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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.
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.
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.
Sustained anticipatory anxiety is central to Generalized Anxiety Disorder (GAD). During anticipatory anxiety, phasic threat responding appears to be mediated by the amygdala, while sustained threat responding seems related to the bed nucleus of the stria terminalis (BNST). Although sustained anticipatory anxiety in GAD patients was proposed to be associated with BNST activity alterations, firm evidence is lacking. We aimed to explore temporal characteristics of BNST and amygdala activity during threat anticipation in GAD patients. Nineteen GAD patients and nineteen healthy controls (HC) underwent functional magnetic resonance imaging (fMRI) during a temporally unpredictable threat anticipation paradigm. We defined phasic and a systematic variation of sustained response models for blood oxygen level-dependent responses during threat anticipation, to disentangle temporally dissociable involvement of the BNST and the amygdala. GAD patients relative to HC responded with increased phasic amygdala activity to onset of threat anticipation and with elevated sustained BNST activity that was delayed relative to the onset of threat anticipation. Both the amygdala and the BNST displayed altered responses during threat anticipation in GAD patients, albeit with different time courses. The results for the BNST activation hint towards its role in sustained threat responding, and contribute to a deeper understanding of pathological sustained anticipatory anxiety in GAD.
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.
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.
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 .