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Background:Methylphenidate (MPH) is the first-line pharmacological treatment of attention-deficit/hyperactivity disorder (ADHD). MPH binds to the dopamine (DA) transporter (DAT), which has high density in the striatum. Assessments of the striatal dopamine transporter by single positron emission computed tomography (SPECT) in childhood and adolescent patients are rare but can provide insight on how the effects of MPH affect DAT availability. The aim of our within-subject study was to investigate the effect of MPH on DAT availability and how responsivity to MPH in DAT availability is linked to clinical symptoms and cognitive functioning.MethodsThirteen adolescent male patients (9–16 years) with a diagnosis of ADHD according to the DSM-IV and long-term stimulant medication (for at least 6 months) with MPH were assessed twice within 7 days using SPECT after application of I-123-β-CIT to examine DAT binding potential (DAT BP). SPECT measures took place in an on- and off-MPH status balanced for order across participants. A virtual reality continuous performance test was performed at each time point. Further clinical symptoms were assessed for baseline off-MPH.ResultsOn-MPH status was associated with a highly significant change (−29.9%) of striatal DAT BP as compared to off-MPH (t = −4.12, p = 0.002). A more pronounced change in striatal DAT BP was associated with higher off-MPH attentional and externalizing symptom ratings (Pearson r = 0.68, p = 0.01). Striatal DAT BP off-MPH, but not on-MPH, was associated with higher symptom ratings (Pearson r = 0.56, p = 0.04).ConclusionOur findings corroborate previous reports from mainly adult samples that MPH changes striatal DAT BP availability and suggest higher off-MPH DAT BP, likely reflecting low baseline DA levels, as a marker of symptom severity.

Model-based (MB) control over rewards is negatively associated with obsessive-compulsive (OC) symptoms. However, the OC phenotype is strongly concerned with punishments and enhanced avoidance. In contrast, continuous substance use (SU) is linked to disrupted punishments integration in future action planning and MB control over rewards was only inconsistently shown to be impaired in SU symptoms. Still, the role of positive versus negative outcomes in the relationship between MB control and OC versus SU symptoms remains to be investigated. We hypothesize increased MB control for punishments versus gains with increasing OC symptoms and decreased MB control for punishments versus gains with increasing SU symptoms. We will collect two independent samples (n=380 per task) online, with each sample completing one version of two valence-dependent 2-step tasks to assess distinct aspects of MB control combined with symptom questionnaires. This study can elucidate inter-individual differences in valence-dependent MB control relevant to unique aspects of psychopathology.

This preregistration gives an overview of the background, overarching hypotheses, and design of a large study consisting of several subprojects. Detailed information about the subprojects and the respective analysis plans can be found in separate preregistrations.

In order to navigate goal-directed behavior in an ever-changing complex environment, a fine balance between maintaining and updating of goal-relevant information is required. A cognitive system crucially involved in these processes is our working memory (WM). While maintenance of WM representations is thought to be implemented by recurrent excitatory networks in the PFC (Seamans et al., 2003, Curtis & D’Esposito, 2003; Fallon et al., 2017), updating is accomplished via fronto-striatal go/no-go pathway modulations (O’Reilly and Frank, 2006, Fallon & Cools, 2014; Fallon, van der Schaaf, ter Huurne, & Cools, 2017). Importantly, neurocomputational models, and fMRI and PET studies have demonstrated the involvement of dopaminergic signaling in the modulation of these two complementary processes (Durstewitz & Seamans, 2008; Hazy, Frank, & O’Reilly, 2007; O’Reilly & Frank, 2006). In line with this, flexible maintenance and updating of WM representation has been associated with certain single-nucleotide polymorphisms (COMT and DRD2), both of which are indicative for frontal and striatal dopamine levels, respectively. (Käenmäki et al., 2010; Syvänen et al., 1997; Hirvonen et al., 2005; Leyton et al., 2004; Montgomery et al., 2003). With respect to the COMT gene, Met allele carriers (who supposingly have high prefrontal DA concentrations) are reported to perform better on tasks that require stable maintenance of working memory representations (Berryhill et al., 2013, Farrell et al., 2012; Savitz, Solms, & Ramesar, 2006). Val carriers (who supposingly have low prefrontal DA concentrations) however, perform better on tasks that mainly probe cognitive flexibility (Cameron et al., 2018; Colzato et al., 2010). With respect to the DRD2/ANKK1-TaqIA polymorphism it has been shown that carriers of the A1 allele have up to 30% reduced D2 receptor density in striatum and outperform non-carriers on