Dopamine release, diffusion and uptake: A computational model for synaptic and volume transmission.

Computational modeling of dopamine transmission is challenged by complex underlying mechanisms. Here we present a new computational model that (I) simultaneously regards release, diffusion and uptake of dopamine, (II) considers multiple terminal release events and (III) comprises both synaptic and volume transmission by incorporating the geometry of the synaptic cleft. We were able to validate our model in that it simulates concentration values comparable to physiological values observed in empirical studies. Further, although synaptic dopamine diffuses into extra-synaptic space, our model reflects a very localized signal occurring on the synaptic level, i.e. synaptic dopamine release is negligibly recognized by neighboring synapses. Moreover, increasing evidence suggests that cognitive performance can be predicted by signal variability of neuroimaging data (e.g. BOLD). Signal variability in target areas of dopaminergic neurons (striatum, cortex) may arise from dopamine concentration variability. On that account we compared spatio-temporal variability in a simulation mimicking normal dopamine transmission in striatum to scenarios of enhanced dopamine release and dopamine uptake inhibition. We found different variability characteristics between the three settings, which may in part account for differences in empirical observations. From a clinical perspective, differences in striatal dopaminergic signaling contribute to differential learning and reward processing, with relevant implications for addictive- and compulsive-like behavior. Specifically, dopaminergic tone is assumed to impact on phasic dopamine and hence on the integration of reward-related signals. However, in humans DA tone is classically assessed using PET, which is an indirect measure of endogenous DA availability and suffers from temporal and spatial resolution issues. We discuss how this can lead to discrepancies with observations from other methods such as microdialysis and show how computational modeling can help to refine our understanding of DA transmission.

Enhanced Go and NoGo Learning in Individuals With Obesity.

Overeating in individuals with obesity is hypothesized to be partly caused by automatic action tendencies to food cues that have the potential to override goal-directed dietary restriction. Individuals with obesity are often characterized by alterations in the processing of such rewarding food, but also of non-food stimuli, and previous research has suggested a stronger impact on the execution of goal-directed actions in obesity. Here, we investigated whether Pavlovian cues can also corrupt the learning of new approach or withdrawal behavior in individuals with obesity. We employed a probabilistic Pavlovian-instrumental learning paradigm in which participants (29 normal-weight and 29 obese) learned to actively respond (Go learning) or withhold a response (NoGo learning) in order to gain monetary rewards or avoid losses. Participants were better at learning active approach responses (Go) in the light of anticipated rewards and at learning to withhold a response (NoGo) in the light of imminent punishments. Importantly, there was no evidence for a stronger corruption of instrumental learning in individuals with obesity. Instead, they showed better learning across conditions than normal-weight participants. Using a computational reinforcement learning model, we additionally found an increased learning rate in individuals with obesity. Previous studies have mostly reported a lower reinforcement learning performance in individuals with obesity. Our results contradict this and suggest that their performance is not universally impaired: Instead, while previous studies found reduced stimulus-value learning, individuals with obesity may show better action-value learning. Our findings highlight the need for a broader investigation of behavioral adaptation in obesity across different task designs and types of reinforcement learning.

Hemispheric asymmetries in resting-state EEG and fMRI are related to approach and avoidance behaviour, but not to eating behaviour or BMI.

Much of our behaviour is driven by two motivational dimensions-approach and avoidance. These have been related to frontal hemispheric asymmetries in clinical and resting-state EEG studies: Approach was linked to higher activity of the left relative to the right hemisphere, while avoidance was related to the opposite pattern. Increased approach behaviour, specifically towards unhealthy foods, is also observed in obesity and has been linked to asymmetry in the framework of the right-brain hypothesis of obesity. Here, we aimed to replicate previous EEG findings of hemispheric asymmetries for self-reported approach/avoidance behaviour and to relate them to eating behaviour. Further, we assessed whether resting fMRI hemispheric asymmetries can be detected and whether they are related to approach/avoidance, eating behaviour and BMI. We analysed three samples: Sample 1 (n = 117) containing EEG and fMRI data from lean participants, and Samples 2 (n = 89) and 3 (n = 152) containing fMRI data from lean, overweight and obese participants. In Sample 1, approach behaviour in women was related to EEG, but not to fMRI hemispheric asymmetries. In Sample 2, approach/avoidance behaviours were related to fMRI hemispheric asymmetries. Finally, hemispheric asymmetries were not related to either BMI or eating behaviour in any of the samples. Our study partly replicates previous EEG findings regarding hemispheric asymmetries and indicates that this relationship could also be captured using fMRI. Our findings suggest that eating behaviour and obesity are likely to be mediated by mechanisms not directly relating to frontal asymmetries in neuronal activation quantified with EEG and fMRI.

