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Kind representations

David Stawarczyk, Olivier Jeunehomme, Arnaud D'Argembeau
Episodic memories are typically composed of perceptual information derived from the external environment and representations of internal states (e.g., one's thoughts during prior episodes). To date, however, research has mostly focused on the remembrance of external stimuli, such that little is known about how internal mentation is represented within episodic memory. In the present fMRI study, we examined the neural correlates of these 2 components of episodic memories using a novel method of cuing memories from photographs taken during real-life events...
October 17, 2017: Cerebral Cortex
Lindsey A Drayton, Laurie R Santos
Recently, comparative psychologists have suggested that primates represent others' knowledge states. Evidence for this claim comes from studies demonstrating that primates expect others to maintain representations of objects when those objects are not currently visible. However, little work has explored whether nonhuman primates expect others to share the more sophisticated kinds of object knowledge that they themselves possess. We therefore investigated whether primates attribute to others knowledge that is acquired through the mental transformation of a static object representation...
October 14, 2017: Cognition
Zhaoxiang Zhang, Jiaxin Chen, Qiang Wu, Ling Shao
Remote person identification by gait is one of the most important topics in the field of computer vision and pattern recognition. However, gait recognition suffers severely from the appearance variance caused by the view change. It is very common that gait recognition has a high performance when the view is fixed but the performance will have a sharp decrease when the view variance becomes significant. Existing approaches have tried all kinds of strategies like tensor analysis or view transform models to slow down the trend of performance decrease but still have potential for further improvement...
October 13, 2017: IEEE Transactions on Cybernetics
Emily S Cross, Antonia F de C Hamilton, Nichola Rice Cohen, Scott T Grafton
Here we examined neural substrates for physically and observationally learning to construct novel objects, and characterized brain regions associated with each kind of learning using fMRI. Each participant was assigned a training partner, and for five consecutive days practiced tying one group of knots ("tied" condition) or watched their partner tie different knots ("watched" condition) while a third set of knots remained untrained. Functional MRI was obtained prior to and immediately following the week of training while participants performed a visual knot-matching task...
2017: PloS One
Peilin He, Pengfei Jia, Siqi Qiao, Shukai Duan
For an electronic nose (E-nose) in wound infection distinguishing, traditional learning methods have always needed large quantities of labeled wound infection samples, which are both limited and expensive; thus, we introduce self-taught learning combined with sparse autoencoder and radial basis function (RBF) into the field. Self-taught learning is a kind of transfer learning that can transfer knowledge from other fields to target fields, can solve such problems that labeled data (target fields) and unlabeled data (other fields) do not share the same class labels, even if they are from entirely different distribution...
October 7, 2017: Sensors
Rutger H J Fick, Alexandra Petiet, Mathieu Santin, Anne-Charlotte Philippe, Stephane Lehericy, Rachid Deriche, Demian Wassermann
Effective representation of the four-dimensional diffusion MRI signal - varying over three-dimensional q-space and diffusion time τ - is a sought-after and still unsolved challenge in diffusion MRI (dMRI). We propose a functional basis approach that is specifically designed to represent the dMRI signal in this qτ-space. Following recent terminology, we refer to our qτ-functional basis as "qτ-dMRI". qτ-dMRI can be seen as a time-dependent realization of q-space imaging by Paul Callaghan and colleagues. We use GraphNet regularization - imposing both signal smoothness and sparsity - to drastically reduce the number of diffusion-weighted images (DWIs) that is needed to represent the dMRI signal in the qτ-space...
September 14, 2017: Medical Image Analysis
Kimberly L Stachenfeld, Matthew M Botvinick, Samuel J Gershman
A cognitive map has long been the dominant metaphor for hippocampal function, embracing the idea that place cells encode a geometric representation of space. However, evidence for predictive coding, reward sensitivity and policy dependence in place cells suggests that the representation is not purely spatial. We approach this puzzle from a reinforcement learning perspective: what kind of spatial representation is most useful for maximizing future reward? We show that the answer takes the form of a predictive representation...
October 2, 2017: Nature Neuroscience
Handong Zhao, Hongfu Liu, Zhengming Ding, Yun Fu
Identifying different types of data outliers with abnormal behaviors in multi-view data setting is challenging due to the complicated data distributions across different views. Conventional approaches achieve this by learning a new latent feature representation with the pairwise constraint on different view data. In this paper, we argue that the existing methods are expensive in generalizing their models from two-view data to three-view (or more) data, in terms of the number of introduced variables and detection performance...
September 20, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Krystyna Bielecka, Mira Marcinów
In this paper, we defend a representational approach to at least some kinds of non-human psychopathology. Mentally-ill non-human minds, in particular in delusions, obsessive-compulsive disorders and similar cognitive states, are traditionally understood in purely behavioral terms. In contrast, we argue that non-human mental psychopathology should be at least sometimes not only ascribed contentful mental representation but also understood as really having these states. To defend this view, we appeal to the interactivist account of mental representation, which is a kind of a constructive approach to meaning...
2017: Biosemiotics
Hai Ming Ni, Da Wei Qi, Hongbo Mu
Converting DNA sequence to image by using chaos game representation (CGR) is an effective genome sequence pretreatment technology, which provides the basis for further analysis between the different genes. In this paper, we have constructed 10 mammal species, 48 hepatitis E virus (HEV), and 10 kinds of bacteria genetic CGR images, respectively, to calculate the mean structural similarity (MSSIM) coefficient between every two CGR images. From our analysis, the MSSIM coefficient of gene CGR images can accurately reflect the similarity degrees between different genomes...
