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In dialogue, language processing is adapted to the conversational partner. We hypothesize that the brain facilitates partner-adapted language processing through preparatory neural configurations (task sets) that are tailored to the conversational partner. In this experiment, we measured neural activity with functional magnetic resonance imaging (fMRI) while healthy participants in the scanner (a) engaged in a verbal communication task with a conversational partner outside of the scanner, or (b) spoke outside of a conversational context (to test the microphone). Using multivariate searchlight analysis, we identify cortical regions that represent information on whether speakers plan to speak to a conversational partner or without having a partner. Most notably a region that has been associated with processing social-affective information and perspective taking, the ventromedial prefrontal cortex, as well as regions that have been associated with prospective task representation, the bilateral ventral prefrontal cortex, are involved in encoding the speaking condition. Our results suggest that speakers prepare, in advance of speaking, for the social context in which they will speak., (© The Author (2017). Published by Oxford University Press.)

Focused attention meditations have been shown to improve psychological health and wellbeing and are nowadays an integral part of many psychotherapies. While research on the neural correlates of focused attention meditation is increasing, findings vary on whether meditations are associated with high or low activity in the default mode network (DMN). To clarify the relationship between focused attention meditation and the activity in DMN regions, it may be helpful to distinguish internal and external attention as well as different phases within one meditation: During focused attention meditation, the practitioner switches between mindful attention, mind-wandering and refocusing. Here, we employed a thought-probe paradigm to study the neural correlates of these different phases. Twenty healthy, meditation naïve participants were introduced to external (mindfulness of sound) and internal (mindfulness of breathing) attention meditation and then practiced the meditation at home for four consecutive days. They then performed the same focused attention meditations during fMRI scanning, in four runs alternating between internal and external attention. At pseudorandom intervals, participants were asked whether they had just been focused on the task (mindful attention) or had been distracted (mind-wandering). During mindful attention, brain regions typically associated with the DMN, such as the medial prefrontal cortex, posterior cingulate cortex and left temporoparietal junction showed significantly less neural activation compared to mind-wandering phases. Reduced activity of the DMN was found during both external and internal attention, with stronger deactivation in the posterior cingulate cortex during internal attention compared to external attention. Moreover, refocusing after mind-wandering was associated with activity in the left inferior frontal gyrus. Our results support the theory that mindful attention is associated with reduced DMN activity compared to mind-wandering, independent of the practitioner's attention focus (i.e., internal vs. external)., (Copyright © 2017 Elsevier Inc. All rights reserved.)

There is an ongoing debate in philosophy and psychology about when one should consider an action to be free. Several aspects are frequently suggested as relevant: (a) a prior intention, (b) a conscious action-related thought, (c) prior deliberation, (d) a meaningful choice, (e) different consequences of the action, and (f) the duration between intention and action. Here we investigated which criteria laypeople adopt and thus probed their intuitions about free actions in three surveys based on daily life scenarios. First, our results indicate that laypeople consider a conscious intention important for an action to be free. Second, laypeople consider spontaneous actions without consequences to be freer than actions with prior deliberation. Third, laypeople consider proximal rather than distal intentions relevant when it comes to judging actions as free. Taken together, these results suggest that simple laboratory experiments on action choices reflect laypeople's intuitions of free actions to a considerable degree., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Studies in humans and non-human primates have provided evidence for storage of working memory contents in multiple regions ranging from sensory to parietal and prefrontal cortex. We discuss potential explanations for these distributed representations: (i) features in sensory regions versus prefrontal cortex differ in the level of abstractness and generalizability; and (ii) features in prefrontal cortex reflect representations that are transformed for guidance of upcoming behavioral actions. We propose that the propensity to produce persistent activity is a general feature of cortical networks. Future studies may have to shift focus from asking where working memory can be observed in the brain to how a range of specialized brain areas together transform sensory information into a delayed behavioral response., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Prospective clinical studies support a link between psychological stress and multiple sclerosis (MS) disease severity, and peripheral stress systems are frequently dysregulated in MS patients. However, the exact link between neurobiological stress systems and MS symptoms is unknown. To evaluate the link between neural stress responses and disease parameters, we used an arterial-spin-labeling functional MRI stress paradigm in 36 MS patients and 21 healthy controls. Specifically, we measured brain activity during a mental arithmetic paradigm with performance-adaptive task frequency and performance feedback and related this activity to disease parameters. Across all participants, stress increased heart rate, perceived stress, and neural activity in the visual, cerebellar and insular cortex areas compared with a resting condition. None of these responses was related to cognitive load (task frequency). Consistently, although performance and cognitive load were lower in patients than in controls, stress responses did not differ between groups. Insula activity elevated during stress compared with rest was negatively linked to impairment of pyramidal and cerebral functions in patients. Cerebellar activation was related negatively to gray matter (GM) atrophy (i.e., positively to GM volume) in patients. Interestingly, this link was also observed in overlapping areas in controls. Cognitive load did not contribute to these associations. The results show that our task induced psychological stress independent of cognitive load. Moreover, stress-induced brain activity reflects clinical disability in MS. Finally, the link between stress-induced activity and GM volume in patients and controls in overlapping areas suggests that this link cannot be caused by the disease alone., Competing Interests: The authors declare no conflict of interest.