Liking and left amygdala activity during food versus nonfood processing are modulated by emotional context.

Emotions can influence our eating behaviors. Facing an acute stressor or being in a positive mood are examples of situations that tend to modify appetite. However, the question of how the brain integrates these emotion-related changes in food processing remains elusive. Here, we designed an emotional priming fMRI task to test if amygdala activity during food pictures differs depending on the emotional context. Fifty-eight female participants completed a novel emotional priming task, in which emotional images of negative, neutral, or positive situations were followed by pictures of either foods or objects. After priming in each trial, participants rated how much they liked the shown foods or objects. We analyzed how brain activity during the contrast "foods > objects" changed according to the emotional context-in the whole brain and in the amygdala. We also examined the potential effect of adiposity (i.e., waist circumference). We observed a higher difference between liking scores for foods and objects after positive priming than after neutral priming. In the left amygdala, activity in the contrast "foods > objects" was higher after neutral priming relative to negative priming. Waist circumference was not significantly related to this emotional priming effect on food processing. Our results suggest that emotional context alters food and nonfood perception, both in terms of liking scores and with regard to engagement of the left amygdala. Moreover, our findings indicate that emotional context has an impact on the salience advantage of food, possibly affecting eating behavior.

Atrophy in midbrain & cerebral/cerebellar pedunculi is characteristic for progressive supranuclear palsy - A double-validation whole-brain meta-analysis.

OBJECTIVE: Progressive supranuclear palsy (PSP) is an atypical parkinsonian syndrome characterized by vertical gaze palsy and postural instability. Midbrain atrophy is suggested as a hallmark, but it has not been validated systematically in whole-brain imaging. METHODS: We conducted whole-brain meta-analyses identifying disease-related atrophy in structural MRI. Eighteen studies were identified (N = 315 PSP, 393 controls) and separated into gray or white matter analyses (15/12). All patients were diagnosed according to the National Institute of Neurological Disorders and Stroke and the Society for PSP (NINDS-SPSP criteria, Litvan et al. (1996a)), which are now considered as PSP-Richardson syndrome (Höglinger et al., 2017). With overlay analyses, we double-validated two meta-analytical algorithms: anatomical likelihood estimation and seed-based D mapping. Additionally, we conducted region-of-interest effect size meta-analyses on radiological biomarkers and subtraction analyses differentiating PSP from Parkinson's disease. RESULTS: Whole brain meta-analyses revealed consistent gray matter atrophy in bilateral thalamus, anterior insulae, midbrain, and left caudate nucleus. White matter alterations were consistently detected in bilateral superior/middle cerebellar pedunculi, cerebral pedunculi, and midbrain atrophy. Region-of-interest meta-analyses demonstrated that midbrain metrics generally perform very well in distinguishing PSP from other parkinsonian syndromes with strong effect sizes. Subtraction analyses identified the midbrain as differentiating between PSP and Parkinson's disease. CONCLUSIONS: Our meta-analyses identify gray matter atrophy of the midbrain and white matter atrophy of the cerebral/cerebellar pedunculi and midbrain as characteristic for PSP. Results support the incorporation of structural MRI data, and particularly these structures, into the revised PSP diagnostic criteria.

FDG-PET hypometabolism is more sensitive than MRI atrophy in Parkinson's disease: A whole-brain multimodal imaging meta-analysis.

Recently, revised diagnostic criteria for Parkinson's disease (PD) were introduced (Postuma et al., 2015). Yet, except for well-established dopaminergic imaging, validated imaging biomarkers for PD are still missing, though they could improve diagnostic accuracy. We conducted systematic meta-analyses to identify PD-specific markers in whole-brain structural magnetic resonance imaging (MRI), [18F]-fluorodeoxyglucose-positron emission tomography (FDG-PET) and diffusion tensor imaging (DTI) studies. Overall, 74 studies were identified including 2323 patients and 1767 healthy controls. Studies were first grouped according to imaging modalities (MRI 50; PET 14; DTI 10) and then into subcohorts based on clinical phenotypes. To ensure reliable results, we combined established meta-analytical algorithms - anatomical likelihood estimation and seed-based D mapping - and cross-validated them in a conjunction analysis. Glucose hypometabolism was found using FDG-PET extensively in bilateral inferior parietal cortex and left caudate nucleus with both meta-analytic methods. This hypometabolism pattern was confirmed in subcohort analyses and related to cognitive deficits (inferior parietal cortex) and motor symptoms (caudate nucleus). Structural MRI showed only small focal gray matter atrophy in the middle occipital gyrus that was not confirmed in subcohort analyses. DTI revealed fractional anisotropy reductions in the cingulate bundle near the orbital and anterior cingulate gyri in PD. Our results suggest that FDG-PET reliably identifies consistent functional brain abnormalities in PD, whereas structural MRI and DTI show only focal alterations and rather inconsistent results. In conclusion, FDG-PET hypometabolism outperforms structural MRI in PD, although both imaging methods do not offer disease-specific imaging biomarkers for PD.