September 20, 2017: Genomics
Hernando Taborda-Osorio, Erik W Cheries
People's explanations about the biological world are heavily biased toward internal, non-obvious properties. Adults and children as young as 5 years of age find internal properties more causally central than external features for explaining general biological processes and category membership. In this paper, we describe how this 'internal property bias' may be grounded in two different developmental precursors observed in studies with infants: (1) an early understanding of biological agency that is apparent in infants' reasoning about animals, and (2) the acquisition of kind-based representations that distinguish between essential and accidental properties, spanning from animals to artifacts...
October 2017: Psychonomic Bulletin & Review
Arnaud Boujut, David Clarys
The aim of this study was to highlight that episodic memory and working memory compete for the same resource, which would be diminished in aging. Using the remember/know paradigm, we compared the interference related to the retrieval of words on the parallel processing of preestablished relational bindings (Shifting condition) or newly established relational bindings (Updating condition). Within each age-group, participants had comparable performances in remembering across recognition conditions. However, the results showed that only updating activity was impaired after a remember response was given in the younger group...
September 18, 2017: Neuropsychology, Development, and Cognition. Section B, Aging, Neuropsychology and Cognition
Shaoguang Huang, Hongyan Zhang, Aleksandra Pižurica
Sparse representation has been extensively investigated for hyperspectral image (HSI) classification and led to substantial improvements in the performance over the traditional methods, such as support vector machine (SVM). However, the existing sparsity-based classification methods typically assume Gaussian noise, neglecting the fact that HSIs are often corrupted by different types of noise in practice. In this paper, we develop a robust classification model that admits realistic mixed noise, which includes Gaussian noise and sparse noise...
September 12, 2017: Sensors
Jiazhi Xia, Fenjin Ye, Wei Chen, Yusi Wang, Weifeng Chen, Yuxin Ma, Anthony K H Tung
Many approaches for analyzing a high-dimensional dataset assume that the dataset contains specific structures, e.g., clusters in linear subspaces or non-linear manifolds. This yields a trial-and-error process to verify the appropriate model and parameters. This paper contributes an exploratory interface that supports visual identification of low-dimensional structures in a high-dimensional dataset, and facilitates the optimized selection of data models and configurations. Our key idea is to abstract a set of global and local feature descriptors from the neighborhood graph-based representation of the latent low-dimensional structure, such as pairwise geodesic distance (GD) among points and pairwise local tangent space divergence (LTSD) among pointwise local tangent spaces (LTS)...
August 29, 2017: IEEE Transactions on Visualization and Computer Graphics
Magdalena Razmus
Neuropsychological literature suggests that body representation is a multidimensional concept consisting of various types of representations. Previous studies have demonstrated dissociations between three types of body representation specified by the kind of data and processes, i.e. body schema, body structural description, and body semantics. The aim of the study was to describe the state of body representation in patients after vascular brain injuries and to provide evidence for the different types of body representation...
August 29, 2017: Cognitive Processing
Magnus Boman, Erik Kruse
The objective of this study is to critically assess the possible roles of information and communications technology (ICT) in supporting global health goals. This is done by considering privilege and connectibility. In short, ICT can contribute by providing health information via four different kinds of access, each with its own history and prospective future. All four are analyzed here, in two perspectives: business-as-usual and disruptive. Health data analytics is difficult since the digital representation of past, current, and future health information is lacking...
June 2017: Global Health Action
Philippe Huneman, Johannes Martens
Natural selection is often envisaged as the ultimate cause of the apparent rationality exhibited by organisms in their specific habitat. Given the equivalence between selection and rationality as maximizing processes, one would indeed expect organisms to implement rational decision-makers. Yet, many violations of the clauses of rationality have been witnessed in various species such as starlings, hummingbirds, amoebas and honeybees. This paper attempts to interpret such discrepancies between economic rationality (defined by the main axioms of rational choice theory) and biological rationality (defined by natural selection)...
August 17, 2017: History and Philosophy of the Life Sciences
Montaña Cámara, Ana Muñoz van den Eynde, José A López Cerezo
Using data obtained from Spanish surveys on the public perception of science, this article presents a critical review of current practices of population profile segmentation, including the one-dimensional representation of perceived risks and benefits and of the systematic underestimation of critical attitudes to the social impact of science and technology. We use discriminant analysis to detect a somewhat hidden cluster in the Spanish population which we call 'critical engagers'. These individuals are critically and socially responsible and are not reticent about expressing concern regarding scientific-technological change...
August 1, 2017: Public Understanding of Science
Alberto Greco, Stefania Moretti
Category learning performance can be influenced by many contextual factors, but the effects of these factors are not the same for all learners. The present study suggests that these differences can be due to the different ways evidence is used, according to two main basic modalities of processing information, analytically or holistically. In order to test the impact of the information provided, an inductive rule-based task was designed, in which feature salience and comparison informativeness between examples of two categories were manipulated during the learning phases, by introducing and progressively reducing some perceptual biases...
August 14, 2017: Cognitive Processing
David Cárdenas-Peña, Diego Collazos-Huertas, German Castellanos-Dominguez
Alzheimer's disease (AD) is the kind of dementia that affects the most people around the world. Therefore, an early identification supporting effective treatments is required to increase the life quality of a wide number of patients. Recently, computer-aided diagnosis tools for dementia using Magnetic Resonance Imaging scans have been successfully proposed to discriminate between patients with AD, mild cognitive impairment, and healthy controls. Most of the attention has been given to the clinical data, provided by initiatives as the ADNI, supporting reliable researches on intervention, prevention, and treatments of AD...
2017: Frontiers in Neuroscience
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