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Adolescence has been linked to an enhanced tolerance of uncertainty and risky behavior and is possibly connected to an increased response toward rewards. However, previous research has produced inconsistent findings. To investigate whether these findings are due to different reward probabilities used in the experimental design, we extended a monetary incentive delay (MID) task by including three different reward probabilities. Using functional magnetic resonance imaging, 25 healthy adolescents and 22 adults were studied during anticipation of rewards in the VS. Differently colored cue stimuli indicated either a monetary or verbal trial and symbolized different reward probabilities, to which the participants were blinded. Results demonstrated faster reaction times for lower reward probabilities (33%) in both age groups. Adolescents were slower through all conditions and had less activation on a neural level. Imaging results showed a three-way interaction between age group x condition x reward probability with differences in percent signal change between adolescents and adults for the high reward probabilities (66%, 88%) while adolescents demonstrated differences for the lowest (33%). Therefore, previous inconsistent findings could be due to different reward probabilities, which makes examining these crucial for a better understanding of adolescent and adult behavior.
In human neuroscientific research, there has been an increasing interest in how the brain computes the value of an anticipated outcome. However, evidence is still missing about which valuation related brain regions are modulated by the proximity to an expected goal and the previously invested effort to reach a goal. The aim of this dissertation is to investigate the effects of goal proximity and invested effort on valuation related regions in the human brain. We addressed this question in two fMRI studies by integrating a commonly used reward anticipation task in differential versions of a Multitrial Reward Schedule Paradigm. In both experiments, subjects had to perform consecutive reward anticipation tasks under two different reward contingencies: in the delayed condition, participants received a monetary reward only after successful completion of multiple consecutive trials. In the immediate condition, money was earned after every successful trial. In the first study, we could demonstrate that the rostral cingulate zone of the posterior medial frontal cortex signals action value contingent to goal proximity, thereby replicating neurophysiological findings about goal proximity signals in a homologous region in non-human primates. The findings of the second study imply that brain regions associated with general cognitive control processes are modulated by previous effort investment. Furthermore, we found the posterior lateral prefrontal cortex and the orbitofrontal cortex to be involved in coding for the effort-based context of a situation. In sum, these results extend the role of the human rostral cingulate zone in outcome evaluation to the continuous updating of action values over a course of action steps based on the proximity to the expected reward. Furthermore, we tentatively suggest that previous effort investment invokes processes under the control of the executive system, and that posterior lateral prefrontal cortex and the orbitofrontal cortex are involved in an effort-based context representation that can be used for outcome evaluation that is dependent on the characteristics of the current situation.
Talking about emotion and sharing emotional experiences is a key component of human interaction. Specifically, individuals often consider the reactions of other people when evaluating the meaning and impact of an emotional stimulus. It has not yet been investigated, however, how emotional arousal ratings and physiological responses elicited by affective stimuli are influenced by the rating of an interaction partner. In the present study, pairs of participants were asked to rate and communicate the degree of their emotional arousal while viewing affective pictures. Strikingly, participants adjusted their arousal ratings to match up with their interaction partner. In anticipation of the affective picture, the interaction partner’s arousal ratings correlated positively with activity in anterior insula and prefrontal cortex. During picture presentation, social influence was reflected in the ventral striatum, that is, activity in the ventral striatum correlated negatively with the interaction partner’s ratings. Results of the study show that emotional alignment through the influence of another person’s communicated experience has to be considered as a complex phenomenon integrating different components including emotion anticipation and conformity.
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.