Altered monetary loss processing and reinforcement-based learning in individuals with obesity.

Individuals with obesity are often characterized by alterations in reward processing. This may affect how new information is used to update stimulus values during reinforcement-based learning. Here, we investigated obesity-related changes in non-food reinforcement processing, their impact on learning performance as well as the neural underpinnings of reinforcement-based learning in obesity. Nineteen individuals with obesity (BMI > = 30 kg/m2, 10 female) and 23 lean control participants (BMI 18.5-24.9 kg/m2, 11 female) performed a probabilistic learning task during functional magnetic resonance imaging (fMRI), in which they learned to choose between advantageous and disadvantageous choice options in separate monetary gain, loss, and neutral conditions. During learning individuals with obesity made a significantly lower number of correct choices and accumulated a significantly lower overall monetary outcome than lean control participants. FMRI analyses revealed aberrant medial prefrontal cortex responses to monetary losses in individuals with obesity. There were no significant group differences in the regional representation of prediction errors. However, we found evidence for increased functional connectivity between the ventral striatum and insula in individuals with obesity. The present results suggest that obesity is associated with aberrant value representations for monetary losses, alterations in functional connectivity during the processing of learning outcomes, as well as a decresased reinforcement-based learning performance. This may affect how new information is incorporated to adjust dysfunctional behavior and could be a factor contributing to the maintenance of dysfunctional eating behavior in obesity.

Cardiac Concomitants of Feedback and Prediction Error Processing in Reinforcement Learning.

Successful learning hinges on the evaluation of positive and negative feedback. We assessed differential learning from reward and punishment in a monetary reinforcement learning paradigm, together with cardiac concomitants of positive and negative feedback processing. On the behavioral level, learning from reward resulted in more advantageous behavior than learning from punishment, suggesting a differential impact of reward and punishment on successful feedback-based learning. On the autonomic level, learning and feedback processing were closely mirrored by phasic cardiac responses on a trial-by-trial basis: (1) Negative feedback was accompanied by faster and prolonged heart rate deceleration compared to positive feedback. (2) Cardiac responses shifted from feedback presentation at the beginning of learning to stimulus presentation later on. (3) Most importantly, the strength of phasic cardiac responses to the presentation of feedback correlated with the strength of prediction error signals that alert the learner to the necessity for behavioral adaptation. Considering participants' weight status and gender revealed obesity-related deficits in learning to avoid negative consequences and less consistent behavioral adaptation in women compared to men. In sum, our results provide strong new evidence for the notion that during learning phasic cardiac responses reflect an internal value and feedback monitoring system that is sensitive to the violation of performance-based expectations. Moreover, inter-individual differences in weight status and gender may affect both behavioral and autonomic responses in reinforcement-based learning.

Failing to learn from negative prediction errors: Obesity is associated with alterations in a fundamental neural learning mechanism.

Prediction errors (PEs) encode the difference between expected and actual action outcomes in the brain via dopaminergic modulation. Integration of these learning signals ensures efficient behavioral adaptation. Obesity has recently been linked to altered dopaminergic fronto-striatal circuits, thus implying impairments in cognitive domains that rely on its integrity. 28 obese and 30 lean human participants performed an implicit stimulus-response learning paradigm inside an fMRI scanner. Computational modeling and psycho-physiological interaction (PPI) analysis was utilized for assessing PE-related learning and associated functional connectivity. We show that human obesity is associated with insufficient incorporation of negative PEs into behavioral adaptation even in a non-food context, suggesting differences in a fundamental neural learning mechanism. Obese subjects were less efficient in using negative PEs to improve implicit learning performance, despite proper coding of PEs in striatum. We further observed lower functional coupling between ventral striatum and supplementary motor area in obese subjects subsequent to negative PEs. Importantly, strength of functional coupling predicted task performance and negative PE utilization. These findings show that obesity is linked to insufficient behavioral adaptation specifically in response to negative PEs, and to associated alterations in function and connectivity within the fronto-striatal system. Recognition of neural differences as a central characteristic of obesity hopefully paves the way to rethink established intervention strategies: Differential behavioral sensitivity to negative and positive PEs should be considered when designing intervention programs. Measures relying on penalization of unwanted behavior may prove less effective in obese subjects than alternative approaches.

