Quantifying patterns of brain activity: Distinguishing unaffected siblings from participants with ADHD and healthy individuals

Wolfers, Thomas; Rooij, Daan van; Oosterlaan, Jaap; Heslenfeld, Dirk J.; Hartman, Catharina A.; Hoekstra, Pieter J.; Beckmann, Christian F.; Franke, Barbara; Buitelaar, Jan K.; Marquand, André F.

doi:10.1016/j.nicl.2016.06.020

Cited by 17 publications

(22 citation statements)

References 58 publications

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“…Importantly our findings are in line with the literature on ADHD. Unmedicated patients with ADHD show increased odour detection sesnitivity compared to healthy controls 19 , 50 together with hightened motor impulsivity levels, evidenced by poor performance on the SST 51 , 52 . Interestingly, medication with methylphenidate, known to influence dopaminergic transmission, normalizes odour sensitivity 19 and simultaneously, improves response inhibition in children with ADHD 53 .…”

Section: Discussionmentioning

confidence: 98%

Decreased olfactory discrimination is associated with impulsivity in healthy volunteers

Herman

Critchley

Duka

2018

Sci Rep

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In clinical populations, olfactory abilities parallel executive function, implicating shared neuroanatomical substrates within the ventral prefrontal cortex. In healthy individuals, the relationship between olfaction and personality traits or certain cognitive and behavioural characteristics remains unexplored. We therefore tested if olfactory function is associated with trait and behavioural impulsivity in nonclinical individuals. Eighty-three healthy volunteers (50 females) underwent quantitative assessment of olfactory function (odour detection threshold, discrimination, and identification). Each participant was rated for trait impulsivity index using the Barratt Impulsiveness Scale and performed a battery of tasks to assess behavioural impulsivity (Stop Signal Task, SST; Information Sampling Task, IST; Delay Discounting). Lower odour discrimination predicted high ratings in non-planning impulsivity (Barratt Non-Planning impulsivity subscale); both, lower odour discrimination and detection threshold predicted low inhibitory control (SST; increased motor impulsivity). These findings extend clinical observations to support the hypothesis that deficits in olfactory ability are linked to impulsive tendencies within the healthy population. In particular, the relationship between olfactory abilities and behavioural inhibitory control (in the SST) reinforces evidence for functional overlap between neural networks involved in both processes. These findings may usefully inform the stratification of people at risk of impulse-control-related problems and support planning early clinical interventions.

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Section: Discussionmentioning

confidence: 98%

Decreased olfactory discrimination is associated with impulsivity in healthy volunteers

Herman

Critchley

Duka

2018

Sci Rep

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“…A prime example, the ADHD-200 competition, in which ADHD was predicted on the basis of different brain read-outs, showed predictions that did not exceed 60% accuracy (The ADHD 200 consortium, 2012). These outcomes were replicated in follow-up research, summarized in different reviews and studies using all kinds of brain imaging readouts (Sabuncu and Konukoglu, 2014; Wolfers et al ., 2015 a , 2016, 2017). Here, we used mass-univariate predictions, similar to voxel-based morphometry.…”

Section: Discussionmentioning

confidence: 99%

“…Attention-deficit/hyperactivity disorder (ADHD) is a prevalent and impairing neurodevelopmental disorder, which persists into adulthood in a substantial part of the patients (Simon et al ., 2009). Reliable group differences between healthy individuals and those with ADHD have been established for various biological readouts (Bush et al ., 2005; Seidman et al ., 2005; Valera et al ., 2007; Cortese and Castellanos, 2012; van Ewijk et al ., 2012; van Rooij et al ., 2015; Wolfers et al ., 2016). These include neuroimaging-based brain readouts, where differences in gray matter volume, white matter volume, as well as functional brain readouts (Frodl and Skokauskas, 2012; Onnink et al ., 2014; Faraone et al ., 2015; Greven et al ., 2015; Wolfers et al ., 2015 b , 2017; Francx et al ., 2016; Norman et al ., 2016) have been reported.…”

