Bodily Maps of Symptoms and Emotions in Parkinson's Disease

BACKGROUND

Emotions are reflected in bodily sensations, and these reflections are abnormal in psychiatric conditions. However, emotion-related bodily sensations have not been studied in neurological disorders.

OBJECTIVE

The aim of this study was to investigate whether Parkinson's disease (PD) is associated with altered bodily representations of emotions.

METHODS

Symptoms and emotion-related sensations were investigated in 380 patients with PD and 79 control subjects, using a topographical self-report method, termed body sensation mapping. The bodily mapping data were analyzed with pixelwise generalized linear models and principal component analyses.

RESULTS

Bodily maps of symptoms showed characteristic patterns of PD motor symptom distributions. Compared with control subjects, PD patients showed decreased parasternal sensation of anger, and longer PD symptom duration was associated with increased abdominal sensation of anger (PFWE < 0.05). The PD-related sensation patterns were abnormal across all basic emotions (P < 0.05).

CONCLUSIONS

The results demonstrate altered bodily maps of emotions in PD, providing novel insight into the nonmotor effects of PD. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Neuroscience meets behavior: A systematic literature review on magnetic resonance imaging of the brain combined with real-world digital phenotyping

A primary goal of neuroscience is to understand the relationship between the brain and behavior. While magnetic resonance imaging (MRI) examines brain structure and function under controlled conditions, digital phenotyping via portable automatic devices (PAD) quantifies behavior in real-world settings. Combining these two technologies may bridge the gap between brain imaging, physiology, and real-time behavior, enhancing the generalizability of laboratory and clinical findings. However, the use of MRI and data from PADs outside the MRI scanner remains underexplored. Herein, we present a Preferred Reporting Items for Systematic Reviews and Meta-Analysis systematic literature review that identifies and analyzes the current state of research on the integration of brain MRI and PADs. PubMed and Scopus were automatically searched using keywords covering various MRI techniques and PADs. Abstracts were screened to only include articles that collected MRI brain data and PAD data outside the laboratory environment. Full-text screening was then conducted to ensure included articles combined quantitative data from MRI with data from PADs, yielding 94 selected papers for a total of N = 14,778 subjects. Results were reported as cross-frequency tables between brain imaging and behavior sampling methods and patterns were identified through network analysis. Furthermore, brain maps reported in the studies were synthesized according to the measurement modalities that were used. Results demonstrate the feasibility of integrating MRI and PADs across various study designs, patient and control populations, and age groups. The majority of published literature combines functional, T1-weighted, and diffusion weighted MRI with physical activity sensors, ecological momentary assessment via PADs, and sleep. The literature further highlights specific brain regions frequently correlated with distinct MRI-PAD combinations. These combinations enable in-depth studies on how physiology, brain function and behavior influence each other. Our review highlights the potential for constructing brain-behavior models that extend beyond the scanner and into real-world contexts.

Development and psychometric testing of the perception of nursing profession instrument

BACKGROUND

Perceptions of the nursing profession influence career choices in nursing. An unrealistic perception might lead students to drop out of nursing education programmes. Objective measurement of the nursing applicants' perceptions at the student selection stage could enhance their career choices in nursing.

AIM

To develop and psychometrically evaluate the Perception of Nursing Profession Instrument (PNPI).

DESIGN

Mixed method design.

METHOD

Two versions of the PNPI were developed during the years 2016-2022. The first version was based on documents describing the nursing profession and the second version was based on an integrative literature review, a focus groups study and a document analysis of descriptions of the nursing profession. The meta-ethnographic approach was used to synthesize the results and form a theoretical framework for developing the PNPI (60 items). Item content validity was evaluated by an expert panel of nurses (n = 7). The psychometric properties of the instrument were analysed using the item response theory approach.

RESULTS

The development process resulted in the 40-item PNPI with the following subscales: the content of nursing work, the career in nursing, the nature of nursing work and the characteristics of a nurse. The psychometric analysis revealed unidimensionality and goodness of fit to the partial credit model; however, the item difficulty was not well matched with the participants' abilities.

CONCLUSION

The PNPI is a novel instrument for objectively measuring perceptions of the nursing profession. For further development, item difficulty must be enhanced to improve the measurement accuracy of the nursing applicants' perceptions of the nursing profession.

IMPACT

Perceptions of the nursing profession influence career choices, but there is a lack of objective assessment instruments that can be used in nursing student selection setting to measure the perception. The results of this study offer an instrument to measure perception, while also suggesting ideas for further development.

Functional organization of social perception in the human brain

Humans rapidly extract diverse and complex information from ongoing social interactions, but the perceptual and neural organization of the different aspects of social perception remains unresolved. We showed short movie clips with rich social content to 97 healthy participants while their haemodynamic brain activity was measured with fMRI. The clips were annotated moment-to-moment for a large set of social features and 45 of the features were evaluated reliably between annotators. Cluster analysis of the social features revealed that 13 dimensions were sufficient for describing the social perceptual space. Three different analysis methods were used to map the social perceptual processes in the human brain. Regression analysis mapped regional neural response profiles for different social dimensions. Multivariate pattern analysis then established the spatial specificity of the responses and intersubject correlation analysis connected social perceptual processing with neural synchronization. The results revealed a gradient in the processing of social information in the brain. Posterior temporal and occipital regions were broadly tuned to most social dimensions and the classifier revealed that these responses showed spatial specificity for social dimensions; in contrast Heschl gyri and parietal areas were also broadly associated with different social signals, yet the spatial patterns of responses did not differentiate social dimensions. Frontal and subcortical regions responded only to a limited number of social dimensions and the spatial response patterns did not differentiate social dimension. Altogether these results highlight the distributed nature of social processing in the brain.

Application of simultaneous uncertainty quantification for image segmentation with probabilistic deep learning: Performance benchmarking of oropharyngeal cancer target delineation as a use-case

Background

Oropharyngeal cancer (OPC) is a widespread disease, with radiotherapy being a core treatment modality. Manual segmentation of the primary gross tumor volume (GTVp) is currently employed for OPC radiotherapy planning, but is subject to significant interobserver variability. Deep learning (DL) approaches have shown promise in automating GTVp segmentation, but comparative (auto)confidence metrics of these models predictions has not been well-explored. Quantifying instance-specific DL model uncertainty is crucial to improving clinician trust and facilitating broad clinical implementation. Therefore, in this study, probabilistic DL models for GTVp auto-segmentation were developed using large-scale PET/CT datasets, and various uncertainty auto-estimation methods were systematically investigated and benchmarked.

