Abnormal Reactivity of Brain Oscillations to Visual Search Target in Children With Attention-Deficit/Hyperactivity Disorder

A Network Approach to Understanding the Role of Executive Functioning and Alpha Oscillations in Inattention and Hyperactivity-Impulsivity Symptoms of ADHD

OBJECTIVE

ADHD is a prevalent neurodevelopmental disorder characterized by symptoms of inattention and hyperactivity-impulsivity. Impairments in executive functioning (EF) are central to models of ADHD, while alpha-band spectral power event-related decreases (ERD) have emerged as a putative electroencephalography (EEG) biomarker of EF in ADHD. Little is known about the roles of EF and alpha ERD and their interactions with symptoms of ADHD.

METHOD

We estimated network models of ADHD symptoms and integrated alpha ERD measures into the symptom network.

RESULTS

EF emerges as a bridge network node connecting alpha ERD and the hyperactivity/impulsivity and inattention symptoms. We found that EF most closely relates to a subset of symptoms, namely the motoric symptoms, "seat" (difficulty staying seated), and "runs" (running or climbing excessively).

CONCLUSIONS

EF functions as a bridge node connecting alpha ERD and the ADHD symptom network. Motoric-type symptoms and EF deficits may constitute important nodes in the interplay between behavior/symptoms, cognition, and neurophysiological markers of ADHD.

Multisensory Enhancement of Cognitive Control over Working Memory Capture of Attention in Children with ADHD

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in school-age children. Although it has been well documented that children with ADHD are associated with impairment of executive functions including working memory (WM) and inhibitory control, there is not yet a consensus as to the relationship between ADHD and memory-driven attentional capture (i.e., representations in WM bias attention toward the WM-matched distractors). The present study herein examined whether children with ADHD have sufficient cognitive control to modulate memory-driven attentional capture. 73 school-age children (36 with ADHD and 37 matched typically developing (TD) children) were instructed to perform a visual search task while actively maintaining an item in WM. In such a paradigm, the modality and the validity of the memory sample were manipulated. The results showed that under the visual WM encoding condition, no memory-driven attentional capture was observed in TD children, but significant capture was found in children with ADHD. In addition, under the audiovisual WM encoding condition, memory-matched distractors did not capture the attention of both groups. The results indicate a deficit of cognitive control over memory-driven attentional capture in children with ADHD, which can be improved by multisensory WM encoding. These findings enrich the relationship between ADHD and cognitive control and provide new insight into the influence of cross-modal processing on attentional guidance.

Information-based multivariate decoding reveals imprecise neural encoding in children with attention deficit hyperactivity disorder during visual selective attention

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in school-age children. Attentional orientation is a potential clinical diagnostic marker to aid in the early diagnosis of ADHD. However, the underlying pathophysiological substrates of impaired attentional orienting in childhood ADHD remain unclear. Electroencephalography (EEG) was measured in 135 school-age children (70 with childhood ADHD and 65 matched typically developing children) to directly investigate target localization during spatial selective attention through univariate ERP analysis and information-based multivariate pattern machine learning analysis. Compared with children with typical development, a smaller N2pc was found in the ADHD group through univariate ERP analysis. Children with ADHD showed a lower parieto-occipital multivariate decoding accuracy approximately 240-340 ms after visual search onset, which predicts a slower reaction time and larger standard deviation of reaction time. Furthermore, a significant correlation was found between N2pc and decoding accuracy in typically developing children but not in children with ADHD. These observations reveal that impaired attentional orienting in ADHD may be due to inefficient neural encoding responses. By using a personalized information-based multivariate machine learning approach, we have advanced the understanding of cognitive deficits in neurodevelopmental disorders. Our study provides potential research directions for the early diagnosis and optimization of personalized intervention in children with ADHD.