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Towards Understanding Human Functional Brain Development with Explainable Artificial Intelligence: Challenges and Perspectives

Andreu-Perez, Javier and Hagras, Hani and Kiani, Mehrin and Rigato, Silvia and Filippetti, Maria Laura (2022) 'Towards Understanding Human Functional Brain Development with Explainable Artificial Intelligence: Challenges and Perspectives.' IEEE Computational Intelligence Magazine, 17 (1). pp. 16-33. ISSN 1556-603X

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Abstract

The last decades have seen significant advancements in non-invasive neuroimaging technologies that have been increasingly adopted to examine human brain development. However, these improvements have not necessarily been followed by more sophisticated data analysis measures that are able to explain the mechanisms underlying functional brain development. For example, the shift from univariate (single area in the brain) to multivariate (multiple areas in brain) analysis paradigms is of significance as it allows investigations into the interactions between different brain regions. However, despite the potential of multivariate analysis to shed light on the interactions between developing brain regions, artificial intelligence (AI) techniques applied render the analysis non-explainable. The purpose of this paper is to understand the extent to which current state-of-the-art AI techniques can inform functional brain development. In addition, a review of which AI techniques are more likely to explain their learning based on the processes of brain development as defined by developmental cognitive neuroscience (DCN) frameworks is also undertaken. This work also proposes that eXplainable AI (XAI) may provide viable methods to investigate functional brain development as hypothesised by DCN frameworks.

Item Type: Article
Uncontrolled Keywords: q-bio.NC; cs.AI
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Faculty of Science and Health > Psychology, Department of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 26 Jan 2022 16:15
Last Modified: 19 Apr 2022 09:13
URI: http://repository.essex.ac.uk/id/eprint/31930

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