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https://www.readbyqxmd.com/read/27913371/multiview-convolutional-neural-networks-for-multidocument-extractive-summarization
#1
Yong Zhang, Meng Joo Er, Rui Zhao, Mahardhika Pratama
Multidocument summarization has gained popularity in many real world applications because vital information can be extracted within a short time. Extractive summarization aims to generate a summary of a document or a set of documents by ranking sentences and the ranking results rely heavily on the quality of sentence features. However, almost all previous algorithms require hand-crafted features for sentence representation. In this paper, we leverage on word embedding to represent sentences so as to avoid the intensive labor in feature engineering...
November 28, 2016: IEEE Transactions on Cybernetics
https://www.readbyqxmd.com/read/27911322/shape-attributes-of-brain-structures-as-biomarkers-for-alzheimer-s-disease
#2
Tanya Glozman, Justin Solomon, Franco Pestilli, Leonidas Guibas
We describe a fully automatic framework for classification of two types of dementia based on the differences in the shape of brain structures. We consider Alzheimer's disease (AD), mild cognitive impairment of individuals who converted to AD within 18 months (MCIc), and normal controls (NC). Our approach uses statistical learning and a feature space consisting of projection-based shape descriptors, allowing for canonical representation of brain regions. Our framework automatically identifies the structures most affected by the disease...
November 26, 2016: Journal of Alzheimer's Disease: JAD
https://www.readbyqxmd.com/read/27909400/the-demise-of-the-synapse-as-the-locus-of-memory-a-looming-paradigm-shift
#3
Patrick C Trettenbrein
Synaptic plasticity is widely considered to be the neurobiological basis of learning and memory by neuroscientists and researchers in adjacent fields, though diverging opinions are increasingly being recognized. From the perspective of what we might call "classical cognitive science" it has always been understood that the mind/brain is to be considered a computational-representational system. Proponents of the information-processing approach to cognitive science have long been critical of connectionist or network approaches to (neuro-)cognitive architecture, pointing to the shortcomings of the associative psychology that underlies Hebbian learning as well as to the fact that synapses are practically unfit to implement symbols...
2016: Frontiers in Systems Neuroscience
https://www.readbyqxmd.com/read/27909395/reversal-learning-in-humans-and-gerbils-dynamic-control-network-facilitates-learning
#4
Christian Jarvers, Tobias Brosch, André Brechmann, Marie L Woldeit, Andreas L Schulz, Frank W Ohl, Marcel Lommerzheim, Heiko Neumann
Biologically plausible modeling of behavioral reinforcement learning tasks has seen great improvements over the past decades. Less work has been dedicated to tasks involving contingency reversals, i.e., tasks in which the original behavioral goal is reversed one or multiple times. The ability to adjust to such reversals is a key element of behavioral flexibility. Here, we investigate the neural mechanisms underlying contingency-reversal tasks. We first conduct experiments with humans and gerbils to demonstrate memory effects, including multiple reversals in which subjects (humans and animals) show a faster learning rate when a previously learned contingency re-appears...
2016: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/27909103/habenula-induced-inhibition-of-midbrain-dopamine-neurons-is-diminished-by-lesions-of-the-rostromedial-tegmental-nucleus
#5
P Leon Brown, Heather Palacorolla, Dana Brady, Katelyn Riegger, Greg I Elmer, Paul D Shepard
: Neurons in the lateral habenula (LHb) are transiently activated by aversive events and have been implicated in associative learning. Functional changes associated with tonic and phasic activation of the LHb are often attributed to a corresponding inhibition of midbrain dopamine (DA) neurons. Activation of GABAergic neurons in the rostromedial tegmental nucleus (RMTg), a region that receives dense projections from the LHb and projects strongly to midbrain monoaminergic nuclei, is believed to underlie the transient inhibition of DA neurons attributed to activation of the LHb...
December 1, 2016: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/27906502/using-our-hands-to-change-our-minds
#6
REVIEW
Susan Goldin-Meadow
Jean Piaget was a master at observing the routine behaviors children produce as they go from knowing less to knowing more about at a task, and making inferences not only about how children understand the task at each point, but also about how they progress from one point to the next. This article examines a routine behavior that Piaget overlooked-the spontaneous gestures speakers produce as they explain their solutions to a problem. These gestures are not mere hand waving. They reflect ideas that the speaker has about the problem, often ideas that are not found in that speaker's talk...
December 1, 2016: Wiley Interdisciplinary Reviews. Cognitive Science
https://www.readbyqxmd.com/read/27905515/neonicotinoid-induced-impairment-of-odour-coding-in-the-honeybee
#7
Mara Andrione, Giorgio Vallortigara, Renzo Antolini, Albrecht Haase
Exposure to neonicotinoid pesticides is considered one of the possible causes of honeybee (Apis mellifera) population decline. At sublethal doses, these chemicals have been shown to negatively affect a number of behaviours, including performance of olfactory learning and memory, due to their interference with acetylcholine signalling in the mushroom bodies. Here we provide evidence that neonicotinoids can affect odour coding upstream of the mushroom bodies, in the first odour processing centres of the honeybee brain, i...