Methods

We utilized the publicly available 2021 HECKTOR Challenge training dataset with 224 co-registered PET/CT scans of OPC patients with corresponding GTVp segmentations as a development set. A separate set of 67 co-registered PET/CT scans of OPC patients with corresponding GTVp segmentations was used for external validation. Two approximate Bayesian deep learning methods, the MC Dropout Ensemble and Deep Ensemble, both with five submodels, were evaluated for GTVp segmentation and uncertainty performance. The segmentation performance was evaluated using the volumetric Dice similarity coefficient (DSC), mean surface distance (MSD), and Hausdorff distance at 95% (95HD). The uncertainty was evaluated using four measures from literature: coefficient of variation (CV), structure expected entropy, structure predictive entropy, and structure mutual information, and additionally with our novel Dice-risk measure. The utility of uncertainty information was evaluated with the accuracy of uncertainty-based segmentation performance prediction using the Accuracy vs Uncertainty (AvU) metric, and by examining the linear correlation between uncertainty estimates and DSC. In addition, batch-based and instance-based referral processes were examined, where the patients with high uncertainty were rejected from the set. In the batch referral process, the area under the referral curve with DSC (R-DSC AUC) was used for evaluation, whereas in the instance referral process, the DSC at various uncertainty thresholds were examined.

Results

Both models behaved similarly in terms of the segmentation performance and uncertainty estimation. Specifically, the MC Dropout Ensemble had 0.776 DSC, 1.703 mm MSD, and 5.385 mm 95HD. The Deep Ensemble had 0.767 DSC, 1.717 mm MSD, and 5.477 mm 95HD. The uncertainty measure with the highest DSC correlation was structure predictive entropy with correlation coefficients of 0.699 and 0.692 for the MC Dropout Ensemble and the Deep Ensemble, respectively. The highest AvU value was 0.866 for both models. The best performing uncertainty measure for both models was the CV which had R-DSC AUC of 0.783 and 0.782 for the MC Dropout Ensemble and Deep Ensemble, respectively. With referring patients based on uncertainty thresholds from 0.85 validation DSC for all uncertainty measures, on average the DSC improved from the full dataset by 4.7% and 5.0% while referring 21.8% and 22% patients for MC Dropout Ensemble and Deep Ensemble, respectively.

Conclusion

We found that many of the investigated methods provide overall similar but distinct utility in terms of predicting segmentation quality and referral performance. These findings are a critical first-step towards more widespread implementation of uncertainty quantification in OPC GTVp segmentation.

Lipreading a naturalistic narrative in a female population: Neural characteristics shared with listening and reading

INTRODUCTION

Few of us are skilled lipreaders while most struggle with the task. Neural substrates that enable comprehension of connected natural speech via lipreading are not yet well understood.

METHODS

We used a data-driven approach to identify brain areas underlying the lipreading of an 8-min narrative with participants whose lipreading skills varied extensively (range 6-100%, mean = 50.7%). The participants also listened to and read the same narrative. The similarity between individual participants' brain activity during the whole narrative, within and between conditions, was estimated by a voxel-wise comparison of the Blood Oxygenation Level Dependent (BOLD) signal time courses.

RESULTS

Inter-subject correlation (ISC) of the time courses revealed that lipreading, listening to, and reading the narrative were largely supported by the same brain areas in the temporal, parietal and frontal cortices, precuneus, and cerebellum. Additionally, listening to and reading connected naturalistic speech particularly activated higher-level linguistic processing in the parietal and frontal cortices more consistently than lipreading, probably paralleling the limited understanding obtained via lip-reading. Importantly, higher lipreading test score and subjective estimate of comprehension of the lipread narrative was associated with activity in the superior and middle temporal cortex.

CONCLUSIONS

Our new data illustrates that findings from prior studies using well-controlled repetitive speech stimuli and stimulus-driven data analyses are also valid for naturalistic connected speech. Our results might suggest an efficient use of brain areas dealing with phonological processing in skilled lipreaders.

Segmentation stability of human head and neck cancer medical images for radiotherapy applications under de-identification conditions: Benchmarking data sharing and artificial intelligence use-cases

Background

Demand for head and neck cancer (HNC) radiotherapy data in algorithmic development has prompted increased image dataset sharing. Medical images must comply with data protection requirements so that re-use is enabled without disclosing patient identifiers. Defacing, i.e., the removal of facial features from images, is often considered a reasonable compromise between data protection and re-usability for neuroimaging data. While defacing tools have been developed by the neuroimaging community, their acceptability for radiotherapy applications have not been explored. Therefore, this study systematically investigated the impact of available defacing algorithms on HNC organs at risk (OARs).

Methods

A publicly available dataset of magnetic resonance imaging scans for 55 HNC patients with eight segmented OARs (bilateral submandibular glands, parotid glands, level II neck lymph nodes, level III neck lymph nodes) was utilized. Eight publicly available defacing algorithms were investigated: afni_refacer, DeepDefacer, defacer, fsl_deface, mask_face, mri_deface, pydeface, and quickshear. Using a subset of scans where defacing succeeded (N=29), a 5-fold cross-validation 3D U-net based OAR auto-segmentation model was utilized to perform two main experiments: 1.) comparing original and defaced data for training when evaluated on original data; 2.) using original data for training and comparing the model evaluation on original and defaced data. Models were primarily assessed using the Dice similarity coefficient (DSC).

Results

Most defacing methods were unable to produce any usable images for evaluation, while mask_face, fsl_deface, and pydeface were unable to remove the face for 29%, 18%, and 24% of subjects, respectively. When using the original data for evaluation, the composite OAR DSC was statistically higher (p ≤ 0.05) for the model trained with the original data with a DSC of 0.760 compared to the mask_face, fsl_deface, and pydeface models with DSCs of 0.742, 0.736, and 0.449, respectively. Moreover, the model trained with original data had decreased performance (p ≤ 0.05) when evaluated on the defaced data with DSCs of 0.673, 0.693, and 0.406 for mask_face, fsl_deface, and pydeface, respectively.

Conclusion

Defacing algorithms may have a significant impact on HNC OAR auto-segmentation model training and testing. This work highlights the need for further development of HNC-specific image anonymization methods.

Do sparse brain activity patterns underlie human cognition?

Accumulating multivariate pattern analysis (MVPA) results from fMRI studies suggest that information is represented in fingerprint patterns of activations and deactivations during perception, emotions, and cognition. We postulate that these fingerprint patterns might reflect neuronal-population level sparse code documented in two-photon calcium imaging studies in animal models, i.e., information represented in specific and reproducible ensembles of a few percent of active neurons amidst widespread inhibition in neural populations. We suggest that such representations constitute a fundamental organizational principle via interacting across multiple levels of brain hierarchy, thus giving rise to perception, emotions, and cognition.

Artificial Intelligence for Radiation Oncology Applications Using Public Datasets

Artificial intelligence (AI) has exceptional potential to positively impact the field of radiation oncology. However, large curated datasets - often involving imaging data and corresponding annotations - are required to develop radiation oncology AI models. Importantly, the recent establishment of Findable, Accessible, Interoperable, Reusable (FAIR) principles for scientific data management have enabled an increasing number of radiation oncology related datasets to be disseminated through data repositories, thereby acting as a rich source of data for AI model building. This manuscript reviews the current and future state of radiation oncology data dissemination, with a particular emphasis on published imaging datasets, AI data challenges, and associated infrastructure. Moreover, we provide historical context of FAIR data dissemination protocols, difficulties in the current distribution of radiation oncology data, and recommendations regarding data dissemination for eventual utilization in AI models. Through FAIR principles and standardized approaches to data dissemination, radiation oncology AI research has nothing to lose and everything to gain.

