[Show abstract][Hide abstract] ABSTRACT: Impulsivity is a multidimensional construct that has been suggested as a vulnerability factor for several psychiatric disorders, especially addiction disorders. Poor response inhibition may constitute one facet of impulsivity. Trait impulsivity can be assessed by self-report questionnaires such as the widely used Barratt Impulsiveness Scale (BIS-11). However, regarding the multidimensionality of impulsivity different concepts have been proposed, in particular the UPPS self-report questionnaire ('Urgency', 'Lack of Premeditation, 'Lack of Perseverance', 'Sensation Seeking') that is based on a factor analytic approach. The question as to which aspects of trait impulsivity map on individual differences of the behavioral and neural correlates of response inhibition so far remains unclear. In the present study, we investigated 52 healthy individuals that scored either very high or low on the BIS-11 and underwent a reward-modulated Stop-signal task during fMRI. Neither behavioral nor neural differences were observed with respect to high- and low-BIS groups. In contrast, UPPS subdomain Urgency best explained inter-individual variability in SSRT scores and was further negatively correlated to right IFG/aI activation in 'Stop>Go' trials - a key region for response inhibition. Successful response inhibition in rewarded compared to nonrewarded stop trials yielded ventral striatal (VS) activation which might represent a feedback signal. Interestingly, only participants with low Urgency scores were able to use this VS feedback signal for better response inhibition. Our findings indicate that the relationship of impulsivity and response inhibition has to be treated carefully. We propose Urgency as an important subdomain that might be linked to response inhibition as well as to the use of reward-based neural signals. Based on the present results, further studies examining the influence of impulsivity on psychiatric disorders should take into account Urgency as an important modulator of behavioral adaptation.
[Show abstract][Hide abstract] ABSTRACT: The fronto-limbic network interaction, driven by glutamatergic and dopaminergic neurotransmission, represents a core mechanism of motivated behavior and personality traits. Reward seeking behavior undergoes tremendous changes in adolescence paralleled by neurobiological changes of this network including the prefrontal cortex, striatum and amygdala. Since fronto-limbic dysfunctions also underlie major psychiatric diseases beginning in adolescence, this investigation focuses on network characteristics separating adolescents from adults. To investigate differences in network interactions, the brain reward system activity (slot machine task) together with frontal glutamate concentration (anterior cingulate cortex, ACC) was measured in 28 adolescents and 26 adults employing functional magnetic resonance imaging and magnetic resonance spectroscopy, respectively. An inverse coupling of glutamate concentrations in the ACC and activation of the ventral striatum was observed in adolescents. Further, amygdala response in adolescents was negatively correlated with the personality trait impulsivity. For adults, no significant associations of network components or correlations with impulsivity were found. The inverse association between frontal glutamate concentration and striatal activation in adolescents is in line with the triadic model of motivated behavior stressing the important role of frontal top-down inhibition on limbic structures. Our data identified glutamate as the mediating neurotransmitter of this inhibitory process and demonstrates the relevance of glutamate on the reward system and related behavioral traits like impulsivity. This fronto-limbic coupling may represent a vulnerability factor for psychiatric disorders starting in adolescence but not in adulthood.
Brain Structure and Function 07/2014; · 7.84 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Human and animal work suggests a shift from goal-directed to habitual decision-making in addiction. However, the evidence for this in human alcohol dependence is as yet inconclusive.
[Show abstract][Hide abstract] ABSTRACT: In experimental psychology different experiments have been developed to assess goal-directed as compared to habitual control over instrumental decisions. Similar to animal studies selective devaluation procedures have been used. More recently sequential decision-making tasks have been designed to assess the degree of goal-directed vs. habitual choice behavior in terms of an influential computational theory of model-based compared to model-free behavioral control. As recently suggested, different measurements are thought to reflect the same construct. Yet, there has been no attempt to directly assess the construct validity of these different measurements. In the present study, we used a devaluation paradigm and a sequential decision-making task to address this question of construct validity in a sample of 18 healthy male human participants. Correlational analysis revealed a positive association between model-based choices during sequential decisions and goal-directed behavior after devaluation suggesting a single framework underlying both operationalizations and speaking in favor of construct validity of both measurement approaches. Up to now, this has been merely assumed but never been directly tested in humans.
