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Tobacco smoking is associated with deleterious health outcomes. Most smokers want to quit smoking, yet relapse rates are high. Understanding neural differences associated with tobacco use may help generate novel treatment options. Several animal studies have recently highlighted the central role of the thalamus in substance use disorders, but this research focus has been understudied in human smokers. Here, we investigated associations between structural and functional magnetic resonance imaging measures of the thalamus and its subnuclei to distinct smoking characteristics. We acquired anatomical scans of 32 smokers as well as functional resting‐state scans before and after a cue‐reactivity task. Thalamic functional connectivity was associated with craving and dependence severity, whereas the volume of the thalamus was associated with dependence severity only. Craving, which fluctuates rapidly, was best characterized by differences in brain function, whereas the rather persistent syndrome of dependence severity was associated with both brain structural differences and function. Our study supports the notion that functional versus structural measures tend to be associated with behavioural measures that evolve at faster versus slower temporal scales, respectively. It confirms the importance of the thalamus to understand mechanisms of addiction and highlights it as a potential target for brain‐based interventions to support smoking cessation, such as brain stimulation and neurofeedback.

Craving is a core symptom of cocaine use disorder and a major factor for relapse risk. To date, there is no pharmacological therapy to treat this disease or at least to alleviate cocaine craving as a core symptom. In animal models, impaired prefrontal-striatal signalling leading to altered glutamate release in the nucleus accumbens appear to be the prerequisite for cocaine-seeking. Thus, those network and metabolic changes may constitute the underlying mechanisms for cocaine craving and provide a potential treatment target. In humans, there is recent evidence for corresponding glutamatergic alterations in the nucleus accumbens, however, the underlying network disturbances that lead to this glutamate imbalance remain unknown. In this state-dependent randomized, placebo-controlled, double-blinded, cross-over multimodal study, resting state functional magnetic resonance imaging in combination with small-voxel proton magnetic resonance spectroscopy (voxel size: 9.4 × 18.8 × 8.4 mm3) was applied to assess network-level and associated neurometabolic changes during a non-craving and a craving state, induced by a custom-made cocaine-cue film, in 18 individuals with cocaine use disorder and 23 healthy individuals. Additionally, we assessed the potential impact of a short-term challenge of N-acetylcysteine, known to normalize disturbed glutamate homeostasis and to thereby reduce cocaine-seeking in animal models of addiction, compared to a placebo. We found increased functional connectivity between the nucleus accumbens and the dorsolateral prefrontal cortex during the cue-induced craving state. However, those changes were not linked to alterations in accumbal glutamate levels. Whereas we additionally found increased functional connectivity between the nucleus accumbens and a midline part of the thalamus during the cue-induced craving state. Furthermore, obsessive thinking about cocaine and the actual intensity of cocaine use were predictive of cue-induced functional connectiv

The brain and its health are essential for our (physical mental, social, and spiritual) wellbeing, for being able to realize our potential as individuals, and also for a fair, well-functioning, and productive society. However, today the world is facing a healthcare crisis related to the very high (and increasing) burden of brain disorders. As a response to this crisis, the “Swiss Brain Health Plan” (SBHP) was conceptualized in the context of other initiatives launched to value, promote, and protect brain health over the entire life course. In the first section of this position paper, the following fundamental considerations of the SBHP are discussed: (1) the high (and increasing) burden of brain disorders in terms of prevalence (>50% of the population suffers from a brain disorder), disability, mortality, and costs; (2) the prevention of brain disorders; (3) the operational definition of brain health; (4) determinants of brain health; (5) international initiatives to promote brain (including mental) health including the World Health Organization (WHO) intersectorial global action plan on epilepsy and other neurological disorders (NDs) (IGAP) and the WHO comprehensive mental health action plan. In the second section of the paper, the five strategic objectives of the SBHP, which has the vision of promoting brain health for all across the entire life course, are presented: (1) to raise awareness; (2) strengthen cross-disciplinary and interprofessional training/educational programs for healthcare professionals; (3) foster research on brain health determinants and individualized prevention of brain disorders; (4) prioritize a holistic (non-disease-specific), integrated, person-centered public health approach to promote brain health and prevent brain disorders through collaborations across scientific, health care, commercial, societal and governmental stakeholders and insurance providers; (5) support, empower, and engage patients, caregivers, and patient organizations, an

