TY - JOUR A1 - Brem, Silvia A1 - Grünblatt, Edna A1 - Drechsler, Renate A1 - Riederer, Peter A1 - Walitza, Susanne T1 - The neurobiological link between OCD and ADHD JF - Attention Deficit and Hyperactivity Disorders N2 - Obsessive compulsive disorder (OCD) and attention deficit hyperactivity disorder (ADHD) are two of the most common neuropsychiatric diseases in paediatric populations. The high comorbidity of ADHD and OCD with each other, especially of ADHD in paediatric OCD, is well described. OCD and ADHD often follow a chronic course with persistent rates of at least 40–50 %. Family studies showed high heritability in ADHD and OCD, and some genetic findings showed similar variants for both disorders of the same pathogenetic mechanisms, whereas other genetic findings may differentiate between ADHD and OCD. Neuropsychological and neuroimaging studies suggest that partly similar executive functions are affected in both disorders. The deficits in the corresponding brain networks may be responsible for the perseverative, compulsive symptoms in OCD but also for the disinhibited and impulsive symptoms characterizing ADHD. This article reviews the current literature of neuroimaging, neurochemical circuitry, neuropsychological and genetic findings considering similarities as well as differences between OCD and ADHD. KW - OCD KW - ADHD KW - neuroimaging KW - genetics KW - neuropsychology KW - fMRI KW - MRI KW - EEG KW - neurobiology Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-121312 VL - 6 IS - 3 ER - TY - JOUR A1 - Saulin, Anne A1 - Horn, Ulrike A1 - Lotze, Martin A1 - Kaiser, Jochen A1 - Hein, Grit T1 - The neural computation of human prosocial choices in complex motivational states JF - NeuroImage N2 - Motives motivate human behavior. Most behaviors are driven by more than one motive, yet it is unclear how different motives interact and how such motive combinations affect the neural computation of the behaviors they drive. To answer this question, we induced two prosocial motives simultaneously (multi-motive condition) and separately (single motive conditions). After the different motive inductions, participants performed the same choice task in which they allocated points in favor of the other person (prosocial choice) or in favor of themselves (egoistic choice). We used fMRI to assess prosocial choice-related brain responses and drift diffusion modeling to specify how motive combinations affect individual components of the choice process. Our results showed that the combination of the two motives in the multi-motive condition increased participants' choice biases prior to the behavior itself. On the neural level, these changes in initial prosocial bias were associated with neural responses in the bilateral dorsal striatum. In contrast, the efficiency of the prosocial decision process was comparable between the multi-motive and the single-motive conditions. These findings provide insights into the computation of prosocial choices in complex motivational states, the motivational setting that drives most human behaviors . KW - motivation KW - social decision-making KW - hierarchical drift-diffusion modeling KW - fMRI KW - social neuroscience Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-265852 VL - 247 ER - TY - JOUR A1 - Weiß, Martin A1 - Iotzov, Vassil A1 - Zhou, Yuqing A1 - Hein, Grit T1 - The bright and dark sides of egoism JF - Frontiers in Psychiatry N2 - Despite its negative reputation, egoism – the excessive concern for one’s own welfare – can incite prosocial behavior. So far, however, egoism-based prosociality has received little attention. Here, we first provide an overview of the conditions under which egoism turns into a prosocial motive, review the benefits and limitations of egoism-based prosociality, and compare them with empathy-driven prosocial behavior. Second, we summarize studies investigating the neural processing of egoism-based prosocial decisions, studies investigating the neural processing of empathy-based prosocial decisions, and the small number of studies that compared the neural processing of prosocial decisions elicited by the different motives. We conclude that there is evidence for differential neural networks involved in egoism and empathy-based prosocial decisions. However, this evidence is not yet conclusive, because it is mainly based on the comparison of different experimental paradigms which may exaggerate or overshadow the effect of the different motivational states. Finally, we propose paradigms and research questions that should be tackled in future research that could help to specify how egoism can be used to enhance other prosocial behavior and motivation, and the how it could be tamed. KW - egoism KW - incentives KW - prosociality KW - social motives KW - fMRI Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-297183 SN - 1664-0640 VL - 13 ER - TY - JOUR A1 - Mourão-Miranda, Janaina A1 - Hardoon, David R. A1 - Hahn, Tim A1 - Marquand, Andre F. A1 - Williams, Steve C.R. A1 - Shawe-Taylor, John A1 - Brammer, Michael T1 - Patient classification as an outlier detection problem: An application of the One-Class Support Vector Machine JF - NeuroImage N2 - Pattern recognition approaches, such as the Support Vector Machine (SVM), have been successfully used to classify groups of individuals based on their patterns of brain activity or structure. However these approaches focus on finding group differences and are not applicable to situations where one is interested in accessing deviations from a specific class or population. In the present work we propose an application of the one-class SVM (OC-SVM) to investigate if patterns of fMRI response to sad facial expressions in depressed patients would be classified as outliers in relation to patterns of healthy control subjects. We defined features based on whole brain voxels and anatomical regions. In both cases we found a significant correlation between the OC-SVM predictions and the patients' Hamilton Rating Scale for Depression (HRSD), i.e. the more depressed the patients were the more of an outlier they were. In addition the OC-SVM split the patient groups into two subgroups whose membership was associated with future response to treatment. When applied to region-based features the OC-SVM classified 52% of patients as outliers. However among the patients classified as outliers 70% did not respond to treatment and among those classified as non-outliers 89% responded to treatment. In addition 89% of the healthy controls were classified as non-outliers. KW - fMRI KW - Pattern classification KW - Depression KW - Machine learning KW - Support Vector Machine KW - Outlier detection Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-141412 VL - 58 IS - 3 ER - TY - JOUR A1 - Biehl, Stefanie C. A1 - Merz, Christian J. A1 - Dresler, Thomas A1 - Heupel, Julia A1 - Reichert, Susanne A1 - Jacob, Christian P. A1 - Deckert, Jürgen A1 - Herrmann, Martin J. T1 - Increase or Decrease of fMRI Activity in Adult Attention Deficit/ Hyperactivity Disorder: Does It Depend on Task Difficulty? JF - International Journal of Neuropsychopharmacology N2 - Background: Attention deficit/hyperactivity disorder has been shown to affect working memory, and fMRI studies in children and adolescents with attention deficit/hyperactivity disorder report hypoactivation in task-related attentional networks. However, studies with adult attention deficit/hyperactivity disorder patients addressing this issue as well as the effects of clinically valid methylphenidate treatment are scarce. This study contributes to closing this gap. Methods: Thirty-five adult patients were randomized to 6 weeks of double-blind placebo or methylphenidate treatment. Patients completed an fMRI n-back working memory task both before and after the assigned treatment, and matched healthy controls were tested and compared to the untreated patients. Results: There were no whole-brain differences between any of the groups. However, when specified regions of interest were investigated, the patient group showed enhanced BOLD responses in dorsal and ventral areas before treatment. This increase was correlated with performance across all participants and with attention deficit/hyperactivity disorder symptoms in the patient group. Furthermore, we found an effect of treatment in the right superior frontal gyrus, with methylphenidate-treated patients exhibiting increased activation, which was absent in the placebo-treated patients. Conclusions: Our results indicate distinct activation differences between untreated adult attention deficit/hyperactivity disorder patients and matched healthy controls during a working memory task. These differences might reflect compensatory efforts by the patients, who are performing at the same level as the healthy controls. We furthermore found a positive effect of methylphenidate on the activation of a frontal region of interest. These observations contribute to a more thorough understanding of adult attention deficit/hyperactivity disorder and provide impulses for the evaluation of therapy-related changes. KW - working memory KW - clinical trial KW - child memory KW - short-term methylphenidate brain KW - methylphenidate KW - adult attention deficit/hyperactivity disorder KW - fMRI KW - functional magnetic resonance imaging Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-147551 VL - 19 IS - 10 ER - TY - JOUR A1 - Akhrif, Atae A1 - Romanos, Marcel A1 - Domschke, Katharina A1 - Schmitt-Boehrer, Angelika A1 - Neufang, Susanne T1 - Fractal Analysis of BOLD Time Series in a Network Associated With Waiting Impulsivity JF - Frontiers in Physiology N2 - Fractal phenomena can be found in numerous scientific areas including neuroscience. Fractals are structures, in which the whole has the same shape as its parts. A specific structure known as