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.

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.

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.

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.

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.

Comparison of variants of canonical correlation analysis and partial least squares for combined analysis of MRI and genetic data.

The standard analysis approach in neuroimaging genetics studies is the mass-univariate linear modeling (MULM) approach. From a statistical view, however, this approach is disadvantageous, as it is computationally intensive, cannot account for complex multivariate relationships, and has to be corrected for multiple testing. In contrast, multivariate methods offer the opportunity to include combined information from multiple variants to discover meaningful associations between genetic and brain imaging data. We assessed three multivariate techniques, partial least squares correlation (PLSC), sparse canonical correlation analysis (sparse CCA) and Bayesian inter-battery factor analysis (Bayesian IBFA), with respect to their ability to detect multivariate genotype-phenotype associations. Our goal was to systematically compare these three approaches with respect to their performance and to assess their suitability for high-dimensional and multi-collinearly dependent data as is the case in neuroimaging genetics studies. In a series of simulations using both linearly independent and multi-collinear data, we show that sparse CCA and PLSC are suitable even for very high-dimensional collinear imaging data sets. Among those two, the predictive power was higher for sparse CCA when voxel numbers were below 400 times sample size and candidate SNPs were considered. Accordingly, we recommend Sparse CCA for candidate phenotype, candidate SNP studies. When voxel numbers exceeded 500 times sample size, the predictive power was the highest for PLSC. Therefore, PLSC can be considered a promising technique for multivariate modeling of high-dimensional brain-SNP-associations. In contrast, Bayesian IBFA cannot be recommended, since additional post-processing steps were necessary to detect causal relations. To verify the applicability of sparse CCA and PLSC, we applied them to an experimental imaging genetics data set provided for us. Most importantly, application of both methods replicated the findings of this data set.

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.

Slave to habit? Obesity is associated with decreased behavioural sensitivity to reward devaluation.

The motivational value of food is lower during satiety compared to fasting. Dynamic changes in motivational value promote food seeking or meal cessation. In obesity this mechanism might be compromised since obese subjects ingest energy beyond homeostatic needs. Thus, lower adaptation of eating behaviour with respect to changes in motivational value might cause food overconsumption in obesity. To test this hypothesis, we implemented a selective satiation procedure to investigate the relationship between obesity and the size of the behavioural devaluation effect in humans. Lean to obese men (mean age 25.9, range 19-30 years; mean BMI 29.1, range 19.2-45.1 kg/m(2)) were trained on a free operant paradigm and learned to associate cues with the possibility to win different food rewards by pressing a button. After the initial training phase, one of the rewards was devalued by consumption. Response rates for and wanting of the different rewards were measured pre and post devaluation. Behavioural sensitivity to reward devaluation, measured as the magnitude of difference between pre and post responses, was regressed against BMI. Results indicate that (1) higher BMI compared to lower BMI in men led to an attenuated behavioural adjustment to reward devaluation, and (2) the decrease in motivational value was associated with the decrease in response rate between pre and post. Change in explicitly reported motivational value, however, was not affected by BMI. Thus, we conclude that high BMI in men is associated with lower behavioural adaptation with respect to changes in motivational value of food, possibly resulting in automatic overeating patterns that are hard to control in daily life.

Ultra-high 7T MRI of structural age-related changes of the subthalamic nucleus.

The subthalamic nucleus (STh) is a small subcortical structure which is involved in regulating motor as well as cognitive functions. Due to its small size and close proximity to other small subcortical structures, it has been a challenge to localize and visualize it using magnetic resonance imaging (MRI). Currently there are several standard atlases available that are used to localize the STh in functional MRI studies and clinical procedures such as deep brain stimulation (DBS). DBS is an increasingly common neurosurgical procedure that has been successfully used to alleviate motor symptoms present in Parkinson's disease. However, current atlases are based on low sample sizes and restricted age ranges (Schaltenbrand and Wahren, 1977), and hence the use of these atlases effectively ignores the substantial structural brain changes that are associated with aging. In the present study, ultra-high field 7 tesla (T) magnetic resonance imaging (MRI) in humans was used to visualize and segment the STh in young, middle-aged, and elderly participants. The resulting probabilistic atlas maps for all age groups show that the STh shifts in the lateral direction with increasing age. In sum, the results of the present study suggest that age has to be taken into account in atlases for the optimal localization of the STh in healthy and diseased brains.

Response inhibition and its relation to multidimensional impulsivity.

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.

A gradual increase of iron toward the medial-inferior tip of the subthalamic nucleus.

