scholarly journals Brain Relatively Inert Network: Taking Adult Attention Deficit Hyperactivity Disorder as an Example

2021 ◽  
Vol 15 ◽  
Author(s):  
Hua Zhang ◽  
Weiming Zeng ◽  
Jin Deng ◽  
Yuhu Shi ◽  
Le Zhao ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Functional Connectivity ◽  
Attention Deficit ◽  
Information Integration ◽  
Adult Adhd ◽  
Brain Regions ◽  
Hyperactivity Disorder ◽  
Left Brain ◽  
The Right ◽  
The Brain

Resting-state functional MRI (rs-fMRI) has been increasingly applied in the research of brain cognitive science and psychiatric diseases. However, previous studies only focused on specific activation areas of the brain, and there are few studies on the inactivation areas. This may overlook much information that explains the brain’s cognitive function. In this paper, we propose a relatively inert network (RIN) and try to explore its important role in understanding the cognitive mechanism of the brain and the study of mental diseases, using adult attention deficit hyperactivity disorder (ADHD) as an example. Here, we utilize methods based on group independent component analysis (GICA) and t-test to identify RIN and calculate its corresponding time series. Through experiments, alterations in the RIN and the corresponding activation network (AN) in adult ADHD patients are observed. And compared with those in the left brain, the activation changes in the right brain are greater. Further, when the RIN functional connectivity is introduced as a feature to classify adult ADHD patients from healthy controls (HCs), the classification accuracy rate is 12% higher than that of the original functional connectivity feature. This was also verified by testing on an independent public dataset. These findings confirm that the RIN of the brain contains much information that will probably be neglected. Moreover, this research provides an effective new means of exploring the information integration between brain regions and the diagnosis of mental illness.

scholarly journals Functional network topology of the right insula affects emotion dysregulation in hyperactive-impulsive attention-deficit/hyperactivity disorder

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tammo Viering ◽  
Pieter J. Hoekstra ◽  
Alexandra Philipsen ◽  
Jilly Naaijen ◽  
Andrea Dietrich ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Network Topology ◽  
Resting State ◽  
Latent Variable ◽  
Emotion Dysregulation ◽  
Adult Adhd ◽  
Brain Regions ◽  
Graph Analysis ◽  
Hyperactivity Disorder ◽  
The Right

AbstractEmotion dysregulation is common in attention-deficit/hyperactivity disorder (ADHD). It is highly prevalent in young adult ADHD and related to reduced well-being and social impairments. Neuroimaging studies reported neural activity changes in ADHD in brain regions associated with emotion processing and regulation. It is however unknown whether deficits in emotion regulation relate to changes in functional brain network topology in these regions. We used a combination of graph analysis and structural equation modelling (SEM) to analyze resting-state functional connectivity in 147 well-characterized young adults with ADHD and age-matched healthy controls from the NeuroIMAGE database. Emotion dysregulation was gauged with four scales obtained from questionnaires and operationalized through a latent variable derived from SEM. Graph analysis was applied to resting-state data and network topology measures were entered into SEM models to identify brain regions whose local network integration and connectedness differed between subjects and was associated with emotion dysregulation. The latent variable of emotion dysregulation was characterized by scales gauging emotional distress, emotional symptoms, conduct symptoms, and emotional lability. In individuals with ADHD characterized by prominent hyperactivity-impulsivity, the latent emotion dysregulation variable was related to an increased clustering and local efficiency of the right insula. Thus, in the presence of hyperactivity-impulsivity, clustered network formation of the right insula may underpin emotion dysregulation in young adult ADHD.

scholarly journals Brain-behavior patterns define a dimensional biotype in medication-naïve adults with attention-deficit hyperactivity disorder

2017 ◽  
Author(s):  
Hsiang-Yuan Lin ◽  
Luca Cocchi ◽  
Andrew Zalesky ◽  
Jinglei Lv ◽  
Alistair Perry ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Functional Connectivity ◽  
Attention Deficit ◽  
Resting State ◽  
Adult Adhd ◽  
Healthy Controls ◽  
Clustering Methods ◽  
Childhood Onset ◽  
Default Mode ◽  
Hyperactivity Disorder

AbstractBackgroundChildhood-onset attention-deficit hyperactivity disorder (ADHD) in adults is clinically heterogeneous and commonly presents with different patterns of cognitive deficits. It is unclear if this clinical heterogeneity expresses a dimensional or categorical difference in ADHD.MethodsWe first studied differences in functional connectivity in multi-echo resting-state functional magnetic resonance imaging (rs-fMRI) acquired from 80 medication-naïve adults with ADHD and 123 matched healthy controls. We then used canonical correlation analysis (CCA) to identify latent relationships between symptoms and patterns of altered functional connectivity (dimensional biotype) in patients. Clustering methods were implemented to test if the individual associations between resting-state brain connectivity and symptoms reflected a non-overlapping categorical biotype.ResultsAdults with ADHD showed stronger functional connectivity compared to healthy controls, predominantly between the default-mode, cingulo-opercular and subcortical networks. CCA identified a single mode of brain-symptom co-variation, corresponding to an ADHD dimensional biotype. This dimensional biotype is characterized by a unique combination of altered connectivity correlating with symptoms of hyperactivity-impulsivity, inattention, and intelligence. Clustering analyses did not support the existence of distinct categorical biotypes of adult ADHD.ConclusionsOverall, our data advance a novel finding that the reduced functional segregation between default-mode and cognitive control networks supports a clinically important dimensional biotype of childhood-onset adult ADHD. Despite the heterogeneity of its presentation, our work suggests that childhood-onset adult ADHD is a single disorder characterized by dimensional brain-symptom mediators.

