The article by Meredith Minear and Denise C. Park describes the creation of a comprehensive database of adult facial stimuli, aiming to address the lack of diverse age representations in existing face databases. The database includes 575 individual faces ranging from ages 18 to 93, with a focus on recruiting older adults. The faces are categorized into four age groups: 18-29, 30-49, 50-69, and 70 and older. The database is designed to be more representative of the adult lifespan and is available for researchers to access at http://agingmind.cns.uiuc.edu/facedb/. The authors highlight the importance of including a wide range of ages in face research, as older adults often show impaired recognition of unfamiliar faces compared to younger adults. They also discuss the impact of experiential factors, such as familiarity with certain types of faces, on memory performance. The database addresses these issues by providing a broader age range and higher resolution images, which are crucial for studies on aging and face perception. The method section details the recruitment process, which involved visiting various locations in northern Ohio and southern Michigan to collect digital photographs from volunteers. The participants were paid for their participation, and their demographic information was recorded. The resulting database includes detailed information about each face, such as age, gender, and facial expression, and is structured to facilitate easy sorting and access for researchers.The article by Meredith Minear and Denise C. Park describes the creation of a comprehensive database of adult facial stimuli, aiming to address the lack of diverse age representations in existing face databases. The database includes 575 individual faces ranging from ages 18 to 93, with a focus on recruiting older adults. The faces are categorized into four age groups: 18-29, 30-49, 50-69, and 70 and older. The database is designed to be more representative of the adult lifespan and is available for researchers to access at http://agingmind.cns.uiuc.edu/facedb/. The authors highlight the importance of including a wide range of ages in face research, as older adults often show impaired recognition of unfamiliar faces compared to younger adults. They also discuss the impact of experiential factors, such as familiarity with certain types of faces, on memory performance. The database addresses these issues by providing a broader age range and higher resolution images, which are crucial for studies on aging and face perception. The method section details the recruitment process, which involved visiting various locations in northern Ohio and southern Michigan to collect digital photographs from volunteers. The participants were paid for their participation, and their demographic information was recorded. The resulting database includes detailed information about each face, such as age, gender, and facial expression, and is structured to facilitate easy sorting and access for researchers.