From classical methods to generative models: Tackling the unreliability of neuroscientific measures in mental health research
Advances in computational statistics and corresponding shifts in funding initiatives over the
past few decades have led to a proliferation of neuroscientific measures being developed in …
past few decades have led to a proliferation of neuroscientific measures being developed in …
Using reinforcement learning models in social neuroscience: frameworks, pitfalls and suggestions of best practices
The recent years have witnessed a dramatic increase in the use of reinforcement learning
(RL) models in social, cognitive and affective neuroscience. This approach, in combination …
(RL) models in social, cognitive and affective neuroscience. This approach, in combination …
Theoretically informed generative models can advance the psychological and brain sciences: Lessons from the reliability paradox
Theories of individual differences are foundational to psychological and brain sciences, yet
they are traditionally developed and tested using superficial summaries of data (eg, mean …
they are traditionally developed and tested using superficial summaries of data (eg, mean …
[PDF][PDF] Learning from the reliability paradox: How theoretically informed generative models can advance the social, behavioral, and brain sciences
A primary aim of social, behavioral, and brain sciences is to develop explanations that
answer questions of why or how observed psychological phenomena occur (Hempel & …
answer questions of why or how observed psychological phenomena occur (Hempel & …
Long-term outcomes of adolescent THC exposure on translational cognitive measures in adulthood in an animal model and computational assessment of human data
Importance Although perceived as relatively harmless and nonaddictive, adolescent
cannabis use significantly increases the likelihood of developing cannabis use disorder in …
cannabis use significantly increases the likelihood of developing cannabis use disorder in …
Parallel model-based and model-free reinforcement learning for card sorting performance
Abstract The Wisconsin Card Sorting Test (WCST) is considered a gold standard for the
assessment of cognitive flexibility. On the WCST, repeating a sorting category following …
assessment of cognitive flexibility. On the WCST, repeating a sorting category following …
Altered reinforcement learning in Narcolepsy type I and other central disorders of hypersomnolence
Cognitive impairments are described in central disorders of hypersomnolence (CDH), but
studies remain very limited and largely focused on narcolepsy type 1 (NT1). The precise …
studies remain very limited and largely focused on narcolepsy type 1 (NT1). The precise …
Decision-making (in) flexibility in gambling disorder
Background Behavioral flexibility–the ability to dynamically readjust our behavior in
response to reward contingency changes–is often investigated using probabilistic reversal …
response to reward contingency changes–is often investigated using probabilistic reversal …
Decision‐making biases in suicide attempters with major depressive disorder: A computational modeling study using the balloon analog risk task (BART)
Background In the last decade, suicidality has been increasingly theorized as a distinct
phenomenon from major depressive disorder (MDD), with unique psychological and neural …
phenomenon from major depressive disorder (MDD), with unique psychological and neural …
Development of a novel computational model for the Balloon Analogue Risk Task: The exponential-weight mean–variance model
H Park, J Yang, J Vassileva, WY Ahn - Journal of Mathematical Psychology, 2021 - Elsevier
Abstract The Balloon Analogue Risk Task (BART) is a popular task used to measure risk-
taking behavior. To identify cognitive processes associated with choice behavior on the …
taking behavior. To identify cognitive processes associated with choice behavior on the …