October 5, 2023
It sounds like science fiction, but scientists have been testing computerized methods to train the brains of ADHD people to reduce both ADHD symptoms and cognitive deficits such as difficulties with memory or attention.
Two main approaches have been used: cognitive training and neurofeedback. Cognitive training methods ask patients to practice tasks aimed at teaching specific skills, such as retaining information in memory or inhibiting impulsive responses.
Currently, results from ADHD brain studies suggest that the ADHD brain is not very different from the non-ADHD brain, but that ADHD leads to small differences in the structure, organization, and functioning of the brain. The idea behind cognitive training is that the brain can be reorganized to accomplish tasks through a structured learning process. Cognitive retraining helps people who have suffered brain damage, so it was logical to think it might help the types of brain differences seen in ADHD people. Several software packages have been created to deliver cognitive training sessions to ADHD people.
Neurofeedback was applied to ADHD after it had been observed, in many studies, that people with ADHD have unusual brain waves as measured by the electroencephalogram (EEG). We believe that these unusual brain waves are caused by the different ways that the ADHD brain processes information. Because these differences lead to problems with memory, attention, inhibiting responses, and other areas of cognition and behavior, it was believed that normalizing the brain waves might reduce ADHD symptoms.
In a neurofeedback session, patients sit with a computer that reads their brain waves via wires connected to their heads. The patient is asked to do a task on the computer that is known to produce a specific type of brain wave. The computer gives feedback via sound or a visual on the computer screen that tells the patient how 'normal' their brainwaves are. By modifying their behavior, patients learn to change their brain waves. The method is called neurofeedback because it gives patients direct feedback about how their brains are processing information.
Both cognitive training and neurofeedback have been extensively studied. If you've been reading my blogs about ADHD, you know that I play by the rules of evidence-based medicine. My view is that the only way to be sure that a treatment works is to see what researchers have published in scientific journals. The highest level of evidence is a meta-analysis of randomized controlled clinical trials. This ensures that many rigorous studies have been conducted and summarized with a sophisticated mathematical method.
Although both cognitive training and neurofeedback are rational methods based on good science, meta-analyses suggest that they do not help reduce ADHD symptoms. They may be helpful for specific problems, such as problems with memory, but more work is needed to be certain if that is true. The future may bring better news about these methods if they are modified and become more effective. You can learn more about non-pharmacologic treatment for ADHD from a book I recently edited: Faraone, S. V. &Antshel, K. M. (2014). ADHD: Non-Pharmacologic Interventions. Child Adolesc Psychiatr Clin N Am 23, xiii-xiv.
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.
The Study Setup
The researchers recruited children aged 6-12 years diagnosed with ASD and/or ADHD, along with their non-ASD/ADHD siblings and the unrelated non-ASD/ADHD volunteers. The diagnoses were confirmed using standardized assessments like the Autism Diagnostic Observation Schedule-2 (ADOS-2). The study looked at gut microbial diversity using advanced DNA extraction and sequencing techniques, comparing alpha-diversity indices (which reflect the variety and evenness of microbial species within each gut sample) across different groups. They also assessed dietary diversity through standardized questionnaires.
Key Findings
The study included 98 subjects, comprising children with ASD, ADHD, both ASD and ADHD, their non-ASD/ADHD siblings, and the unrelated controls. Here's what they discovered:
What Does This Mean?
The study highlights intriguing connections between gut microbiota and neurodevelopmental disorders like ASD and ADHD. The lower gut microbial diversity observed in children with ASD points towards potential links between gut health and the pathophysiology of ASD. Understanding these connections is crucial for developing targeted therapeutic interventions.
Implications and Future Directions
This research underscores the importance of considering gut microbiota in the context of neurodevelopmental disorders. Moving forward, future studies should account for factors like co-occurrence of ASD and ADHD, as well as carefully control for dietary influences. This will help unravel the complex interplay between gut microbiota, diet, and neurodevelopmental disorders, paving the way for innovative treatments and interventions.
In summary, studies like this shed light on the intricate relationship between our gut health, diet, and brain function. By unraveling these connections, researchers are opening new avenues for understanding and potentially treating conditions like ASD and ADHD.
A commonly reported risk associated with ADHD medication is reduced growth in height. But studies to date have generally not adequately described or measured possible confounders, such as genetic factors, prenatal factors, or socioeconomic factors. What if ADHD were associated with reduced height even in the absence of medications?
An international study team explored this question by performing a nationwide population study comparing data from before (1968-1991) and after (1992-2020) the adoption of stimulant therapy for ADHD in Sweden.
The country’s single-payer health insurance system that connects patient records with all other national registers through unique personal identification numbers makes such analysis possible. Sweden also has military service conscription, which records the heights of 18-year-old males.
The participants were all 14,268 Swedish males with a diagnosis of ADHD who were drafted into military service at any time from 1968 through 2020.
Up to five non-ADHD controls were identified for each ADHD case, matched by sex (they had to be male), birth year, and county. The total number of controls was 71,339.
Among 34,586 participants in the period before adoption of stimulant medications (1968-1991), those diagnosed with ADHD had roughly 30% greater odds of being shorter than normal (166-172 vs. 173-185 cm) than typically developing controls. That dropped to 20% greater odds among the 34,714 participants in the cohort following adoption of stimulant medications.
The odds of those diagnosed with ADHD being much shorter than normal (150-165 vs. 173-185 cm) remained identical (about 55% greater) among the almost 30,000 participants in both cohorts.
In other words, there was no increase in the odds of ADHD individuals being shorter than normal after adoption of stimulant therapy in Sweden compared with before such adoption.
Furthermore, after adjusting for known confounders, including birth weight, inflammatory bowel disease, celiac disease, hypothyroidism, anxiety disorders, depression, substance use disorder, and highest parental education, the odds of those diagnosed with ADHD being shorter than normal or much shorter than normal in the 1992-2020 cohort dropped to roughly 10% and 30% greater, respectively.
Could it be the disorder itself rather than stimulant treatment that is associated with reduced height in individuals diagnosed with ADHD?
To address effects of environmental and familial/genetic confounding, the team then compared the entire cohort of males diagnosed with ADHD from 1968 through 2020 with typically developing male relatives, ranging from first cousins to full siblings.
Among full siblings, the odds of those with ADHD diagnoses being shorter (over 90,000 participants) or much shorter (over 77,000 participants) were a statistically significant 14% and 18%, respectively.
The authors concluded, “Our findings suggest that ADHD is associated with shorter height. On a population level, this association was present both before and after ADHD-medications were available in Sweden. The association between ADHD and height was partly explained by prenatal factors, psychiatric comorbidity, low SES [socioeconomic status] and a shared familial liability for ADHD.”
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