In multivariate pattern analysis of neuroimaging data, 'second-level' inference is often performed by entering classification accuracies into a t-test vs chance level across subjects. We argue that while the random-effects analysis implemented by the t-test does provide population inference if applied to activation differences, it fails to do so in the case of classification accuracy or other 'information-like' measures, because the true value of such measures can never be below chance level. This constraint changes the meaning of the population-level null hypothesis being tested, which becomes equivalent to the global null hypothesis that there is no effect in any subject in the population. Consequently, rejecting it only allows to infer that there are some subjects in which there is an information effect, but not that it generalizes, rendering it effectively equivalent to fixed-effects analysis. This statement is supported by theoretical arguments as well as simulations. We review possible alternative approaches to population inference for information-based imaging, converging on the idea that it should not target the mean, but the prevalence of the effect in the population. One method to do so, 'permutation-based information prevalence inference using the minimum statistic', is described in detail and applied to empirical data., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Voxel-wise general linear models (GLMs) are a standard approach for analyzing functional magnetic resonance imaging (fMRI) data. An advantage of GLMs is that they are flexible and can be adapted to the requirements of many different data sets. However, the specification of first-level GLMs leaves the researcher with many degrees of freedom which is problematic given recent efforts to ensure robust and reproducible fMRI data analysis. Formal model comparisons that allow a systematic assessment of GLMs are only rarely performed. On the one hand, too simple models may underfit data and leave real effects undiscovered. On the other hand, too complex models might overfit data and also reduce statistical power. Here we present a systematic approach termed cross-validated Bayesian model selection (cvBMS) that allows to decide which GLM best describes a given fMRI data set. Importantly, our approach allows for non-nested model comparison, i.e. comparing more than two models that do not just differ by adding one or more regressors. It also allows for spatially heterogeneous modelling, i.e. using different models for different parts of the brain. We validate our method using simulated data and demonstrate potential applications to empirical data. The increased use of model comparison and model selection should increase the reliability of GLM results and reproducibility of fMRI studies., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: The cause of cognitive impairment in acutely hospitalized geriatric patients is often unclear. The diagnostic process is challenging but important in order to treat potentially life-threatening etiologies or identify underlying neurodegenerative disease., Objective: To evaluate the add-on diagnostic value of structural and metabolic neuroimaging in newly manifested cognitive impairment in elderly geriatric inpatients., Methods: Eighty-one inpatients (55 females, 81.6±5.5 y) without history of cognitive complaints prior to hospitalization were recruited in 10 acute geriatrics clinics. Primary inclusion criterion was a clinical hypothesis of Alzheimer's disease (AD), cerebrovascular disease (CVD), or mixed AD+CVD etiology (MD), which remained uncertain after standard diagnostic workup. Additional procedures performed after enrollment included detailed neuropsychological testing and structural MRI and FDG-PET of the brain. An interdisciplinary expert team established the most probable etiologic diagnosis (non-neurodegenerative, AD, CVD, or MD) integrating all available data. Automatic multimodal classification based on Random Undersampling Boosting was used for rater-independent assessment of the complementary contribution of the additional diagnostic procedures to the etiologic diagnosis., Results: Automatic 4-class classification based on all diagnostic routine standard procedures combined reproduced the etiologic expert diagnosis in 31% of the patients (p = 0.100, chance level 25%). Highest accuracy by a single modality was achieved by MRI or FDG-PET (both 45%, p≤0.001). Integration of all modalities resulted in 76% accuracy (p≤0.001)., Conclusion: These results indicate substantial improvement of diagnostic accuracy in uncertain de novo cognitive impairment in acutely hospitalized geriatric patients with the integration of structural MRI and brain FDG-PET into the diagnostic process.

Several brain regions appear to play a role in representing different body identities. The specific contribution of each of these regions is still unclear, however. Here we investigated which brain areas enable the visual distinction between self and other bodies of different familiarity, and between familiar and unfamiliar other individuals, and moreover, where identity-specific information on the three individuals was encoded. Participants were confronted with standardized headless human body stimuli either showing the participant's own, a personally familiar or an unfamiliar other body, while performing a luminance discrimination task. Employing multivariate pattern analysis, we were able to identify areas that allowed for the distinction of self from personal familiar other bodies within the medial prefrontal cortex (mPFC) and posterior cingulate cortex/precuneus. Successful distinction of self from unfamiliar others was possible in the left middle frontal gyrus, the right inferior frontal gyrus, the left pre-supplementary motor area and the right putamen. Personally familiar others could be distinguished from unfamiliar others in the right temporoparietal junction (TPJ). An analysis of identity-specific information revealed a spatial gradient ranging from inferior posterior to superior anterior portions of the mPFC that was associated with encoding identity-related information for self via familiar to unfamiliar other bodies, respectively. Furthermore, several midline and frontal regions encoded information on more than one identity. The TPJ's role in deviance detection was underlined, as only identity-specific information on unfamiliar others was encoded here. Together, our findings suggest substantial spatial overlap in neural correlates of self and other body representation and thus, support the hypothesis of a socially-related representation of the self., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The affective value of a stimulus substantially influences its potency to gain access to awareness. Here, we sought to elucidate the neural mechanisms underlying such affective salience in a combined behavioral and fMRI experiment. Healthy individuals with varying degrees of spider phobia were presented with pictures of spiders and flowers suppressed from view by continuous flash suppression. Applying multivoxel pattern analysis, we found that the average time that spider stimuli took relative to flowers to gain access to awareness in each participant could be decoded from fMRI signals evoked by suppressed spider versus flower stimuli in occipitotemporal and orbitofrontal cortex. Our results indicate neural signals during unconscious processing of complex visual information in orbitofrontal and ventral visual areas predict access to awareness of this information, suggesting a crucial role for these higher-level cortical regions in mediating affective salience., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

A defining trait of human cognition is the capacity to form compounds out of simple thoughts. This ability relies on the logical connectives AND, OR and IF. Simple propositions, e.g., 'There is a fork' and 'There is a knife', can be combined in alternative ways using logical connectives: e.g., 'There is a fork AND there is a knife', 'There is a fork OR there is a knife', 'IF there is a fork, there is a knife'. How does the brain represent compounds based on different logical connectives, and how are compounds evaluated in relation to new facts? In the present study, participants had to maintain and evaluate conjunctive (AND), disjunctive (OR) or conditional (IF) compounds while undergoing functional MRI. Our results suggest that, during maintenance, the left posterior inferior frontal gyrus (pIFG, BA44, or Broca's area) represents the surface form of compounds. During evaluation, the left pIFG switches to processing the full logical meaning of compounds, and two additional areas are recruited: the left anterior inferior frontal gyrus (aIFG, BA47) and the left intraparietal sulcus (IPS, BA40). The aIFG shows a pattern of activation similar to pIFG, and compatible with processing the full logical meaning of compounds, whereas activations in IPS differ with alternative interpretations of conditionals: logical vs conjunctive. These results uncover the functions of a basic cortical network underlying human compositional thought, and provide a shared neural foundation for the cognitive science of language and reasoning., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Intentional action is essential to human behavior, yet its neural basis remains poorly understood. In order to identify neural networks specifically involved in intentional action, freely chosen and externally cued intentions have previously been contrasted. This has led to the identification of a fronto-parietal network, which is involved in freely choosing one's intentions. However, it remains unclear whether this network encodes specific intentions, or whether it merely reflects general preparatory or control processes correlated with intentional action. Here, we used MVPA on fMRI data to identify brain regions encoding non-motor intentions that were either freely chosen or externally cued. We found that a fronto-parietal network, including the lateral prefrontal cortex, premotor, and parietal cortex, contained information about both freely chosen and externally cued intentions. Importantly, MVPA cross-classification indicated that this network represents the content of our intentions similarly, regardless of whether these intentions are freely chosen or externally cued. This finding suggests that the intention network has a general role in processing and representing intentions independent of their origin., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Being able to comprehend another person's intentions and emotions is essential for successful social interaction. However, it is currently unknown whether the human brain possesses a neural mechanism that attracts people to others whose mental states they can easily understand. Here we show that the degree to which a person feels attracted to another person can change while they observe the other's affective behavior, and that these changes depend on the observer's confidence in having correctly understood the other's affective state. At the neural level, changes in interpersonal attraction were predicted by activity in the reward system of the observer's brain. Importantly, these effects were specific to individual observer-target pairs and could not be explained by a target's general attractiveness or expressivity. Furthermore, using multivoxel pattern analysis (MVPA), we found that neural activity in the reward system of the observer's brain varied as a function of how well the target's affective behavior matched the observer's neural representation of the underlying affective state: The greater the match, the larger the brain's intrinsic reward signal. Taken together, these findings provide evidence that reward-related neural activity during social encounters signals how well an individual's "neural vocabulary" is suited to infer another person's affective state, and that this intrinsic reward might be a source of changes in interpersonal attraction.

