scholarly journals Dynamic configuration of large-scale cortical networks during an inhibitory task accounts for heterogeneity in attention-deficit/hyperactivity disorder traits

2021 ◽  
Author(s):  
Jonah Kember ◽  
Carolynn Hare ◽  
Ayda Tekok-Kilic ◽  
William Marshall ◽  
Stephen M. Emrich ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Cognitive Processing ◽  
Attention Deficit ◽  
Large Scale ◽  
Compensatory Mechanism ◽  
Phase Lag ◽  
Dynamic Configuration ◽  
Dynamic Task ◽  
Hyperactivity Disorder ◽  
Response Execution

The heterogeneity of attention-deficit/hyperactivity disorder (ADHD) traits (inattention vs. hyperactivity/impulsivity) complicates diagnosis and intervention. Identifying how the configuration of large-scale functional brain networks during cognitive processing correlate with this heterogeneity could help us understand the neural mechanisms altered across ADHD presentations. Here, we recorded high-density EEG while 62 non-clinical participants (ages 18-24; 32 male) underwent an inhibitory control task (Go/No-Go). Functional EEG networks were created using sensors as nodes and across-trial phase-lag index values as edges. Using cross-validated LASSO regression, we examined whether graph-theory metrics applied to both static networks (averaged across time-windows: -500 to 0ms, 0 to500ms) and dynamic networks (temporally layered with 2ms intervals), were associated with hyperactive/impulsive and inattentive traits. Network configuration during response execution/inhibition was associated with hyperactive/impulsive (mean R2 across test sets = .20, SE = .02), but not inattentive traits. Post-stimulus results at higher frequencies (Beta, 14-29Hz; Gamma, 30-90Hz) showed the strongest association with hyperactive/impulsive traits, and predominantly reflected less burst-like integration between modules in oscillatory beta networks during execution, and increased integration/small-worldness in oscillatory gamma networks during inhibition. We interpret the beta network results as reflecting weaker integration between specialized pre-frontal and motor systems during motor response preparation, and the gamma results as reflecting a compensatory mechanism used to integrate processing between less functionally specialized networks. This research demonstrates that the neural network mechanisms underlying response execution/inhibition might be associated with hyperactive/impulsive traits, and that dynamic, task-related changes in EEG functional networks may be useful in disentangling ADHD heterogeneity.

scholarly journals Medida de las emociones en niños con TDAH: un ensayo experimental con la técnica de potenciales evocados

2017 ◽  
Vol 15 (5) ◽  
Author(s):  
Yoana Campeño Martínez ◽  
José Jesús Gázquez Linares ◽  
Víctor Santiuste Bermejo
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Lexical Decision ◽  
Cognitive Processing ◽  
Attention Deficit ◽  
Emotional Processing ◽  
Emotional Content ◽  
Hyperactivity Disorder

El trastorno por déficit de atención con hiperactividad (TDAH) es un trastorno complejo de origen neurobiológico, caracterizado tanto por sus implicaciones cognitivas como por su afectación a la base afectiva y emocional del procesamiento cognitivo. En esta investigación se han analizado las diferencias en el procesamiento cognitivo del contenido emocional, con la finalidad de evaluar las dificultades que presentan las personas con TDAH en dichas tareas, a través de la medición del contenido emocional de las palabras de una prueba de decisión léxica The attention deficit hyperactivity disorder (ADHD) is a complex neurobiological disorder origin, characterized both its cognitive implications of their involvement as the basis of affective and cognitive emotional processing. This research has analyzed the differences in cognitive processing of emotional content, with the aim of assessing the difficulties presented by persons with ADHD in these tasks, by measuring the emotional content of the words of a test lexical decision

Large-scale neocortical dynamic function and EEG: Use of theory and methods in clinical research on children with Attention Deficit Hyperactivity Disorder

2000 ◽  
Vol 23 (3) ◽  
pp. 411-411
Author(s):  
Michael Murias ◽  
James M. Swanson
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Attention Deficit ◽  
Large Scale ◽  
Dynamic Theory ◽  
Clinical Population ◽  
Hyperactivity Disorder ◽  
Age Related ◽  
Dynamic Function ◽  
Eeg Data ◽  
Regional Specificity

We used Nunez's physiologically based dynamic theory of EEG to make predictions about a clinical population of children with Attention Deficit Hyperactivity Disorder (ADHD) known to have neuronanatomical abnormalities. Analysis of high-density EEG data (long-range coherence) showed expected age-related differences and surprising regional specificity that is consistent with some of the literature in this clinical area.

Effect of Impairment on the Prevalence and Comorbidities of Attention Deficit Hyperactivity Disorder in a National Survey: Nation-Wide Prevalence and Comorbidities of ADHD

2021 ◽  
pp. 108705472110179
Author(s):  
Eyup Sabri Ercan ◽  
Gul Unsel-Bolat ◽  
Ali Evren Tufan ◽  
Sevcan Karakoc Demirkaya ◽  
Oznur Bilac ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Attention Deficit ◽  
Large Scale ◽  
Psychiatric Comorbidity ◽  
Diagnostic Interview ◽  
Adhd Group ◽  
Hyperactivity Disorder ◽  
Oppositional Defiant ◽  
Dsm Iv ◽  
Screening Scale

Objective: This study aimed to determine the prevalence and comorbidities of attention-deficit hyperactivity disorder (ADHD) by evaluating a large-scale nation-wide sample of children. Method: The inclusion criterion was being enrolled as a 2nd, 3rd, or 4th-grade student. A semi-structured diagnostic interview (K-SADS-PL), DSM-IV-Based Screening Scale for Disruptive Behavior Disorders, and assessment of impairment (by both parents and teachers) were applied to 5,842 participants. Results: The prevalence of ADHD was 19.5% without impairment and 12.4% with impairment. Both ADHD with and without impairment groups had similar psychiatric comorbidity rates except for oppositional defiant disorder (ODD) and conduct disorder (CD) diagnoses. Impairment in the ADHD group resulted in significantly higher ODD and CD diagnoses. Conclusion: Even when impairment is not described, other psychiatric disorders accompany the diagnosis of ADHD and may cause impairment in the future. Impairment in the diagnosis of ADHD significantly increases the likelihood of ODD and CD.

Sign in / Sign up

Export Citation Format

Share Document