This is not the latest version of this item. The latest version can be found here.
A model of selection history in visual attention - CogSci 2021
No Thumbnail Available
Date
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Description
Content
This repository contains the files and data necessary to recreate the results from the paper
N.Meibodi, H.Abbasi, A. Schuboe, D. Endres (2021) A Model of Selection History in Visual Attention, Proceedings of the 2021 Conference of the Society of Cognitive Science, Vienna, Austria.
File list
attention_models_cogsci.py: run this file in python 3.8 to recreate results:
• maps_weights.pdf: bar plots to compare the maps’ weights between groups (color and shape). Fig5 in the paper.
• evidence_par.pdf: model evidences on bar plots to compare three models. Fig4 in the paper.
• model_evidence_par.xlsx: model evidences are saved in this file, when models are fitted across participants.
• model_evidence_group.xlsx: model evidences are saved in this file, when models are fitted across groups.
• CG.pdf and SG.pdf: Ex-Gaussian distributions of reaction times, fitted on the data and also model predicted distributions, for color group and shape group participants. Fig6 in the paper. torch_hessian.py: computation of Hessian matrix, needs to be in the same directory as 'attention_models_cogsci.py'
Data_CogSci2021.xlsx: Data from which models are learned
'Description of the uploaded dataset - CogSci 2021.docx': Description of data format and content.
paper_cogsci.pdf: preprint of the proceedings paper.
Acknowledgements
This work was supported by the SFB-TRR 135 'Cardinal Mechanisms of Perception', projects C6 and B3, and 'The Adaptive Mind', funded by the Excellence Program of the Hessian Ministry for Science and the Arts.
Keywords
Psychology, Cognitive Science
Citation
Collections
Endorsement
Review
Supplemented By
Referenced By
Creative Commons license
Except where otherwised noted, this item's license is described as Creative Commons Attribution 4.0
Version History
You are currently viewing version 1 of the item.