Section: Introductionmentioning

confidence: 99%

Individual differencesv.the average patient: mapping the heterogeneity in ADHD using normative models

et al. 2019

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BackgroundThe present paper presents a fundamentally novel approach to model individual differences of persons with the same biologically heterogeneous mental disorder. Unlike prevalent case-control analyses, that assume a clear distinction between patient and control groups and thereby introducing the concept of an ‘average patient’, we describe each patient's biology individually, gaining insights into the different facets that characterize persistent attention-deficit/hyperactivity disorder (ADHD).MethodsUsing a normative modeling approach, we mapped inter-individual differences in reference to normative structural brain changes across the lifespan to examine the degree to which case-control analyses disguise differences between individuals.ResultsAt the level of the individual, deviations from the normative model were frequent in persistent ADHD. However, the overlap of more than 2% between participants with ADHD was only observed in few brain loci. On average, participants with ADHD showed significantly reduced gray matter in the cerebellum and hippocampus compared to healthy individuals. While the case-control differences were in line with the literature on ADHD, individuals with ADHD only marginally reflected these group differences.ConclusionsCase-control comparisons, disguise inter-individual differences in brain biology in individuals with persistent ADHD. The present results show that the ‘average ADHD patient’ has limited informative value, providing the first evidence for the necessity to explore different biological facets of ADHD at the level of the individual and practical means to achieve this end.

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“…The SST measures are explained in more detail by Logan68 and Verbruggen and Logan 77. Data from participants who score below 70% in performance accuracy on the ‘go’ trials will be excluded 78. As the ‘mean’ method of SSRT calculation is susceptible to the shape of the RT distribution and to group differences in RT, we will calculate SSRT by the block-based integration method 79…”

Section: Methods and Analysesmentioning

confidence: 99%

Perceptual timing in children with attention-deficit/hyperactivity disorder (ADHD) as measured by computer-based experiments versus real-life tasks: protocol for a cross-sectional experimental study in an ambulatory setting

Marx¹,

Reis²,

Berger³

2019

BMJ Open

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IntroductionThe goal of this study is to get a better understanding of the fundamentals of perceptual timing deficits, that is, difficulties with estimating durations of explicitly attended temporal intervals, in children with attention-deficit/hyperactivity disorder (ADHD). Whereas these deficits were repeatedly demonstrated in laboratory studies using computer-based timing tasks, we will additionally implement a more practical task reflecting real-life activity. In doing so, the research questions of the planned study follow a hierarchically structured path ‘from lab to life’: Are the timing abilities of children with ADHD really disturbed both in the range of milliseconds and in the range of seconds? What causes these deficits? Do children with ADHD rather display a global perceptual timing deficit, or do different ‘timing types’ exist? Are timing deficits present during real-life activities as well, and are they based on the same mechanisms as in computerised tasks?Methods and analysesA quasi-experimental study with two groups of male children aged 8–12 years (ADHD; controls) and with a cross-sectional design will be used to address our research questions. Statistical analyses of the dependent variables will comprise (repeated) measures analyses of variance, stepwise multiple regression analyses and latent class models. With an estimated dropout rate of 25%, power analysis indicated a sample size of 140 subjects (70 ADHD, 70 controls) to detect medium effect sizes.Ethics and disseminationEthics approval was obtained from the ethics committee of the Faculty of Medicine, University of Rostock. Results will be disseminated to researcher, clinician and patient communities in peer-reviewed journals and at scientific conferences, at a meeting of the local ADHD competence network and on our web page which will summarise the study results in an easily comprehensible manner.Trial registration numberDRKS00015760

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Quantifying patterns of brain activity: Distinguishing unaffected siblings from participants with ADHD and healthy individuals

Cited by 17 publications

References 58 publications

Decreased olfactory discrimination is associated with impulsivity in healthy volunteers

Decreased olfactory discrimination is associated with impulsivity in healthy volunteers

Individual differencesv.the average patient: mapping the heterogeneity in ADHD using normative models

Perceptual timing in children with attention-deficit/hyperactivity disorder (ADHD) as measured by computer-based experiments versus real-life tasks: protocol for a cross-sectional experimental study in an ambulatory setting

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