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A Novel Explainability Approach for Technology-Driven Translational Research on Brain Aging.

Adam Turnbull^1,2, Robert M Kaplan³, Ehsan Adeli^1,3,4

¹Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.

Journal of Alzheimer'S Disease : JAD

|June 27, 2022

Summary

Technology can help predict, monitor, and modify brain aging to maintain functional independence. Incorporating explainability principles like causality and fairness early in development is crucial for effective brain aging technology.

Keywords:

Artificial intelligence brain aging explainability technology translational research

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Published on: November 14, 2017

Area of Science:

Neuroscience
Biotechnology
Gerontology

Background:

Brain aging impairs functional independence, necessitating technological solutions.
Translational research faces challenges balancing mechanistic precision with clinical relevance in brain aging technology.
Existing brain aging technologies require improved integration of pathophysiology and functional outcomes.

Purpose of the Study:

To propose a framework for developing brain aging technology that bridges mechanistic understanding and clinical utility.
To advocate for the integration of explainability desiderata (causality, informativeness, transferability, fairness) into early-stage technology design.
To illustrate a novel approach using peripheral neuroplasticity markers.

Main Methods:

Synthesizing mechanistic, translational, and clinical research frameworks.
Developing technology-driven brain aging research methodologies.
Applying electrocardiography-based peripheral neuroplasticity markers as a case study.

Main Results:

A proposed framework for brain aging technology development emphasizing explainability.
Demonstration of how peripheral markers can inform brain aging technology.
Highlighting the importance of causality, informativeness, transferability, and fairness.

Conclusions:

Integrating explainability into early-stage research will enhance the development of effective brain aging technologies.
This approach facilitates the link between brain pathophysiology and functional independence in translational research.
The proposed framework promotes the adoption of clinically relevant and mechanistically sound brain aging solutions.