Analysis of goal, feedback and rewards on sustained attention via machine learning
These findings highlight the potential of machine learning to advance research on sustained attention and behavior, particularly in studies incorporating pupillometry or other physiological measurements, offering new avenues for understanding and analysis.
Authors
- Matthew K. Robison (ORCID: https://orcid.org/0000-0003-3565-6002)
- Nimalika Fernando (ORCID: https://orcid.org/0000-0002-4453-7235)
- Pedro D. Maia (ORCID: https://orcid.org/0000-0002-3335-4257)
Institutions
- University of Notre Dame (US)
- The University of Texas at Arlington (US)
Publication Details
- Journal
- Frontiers in Behavioral Neuroscience
- Published
- 2024-12-19
- DOI
- https://doi.org/10.3389/fnbeh.2024.1386723
- Primary Topic
- Mind wandering and attention
- Type
- article
- Field-Weighted Citation Impact
- 0.00