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https://www.readbyqxmd.com/read/28938250/listening-effort-how-the-cognitive-consequences-of-acoustic-challenge-are-reflected-in-brain-and-behavior
#1
Jonathan E Peelle
Everyday conversation frequently includes challenges to the clarity of the acoustic speech signal, including hearing impairment, background noise, and foreign accents. Although an obvious problem is the increased risk of making word identification errors, extracting meaning from a degraded acoustic signal is also cognitively demanding, which contributes to increased listening effort. The concepts of cognitive demand and listening effort are critical in understanding the challenges listeners face in comprehension, which are not fully predicted by audiometric measures...
September 21, 2017: Ear and Hearing
https://www.readbyqxmd.com/read/28938129/global-exponential-stability-of-inertial-memristor-based-neural-networks-with-time-varying-delays-and-impulses
#2
Wei Zhang, Tingwen Huang, Xing He, Chuandong Li
In this study, we investigate the global exponential stability of inertial memristor-based neural networks with impulses and time-varying delays. We construct inertial memristor-based neural networks based on the characteristics of the inertial neural networks and memristor. Impulses with and without delays are considered when modeling the inertial neural networks simultaneously, which are of great practical significance in the current study. Some sufficient conditions are derived under the framework of the Lyapunov stability method, as well as an extended Halanay differential inequality and a new delay impulsive differential inequality, which depend on impulses with and without delays, in order to guarantee the global exponential stability of the inertial memristor-based neural networks...
April 13, 2017: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/28938072/machine-learning-for-silver-nanoparticle-electron-transfer-property-prediction
#3
Baichuan Sun, Michael Fernandez, Amanda S Barnard
Nanoparticles exhibit diverse structural and morphological features that are often inter-connected, making the correlation of structure/property relationships challenging. In this study a multi-structure/single-property relationship of silver nanoparticles is developed for the energy of Fermi level, which can be tuned to improve the transfer of electrons in a variety of applications. By combining different machine learning analytical algorithms, including k-mean, logistic regression and random forest with electronic structure simulations, we find that the degree of twinning (characterised by the fraction of hexagonal closed packed atoms) and the population of {111} facet (characterized by a surface coordination number of 9) are strongly correlated to the Fermi energy of silver nanoparticles...
September 22, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28938009/altering-neuronal-excitability-to-preserve-network-connectivity-in-a-computational-model-of-alzheimer-s-disease
#4
Willem de Haan, Elisabeth C W van Straaten, Alida A Gouw, Cornelis J Stam
Neuronal hyperactivity and hyperexcitability of the cerebral cortex and hippocampal region is an increasingly observed phenomenon in preclinical Alzheimer's disease (AD). In later stages, oscillatory slowing and loss of functional connectivity are ubiquitous. Recent evidence suggests that neuronal dynamics have a prominent role in AD pathophysiology, making it a potentially interesting therapeutic target. However, although neuronal activity can be manipulated by various (non-)pharmacological means, intervening in a highly integrated system that depends on complex dynamics can produce counterintuitive and adverse effects...
September 22, 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28937989/limited-synapse-overproduction-can-speed-development-but-sometimes-with-long-term-energy-and-discrimination-penalties
#5
Harang Ju, Costa M Colbert, William B Levy
Neural circuit development requires that synapses be formed between appropriate neurons. In addition, for a hierarchical network, successful development involves a sequencing of developmental events. It has been suggested that one mechanism that helps speed up development of proper connections is an early overproduction of synapses. Using a computational model of synapse development, such as adaptive synaptogenesis, it is possible to study such overproduction and its role in speeding up development; it is also possible to study other outcomes of synapse overproduction that are seemingly new to the literature...
