Embracing deepfakes and AI-generated images in neuroscience research

被引:4
|
作者
Becker, Casey [1 ]
Laycock, Robin [1 ]
机构
[1] RMIT Univ, Melbourne, Australia
关键词
artificial neural networks; dynamic stimuli; perception; research methods; vision;
D O I
10.1111/ejn.16052
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
The rise of deepfakes and AI-generated images has raised concerns regarding their potential misuse. However, this commentary highlights the valuable opportunities these technologies offer for neuroscience research. Deepfakes deliver accessible, realistic and customisable dynamic face stimuli, while generative adversarial networks (GANs) can generate and modify diverse and high-quality static content. These advancements can enhance the variability and ecological validity of research methods and enable the creation of previously unattainable stimuli. When AI-generated images are informed by brain responses, they provide unique insights into the structure and function of visual systems. The authors argue that experimental psychologists and cognitive neuroscientists stay informed about these emerging tools and embrace their potential to advance the field of visual neuroscience.
引用
收藏
页码:2657 / 2661
页数:5
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