Understanding Decision-Making Across the Lifespan Needs Theoretical Neuroscience

TL;DR

This paper advocates for integrating modern theoretical neuroscience tools into aging research to better understand how decision-making mechanisms evolve across the lifespan.

Contribution

It highlights the gap between aging studies and theoretical neuroscience and proposes using advanced modeling techniques to develop mechanistic explanations.

Findings

Aging research has relied on simple behavioral metrics.

Recent advances in neural modeling can improve understanding of decision changes.

Integrating these approaches can lead to more mechanistic insights.

Abstract

Understanding how decision making changes across the lifespan is a central challenge for neuroscience, yet research on cognitive aging has remained largely disconnected from the theoretical and computational advances that now shape modern systems neuroscience. Over the past two decades, theoretical frameworks have transformed how we study cognition in young, healthy brains, providing principled tools to model latent decision states, neural dynamics, population codes, and interareal communication. In contrast, aging research has often relied on single metric behavioral readouts, cross sectional comparisons, and descriptive neural analyses, limiting our ability to explain fundamental differences in individual aging trajectories. This gap represents a missed opportunity because aging offers a powerful platform for testing theories of neural computation, stability, and flexibility under changing biological constraints. Here, we argue that closer integration between aging research and contemporary theoretical neuroscience can move the field beyond descriptive accounts toward more mechanistic explanations of decision making across the lifespan. To this end, we outline how recent advances in behavioral quantification, latent state modeling, dynamical systems, encoding models, representational geometry, and recurrent neural networks offer a rich theoretical toolkit for neuroscientists studying decision making across the lifespan.