Meta-analytic evidence for a core problem solving network across multiple representational domains
Problem solving is a complex skill engaging multi-stepped reasoning processes to find
unknown solutions. The breadth of real-world contexts requiring problem solving is mirrored …
unknown solutions. The breadth of real-world contexts requiring problem solving is mirrored …
An instance theory of semantic memory
Distributional semantic models (DSMs) specify learning mechanisms with which humans
construct a deep representation of word meaning from statistical regularities in language …
construct a deep representation of word meaning from statistical regularities in language …
Learning neural representations of human cognition across many fMRI studies
Cognitive neuroscience is enjoying rapid increase in extensive public brain-imaging
datasets. It opens the door to large-scale statistical models. Finding a unified perspective for …
datasets. It opens the door to large-scale statistical models. Finding a unified perspective for …
Latent environment allocation of microbial community data
As data for microbial community structures found in various environments has increased,
studies have examined the relationship between environmental labels given to retrieved …
studies have examined the relationship between environmental labels given to retrieved …
The Semantic Librarian: A search engine built from vector-space models of semantics
H Aujla, MJC Crump, MT Cook… - Behavior Research …, 2019 - Springer
Psychologists have made substantial progress at developing empirically validated formal
expressions of how people perceive, learn, remember, think, and know. In this article, we …
expressions of how people perceive, learn, remember, think, and know. In this article, we …
[HTML][HTML] aXonica: a support package for MRI based Neuroimaging
Abstract Magnetic Resonance Imaging (MRI) assists in studying the nervous system. MRI
scans undergo significant processing before presenting the final images to medical …
scans undergo significant processing before presenting the final images to medical …
Utilizing latent posting style for authorship attribution on short texts
P Leepaisomboon, M Iwaihara - … , Intl Conf on Cloud and Big …, 2019 - ieeexplore.ieee.org
Character n-grams and word n-grams are the most widely used features for authorship
attribution on short texts. In this paper, we propose a new method which exploits latent …
attribution on short texts. In this paper, we propose a new method which exploits latent …
VSEC-LDA: boosting topic modeling with embedded vocabulary selection
Topic modeling has found wide application in many problems where latent structures of the
data are crucial for typical inference tasks. When applying a topic model, a relatively …
data are crucial for typical inference tasks. When applying a topic model, a relatively …
word2brain
A Nunes - bioRxiv, 2018 - biorxiv.org
Mapping brain functions to their underlying neural substrates is a central goal of cognitive
neuroscience. Functional magnetic resonance imaging (fMRI) has proven indispensable in …
neuroscience. Functional magnetic resonance imaging (fMRI) has proven indispensable in …
Extended Functional Connectivity of Convergent Structural Alterations Among Anxiety Disorders: A Meta-Analysis and Functional Connectivity Analysis
BS Pankey - 2021 - digitalcommons.fiu.edu
Anxiety-related disorders are some of the most pervasive mental health disorders affecting
adult and youth populations. Despite growing evidence of the neurobiology associated with …
adult and youth populations. Despite growing evidence of the neurobiology associated with …