Individual differences in reward‐based learning predict fluid reasoning abilities
The ability to reason and problem‐solve in novel situations, as measured by the Raven's
Advanced Progressive Matrices (RAPM), is highly predictive of both cognitive task …
Advanced Progressive Matrices (RAPM), is highly predictive of both cognitive task …
[HTML][HTML] Bayesian inference for multidimensional scaling representations with psychologically interpretable metrics
Multidimensional scaling (MDS) models represent stimuli as points in a space consisting of
a number of psychological dimensions, such that the distance between pairs of points …
a number of psychological dimensions, such that the distance between pairs of points …
Computational cognitive neuroscience.
FG Ashby - 2018 - psycnet.apa.org
Cognitive neuroscience was born in the 1990s amid a technological explosion that
produced powerful new methods for non-invasively studying the human brain, including …
produced powerful new methods for non-invasively studying the human brain, including …
Toward an integrated account of object and action selection: A computational analysis and empirical findings from reaching-to-grasp and tool-use
The act of reaching for and acting upon an object involves two forms of selection: selection
of the object as a target, and selection of the action to be performed. While these two forms …
of the object as a target, and selection of the action to be performed. While these two forms …
A computational model of focused attention meditation and its transfer to a sustained attention task
AJ Moye, MK Van Vugt - IEEE Transactions on Affective …, 2019 - ieeexplore.ieee.org
Meditation has been shown to aid with the management of affective disorders through
improving emotion regulation. Here we begin to develop a theory of meditation by creating a …
improving emotion regulation. Here we begin to develop a theory of meditation by creating a …
Measuring model flexibility with parameter space partitioning: An introduction and application example
A primary criterion on which models of cognition are evaluated is their ability to fit empirical
data. To understand the reason why a model yields a good or poor fit, it is necessary to …
data. To understand the reason why a model yields a good or poor fit, it is necessary to …
Modeling perceptual expertise.
TJ Palmeri, GW Cottrell - 2010 - psycnet.apa.org
In this chapter we delineate what we believe to be the important characteristics of perceptual
expertise that a complete model should try to capture, motivate why computational models …
expertise that a complete model should try to capture, motivate why computational models …
[HTML][HTML] Relative cue encoding in the context of sophisticated models of categorization: Separating information from categorization
KS Apfelbaum, B McMurray - Psychonomic bulletin & review, 2015 - Springer
Traditional studies of human categorization often treat the processes of encoding features
and cues as peripheral to the question of how stimuli are categorized. However, in domains …
and cues as peripheral to the question of how stimuli are categorized. However, in domains …
The interaction between competition, learning, and habituation dynamics in speech perception
L Lancia, B Winter - Laboratory Phonology, 2013 - degruyter.com
Even though the outcome of the perception of phonological patterns is categorical, this
process might still arise from continuous dynamics. Here, we propose a unified dynamical …
process might still arise from continuous dynamics. Here, we propose a unified dynamical …
Pigeon category learning: Revisiting the Shepard, Hovland, and Jenkins (1961) tasks.
VM Navarro, R Jani, EA Wasserman - Journal of Experimental …, 2019 - psycnet.apa.org
In a seminal study, Shepard, Hovland, and Jenkins (1961; henceforth SHJ) assessed
potential mechanisms involved in categorization learning. To do so, they sequentially …
potential mechanisms involved in categorization learning. To do so, they sequentially …