In humans, spontaneous movements are often preceded by early brain signals. One such signal is the readiness potential (RP) that gradually arises within the last second preceding a movement. An important question is whether people are able to cancel movements after the elicitation of such RPs, and if so until which point in time. Here, subjects played a game where they tried to press a button to earn points in a challenge with a brain-computer interface (BCI) that had been trained to detect their RPs in real time and to emit stop signals. Our data suggest that subjects can still veto a movement even after the onset of the RP. Cancellation of movements was possible if stop signals occurred earlier than 200 ms before movement onset, thus constituting a point of no return.

Perceptual confidence refers to the degree to which we believe in the accuracy of our percepts. Signal detection theory suggests that perceptual confidence is computed from an internal "decision variable," which reflects the amount of available information in favor of one or another perceptual interpretation of the sensory input. The neural processes underlying these computations have, however, remained elusive. Here, we used fMRI and multivariate decoding techniques to identify regions of the human brain that encode this decision variable and confidence during a visual motion discrimination task. We used observers' binary perceptual choices and confidence ratings to reconstruct the internal decision variable that governed the subjects' behavior. A number of areas in prefrontal and posterior parietal association cortex encoded this decision variable, and activity in the ventral striatum reflected the degree of perceptual confidence. Using a multivariate connectivity analysis, we demonstrate that patterns of brain activity in the right ventrolateral prefrontal cortex reflecting the decision variable were linked to brain signals in the ventral striatum reflecting confidence. Our results suggest that the representation of perceptual confidence in the ventral striatum is derived from a transformation of the continuous decision variable encoded in the cerebral cortex., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

When choosing actions, humans have to balance carefully between different task demands. On the one hand, they should perform tasks repeatedly to avoid frequent and effortful switching between different tasks. On the other hand, subjects have to retain their flexibility to adapt to changes in external task demands such as switching away from an increasingly difficult task. Here, we developed a difficulty-based choice task to investigate how subjects voluntarily select task-sets in predictably changing environments. Subjects were free to choose 1 of the 3 task-sets on a trial-by-trial basis, while the task difficulty changed dynamically over time. Subjects self-sequenced their behavior in this environment while we measured brain responses with functional magnetic resonance imaging (fMRI). Using multivariate decoding, we found that task choices were encoded in the medial prefrontal cortex (dorso-medial prefrontal cortex, dmPFC, and dorsal anterior cingulate cortex, dACC). The same regions were found to encode task difficulty, a major factor influencing choices. Importantly, the present paradigm allowed us to disentangle the neural code for task choices and task difficulty, ensuring that activation patterns in dmPFC/dACC independently encode these 2 factors. This finding provides new evidence for the importance of the dmPFC/dACC for task-selection and motivational functions in highly dynamic environments., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Rewards obtained from specific behaviors can and do change across time. To adapt to such conditions, humans need to represent and update associations between behaviors and their outcomes. Much previous work focused on how rewards affect the processing of specific tasks. However, abstract associations between multiple potential behaviors and multiple rewards are an important basis for adaptation as well. In this experiment, we directly investigated which brain areas represent associations between multiple tasks and rewards, using time-resolved multivariate pattern analysis of functional magnetic resonance imaging data. Importantly, we were able to dissociate neural signals reflecting task-reward associations from those related to task preparation and reward expectation processes, variables that were often correlated in previous research. We hypothesized that brain regions involved in processing tasks and/or rewards will be involved in processing associations between them. Candidate areas included the dorsal anterior cingulate cortex, which is involved in associating simple actions and rewards, and the parietal cortex, which has been shown to represent task rules and action values. Our results indicate that local spatial activation patterns in the inferior parietal cortex indeed represent task-reward associations. Interestingly, the parietal cortex flexibly changes its content of representation within trials. It first represents task-reward associations, later switching to process tasks and rewards directly. These findings highlight the importance of the inferior parietal cortex in associating behaviors with their outcomes and further show that it can flexibly reconfigure its function within single trials. Significance statement: Rewards obtained from specific behaviors rarely remain constant over time. To adapt to changing conditions, humans need to continuously update and represent the current association between behavior and its outcomes. However, little is known about the neural representation of behavior-outcome associations. Here, we used multivariate pattern analysis of functional magnetic resonance imaging data to investigate the neural correlates of such associations. Our results demonstrate that the parietal cortex plays a central role in representing associations between multiple behaviors and their outcomes. They further highlight the flexibility of the parietal cortex, because we find it to adapt its function to changing task demands within trials on relatively short timescales., (Copyright © 2015 the authors 0270-6474/15/3512356-11$15.00/0.)