September 22, 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28937644/american-sign-language-alphabet-recognition-using-a-neuromorphic-sensor-and-an-artificial-neural-network
#6
Miguel Rivera-Acosta, Susana Ortega-Cisneros, Jorge Rivera, Federico Sandoval-Ibarra
This paper reports the design and analysis of an American Sign Language (ASL) alphabet translation system implemented in hardware using a Field-Programmable Gate Array. The system process consists of three stages, the first being the communication with the neuromorphic camera (also called Dynamic Vision Sensor, DVS) sensor using the Universal Serial Bus protocol. The feature extraction of the events generated by the DVS is the second part of the process, consisting of a presentation of the digital image processing algorithms developed in software, which aim to reduce redundant information and prepare the data for the third stage...
September 22, 2017: Sensors
https://www.readbyqxmd.com/read/28937340/research-domain-criteria-as-psychiatric-nosology
#7
Faisal Akram, James Giordano
Diagnostic classification systems in psychiatry have continued to rely on clinical phenomenology, despite limitations inherent in that approach. In view of these limitations and recent progress in neuroscience, the National Institute of Mental Health (NIMH) has initiated the Research Domain Criteria (RDoC) project to develop a more neuroscientifically based system of characterizing and classifying psychiatric disorders. The RDoC initiative aims to transform psychiatry into an integrative science of psychopathology in which mental illnesses will be defined as involving putative dysfunctions in neural nodes and networks...
October 2017: Cambridge Quarterly of Healthcare Ethics: CQ: the International Journal of Healthcare Ethics Committees
https://www.readbyqxmd.com/read/28937298/probing-the-toxicity-of-nanoparticles-a-unified-in-silico-machine-learning-model-based-on-perturbation-theory
#8
Riccardo Concu, Valeria V Kleandrova, Alejandro Speck-Planche, M Natália D S Cordeiro
Nanoparticles (NPs) are part of our daily life, having a wide range of applications in engineering, physics, chemistry, and biomedicine. However, there are serious concerns regarding the harmful effects that NPs can cause to the different biological systems and their ecosystems. Toxicity testing is an essential step for assessing the potential risks of the NPs, but the experimental assays are often very expensive and usually too slow to flag the number of NPs that may cause adverse effects. In silico models centered on quantitative structure-activity/toxicity relationships (QSAR/QSTR) are alternative tools that have become valuable supports to risk assessment, rationalizing the search for safer NPs...
September 22, 2017: Nanotoxicology
https://www.readbyqxmd.com/read/28937281/tracking-by-detection-of-surgical-instruments-in-minimally-invasive-surgery-via-the-convolutional-neural-network-deep-learning-based-method
#9
Zijian Zhao, Sandrine Voros, Ying Weng, Faliang Chang, Ruijian Li
BACKGROUND: Worldwide propagation of minimally invasive surgeries (MIS) is hindered by their drawback of indirect observation and manipulation, while monitoring of surgical instruments moving in the operated body required by surgeons is a challenging problem. Tracking of surgical instruments by vision-based methods is quite lucrative, due to its flexible implementation via software-based control with no need to modify instruments or surgical workflow. METHODS: A MIS instrument is conventionally split into a shaft and end-effector portions, while a 2D/3D tracking-by-detection framework is proposed, which performs the shaft tracking followed by the end-effector one...
September 22, 2017: Computer Assisted Surgery (Abingdon, England)
https://www.readbyqxmd.com/read/28935904/functional-neural-networks-of-honesty-and-dishonesty-in-children-evidence-from-graph-theory-analysis
#10
Xiao Pan Ding, Si Jia Wu, Jiangang Liu, Genyue Fu, Kang Lee
The present study examined how different brain regions interact with each other during spontaneous honest vs. dishonest communication. More specifically, we took a complex network approach based on the graph-theory to analyze neural response data when children are spontaneously engaged in honest or dishonest acts. Fifty-nine right-handed children between 7 and 12 years of age participated in the study. They lied or told the truth out of their own volition. We found that lying decreased both the global and local efficiencies of children's functional neural network...