Classification of emotion categories based on functional connectivity patterns of the human brain

Neurophysiological and psychological models posit that emotions depend on connections across wide-spread corticolimbic circuits. While previous studies using pattern recognition on neuroimaging data have shown differences between various discrete emotions in brain activity patterns, less is known about the differences in functional connectivity. Thus, we employed multivariate pattern analysis on functional magnetic resonance imaging data (i) to develop a pipeline for applying pattern recognition in functional connectivity data, and (ii) to test whether connectivity patterns differ across emotion categories. Six emotions (anger, fear, disgust, happiness, sadness, and surprise) and a neutral state were induced in 16 participants using one-minute-long emotional narratives with natural prosody while brain activity was measured with functional magnetic resonance imaging (fMRI). We computed emotion-wise connectivity matrices both for whole-brain connections and for 10 previously defined functionally connected brain subnetworks and trained an across-participant classifier to categorize the emotional states based on whole-brain data and for each subnetwork separately. The whole-brain classifier performed above chance level with all emotions except sadness, suggesting that different emotions are characterized by differences in large-scale connectivity patterns. When focusing on the connectivity within the 10 subnetworks, classification was successful within the default mode system and for all emotions. We thus show preliminary evidence for consistently different sustained functional connectivity patterns for instances of emotion categories particularly within the default mode system.

The Open Brain Consent: Informing research participants and obtaining consent to share brain imaging data

Having the means to share research data openly is essential to modern science. For human research, a key aspect in this endeavor is obtaining consent from participants, not just to take part in a study, which is a basic ethical principle, but also to share their data with the scientific community. To ensure that the participants' privacy is respected, national and/or supranational regulations and laws are in place. It is, however, not always clear to researchers what the implications of those are, nor how to comply with them. The Open Brain Consent (https://open-brain-consent.readthedocs.io) is an international initiative that aims to provide researchers in the brain imaging community with information about data sharing options and tools. We present here a short history of this project and its latest developments, and share pointers to consent forms, including a template consent form that is compliant with the EU general data protection regulation. We also share pointers to an associated data user agreement that is not only useful in the EU context, but also for any researchers dealing with personal (clinical) data elsewhere.

Physical activity and aerobic fitness in relation to local and interhemispheric functional connectivity in adolescents' brains

INTRODUCTION

Adolescents have experienced decreased aerobic fitness levels and insufficient physical activity levels over the past decades. While both physical activity and aerobic fitness are related to physical and mental health, little is known concerning how they manifest in the brain during this stage of development, characterized by significant physical and psychosocial changes. The aim of the study is to examine the associations between both physical activity and aerobic fitness with brains' functional connectivity.

METHODS

Here, we examined how physical activity and aerobic fitness are associated with local and interhemispheric functional connectivity of the adolescent brain (n = 59), as measured with resting-state functional magnetic resonance imaging. Physical activity was measured by hip-worn accelerometers, and aerobic fitness by a maximal 20-m shuttle run test.

RESULTS

We found that higher levels of moderate-to-vigorous intensity physical activity, but not aerobic fitness, were linked to increased local functional connectivity as measured by regional homogeneity in 13-16-year-old participants. However, we did not find evidence for significant associations between adolescents' physical activity or aerobic fitness and interhemispheric connectivity, as indicated by homotopic connectivity.

CONCLUSIONS

These results suggest that physical activity, but not aerobic fitness, is related to local functional connectivity in adolescents. Moreover, physical activity shows an association with a specific brain area involved in motor functions but did not display any widespread associations with other brain regions. These results can advance our understanding of the behavior-brain associations in adolescents.

Idiosynchrony: From shared responses to individual differences during naturalistic neuroimaging

Two ongoing movements in human cognitive neuroscience have researchers shifting focus from group-level inferences to characterizing single subjects, and complementing tightly controlled tasks with rich, dynamic paradigms such as movies and stories. Yet relatively little work combines these two, perhaps because traditional analysis approaches for naturalistic imaging data are geared toward detecting shared responses rather than between-subject variability. Here, we review recent work using naturalistic stimuli to study individual differences, and advance a framework for detecting structure in idiosyncratic patterns of brain activity, or "idiosynchrony". Specifically, we outline the emerging technique of inter-subject representational similarity analysis (IS-RSA), including its theoretical motivation and an empirical demonstration of how it recovers brain-behavior relationships during movie watching using data from the Human Connectome Project. We also consider how stimulus choice may affect the individual signal and discuss areas for future research. We argue that naturalistic neuroimaging paradigms have the potential to reveal meaningful individual differences above and beyond those observed during traditional tasks or at rest.

Effects of spatial smoothing on group-level differences in functional brain networks

Brain connectivity with functional magnetic resonance imaging (fMRI) is a popular approach for detecting differences between healthy and clinical populations. Before creating a functional brain network, the fMRI time series must undergo several preprocessing steps to control for artifacts and to improve data quality. However, preprocessing may affect the results in an undesirable way. Spatial smoothing, for example, is known to alter functional network structure. Yet, its effects on group-level network differences remain unknown. Here, we investigate the effects of spatial smoothing on the difference between patients and controls for two clinical conditions: autism spectrum disorder and bipolar disorder, considering fMRI data smoothed with Gaussian kernels (0–32 mm). We find that smoothing affects network differences between groups. For weighted networks, incrementing the smoothing kernel makes networks more different. For thresholded networks, larger smoothing kernels lead to more similar networks, although this depends on the network density. Smoothing also alters the effect sizes of the individual link differences. This is independent of the region of interest (ROI) size, but varies with link length. The effects of spatial smoothing are diverse, nontrivial, and difficult to predict. This has important consequences: The choice of smoothing kernel affects the observed network differences.

Spatial smoothing is a preprocessing tool commonly applied to reduce the amount of noise in functional magnetic resonance imaging (fMRI) data. However, smoothing is known to affect the outcomes of functional brain network analysis at the level of individual subjects in undesired ways. Here, we investigate how spatial smoothing affects the observed differences in brain network structure between subject groups. Using fMRI data from two clinical populations and healthy controls, we show that the between-group differences in network structure depend on the amount of spatial smoothing applied during preprocessing in a nontrivial way. The optimal level of spatial smoothing is difficult to define and probably depends on a set of analysis parameters. Therefore, we recommend applying spatial smoothing only after careful consideration.

