This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.
SoCal Kinesia and Incentivization for Parkinson’s Disease (SKIP): Approach-Avoid
Output Details
Description
Approach-Avoid Task (approachavoid) from the SKIP Dataset
The Socal Kinesia and Incentivization for Parkinson's Disease (SKIP) dataset facilitates research across human sciences, focusing on human movement and the modulatory impact of incentivization, specifically in the context of Parkinson's Disease (PD).
SKIP so far contains three task-based fMRI datasets and one resting-state fMRI dataset.
This dataset: Approach-Avoid Task (approachavoid)
Description: 78 participants making time-constrained reaches toward or away from emotional images.
Valence (Positive and Negative) of pictures and joystick movement direction (Approach and Avoid) were manipulated.
Participants pulled the joystick towards themselves (approach) or away from themselves (avoid) based on the picture's valence.
Task design creates emotion-action congruent (Positive-Approach, Negative-Avoid) and incongruent (Positive-Avoid, Negative-Approach) conditions.
Current Version: 1.0.1
Note: This version contains data from healthy controls only. Future updates will include data from PD patients and a broader range of assays in both healthy controls and PD subjects, such as cardiac-autonomic and pupillometry data.
Our goal for SKIP (https://socalkinesia.org/about/) is to become the leading global resource as the world advances in its capacity for powerful and innovative analyses, allowing researchers free access to comprehensive physiological and behavioral assays of movement, and how incentives influence them, in the context of PD.
Identifier (DOI)
10.18112/openneuro.ds005265.v1.0.0