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The FoodCast research image database (FRIDa).

Foroni F, Pergola G, Argiris G, Rumiati RI - Front Hum Neurosci (2013)

Bottom Line: Despite the importance of the issues and the relevance of this research, comprehensive and validated databases of stimuli are rather limited, outdated, or not available for non-commercial purposes to independent researchers who aim at developing their own research program.The FoodCast Research Image Database (FRIDa) we present here includes 877 images belonging to eight different categories: natural-food (e.g., strawberry), transformed-food (e.g., french fries), rotten-food (e.g., moldy banana), natural-non-food items (e.g., pinecone), artificial food-related objects (e.g., teacup), artificial objects (e.g., guitar), animals (e.g., camel), and scenes (e.g., airport).FRIDa has been validated on a sample of healthy participants (N = 73) on standard variables (e.g., valence, familiarity, etc.) as well as on other variables specifically related to food items (e.g., perceived calorie content); it also includes data on the visual features of the stimuli (e.g., brightness, high frequency power, etc.).

View Article: PubMed Central - PubMed

Affiliation: Cognitive Neuroscience Sector, SISSA - Trieste Trieste, Italy.

ABSTRACT
In recent years we have witnessed an increasing interest in food processing and eating behaviors. This is probably due to several reasons. The biological relevance of food choices, the complexity of the food-rich environment in which we presently live (making food-intake regulation difficult), and the increasing health care cost due to illness associated with food (food hazards, food contamination, and aberrant food-intake). Despite the importance of the issues and the relevance of this research, comprehensive and validated databases of stimuli are rather limited, outdated, or not available for non-commercial purposes to independent researchers who aim at developing their own research program. The FoodCast Research Image Database (FRIDa) we present here includes 877 images belonging to eight different categories: natural-food (e.g., strawberry), transformed-food (e.g., french fries), rotten-food (e.g., moldy banana), natural-non-food items (e.g., pinecone), artificial food-related objects (e.g., teacup), artificial objects (e.g., guitar), animals (e.g., camel), and scenes (e.g., airport). FRIDa has been validated on a sample of healthy participants (N = 73) on standard variables (e.g., valence, familiarity, etc.) as well as on other variables specifically related to food items (e.g., perceived calorie content); it also includes data on the visual features of the stimuli (e.g., brightness, high frequency power, etc.). FRIDa is a well-controlled, flexible, validated, and freely available (http://foodcast.sissa.it/neuroscience/) tool for researchers in a wide range of academic fields and industry.

No MeSH data available.


Related in: MedlinePlus

Examples of the stimuli from the database. Tree examples of items from each category of stimuli. Information regarding the examples is reported in the Appendix.
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Figure 1: Examples of the stimuli from the database. Tree examples of items from each category of stimuli. Information regarding the examples is reported in the Appendix.

Mentions: The final database comprises 877 images. All images are open-source and compiled from a web-based search. Each image depicts an item belonging to one of eight different categories: (1) natural-food (e.g., strawberry; N = 99 images); (2) transformed-food (e.g., french fries; N = 153 images); (3) rotten-food (e.g., moldy banana; N = 43 images); (4) natural-non-food items (e.g., pinecone; N = 53 images), (5) artificial food-related objects (e.g., teacup; N = 119 images); (6) artificial objects (e.g., guitar; N = 299 images); (7) animals (e.g., camel; N = 54 images); and (8) scenes (e.g., airport; N = 57 images). Figure 1 displays three examples of picture for each category.


The FoodCast research image database (FRIDa).

Foroni F, Pergola G, Argiris G, Rumiati RI - Front Hum Neurosci (2013)

Examples of the stimuli from the database. Tree examples of items from each category of stimuli. Information regarding the examples is reported in the Appendix.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3585434&req=5

Figure 1: Examples of the stimuli from the database. Tree examples of items from each category of stimuli. Information regarding the examples is reported in the Appendix.
Mentions: The final database comprises 877 images. All images are open-source and compiled from a web-based search. Each image depicts an item belonging to one of eight different categories: (1) natural-food (e.g., strawberry; N = 99 images); (2) transformed-food (e.g., french fries; N = 153 images); (3) rotten-food (e.g., moldy banana; N = 43 images); (4) natural-non-food items (e.g., pinecone; N = 53 images), (5) artificial food-related objects (e.g., teacup; N = 119 images); (6) artificial objects (e.g., guitar; N = 299 images); (7) animals (e.g., camel; N = 54 images); and (8) scenes (e.g., airport; N = 57 images). Figure 1 displays three examples of picture for each category.

Bottom Line: Despite the importance of the issues and the relevance of this research, comprehensive and validated databases of stimuli are rather limited, outdated, or not available for non-commercial purposes to independent researchers who aim at developing their own research program.The FoodCast Research Image Database (FRIDa) we present here includes 877 images belonging to eight different categories: natural-food (e.g., strawberry), transformed-food (e.g., french fries), rotten-food (e.g., moldy banana), natural-non-food items (e.g., pinecone), artificial food-related objects (e.g., teacup), artificial objects (e.g., guitar), animals (e.g., camel), and scenes (e.g., airport).FRIDa has been validated on a sample of healthy participants (N = 73) on standard variables (e.g., valence, familiarity, etc.) as well as on other variables specifically related to food items (e.g., perceived calorie content); it also includes data on the visual features of the stimuli (e.g., brightness, high frequency power, etc.).

View Article: PubMed Central - PubMed

Affiliation: Cognitive Neuroscience Sector, SISSA - Trieste Trieste, Italy.

ABSTRACT
In recent years we have witnessed an increasing interest in food processing and eating behaviors. This is probably due to several reasons. The biological relevance of food choices, the complexity of the food-rich environment in which we presently live (making food-intake regulation difficult), and the increasing health care cost due to illness associated with food (food hazards, food contamination, and aberrant food-intake). Despite the importance of the issues and the relevance of this research, comprehensive and validated databases of stimuli are rather limited, outdated, or not available for non-commercial purposes to independent researchers who aim at developing their own research program. The FoodCast Research Image Database (FRIDa) we present here includes 877 images belonging to eight different categories: natural-food (e.g., strawberry), transformed-food (e.g., french fries), rotten-food (e.g., moldy banana), natural-non-food items (e.g., pinecone), artificial food-related objects (e.g., teacup), artificial objects (e.g., guitar), animals (e.g., camel), and scenes (e.g., airport). FRIDa has been validated on a sample of healthy participants (N = 73) on standard variables (e.g., valence, familiarity, etc.) as well as on other variables specifically related to food items (e.g., perceived calorie content); it also includes data on the visual features of the stimuli (e.g., brightness, high frequency power, etc.). FRIDa is a well-controlled, flexible, validated, and freely available (http://foodcast.sissa.it/neuroscience/) tool for researchers in a wide range of academic fields and industry.

No MeSH data available.


Related in: MedlinePlus