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.
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AuthorsEndres, Dominik, Prof. Dr.
ContributorsResearcher: Meibodi, Neda, MSc
LicenseCreative Commons Attribution 4.0
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attention_cogsci-CogSci2021v2.tar .tar1.806Mbee12b3725ce3bed02bbdb293ea0bcb48
license_CC-BY-4.0.txt .txt18.21Kb380b31767eeb6303e3bc300d8846f180
Creative Commons Attribution 4.0
Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0

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