The subthalamic nucleus (STN) is an important node of the cortico-basal ganglia network and the main target of deep brain stimulation (DBS) in Parkinson's disease. Histological studies have revealed an inhomogeneous iron distribution within the STN, which has been related to putative subdivisions within this nucleus. Here, we investigate the iron distribution in more detail using quantitative susceptibility mapping (QSM), a novel magnetic resonance imaging (MRI) contrast mechanism. QSM allows for detailed assessment of iron content in both in vivo and postmortem tissue. Twelve human participants and 7 postmortem brain samples containing the STN were scanned using ultra-high field 7 Tesla (T) MRI. Iron concentrations were found to be higher in the medial-inferior tip of the STN. Using quantitative methods we show that the increase of iron concentration towards the medial-inferior tip is of a gradual rather than a discrete nature.

Cortico-striatal connections predict control over speed and accuracy in perceptual decision making.

When people make decisions they often face opposing demands for response speed and response accuracy, a process likely mediated by response thresholds. According to the striatal hypothesis, people decrease response thresholds by increasing activation from cortex to striatum, releasing the brain from inhibition. According to the STN hypothesis, people decrease response thresholds by decreasing activation from cortex to subthalamic nucleus (STN); a decrease in STN activity is likewise thought to release the brain from inhibition and result in responses that are fast but error-prone. To test these hypotheses-both of which may be true-we conducted two experiments on perceptual decision making in which we used cues to vary the demands for speed vs. accuracy. In both experiments, behavioral data and mathematical model analyses confirmed that instruction from the cue selectively affected the setting of response thresholds. In the first experiment we used ultra-high-resolution 7T structural MRI to locate the STN precisely. We then used 3T structural MRI and probabilistic tractography to quantify the connectivity between the relevant brain areas. The results showed that participants who flexibly change response thresholds (as quantified by the mathematical model) have strong structural connections between presupplementary motor area and striatum. This result was confirmed in an independent second experiment. In general, these findings show that individual differences in elementary cognitive tasks are partly driven by structural differences in brain connectivity. Specifically, these findings support a cortico-striatal control account of how the brain implements adaptive switches between cautious and risky behavior.

Cortico-subthalamic white matter tract strength predicts interindividual efficacy in stopping a motor response.

The subthalamic nucleus (STN) is a small but vitally important structure in the basal ganglia. Because of its small volume, and its localization in the basal ganglia, the STN can best be visualized using ultra-high resolution 7 Tesla (T) magnetic resonance imaging (MRI). In the present study, first we individually segmented 7 T MRI STN masks to generate atlas probability maps. Secondly, the individually segmented STN masks and the probability maps were used to derive cortico-subthalamic white matter tract strength. Tract strength measures were then taken to test two functional STN hypotheses which account for the efficiency in stopping a motor response: the right inferior fronto-subthalamic (rIFC-STN) hypothesis and the posterior medial frontal cortex-subthalamic (pMFC-STN) hypothesis. Results of two independent experiments show that increased white matter tract strength between the pMFC and STN results in better stopping behaviour.

Direct visualization of the subthalamic nucleus and its iron distribution using high-resolution susceptibility mapping.

Histological studies have shown a relatively high iron concentration in the subthalamic nucleus (STN). T2- and T2*-weighted sequences have previously been used to visualize the STN in vivo. The phase information of gradient-echo images reflects the magnetic tissue properties more directly, e.g., iron is more paramagnetic than water. Unfortunately, phase images suffer from non-local effects and orientation dependency. The goal of this study is to delineate the STN more precisely using susceptibility maps, calculated from phase images, which directly index magnetic tissue properties while removing the non-local effects and orientation dependency. Use of 7T MRI enables high spatial resolution with good signal to noise ratio (SNR). Eight healthy subjects were scanned at 7T using a high-resolution 3D gradient-echo sequence. Susceptibility maps were calculated from phase data using a thresholding Fourier approach and a regularization approach using spatial priors. The susceptibility maps clearly distinguish the STN from the adjacent substantia nigra (SN). Their susceptibilities are quantitatively different (0.06 and 0.1 ppm for the STN and SN, respectively). These maps allowed the STN, SN, and the red nucleus to be manually segmented, thus providing 3D visualization of their boundaries. In sum, the STN can be more clearly distinguished from adjacent structures in susceptibility maps than in T2*-weighted images or phase images.

Exploring functional relations between brain regions from fMRI meta-analysis data: comments on Ramsey, Spirtes, and Glymour.

In this paper, we address the critical assessment of Ramsey et al. of our method for learning partially directed graphs from meta-analysis imaging data (Neumann et al., 2010). We argue that our method provides valid and interpretable results when applied to data representing a single experimental paradigm. Simulations further suggest that, despite theoretical limitations, the application of our method to mixed probability distributions yields reliable results with error rates at acceptable levels. Finally, we discuss the nature of meta-analysis data and the notion of causality in the context of functional neuroimaging.

Continuous theta-burst stimulation (cTBS) over the lateral prefrontal cortex alters reinforcement learning bias.