Classification of Attention Deficit Hyperactivity Disorder using Variational Autoencoder

2021 ◽  
Vol 11 (2) ◽  
pp. 81-87
Author(s):  
Azurah A Samah ◽  
Siti Nurul Aqilah Ahmad ◽  
Hairudin Abdul Majid ◽  
Zuraini Ali Shah ◽  
Haslina Hashim ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Functional Connectivity ◽  
Attention Deficit ◽  
Early Stage ◽  
Region Of Interest ◽  
Brain Regions ◽  
Physical Symptoms ◽  
Medical Test ◽  
Hyperactivity Disorder ◽  
Variational Autoencoder

Attention Deficit Hyperactivity Disorder (ADHD) categorize as one of the typical neurodevelopmental and mental disorders. Over the years, researchers have identified ADHD as a complicated disorder since it is not directly tested with a standard medical test such as a blood or urine test on the early-stage diagnosis. Apart from the physical symptoms of ADHD, clinical data of ADHD patients show that most of them have learning problems. Therefore, functional Magnetic Resonance Imaging (fMRI) is considered the most suitable method to determine functional activity in the brain region to understand brain disorders of ADHD. One of the ways to diagnose ADHD is by using deep learning techniques, which can increase the accuracy of predicting ADHD using the fMRI dataset. Past attempts of classifying ADHD based on functional connectivity coefficient using the Deep Neural Network (DNN) result in 95% accuracy. As Variational Autoencoder (VAE) is the most popular in extracting high-level data, this model is applied in this study. This study aims to enhance the performance of VAE to increase the accuracy in classifying ADHD using fMRI data based on functional connectivity analysis. The preprocessed fMRI dataset is used for decomposition to find the region of interest (ROI), followed by Independent Component Analysis (ICA) that calculates the correlation between brain regions and creates functional connectivity matrices for each subject. As a result, the VAE model achieved an accuracy of 75% on classifying ADHD.

scholarly journals Study of white matter integrity in fathers of children with attention deficit hyperactivity disorder

2021 ◽  
Vol 28 (1) ◽  
Author(s):  
Heba H. ElShahawi ◽  
Safeya M. Effat ◽  
Eman M. Shorab ◽  
Hossam M. Sakr ◽  
Safaa E. Azab ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
White Matter ◽  
Attention Deficit ◽  
Adult Adhd ◽  
Neurodevelopmental Disorder ◽  
Occurrence Rate ◽  
Adhd Group ◽  
Corona Radiata ◽  
Hyperactivity Disorder ◽  
The Right

Abstract Background Attention deficit hyperactivity disorder (ADHD) is an early-onset neurodevelopmental disorder that can extend into adulthood with multiple reported neuroimaging abnormalities. The focus of this research was to assess white matter impairments in ADHD children’s fathers with and without potential adult ADHD to see if these differences are connected with the persistence of ADHD into adulthood. Results The occurrence rate of the potential adult ADHD diagnosis among fathers of children with ADHD was 60%. There were statistically significant differences between fathers with ADHD and the non-ADHD population, due to the fact that the mean FA of the left superior corona radiata and the right posterior corona radiata were lower in the ADHD group than in the non-ADHD group, while the FA of the ADHD group was significantly greater than that of the non-ADHD group in terms of the left and right anterior thalamic radiations, the right superior longitudinal fasciculus and the left anterior corona radiata. Conclusions We observed an increased prevalence of ADHD in fathers of children diagnosed with ADHD. Fathers with potential adult ADHD have a variety of white matter abnormalities that reflect the neurobiological basis of ADHD, even in sub-threshold cases. This may provide insight into the neuroanatomical locations associated with the maintenance of ADHD throughout adulthood.

Effects of the dopamine transporter gene on striatal functional connectivity in youths with attention-deficit/hyperactivity disorder

2020 ◽  
pp. 1-11 ◽  
Author(s):  
Chi-Yung Shang ◽  
Hsiang-Yuan Lin ◽  
Susan Shur-Fen Gau
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Functional Connectivity ◽  
Dopamine Transporter ◽  
Attention Deficit ◽  
Visual Memory ◽  
Memory Performance ◽  
Transporter Gene ◽  
Hyperactivity Disorder ◽  
The Right ◽  
T Haplotype