Tobacco smoking is one of the leading causes of preventable death and disease worldwide. Most smokers want to quit, but relapse rates are high. To improve current smoking cessation treatments, a better understanding of the underlying mechanisms of nicotine dependence and related craving behaviour is needed. Studies on cue-driven cigarette craving have been a particularly useful tool for investigating the neural mechanisms of drug craving. Here, functional neuroimaging studies in humans have identified a core network of craving-related brain responses to smoking cues that comprises of amygdala, anterior cingulate cortex, orbitofrontal cortex, posterior cingulate cortex and ventral striatum. However, most functional Magnetic Resonance Imaging (fMRI) cue-reactivity studies do not adjust their stimuli for emotional valence, a factor assumed to confound craving-related brain responses to smoking cues. Here, we investigated the influence of emotional valence on key addiction brain areas by disentangling craving- and valence-related brain responses with parametric modulators in 32 smokers. For one of the suggested key regions for addiction, the amygdala, we observed significantly stronger brain responses to the valence aspect of the presented images than to the craving aspect. Our results emphasize the need for carefully selecting stimulus material for cue-reactivity paradigms, in particular with respect to emotional valence. Further, they can help designing future research on teasing apart the diverse psychological dimensions that comprise nicotine dependence and, therefore, can lead to a more precise mapping of craving-associated brain areas, an important step towards more tailored smoking cessation treatments. Keywords: craving; cue-reactivity; functional Magnetic Resonance Imaging; neuroimaging; nicotine use disorder; smoking.

Background: Avolition and anhedonia are common symptoms in schizophrenia and are related to poor long-term prognosis. There is evidence for aberrant cortico-striatal function and connectivity as neural substrate of avolition and anhedonia. However, it remains unclear how both relate to shared or distinct striatal coupling with large-scale intrinsic networks. Using resting state functional magnetic resonance imaging (rs-fMRI) this study investigated the association of large-scale cortico-striatal functional connectivity with self-reported and clinician-rated avolition and anhedonia in subjects with schizophrenia. Methods: Seventeen subjects with schizophrenia (SZ) and 28 healthy controls (HC) underwent rs-fMRI. Using Independent Component Analysis (ICA), we assessed Independent Components (ICs) reflecting intrinsic connectivity networks (ICNs), intra intrinsic functional connectivity within the ICs (intra-iFC), and intrinsic functional connectivity between different ICs (inter-iFC). Avolition and anhedonia were assessed using the Self Evaluation Scale for Negative Symptoms and the Brief Negative Symptom Scale. Results: ICA revealed three striatal components and six cortical ICNs. Both self-rated avolition and anhedonia correlated with increased inter-iFC between the caudate and posterior Default Mode Network (pDMN) and between the caudate and Central Executive Network (CEN). In contrast, clinician-rated avolition and anhedonia were not correlated with cortico-striatal connectivity. Group comparison revealed trend-wise decreased inter-iFC between the caudate and Salience Network (SN) in schizophrenia patients compared to HC. Discussion: Self-rated, but not clinician-rated, avolition and anhedonia was associated with aberrant striatal coupling with the default mode and the central executive network. These findings suggest that self-reported and clinician-rated scores might capture different aspects of motivational and hedonic deficits in schizophrenia and therefore rel

Background and aimsAlcohol Use Disorder (AUD) is characterized by a reduction in goal-directed behavior, with alcohol use taking precedence over other areas of life. These features in AUD resemble negative symptoms in schizophrenia, especially the reduction in motivation and pleasure (MAP). Given the clinical similarities of negative symptoms across diagnostic categories, it comes as a surprise that there are few investigations on negative symptoms in alcohol and other substance use disorders. To our knowledge, our study is the first to assess negative symptoms in AUD based on a two-factorial approach, and to investigate the interrelation of these dimensions with the severity of AUD, and alcohol craving.Materials and methodsWe examined a sample of 42 patients with AUD at the Psychiatric University Hospital in Zurich. Participants provided self-report and interview-based measures of the severity of AUD, negative symptoms, and alcohol craving. Finally, we used data from the electronic health records of the patients.ResultsPatients with AUD show negative symptoms to a similar extent as patients with schizophrenia or bipolar disorder. We found a positive correlation between the extent of impairment within the MAP factor and overall severity of AUD. Furthermore, MAP negative symptoms were correlated with alcohol craving. In a linear regression, negative symptoms predicted alcohol craving whereas depression did not.SummaryNegative symptoms as conceptualized for schizophrenia are prevalent in patients with AUD and associated with the severity of AUD. More specifically, severity of AUD correlates with diminished motivation and pleasure, highlighting the importance of disturbances in motivational functions in AUD. This is further supported by the correlation between negative symptoms and craving, a hallmark of AUD. Taken together, our findings suggest that negative symptoms might be a highly relevant but hitherto often neglected therapeutic target in AUD.