The prefrontal cortex is known to play a key role in higher-order cognitive functions. Recently, we showed that this brain region is active in reinforcement learning, during which subjects constantly have to integrate trial outcomes in order to optimize performance. To further elucidate the role of the dorsolateral prefrontal cortex (DLPFC) in reinforcement learning, we applied continuous theta-burst stimulation (cTBS) either to the left or right DLPFC, or to the vertex as a control region, respectively, prior to the performance of a probabilistic learning task in an fMRI environment. While there was no influence of cTBS on learning performance per se, we observed a stimulation-dependent modulation of reward vs. punishment sensitivity: Left-hemispherical DLPFC stimulation led to a more reward-guided performance, while right-hemispherical cTBS induced a more avoidance-guided behavior. FMRI results showed enhanced prediction error coding in the ventral striatum in subjects stimulated over the left as compared to the right DLPFC. Both behavioral and imaging results are in line with recent findings that left, but not right-hemispherical stimulation can trigger a release of dopamine in the ventral striatum, which has been suggested to increase the relative impact of rewards rather than punishment on behavior.

Striatum and pre-SMA facilitate decision-making under time pressure.

Human decision-making almost always takes place under time pressure. When people are engaged in activities such as shopping, driving, or playing chess, they have to continually balance the demands for fast decisions against the demands for accurate decisions. In the cognitive sciences, this balance is thought to be modulated by a response threshold, the neural substrate of which is currently subject to speculation. In a speed decision-making experiment, we presented participants with cues that indicated different requirements for response speed. Application of a mathematical model for the behavioral data confirmed that cueing for speed lowered the response threshold. Functional neuroimaging showed that cueing for speed activates the striatum and the pre-supplementary motor area (pre-SMA), brain structures that are part of a closed-loop motor circuit involved in the preparation of voluntary action plans. Moreover, activation in the striatum is known to release the motor system from global inhibition, thereby facilitating faster but possibly premature actions. Finally, the data show that individual variation in the activation of striatum and pre-SMA is selectively associated with individual variation in the amplitude of the adjustments in the response threshold estimated by the mathematical model. These results demonstrate that when people have to make decisions under time pressure their striatum and pre-SMA show increased levels of activation.

Adaptive coding of action values in the human rostral cingulate zone.

Correctly selecting appropriate actions in an uncertain environment requires gathering experience about the available actions by sampling them over several trials. Recent findings suggest that the human rostral cingulate zone (RCZ) is important for the integration of extended action-outcome associations across multiple trials and in coding the subjective value of each action. During functional magnetic resonance imaging, healthy volunteers performed two versions of a probabilistic reversal learning task with high (HP) or low (LP) reward probabilities that required them to integrate action-outcome relations over lower or higher numbers of trials, respectively. In the HP session, subjects needed fewer trials to adjust their behavior in response to a reversal of response-reward contingencies. Similarly, the learning rate derived from a reinforcement learning model was higher in the HP condition. This was accompanied by a stronger response of the RCZ to negative feedback upon reversals in the HP condition. Furthermore, RCZ activity related to negative reward prediction errors varied as a function of the learning rate, which determines to what extent the prediction error is used to update action values. These data show that RCZ responses vary as a function of the information content provided by the environment. The more likely a negative event indicates the need for behavioral adaptations, the more prominent is the response of the RCZ. Thus, both the window of trials over which reinforcement information is integrated and adjustment of action values in the RCZ covary with the stochastics of the environment.

Dopamine DRD2 polymorphism alters reversal learning and associated neural activity.

In humans, presence of an A1 allele of the DRD2/ANKK1-TaqIa polymorphism is associated with reduced expression of dopamine (DA) D(2) receptors in the striatum. Recently, it was observed that carriers of the A1 allele (A1+ subjects) showed impaired learning from negative feedback in a reinforcement learning task. Here, using functional MRI (fMRI), we investigated carriers and noncarriers of the A1 allele while they performed a probabilistic reversal learning task. A1+ subjects showed subtle deficits in reversal learning. In particular, these deficits consisted of an impairment in sustaining the newly rewarded response after a reversal and in a generally decreased tendency to stick with a rewarded response. Both genetic groups showed increased fMRI signal in response to negative feedback in the rostral cingulate zone (RCZ) and anterior insula. Negative feedback that incurred a change in behavior additionally engaged the ventral striatum and a region of the midbrain consistent with the location of dopaminergic cell groups. The response of the RCZ to negative feedback increased as a function of preceding negative feedback. However, this graded response was not observed in the A1+ group. Furthermore, the A1+ group also showed diminished recruitment of the right ventral striatum and the right lateral orbitofrontal cortex (lOFC) during reversals. Together, these results suggest that a genetically driven reduction in DA D(2) receptors leads to deficient feedback integration in RCZ. This, in turn, was accompanied by impaired recruitment of the ventral striatum and the right lOFC during reversals, which might explain the behavioral differences between the genetic groups.