Frontiers in Human Neuroscience 01/2014; 8:587. · 2.91 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: While watching movies, the brain integrates the visual information and the musical soundtrack into a coherent percept. Multisensory integration can lead to emotion elicitation on which soundtrack valences may have a modulatory impact. Here, dynamic kissing scenes from romantic comedies were presented to 22 participants (13 females) during fMRI scanning. The kissing scenes were either accompanied by happy music, sad music or no music. Evidence from cross-modal studies motivated a predefined three-region network for multisensory integration of emotion, consisting of the fusiform gyrus (FG), the amygdala (AMY) and the anterior superior temporal gyrus (aSTG). The interactions in this network were investigated using dynamic causal models of effective connectivity. This revealed bilinear modulations by happy and sad music with suppression effects on the connectivity from FG and AMY to aSTG. Nonlinear dynamic causal modeling showed a suppressive gating effect of aSTG on fusiform-amygdalar connectivity. In conclusion, fusiform to amygdala coupling strength is modulated via feedback through aSTG as region for multisensory integration of emotional material. This mechanism was emotion-specific and more pronounced for sad music. Therefore, soundtrack valences may modulate emotion elicitation in movies by differentially changing preprocessed visual information to the amygdala.
Social Cognitive and Affective Neuroscience 12/2013; · 5.04 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Subjects with schizophrenia are impaired at reinforcement-driven reversal learning from as early as their first episode. The neurobiological basis of this deficit is unknown. We obtained behavioral and fMRI data in 24 unmedicated, primarily first episode, schizophrenia patients and 24 age-, IQ- and gender-matched healthy controls during a reversal learning task. We supplemented our fMRI analysis, focusing on learning from prediction errors, with detailed computational modeling to probe task solving strategy including an ability to deploy an internal goal directed model of the task. Patients displayed reduced functional activation in the ventral striatum (VS) elicited by prediction errors. However, modeling task performance revealed that a subgroup did not adjust their behavior according to an accurate internal model of the task structure, and these were also the more severely psychotic patients. In patients who could adapt their behavior, as well as in controls, task solving was best described by cognitive strategies according to a Hidden Markov Model. When we compared patients and controls who acted according to this strategy, patients still displayed a significant reduction in VS activation elicited by informative errors that precede salient changes of behavior (reversals). Thus, our study shows that VS dysfunction in schizophrenia patients during reward-related reversal learning remains a core deficit even when controlling for task solving strategies. This result highlights VS dysfunction is tightly linked to a reward-related reversal learning deficit in early, unmedicated schizophrenia patients.
[Show abstract][Hide abstract] ABSTRACT: In recent years, there has been increasing interest in research on geographical variation in the incidence of schizophrenia and other psychoses. In this paper, we review the evidence on variation in incidence of schizophrenia and other psychoses in terms of place, as well as the individual- and area-level factors that account for this variation. We further review findings on potential mechanisms that link adverse urban environment and psychosis. There is evidence from earlier and more recent studies that urbanicity is associated with an increased incidence of schizophrenia and non-affective psychosis. In addition, considerable variation in incidence across neighbourhoods has been observed for these disorders. Findings suggest it is unlikely that social drift alone can fully account for geographical variation in incidence. Evidence further suggests that the impact of adverse social contexts - indexed by area-level exposures such as population density, social fragmentation and deprivation - on risk of psychosis is explained (confounding) or modified (interaction) by environmental exposures at the individual level (i.e., cannabis use, social adversity, exclusion and discrimination). On a neurobiological level, several studies suggest a close link between social adversity, isolation and stress on the one hand, and monoamine dysfunction on the other, which resembles findings in schizophrenia patients. However, studies directly assessing correlations between urban stress or discrimination and neurobiological alterations in schizophrenia are lacking to date.
World psychiatry: official journal of the World Psychiatric Association (WPA) 10/2013; 12(3):187-197. · 8.97 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: This proof-of-concept study examines the feasibility of defining subgroups in psychiatric spectrum disorders by generative embedding, using dynamical system models which infer neuronal circuit mechanisms from neuroimaging data. To this end, we re-analysed an fMRI dataset of 41 patients diagnosed with schizophrenia and 42 healthy controls performing a numerical n-back working-memory task. In our generative-embedding approach, we used parameter estimates from a dynamic causal model (DCM) of a visual–parietal–prefrontal network to define a model-based feature space for the subsequent application of supervised and unsupervised learning techniques. First, using a linear support vector machine for classification, we were able to predict individual diagnostic labels significantly more accurately (78%) from DCM-based effective connectivity estimates than from functional connectivity between (62%) or local activity within the same regions (55%). Second, an unsupervised approach based on variational Bayesian Gaussian mixture modelling provided evidence for two clusters which mapped onto patients and controls with nearly the same accuracy (71%) as the supervised approach. Finally, when restricting the analysis only to the patients, Gaussian mixture modelling suggested the existence of three patient subgroups, each of which was characterised by a different architecture of the visual–parietal–prefrontal working-memory network. Critically, even though this analysis did not have access to information about the patients' clinical symptoms, the three neurophysiologically defined subgroups mapped onto three clinically distinct subgroups, distinguished by significant differences in negative symptom severity, as assessed on the Positive and Negative Syndrome Scale (PANSS). In summary, this study provides a concrete example of how psychiatric spectrum diseases may be split into subgroups that are defined in terms of neurophysiological mechanisms specified by a generative model of network dynamics such as DCM. The results corroborate our previous findings in stroke patients that generative embedding, compared to analyses of more conventional measures such as functional connectivity or regional activity, can significantly enhance both the interpretability and performance of computational approaches to clinical classification.