The dopaminergic midbrain is associated with reinforcement learning, motivation and decision-making – functions often disturbed in neuropsychiatric disorders. Previous research has shown that dopaminergic midbrain activity can be endogenously modulated via neurofeedback. However, the robustness of endogenous modulation, a requirement for clinical translation, is unclear. Here, we examine whether the activation of particular brain regions associates with successful regulation transfer when feedback is no longer available. Moreover, to elucidate mechanisms underlying effective self-regulation, we study the relation of successful transfer with learning (temporal difference coding) outside the midbrain during neurofeedback training and with individual reward sensitivity in a monetary incentive delay (MID) task. Fifty-nine participants underwent neurofeedback training either in standard (Study 1 N = 15, Study 2 N = 28) or control feedback group (Study 1, N = 16). We find that successful self-regulation is associated with prefrontal reward sensitivity in the MID task (N = 25), with a decreasing relation between prefrontal activity and midbrain learning signals during neurofeedback training and with increased activity within cognitive control areas during transfer. The association between midbrain self-regulation and prefrontal temporal difference and reward sensitivity suggests that reinforcement learning contributes to successful self-regulation. Our findings provide insights in the control of midbrain activity and may facilitate individually tailoring neurofeedback training.

Tobacco smoking is associated with deleterious health outcomes. Most smokers want to quit smoking, yet relapse rates are high. Understanding neural differences associated with tobacco use may help generate novel treatment options. Several animal studies have recently highlighted the central role of the thalamus in substance use disorders, but this research focus has been understudied in human smokers. Here, we investigated associations between structural and functional magnetic resonance imaging measures of the thalamus and its subnuclei to distinct smoking characteristics. We acquired anatomical scans of 32 smokers as well as functional resting-state scans before and after a cue-reactivity task. Thalamic functional connectivity was associated with craving and dependence severity, whereas the volume of the thalamus was associated with dependence severity only. Craving, which fluctuates rapidly, was best characterized by differences in brain function, whereas the rather persistent syndrome of dependence severity was associated with both brain structural differences and function. Our study supports the notion that functional versus structural measures tend to be associated with behavioral measures that evolve at faster versus slower temporal scales, respectively. It confirms the importance of the thalamus to understand mechanisms of addiction and highlights it as a potential target for brain-based interventions to support smoking cessation, such as brain stimulation and neurofeedback.

Due to high infections rates and a high death toll of the COVID-19 pandemic, it is important to have daily updated forecasted estimates for the next weeks in order to allocate the scare resources as good as possible. We propose a pragmatic model to forecast the COVID-19 epidemic by applying a mixture normal distribution to open accessible WHO data. We specified a simple joint model on data from 20 countries with number of confirmed COVID-19 infections and number of COVID-19 deaths. We found that the duration of an epidemic wave (99% of total size) was usually between 45 – 48 days. Using data up to April 6, 2020, we found in six of 20 counties two waves, spaced between 21 and 47 days. In China and Korea the first wave was bigger, and in Denmark, Iran, Japan, and Sweden the second wave was stronger. Lag time between time trends in confirmed infections and time trends in deaths varied between 3.1 and 9.5 days. We obtained a good fit between observed and modelled data in almost all countries. In about halve of the countries the highest peak of the COVID-19 epidemic had been reached until April 6, 2020. Among the 20 countries, it is predicted that the USA will reach the highest numbers of confirmed infections (653 683 – 802 205) and number of deaths (36 591 – 53 286). Taken together, for many countries reasonable and up-to-date forecasting seems to be feasible. This method therefore bears a high potential for assisting decision makers to adjust the measures aiming at reducing the spread of the virus appropriately.

Substance use disorders (SUD) represent a significant public health issue with a high need for novel and efficacious treatment options. In light of this high unmet need, recent results reporting beneficial outcomes of psychedelic-assisted therapy in SUD are particularly relevant. However, several questions remain with regard to this treatment approach. The clinical mechanisms of action of psychedelic substances in the treatment of SUD are not well understood. Closing this knowledge gap is critical to inform and optimize the psychotherapeutic embedding of the acute substance administration. In this chapter, we discuss potential mechanisms that have implications on psychotherapeutic approaches including induced neuroplasticity, alterations in brain network connectivity, reward and emotion processing, social connectedness, insight, and mystical experiences. Furthermore, we outline considerations and approaches that leverage these mechanisms in order to optimize the therapeutic embedding by maximizing synergy between substance effects and psychotherapy. Understanding the mechanisms of action, developing psychotherapeutic approaches accordingly, and evaluating their synergistic efficacy in scientific studies will be critical to advance the framework of psychedelic-assisted therapy for addiction, create evidence-based approaches, and achieve the best treatment outcome for patients with SUD.

