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https://www.readbyqxmd.com/read/28729738/human-hippocampal-pre-activation-predicts-behavior
#1
Anna Jafarpour, Vitoria Piai, Jack J Lin, Robert T Knight
The response to an upcoming salient event is accelerated when the event is expected given the preceding events - i.e. a temporal context effect. For example, naming a picture following a strongly constraining temporal context is faster than naming a picture after a weakly constraining temporal context. We used sentences as naturalistic stimuli to manipulate expectations on upcoming pictures without prior training. Here, using intracranial recordings from the human hippocampus we found more power in the high-frequency band prior to high-expected pictures than weakly expected ones...
July 20, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28727543/non-small-cell-lung-cancer-radiogenomics-map-identifies-relationships-between-molecular-and-imaging-phenotypes-with-prognostic-implications
#2
Mu Zhou, Ann Leung, Sebastian Echegaray, Andrew Gentles, Joseph B Shrager, Kristin C Jensen, Gerald J Berry, Sylvia K Plevritis, Daniel L Rubin, Sandy Napel, Olivier Gevaert
Purpose To create a radiogenomic map linking computed tomographic (CT) image features and gene expression profiles generated by RNA sequencing for patients with non-small cell lung cancer (NSCLC). Materials and Methods A cohort of 113 patients with NSCLC diagnosed between April 2008 and September 2014 who had preoperative CT data and tumor tissue available was studied. For each tumor, a thoracic radiologist recorded 87 semantic image features, selected to reflect radiologic characteristics of nodule shape, margin, texture, tumor environment, and overall lung characteristics...
July 20, 2017: Radiology
https://www.readbyqxmd.com/read/28713303/investigating-thematic-roles-through-implicit-learning-evidence-from-light-verb-constructions
#3
Eva Wittenberg, Manizeh Khan, Jesse Snedeker
The syntactic structure of a sentence is usually a strong predictor of its meaning: Each argument noun phrase (i.e., Subject and Object) should map onto exactly one thematic role (i.e., Agent and Patient, respectively). Some constructions, however, are exceptions to this pattern. This paper investigates how the syntactic structure of an utterance contributes to its construal, using ditransitive English light verb constructions, such as "Nils gave a hug to his brother," as an example of such mismatches: Hugging is a two-role event, but the ditransitive syntactic structure suggests a three-role event...
2017: Frontiers in Psychology
https://www.readbyqxmd.com/read/28693370/toward-a-graded-psycholexical-space-mapping-model-sublexical-and-lexical-representations-in-chinese-character-reading-development
#4
Xiuli Tong, Catherine McBride
Following a review of contemporary models of word-level processing for reading and their limitations, we propose a new hypothetical model of Chinese character reading, namely, the graded lexical space mapping model that characterizes how sublexical radicals and lexical information are involved in Chinese character reading development. The underlying assumption of this model is that Chinese character recognition is a process of competitive mappings of phonology, semantics, and orthography in both lexical and sublexical systems, operating as functions of statistical properties of print input based on the individual's specific level of reading...
July 1, 2017: Journal of Learning Disabilities
https://www.readbyqxmd.com/read/28692956/deepfix-a-fully-convolutional-neural-network-for-predicting-human-eye-fixations
#5
Srinivas S S Kruthiventi, Kumar Ayush, R Venkatesh Babu
Understanding and predicting the human visual attention mechanism is an active area of research in the fields of neuroscience and computer vision. In this paper, we propose DeepFix, a fully convolutional neural network, which models the bottom-up mechanism of visual attention via saliency prediction. Unlike classical works, which characterize the saliency map using various hand-crafted features, our model automatically learns features in a hierarchical fashion and predicts the saliency map in an end-to-end manner...
September 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28690513/feature-selection-methods-for-zero-shot-learning-of-neural-activity
#6
Carlos A Caceres, Matthew J Roos, Kyle M Rupp, Griffin Milsap, Nathan E Crone, Michael E Wolmetz, Christopher R Ratto
Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows) have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28679928/semantic-web-reusable-learning-objects-personal-learning-networks-in-health-key-pieces-for-digital-health-literacy
#7
Stathis Th Konstantinidis, Heather Wharrad, Richard Windle, Panagiotis D Bamidis
The knowledge existing in the World Wide Web is exponentially expanding, while continuous advancements in health sciences contribute to the creation of new knowledge. There are a lot of efforts trying to identify how the social connectivity can endorse patients' empowerment, while other studies look at the identification and the quality of online materials. However, emphasis has not been put on the big picture of connecting the existing resources with the patients "new habits" of learning through their own Personal Learning Networks...