December 1, 2016: Scientific Reports
https://www.readbyqxmd.com/read/27903489/finding-important-terms-for-patients-in-their-electronic-health-records-a-learning-to-rank-approach-using-expert-annotations
#8
Jinying Chen, Jiaping Zheng, Hong Yu
BACKGROUND: Many health organizations allow patients to access their own electronic health record (EHR) notes through online patient portals as a way to enhance patient-centered care. However, EHR notes are typically long and contain abundant medical jargon that can be difficult for patients to understand. In addition, many medical terms in patients' notes are not directly related to their health care needs. One way to help patients better comprehend their own notes is to reduce information overload and help them focus on medical terms that matter most to them...
November 30, 2016: JMIR Medical Informatics
https://www.readbyqxmd.com/read/27900919/do-infants-discriminate-non-linguistic-vocal-expressions-of-positive-emotions
#9
Melanie Soderstrom, Melissa Reimchen, Disa Sauter, James L Morgan
Adults are highly proficient in understanding emotional signals from both facial and vocal cues, including when communicating across cultural boundaries. However, the developmental origin of this ability is poorly understood, and in particular, little is known about the ontogeny of differentiation of signals with the same valence. The studies reported here employed a habituation paradigm to test whether preverbal infants discriminate between non-linguistic vocal expressions of relief and triumph. Infants as young as 6 months who had habituated to relief or triumph showed significant discrimination of relief and triumph tokens at test (i...
February 2017: Cognition & Emotion
https://www.readbyqxmd.com/read/27898305/view-aligned-hypergraph-learning-for-alzheimer-s-disease-diagnosis-with-incomplete-multi-modality-data
#10
Mingxia Liu, Jun Zhang, Pew-Thian Yap, Dinggang Shen
Effectively utilizing incomplete multi-modality data for the diagnosis of Alzheimer's disease (AD) and its prodrome (i.e., mild cognitive impairment, MCI) remains an active area of research. Several multi-view learning methods have been recently developed for AD/MCI diagnosis by using incomplete multi-modality data, with each view corresponding to a specific modality or a combination of several modalities. However, existing methods usually ignore the underlying coherence among views, which may lead to sub-optimal learning performance...
November 16, 2016: Medical Image Analysis
https://www.readbyqxmd.com/read/27896977/a-deep-learning-approach-for-cancer-detection-and-relevant-gene-identification
#11
Padideh Danaee, Reza Ghaeini, David A Hendrix
Cancer detection from gene expression data continues to pose a challenge due to the high dimensionality and complexity of these data. After decades of research there is still uncertainty in the clinical diagnosis of cancer and the identification of tumor-specific markers. Here we present a deep learning approach to cancer detection, and to the identification of genes critical for the diagnosis of breast cancer. First, we used Stacked Denoising Autoencoder (SDAE) to deeply extract functional features from high dimensional gene expression profiles...
2016: Pacific Symposium on Biocomputing
https://www.readbyqxmd.com/read/27896710/how-social-network-heterogeneity-facilitates-lexical-access-and-lexical-prediction
#12
Shiri Lev-Ari, Zeshu Shao
People learn language from their social environment. As individuals differ in their social networks, they might be exposed to input with different lexical distributions, and these might influence their linguistic representations and lexical choices. In this article we test the relation between linguistic performance and 3 social network properties that should influence input variability, namely, network size, network heterogeneity, and network density. In particular, we examine how these social network properties influence lexical prediction, lexical access, and lexical use...
November 28, 2016: Memory & Cognition
https://www.readbyqxmd.com/read/27893388/sparse-representation-based-multiple-frame-video-super-resolution
#13
Qiqin Dai, Seunghwan Yoo, Armin Kappeler, Aggelos K Katsaggelos
In this paper, we propose two multiple-frame superresolution (SR) algorithms based on dictionary learning and motion estimation. First, we adopt the use of video bilevel dictionary learning which has been used for single-frame SR. It is extended to multiple frames by using motion estimation with subpixel accuracy. We propose a batch and a temporally recursive multi-frame SR algorithm, which improve over single frame SR. Finally, we propose a novel dictionary learning algorithm utilizing consecutive video frames, rather than still images or individual video frames, which further improves the performance of the video SR algorithms...