The modulation of neural activity in visual cortex is thought to be a key mechanism of visual attention. The investigation of attentional modulation in high-level visual areas, however, is hampered by the lack of clear tuning or contrast response functions. In the present functional magnetic resonance imaging study we therefore systematically assessed how small voxel-wise biases in object preference across hundreds of voxels in the lateral occipital complex were affected when attention was directed to objects. We found that the strength of attentional modulation depended on a voxel's object preference in the absence of attention, a pattern indicative of an amplificatory mechanism. Our results show that such attentional modulation effectively increased the mutual information between voxel responses and object identity. Further, these local modulatory effects led to improved information-based object readout at the level of multi-voxel activation patterns and to an increased reproducibility of these patterns across repeated presentations. We conclude that attentional modulation enhances object coding in local and distributed object representations of the lateral occipital complex., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Human fMRI signals exhibit a spatial patterning that contains detailed information about a person's mental states. Using classifiers it is possible to access this information and study brain processes at the level of individual mental representations. The precise link between fMRI signals and neural population signals still needs to be unraveled. Also, the interpretation of classification studies needs to be handled with care. Nonetheless, pattern-based analyses make it possible to investigate human representational spaces in unprecedented ways, especially when combined with computational modeling., (Copyright © 2015 Elsevier Inc. All rights reserved.)

For successful communication, conversational partners need to estimate each other's current knowledge state. Nonverbal facial and bodily cues can reveal relevant information about how confident a speaker is about what they are saying. Using functional magnetic resonance imaging, we aimed to identify brain regions that encode how confident a speaker is perceived to be. Participants viewed videos of people answering general knowledge questions and judged each respondent's confidence in their answer. Our results suggest a distinct role of two neural networks known to support social inferences, the so-called mentalizing and the mirroring network. While activation in both networks underlies the processing of nonverbal cues, only activity in the mentalizing network, most notably the medial prefrontal cortex and the bilateral temporoparietal junction, is modulated by how confident the respondent is judged to be. Our results support an integrative account of the mirroring and mentalizing network, in which the two systems support each other in aiding pragmatic processing., (© The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.)

Bilinguals require a high degree of cognitive control to select the language intended for speaking and inhibit the unintended. Previous neuroimaging studies have not teased apart brain regions for generating the intention to use a given language, and those for speaking in that language. Separating these two phases can clarify at what stage competition between languages occurs. In this fMRI study German-English bilinguals were first cued to use German or English. After a delay, they named a picture in the cued language. During the intention phase, the precuneus, right superior lateral parietal lobule, and middle temporal gyrus were more activated when participants had to update the currently active language. During language execution activation was higher for English compared to German in brain areas associated with cognitive control, most notably the anterior cingulate and the caudate. Our results suggest two different systems enabling cognitive control during bilingual language production., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Background: This study investigates the prediction of mild cognitive impairment-to-Alzheimer's disease (MCI-to-AD) conversion based on extensive multimodal data with varying degrees of missing values., Methods: Based on Alzheimer's Disease Neuroimaging Initiative data from MCI-patients including all available modalities, we predicted the conversion to AD within 3 years. Different ways of replacing missing data in combination with different classification algorithms are compared. The performance was evaluated on features prioritized by experts and automatically selected features., Results: The conversion to AD could be predicted with a maximal accuracy of 73% using support vector machines and features chosen by experts. Among data modalities, neuropsychological, magnetic resonance imaging, and positron emission tomography data were most informative. The best single feature was the functional activities questionnaire., Conclusion: Extensive multimodal and incomplete data can be adequately handled by a combination of missing data substitution, feature selection, and classification.

Many daily behaviors require us to actively focus on the current task and ignore all other distractions. Yet, ignoring everything else might hinder the ability to discover new ways to achieve the same goal. Here, we studied the neural mechanisms that support the spontaneous change to better strategies while an established strategy is executed. Multivariate neuroimaging analyses showed that before the spontaneous change to an alternative strategy, medial prefrontal cortex (MPFC) encoded information that was irrelevant for the current strategy but necessary for the later strategy. Importantly, this neural effect was related to future behavioral changes: information encoding in MPFC was changed only in participants who eventually switched their strategy and started before the actual strategy change. This allowed us to predict spontaneous strategy shifts ahead of time. These findings suggest that MPFC might internally simulate alternative strategies and shed new light on the organization of PFC., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Perceptual learning is the improvement in perceptual performance through training or exposure. Here, we used fMRI before and after extensive behavioral training to investigate the effects of perceptual learning on the recognition of objects under challenging viewing conditions. Objects belonged either to trained or untrained categories. Trained categories were further subdivided into trained and untrained exemplars and were coupled with high or low monetary rewards during training. After a 3-day training, object recognition was markedly improved. Although there was a considerable transfer of learning to untrained exemplars within categories, an enhancing effect of reward reinforcement was specific to trained exemplars. fMRI showed that hippocampus responses to both trained and untrained exemplars of trained categories were enhanced by perceptual learning and correlated with the effect of reward reinforcement. Our results suggest a key role of hippocampus in object recognition after perceptual learning.

A variety of studies suggest that efficient treatments to induce short-term dietary success in obesity exist. However, sustained maintenance of reduced weight is rare as a large proportion of patients start to regain weight when treatment is discontinued. Thus, from a clinical perspective, it would be desirable to identify factors that counteract post-diet weight regain across longer time-scales. To address this question, we extended our previous work on neural impulse control mechanisms of short-term dietary success in obesity and now investigated the mechanisms counteracting long-term weight regain after a diet. Specifically, we measured neural impulse control during a delay discounting task with fMRI at two time points, i.e. the beginning ('T0') and the end ('T12') of a one-year follow-up interval after a 12-week diet. Then, we tested whether activity in the dorsolateral prefrontal cortex (DLPFC) at T0 and whether activity changes across the follow-up period (T0-T12) are linked to success in weight maintenance. The analyses conducted show that control-related DLPFC activity at T0 was coupled to the degree of success in weight maintenance. Consistently, also behavioral measures of control were linked to the degree of success in maintenance. A direct comparison of neural and behavioral control parameters for prognostic weight change modeling revealed that neural signals were more informative. Taken together, neural impulse control in the DLPFC measured with fMRI directly after a diet predicts real-world diet success in obese patients across extended time periods., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Functional neuroimaging has provided evidence for altered function of mesolimbic circuits implicated in reward processing, first and foremost the ventral striatum, in patients with schizophrenia. While such findings based on significant group differences in brain activations can provide important insights into the pathomechanisms of mental disorders, the use of neuroimaging results from standard univariate statistical analysis for individual diagnosis has proven difficult. In this proof of concept study, we tested whether the predictive accuracy for the diagnostic classification of schizophrenia patients vs. healthy controls could be improved using multivariate pattern analysis (MVPA) of regional functional magnetic resonance imaging (fMRI) activation patterns for the anticipation of monetary reward. With a searchlight MVPA approach using support vector machine classification, we found that the diagnostic category could be predicted from local activation patterns in frontal, temporal, occipital and midbrain regions, with a maximal cluster peak classification accuracy of 93% for the right pallidum. Region-of-interest based MVPA for the ventral striatum achieved a maximal cluster peak accuracy of 88%, whereas the classification accuracy on the basis of standard univariate analysis reached only 75%. Moreover, using support vector regression we could additionally predict the severity of negative symptoms from ventral striatal activation patterns. These results show that MVPA can be used to substantially increase the accuracy of diagnostic classification on the basis of task-related fMRI signal patterns in a regionally specific way.