[Show abstract][Hide abstract] ABSTRACT: Abnormalities in reinforcement learning are a key finding in schizophrenia and have been proposed to be linked to elevated levels of dopamine neurotransmission. Behavioral deficits in reinforcement learning and their neural correlates may contribute to the formation of clinical characteristics of schizophrenia. The ability to form predictions about future outcomes is fundamental for environmental interactions and depends on neuronal teaching signals, like reward prediction errors. While aberrant prediction errors, that encode non-salient events as surprising, have been proposed to contribute to the formation of positive symptoms, a failure to build neural representations of decision values may result in negative symptoms. Here, we review behavioral and neuroimaging research in schizophrenia and focus on studies that implemented reinforcement learning models. In addition, we discuss studies that combined reinforcement learning with measures of dopamine. Thereby, we suggest how reinforcement learning abnormalities in schizophrenia may contribute to the formation of psychotic symptoms and may interact with cognitive deficits. These ideas point toward an interplay of more rigid versus flexible control over reinforcement learning. Pronounced deficits in the flexible or model-based domain may allow for a detailed characterization of well-established cognitive deficits in schizophrenia patients based on computational models of learning. Finally, we propose a framework based on the potentially crucial contribution of dopamine to dysfunctional reinforcement learning on the level of neural networks. Future research may strongly benefit from computational modeling but also requires further methodological improvement for clinical group studies. These research tools may help to improve our understanding of disease-specific mechanisms and may help to identify clinically relevant subgroups of the heterogeneous entity schizophrenia.
[Show abstract][Hide abstract] ABSTRACT: Age-related decline in cognitive speed has been associated with prefrontal dopamine D1 receptor availability, but the contribution of presynaptic dopamine and noradrenaline innervation to age-related changes in cognition is unknown.
In a group of 16 healthy participants aged 22-61 years, we used PET and the radioligand FDOPA to measure catecholamine synthesis capacity (K (in) (app); millilitres per gram per minute) and the digit symbol substitution test to measure cognitive speed, a component of fluid IQ.
Cognitive speed was associated with the magnitude of K (in) (app) in the prefrontal cortex (p < 0.0005). Both cognitive speed (p = 0.003) and FDOPA K (in) (app) (p < 0.0005) declined with age, both in a standard voxel-wise analysis and in a volume-of-interest analysis with partial volume correction, and the correlation between cognitive speed and K (in) (app) remained significant beyond the effects of age (p = 0.047). MR-based segmentation revealed that these age-related declines were not attributable to age-related alterations in grey matter density.
Our findings indicate that age-related changes in the capacity of the prefrontal cortex to synthesize catecholamines, irrespective of cortical atrophy, may underlie age-related decline in cognitive speed.
European Journal of Nuclear Medicine 06/2012; 39(9):1462-6. · 4.53 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The neural mechanisms behind cognitive deficits in schizophrenia still remain unclear. Functional neuroimaging studies on working memory (WM) yielded inconsistent results, suggesting task performance as a moderating variable of prefrontal activation. Beyond regional specific activation, disordered integration of brain regions was supposed as a critical pathophysiological mechanism of cognitive deficits in schizophrenia. Here, we first hypothesized that prefrontal activation implicated in WM depends primarily on task performance and therefore stratified participants into performance subgroups. Second, in line with the dysconnectivity hypothesis, we asked whether connectivity in the prefrontal-parietal network underlying WM is altered in all patients. We used functional magnetic resonance imaging in human subjects (41 schizophrenia patients, 42 healthy controls) and dynamic causal modeling to examine effective connectivity during a WM task. In line with our first hypothesis, we found that prefrontal activation was differentially modulated by task performance: there was a significant task by group by performance interaction revealing an increase of activation with performance in patients and a decrease with performance in controls. Beyond that, we show for the first time that WM-dependent effective connectivity from prefrontal to parietal cortex is reduced in all schizophrenia patients. This finding was independent of performance. In conclusion, our results are in line with the highly influential hypothesis that the relationship between WM performance and prefrontal activation follows an inverted U-shaped function. Moreover, this study in a large sample of patients reveals a mechanism underlying prefrontal inefficiency and cognitive deficits in schizophrenia, thereby providing direct experimental evidence for the dysconnectivity hypothesis.
Journal of Neuroscience 01/2012; 32(1):12-20. · 6.91 Impact Factor