Behavioral y Neurofunctional Profiles of Delay Aversion en Children with Attention-Déficit Hyperactivity Disorder

Abstract

[eng] Despete sustancial efforts en un rasgo cognitivo heterogeneity en ADHD, la examinación de motivación variabilidad, particularmente delay aversion, remains limited. Este estudio lleva a la identificación homogénea delay-averse profiles en personas con ADHD para un motivador deficits motivador. Delay-averse profiles estaban examinadas en el clinically well-characterized sample of 43 children with ADHD and 47 control participantes usando cluster analyses donde tienen experiential delay discounting task. External validation analyses incluyen parientes' and teachers' clínicas ratings, and fNIRS-based resting-state functional connectivity (rsFC) from the frontoparietal (FPN) and the default mode (DMN) networks. En five-profile solution best fit the data. Two clusters, labeled Conventional and Conventional-steeper, exhibidos en conventional reward discount with increased delay but differed in the discounting slope. Three clusters demonstrated altered discounting: Steep discounting (abrupto devaluation of the reward), Shallow discounting (shallow discounting), Zero discounting (no devaluation across delay durations). 77.78% ADHD-C clusters clustered in steep discounting profiles, while 41.67% ADHD-IN children estaban en Shallow and Zero profiles, showing a significante disparity en la distribución de categorías presentaciones. External validation showed no differences in clinical ratings. However, clusters show Zero and Shallow discounting demonstrated hypoconnectivity within and between FPN and DMN nodos. Delay aversion in ADHD spans a continuum from decreased to increased discounting rather than being solely defined by steeper discounting. Las findings alcanzan la relevancia de las dimensiones adaptadas al capturar ADHD's motivacional heterogeneity e identificando distinto neurobiological sustratos, con implicaciones para improvisar diagnósticos de protocolos e intervenciones de estrategias mediante la incorporación de behavioral measures of reward processing.