A fundamental issue in visual cognition is whether high-level visual areas code objects in a part-based or a view-based (holistic) format. Previous behavioral and neuroimaging studies that examined the viewpoint invariance of object recognition have yielded ambiguous results, providing evidence for either type of representational format. A critical factor distinguishing the two formats could be the availability of attentional resources, as a number of priming studies have found greater viewpoint invariance for attended compared to unattended objects. It has therefore been suggested that the activation of part-based representations requires attention, whereas the activation of holistic representations occurs automatically irrespective of attention. Using functional magnetic resonance imaging in combination with a novel multivariate pattern analysis approach, the present study probed the format of object representations in human lateral occipital complex and its dependence on attention. We presented human participants with intact and half-split versions of objects that were either attended or unattended. Cross-classifying between intact and split objects, we found that the object-related information coded in activation patterns of intact objects is fully preserved in the patterns of split objects and vice versa. Importantly, the generalization between intact and split objects did not depend on attention. We conclude that lateral occipital complex codes objects in a non-holistic format, both in the presence and absence of attention., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Active and flexible manipulations of memory contents "in the mind's eye" are believed to occur in a dedicated neural workspace, frequently referred to as visual working memory. Such a neural workspace should have two important properties: The ability to store sensory information across delay periods and the ability to flexibly transform sensory information. Here we used a combination of functional MRI and multivariate decoding to indentify such neural representations. Subjects were required to memorize a complex artificial pattern for an extended delay, then rotate the mental image as instructed by a cue and memorize this transformed pattern. We found that patterns of brain activity already in early visual areas and posterior parietal cortex encode not only the initially remembered image, but also the transformed contents after mental rotation. Our results thus suggest that the flexible and general neural workspace supporting visual working memory can be realized within posterior brain regions., (Copyright © 2014 Elsevier Inc. All rights reserved.)

The multivariate analysis of brain signals has recently sparked a great amount of interest, yet accessible and versatile tools to carry out decoding analyses are scarce. Here we introduce The Decoding Toolbox (TDT) which represents a user-friendly, powerful and flexible package for multivariate analysis of functional brain imaging data. TDT is written in Matlab and equipped with an interface to the widely used brain data analysis package SPM. The toolbox allows running fast whole-brain analyses, region-of-interest analyses and searchlight analyses, using machine learning classifiers, pattern correlation analysis, or representational similarity analysis. It offers automatic creation and visualization of diverse cross-validation schemes, feature scaling, nested parameter selection, a variety of feature selection methods, multiclass capabilities, and pattern reconstruction from classifier weights. While basic users can implement a generic analysis in one line of code, advanced users can extend the toolbox to their needs or exploit the structure to combine it with external high-performance classification toolboxes. The toolbox comes with an example data set which can be used to try out the various analysis methods. Taken together, TDT offers a promising option for researchers who want to employ multivariate analyses of brain activity patterns.

Social context plays an important role in human communication. Depending on the nature of the source, the same communication signal might be processed in fundamentally different ways. However, the selective modulation (or "gating") of the flow of neural information during communication is not fully understood. Here, we use multivoxel pattern analysis (MVPA) and multivoxel connectivity analysis (MVCA), a novel technique that allows to analyse context-dependent changes of the strength interregional coupling between ensembles of voxels, to examine how the human brain differentially gates content-specific sensory information during ongoing perception of communication signals. In a simulated electronic communication experiment, participants received two alternative text messages during fMRI ("happy" or "sad") which they believed had been sent either by their real-life friend outside the scanner or by a computer. A region in the dorsal medial prefrontal cortex (dmPFC) selectively increased its functional coupling with sensory-content encoding regions in the visual cortex when a text message was perceived as being sent by the participant's friend, and decreased its functional coupling with these regions when a text message was perceived as being sent by the computer. Furthermore, the strength of neural encoding of content-specific information of text messages in the dmPFC was modulated by the social tie between the participant and her friend: the more of her spare time a participant reported to spend with her friend the stronger was the neural encoding. This suggests that the human brain selectively gates sensory information into the relevant network for processing the mental states of others, depending on the source of the communication signal., (Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.)

