Journal article
Brain fingerprinting: A promising future application for predicting mental illness
Futures, Vol.152, pp.1-9
2023
Appears in Thompson Institute Research Collection
Abstract
Given the significant and increasing mental health challenges faced by society, a new vision for the future of mental health is greatly needed. The determination of individual uniqueness of brain activity - known as ‘brain fingerprinting’ – shows great promise as a predictor of mental health outcomes, and thus could be the future of personalised mental health care. In this paper, we describe the importance of brain changes in adolescence and how by applying artificial intelligence-based predictive models we can harness the complexity of the underlying neurobiology to proactively address emerging mental health problems. We also describe the issues that the future application of brain uniqueness tracking (or similar) depends on, to provide the greatest value for society. We explore the potential effects of external systemic trends on mental health futures and various scenarios that involve future applications of brain fingerprinting, including a range of potential unintended consequences of this proposed predictive technology and how anticipatory governance can help mitigate such outcomes. Our key recommendation for future pre-emptive/preventative mental healthcare is that all young people (aged ∼12 years) are provided with the opportunity to undertake a free brain scan that could be utilised to predict mental health risks.
Details
- Title
- Brain fingerprinting: A promising future application for predicting mental illness
- Authors
- Daniel F. Hermens (Corresponding Author) - University of the Sunshine Coast, Queensland, Thompson InstituteColin Russo (Author) - Engaging FuturesZack Shan (Author) - University of the Sunshine Coast, Queensland, Thompson InstituteJim Lagopoulos (Author) - University of the Sunshine Coast, Queensland, Thompson Institute
- Publication details
- Futures, Vol.152, pp.1-9
- Publisher
- Elsevier Ltd
- Date published
- 2023
- DOI
- 10.1016/j.futures.2023.103211
- ISSN
- 1873-6378
- Organisation Unit
- School of Social Sciences - Legacy; Thompson Institute
- Language
- English
- Record Identifier
- 99739154602621
- Output Type
- Journal article
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