Inter-subject Similarity of Brain Activity in Expert Musicians After Multimodal Learning: A Behavioral and Neuroimaging Study on Learning to Play a Piano Sonata

Human behavior is inherently multimodal and relies on sensorimotor integration. This is evident when pianists exhibit activity in motor and premotor cortices, as part of a dorsal pathway, while listening to a familiar piece of music, or when naïve participants learn to play simple patterns on the piano. Here we investigated the interaction between multimodal learning and dorsal-stream activity over the course of four weeks in ten skilled pianists by adopting a naturalistic data-driven analysis approach. We presented the pianists with audio-only, video-only and audiovisual recordings of a piano sonata during functional magnetic resonance imaging (fMRI) before and after they had learned to play the sonata by heart for a total of four weeks. We followed the learning process and its outcome with questionnaires administered to the pianists, one piano instructor following their training, and seven external expert judges. The similarity of the pianists' brain activity during stimulus presentations was examined before and after learning by means of inter-subject correlation (ISC) analysis. After learning, an increased ISC was found in the pianists while watching the audiovisual performance, particularly in motor and premotor regions of the dorsal stream. While these brain structures have previously been associated with learning simple audio-motor sequences, our findings are the first to suggest their involvement in learning a complex and demanding audiovisual-motor task. Moreover, the most motivated learners and the best performers of the sonata showed ISC in the dorsal stream and in the reward brain network.

Variability in the analysis of a single neuroimaging dataset by many teams

Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2-5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.

Social perspective-taking shapes brain hemodynamic activity and eye movements during movie viewing

Putting oneself into the shoes of others is an important aspect of social cognition. We measured brain hemodynamic activity and eye-gaze patterns while participants were viewing a shortened version of the movie 'My Sister's Keeper' from two perspectives: that of a potential organ donor, who violates moral norms by refusing to donate her kidney, and that of a potential organ recipient, who suffers in pain. Inter-subject correlation (ISC) of brain activity was significantly higher during the potential organ donor's perspective in dorsolateral and inferior prefrontal, lateral and inferior occipital, and inferior-anterior temporal areas. In the reverse contrast, stronger ISC was observed in superior temporal, posterior frontal and anterior parietal areas. Eye-gaze analysis showed higher proportion of fixations on the potential organ recipient during both perspectives. Taken together, these results suggest that during social perspective-taking different brain areas can be flexibly recruited depending on the nature of the perspective that is taken.

Contextual knowledge provided by a movie biases implicit perception of the protagonist

We are constantly categorizing other people as belonging to our in-group (‘one of us’) or out-group (‘one of them’). Such grouping occurs fast and automatically and can be based on others’ visible characteristics such as skin color or clothing style. Here we studied neural underpinnings of implicit social grouping not often visible on the face, male sexual orientation. A total of 14 homosexuals and 15 heterosexual males were scanned in functional magnetic resonance imaging while watching a movie about a homosexual man, whose face was also presented subliminally before (subjects did not know about the character’s sexual orientation) and after the movie. We discovered significantly stronger activation to the man’s face after seeing the movie in homosexual but not heterosexual subjects in medial prefrontal cortex, frontal pole, anterior cingulate cortex, right temporal parietal junction and bilateral superior frontal gyrus. In previous research, these brain areas have been connected to social perception, self-referential thinking, empathy, theory of mind and in-group perception. In line with previous studies showing biased perception of in-/out-group faces to be context dependent, our novel approach further demonstrates how complex contextual knowledge gained under naturalistic viewing can bias implicit social perception.

Agito ergo sum: Correlates of spatio-temporal motion characteristics during fMRI

The impact of in-scanner motion on functional magnetic resonance imaging (fMRI) data has a notorious reputation in the neuroimaging community. State-of-the-art guidelines advise to scrub out excessively corrupted frames as assessed by a composite framewise displacement (FD) score, to regress out models of nuisance variables, and to include average FD as a covariate in group-level analyses. Here, we studied individual motion time courses at time points typically retained in fMRI analyses. We observed that even in this set of putatively clean time points, motion exhibited a very clear spatio-temporal structure, so that we could distinguish subjects into separate groups of movers with varying characteristics. Then, we showed that this spatio-temporal motion cartography tightly relates to a broad array of anthropometric and cognitive factors. Convergent results were obtained from two different analytical perspectives: univariate assessment of behavioural differences across mover subgroups unraveled defining markers, while subsequent multivariate analysis broadened the range of involved factors and clarified that multiple motion/behaviour modes of covariance overlap in the data. Our results demonstrate that even the smaller episodes of motion typically retained in fMRI analyses carry structured, behaviourally relevant information. They call for further examinations of possible biases in current regression-based motion correction strategies.

Anomalous Bodily Maps of Emotions in Schizophrenia

OBJECTIVE

Embodied emotions arise from interoceptive and somatosensory processes, and are essential to the development of a stable sense of self. Emotional embodiment is therefore inherently interwoven with our sense of bodily self-awareness, and allows us to navigate complex social situations. Given that the core feature of schizophrenia (SZ) is characterized by the presence of bodily self-disturbances and social-emotional deficits, we hypothesized that embodiment of emotion would be disrupted in SZ.

METHOD

Twenty-six medicated individuals with SZ and 26 demographically matched controls used a computerized topographical mapping tool ("EmBODY") to indicate on a body outline where they felt bodily sensations while experiencing an emotion. There were 13 different emotions plus a neutral state. The resulting bodily maps of emotions were quantitatively compared between groups using linear discriminant analysis and similarity scores.

RESULTS

Bodily maps of emotions were anomalous in SZ as indicated by indistinguishable maps across different emotions. Relative to the control group, patients reported less discrete and less clear bodily sensations across emotions. In particular, bodily maps for low-arousal emotions were atypical in comparison with healthy controls.

CONCLUSIONS

Anomalous and undifferentiated mapping of embodied emotions in SZ could lead to deficits in linking bodily sensations to conceptual categories of emotions. Disrupted emotional embodiment could also contribute to poor social functioning. Abnormal bodily sensations of emotions might therefore be a promising target for future psychosocial interventions.

Emotions amplify speaker-listener neural alignment

Individuals often align their emotional states during conversation. Here, we reveal how such emotional alignment is reflected in synchronization of brain activity across speakers and listeners. Two "speaker" subjects told emotional and neutral autobiographical stories while their hemodynamic brain activity was measured with functional magnetic resonance imaging (fMRI). The stories were recorded and played back to 16 "listener" subjects during fMRI. After scanning, both speakers and listeners rated the moment-to-moment valence and arousal of the stories. Time-varying similarity of the blood-oxygenation-level-dependent (BOLD) time series was quantified by intersubject phase synchronization (ISPS) between speaker-listener pairs. Telling and listening to the stories elicited similar emotions across speaker-listener pairs. Arousal was associated with increased speaker-listener neural synchronization in brain regions supporting attentional, auditory, somatosensory, and motor processing. Valence was associated with increased speaker-listener neural synchronization in brain regions involved in emotional processing, including amygdala, hippocampus, and temporal pole. Speaker-listener synchronization of subjective feelings of arousal was associated with increased neural synchronization in somatosensory and subcortical brain regions; synchronization of valence was associated with neural synchronization in parietal cortices and midline structures. We propose that emotion-dependent speaker-listener neural synchronization is associated with emotional contagion, thereby implying that listeners reproduce some aspects of the speaker's emotional state at the neural level.