Background Alternative cannabis regulation models are discussed and implemented worldwide. A baseline scenario under the assumption of no policy or market changes may prove useful to forecast cannabis use and treatment demand and evaluate changes in legislation. Methods Based on data of the Continuous Rolling Survey of Addictive Behaviours and Related Risks on cannabis use, age, gender and nationality from 2011 to 2015, we used general estimating equation analysis to model lifetime and 30-days prevalence from 2015 to 2045 in Switzerland accounting for demographic trends. Results Lifetime prevalence of cannabis use is projected to grow from 28.3% (CI 95% 27.8–28.8) in 2015 to 42.0% (CI 95% 41.0–43.0) in 2045. 30-days prevalence would increase slightly from 2.70% (CI 95% 2.53–2.88) to 3.39% (CI 95% 3.11–3.66). Due to population growth, absolute numbers with past 30-day cannabis use are estimated to increase from 202,784 (CI 95% 189,534–216,035) to 314,302 (CI 95% 288,504–340,100). Among those aged under 30 years no substantial change in lifetime and 30-days prevalence of cannabis use is projected. Larger changes are estimated to occur in the age group 30+. The mean age of past 30-day cannabis users would increase for men with Swiss nationality from 30.3 to 38.7 years. Discussion Population-based survey data and demographic projections can be used to develop baseline scenarios of future cannabis use. Assuming no changes in cannabis legislation, growing absolute numbers of users will likely increase treatment demand. Cannabis use is estimated to increase among the group aged >30 years, which is currently underrepresented in clinical treatment and research. Our findings highlight the need for prospective baseline scenarios to evaluate the impact of legislative changes on cannabis use. Moreover, in Switzerland effective prevention and treatment interventions for cannabis use disorders are required even if cannabis legislation remains unchanged.

Cocaine is one of the most commonly used substances worldwide. It has a strong addictive potential, which often leads to excessive consumption causing pronounced physical and psychological harm to users. There is currently no approved or effective medication to treat cocaine use disorders. However, in the last decades, significant efforts have been made to identify medications that could increase the effectiveness of treatments, with several drugs showing some promise. Although current evidence to either support or reject their ultimate efficacy is insufficient, encouraging indications have been found in studies testing dopamine agonists to reduce cocaine use or prevent relapse. Particularly, positive signals have been identified for long-acting amphetamine formulations and for modafinil, each under specific conditions such as comorbid psychiatric disorders. Medications addressing cocaine-related glutamate disturbances, such as N-acetylcysteine and ketamine, have also shown some beneficial effects on cocaine craving and other withdrawal symptoms as well as on the severity of cocaine use. However, it remains unclear whether these drugs can consistently achieve therapeutic benefits in the longer term and in heterogeneous clinical populations. In sum, conclusive statements about the clinical efficacy of the tested medications cannot yet be made. While renewed emphasis on the discovery of novel drug targets for the treatment of cocaine use disorders is needed, there is also a clear necessity for further investigation of the most promising existing medications, such as ketamine, N-acetylcysteine, modafinil, and extended-release amphetamines, in longitudinal study designs with large patient samples to establish their potential long-term therapeutic value.

Changed reward functions have been proposed as a core feature of stimulant addiction, typically observed as reduced neural responses to non-drug-related rewards. However, it was unclear yet how specific this deficit is for different types of non-drug rewards arising from social and non-social reinforcements. We used functional neuroimaging in cocaine users to investigate explicit social reward as modeled by agreement of music preferences with music experts. In addition, we investigated non-social reward as modeled by winning desired music pieces. The study included 17 chronic cocaine users and 17 matched stimulant-naive healthy controls. Cocaine users, compared with controls, showed blunted neural responses to both social and non-social reward. Activation differences were located in the ventromedial prefrontal cortex overlapping for both reward types and, thus, suggesting a non-specific deficit in the processing of non-drug rewards. Interestingly, in the posterior lateral orbitofrontal cortex, social reward responses of cocaine users decreased with the degree to which they were influenced by social feedback from the experts, a response pattern that was opposite to that observed in healthy controls. The present results suggest that cocaine users likely suffer from a generalized impairment in value representation as well as from an aberrant processing of social feedback.

