocket of PDZ domain, which can constitute a complicated salt-bridge network across the complex interface...
November 30, 2016: Computational Biology and Chemistry
https://www.readbyqxmd.com/read/27923064/sparse-regression-based-structure-learning-of-stochastic-reaction-networks-from-single-cell-snapshot-time-series
#7
Anna Klimovskaia, Stefan Ganscha, Manfred Claassen
Stochastic chemical reaction networks constitute a model class to quantitatively describe dynamics and cell-to-cell variability in biological systems. The topology of these networks typically is only partially characterized due to experimental limitations. Current approaches for refining network topology are based on the explicit enumeration of alternative topologies and are therefore restricted to small problem instances with almost complete knowledge. We propose the reactionet lasso, a computational procedure that derives a stepwise sparse regression approach on the basis of the Chemical Master Equation, enabling large-scale structure learning for reaction networks by implicitly accounting for billions of topology variants...
December 2016: PLoS Computational Biology
https://www.readbyqxmd.com/read/27923054/fused-regression-for-multi-source-gene-regulatory-network-inference
#8
Kari Y Lam, Zachary M Westrick, Christian L Müller, Lionel Christiaen, Richard Bonneau
Understanding gene regulatory networks is critical to understanding cellular differentiation and response to external stimuli. Methods for global network inference have been developed and applied to a variety of species. Most approaches consider the problem of network inference independently in each species, despite evidence that gene regulation can be conserved even in distantly related species. Further, network inference is often confined to single data-types (single platforms) and single cell types. We introduce a method for multi-source network inference that allows simultaneous estimation of gene regulatory networks in multiple species or biological processes through the introduction of priors based on known gene relationships such as orthology incorporated using fused regression...
December 2016: PLoS Computational Biology
https://www.readbyqxmd.com/read/27922974/training-and-validating-a-deep-convolutional-neural-network-for-computer-aided-detection-and-classification-of-abnormalities-on-frontal-chest-radiographs
#9
Mark Cicero, Alexander Bilbily, Errol Colak, Tim Dowdell, Bruce Gray, Kuhan Perampaladas, Joseph Barfett
OBJECTIVES: Convolutional neural networks (CNNs) are a subtype of artificial neural network that have shown strong performance in computer vision tasks including image classification. To date, there has been limited application of CNNs to chest radiographs, the most frequently performed medical imaging study. We hypothesize CNNs can learn to classify frontal chest radiographs according to common findings from a sufficiently large data set. MATERIALS AND METHODS: Our institution's research ethics board approved a single-center retrospective review of 35,038 adult posterior-anterior chest radiographs and final reports performed between 2005 and 2015 (56% men, average age of 56, patient type: 24% inpatient, 39% outpatient, 37% emergency department) with a waiver for informed consent...
December 5, 2016: Investigative Radiology
https://www.readbyqxmd.com/read/27922118/mining-visualizing-and-comparing-multidimensional-biomolecular-data-using-the-genomics-data-miner-gmine-web-server
#10
Carla Proietti, Martha Zakrzewski, Thomas S Watkins, Bernard Berger, Shihab Hasan, Champa N Ratnatunga, Marie-Jo Brion, Peter D Crompton, John J Miles, Denise L Doolan, Lutz Krause
Genomics Data Miner (GMine) is a user-friendly online software that allows non-experts to mine, cluster and compare multidimensional biomolecular datasets. Various powerful visualization techniques are provided, generating high quality figures that can be directly incorporated into scientific publications. Robust and comprehensive analyses are provided via a broad range of data-mining techniques, including univariate and multivariate statistical analysis, supervised learning, correlation networks, clustering and multivariable regression...
December 6, 2016: Scientific Reports
https://www.readbyqxmd.com/read/27920762/artificial-intelligence-vs-statistical-modeling-and-optimization-of-continuous-bead-milling-process-for-bacterial-cell-lysis
#11
Shafiul Haque, Saif Khan, Mohd Wahid, Sajad A Dar, Nipunjot Soni, Raju K Mandal, Vineeta Singh, Dileep Tiwari, Mohtashim Lohani, Mohammed Y Areeshi, Thavendran Govender, Hendrik G Kruger, Arshad Jawed
For a commercially viable recombinant intracellular protein production process, efficient cell lysis and protein release is a major bottleneck. The recovery of recombinant protein, cholesterol oxidase (COD) was studied in a continuous bead milling process. A full factorial response surface methodology (RSM) design was employed and compared to artificial neural networks coupled with genetic algorithm (ANN-GA). Significant process variables, cell slurry feed rate (A), bead load (B), cell load (C), and run time (D), were investigated and optimized for maximizing COD recovery...
2016: Frontiers in Microbiology
https://www.readbyqxmd.com/read/27920733/chinese-writing-of-deaf-or-hard-of-hearing-students-and-normal-hearing-peers-from-complex-network-approach
#12
Huiyuan Jin, Haitao Liu
Deaf or hard-of-hearing individuals usually face a greater challenge to learn to write than their normal-hearing counterparts. Due to the limitations of traditional research methods focusing on microscopic linguistic features, a holistic characterization of the writing linguistic features of these language users is lacking. This study attempts to fill this gap by adopting the methodology of linguistic complex networks. Two syntactic dependency networks are built in order to compare the macroscopic linguistic features of deaf or hard-of-hearing students and those of their normal-hearing peers...