2017: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/28653794/predicting-the-brain-activation-pattern-associated-with-the-propositional-content-of-a-sentence-modeling-neural-representations-of-events-and-states
#8
Jing Wang, Vladimir L Cherkassky, Marcel Adam Just
Even though much has recently been learned about the neural representation of individual concepts and categories, neuroimaging research is only beginning to reveal how more complex thoughts, such as event and state descriptions, are neurally represented. We present a predictive computational theory of the neural representations of individual events and states as they are described in 240 sentences. Regression models were trained to determine the mapping between 42 neurally plausible semantic features (NPSFs) and thematic roles of the concepts of a proposition and the fMRI activation patterns of various cortical regions that process different types of information...
June 27, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28648889/mapping-between-fmri-responses-to-movies-and-their-natural-language-annotations
#9
REVIEW
Kiran Vodrahalli, Po-Hsuan Chen, Yingyu Liang, Christopher Baldassano, Janice Chen, Esther Yong, Christopher Honey, Uri Hasson, Peter Ramadge, Kenneth A Norman, Sanjeev Arora
Several research groups have shown how to map fMRI responses to the meanings of presented stimuli. This paper presents new methods for doing so when only a natural language annotation is available as the description of the stimulus. We study fMRI data gathered from subjects watching an episode of BBCs Sherlock (Chen et al., 2017), and learn bidirectional mappings between fMRI responses and natural language representations. By leveraging data from multiple subjects watching the same movie, we were able to perform scene classification with 72% accuracy (random guessing would give 4%) and scene ranking with average rank in the top 4% (random guessing would give 50%)...
June 22, 2017: NeuroImage
https://www.readbyqxmd.com/read/28616382/improving-language-mapping-in-clinical-fmri-through-assessment-of-grammar
#10
Monika Połczyńska, Kevin Japardi, Susan Curtiss, Teena Moody, Christopher Benjamin, Andrew Cho, Celia Vigil, Taylor Kuhn, Michael Jones, Susan Bookheimer
INTRODUCTION: Brain surgery in the language dominant hemisphere remains challenging due to unintended post-surgical language deficits, despite using pre-surgical functional magnetic resonance (fMRI) and intraoperative cortical stimulation. Moreover, patients are often recommended not to undergo surgery if the accompanying risk to language appears to be too high. While standard fMRI language mapping protocols may have relatively good predictive value at the group level, they remain sub-optimal on an individual level...
2017: NeuroImage: Clinical
https://www.readbyqxmd.com/read/28602887/cross-modal-recruitment-of-auditory-and-orofacial-areas-during-sign-language-in-a-deaf-subject
#11
Juan Martino, Carlos Velasquez, Javier Vázquez-Bourgon, Enrique Marco de Lucas, Elsa Gomez
BACKGROUND: Modern sign languages used by deaf people are fully expressive, natural human languages that are perceived visually and produced manually. The literature contains little data concerning human brain organization in conditions of deficient sensory information such as deafness. CASE DESCRIPTION: A deaf-mute patient underwent surgery of a left temporoinsular low-grade glioma. The patient underwent awake surgery with intraoperative electrical stimulation mapping, allowing direct study of the cortical and subcortical organization of sign language...
July 10, 2017: World Neurosurgery
https://www.readbyqxmd.com/read/28601710/evolution-of-word-meanings-through-metaphorical-mapping-systematicity-over-the-past-millennium
#12
Yang Xu, Barbara C Malt, Mahesh Srinivasan
One way that languages are able to communicate a potentially infinite set of ideas through a finite lexicon is by compressing emerging meanings into words, such that over time, individual words come to express multiple, related senses of meaning. We propose that overarching communicative and cognitive pressures have created systematic directionality in how new metaphorical senses have developed from existing word senses over the history of English. Given a large set of pairs of semantic domains, we used computational models to test which domains have been more commonly the starting points (source domains) and which the ending points (target domains) of metaphorical mappings over the past millennium...
June 8, 2017: Cognitive Psychology
https://www.readbyqxmd.com/read/28600249/egocentric-mapping-of-body-surface-constraints
#13
Eray Molla, Henrique Galvan Debarba, Ronan Boulic
The relative location of human body parts often materializes the semantics of on-going actions, intentions and even emotions expressed, or performed, by a human being. However, traditional methods of performance animation fail to correctly and automatically map the semantics of performer postures involving self-body contacts onto characters with different sizes and proportions. Our method proposes an egocentric normalization of the body-part relative distances to preserve the consistency of self contacts for a large variety of human-like target characters...
June 7, 2017: IEEE Transactions on Visualization and Computer Graphics
https://www.readbyqxmd.com/read/28600247/multimodal-similarity-gaussian-process-latent-variable-model
#14
Guoli Song, Shuhui Wang, Qingming Huang, Qi Tian
Data from real applications involve multiple modalities representing content with the same semantics from complementary aspects. However, relations among heterogeneous modalities are simply treated as observation-to-fit by existing work, and the parameterized modality specific mapping functions lack flexibility in directly adapting to the content divergence and semantic complicacy in multimodal data. In this paper, we build our work based on the Gaussian process latent variable model (GPLVM) to learn the non-parametric mapping functions and transform heterogeneous modalities into a shared latent space...
