2020
DOI: 10.3389/fpsyg.2020.585044
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Food Folio by Columbia Center for Eating Disorders: A Freely Available Food Image Database

Abstract: Food images are useful stimuli for the study of cognitive processes as well as eating behavior. To enhance rigor and reproducibility in task-based research, it is advantageous to have stimulus sets that are publicly available and well characterized. Food Folio by Columbia Center for Eating Disorders is a publicly available set of 138 images of Western food items. The set was developed for the study of eating disorders, particularly for use in tasks that capture eating behavior characteristic of these illnesses… Show more

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Cited by 11 publications
(29 citation statements)
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“…The distribution of taste ratings among HC was skewed relative to AN, resulting in high/low-taste food labels that did not capture the well-characterized influence of taste on choices among HC that was also previously observed in this sample (Foerde et al, 2015). This did not appear to alter the decoding results presented here, but future studies that seek to employ classification methods could specifically select stimulus sets to address such concerns (Lloyd and Foerde, 2020; Lloyd et al, 2020; Schebendach et al, 2020). It should be noted that the magnitude of decoding accuracies should be interpreted with caution because these measures can be influenced by ROI size, degree of voxel smoothing, and the size of training and test data sets, among other factors (Haynes, 2015).…”
Section: Discussionmentioning
confidence: 73%
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“…The distribution of taste ratings among HC was skewed relative to AN, resulting in high/low-taste food labels that did not capture the well-characterized influence of taste on choices among HC that was also previously observed in this sample (Foerde et al, 2015). This did not appear to alter the decoding results presented here, but future studies that seek to employ classification methods could specifically select stimulus sets to address such concerns (Lloyd and Foerde, 2020; Lloyd et al, 2020; Schebendach et al, 2020). It should be noted that the magnitude of decoding accuracies should be interpreted with caution because these measures can be influenced by ROI size, degree of voxel smoothing, and the size of training and test data sets, among other factors (Haynes, 2015).…”
Section: Discussionmentioning
confidence: 73%
“…This reduced sensitivity to tastiness may explain why classifier evidence of taste among HC did not predict the magnitude of their choice preferences. Future studies that employ food stimulus sets with more normally distributed taste ratings among participants may have more success in characterizing the contribution of OFC representations of tastiness to choices in normative decision-making (Lloyd et al, 2020).…”
Section: Discussionmentioning
confidence: 99%
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