Background: Cue-reactivity paradigms provide valuable insights into the underlying mechanisms of nicotine craving in nicotine-dependent subjects. In order to study cue-driven nicotine craving, robust and validated stimulus datasets are essential. Objectives: The aim of this study was to generate and validate a large set of individually rated smoking-related cues that allow for assessment of different stimulus intensities along the dimensions craving, valence, and arousal. Methods: The image database consisted of 330 visual cues. Two hundred fifty smoking-associated pictures (Creative Commons license) were chosen from online databases and showed a widespread variety of smoking-associated content. Eighty pictures from previously published databases were included for cross-validation. Forty volunteers with tobacco use disorder rated "urge-to-smoke," "valence," and "arousal" for all images on a 100-point visual analogue scale. Pictures were also labelled according to 18 categories such as lit/unlit cigarettes in mouth, cigarette end, and cigarette in ashtray. Results: Ratings (mean ± SD) were as follows: urge to smoke, 44.9 ± 13.2; valence, 51.2 ± 7.6; and arousal, 54.6 ± 7.1. All ratings, particularly "urge to smoke," were widely distributed along the whole scale spectrum. Conclusions: We present a novel image library of well-described smoking-related cues, which were rated on a continuous scale along the dimensions craving, valence, and arousal that accounts for inter-individual differences. The rating software, image database, and their ratings are publicly available at https://smocuda.github.io.

Cocaine addiction is characterized by overwhelming craving for the substance, which drives its escalating use despite adverse consequences. Animal models suggest a disrupted glutamate homeostasis in the nucleus accumbens to underlie addiction-like behaviour. After chronic administration of cocaine, rodents show decreased levels of accumbal glutamate, whereas drug-seeking reinstatement is associated with enhanced glutamatergic transmission. However, due to technical obstacles, the role of disturbed glutamate homeostasis for cocaine addiction in humans remains only partially understood, and accordingly, no approved pharmacotherapy exists. Here, we applied a tailored proton magnetic resonance spectroscopy protocol that allows glutamate quantification within the human nucleus accumbens. We found significantly reduced basal glutamate concentrations in the nucleus accumbens in cocaine-addicted (N = 26) compared to healthy individuals (N = 30), and increased glutamate levels during cue-induced craving in cocaine-addicted individuals compared to baseline. These glutamatergic alterations, however, could not be significantly modulated by a short-term challenge of N-acetylcysteine (2400 mg/day on two days). Taken together, our findings reveal a disturbed accumbal glutamate homeostasis as a key neurometabolic feature of cocaine addiction also in humans. Therefore, we suggest the glutamatergic system as a promising target for the development of novel pharmacotherapies, and in addition, as a potential biomarker for a personalised medicine approach in addiction.

Anhedonia has been associated with abnormal reward-related striatal dopamine functioning in patients with different psychiatric disorders. Here, we tested whether anhedonia expression mapped onto striatal volume across several psychiatric diagnoses. T1-weighted images from 313 participants including 89 healthy controls (HC), 22 patients with opioid use disorder (OUD), 50 patients with major depressive disorder (MDD), 45 patients with borderline personality disorder (BPD), 49 patients with first-episode psychosis (FEP), 43 patients with cocaine use disorder (CUD) and 15 patients with schizophrenia (SZ) were included. Anhedonia was assessed with subscores of the Beck Depression Inventory (BDI) and/or the Scale for the Assessment of Negative Symptoms (SANS). Voxel-based morphometry (VBM) was conducted for identifying dimensional symptom-structure associations using region of interest (ROI, dorsal and ventral striatum) and whole-brain analyses, as well as for group comparisons of striatal volume. ROI analyses revealed significant negative relationships between putamen volume and BDI and SANS anhedonia scores across OUD, MDD, BPD, CUD and SZ patients (n = 175) and MDD, FEP and SZ patients (n = 114), respectively. Whole-brain VBM analyses confirmed these associations and further showed negative relationships between anhedonia severity and volume of the bilateral cerebellum. There were group differences in right accumbens volume, which however were not related to anhedonia expression across the different diagnoses. Our findings indicate volumetric abnormalities in the putamen and cerebellum as a common neural substrate of anhedonia severity that cut across psychiatric entities.

