Adolescents with depression exhibit negative biases in autobiographical memory with detrimental consequences for their self-concept and well-being. Investigating how adolescents relive positive autobiographical memories and activate the underlying neural networks could reveal mechanisms that drive such biases. This study investigated neural networks when reliving positive and neutral memories, and how neural activity is modulated by valence and vividness in adolescents with and without depression.

These data represent autobiographical memory characteristics as well as neural networks when reliving positive and neutral autobiographical memories in adolescents with and without depression, obtained via event-related independent component analysis (eICA). Adolescents (N = 69; n = 17 with depression) retrieved positive and neutral autobiographical memories. On a separate day, they relived these memories during fMRI scanning, and reported on pleasantness and vividness after reliving each memory. We used eICA, a multivariate, data-driven approach, to characterize neural networks supporting autobiographical recollection.

The de-identified processed data, analysis scripts and materials for this study are available on DataverseNL (https://doi.org/10.34894/DHRHI1). The group-level MRI data are available on Neurovault (https://neurovault.org/collections/14102/). We are unable to make the raw data publicly available, given that participants not explicitly consented for sharing their (coded) raw data on a public repository. To obtain these data, ethics committee approval and a data sharing agreement would be required. For any questions or additional material, please contact the corresponding author.