September 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28587117/deepmap-recognizing-high-level-indoor-semantics-using-virtual-features-and-samples-based-on-a-multi-length-window-framework
#15
Wei Zhang, Siwang Zhou
Existing indoor semantic recognition schemes are mostly capable of discovering patterns through smartphone sensing, but it is hard to recognize rich enough high-level indoor semantics for map enhancement. In this work we present DeepMap+, an automatical inference system for recognizing high-level indoor semantics using complex human activities with wrist-worn sensing. DeepMap+ is the first deep computation system using deep learning (DL) based on a multi-length window framework to enrich the data source. Furthermore, we propose novel methods of increasing virtual features and virtual samples for DeepMap+ to better discover hidden patterns of complex hand gestures...
May 26, 2017: Sensors
https://www.readbyqxmd.com/read/28579952/brain-network-for-the-core-deficits-of-semantic-dementia-a-neural-network-connectivity-behavior-mapping-study
#16
Yan Chen, Keliang Chen, Junhua Ding, Yumei Zhang, Qing Yang, Yingru Lv, Qihao Guo, Zaizhu Han
Individuals with semantic dementia (SD) typically suffer from selective semantic deficits due to degenerative brain atrophy. Although some brain regions have been found to be correlated with the semantic impairments of SD patients, it is unclear if the damage is actually responsible for SD patients' semantic disorders because these findings were primarily obtained by examining the roles of local individual regions themselves without considering the influence of other regions that are functionally or structurally connected to the local individual regions...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28575757/sensorimotor-experience-and-verb-category-mapping-in-human-sensory-motor-and-parietal-neurons
#17
Ying Yang, Michael Walsh Dickey, Julie Fiez, Brian Murphy, Tom Mitchell, Jennifer Collinger, Elizabeth Tyler-Kabara, Michael Boninger, Wei Wang
Semantic grounding is the process of relating meaning to symbols (e.g., words). It is the foundation for creating a representational symbolic system such as language. Semantic grounding for verb meaning is hypothesized to be achieved through two mechanisms: sensorimotor mapping, i.e., directly encoding the sensorimotor experiences the verb describes, and verb-category mapping, i.e., encoding the abstract category a verb belongs to. These two mechanisms were investigated by examining neuronal-level spike (i...
May 6, 2017: Cortex; a Journal Devoted to the Study of the Nervous System and Behavior
https://www.readbyqxmd.com/read/28572785/age-of-acquisition-effects-on-word-processing-for-chinese-native-learners-english-erp-evidence-for-the-arbitrary-mapping-hypothesis
#18
Jin Xue, Tongtong Liu, Fernando Marmolejo-Ramos, Xuna Pei
The present study aimed at distinguishing processing of early learned L2 words from late ones for Chinese natives who learn English as a foreign language. Specifically, we examined whether the age of acquisition (AoA) effect arose during the arbitrary mapping from conceptual knowledge onto linguistic units. The behavior and ERP data were collected when 28 Chinese-English bilinguals were asked to perform semantic relatedness judgment on word pairs, which represented three stages of word learning (i.e., primary school, junior and senior high schools)...
2017: Frontiers in Psychology
https://www.readbyqxmd.com/read/28555611/real-time-inference-of-word-relevance-from-electroencephalogram-and-eye-gaze
#19
Markus Andreas Wenzel, Mihail Bogojeski, Benjamin Blankertz
OBJECTIVE: Brain-computer interfaces can potentially map the subjective relevance of the visual surrounding, based on neural activity and eye movements, in order to infer the interest of a person in real-time. APPROACH: Readers looked for words belonging to one out of five semantic categories, while a stream of words passed at different locations on the screen. It was estimated in real-time which words and thus which semantic category interested each reader based on the electroencephalogram (EEG) and the eye gaze...
May 30, 2017: Journal of Neural Engineering
https://www.readbyqxmd.com/read/28548027/dissociation-between-preserved-body-structural-description-and-impaired-body-image-following-a-pediatric-spinal-trauma
#20
Gerardo Salvato, Valeria Peviani, Elisa Scarano, Pina Scarpa, Alessandra Leo, Tiziana Redaelli, Michele Spinelli, Maurizio Sberna, Gabriella Bottini
In adult patients, Spinal Cord Injury (SCI) may influence the mental Body Representation (BR). Currently, there is no evidence on the modulation of SCI on BR during early stages of cognitive development. Here, we investigated BR in a 3-year-old child with complete SCI. The patient was administered with a specific battery assessing different BR components. We found evidence for putative classical neuropsychological dissociation between a preserved topological map with impaired semantic knowledge of the body...
May 26, 2017: Neurocase
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