September 21, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28934956/parameters-sensitivity-assessment-and-heat-source-localization-using-infrared-imaging-techniques
#11
Maryam Rastgar-Jazi, Farah Mohammadi
BACKGROUND: At present, infrared (IR) imaging is used both as a non-invasive and a non-ionizing technology. Using an IR camera, it is possible to measure body surface temperature in order to detect tumors and malignant cells. Tumors have a high amount of vasculature and an enhanced metabolism rate, which may result in an increase in body surface temperature by several degrees above its normal level. METHODS: Using thermograms, it is possible to assess various tumor parameters, such as depth, intensity, and radius...
September 21, 2017: Biomedical Engineering Online
https://www.readbyqxmd.com/read/28934291/emotional-metacontrol-of-attention-top-down-modulation-of-sensorimotor-processes-in-a-robotic-visual-search-task
#12
Marwen Belkaid, Nicolas Cuperlier, Philippe Gaussier
Emotions play a significant role in internal regulatory processes. In this paper, we advocate four key ideas. First, novelty detection can be grounded in the sensorimotor experience and allow higher order appraisal. Second, cognitive processes, such as those involved in self-assessment, influence emotional states by eliciting affects like boredom and frustration. Third, emotional processes such as those triggered by self-assessment influence attentional processes. Last, close emotion-cognition interactions implement an efficient feedback loop for the purpose of top-down behavior regulation...
2017: PloS One
https://www.readbyqxmd.com/read/28934220/prediction-of-thermal-conductivity-of-polyvinylpyrrolidone-pvp-electrospun-nanocomposite-fibers-using-artificial-neural-network-and-prey-predator-algorithm
#13
Waseem S Khan, Nawaf N Hamadneh, Waqar A Khan
In this study, multilayer perception neural network (MLPNN) was employed to predict thermal conductivity of PVP electrospun nanocomposite fibers with multiwalled carbon nanotubes (MWCNTs) and Nickel Zinc ferrites [(Ni0.6Zn0.4) Fe2O4]. This is the second attempt on the application of MLPNN with prey predator algorithm for the prediction of thermal conductivity of PVP electrospun nanocomposite fibers. The prey predator algorithm was used to train the neural networks to find the best models. The best models have the minimal of sum squared error between the experimental testing data and the corresponding models results...
2017: PloS One
https://www.readbyqxmd.com/read/28932991/automated-reference-free-detection-of-motion-artifacts-in-magnetic-resonance-images
#14
Thomas Küstner, Annika Liebgott, Lukas Mauch, Petros Martirosian, Fabian Bamberg, Konstantin Nikolaou, Bin Yang, Fritz Schick, Sergios Gatidis
OBJECTIVES: Our objectives were to provide an automated method for spatially resolved detection and quantification of motion artifacts in MR images of the head and abdomen as well as a quality control of the trained architecture. MATERIALS AND METHODS: T1-weighted MR images of the head and the upper abdomen were acquired in 16 healthy volunteers under rest and under motion. Images were divided into overlapping patches of different sizes achieving spatial separation...
September 20, 2017: Magma
https://www.readbyqxmd.com/read/28932980/understanding-clinical-mammographic-breast-density-assessment-a-deep-learning-perspective
#15
Aly A Mohamed, Yahong Luo, Hong Peng, Rachel C Jankowitz, Shandong Wu
Mammographic breast density has been established as an independent risk marker for developing breast cancer. Breast density assessment is a routine clinical need in breast cancer screening and current standard is using the Breast Imaging and Reporting Data System (BI-RADS) criteria including four qualitative categories (i.e., fatty, scattered density, heterogeneously dense, or extremely dense). In each mammogram examination, a breast is typically imaged with two different views, i.e., the mediolateral oblique (MLO) view and cranial caudal (CC) view...