pink noise (also called fractal or 1/f noise) is one key fractal manifestation, exhibits both stability and adaptability, and can be addressed via the Hurst exponent (H). FMRI studies using H on regional fMRI time courses used fractality as an important characteristic to unravel neural networks from artificial noise. In this fMRI-study, we examined 103 healthy male students at rest and while performing the 5-choice serial reaction time task. We addressed fractality in a network associated with waiting impulsivity using the adaptive fractal analysis (AFA) approach to determine H. We revealed the fractal nature of the impulsivity network. Furthermore, fractality was influenced by individual impulsivity in terms of decreasing fractality with higher impulsivity in regions of top-down control (left middle frontal gyrus) as well as reward processing (nucleus accumbens and anterior cingulate cortex). We conclude that fractality as determined via H is a promising marker to quantify deviations in network functions at an early stage and, thus, to be able to inform preventive interventions before the manifestation of a disorder. KW - fMRI KW - Hurst Exponent KW - frontal cortex KW - nucleus accumbens KW - biomarker KW - impulse control disorders Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-189191 SN - 1664-042X VL - 9 ER - TY - JOUR A1 - Blechert, Jens A1 - Meule, Adrian A1 - Busch, Niko A. A1 - Ohla, Kathrin T1 - Food-pics: an image database for experimental research on eating and appetite JF - Frontiers in Psychology N2 - Our current environment is characterized by the omnipresence of food cues. The sight and smell of real foods, but also graphically depictions of appetizing foods, can guide our eating behavior, for example, by eliciting food craving and influencing food choice. The relevance of visual food cues on human information processing has been demonstrated by a growing body of studies employing food images across the disciplines of psychology, medicine, and neuroscience. However, currently used food image sets vary considerably across laboratories and image characteristics (contrast, brightness, etc.) and food composition (calories, macronutrients, etc.) are often unspecified. These factors might have contributed to some of the inconsistencies of this research. To remedy this, we developed food-pics, a picture database comprising 568 food images and 315 non-food images along with detailed meta-data. A total of N = 1988 individuals with large variance in age and weight from German speaking countries and North America provided normative ratings of valence, arousal, palatability, desire to eat, recognizability and visual complexity. Furthermore, data on macronutrients (g), energy density (kcal), and physical image characteristics (color composition, contrast, brightness, size, complexity) are provided. The food-pics image database is freely available under the creative commons license with the hope that the set will facilitate standardization and comparability across studies and advance experimental research on the determinants of eating behavior. Read F KW - food-cues KW - standardized food images KW - ERP KW - image properties KW - anorexia nervosa KW - restrained eaters KW - high calorie KW - brain KW - weight loss KW - visual-attention KW - responses KW - cues KW - reward KW - hunger KW - fMRI KW - eating behavior KW - obesity KW - food pictures Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-115987 SN - 1664-1078 VL - 5 ER - TY - JOUR A1 - Likowski, Katja U. A1 - Mühlberger, Andreas A1 - Gerdes, Antje B. M. A1 - Wieser, Mattias J. A1 - Pauli, Paul A1 - Weyers, Peter T1 - Facial mimicry and the mirror neuron system: simultaneous acquisition of facial electromyography and functional magnetic resonance imaging N2 - Numerous studies have shown that humans automatically react with congruent facial reactions, i.e., facial mimicry, when seeing a vis-á-vis’ facial expressions. The current experiment is the first investigating the neuronal structures responsible for differences in the occurrence of such facial mimicry reactions by simultaneously measuring BOLD and facial EMG in an MRI scanner. Therefore, 20 female students viewed emotional facial expressions (happy, sad, and angry) of male and female avatar characters. During picture presentation, the BOLD signal as well as M. zygomaticus major and M. corrugator supercilii activity were recorded simultaneously. Results show prototypical patterns of facial mimicry after correction for MR-related artifacts: enhanced M. zygomaticus major activity in response to happy and enhanced M. corrugator supercilii activity in response to sad and angry expressions. Regression analyses show that these congruent facial reactions correlate significantly with activations in the IFG, SMA, and cerebellum. Stronger zygomaticus reactions to happy faces were further associated to increased activities in the