2016: Frontiers in Psychology
https://www.readbyqxmd.com/read/27920096/structural-pathways-supporting-swift-acquisition-of-new-visuomotor-skills
#13
Ari E Kahn, Marcelo G Mattar, Jean M Vettel, Nicholas F Wymbs, Scott T Grafton, Danielle S Bassett
Human skill learning requires fine-scale coordination of distributed networks of brain regions linked by white matter tracts to allow for effective information transmission. Yet how individual differences in these anatomical pathways may impact individual differences in learning remains far from understood. Here, we test the hypothesis that individual differences in structural organization of networks supporting task performance predict individual differences in the rate at which humans learn a visuomotor skill...
December 5, 2016: Cerebral Cortex
https://www.readbyqxmd.com/read/27919695/metabolomics-identifies-perturbations-in-amino-acid-metabolism-in-the-prefrontal-cortex-of-the-learned-helplessness-rat-model-of-depression
#14
Xinyu Zhou, Lanxiang Liu, Yuqing Zhang, Juncai Pu, Lining Yang, Chanjuan Zhou, Shuai Yuan, Hanping Zhang, Peng Xie
Major depressive disorder is a serious psychiatric condition associated with high rates of suicide and is a leading cause of health burden worldwide. However, the underlying molecular mechanisms of major depression are still essentially unclear. In our study, a non-targeted gas chromatography-mass spectrometry-based metabolomics approach was used to investigate metabolic changes in the prefrontal cortex of the learned helplessness rat model of depression. Body-weight measurements and behavioral tests including the active escape test, sucrose preference test, forced swimming test, elevated plus-maze and open field test were used to assess changes in the behavioral spectrum after inescapable footshock stress...
December 2, 2016: Neuroscience
https://www.readbyqxmd.com/read/27919220/deepqa-improving-the-estimation-of-single-protein-model-quality-with-deep-belief-networks
#15
Renzhi Cao, Debswapna Bhattacharya, Jie Hou, Jianlin Cheng
BACKGROUND: Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. RESULTS: We introduce a novel single-model quality assessment method DeepQA based on deep belief network that utilizes a number of selected features describing the quality of a model from different perspectives, such as energy, physio-chemical characteristics, and structural information...
December 5, 2016: BMC Bioinformatics
https://www.readbyqxmd.com/read/27918886/computational-principles-and-models-of-multisensory-integration
#16
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/27918853/sustainable-interprofessional-teamwork-needs-a-team-friendly-healthcare-system-experiences-from-a-collaborative-dutch-programme
#17
Anneke van Dijk-de Vries, Jerôme Jean Jacques van Dongen, Marloes Amantia van Bokhoven
The significance of effective interprofessional teamwork to improve the quality of care has been widely recognised. Effective interprofessional teamwork calls on good collaboration between professionals and patients, coordination between professionals, and the development of teamwork over time. Effective development of teams also requires support from the wider organisational context. In a Dutch village, healthcare professionals work closely together, and mutual consultations as well as interprofessional meetings take place on a regular basis...
December 5, 2016: Journal of Interprofessional Care
https://www.readbyqxmd.com/read/27917394/a-deep-ensemble-learning-method-for-monaural-speech-separation
#18
Xiao-Lei Zhang, DeLiang Wang
Monaural speech separation is a fundamental problem in robust speech processing. Recently, deep neural network (DNN)-based speech separation methods, which predict either clean speech or an ideal time-frequency mask, have demonstrated remarkable performance improvement. However, a single DNN with a given window length does not leverage contextual information sufficiently, and the differences between the two optimization objectives are not well understood. In this paper, we propose a deep ensemble method, named multicontext networks, to address monaural speech separation...
March 2016: IEEE/ACM Transactions on Audio, Speech, and Language Processing
https://www.readbyqxmd.com/read/27916841/market-model-for-resource-allocation-in-emerging-sensor-networks-with-reinforcement-learning
#19
Yue Zhang, Bin Song, Ying Zhang, Xiaojiang Du, Mohsen Guizani
Emerging sensor networks (ESNs) are an inevitable trend with the development of the Internet of Things (IoT), and intend to connect almost every intelligent device. Therefore, it is critical to study resource allocation in such an environment, due to the concern of efficiency, especially when resources are limited. By viewing ESNs as multi-agent environments, we model them with an agent-based modelling (ABM) method and deal with resource allocation problems with market models, after describing users' patterns...
November 29, 2016: Sensors
https://www.readbyqxmd.com/read/27916665/task-modulations-and-clinical-manifestations-in-the-brain-functional-connectome-in-1615-fmri-datasets
#20
Tobias Kaufmann, Dag Alnæs, Christine Lycke Brandt, Nhat Trung Doan, Karolina Kauppi, Francesco Bettella, Trine V Lagerberg, Akiah O Berg, Srdjan Djurovic, Ingrid Agartz, Ingrid S Melle, Torill Ueland, Ole A Andreassen, Lars T Westlye
OBJECTIVE: An abundance of experimental studies have motivated a range of models concerning the cognitive underpinnings of severe mental disorders, yet the conception that cognitive and brain dysfunction is confined to specific cognitive domains and contexts has limited ecological validity. Schizophrenia and bipolar spectrum disorders have been conceptualized as disorders of brain connectivity; yet little is known about the pervasiveness across cognitive tasks. METHOD: To address this outstanding issue of context specificity, we estimated functional network connectivity from fMRI data obtained during five cognitive tasks (0-back, 2-back, go/no-go, recognition of positive faces, negative faces) in 90 patients with schizophrenia, 97 patients with bipolar spectrum disorder, and 136 healthy controls, including 1615 fMRI datasets in total...
December 1, 2016: NeuroImage
keyword
keyword
56842
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"