Abstract Background The dopamine transporter gene (DAT1), striatal network dysfunction, and visual memory deficits have been consistently reported to be associated with attention-deficit/hyperactivity disorder (ADHD). This study aimed to examine the effects of the DAT1 rs27048 (C)/rs429699 (T) haplotype on striatal functional connectivity and visual memory performance in youths with ADHD. Method After excluding those who had excessive head motion, a total of 96 drug-naïve youths with ADHD and 114 typically developing (TD) youths were assessed with the resting-state functional magnetic resonance imaging and the delayed matching to sample (DMS) task for visual memory. We examined the effects of ADHD, DAT1 CT haplotype, and the ADHD × CT haplotype interaction on the functional connectivity of five striatal seeds. We also correlated visual memory performance with the functional connectivity of striatal subregions, which showed significant diagnosis × genotype interactions. Results Compared with TD youths, ADHD youths showed significant hypoconnectivity of the left dorsal caudate (DC) with bilateral sensorimotor clusters. Significant diagnosis × genotype interactions were found in the connectivity between the left DC and the right sensorimotor cluster, and between the right DC and the left dorsolateral prefrontal/bilateral anterior cingulate clusters. Furthermore, the connectivity of the left DC showing significant diagnosis × genotype interactions was associated with DMS performance in youths with ADHD who carried the DAT1 CT haplotype. Conclusions A novel gene-brain-behavior association between the left DC functional connectivity and visual memory performance in ADHD youths with the DAT1 rs27048 (C)/rs429699 (T) haplotype suggests a differential effect of DAT1 genotype altering specific brain function causing neuropsychological dysfunction in ADHD.

scholarly journals Brain–behavior patterns define a dimensional biotype in medication-naïve adults with attention-deficit hyperactivity disorder

2018 ◽  
Vol 48 (14) ◽  
pp. 2399-2408 ◽  
Author(s):  
Hsiang-Yuan Lin ◽  
Luca Cocchi ◽  
Andrew Zalesky ◽  
Jinglei Lv ◽  
Alistair Perry ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Functional Connectivity ◽  
Attention Deficit ◽  
Resting State ◽  
Adult Adhd ◽  
Healthy Controls ◽  
Clustering Methods ◽  
Childhood Onset ◽  
Default Mode ◽  
Hyperactivity Disorder

AbstractBackgroundChildhood-onset attention-deficit hyperactivity disorder (ADHD) in adults is clinically heterogeneous and commonly presents with different patterns of cognitive deficits. It is unclear if this clinical heterogeneity expresses a dimensional or categorical difference in ADHD.MethodsWe first studied differences in functional connectivity in multi-echo resting-state functional magnetic resonance imaging (rs-fMRI) acquired from 80 medication-naïve adults with ADHD and 123 matched healthy controls. We then used canonical correlation analysis (CCA) to identify latent relationships between symptoms and patterns of altered functional connectivity (dimensional biotype) in patients. Clustering methods were implemented to test if the individual associations between resting-state brain connectivity and symptoms reflected a non-overlapping categorical biotype.ResultsAdults with ADHD showed stronger functional connectivity compared to healthy controls, predominantly between the default-mode, cingulo-opercular and subcortical networks. CCA identified a single mode of brain–symptom co-variation, corresponding to an ADHD dimensional biotype. This dimensional biotype is characterized by a unique combination of altered connectivity correlating with symptoms of hyperactivity-impulsivity, inattention, and intelligence. Clustering analyses did not support the existence of distinct categorical biotypes of adult ADHD.ConclusionsOverall, our data advance a novel finding that the reduced functional segregation between default-mode and cognitive control networks supports a clinically important dimensional biotype of childhood-onset adult ADHD. Despite the heterogeneity of its presentation, our work suggests that childhood-onset adult ADHD is a single disorder characterized by dimensional brain–symptom mediators.

scholarly journals Dynamic Functional Connectivity Reveals Abnormal Variability in the Amygdala Subregions of Children With Attention-Deficit/Hyperactivity Disorder

2021 ◽  
Vol 15 ◽  
Author(s):  
Yue Yang ◽  
Binrang Yang ◽  
Linlin Zhang ◽  
Gang Peng ◽  
Diangang Fang
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Functional Connectivity ◽  
Attention Deficit ◽  
Cognitive Functions ◽  
Adhd Group ◽  
Dynamic Functional Connectivity ◽  
Children With Adhd ◽  
Hyperactivity Disorder ◽  
Window Method ◽  
The Right

Objective: This study investigates whether the dynamic functional connectivity (dFC) of the amygdala subregions is altered in children with attention-deficit/hyperactivity disorder (ADHD).Methods: The dFC of the amygdala subregions was systematically calculated using a sliding time window method, for 75 children with ADHD and 20 healthy control (HC) children.Results: Compared with the HC group, the right superficial amygdala exhibited significantly higher dFC with the right prefrontal cortex, the left precuneus, and the left post-central gyrus for children in the ADHD group. The dFC of the amygdala subregions showed a negative association with the cognitive functions of children in the ADHD group.Conclusion: Functional connectivity of the amygdala subregions is more unstable among children with ADHD. In demonstrating an association between the stability of functional connectivity of the amygdala and cognitive functions, this study may contribute by providing a new direction for investigating the internal mechanism of ADHD.

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