BACKGROUND AND AIMS Elite athletes may use psychotropic substances for recreational reasons, (perceived) performance enhancement or self-medication. Causes can overlap. For athletes, substance use may be associated with various medical and social risks. Psychoactive substances include alcohol and nicotine, illicit and various prescription drugs, which all have a potential for abuse and dependence. This paper reviews the existing literature on the use of psychoactive substances and associated substance use disorders among elite athletes in terms of prevalence, patterns of use, as well as underlying causes and risk factors. METHODS Due to the heterogeneous and partially fragmentary study data, a narrative approach with selection of applicable publications of a Medline search was chosen. RESULTS The most commonly used psychoactive substances among elite athletes were alcohol, nicotine, cannabis, stimulants and (prescription) opioids. Overall consumption rates are lower in professional sports than in the general population, but use of several substances (smokeless tobacco products, prescription opioids, stimulants) have high prevalence in specific sports and athlete groups. Substance use is subject to multiple risk factors and varies by substance class, sport discipline, country and gender, among other factors. CONCLUSION Knowledge on the underlying causes and patterns of substance use, as well as the prevalence of substance use disorders in professional sports, is still limited. High prevalence of various substances (i.e., nicotine, prescription opioids) may indicate potentially harmful patterns of use, requiring further research. Specific preventive and therapeutic concepts for the treatment of substance use disorders in elite athletes should be developed. Keywords: elite athlete, professional sports, psychotropic substances, recreational substance use, substance use disorders, performance enhancing substances, sports medicine

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.

Altered cerebral connectivity is one of the core pathophysiological mechanism underlying the development and progression of information-processing deficits in schizophrenia. To date, most diffusion tensor imaging (DTI) studies used fractional anisotropy (FA) to investigate disrupted white matter connections. However, a quantitative interpretation of FA changes is often impeded by the inherent limitations of the underlying tensor model. A more fine-grained measure of white matter alterations could be achieved by measuring fiber density (FD) - a novel non-tensor-derived diffusion marker. This study investigates, for the first time, FD alterations in schizophrenia patients. FD and FA maps were derived from diffusion data of 25 healthy controls (HC) and 21 patients with schizophrenia (SZ). Using tract-based spatial statistics (TBSS), group differences in FD and FA were investigated across the entire white matter. Furthermore, we performed a region of interest (ROI) analysis of frontal fasciculi to detect potential correlations between FD and positive symptoms. As a result, whole brain TBSS analysis revealed reduced FD in SZ patients compared to HC in several white matter tracts including the left and right thalamic radiation (TR), superior longitudinal fasciculus (SLF), corpus callosum (CC), and corticospinal tract (CST). In contrast, there were no significant FA differences between groups. Further, FD values in the TR were negatively correlated with the severity of positive symptoms and medication dose in SZ patients. In summary, a novel diffusion-weighted data analysis approach enabled us to identify widespread FD changes in SZ patients with most prominent white matter alterations in the frontal and subcortical regions. Our findings suggest that the new FD measure may be more sensitive to subtle changes in the white matter microstructure compared to FA, particularly in the given population. Therefore, investigating FD may be a promising approach to detect subtle chang

The dopaminergic midbrain is associated with elementary brain functions, such as reward processing, reinforcement learning, motivation and decision-making that are often disturbed in neuropsychiatric disease. Previous research has shown that activity in the dopaminergic midbrain can be endogenously modulated via neurofeedback, suggesting potential for non-pharmacological interventions. However, the robustness of endogenous modulation, a requirement for clinical translation, is unclear. Here, we used non-invasive modulation of the dopaminergic midbrain activity by real-time neurofeedback to examine how self-modulation capability affects transfer and correlated activation across the brain. In addition, to further elucidate potential mechanisms underlying successful self-regulation, we studied individual prediction error coding during neurofeedback training, and, during a completely independent monetary incentive delay (MID) task, individual reward sensitivity. Fifty-nine participants underwent neurofeedback training either in a veridical or inverted feedback group. Post-training activity within the cognitive control network was increased only in those individuals with successful self-regulation of the dopaminergic midbrain during neurofeedback training. Successful learning to regulate was accompanied by decreasing prefrontal prediction error signals and increased prefrontal reward sensitivity in the MID task. Our findings suggest that the cognitive control network contributes to successful transfer of the capability to upregulate the dopaminergic midbrain. The link of dopaminergic self-regulation with individual differences in prefrontal prediction error and reward sensitivity indicates that reinforcement learning contributes to successful top-down control of the midbrain. Our findings therefore provide new insights in the cognitive control of dopaminergic midbrain activity and pave the way to improving neurofeedback training in neuropsychiatric patients.