January 12, 2022

Adult ADHD: How do those with the full syndrome compare with those who are subthreshold on executive functioning, and are EEGs of any use in diagnosis?

Noting that to date, no study investigated potential behavioral and neural markers in adults with subthreshold ADHD as compared to adults with full syndrome ADHD and healthy controls, the German team of researchers at the University of Tübingen out to do just that, recruiting volunteers through flyers and advertisements.

Their ADHD sample consisted of 113 adults between 18 and 60 years of age (mean age 38) who fulfilled the DSM-IV-TR criteria of ADHD and were either not on medication or a steady dose of medication over the prior two months.

Another 46 participants (also mean age 38), whose symptoms did not reach the DSM-IV-TR criteria, were assigned to the group with subthreshold ADHD.

The control sample was comprised of 42 healthy participants (mean age 37).

Individuals with schizophrenia, bipolar disorder, borderline personality disorder, epilepsy, or traumatic brain injury were excluded from the sample, as were those with current substance abuse or dependence.

All participants were German-speaking Caucasians. There were no significant differences in gender, age, education, or verbal/nonverbal intelligence among the three groups.

Participants first completed an online pre-screening, which was followed up with an interview to confirm the ADHD diagnosis.

ADHD impairs executive functions, "defined as the 'top-down' cognitive abilities for maintaining problem-solving skills to achieve future goals." The researchers explored three categories of executive functioning: 1) capacity for inhibition, "the ability to inhibit dominant, automatic, or prepotent responses when necessary- 2) ability to shift, enabling smooth switching between tasks or mental sets; and 3) ability to update, "updating and monitoring of working memory representations." Participants took a battery of neuropsychological tests to assess performance in each category.

Significant differences emerged between the group with ADHD and healthy controls in all measures except one: the STROOP Reading test. But there were no significant differences between participants suffering from subthreshold and full-syndrome ADHD. Nor were there any significant differences between those with subthreshold ADHD and healthy controls.

The researchers also recorded electroencephalograms(EEGs) for each participant. In healthy individuals, there is little to no association between resting-state EEG spectral power measures and executive functions. In individuals with ADHD, some studies have indicated increased theta-to-beta ratios, while others have found no significant differences. This study found no significant differences between the three groups.

The authors concluded, "The main results of the study can be summarized as follows: First, increased executive function deficits (in updating, inhibition, and shifting functions) could be observed in the full syndrome ADHD as compared to the healthy control group while, on the electrophysiological level, no differences in the theta to the beta ratio between these groups were found. Second, we observed only slightly impaired neuropsychological functions and no abnormal electrophysiological activity in the subthreshold ADHD sample. Taken together, our data suggest some practical uses of the assessment of objective cognitive markers but no additional value of examining electrophysiological characteristics in the diagnosis of subthreshold and full syndrome ADHD in adulthood."

They added, "These findings deeply question the value of including resting EEG markers into the diagnostic procedure and also have implications for standard neurofeedback protocols frequently used in the treatment of ADHD, where patients are trained to reduce their theta power while simultaneously increasing beta activity."

Alexander Schneider, Nina Maria Höhnle, Michael Schönenberg, "Cognitive and electrophysiological markers of the adult full syndrome and subthreshold attention-deficit/hyperactivity disorder," Journal of Psychiatric Research(2020)127,80-86,https://doi.org/10.1016/j.jpsychires.2020.05.004.

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Understanding Attention to Social Images in Children with ADHD and Autism

NEWS TUESDAY: Understanding Attention to Social Images in Children with ADHD and Autism

In the field of mental health, professionals often use a variety of tools to diagnose and understand neurodevelopmental disorders such as Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD). One such tool is the Autism Diagnostic Observation Schedule (ADOS), which is specifically designed to help diagnose autism. However, the ADOS wasn't originally intended for children who have both autism and ADHD, though this comorbidity is not uncommon.

A recent study aimed to explore how children with ADHD, autism, or both, pay attention to social images, such as faces. The study focused on using eye-tracking technology to measure where children direct their gaze when viewing pictures, and how long they look at certain parts of the image. This is important because differences in visual attention can provide insights into the nature of these disorders.

The researchers included 84 children in their study, categorized into four groups: those with ASD, those with ADHD, those with both ASD and ADHD, and neurotypical (NT) children without these conditions. During the study, children were shown social scenes from the ADOS, and their eye movements were recorded. The ADOS assessment was administered afterward. To ensure that the results were not influenced by medications, children who were on stimulant medications for ADHD were asked to pause their medication temporarily.

