# Dynamic modeling in neurocognitive frameworks of childhood ADHD: a review of inhibitory control and reward systems

## TL;DR

This review explores how ADHD in children involves problems with impulse control and reward processing, using new dynamic models to better understand brain mechanisms.

## Contribution

The paper introduces dynamic modeling approaches to traditional ADHD neurocognitive frameworks, revealing novel neurodynamic mechanisms.

## Key findings

- Children with ADHD show impairments in inhibitory control and reward processing.
- Dynamic models reveal altered brain states and adaptive response strategies in ADHD.
- Pharmacological studies show how medication modulates inhibitory and reward systems.

## Abstract

Cognitive models of attention deficit hyperactivity disorder (ADHD) have traditionally centered on deficits in inhibitory control and motivation. A substantial body of empirical research supports impairments in both domains: children with ADHD exhibit elevated commission error rates, prolonged stop-signal reaction time, and a strong preference for smaller immediate rewards over larger delayed ones. In the first part of this review, we synthesize key findings from behavioral and task-state functional neuroimaging studies that characterize these deficits, highlighting how deficits in inhibitory control and motivation/reward systems manifest across tasks and contexts. We further examine evidence on the interplay between the two systems and how their interaction is altered in children with ADHD. In the second part, we introduce recent advances in cognitive and computational neuroscience that extend classic neurocognitive models by incorporating dynamic perspectives. Specifically, we describe the dynamic dual-control framework, which distinguishes between proactive and reactive inhibitory control, and highlight dynamics of trial-by-trial adaptive response strategy adjustment. We also review emerging computational models that can identify latent brain states and their evolution during task performance, revealing novel neurodynamic mechanisms that may underlie cognitive instability in ADHD. Additionally, we discuss pharmacological studies that shed light on how the inhibitory control and motivation/reward systems are modulated by medication. Finally, we address current limitations and challenges in ADHD research, with a particular focus on task-state functional neuroimaging, and propose future directions for advancing the field. By integrating dynamic modeling approaches with established neurocognitive frameworks, this review aims to deepen our understanding of the brain mechanisms underlying ADHD and to inform the development of more precise and effective interventions.