Rationale: Both attention deficit-/hyperactivity disorder (ADHD) and alcohol use disorder (AUD) are accompanied by deficits in response inhibition. Furthermore, the prevalence of comorbidity of ADHD and AUD is high. However, there is a lack of research on whether the same neuronal subprocesses of inhibition (i.e., interference inhibition, action withholding and action cancellation) exhibit deficits in both psychiatric disorders. Methods: We examined these three neural subprocesses of response inhibition in patient groups and healthy controls: non-medicated individuals with ADHD (ADHD; N = 16), recently detoxified and abstinent individuals with alcohol use disorder (AUD; N = 15), and healthy controls (HC; N = 15). A hybrid response inhibition task covering interference inhibition, action withholding, and action cancellation was applied using a 3T functional magnetic resonance imaging (fMRI). Results: Individuals with ADHD showed an overall stronger hypoactivation in attention related brain areas compared to AUD or HC during action withholding. Further, this hypoactivation was more accentuated during action cancellation. Individuals with AUD recruited a broader network, including the striatum, compared to HC during action withholding. During action cancellation, however, they showed hypoactivation in motor regions. Additionally, specific neural activation profiles regarding group and subprocess became apparent. Conclusions: Even though deficits in response inhibition are related to both ADHD and AUD, neural activation and recruited networks during response inhibition differ regarding both neuronal subprocesses and examined groups. While a replication of this study is needed in a larger sample, the results suggest that tasks have to be carefully selected when examining neural activation patterns of response inhibition either in research on various psychiatric disorders or transdiagnostic questions.
Pattern recognition applied to whole-brain neuroimaging data, such as functional Magnetic Resonance Imaging (fMRI), has proved successful at discriminating psychiatric patients from healthy participants. However, predictive patterns obtained from whole-brain voxel-based features are difficult to interpret in terms of the underlying neurobiology. Many psychiatric disorders, such as depression and schizophrenia, are thought to be brain connectivity disorders. Therefore, pattern recognition based on network models might provide deeper insights and potentially more powerful predictions than whole-brain voxel-based approaches. Here, we build a novel sparse network-based discriminative modeling framework, based on Gaussian graphical models and L1-norm regularized linear Support Vector Machines (SVM). In addition, the proposed framework is optimized in terms of both predictive power and reproducibility/stability of the patterns. Our approach aims to provide better pattern interpretation than voxel-based whole-brain approaches by yielding stable brain connectivity patterns that underlie discriminative changes in brain function between the groups. We illustrate our technique by classifying patients with major depressive disorder (MDD) and healthy participants, in two (event- and block-related) fMRI datasets acquired while participants performed a gender discrimination and emotional task, respectively, during the visualization of emotional valent faces.
Human deep sleep is characterized by reduced sensory activity, responsiveness to stimuli, and conscious awareness. Given its ubiquity and reversible nature, it represents an attractive paradigm to study the neural changes which accompany the loss of consciousness in humans. In particular, the deepest stages of sleep can serve as an empirical test for the predictions of theoretical models relating the phenomenology of consciousness with underlying neural activity. A relatively recent shift of attention from the analysis of evoked responses toward spontaneous (or “resting state”) activity has taken place in the neuroimaging community, together with the development of tools suitable to study distributed functional interactions. In this review we focus on recent functional Magnetic Resonance Imaging (fMRI) studies of spontaneous activity during sleep and their relationship with theoretical models for human consciousness generation, considering the global workspace theory, the information integration theory, and the dynamical core hypothesis. We discuss the venues of research opened by these results, emphasizing the need to extend the analytic methodology in order to obtain a dynamical picture of how functional interactions change over time and how their evolution is modulated during different conscious states. Finally, we discuss the need to experimentally establish absent or reduced conscious content, even when studying the deepest sleep stages.
