Objective: Attention deficit/hyperactivity disorder (ADHD) is a complex disorder, characterized by different presentations with distinct cognitive and neurobiological characterizations. Here we aimed to investigate whether sleep spindle activity, which has been associated with brain maturation, may be a potential biomarker able to differentiate ADHD presentations in school-aged children (7–11 years). Method: Spindle characteristics were extracted from overnight polysomnography in 74 children (27 ADHD-Inattentive [IQ = 96.04], 25 ADHD-hyperactive/impulsive [IQ = 98.9], and 22 ADHD-combined [IQ = 96.1]). We obtained data of the frontal (Fz) and parietal (Pz) derivations using a validated spindle detection algorithm. Results: Children with ADHD showed a higher number and density of slow compared to fast spindles which were more frequent in frontal area. No differences were observed among ADHD presentations for any spindle characteristics. Spindle frequency and density increased with age, indicating an age-dependent maturation of different sleep spindles. However, no associations between IQ and spindle characteristics were observed. Conclusions: In children with ADHD the spindle characteristics evolve with age but sleep spindle activity does not seem to be a valid biomarker of ADHD phenotypes or general cognitive ability.

Characteristics of sleep spindles in school-aged children with attention-deficit/hyperactivity disorder

Cellini N.
Formal Analysis
;
2021

Abstract

Objective: Attention deficit/hyperactivity disorder (ADHD) is a complex disorder, characterized by different presentations with distinct cognitive and neurobiological characterizations. Here we aimed to investigate whether sleep spindle activity, which has been associated with brain maturation, may be a potential biomarker able to differentiate ADHD presentations in school-aged children (7–11 years). Method: Spindle characteristics were extracted from overnight polysomnography in 74 children (27 ADHD-Inattentive [IQ = 96.04], 25 ADHD-hyperactive/impulsive [IQ = 98.9], and 22 ADHD-combined [IQ = 96.1]). We obtained data of the frontal (Fz) and parietal (Pz) derivations using a validated spindle detection algorithm. Results: Children with ADHD showed a higher number and density of slow compared to fast spindles which were more frequent in frontal area. No differences were observed among ADHD presentations for any spindle characteristics. Spindle frequency and density increased with age, indicating an age-dependent maturation of different sleep spindles. However, no associations between IQ and spindle characteristics were observed. Conclusions: In children with ADHD the spindle characteristics evolve with age but sleep spindle activity does not seem to be a valid biomarker of ADHD phenotypes or general cognitive ability.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3382265
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