November 22, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/27893380/area-determination-of-diabetic-foot-ulcer-images-using-a-cascaded-two-stage-svm-based-classification
#14
Lei Wang, Peder Pedersen, Emmanuel Agu, Diane Strong, Bengisu Tulu
It is standard practice for clinicians and nurses to primarily assess patients' wounds via visual examination. This subjective method can be inaccurate in wound assessment and also represents a significant clinical workload. Hence, computer-based systems, especially implemented on mobile devices, can provide automatic, quantitative wound assessment and can thus be valuable for accurately monitoring wound healing status. Out of all wound assessment parameters, the measurement of the wound area is the most suitable for automated analysis...
November 23, 2016: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/27893378/semi-supervised-stacked-label-consistent-autoencoder-for-reconstruction-and-analysis-of-biomedical-signals
#15
Angshul Majumdar, Anupriya Gogna, Rabab Ward
: An autoencoder based framework that simultaneously reconstruct and classify biomedical signals is proposed. Previous work has treated reconstruction and classification as separate problems. This is the first work that proposes a combined framework to address the issue in a holistic fashion. METHODS: For tele-monitoring purposes, reconstruction techniques of biomedical signals are largely based on compressed sensing (CS); these are 'designed' techniques where the reconstruction formulation is based on some 'assumption' regarding the signal...
November 22, 2016: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/27891105/global-cue-inconsistency-diminishes-learning-of-cue-validity
#16
Tony S L Wang, Nicole Christie, Piers D L Howe, Daniel R Little
In daily life, we make decisions that are associated with probabilistic outcomes (e.g., the chance of rain today). People search for and utilize information that validly predicts an outcome (i.e., we look for dark clouds to indicate the possibility of rain). In the current study (N = 107), we present a two-stage learning task that examines how participants learn and utilize predictive information within a probabilistic learning environment. In the first stage, participants select one of three cues that gives predictive information about the outcome of the second stage...
2016: Frontiers in Psychology
https://www.readbyqxmd.com/read/27890605/developmental-metaplasticity-in-neural-circuit-codes-of-firing-and-structure
#17
Yoram Baram
Firing-rate dynamics have been hypothesized to mediate inter-neural information transfer in the brain. While the Hebbian paradigm, relating learning and memory to firing activity, has put synaptic efficacy variation at the center of cortical plasticity, we suggest that the external expression of plasticity by changes in the firing-rate dynamics represents a more general notion of plasticity. Hypothesizing that time constants of plasticity and firing dynamics increase with age, and employing the filtering property of the neuron, we obtain the elementary code of global attractors associated with the firing-rate dynamics in each developmental stage...
September 30, 2016: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/27888690/exploring-socioeconomic-differences-in-syntactic-development-through-the-lens-of-real-time-processing
#18
Yi Ting Huang, Kathryn Leech, Meredith L Rowe
Differences in caregiver input across socioeconomic status (SES) predict syntactic development, but the mechanisms are not well understood. Input effects may reflect the exposure needed to acquire syntactic representations during learning (e.g., does the child have the relevant structures for passive sentences?) or access this knowledge during communication (e.g., can she use the past participle to infer the meaning of passives?). Using an eye-tracking and act-out paradigm, the current study distinguishes these mechanisms by comparing the interpretation of actives and passives in 3- to 7-year-olds (n=129) from varying SES backgrounds...
November 23, 2016: Cognition
https://www.readbyqxmd.com/read/27888170/a-predictive-model-for-medical-events-based-on-contextual-embedding-of-temporal-sequences
#19
Wael Farhan, Zhimu Wang, Yingxiang Huang, Shuang Wang, Fei Wang, Xiaoqian Jiang
BACKGROUND: Medical concepts are inherently ambiguous and error-prone due to human fallibility, which makes it hard for them to be fully used by classical machine learning methods (eg, for tasks like early stage disease prediction). OBJECTIVE: Our work was to create a new machine-friendly representation that resembles the semantics of medical concepts. We then developed a sequential predictive model for medical events based on this new representation. METHODS: We developed novel contextual embedding techniques to combine different medical events (eg, diagnoses, prescriptions, and labs tests)...
November 25, 2016: JMIR Medical Informatics
https://www.readbyqxmd.com/read/27886450/comprehending-3d-diagrams-sketching-to-support-spatial-reasoning
#20
Kristin M Gagnier, Kinnari Atit, Carol J Ormand, Thomas F Shipley
Science, technology, engineering, and mathematics (STEM) disciplines commonly illustrate 3D relationships in diagrams, yet these are often challenging for students. Failing to understand diagrams can hinder success in STEM because scientific practice requires understanding and creating diagrammatic representations. We explore a new approach to improving student understanding of diagrams that convey 3D relations that is based on students generating their own predictive diagrams. Participants' comprehension of 3D spatial diagrams was measured in a pre- and post-design where students selected the correct 2D slice through 3D geologic block diagrams...
November 25, 2016: Topics in Cognitive Science
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