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6 result(s) for "Groefsema, Martine"
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Correlation between brain function and ADHD symptom changes in children with ADHD following a few-foods diet: an open-label intervention trial
Research into the effect of nutrition on attention-deficit hyperactivity disorder (ADHD) in children has shown that the few-foods diet (FFD) substantially decreases ADHD symptoms in 60% of children. However, the underlying mechanism is unknown. In this open-label nutritional intervention study we investigated whether behavioural changes after following an FFD are associated with changes in brain function during inhibitory control in 79 boys with ADHD, aged 8–10 years. Parents completed the ADHD Rating Scale before (t1) and after the FFD (t2). Functional magnetic resonance imaging (fMRI) scans were acquired during a stop-signal task at t1 and t2, and initial subject-level analyses were done blinded for ARS scores. Fifty (63%) participants were diet responders, showing a decrease of ADHD symptoms of at least 40%. Fifty-three children had fMRI scans of sufficient quality for further analysis. Region-of-interest analyses demonstrated that brain activation in regions implicated in the stop-signal task was not associated with ADHD symptom change. However, whole-brain analyses revealed a correlation between ADHD symptom decrease and increased precuneus activation (p FWE(cluster)  = 0.015 for StopSuccess > Go trials and p FWE(cluster)  < 0.001 for StopSuccess > StopFail trials). These results provide evidence for a neurocognitive mechanism underlying the efficacy of a few-foods diet in children with ADHD.
Predicting future drinking among young adults: using ensemble machine-learning to combine MRI with psychometrics and behaviour
Background: While most research into predictors of problematic alcohol use has focused on adolescence, young adults are also at elevated risk, and differ from adolescents and adults in terms of exposure to alcohol and neurodevelopment. Here we examined predictors of alcohol use among young adults at a 1-year follow-up using a broad predictive modelling approach. Methods: Data in four modalities were included from 128 men aged between 18 and 25 years; functional MRI regions-of-interest from 1) a beer-incentive delay task, and 2) a social alcohol cue-exposure task, 3) grey matter data, and 4) non-neuroimaging data (i.e. psychometric and behavioural). These modalities were combined into an ensemble model to predict follow-up Alcohol Use Disorder Identification (AUDIT) scores, and were tested separately for their contribution. To reveal specificity for the prediction of future AUDIT scores, the same analyses were carried out for current AUDIT score. Results: The ensemble resulted in a more accurate estimation of follow-up AUDIT score than any single modality. Only removal of the social alcohol cue-exposure task and of the non-neuroimaging data significantly worsened predictions. Reporting to need a drink in the morning to start the day was the strongest unique predictor of future drinking along with anterior cingulate cortex and cerebellar activity. Conclusions: Alcohol-related task fMRI activity is a valuable predictor for future drinking among young adults alongside non-neuroimaging variables. Multi-modal prediction models best predict future drinking among young adults and may play an important part in the move towards individualized treatment and prevention efforts.
Cue-reactivity and approach bias to social alcohol cues and their association with drinking in a social setting in young adults
Alcohol is mainly consumed in social settings, in which people often adapt their drinking behavior to that of others, also called imitation of drinking. Yet, it remains unclear what drives this drinking in a social setting. In this study, we expected to see stronger brain and behavioral responses to social compared to non-social alcohol cues, that would be associated with actual drinking in a social setting. The sample consisted of 153 beer-drinking males, aged 18-25 years. Brain responses to social alcohol cues were measured during an alcohol cue exposure task in the scanner. Behavioral responses to social alcohol cues were measured using a stimulus-response compatibility task, providing an index of approach bias towards these cues. Drinking in a social setting was measured in a Bar-Lab setting. Specific brain responses to social alcohol cues were observed in the bilateral superior temporal sulcus and the left inferior parietal lobe. There was no approach bias towards social alcohol cues specifically, however, we did find an approach bias towards alcohol (versus soda) cues in general. Brain responses and approach bias towards social alcohol cues were unrelated and not associated with drinking, measured in the Bar-Lab. Thus, we found no support for a relation between drinking in a social setting on the one hand, and brain cue-reactivity or behavioral approach biases to social alcohol cues on the other hand. This suggests that, in contrast to our hypothesis, drinking in a social setting may not be driven by brain or behavioral responses to social alcohol cues. Footnotes * https://neurovault.org/collections/IVCNOFBQ/
Brain responses to anticipating and receiving beer: Comparing light, at-risk, and dependent alcohol users
Background: Impaired brain processing of alcohol-related rewards has been suggested to play a central role in alcohol use disorder. Yet, evidence remains inconsistent, and mainly originates from studies in which participants passively observe alcohol cues or taste alcohol. Here we designed a protocol in which beer consumption was predicted by incentive cues and contingent on instrumental action, closer to real life situations. We predicted that anticipating and receiving beer (compared with water) would elicit activity in the brain reward network, and that this activity would correlate with drinking level across participants. Methods: The sample consisted of 150 beer-drinking males, aged 18-25 years. Three groups were defined based on AUDIT scores: light drinkers (n=40), at-risk drinkers (n=63), and dependent drinkers (n=47). fMRI measures were obtained while participants engaged in the Beer Incentive Delay task involving beer- and water-predicting cues, followed by real sips of beer or water. Results: During anticipation, outcome notification and delivery of beer compared with water, higher activity was found in a reward-related brain network including the medial prefrontal cortex, orbitofrontal cortex and amygdala. Yet, no activity was observed in the striatum, and no differences were found between the groups. Conclusions: Our results reveal that anticipating, obtaining and tasting beer activates parts of the brain reward network, but that these brain responses do not differentiate between different drinking levels. We speculate that other factors, such as cognitive control or sensitivity to social context, may be more discriminant predictors of drinking behaviour in young adults.
A structural MRI marker predicts individual differences in impulsivity and classifies patients with behavioral-variant frontotemporal dementia from matched controls
Impulsivity and higher preference for sooner over later rewards (i.e., delay discounting) are transdiagnostic markers of many psychiatric and neurodegenerative disorders. Yet, their neurobiological basis is still debated. Here, we aimed at 1) identifying a structural MRI signature of delay discounting in healthy adults, and 2) validating it in patients with behavioral variant frontotemporal dementia (bvFTD)-a neurodegenerative disease characterized by high impulsivity. We used a machine-learning algorithm to predict individual differences in delay discounting rates based on whole-brain grey matter density maps in healthy male adults (Study 1, N=117). This resulted in a cross-validated prediction-outcome correlation of =0.35 ( =0.0028). We tested the validity of this brain signature in an independent sample of 166 healthy adults (Study 2) and its clinical relevance in 24 bvFTD patients and 18 matched controls (Study 3). In Study 2, responses of the brain signature did not correlate significantly with discounting rates, but in both Studies 1 and 2, they correlated with psychometric measures of trait urgency-a measure of impulsivity. In Study 3, brain-based predictions correlated with discounting rates, separated bvFTD patients from controls with 81% accuracy, and were associated with the severity of disinhibition among patients. Our results suggest a new structural brain pattern-the Structural Impulsivity Signature (SIS)-which predicts individual differences in impulsivity from whole-brain structure, albeit with small-to-moderate effect sizes. It provides a new brain target that can be tested in future studies to assess its diagnostic value in bvFTD and other neurodegenerative and psychiatric conditions characterized by high impulsivity.