Disentangling the neural correlates of corticobasal syndrome and corticobasal degeneration with systematic and quantitative ALE meta-analyses.

Corticobasal degeneration is a scarce neurodegenerative disease, which can only be confirmed by histopathological examination. Reported to be associated with various clinical syndromes, its classical clinical phenotype is corticobasal syndrome. Due to the rareness of corticobasal syndrome/corticobasal degeneration and low numbers of patients included in single studies, meta-analyses are particularly suited to disentangle features of the clinical syndrome and histopathology. Using PubMed, we identified 11 magnetic resonance imaging studies measuring atrophy in 22 independent cohorts with 200 patients contrasted to 318 healthy controls. The anatomic likelihood estimation method was applied to reveal affected brain regions across studies. Corticobasal syndrome was related to gray matter loss in the basal ganglia/thalamus, frontal, parietal, and temporal lobes. In corticobasal degeneration patients, atrophy in the thalamus, frontal, temporal, and occipital lobes were found. Finally, in a conjunction analysis, the bilateral thalamus, the bilateral posterior frontomedian cortex, posterior midcingulate cortex and premotor area/supplementary motor area, and the left posterior superior and middle frontal gyrus/precentral gyrus were identified as areas associated with both, corticobasal syndrome and corticobasal degeneration. Remarkably, atrophy in the premotor area/supplementary motor area and posterior midcingulate/frontomedian cortex seems to be specific for corticobasal syndrome/corticobasal degeneration, whereas atrophy in the thalamus and the left posterior superior and middle frontal gyrus/precentral gyrus are also associated with other neurodegenerative diseases according to anatomic likelihood estimation method meta-analyses. Our study creates a new conceptual framework to understand, and distinguish between clinical features (corticobasal syndrome) and histopathological findings (corticobasal degeneration) by powerful data-driven meta-analytic approaches. Furthermore, it proposes regional-specific atrophy as an imaging biomarker for diagnosis of corticobasal syndrome/corticobasal degeneration ante-mortem.

Corrigendum: Brain networks of perceptual decision-making: an fMRI ALE meta-analysis.

[This corrects the article on p. 445 in vol. 8, PMID: 24994979.].

Parasympathetic cardio-regulation during social interactions in individuals with obesity-The influence of negative body image.

Individuals with obesity in Western societies often face weight-related stigmatization and social exclusion. Recurrent exposure to prejudice and negative social feedback alters one's behavior in future social interactions. In this study, we aimed to investigate autonomic nervous system and affective responses to social interactions in individuals with obesity. Women and men with (n = 56) and without (n = 56) obesity participated in episodes of social inclusion and social exclusion using a virtual ball-tossing game. During the experiment, heart rate was measured and parasympathetic activity (overall high-frequency power and event-related cardiac slowing) was analyzed. Our results show that in novel social interactions, women with obesity, relative to the other groups, exhibited the strongest increase in parasympathetic activity. Furthermore, parasympathetic activity was related to a more negative body image in individuals with obesity, but not in lean individuals. Additionally, women with obesity reported a stronger decrease in mood after social exclusion than did the other participants. Our results demonstrate influences of objective and subjective bodily characteristics on parasympathetic cardio-regulation during social interactions. In particular, they show behavioral and physiological alterations during social interactions in women with obesity.

The role of dopamine in positive and negative prediction error utilization during incidental learning - Insights from Positron Emission Tomography, Parkinson's disease and Huntington's disease.