A drama movie activates brains of holistic and analytical thinkers differentially

People socialized in different cultures differ in their thinking styles. Eastern-culture people view objects more holistically by taking context into account, whereas Western-culture people view objects more analytically by focusing on them at the expense of context. Here we studied whether participants, who have different thinking styles but live within the same culture, exhibit differential brain activity when viewing a drama movie. A total of 26 Finnish participants, who were divided into holistic and analytical thinkers based on self-report questionnaire scores, watched a shortened drama movie during functional magnetic resonance imaging. We compared intersubject correlation (ISC) of brain hemodynamic activity of holistic vs analytical participants across the movie viewings. Holistic thinkers showed significant ISC in more extensive cortical areas than analytical thinkers, suggesting that they perceived the movie in a more similar fashion. Significantly higher ISC was observed in holistic thinkers in occipital, prefrontal and temporal cortices. In analytical thinkers, significant ISC was observed in right-hemisphere fusiform gyrus, temporoparietal junction and frontal cortex. Since these results were obtained in participants with similar cultural background, they are less prone to confounds by other possible cultural differences. Overall, our results show how brain activity in holistic vs analytical participants differs when viewing the same drama movie.

Inferior parietal lobule and early visual areas support elicitation of individualized meanings during narrative listening

INTRODUCTION

When listening to a narrative, the verbal expressions translate into meanings and flow of mental imagery. However, the same narrative can be heard quite differently based on differences in listeners' previous experiences and knowledge. We capitalized on such differences to disclose brain regions that support transformation of narrative into individualized propositional meanings and associated mental imagery by analyzing brain activity associated with behaviorally assessed individual meanings elicited by a narrative.

METHODS

Sixteen right-handed female subjects were instructed to list words that best described what had come to their minds while listening to an eight-minute narrative during functional magnetic resonance imaging (fMRI). The fMRI data were analyzed by calculating voxel-wise intersubject correlation (ISC) values. We used latent semantic analysis (LSA) enhanced with Wordnet knowledge to measure semantic similarity of the produced words between subjects. Finally, we predicted the ISC with the semantic similarity using representational similarity analysis.

RESULTS

We found that semantic similarity in these word listings between subjects, estimated using LSA combined with WordNet knowledge, predicting similarities in brain hemodynamic activity. Subject pairs whose individual semantics were similar also exhibited similar brain activity in the bilateral supramarginal and angular gyrus of the inferior parietal lobe, and in the occipital pole.

CONCLUSIONS

Our results demonstrate, using a novel method to measure interindividual differences in semantics, brain mechanisms giving rise to semantics and associated imagery during narrative listening. During listening to a captivating narrative, the inferior parietal lobe and early visual cortical areas seem, thus, to support elicitation of individual meanings and flow of mental imagery.

Distributed affective space represents multiple emotion categories across the human brain

The functional organization of human emotion systems as well as their neuroanatomical basis and segregation in the brain remains unresolved. Here, we used pattern classification and hierarchical clustering to characterize the organization of a wide array of emotion categories in the human brain. We induced 14 emotions (6 ‘basic’, e.g. fear and anger; and 8 ‘non-basic’, e.g. shame and gratitude) and a neutral state using guided mental imagery while participants' brain activity was measured with functional magnetic resonance imaging (fMRI). Twelve out of 14 emotions could be reliably classified from the haemodynamic signals. All emotions engaged a multitude of brain areas, primarily in midline cortices including anterior and posterior cingulate gyri and precuneus, in subcortical regions, and in motor regions including cerebellum and premotor cortex. Similarity of subjective emotional experiences was associated with similarity of the corresponding neural activation patterns. We conclude that different basic and non-basic emotions have distinguishable neural bases characterized by specific, distributed activation patterns in widespread cortical and subcortical circuits. Regionally differentiated engagement of these circuits defines the unique neural activity pattern and the corresponding subjective feeling associated with each emotion.

Opioidergic Regulation of Emotional Arousal: A Combined PET–fMRI Study

Emotions can be characterized by dimensions of arousal and valence (pleasantness). While the functional brain bases of emotional arousal and valence have been actively investigated, the neuromolecular underpinnings remain poorly understood. We tested whether the opioid and dopamine systems involved in reward and motivational processes would be associated with emotional arousal and valence. We used in vivo positron emission tomography to quantify μ-opioid receptor and type 2 dopamine receptor (MOR and D2R, respectively) availability in brains of 35 healthy adult females. During subsequent functional magnetic resonance imaging carried out to monitor hemodynamic activity, the subjects viewed movie scenes of varying emotional content. Arousal and valence were associated with hemodynamic activity in brain regions involved in emotional processing, including amygdala, thalamus, and superior temporal sulcus. Cerebral MOR availability correlated negatively with the hemodynamic responses to arousing scenes in amygdala, hippocampus, thalamus, and hypothalamus, whereas no positive correlations were observed in any brain region. D2R availability—here reliably quantified only in striatum—was not associated with either arousal or valence. These results suggest that emotional arousal is regulated by the MOR system, and that cerebral MOR availability influences brain activity elicited by arousing stimuli.

Regions of Interest as nodes of dynamic functional brain networks

The properties of functional brain networks strongly depend on how their nodes are chosen. Commonly, nodes are defined by Regions of Interest (ROIs), predetermined groupings of fMRI measurement voxels. Earlier, we demonstrated that the functional homogeneity of ROIs, captured by their spatial consistency, varies widely across ROIs in commonly used brain atlases. Here, we ask how ROIs behave as nodes of dynamic brain networks. To this end, we use two measures: spatiotemporal consistency measures changes in spatial consistency across time and network turnover quantifies the changes in the local network structure around an ROI. We find that spatial consistency varies non-uniformly in space and time, which is reflected in the variation of spatiotemporal consistency across ROIs. Furthermore, we see time-dependent changes in the network neighborhoods of the ROIs, reflected in high network turnover. Network turnover is nonuniformly distributed across ROIs: ROIs with high spatiotemporal consistency have low network turnover. Finally, we reveal that there is rich voxel-level correlation structure inside ROIs. Because the internal structure and the connectivity of ROIs vary in time, the common approach of using static node definitions may be surprisingly inaccurate. Therefore, network neuroscience would greatly benefit from node definition strategies tailored for dynamical networks.

Maps of subjective feelings

Subjective feelings are a central feature of human life. We defined the organization and determinants of a feeling space involving 100 core feelings that ranged from cognitive and affective processes to somatic sensations and common illnesses. The feeling space was determined by a combination of basic dimension rating, similarity mapping, bodily sensation mapping, and neuroimaging meta-analysis. A total of 1,026 participants took part in online surveys where we assessed (i) for each feeling, the intensity of four hypothesized basic dimensions (mental experience, bodily sensation, emotion, and controllability), (ii) subjectively experienced similarity of the 100 feelings, and (iii) topography of bodily sensations associated with each feeling. Neural similarity between a subset of the feeling states was derived from the NeuroSynth meta-analysis database based on the data from 9,821 brain-imaging studies. All feelings were emotionally valenced and the saliency of bodily sensations correlated with the saliency of mental experiences associated with each feeling. Nonlinear dimensionality reduction revealed five feeling clusters: positive emotions, negative emotions, cognitive processes, somatic states and illnesses, and homeostatic states. Organization of the feeling space was best explained by basic dimensions of emotional valence, mental experiences, and bodily sensations. Subjectively felt similarity of feelings was associated with basic feeling dimensions and the topography of the corresponding bodily sensations. These findings reveal a map of subjective feelings that are categorical, emotional, and embodied.