Stimulus visibility is associated with neural signals in multiple brain regions, ranging from visual cortex to prefrontal regions. Here we used functional magnetic resonance imaging (fMRI) to investigate to which extent the perceived visibility of a "low-level" grating stimulus is reflected in the brain activity in high-level brain regions. Oriented grating stimuli were presented under varying visibility conditions created by backward masking. Visibility was manipulated using four different stimulus onset asynchronies (SOAs), which created a continuum from invisible to highly visible target stimuli. Brain activity in early visual areas, high-level visual brain regions (fusiform gyrus), as well as parietal and prefrontal brain regions was significantly correlated with subjects' psychometric visibility functions. In addition, increased stimulus visibility was reflected in the functional coupling between low and high-level visual areas. Specifically, neuroimaging signals in the middle occipital gyrus were significantly more correlated with signals in the inferior temporal gyrus when subjects successfully perceived the target stimulus than when they did not. These results provide evidence that not only low-level visual but also high-level brain regions reflect visibility of low-level grating stimuli and that changes in functional connectivity reflect perceived stimulus visibility., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Despite advances in understanding basic organizational principles of the human basal ganglia, accurate in vivo assessment of their anatomical properties is essential to improve early diagnosis in disorders with corticosubcortical pathology and optimize target planning in deep brain stimulation. Main goal of this study was the detailed topological characterization of limbic, associative, and motor subdivisions of the subthalamic nucleus (STN) in relation to corresponding corticosubcortical circuits. To this aim, we used magnetic resonance imaging and investigated independently anatomical connectivity via white matter tracts next to brain tissue properties. On the basis of probabilistic diffusion tractography we identified STN subregions with predominantly motor, associative, and limbic connectivity. We then computed for each of the nonoverlapping STN subregions the covariance between local brain tissue properties and the rest of the brain using high-resolution maps of magnetization transfer (MT) saturation and longitudinal (R1) and transverse relaxation rate (R2*). The demonstrated spatial distribution pattern of covariance between brain tissue properties linked to myelin (R1 and MT) and iron (R2*) content clearly segregates between motor and limbic basal ganglia circuits. We interpret the demonstrated covariance pattern as evidence for shared tissue properties within a functional circuit, which is closely linked to its function. Our findings open new possibilities for investigation of changes in the established covariance pattern aiming at accurate diagnosis of basal ganglia disorders and prediction of treatment outcome., (Copyright © 2014 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.)

Sequential behaviour is widespread not only in humans but also in animals, ranging in different degrees of complexity from locomotion to birdsong or music performance. The capacity to learn new motor sequences relies on the integrity of basal ganglia-cortical loops. In Parkinson's disease the execution of habitual action sequences as well as the acquisition of novel sequences is impaired partly due to a deficiency in being able to generate internal cues to trigger movement sequences. In addition, patients suffering from Parkinson's disease have difficulty initiating or terminating a self-paced sequence of actions. Direct recordings from the basal ganglia in these patients show an increased level of beta (14-30 Hz) band oscillatory activity associated with impairment in movement initiation. In this framework, the current study aims to evaluate in patients with Parkinson's disease the neuronal activity in the subthalamic nucleus related to the encoding of sequence boundaries during the explicit learning of sensorimotor sequences. We recorded local field potential activity from the subthalamic nucleus of 12 patients who underwent deep brain stimulation for the treatment of advanced Parkinson's disease, while the patients in their usual medicated state practiced sequences of finger movements on a digital piano with corresponding auditory feedback. Our results demonstrate that variability in performance during an early phase of sequence acquisition correlates across patients with changes in the pattern of subthalamic beta-band oscillations; specifically, an anticipatory suppression of beta-band activity at sequence boundaries is linked to better performance. By contrast, a more compromised performance is related to attenuation of beta-band activity before within-sequence elements. Moreover, multivariate pattern classification analysis reveals that differential information about boundaries and within-sequence elements can be decoded at least 100 ms before the keystroke from the amplitude of oscillations of subthalamic nucleus activity across different frequency bands, not just from the beta-band. Additional analysis was performed to assess the strength of how much the putative signal encoding class of ordinal position (boundaries, within-sequence elements) is reflected in each frequency band. This analysis demonstrates that suppression of power in the beta-band contains the most class-related information, whereas enhancement of gamma band (31-100 Hz) activity is the second main contributor to the encoding. Our findings support the hypothesis that subthalamic nucleus-mediated gating of salient boundary elements during sequence encoding may be a prerequisite for the adequate acquisition of action sequences and the transition to habitual behaviour., (© The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Humans recognize faces and objects with high speed and accuracy regardless of their orientation. Recent studies have proposed that orientation invariance in face recognition involves an intermediate representation where neural responses are similar for mirror-symmetric views. Here, we used fMRI, multivariate pattern analysis, and computational modeling to investigate the neural encoding of faces and vehicles at different rotational angles. Corroborating previous studies, we demonstrate a representation of face orientation in the fusiform face-selective area (FFA). We go beyond these studies by showing that this representation is category-selective and tolerant to retinal translation. Critically, by controlling for low-level confounds, we found the representation of orientation in FFA to be compatible with a linear angle code. Aspects of mirror-symmetric coding cannot be ruled out when FFA mean activity levels are considered as a dimension of coding. Finally, we used a parametric family of computational models, involving a biased sampling of view-tuned neuronal clusters, to compare different face angle encoding models. The best fitting model exhibited a predominance of neuronal clusters tuned to frontal views of faces. In sum, our findings suggest a category-selective and monotonic code of face orientation in the human FFA, in line with primate electrophysiology studies that observed mirror-symmetric tuning of neural responses at higher stages of the visual system, beyond the putative homolog of human FFA., (Copyright © 2014 the authors 0270-6474/14/3412155-13$15.00/0.)

Sustained, long-term cognitive workload is associated with variations and decrements in performance. Such fluctuations in vigilance can be a risk factor especially during dangerous attention demanding activities. Functional MRI studies have shown that attentional performance is correlated with BOLD-signals, especially in parietal and prefrontal cortical regions. An interesting question is whether these BOLD-signals could be measured in real-world scenarios, say to warn in a dangerous workplace whenever a subjects' vigilance is low. Because fMRI lacks the mobility needed for such applications, we tested whether the monitoring of vigilance might be possible using Near-Infrared Spectroscopy (NIRS). NIRS is a highly mobile technique that measures hemodynamics in the surface of the brain. We demonstrate that non-invasive NIRS signals correlate with vigilance. These signals carry enough information to decode subjects' reaction times at a single trial level.

Currently, it is unclear whether pediatric multiple sclerosis (PMS) is a pathoetiologically homogeneous disease phenotype due to clinical and epidemiological differences between early and late onset PMS (EOPMS and LOPMS). Consequently, the question was raised whether diagnostic guidelines need to be complemented by specific EOPMS markers. To search for such markers, we analyzed cerebral MRI images acquired with standard protocols using computer-based classification techniques. Specifically, we applied classification algorithms to gray (GM) and white matter (WM) tissue probability parameters of small brain regions derived from T2-weighted MRI images of EOPMS patients (onset <12 years), LOPMS patients (onset ≥12 years), and healthy controls (HC). This was done for PMS subgroups matched for disease duration and participant age independently. As expected, maximal diagnostic information for distinguishing PMS patients and HC was found in a periventricular WM area containing lesions (87.1% accuracy, p < 2.2 × 10(-5)). MRI-based biomarkers specific for EOPMS were identified in prefrontal cortex. Specifically, a coordinate in middle frontal gyrus contained maximal diagnostic information (77.3%, p = 1.8 × 10(-4)). Taken together, we were able to identify biomarkers reflecting pathognomonic processes specific for MS patients with very early onset. Especially GM involvement in the separation between PMS subgroups suggests that conventional MRI contains a richer set of diagnostically informative features than previously assumed.

