- AutorIn
- Adriana Böttcher Technische Universität Dresden, Germany
- Nico AdelhöferTechnische Universität Dresden, Germany
- Saskia WilkenGeneral Psychology: Judgment, Decision Making, & Action, Institute of Psychology, University of Hagen, Germany
- Markus Raab
- Sven Hoffmann
- Christian Beste
- Titel
- TRACK—a new algorithm and open‑source tool for the analysis of pursuit‑tracking sensorimotor integration processes
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-933875
- Quellenangabe
- Behavior research methods
Erscheinungsjahr: 2023
Jahrgang: 56
Seiten: 433-446
E-ISSN: 1554-3528 - Abstract (EN)
- In daily life, sensorimotor integration processes are fundamental for many cognitive operations. The pursuit-tracking paradigm is an ecological and valid paradigm to examine sensorimotor integration processes in a more complex environment than many established tasks that assess simple motor responses. However, the analysis of pursuit-tracking performance is complicated, and parameters quantified to examine performance are sometimes ambiguous regarding their interpretation. We introduce an open-source algorithm (TRACK) to calculate a new tracking error metric, the spatial error, based on the identification of the intended target position for the respective cursor position. The identification is based on assigning cursor and target direction changes to each other as key events, based on the assumptions of similarity and proximity. By applying our algorithm to pursuit-tracking data, beyond replication of known effects such as learning or practice effects, we show a higher precision of the spatial tracking error, i.e., it fits our behavioral data better than the temporal tracking error and thus provides new insights and parameters for the investigation of pursuit-tracking behavior. Our work provides an important step towards fully utilizing the potential of pursuit-tracking tasks for research on sensorimotor integration processes.
- Andere Ausgabe
- Link zum Artikel, der zuerst in der Zeitschrift „Behavior research methods” bei Springer erschienen ist.
DOI: 10.3758/s13428-023-02065-w - Freie Schlagwörter (EN)
- Sensorimotor integration, Tracking task, Algorithm
- Klassifikation (DDC)
- 150
- Verlag
- Springer, New York, NY
- Förder- / Projektangaben
- Deutsche Forschungsgemeinschaft (DFG)
FOR 2790: Merkmalsintegration und -abruf in der Handlungssteuerung
ID: 393269228 - Version / Begutachtungsstatus
- publizierte Version / Verlagsversion
- URN Qucosa
- urn:nbn:de:bsz:14-qucosa2-933875
- Veröffentlichungsdatum Qucosa
- 08.11.2024
- Dokumenttyp
- Artikel
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
CC BY 4.0