Reproducibility of importance extraction methods in neural network based fMRI classification

Recent advances in machine learning allow faster training, improved performance and increased interpretability of classification techniques. Consequently, their application in neuroscience is rapidly increasing. While classification approaches have proved useful in functional magnetic resonance imaging (fMRI) studies, there are concerns regarding extraction, reproducibility and visualization of brain regions that contribute most significantly to the classification. We addressed these issues using an fMRI classification scheme based on neural networks and compared a set of methods for extraction of category-related voxel importances in three simulated and two empirical datasets. The simulation data revealed that the proposed scheme successfully detects spatially distributed and overlapping activation patterns upon successful classification. Application of the proposed classification scheme to two previously published empirical fMRI datasets revealed robust importance maps that extensively overlap with univariate maps but also provide complementary information. Our results demonstrate increased statistical power of importance maps compared to univariate approaches for both detection of overlapping patterns and patterns with weak univariate information.

Sharing the social world via intersubject neural synchronisation

Sociability and capability of shared mental states are hallmarks of the human species, and pursuing shared goals oftentimes requires coordinating both behaviour and mental states. Here we review recent work using indices of intersubject neural synchronisation for measuring similarity of mental states across individuals. We discuss the methodological advances and limitations in the analyses based on intersubject synchrony, and discuss how these kinds of model-free analysis techniques enable the investigation of the brain basis of complex social processes. We argue that similarity of brain activity across individuals can be used, under certain conditions, to index the similarity of their subjective states of consciousness, and thus be used for investigating brain basis of mutual understanding and cooperation.

Effects of spatial smoothing on functional brain networks

Graph-theoretical methods have rapidly become a standard tool in studies of the structure and function of the human brain. Whereas the structural connectome can be fairly straightforwardly mapped onto a complex network, there are more degrees of freedom in constructing networks that represent functional connections between brain areas. For functional magnetic resonance imaging (fMRI) data, such networks are typically built by aggregating the blood-oxygen-level dependent signal time series of voxels into larger entities (such as Regions of Interest in some brain atlas) and determining their connection strengths from some measure of time-series correlations. Although it is evident that the outcome must be affected by how the voxel-level time series are treated at the preprocessing stage, there is a lack of systematic studies of the effects of preprocessing on network structure. Here, we focus on the effects of spatial smoothing, a standard preprocessing method for fMRI. We apply various levels of spatial smoothing to resting-state fMRI data and measure the changes induced in functional networks. We show that the level of spatial smoothing clearly affects the degrees and other centrality measures of functional network nodes; these changes are non-uniform, systematic, and depend on the geometry of the brain. The composition of the largest connected network component is also affected in a way that artificially increases the similarity of the networks of different subjects. Our conclusion is that wherever possible, spatial smoothing should be avoided when preprocessing fMRI data for network analysis.

Differential inter-subject correlation of brain activity when kinship is a variable in moral dilemma

Previous behavioural studies have shown that humans act more altruistically towards kin. Whether and how knowledge of genetic relatedness translates into differential neurocognitive evaluation of observed social interactions has remained an open question. Here, we investigated how the human brain is engaged when viewing a moral dilemma between genetic vs. non-genetic sisters. During functional magnetic resonance imaging, a movie was shown, depicting refusal of organ donation between two sisters, with subjects guided to believe the sisters were related either genetically or by adoption. Although 90% of the subjects self-reported that genetic relationship was not relevant, their brain activity told a different story. Comparing correlations of brain activity across all subject pairs between the two viewing conditions, we found significantly stronger inter-subject correlations in insula, cingulate, medial and lateral prefrontal, superior temporal, and superior parietal cortices, when the subjects believed that the sisters were genetically related. Cognitive functions previously associated with these areas include moral and emotional conflict regulation, decision making, and mentalizing, suggesting more similar engagement of such functions when observing refusal of altruism from a genetic sister. Our results show that mere knowledge of a genetic relationship between interacting persons robustly modulates social cognition of the perceiver.

Consistency of Regions of Interest as nodes of fMRI functional brain networks

The functional network approach, where fMRI BOLD time series are mapped to networks depicting functional relationships between brain areas, has opened new insights into the function of the human brain. In this approach, the choice of network nodes is of crucial importance. One option is to consider fMRI voxels as nodes. This results in a large number of nodes, making network analysis and interpretation of results challenging. A common alternative is to use predefined clusters of anatomically close voxels, Regions of Interest (ROIs). This approach assumes that voxels within ROIs are functionally similar. Because these two approaches result in different network structures, it is crucial to understand what happens to network connectivity when moving from the voxel level to the ROI level. We show that the consistency of ROIs, defined as the mean Pearson correlation coefficient between the time series of their voxels, varies widely in resting-state experimental data. Therefore the assumption of similar voxel dynamics within each ROI does not generally hold. Further, the time series of low-consistency ROIs may be highly correlated, resulting in spurious links in ROI-level networks. Based on these results, we recommend that averaging BOLD signals over anatomically defined ROIs should be carefully considered.

Network methods have opened new insights on structure and functional dynamics of the human brain. However, constructing functional brain networks is far from trivial—the neuroscientific community still lacks a standard definition of the nodes of brain networks. In the present article, we consider the two most commonly used approaches: using either imaging voxels or predefined Regions of Interest (ROIs) as nodes of the network. We investigate what happens when voxel-level signals are averaged for obtaining ROI-level networks. We introduce the concept of ROI consistency to characterize the similarity of the dynamics of voxels in an ROI. With the help of consistency, we show that although voxels in an ROI are assumed to behave similarly, this assumption does not hold for all ROIs.

Single dose of mirtazapine modulates whole-brain functional connectivity during emotional narrative processing

The link between neurotransmitter-level effects of antidepressants and their clinical effect remain poorly understood. A single dose of mirtazapine decreases limbic responses to fearful faces in healthy subjects, but it is unknown whether this effect applies to complex emotional situations and dynamic connectivity between brain regions. Thirty healthy volunteers listened to spoken emotional narratives during functional magnetic resonance imaging (fMRI). In an open-label design, 15 subjects received 15mg of mirtazapine two hours prior to fMRI while 15 subjects served as a control group. We assessed the effects of mirtazapine on regional neural responses and dynamic functional connectivity associated with valence and arousal. Mirtazapine attenuated responses to unpleasant events in the right fronto-insular cortex, while modulating responses to arousing events in the core limbic regions and the cortical midline structures (CMS). Mirtazapine decreased responses to unpleasant and arousing events in sensorimotor areas and the anterior CMS implicated in self-referential processing and formation of subjective feelings. Mirtazapine increased functional connectivity associated with positive valence in the CMS and limbic regions. Mirtazapine triggers large-scale changes in regional responses and functional connectivity during naturalistic, emotional stimuli. These span limbic, sensorimotor, and midline brain structures, and may be relevant to the clinical effectiveness of mirtazapine.