measures of cognitive flexibility (Jönsson et al., 1999; Pohjalainen et al., 1998; Stelzel et al., 2009). Importantly, recent studies suggest that these two SNPs act on WM interactively, where there are balanced and unbalanced combinations of genotypes (Gracia-Gracia et al., 2011; Reuter, Schmitz, Corr, & Hennig, 2006). In obese individuals, the accurate adaptation of WM representations seems to be compromised. Behaviorally, obese participants have been shown to perform worse on task that require cognitive adaptation (Steenbergen & Colzato, 2017). Furthermore, obese individuals prefer short-term rewards despite of negative long-term outcome (Horstmann et al., 2011; Mathar et al., 2015) or repeat previously rewarded action, despite of current devaluation (Horstmann et al., 2015b). These findings hence suggest that obese individuals might fail to update the negative consequences of their actions, which could contribute to dysfunctional preservation of maladaptive (eating-) behaviors. Additionally, functional changes in the above mentioned WM-related brain areas have been observed in obesity. Several studies report altered central dopamine levels and dopamine receptor density in striatum (Horstmann, Fenske, and Hankir 2015a, Wang et al., 2001; Dunn et al., 2012; Eisenstein et al., 2013; Kessler et al., 2014; Cosgrove et al., 2015; Horstmann et al., 2015a), as well as changes in grey matter density in PFC in obese individuals (Horstmann et al., 2011; Mathar et al., 2015). While there is general consensus that obesity is associated with alterations in WM functioning (Yang, et al., 2018, Gonzales et al., 2010; Coppin et al., 2014), it remains unclear to what extent and which of the above mentioned WM mechanisms contribute to these impairments. In the present study, we therefore aim to tackle this gap and elucidate on potential impairments in the specific sub processes of WM functioning in obesity. To this end, we implement a task-based fMRI, using a modified version of a delayed match-to-sample task originally designed by Fallon and Cools (2014), which compiles specific conditions that probe updating and maintenance of mental representations. Participants have to remember two target stimuli, signaled by the letter “T” centered between the two stimuli, and match with a probe presented at the end of each trial. The task consists of three task conditions: update, ignore, and maintain. In the update condition participants are first presented with two target stimuli (signaled by the centered “T”). Then they get to see a new pair of target stimuli that displaces the previous target stimuli and has to be matched with the subsequently presented probe. In the ignore condition participants are presented a new set of non-target stimuli (signaled by a centered “N”) after the first set of target stimuli. They have to ignore the non-target stimuli and match the previously presented target stimuli with the subsequent probe. In the maintain condition no distractor stimuli are presented, participants only see one pair of target stimuli that they have to match with the subsequent probe. Instead of the non-target stimuli (maintain condition with matched target-probe delay to the ignore condition) or the first target stimuli (maintain condition with matched target-probe delay to the update condition) a fixation cross is presented. Stimuli and fixation cross remain on the screen for 2000 msec in the first phase of a trial, and 1000 msec in the second phase of a trial. The time of the probe being presented and thus the time for the participant to make a choice is 2000 msec. Feedback whether the choice made at the end of each trial (“Is the present probe one of the two target stimuli?” Yes or No) is not provided. The task is separated in four blocks, with feedback on performance between each block. The three task conditions were equally distributed over all four blocks. Each block consists of 32 trials, amounting to a total of 128 trials. Each trial is separated by a inter-trial interval with a jitter of m 2000 to 6000 msec. The task stimuli are unique, randomly computer-generated, monochromatic RGB “spirographs”. Outcome measures are accuracy and reaction time. The total duration of the task is approximately 30 minutes. At the time of submission, data acquisition has started. All datasets have been collected. The data has not been looked at yet, except for general hypotheses-independent sanity checks (e.g. motion and segmentation checks in the fMRI data, performance above chance checks for the task data)