There has been a long history of research on visual working memory. Whereas early studies have focused on the role of lateral prefrontal cortex in the storage of sensory information, this has been challenged by research in humans that has directly assessed the encoding of perceptual contents, pointing towards a role of visual and parietal regions during storage. In a previous study we used pattern classification to investigate the storage of complex visual color patterns across delay periods. This revealed coding of such contents in early visual and parietal brain regions. Here we aim to investigate whether the involvement of visual and parietal cortex is also observable for other types of complex, visuo-spatial pattern stimuli. Specifically, we used a combination of fMRI and multivariate classification to investigate the retention of complex flow-field stimuli defined by the spatial patterning of motion trajectories of random dots. Subjects were trained to memorize the precise spatial layout of these stimuli and to retain this information during an extended delay. We used a multivariate decoding approach to identify brain regions where spatial patterns of activity encoded the memorized stimuli. Content-specific memory signals were observable in motion sensitive visual area MT+ and in posterior parietal cortex that might encode spatial information in a modality independent manner. Interestingly, we also found information about the memorized visual stimulus in somatosensory cortex, suggesting a potential crossmodal contribution to memory. Our findings thus indicate that working memory storage of visual percepts might be distributed across unimodal, multimodal and even crossmodal brain regions., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Multi-voxel pattern analysis (MVPA) is a fruitful and increasingly popular complement to traditional univariate methods of analyzing neuroimaging data. We propose to replace the standard 'decoding' approach to searchlight-based MVPA, measuring the performance of a classifier by its accuracy, with a method based on the multivariate form of the general linear model. Following the well-established methodology of multivariate analysis of variance (MANOVA), we define a measure that directly characterizes the structure of multi-voxel data, the pattern distinctness D. Our measure is related to standard multivariate statistics, but we apply cross-validation to obtain an unbiased estimate of its population value, independent of the amount of data or its partitioning into 'training' and 'test' sets. The estimate D^ can therefore serve not only as a test statistic, but also as an interpretable measure of multivariate effect size. The pattern distinctness generalizes the Mahalanobis distance to an arbitrary number of classes, but also the case where there are no classes of trials because the design is described by parametric regressors. It is defined for arbitrary estimable contrasts, including main effects (pattern differences) and interactions (pattern changes). In this way, our approach makes the full analytical power of complex factorial designs known from univariate fMRI analyses available to MVPA studies. Moreover, we show how the results of a factorial analysis can be used to obtain a measure of pattern stability, the equivalent of 'cross-decoding'., (Copyright © 2013 Elsevier Inc. All rights reserved.)

A large body of evidence has implicated the posterior parietal and orbitofrontal cortex in the processing of value. However, value correlates perfectly with salience when appetitive stimuli are investigated in isolation. Accordingly, considerable uncertainty has remained about the precise nature of the previously identified signals. In particular, recent evidence suggests that neurons in the primate parietal cortex signal salience instead of value. To investigate neural signatures of value and salience, here we apply multivariate (pattern-based) analyses to human functional MRI data acquired during a noninstrumental outcome-prediction task involving appetitive and aversive outcomes. Reaction time data indicated additive and independent effects of value and salience. Critically, we show that multivoxel ensemble activity in the posterior parietal cortex encodes predicted value and salience in superior and inferior compartments, respectively. These findings reinforce the earlier reports of parietal value signals and reconcile them with the recent salience report. Moreover, we find that multivoxel patterns in the orbitofrontal cortex correlate with value. Importantly, the patterns coding for the predicted value of appetitive and aversive outcomes are similar, indicating a common neural scale for appetite and aversive values in the orbitofrontal cortex. Thus orbitofrontal activity patterns satisfy a basic requirement for a neural value signal.

The increase in spatiotemporal resolution of neuroimaging devices is accompanied by a trend towards more powerful multivariate analysis methods. Often it is desired to interpret the outcome of these methods with respect to the cognitive processes under study. Here we discuss which methods allow for such interpretations, and provide guidelines for choosing an appropriate analysis for a given experimental goal: For a surgeon who needs to decide where to remove brain tissue it is most important to determine the origin of cognitive functions and associated neural processes. In contrast, when communicating with paralyzed or comatose patients via brain-computer interfaces, it is most important to accurately extract the neural processes specific to a certain mental state. These equally important but complementary objectives require different analysis methods. Determining the origin of neural processes in time or space from the parameters of a data-driven model requires what we call a forward model of the data; such a model explains how the measured data was generated from the neural sources. Examples are general linear models (GLMs). Methods for the extraction of neural information from data can be considered as backward models, as they attempt to reverse the data generating process. Examples are multivariate classifiers. Here we demonstrate that the parameters of forward models are neurophysiologically interpretable in the sense that significant nonzero weights are only observed at channels the activity of which is related to the brain process under study. In contrast, the interpretation of backward model parameters can lead to wrong conclusions regarding the spatial or temporal origin of the neural signals of interest, since significant nonzero weights may also be observed at channels the activity of which is statistically independent of the brain process under study. As a remedy for the linear case, we propose a procedure for transforming backward models into forward models. This procedure enables the neurophysiological interpretation of the parameters of linear backward models. We hope that this work raises awareness for an often encountered problem and provides a theoretical basis for conducting better interpretable multivariate neuroimaging analyses., (Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.)