The results of the study showed that children with ASD, whether they also had ADHD or not, tended to spend less time looking at faces compared to children with just ADHD or NT children. The severity of autism symptoms, measured by the Social Communication Questionnaire (SCQ), was associated with reduced attention to faces. Interestingly, ADHD symptom severity, measured by Conners' Rating Scales (CRS-3), did not correlate with how children looked at faces.

These findings suggest that measuring visual attention might be a valuable addition to the assessment process for ASD, especially in cases where ADHD is also present. The study indicates that if a child with ADHD shows reduced attention to faces, it might point to additional challenges related to autism. The researchers noted that more studies with larger groups of children are needed to confirm these findings, but the results are promising. They hope that such measures could eventually enhance diagnostic processes and help in managing the complexities of cases involving comorbidity of ADHD and ASD.

This research opens up the possibility of using eye-tracking as a supplementary diagnostic tool in the assessment of autism, providing a more nuanced understanding of how attentional differences in social settings are linked to ASD and ADHD.

May 14, 2024

NEW STUDY: RASopathies Influences on Neuroanatomical Variation in Children

NEW STUDY: RASopathies Influences on Neuroanatomical Variation in Children

This study investigates how certain genetic disorders, called RASopathies, affect the structure of the brain in children. RASopathies are conditions caused by mutations in a specific signaling pathway in the body. Two common RASopathies are Noonan syndrome (NS) and neurofibromatosis type 1 (NF1), both of which are linked to a higher risk of autism spectrum disorder (ASD) and attention deficit and hyperactivity disorder (ADHD).

The researchers analyzed brain scans of children with RASopathies (91 participants) and compared them to typically developing children (74 participants). They focused on three aspects of brain structure: surface area (SA), cortical thickness (CT), and subcortical volumes.

The results showed that children with RASopathies had both similarities and differences in their brain structure compared to typically developing children. They had increased SA in certain areas of the brain, like the precentral gyrus, but decreased SA in other regions, such as the occipital regions. Additionally, they had thinner CT in the precentral gyrus. However, the effects on subcortical volumes varied between the two RASopathies: children with NS had decreased volumes in certain structures like the striatum and thalamus, while children with NF1 had increased volumes in areas like the hippocampus, amygdala, and thalamus.

Overall, this study highlights how RASopathies can impact the development of the brain in children. The shared effects on SA and CT suggest a common influence of RASopathies on brain development, which could be important for developing targeted treatments in the future.

In summary, understanding how these genetic disorders affect the brain's structure can help researchers and healthcare professionals develop better treatments for affected children.

April 30, 2024

News Tuesday: Integrating Cognition and Eye Movement

Integrating Cognitive Factors and Eye Movement Data in Reading Predictive Models for Children with Dyslexia and ADHD-I

In a recent study, researchers delved into the complex interplay of cognitive processes and eye movements in children with dyslexia and Attention-Deficit/Hyperactivity Disorder. Their findings shed light on predictive models for reading outcomes in these children compared to typical readers.

The study involved 59 children: 19 typical readers, 21 with ADHD, and 19 with developmental dyslexia (DD), all in the 4th grade and around 9 years old on average. Each group underwent thorough neuropsychological and linguistic assessments to understand their psycholinguistic profiles.

During the study, participants engaged in a silent reading task where the text underwent lexical manipulation. Researchers then analyzed eye movement data alongside cognitive factors like memory, attention, and visual processes.

Using multinomial logistic regression, the researchers evaluated predictive models based on three key measures: a linguistic model focusing on phonological awareness, rapid naming, and reading fluency; a cognitive neuropsychological model incorporating memory, attention, and visual processes; and an additive model combining lexical word properties with eye-tracking data, specifically examining word frequency and length effects.

By integrating eye movement data with cognitive factors, the researchers enhanced their ability to predict the development of dyslexia or ADHD, in comparison to typically developing readers. This approach significantly improved the accuracy of predicting reading outcomes in children with learning disabilities.

These findings have profound implications for understanding and addressing reading challenges in children. By considering both cognitive processes and eye movement patterns, educators and clinicians can develop more effective interventions tailored to the specific needs of children with dyslexia and ADHD.

April 30, 2024