Biology subjects

Smit, D. J. A.

Publications and source records attributed to Smit, D. J. A..

4 recordsLinked to original sources

bioRxiv2024

Understanding the development of neural abnormalities in adolescents with mental health problems: a longitudinal study

Many mental health problems are neurodevelopmental in nature and have an onset during childhood. Mental health disorders are associated with neural abnormalities, but it is unclear when those emerge and how this relates to the development of different mental health problems. We used data from the largest longitudinal neurodevelopmental study to identify the structural and functional brain changes that co-occur with the onset of six mental health problems. The results showed premorbid brain-wide abnormalities that were comparable between internalizing and different from externalizing problems, and differential neurodevelopmental trajectories for specific brain regions in 11- to 12-year-old adolescents who developed ADHD, conduct, depressive and oppositional defiant problems. These results reveal that the onset of different mental health problems co-occur with common as well as problem-specific brain abnormalities.

neuroscience↗

bioRxiv2022

Conscious perception and the role of the basal ganglia: preliminary findings from a deep brain stimulation study

Conscious perception is thought to depend on global amplification of sensory input. In recent years, the basal ganglia have been implicated in gating conscious access due to their consistent involvement in thalamocortical loops. However, much of the evidence implicating the basal ganglia in these processes in humans is correlational. The current study is a preliminary investigation in four patients to explore whether deep brain stimulation (DBS) in the basal ganglia might improve conscious perception. In our study, treatment-resistant obsessive-compulsive disorder (OCD) patients with a striatal DBS implant completed two canonical conscious perception tasks: emotion-induced blindness and backward masking. We found preliminary evidence in support of a role played by the basal ganglia in conscious perception at the behavioral level: patients performed better when stimulation was active, but we could not establish neural effects corresponding to these behavioral findings, possibly due to our small sample size. We discuss the potential implications and limitations of our study and delineate avenues for future research.

neuroscience↗

bioRxiv2020

Causal relationships between substance use and insomnia

BackgroundPoor sleep quality and insomnia have been associated with the use of tobacco, alcohol, and cannabis, but it is unclear if there is a causal link. In this Mendelian Randomization (MR) study we examine if insomnia causes substance use and/or if substance use causes insomnia. MethodsMR uses summary effect estimates from a genome-wide association study (GWAS) to create a genetic instrumental variable for a proposed exposure variable and then identifies that same genetic instrument in an outcome GWAS. With data of GWAS of insomnia, smoking (initiation, heaviness, cessation), alcohol use (drinks per week, dependence), and cannabis initiation, bi-directional causal effects were tested. Multiple sensitivity analyses were applied to assess the robustness of the findings. ResultsThere was strong evidence for positive causal effects of insomnia on all substance use phenotypes (smoking traits, alcohol dependence, cannabis initiation), except alcohol per week. The effects on alcohol dependence and cannabis initiation were attenuated after filtering out pleiotropic SNPs. In the other direction, there was strong evidence that smoking initiation increased chances of insomnia (smoking heaviness and cessation could not be tested as exposures). We found no evidence that alcohol use per week, alcohol dependence, or cannabis initiation causally affect insomnia. ConclusionsThere were unidirectional effects of insomnia on alcohol dependence and cannabis initiation, and bidirectional effects between insomnia and smoking measures. Bidirectional effects between smoking and insomnia might give rise to a vicious circle. Future research should investigate if interventions aimed at insomnia are beneficial for substance use treatment.

genetics↗

bioRxiv2018

EEG-based age-prediction models as stable and heritable indicators of brain maturational level in children and adolescents

The human brain shows remarkable development of functional brain activity from childhood to adolescence. Here, we investigated whether electroencephalogram (EEG) recordings are suitable for predicting the age of children and adolescents. Moreover, we investigated whether over-or underestimation of age was stable over longer time periods, as stable prediction error can be interpreted as reflecting individual brain maturational level. Finally, we established whether the age-prediction error was genetically determined. Three minutes eyes-closed resting state EEG data from the longitudinal EEG studies of Netherlands Twin Register (n=836) and Washington University in St. Louis (n = 702) were used at ages 5, 7, 12, 14, 16 and 18. Longitudinal data were available within childhood and adolescence. We calculated power in 1 Hz wide bins (1 to 24 Hz). Random Forest regression and Relevance Vector Machine with 6-fold cross-validation were applied. The best mean absolute prediction error was obtained with Random Forest (1.22 years). Classification of childhood vs. adolescence reached over 94% accuracy. Prediction errors were moderately to highly stable over periods of 1.5 to 2.1 years (0.53 < r < 0.74) and signifcantly affected by genetic factors (heritability between 42% and 79%). Our results show that age prediction from low-cost EEG recordings is comparable in accuracy to those obtained with MRI. Children and adolescents showed stable over- or underestimation of their age, which means that some participants have stable brain activity patterns that reflect those of an older or younger age, and could therefore reflect individual brain maturational level. This prediction error is heritable, suggesting that genes underlie maturational level of functional brain activity. We propose that age prediction based on EEG recordings can be used for tracking neurodevelopment in typically developing children, in preterm children, and in children with neurodevelopmental disorders.

neuroscience↗