Distributed neural signatures of natural audiovisual speech and music in the human auditory cortex

During a conversation or when listening to music, auditory and visual information are combined automatically into audiovisual objects. However, it is still poorly understood how specific type of visual information shapes neural processing of sounds in lifelike stimulus environments. Here we applied multi-voxel pattern analysis to investigate how naturally matching visual input modulates supratemporal cortex activity during processing of naturalistic acoustic speech, singing and instrumental music. Bayesian logistic regression classifiers with sparsity-promoting priors were trained to predict whether the stimulus was audiovisual or auditory, and whether it contained piano playing, speech, or singing. The predictive performances of the classifiers were tested by leaving one participant at a time for testing and training the model using the remaining 15 participants. The signature patterns associated with unimodal auditory stimuli encompassed distributed locations mostly in the middle and superior temporal gyrus (STG/MTG). A pattern regression analysis, based on a continuous acoustic model, revealed that activity in some of these MTG and STG areas were associated with acoustic features present in speech and music stimuli. Concurrent visual stimulus modulated activity in bilateral MTG (speech), lateral aspect of right anterior STG (singing), and bilateral parietal opercular cortex (piano). Our results suggest that specific supratemporal brain areas are involved in processing complex natural speech, singing, and piano playing, and other brain areas located in anterior (facial speech) and posterior (music-related hand actions) supratemporal cortex are influenced by related visual information. Those anterior and posterior supratemporal areas have been linked to stimulus identification and sensory-motor integration, respectively.

Graph coarse-graining reveals differences in the module-level structure of functional brain networks

Networks have become a standard tool for analyzing functional magnetic resonance imaging (fMRI) data. In this approach, brain areas and their functional connections are mapped to the nodes and links of a network. Even though this mapping reduces the complexity of the underlying data, it remains challenging to understand the structure of the resulting networks due to the large number of nodes and links. One solution is to partition networks into modules and then investigate the modules' composition and relationship with brain functioning. While this approach works well for single networks, understanding differences between two networks by comparing their partitions is difficult and alternative approaches are thus necessary. To this end, we present a coarse-graining framework that uses a single set of data-driven modules as a frame of reference, enabling one to zoom out from the node- and link-level details. As a result, differences in the module-level connectivity can be understood in a transparent, statistically verifiable manner. We demonstrate the feasibility of the method by applying it to networks constructed from fMRI data recorded from 13 healthy subjects during rest and movie viewing. While independently partitioning the rest and movie networks is shown to yield little insight, the coarse-graining framework enables one to pinpoint differences in the module-level structure, such as the increased number of intra-module links within the visual cortex during movie viewing. In addition to quantifying differences due to external stimuli, the approach could also be applied in clinical settings, such as comparing patients with healthy controls.

Topography of Human Erogenous Zones

Touching is a powerful means for eliciting sexual arousal. Here, we establish the topographical organization of bodily regions triggering sexual arousal in humans. A total of 704 participants were shown images of same and opposite sex bodies and asked to color the bodily regions whose touching they or members of the opposite sex would experience as sexually arousing while masturbating or having sex with a partner. Resulting erogenous zone maps (EZMs) revealed that the whole body was sensitive to sexual touching, with erogenous hotspots consisting of genitals, breasts, and anus. The EZM area was larger while having sex with a partner versus while masturbating, and was also dependent on sexual desire and heterosexual and homosexual interest levels. We conclude that tactile stimulation of practically all bodily regions may trigger sexual arousal. Extension of the erogenous zones while having sex with a partner may reflect the role of touching in maintenance of reproductive pair bonds.

Bodily maps of emotions across child development

Different basic emotions (anger, fear, disgust, happiness, sadness, and surprise) are consistently associated with distinct bodily sensation maps, which may underlie subjectively felt emotions. Here we investigated the development of bodily sensations associated with basic emotions in 6- to 17-year-old children and adolescents (n = 331). Children as young as 6 years of age associated statistically discernible, discrete patterns of bodily sensations with happiness, fear, and surprise, as well as with emotional neutrality. The bodily sensation maps changed from less to more specific, adult-like patterns as a function of age. We conclude that emotion-related bodily sensations become increasingly discrete over child development. Developing awareness of their emotion-related bodily sensations may shape the way children perceive, label, and interpret emotions.

Reorganization of functionally connected brain subnetworks in high-functioning autism

Previous functional connectivity studies have found both hypo- and hyper-connectivity in brains of individuals having autism spectrum disorder (ASD). Here we studied abnormalities in functional brain subnetworks in high-functioning individuals with ASD during free viewing of a movie containing social cues and interactions. Twenty-six subjects (13 with ASD) watched a 68-min movie during functional magnetic resonance imaging. For each subject, we computed Pearson's correlation between haemodynamic time-courses of each pair of 6-mm isotropic voxels. From the whole-brain functional networks, we derived individual and group-level subnetworks using graph theory. Scaled inclusivity was then calculated between all subject pairs to estimate intersubject similarity of connectivity structure of each subnetwork. Additional 54 individuals (27 with ASD) from the ABIDE resting-state database were included to test the reproducibility of the results. Between-group differences were observed in the composition of default-mode and ventro-temporal-limbic (VTL) subnetworks. The VTL subnetwork included amygdala, striatum, thalamus, parahippocampal, fusiform, and inferior temporal gyri. Further, VTL subnetwork similarity between subject pairs correlated significantly with similarity of symptom gravity measured with autism quotient. This correlation was observed also within the controls, and in the reproducibility dataset with ADI-R and ADOS scores. Our results highlight how the reorganization of functional subnetworks in individuals with ASD clarifies the mixture of hypo- and hyper-connectivity findings. Importantly, only the functional organization of the VTL subnetwork emerges as a marker of inter-individual similarities that co-vary with behavioral measures across all participants. These findings suggest a pivotal role of ventro-temporal and limbic systems in autism.

Topography of social touching depends on emotional bonds between humans

Nonhuman primates use social touch for maintenance and reinforcement of social structures, yet the role of social touch in human bonding in different reproductive, affiliative, and kinship-based relationships remains unresolved. Here we reveal quantified, relationship-specific maps of bodily regions where social touch is allowed in a large cross-cultural dataset (N = 1,368 from Finland, France, Italy, Russia, and the United Kingdom). Participants were shown front and back silhouettes of human bodies with a word denoting one member of their social network. They were asked to color, on separate trials, the bodily regions where each individual in their social network would be allowed to touch them. Across all tested cultures, the total bodily area where touching was allowed was linearly dependent (mean r(2) = 0.54) on the emotional bond with the toucher, but independent of when that person was last encountered. Close acquaintances and family members were touched for more reasons than less familiar individuals. The bodily area others are allowed to touch thus represented, in a parametric fashion, the strength of the relationship-specific emotional bond. We propose that the spatial patterns of human social touch reflect an important mechanism supporting the maintenance of social bonds.

