AI Medical Compendium Journal:
Behavior research methods

Showing 31 to 40 of 66 articles

Deep-SAGA: a deep-learning-based system for automatic gaze annotation from eye-tracking data.

Behavior research methods
With continued advancements in portable eye-tracker technology liberating experimenters from the restraints of artificial laboratory designs, research can now collect gaze data from real-world, natural navigation. However, the field lacks a robust me...

Waiting for baseline stability in single-case designs: Is it worth the time and effort?

Behavior research methods
Researchers and practitioners often use single-case designs (SCDs), or n-of-1 trials, to develop and validate novel treatments. Standards and guidelines have been published to provide guidance as to how to implement SCDs, but many of their recommenda...

IAT faking indices revisited: Aspects of replicability and differential validity.

Behavior research methods
Research demonstrates that IATs are fakeable. Several indices [either slowing down or speeding up, and increasing errors or reducing errors in congruent and incongruent blocks; Combined Task Slowing (CTS); Ratio 150-10000] have been developed to dete...

Machine learning strategy identification: A paradigm to uncover decision strategies with high fidelity.

Behavior research methods
We propose a novel approach, which we call machine learning strategy identification (MLSI), to uncovering hidden decision strategies. In this approach, we first train machine learning models on choice and process data of one set of participants who a...

Measuring national mood with music: using machine learning to construct a measure of national valence from audio data.

Behavior research methods
We propose a new measure of national valence based on the emotional content of a country's most popular songs. We first trained a machine learning model using 191 different audio features embedded within music and use this model to construct a long-r...

Machine learning to detect invalid text responses: Validation and comparison to existing detection methods.

Behavior research methods
A crucial step in analysing text data is the detection and removal of invalid texts (e.g., texts with meaningless or irrelevant content). To date, research topics that rely heavily on analysis of text data, such as autobiographical memory, have lacke...

An exploration of error-driven learning in simple two-layer networks from a discriminative learning perspective.

Behavior research methods
Error-driven learning algorithms, which iteratively adjust expectations based on prediction error, are the basis for a vast array of computational models in the brain and cognitive sciences that often differ widely in their precise form and applicati...

Introducing the Prototypical Stimulus Characteristics Toolbox: Protosc.

Behavior research methods
Many studies use different categories of images to define their conditions. Since any difference between these categories is a valid candidate to explain category-related behavioral differences, knowledge about the objective image differences between...

Tracking strategy changes using machine learning classifiers.

Behavior research methods
In complex tasks, high performers often have better strategies than low performers, even with similar amounts of practice. Relatively little research has examined how people form and change strategies in tasks that permit a large set of strategies. O...

Exploring self-generated thoughts in a resting state with natural language processing.

Behavior research methods
The present study seeks to examine individuals' stream of thought in real time. Specifically, we asked participants to speak their thoughts freely out loud during a typical resting-state condition. We first examined the feasibility and reliability of...