Das ereigniskorrelierte Potential (EKP) P300 ist eines der am häufigsten untersuchten Potentiale des Elektroenzephalogramms (EEG). Wegen der bedeutsamen Rolle der P300 in der kognitiven Forschung mit gesunden Probanden und psychiatrischen Patienten kommt der Suche nach ihren neuronalen Generatoren ein hoher Stellenwert zu. Man geht im Allgemeinen davon aus, dass sie kein einheitliches Potential darstellt und von mehreren weit verstreuten Quellen generiert wird. Die Fragen nach der genauen Anzahl der P300-Subkomponenten, ihrer Lokalisierung sowie den ihnen zugrunde liegenden kognitiven Prozesse sind jedoch nach wie vor ungelöst. Die Zielsetzung der vorliegenden Arbeit war, die P300 mit Hilfe der Kombination vom EEG und der funktionalen Magnetresonanztomografie (fMRT) in ihre Subkomponenten zu untergliedern und deren Quellen zu lokalisieren. Zu diesem Zweck wurden drei kombinierte EEG/fMRT-Studien durchgeführt. Die ersten beiden Studien beinhalten eine abgewandelte Form des klassischen Oddballparadigmas. Bei der dritten Studie handelt es sich um ein Arbeitsgedächtnisexperiment. Durch die Verknüpfung der fMRT-Ergebnisse mit EKP-Daten aus den beiden Oddball-Experimenten konnten die neuronalen Quellen der zwei wichtigsten Subkomponenten der P300, der P3a und P3b, lokalisiert werden. Es konnte gezeigt werden, dass inferiore und posteriore parietale (IPL bzw. PPC) und inferior temporale (IT) Areale zur Entstehung der P3b beitrugen, während hauptsächlich die präzentralen Regionen (PrCS) die P3a generierten. Die Ergebnisse des Arbeitsgedächtnisexperiments bestätigten die P3b-Quellenlokalisierung der Oddball-Untersuchung mit einr Beteiligung von PPC und IT an der Generierung der P3b-Komponente. Das Arbeitsgedächtnisexperiment verdeutlichte aber auch, dass eine komplexere Abrufanforderung (mit langen Reaktionszeiten) zu einer anhaltenden Aktivität im PPC und einer späten Antwort im ventrolateralen präfrontalen Kortex (VLPFC) führte, die eine zweite P3b-Subkomponente generierten. Durch eine umfassende zeitlich-räumliche Trennung der neuronalen Aktivität beim Arbeitsgedächtnisabruf konnten darüber hinaus die einzelnen Stufen der beteiligten Informationsverarbeitungsprozesse (mentale Chronometrie) beschrieben werden. Diese Anwendung ging über die „reine“ Quellenlokalisation der P300-Komponenten hinaus. Die Ergebnisse zeigten frühe transiente Aktivierungen im IT, die sich zeitlich mit dem Beginn einer anhaltenden Aktivität im PPC überlappten. Darüber hinaus wurden eine späte transiente Aktivität im VLPFC und eine späte anhaltende Aktivität im medialen frontalen und motorischen Kortex (MFC bzw. MC) beobachtet. Es liegt nahe, dass diese neuronalen Signaturen einzelne Stufen kognitiver Aufgabenverarbeitungsschritte wie Reizevaluation (IT), Operationen am Gedächtnispuffer (PPC), aktiven Abruf (VLPFC) und Reaktionsorganisation (MFC und MC) reflektieren. Die vorgestellten Quellenmodelle zeigten übereinstimmend, dass mehrere kortikale Generatoren das P300-EKP erzeugen. Dabei trugen neben den erwarteten parietalen interessanterweise auch inferior temporale und inferior frontale Quellen zur P3b bei, während die P3a vor allem auf anterioren Generatoren im prämotorischen Kortex basierte. Diese Ergebnisse bestätigen teilweise die bisherigen Lokalisationsmodelle, die weitgehend auf neuropsychologischen und invasiven neurophysiologischen Befunden beruhen, widersprechen ihnen aber auch zum Teil, besonders was die Abwesenheit der postulierten präfrontalen und hippocampalen Beiträge zur P3a bzw. P3b betrifft.
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.
In recent years, a number of functional and structural neuroimaging studies have investigated the neural bases of aggressive and violent behaviour in children and adolescents. Most functional neuroimaging studies have persued the hypothesis that pathological aggression is a consequence of deficits in the neural circuits involved in emotion processing. There is converging evidence for abnormal neural responses to emotional stimuli in youths with a propensity towards aggressive behaviour. In addition, recent neuroimaging work has suggested that aggressive behaviour is also associated with abnormalities in neural processes that subserve both the inhibitory control of behaviour and the flexible adaptation of behaviour in accord with reinforcement information. Structural neuroimaging studies in children and adolescents with conduct problems are still scarce, but point to deficits in brain structures involved in the processing of social information and in the regulation of social and goal-directed behaviour. The indisputable progress that this research field has made in recent years notwithstanding, the overall picture is still rather patchy and there are inconsistencies between studies that await clarification. Despite this, we attempt to provide an integrated view on the neural abnormalities that may contribute to various forms of juvenile aggression and violence, and discuss research strategies that may help to provide a more profound understanding of these important issues in the future. Keywords: aggression, violence, conduct disorder, fMRI, brain imaging, psychiatry