Incidental learning of appropriate stimulus-response associations is crucial for optimal functioning within our complex environment. Positive and negative prediction errors (PEs) serve as neural teaching signals within distinct ('direct'/'indirect') dopaminergic pathways to update associations and optimize subsequent behavior. Using a computational reinforcement learning model, we assessed learning from positive and negative PEs on a probabilistic task (Weather Prediction Task - WPT) in three populations that allow different inferences on the role of dopamine (DA) signals: (1) Healthy volunteers that repeatedly underwent [11C]raclopride Positron Emission Tomography (PET), allowing for assessment of striatal DA release during learning, (2) Parkinson's disease (PD) patients tested both on and off L-DOPA medication, (3) early Huntington's disease (HD) patients, a disease that is associated with hyper-activation of the 'direct' pathway. Our results show that learning from positive and negative feedback on the WPT is intimately linked to different aspects of dopaminergic transmission. In healthy individuals, the difference in [11C]raclopride binding potential (BP) as a measure for striatal DA release was linearly associated with the positive learning rate. Further, asymmetry between baseline DA tone in the left and right ventral striatum was negatively associated with learning from positive PEs. Female patients with early HD exhibited exaggerated learning rates from positive feedback. In contrast, dopaminergic tone predicted learning from negative feedback, as indicated by an inverted u-shaped association observed with baseline [11C]raclopride BP in healthy controls and the difference between PD patients' learning rate on and off dopaminergic medication. Thus, the ability to learn from positive and negative feedback is a sensitive marker for the integrity of dopaminergic signal transmission in the 'direct' and 'indirect' dopaminergic pathways. The present data are interesting beyond clinical context in that imbalances of dopaminergic signaling have not only been observed for neurological and psychiatric conditions but also been proposed for obesity and adolescence.

Stopping at the sight of food - How gender and obesity impact on response inhibition.

Recent research indicates that reduced inhibitory control is associated with higher body mass index (BMI), higher food craving and increased food intake. However, experimental evidence for the relationship between response inhibition and weight status is inconsistent and to date has been investigated predominantly in women. In the current study, 56 participants (26 obese, 30 lean; 27 female, 29 male) performed a Food Picture Rating Task followed by a Stop Signal Task where pictures of palatable high or low caloric food or non-food items were presented prior to the Go signal. We further assessed participants' self-reported eating behavior and trait impulsivity as potential factors influencing response inhibition, in particular within the food context. Independent of BMI, women showed significantly higher liking for low caloric food items than men. This was accompanied by shorter Stop Signal Reaction Times (SSRT) after high compared to low caloric food pictures for women, and shorter SSRT in women compared to men for high caloric food. No influence of gender on SSRT was observable outside of the food context. While SSRTs did not differ between obese and lean participants across the three picture categories, we found a moderating effect of trait impulsivity on the relationship between BMI and SSRT, specifically in the high caloric food context. Higher BMI was predictive of longer SSRT only for participants with low to normal trait impulsivity, pointing at a complex interplay between response inhibition, general impulsivity and weight status. Our results support the notion that individuals with obesity do not suffer from diminished response inhibition capacity per se. Rather, the ability to withhold a response depends on context and social norms, and strongly interacts with factors like gender and trait impulsivity.

Random Projection for Fast and Efficient Multivariate Correlation Analysis of High-Dimensional Data: A New Approach.

In recent years, the advent of great technological advances has produced a wealth of very high-dimensional data, and combining high-dimensional information from multiple sources is becoming increasingly important in an extending range of scientific disciplines. Partial Least Squares Correlation (PLSC) is a frequently used method for multivariate multimodal data integration. It is, however, computationally expensive in applications involving large numbers of variables, as required, for example, in genetic neuroimaging. To handle high-dimensional problems, dimension reduction might be implemented as pre-processing step. We propose a new approach that incorporates Random Projection (RP) for dimensionality reduction into PLSC to efficiently solve high-dimensional multimodal problems like genotype-phenotype associations. We name our new method PLSC-RP. Using simulated and experimental data sets containing whole genome SNP measures as genotypes and whole brain neuroimaging measures as phenotypes, we demonstrate that PLSC-RP is drastically faster than traditional PLSC while providing statistically equivalent results. We also provide evidence that dimensionality reduction using RP is data type independent. Therefore, PLSC-RP opens up a wide range of possible applications. It can be used for any integrative analysis that combines information from multiple sources.

Differential heart rate responses to social and monetary reinforcement in women with obesity.