Saliency is a measure that describes how attention is guided by local stimulus properties. Some hypotheses assign its computation to specific topographically organized areas of early human visual cortex. However, in most stimuli, saliency is correlated with luminance contrast, which in turn is known to correlate with activity in these early areas. Thus, any observed correlation of local activity with saliency might be due to the area encoding luminance contrast. Here we disentangle encoding of local luminance contrast and saliency by using stimuli where the two properties are uncorrelated. First, we conducted an eye-tracking study to verify that both negative and positive contrast modifications located in individual quadrants of the visual field increase saliency. Second, subjects viewed identical stimuli while fMRI signals were recorded. We find that positive contrast modifications induce a robust increase of activity in V1-V3 and hV4. However, negative contrast modifications lead to a reduced (V1, V2) or comparable (V3, hV4) activity level compared to unmodified quadrants. Furthermore, even with linear multivariate pattern-classification techniques, it is not possible to decode the location of the salient quadrant independent of the type of the contrast modification. Instead, decoding of the contrast-modified location is only possible separately for the two modification types in V1-V3. These findings suggest that the BOLD activity in V1-V3 is dominated by contrast-dependent processes and does not include the contrast invariance necessary for the computation of feature-invariant saliency.

Deficits in impulse control are discussed as key mechanisms for major worldwide health problems such as drug addiction and obesity. For example, obese subjects have difficulty controlling their impulses to overeat when faced with food items. Here, we investigated the role of neural impulse control mechanisms for dietary success in middle-aged obese subjects. Specifically, we used a food-specific delayed gratification paradigm and functional magnetic resonance imaging to measure eating-related impulse-control in middle-aged obese subjects just before they underwent a twelve-week low calorie diet. As expected, we found that subjects with higher behavioral impulse control subsequently lost more weight. Furthermore, brain activity before the diet in VMPFC and DLPFC correlates with subsequent weight loss. Additionally, a connectivity analysis revealed that stronger functional connectivity between these regions is associated with better dietary success and impulse control. Thus, the degree to which subjects can control their eating impulses might depend on the interplay between control regions (DLPFC) and regions signaling the reward of food (VMPFC). This could potentially constitute a general mechanism that also extends to other disorders such as drug addiction or alcohol abuse., (© 2013.)

Visual stimuli can "pop out" if they are different to their background. There has been considerable debate as to the role of primary visual cortex (V1) versus higher visual areas (esp. V4) in pop-out processing. Here we parametrically modulated the relative orientation of stimuli and their backgrounds to investigate the neural correlates of pop-out in visual cortex while subjects were performing a demanding fixation task in a scanner. Whole brain and region of interest analyses confirmed a representation of orientation contrast in extrastriate visual cortex (V4), but not in striate visual cortex (V1). Thus, although previous studies have shown that human V1 can be involved in orientation pop-out, our findings demonstrate that there are cases where V1 is "blind" and pop-out detection is restricted to higher visual areas. Pop-out processing is presumably a distributed process across multiple visual regions., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Successful realization of planned actions requires the brain to encode intentions over delays. Previous research has indicated that several regions in the rostral or anterior prefrontal cortex (PFC) encode delayed intentions. However, different processes may encode the same future task depending on task load during the delay. This difference may depend on the computational resources available when the delay is occupied with an ongoing task and when it is task-free. Here we directly investigated and compared the representation of delayed intentions in the human brain in the presence and absence of ongoing task load during the delay. We acquired fMRI data in combination with an event-based prospective memory design where human subjects remembered to perform the same future tasks over occupied and task-free delays. We used time-resolved multivoxel pattern classification and found that: (1) rostrolateral PFC (BA 46) encoded the delayed intention during both delay types; (2) rostromedial PFC (BA 10) encoded the intentions during occupied delays; whereas (3) a variety of more posterior regions, including the anterior cingulate cortex (BA 24), the supplementary motor area (BA 6), and the precuneus, encoded intentions during task-free delays. Overall, the medial PFC encoded delayed intentions more rostrally in the presence of an ongoing delay task and more caudally in its absence. Thus, rostromedial PFC may play a specialized role in the encoding of prospective memory that depends on higher computational demands (e.g., given higher task load during the delay). In contrast, the rostrolateral PFC is a more general area that encodes future intentions regardless of task load.

Music is known to be capable of reducing perceived exertion during strenuous physical activity. The current interpretation of this modulating effect of music is that music may be perceived as a diversion from unpleasant proprioceptive sensations that go along with exhaustion. Here we investigated the effects of music on perceived exertion during a physically strenuous task, varying musical agency, a task that relies on the experience of body proprioception, rather than simply diverting from it. For this we measured psychologically indicated exertion during physical workout with and without musical agency while simultaneously acquiring metabolic values with spirometry. Results showed that musical agency significantly decreased perceived exertion during workout, indicating that musical agency may actually facilitate physically strenuous activities. This indicates that the positive effect of music on perceived exertion cannot always be explained by an effect of diversion from proprioceptive feedback. Furthermore, this finding suggests that the down-modulating effect of musical agency on perceived exertion may be a previously unacknowledged driving force for the development of music in humans: making music makes strenuous physical activities less exhausting.

Delusions are unfounded yet tenacious beliefs and a symptom of psychotic disorder. Varying degrees of delusional ideation are also found in the healthy population. Here, we empirically validated a neurocognitive model that explains both the formation and the persistence of delusional beliefs in terms of altered perceptual inference. In a combined behavioral and functional neuroimaging study in healthy participants, we used ambiguous visual stimulation to probe the relationship between delusion-proneness and the effect of learned predictions on perception. Delusional ideation was associated with less perceptual stability, but a stronger belief-induced bias on perception, paralleled by enhanced functional connectivity between frontal areas that encoded beliefs and sensory areas that encoded perception. These findings suggest that weakened lower-level predictions that result in perceptual instability are implicated in the emergence of delusional beliefs. In contrast, stronger higher-level predictions that sculpt perception into conformity with beliefs might contribute to the tenacious persistence of delusional beliefs.

Speech is an important carrier of emotional information. However, little is known about how different vocal emotion expressions are recognized in a receiver's brain. We used multivariate pattern analysis of functional magnetic resonance imaging data to investigate to which degree distinct vocal emotion expressions are represented in the receiver's local brain activity patterns. Specific vocal emotion expressions are encoded in a right fronto-operculo-temporal network involving temporal regions known to subserve suprasegmental acoustic processes and a fronto-opercular region known to support emotional evaluation, and, moreover, in left temporo-cerebellar regions covering sequential processes. The right inferior frontal region, in particular, was found to differentiate distinct emotional expressions. The present analysis reveals vocal emotion to be encoded in a shared cortical network reflected by distinct brain activity patterns. These results shed new light on theoretical and empirical controversies about the perception of distinct vocal emotion expressions at the level of large-scale human brain signals., (Copyright © 2012 Wiley Periodicals, Inc.)