September 20, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28932628/a-novel-in-silico-framework-to-improve-mhc-i-epitopes-and-break-the-tolerance-to-melanoma
#16
Cristian Capasso, Aniket Magarkar, Victor Cervera-Carascon, Manlio Fusciello, Sara Feola, Martin Muller, Mariangela Garofalo, Lukasz Kuryk, Siri Tähtinen, Lucio Pastore, Alex Bunker, Vincenzo Cerullo
Tolerance toward tumor antigens, which are shared by normal tissues, have often limited the efficacy of cancer vaccines. However, wild type epitopes can be tweaked to activate cross-reactive T-cell clones, resulting in antitumor activity. The design of these analogs (i.e., heteroclitic peptides) can be difficult and time-consuming since no automated in silico tools are available. Hereby we describe the development of an in silico framework to improve the selection of heteroclitic peptides. The Epitope Discovery and Improvement System (EDIS) was first validated by studying the model antigen SIINFEKL...
2017: Oncoimmunology
https://www.readbyqxmd.com/read/28932189/delayed-mismatch-field-latencies-in-autism-spectrum-disorder-with-abnormal-auditory-sensitivity-a-magnetoencephalographic-study
#17
Junko Matsuzaki, Kuriko Kagitani-Shimono, Hisato Sugata, Ryuzo Hanaie, Fumiyo Nagatani, Tomoka Yamamoto, Masaya Tachibana, Koji Tominaga, Masayuki Hirata, Ikuko Mohri, Masako Taniike
Although abnormal auditory sensitivity is the most common sensory impairment associated with autism spectrum disorder (ASD), the neurophysiological mechanisms remain unknown. In previous studies, we reported that this abnormal sensitivity in patients with ASD is associated with delayed and prolonged responses in the auditory cortex. In the present study, we investigated alterations in residual M100 and MMFs in children with ASD who experience abnormal auditory sensitivity. We used magnetoencephalography (MEG) to measure MMF elicited by an auditory oddball paradigm (standard tones: 300 Hz, deviant tones: 700 Hz) in 20 boys with ASD (11 with abnormal auditory sensitivity: mean age, 9...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28932187/linking-network-activity-to-synaptic-plasticity-during-sleep-hypotheses-and-recent-data
#18
REVIEW
Carlos Puentes-Mestril, Sara J Aton
Research findings over the past two decades have supported a link between sleep states and synaptic plasticity. Numerous mechanistic hypotheses have been put forth to explain this relationship. For example, multiple studies have shown structural alterations to synapses (including changes in synaptic volume, spine density, and receptor composition) indicative of synaptic weakening after a period of sleep. Direct measures of neuronal activity and synaptic strength support the idea that a period of sleep can reduce synaptic strength...
2017: Frontiers in Neural Circuits
https://www.readbyqxmd.com/read/28932183/plant-polyphenols-and-exendin-4-prevent-hyperactivity-and-tnf-%C3%AE-release-in-lps-treated-in-vitro-neuron-astrocyte-microglial-networks
#19
Francesca Gullo, Michela Ceriani, Alessia D'Aloia, Enzo Wanke, Andrew Constanti, Barbara Costa, Marzia Lecchi
Increasing evidence supports a decisive role for neuroinflammation in the neurodegenerative process of several central nervous system (CNS) disorders. Microglia are essential mediators of neuroinflammation and can regulate a broad spectrum of cellular responses by releasing reactive oxygen intermediates, nitric oxide, proteases, excitatory amino acids, and cytokines. We have recently shown that also in ex-vivo cortical networks of neurons, astrocytes and microglia, an increased level of tumor necrosis factor-alpha (TNF-α) was detected a few hours after exposure to the bacterial endotoxin lipopolysaccharide (LPS)...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28932180/hardware-efficient-on-line-learning-through-pipelined-truncated-error-backpropagation-in-binary-state-networks
#20
Hesham Mostafa, Bruno Pedroni, Sadique Sheik, Gert Cauwenberghs
Artificial neural networks (ANNs) trained using backpropagation are powerful learning architectures that have achieved state-of-the-art performance in various benchmarks. Significant effort has been devoted to developing custom silicon devices to accelerate inference in ANNs. Accelerating the training phase, however, has attracted relatively little attention. In this paper, we describe a hardware-efficient on-line learning technique for feedforward multi-layer ANNs that is based on pipelined backpropagation...
2017: Frontiers in Neuroscience
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