Obesity is often accompanied by weight stigmatization; subsequently, individuals with obesity frequently face social rejection. It has been shown that recurrent negative social experiences can alter the perception of social cues. However, the way individuals with obesity process social stimuli is not well understood. This study aims to investigate obesity-related alterations in social compared to nonsocial information processing. Women with obesity (n = 14) and without obesity (n = 14) participated in a social and a monetary incentive delay task in which they anticipated and received positive, negative, and neutral outcomes in the form of faces or money. During the experiment, phasic heart rate changes and reaction times were measured. Women with obesity, compared to lean women, exhibited a stronger differentiation during the anticipation of monetary and social reinforcement, showing slower reaction times to social cues compared to monetary cues. During the outcome processing phase, women with obesity relative to controls demonstrated diminished heart rate responses particularly to negative social outcomes. Interestingly, differences in cardiac responses in participants with obesity were moderated by weight-related teasing experiences. In women with obesity, a higher BMI was associated with blunted cardiac responses to social cues relative to monetary cues only if they reported more emotional pain after weight-related teasing. Our results contribute to a better understanding of social information processing in obesity and give first evidence for the role of negative social experiences in reinforcement processing.

Identifying neural correlates of visual consciousness with ALE meta-analyses.

Neural correlates of consciousness (NCC) have been a topic of study for nearly two decades. In functional imaging studies, several regions have been proposed to constitute possible candidates for NCC, but as of yet, no quantitative summary of the literature on NCC has been done. The question whether single (striate or extrastriate) regions or a network consisting of extrastriate areas that project directly to fronto-parietal regions are necessary and sufficient neural correlates for visual consciousness is still highly debated [e.g., Rees et al., 2002, Nat Rev. Neurosci 3, 261-270; Tong, 2003, Nat Rev. Neurosci 4, 219-229]. The aim of this work was to elucidate this issue and give a synopsis of the present state of the art by conducting systematic and quantitative meta-analyses across functional magnetic resonance imaging (fMRI) studies using several standard paradigms for conscious visual perception. In these paradigms, consciousness is operationalized via perceptual changes, while the visual stimulus remains invariant. An activation likelihood estimation (ALE) meta-analysis was performed, representing the best approach for voxel-wise meta-analyses to date. In addition to computing a meta-analysis across all paradigms, separate meta-analyses on bistable perception and masking paradigms were conducted to assess whether these paradigms show common or different NCC. For the overall meta-analysis, we found significant clusters of activation in inferior and middle occipital gyrus; fusiform gyrus; inferior temporal gyrus; caudate nucleus; insula; inferior, middle, and superior frontal gyri; precuneus; as well as in inferior and superior parietal lobules. These results suggest a subcortical-extrastriate-fronto-parietal network rather than a single region that constitutes the necessary NCC. The results of our exploratory paradigm-specific meta-analyses suggest that this subcortical-extrastriate-fronto-parietal network might be differentially activated as a function of the paradigms used to probe for NCC.

Functional network centrality in obesity: A resting-state and task fMRI study.

Obesity is associated with structural and functional alterations in brain areas that are often functionally distinct and anatomically distant. This suggests that obesity is associated with differences in functional connectivity of regions distributed across the brain. However, studies addressing whole brain functional connectivity in obesity remain scarce. Here, we compared voxel-wise degree centrality and eigenvector centrality between participants with obesity (n=20) and normal-weight controls (n=21). We analyzed resting state and task-related fMRI data acquired from the same individuals. Relative to normal-weight controls, participants with obesity exhibited reduced degree centrality in the right middle frontal gyrus in the resting-state condition. During the task fMRI condition, obese participants exhibited less degree centrality in the left middle frontal gyrus and the lateral occipital cortex along with reduced eigenvector centrality in the lateral occipital cortex and occipital pole. Our results highlight the central role of the middle frontal gyrus in the pathophysiology of obesity, a structure involved in several brain circuits signaling attention, executive functions and motor functions. Additionally, our analysis suggests the existence of task-dependent reduced centrality in occipital areas; regions with a role in perceptual processes and that are profoundly modulated by attention.

The subthalamic nucleus during decision-making with multiple alternatives.

Several prominent neurocomputational models predict that an increase of choice alternatives is modulated by increased activity in the subthalamic nucleus (STN). In turn, increased STN activity allows prolonged accumulation of information. At the same time, areas in the medial frontal cortex such as the anterior cingulate cortex (ACC) and the pre-SMA are hypothesized to influence the information processing in the STN. This study set out to test concrete predictions of STN activity in multiple-alternative decision-making using a multimodal combination of 7 Tesla structural and functional Magnetic Resonance Imaging, and ancestral graph (AG) modeling. The results are in line with the predictions in that increased STN activity was found with an increasing amount of choice alternatives. In addition, our study shows that activity in the ACC is correlated with activity in the STN without directly modulating it. This result sheds new light on the information processing streams between medial frontal cortex and the basal ganglia.