caudate, MTG, and PCC. Corrugator reactions to angry expressions were further correlated with the hippocampus, insula, and STS. Results are discussed in relation to core and extended models of the mirror neuron system (MNS). KW - Psychologie KW - mimicry KW - EMG KW - fMRI KW - mirrorneuronsystem Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-75813 ER - TY - JOUR A1 - Xiu, Daiming A1 - Geiger, Maximilian J. A1 - Klaver, Peter T1 - Emotional face expression modulates occipital-frontal effective connectivity during memory formation in a bottom-up fashion JF - Frontiers in Behavioral Neuroscience N2 - This study investigated the role of bottom-up and top-down neural mechanisms in the processing of emotional face expression during memory formation. Functional brain imaging data was acquired during incidental learning of positive ("happy"), neutral and negative ("angry" or "fearful") faces. Dynamic Causal Modeling (DCM) was applied on the functional magnetic resonance imaging (fMRI) data to characterize effective connectivity within a brain network involving face perception (inferior occipital gyrus and fusiform gyrus) and successful memory formation related areas (hippocampus, superior parietal lobule, amygdala, and orbitofrontal cortex). The bottom-up models assumed processing of emotional face expression along feed forward pathways to the orbitofrontal cortex. The top-down models assumed that the orbitofrontal cortex processed emotional valence and mediated connections to the hippocampus. A subsequent recognition memory test showed an effect of negative emotion on the response bias, but not on memory performance. Our DCM findings showed that the bottom-up model family of effective connectivity best explained the data across all subjects and specified that emotion affected most bottom-up connections to the orbitofrontal cortex, especially from the occipital visual cortex and superior parietal lobule. Of those pathways to the orbitofrontal cortex the connection from the inferior occipital gyrus correlated with memory performance independently of valence. We suggest that bottom-up neural mechanisms support effects of emotional face expression and memory formation in a parallel and partially overlapping fashion. KW - medial temporal lobe KW - human orbitofrontal cortex KW - subsequent memory KW - recognition memory KW - fMRI KW - event-related fMRI KW - posterior parietal cortex KW - short-term-memory KW - human brain KW - prefrontal activity KW - neural mechanisms KW - Dynamic Causal Modeling KW - facial affect KW - memory formation Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-143211 VL - 9 IS - 90 ER - TY - JOUR A1 - Ewald, Heike A1 - Glotzbach-Schoon, Evelyn A1 - Gerdes, Antje B. M. A1 - Andreatta, Marta A1 - Müller, Mathias A1 - Mühlberger, Andreas A1 - Pauli, Paul T1 - Delay and trace fear conditioning in a complex virtual learning environment - neural substrates of extinction JF - Frontiers in Human Neuroscience N2 - Extinction is an important mechanism to inhibit initially acquired fear responses. There is growing evidence that the ventromedial prefrontal cortex (vmPFC) inhibits the amygdala and therefore plays an important role in the extinction of delay fear conditioning. To our knowledge, there is no evidence on the role of the prefrontal cortex in the extinction of trace conditioning up to now. Thus, we compared brain structures involved in the extinction of human delay and trace fear conditioning in a between-subjects-design in an fMRI study. Participants were passively guided through a virtual environment during learning and extinction of conditioned fear. Two different lights served as conditioned stimuli (CS); as unconditioned stimulus (US) a mildly painful electric stimulus was delivered. In the delay conditioning group (DCG) the US was administered with offset of one light (CS+), whereas in the trace conditioning group (TCG) the US was presented 4s after CS+ offset. Both groups showed insular and striatal activation during early extinction, but differed in their prefrontal activation. The vmPFC was mainly activated in the DCG, whereas the TCG showed activation of the dorsolateral prefrontal cortex (dlPFC) during extinction. These results point to different extinction processes in delay and trace conditioning. VmPFC activation during extinction of delay conditioning might reflect the inhibition of the fear response. In contrast, dlPFC activation during extinction of trace conditioning may reflect modulation of working memory processes which are involved in bridging the trace interval and hold information in short term memory. KW - prefrontal cortex KW - delay conditioning KW - trace conditioning KW - extinction KW - virtual reality KW - fMRI KW - medial prefrontal cortex KW - event-related FMRI KW - orbifrontal cortex KW - contextual fear Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-116230 SN - 1662-5161 VL - 8 IS - 323 ER -