Working memory (WM) is a mental workspace where information is maintained but also updated in order to flexibly adapt to an ever-changing complex environment. A fine balance between these two functions of WM—maintenance on the one and updating on the other hand – is therefore essential to navigate goal-directed behavior. While fMRI and PET studies have successfully demonstrated the involvement of dopaminergic fronto-striatal loops in these adaptive processes (Fallon et al., 2014; Fallon et al. 2017, Landau et al. (2009), the underlying neural dynamics remain poorly understood. Information gating is also controlled via the balance between excitation and inhibition in the receiver network (e.g., Vogels & Abbott, 2009). As so, persistent maintenance of WM contents in the PFC depends on recurrent excitatory networks and global feedback inhibition (REF). The inherent ratio of ones excitatory and inhibitory connections thus may pose a predisposition to certain malfunctioning of the to-be-balanced processes. However, the exact interplay of excitatory and inhibitory signals to navigate maintenance and selective updating remains elusive (also see Dipoppa, Szwed, and Gutkin, 2016) Long-Range Temporal Correlations (LRTC) in ongoing oscillations during rest have been demonstrated to characterize the inherent balance of inhibitory and excitatory connections within a neural network (Poil et al., 2012) and emerge when neuronal systems operate at a near critical state (Meisel et al., 2017; Palva et al., 2013; Nikulin & Brismar, 2004; Linkenkaer-Hansen et al., 2001). Near critical system dynamics were associated with optimal information processing (Beggs and Plenz, 2004; Shew & Plenz, 2013; Shew et al., 2011) which, when disrupted, will lead to significant loss of function (Poil et al., 2012; Linkenkaer-Hansen et al., 2005; Monto et al., 2007; Montez et al., 2009; Nikulin et al., 2012). Interestingly, LRTC have a high heritable component (Linkenkaer-Hansen et al., 2007) as well as high test-retest reliability (Nikulin & Brismar, 2004), which hence makes them an eligible candidate for conclusions about inherent network characteristics. Furthermore, previous research also suggests that LRTC may play a crucial role in higher brain functions such as attention (Irrmischer et al., 2018) and adaptive decision making (Colosio et al., 2017). And more recent work indicates that higher LRTC can be related to better working memory performance involving phasic adaptive control and moment-to-moment processing (Mahjoory et al. 2018). Taken together, these findings indicate a potential role of resting-state LRTC for adaptive working memory processes. In the proposed study we therefor aim to investigate how resting state LRTC may support maintenance and/or flexible updating of mental representations. To this end, we will record 10 minutes eyes-closed rest EEG. After that participants will conduct a modified version of a delayed match-to-sample task originally designed by Fallon and Cools (2014), which compiles specific conditions that probe updating and maintenance of mental representations. Participants have to remember two target stimuli, signaled by the letter “T” centered between the two stimuli, and match with a probe presented at the end of each trial. The task consists of four task conditions: update, ignore, and a respective control condition for each of these. In the update condition participants are first presented with two target stimuli (signaled by the centered “T”). Then they get to see a new pair of target stimuli that displaces the previous target stimuli and has to be matched with the subsequently presented probe. In the ignore condition participants are presented a new set of non-target stimuli (signaled by a centered “N”) after the first set of target stimuli. They have to ignore these non-target stimuli and match the previously presented target stimuli with the subsequent probe. In the maintain condition no distractor stimuli are presented; participants only see one pair of target stimuli that they have to match with the subsequent probe. Instead of the non-target stimuli (maintain condition with matched target-probe delay to the ignore condition) or the first target stimuli (maintain condition with matched target-probe delay to the update condition) a fixation cross is presented. Stimuli and fixation cross remain on the screen for 2000 msec. The time of the probe being presented and thus the time for the participant to make a choice is 2000 msec. Feedback whether the choice made at the end of each trial (“Is the present probe one of the two target stimuli?” Yes or No) is not provided. The task is separated in four blocks, with feedback on performance between each block. The four task conditions were equally distributed over all four blocks. Each block consists of 32 trials, amounting to a total of 128 trials. Each trial is separated by an inter-trial interval of 2000 msec. The task stimuli are unique, randomly computer-generated, monochromatic RGB “spirographs”. Outcome measures are accuracy and reaction time. The total duration of the task is approximately 30 minutes. To further capture gating processes that take place during this task, we will extract the novelty-P3 ERP component from task EEG. This component has been established as a brain signature of the updating of contextual information (Barcelo et al.,2006; Barcelo et al., 2007; Perianez and Barcelo, 2009) and relates to task switching performance in a dopamine-dependent fashion (Garcia-Garcia et al., 2011). At the time of submission, data acquisition has started. 38 full datasets have been collected. The data has not been looked at yet.