Fronto-parietal network supports context-dependent speech comprehension

Knowing the context of a discourse is an essential prerequisite for comprehension. Here we used functional magnetic resonance imaging (fMRI) to disclose brain networks supporting context-dependent speech comprehension. During fMRI, 20 participants listened to 1-min spoken narratives preceded by pictures that were either contextually matching or mismatching with the narrative. Matching pictures increased narrative comprehension, decreased hemodynamic activity in Broca׳s area, and enhanced its functional connectivity with left anterior superior frontal gyrus, bilateral inferior parietal cortex, as well as anterior and posterior cingulate cortex. Further, the anterior (BA 45) and posterior (BA 44) portions of Broca׳s area differed in their functional connectivity patterns. Both BA 44 and BA 45 have shown increased connectivity with right angular gyrus and supramarginal gyrus. Whereas BA 44 showed increased connectivity with left angular gyrus, left inferior/middle temporal gyrus and left postcentral gyrus, BA 45 showed increased connectivity with right posterior cingulate cortex, right anterior inferior frontal gyrus, lateral occipital cortex and anterior cingulate cortex. Our results suggest that a fronto-parietal functional network supports context-dependent narrative comprehension, and that Broca׳s area is involved in resolving ambiguity from speech when appropriate contextual cues are lacking.

Emotional speech synchronizes brains across listeners and engages large-scale dynamic brain networks

Speech provides a powerful means for sharing emotions. Here we implement novel intersubject phase synchronization and whole-brain dynamic connectivity measures to show that networks of brain areas become synchronized across participants who are listening to emotional episodes in spoken narratives. Twenty participants' hemodynamic brain activity was measured with functional magnetic resonance imaging (fMRI) while they listened to 45-s narratives describing unpleasant, neutral, and pleasant events spoken in neutral voice. After scanning, participants listened to the narratives again and rated continuously their feelings of pleasantness–unpleasantness (valence) and of arousal–calmness. Instantaneous intersubject phase synchronization (ISPS) measures were computed to derive both multi-subject voxel-wise similarity measures of hemodynamic activity and inter-area functional dynamic connectivity (seed-based phase synchronization, SBPS). Valence and arousal time series were subsequently used to predict the ISPS and SBPS time series. High arousal was associated with increased ISPS in the auditory cortices and in Broca's area, and negative valence was associated with enhanced ISPS in the thalamus, anterior cingulate, lateral prefrontal, and orbitofrontal cortices. Negative valence affected functional connectivity of fronto-parietal, limbic (insula, cingulum) and fronto-opercular circuitries, and positive arousal affected the connectivity of the striatum, amygdala, thalamus, cerebellum, and dorsal frontal cortex. Positive valence and negative arousal had markedly smaller effects. We propose that high arousal synchronizes the listeners' sound-processing and speech-comprehension networks, whereas negative valence synchronizes circuitries supporting emotional and self-referential processing.

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We model how emotional speech synchronizes brains across listeners.

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Participants listened to emotional and neutral narratives during fMRI scan.

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Arousal synchronized auditory cortices and Broca's area.

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Valence synchronized limbic system, prefrontal, and orbitofrontal cortices.

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Valence and arousal triggered distinct patterns of dynamic functional connectivity.

Synchronous brain activity across individuals underlies shared psychological perspectives

For successful communication, we need to understand the external world consistently with others. This task requires sufficiently similar cognitive schemas or psychological perspectives that act as filters to guide the selection, interpretation and storage of sensory information, perceptual objects and events. Here we show that when individuals adopt a similar psychological perspective during natural viewing, their brain activity becomes synchronized in specific brain regions. We measured brain activity with functional magnetic resonance imaging (fMRI) from 33 healthy participants who viewed a 10-min movie twice, assuming once a ‘social’ (detective) and once a ‘non-social’ (interior decorator) perspective to the movie events. Pearson's correlation coefficient was used to derive multisubject voxelwise similarity measures (inter-subject correlations; ISCs) of functional MRI data. We used k-nearest-neighbor and support vector machine classifiers as well as a Mantel test on the ISC matrices to reveal brain areas wherein ISC predicted the participants' current perspective. ISC was stronger in several brain regions—most robustly in the parahippocampal gyrus, posterior parietal cortex and lateral occipital cortex—when the participants viewed the movie with similar rather than different perspectives. Synchronization was not explained by differences in visual sampling of the movies, as estimated by eye gaze. We propose that synchronous brain activity across individuals adopting similar psychological perspectives could be an important neural mechanism supporting shared understanding of the environment.

Posterior parietal cortex activity reflects the significance of others' actions during natural viewing

The posterior parietal cortex (PPC) has been associated with multiple stimulus-driven (e.g., processing stimulus movements, providing visual signals for the motor system), goal-directed (e.g., directing visual attention to a target, processing behavioral priority of intentions), and action-related functions in previous studies with non-naturalistic paradigms. Here, we examined how these functions reflect PPC activity during natural viewing. Fourteen healthy volunteers watched a re-edited movie during functional magnetic resonance imaging (fMRI). Participants separately annotated behavioral priority (accounting for percepts, thoughts, and emotions) they had experienced during movie episodes. Movements in the movie were quantified with computer vision and eye movements were recorded from a separate group of subjects. Our results show that while overlapping dorsomedial PPC areas respond to episodes with multiple types of stimulus content, ventrolateral PPC areas exhibit enhanced activity when viewing goal-directed human hand actions. Furthermore, PPC activity related to viewing goal-directed human hand actions was more accurately explained by behavioral priority than by movements of the stimulus or eye movements. Taken together, our results suggest that PPC participates in perception of goal-directed human hand actions, supporting the view that PPC has a special role in providing visual signals for the motor system ("how"), in addition to processing visual spatial movements ("where").

The brains of high functioning autistic individuals do not synchronize with those of others

Multifaceted and idiosyncratic aberrancies in social cognition characterize autism spectrum disorders (ASDs). To advance understanding of underlying neural mechanisms, we measured brain hemodynamic activity with functional magnetic resonance imaging (fMRI) in individuals with ASD and matched-pair neurotypical (NT) controls while they were viewing a feature film portraying social interactions. Pearson's correlation coefficient was used as a measure of voxelwise similarity of brain activity (InterSubject Correlations—ISCs). Individuals with ASD showed lower ISC than NT controls in brain regions implicated in processing social information including the insula, posterior and anterior cingulate cortex, caudate nucleus, precuneus, lateral occipital cortex, and supramarginal gyrus. Curiously, also within NT group, autism-quotient scores predicted ISC in overlapping areas, including, e.g., supramarginal gyrus and precuneus. In ASD participants, functional connectivity was decreased between the frontal pole and the superior frontal gyrus, angular gyrus, superior parietal lobule, precentral gyrus, precuneus, and anterior/posterior cingulate gyrus. Taken together these results suggest that ISC and functional connectivity measure distinct features of atypical brain function in high-functioning autistic individuals during free viewing of acted social interactions. Our ISC results suggest that the minds of ASD individuals do not ‘tick together’ with others while perceiving identical dynamic social interactions.

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We studied brain function in autism during free viewing of social interactions.

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The brains of individuals with autism do not ‘tick together’ with others.

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Long-range functional connectivity is altered in individuals with autism.

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Link between autistic traits and social brain synchrony extends to normal population.