Neural correlates of explicit social judgments on vocal stimuli

A parcellation scheme of mouse isocortex based on reversals in connectivity gradients

The brain is composed of several anatomically clearly separated structures. This parcellation is often extended into the isocortex, based on anatomical, physiological, or functional differences. Here, we derive a parcellation scheme based purely on the spatial structure of long-range synaptic connections within the cortex. To that end, we analyzed a publicly available dataset of average mouse brain connectivity, and split the isocortex into disjunct regions. Instead of clustering connectivity based on modularity, our scheme is inspired by methods that split sensory cortices into subregions where gradients of neuronal response properties, such as the location of the receptive field, reverse. We calculated comparable gradients from voxelized brain connectivity data and automatically detected reversals in them. This approach better respects the known presence of functional gradients within brain regions than clustering-based approaches. Placing borders at the reversals resulted in a parcellation into 41 subregions that differs significantly from an established scheme in nonrandom ways, but is comparable in terms of the modularity of connectivity between regions. It reveals unexpected trends of connectivity, such as a tripartite split of somatomotor regions along an anterior to posterior gradient. The method can be readily adapted to other organisms and data sources, such as human functional connectivity.

Connectome-based prediction of marital quality in husbands' processing of spousal interactions

Marital quality may decrease during the early years of marriage. Establishing models predicting individualized marital quality may help develop timely and effective interventions to maintain or improve marital quality. Given that marital interactions have an important impact on marital well-being cross-sectionally and prospectively, neural responses during marital interactions may provide insight into neural bases underlying marital well-being. The current study applies connectome-based predictive modeling, a recently developed machine-learning approach, to functional magnetic resonance imaging (fMRI) data from both partners of 25 early-stage Chinese couples to examine whether an individual's unique pattern of brain functional connectivity (FC) when responding to spousal interactive behaviors can reliably predict their own and their partners' marital quality after 13 months. Results revealed that husbands' FC involving multiple large networks, when responding to their spousal interactive behaviors, significantly predicted their own and their wives' marital quality, and this predictability showed gender specificity. Brain connectivity patterns responding to general emotional stimuli and during the resting state were not significantly predictive. This study demonstrates that husbands' differences in large-scale neural networks during marital interactions may contribute to their variability in marital quality and highlights gender-related differences. The findings lay a foundation for identifying reliable neuroimaging biomarkers for developing interventions for marital quality early in marriages.

Social Processing in Eating Disorders: Neuroimaging Paradigms and Research Domain Organizational Constructs

PURPOSE OF REVIEW

Social and environmental factors have been related to both symptom expression of disordered eating in individuals and changes in the prevalence of eating disorders (EDs) in populations. Neural differences in processing social information may contribute to EDs. This review assesses the evidence for aberrant neural responses during social processing in EDs.

RECENT FINDINGS

This review examines how constructs within the social processing domain have been evaluated by neuroimaging paradigms in EDs, including communication, affiliation, and understanding of both oneself and others. Differences related to social processing in EDs include altered processing for self-relevant stimuli, in the context of identity, valence, expectations, and affiliative relationships. Future work is needed to integrate how differences in processing social stimuli relate to alterations in cognitive control and reward as well as specific disordered eating symptoms.

The “beauty premium” effect of voice attractiveness of long speech sounds in outcome-evaluation event-related potentials in a trust game

Previous research suggested that people with attractive voices had an advantage in economic games, even if the voices were only presented for 400 ms. The present study investigated the influence of voice attractiveness on the cooperative trust behavior with longer exposure times to the voices. Event-related potentials (ERPs) were recorded during the feedback outcome evaluation. Participants heard a voice of the partner for 2,040 ms and decided whether to invest to the partner for a possibility to gain more money. The results showed that participants made more invest choices to the attractive partners, replicating the “beauty premium” effect of the attractive voices. Moreover, participants were more likely to invest to male partners. The ERP analysis for the outcome showed that the difference waves of feedback-related negativity (FRN) amplitude were smaller in the attractive voice condition than in the unattractive voice condition, suggesting that the rewarding effect of attractive voices weakened the frustrating feelings of the loss. In sum, the present study confirms that attractive voices with longer presentation durations facilitate cooperative behavior and modulate the processing of feedback evaluations.

How does hemispheric specialization contribute to human-defining cognition?

Uniquely human cognitive faculties arise from flexible interplay between specific local neural modules, with hemispheric asymmetries in functional specialization. Here, we discuss how these computational design principles provide a scaffold that enables some of the most advanced cognitive operations, such as semantic understanding of world structure, logical reasoning, and communication via language. We draw parallels to dual-processing theories of cognition by placing a focus on Kahneman's System 1 and System 2. We propose integration of these ideas with the global workspace theory to explain dynamic relay of information products between both systems. Deepening the current understanding of how neurocognitive asymmetry makes humans special can ignite the next wave of neuroscience-inspired artificial intelligence.

Supramodal neural networks support top-down processing of social signals

The perception of facial and vocal stimuli is driven by sensory input and cognitive top‐down influences. Important top‐down influences are attentional focus and supramodal social memory representations. The present study investigated the neural networks underlying these top‐down processes and their role in social stimulus classification. In a neuroimaging study with 45 healthy participants, we employed a social adaptation of the Implicit Association Test. Attentional focus was modified via the classification task, which compared two domains of social perception (emotion and gender), using the exactly same stimulus set. Supramodal memory representations were addressed via congruency of the target categories for the classification of auditory and visual social stimuli (voices and faces). Functional magnetic resonance imaging identified attention‐specific and supramodal networks. Emotion classification networks included bilateral anterior insula, pre‐supplementary motor area, and right inferior frontal gyrus. They were pure attention‐driven and independent from stimulus modality or congruency of the target concepts. No neural contribution of supramodal memory representations could be revealed for emotion classification. In contrast, gender classification relied on supramodal memory representations in rostral anterior cingulate and ventromedial prefrontal cortices. In summary, different domains of social perception involve different top‐down processes which take place in clearly distinguishable neural networks.

Children and adolescents' neural response to emotional faces and voices: Age-related changes in common regions of activation

The perception of facial and vocal emotional expressions engages overlapping regions of the brain. However, at a behavioral level, the ability to recognize the intended emotion in both types of nonverbal cues follows a divergent developmental trajectory throughout childhood and adolescence. The current study a) identified regions of common neural activation to facial and vocal stimuli in 8- to 19-year-old typically-developing adolescents, and b) examined age-related changes in blood-oxygen-level dependent (BOLD) response within these areas. Both modalities elicited activation in an overlapping network of subcortical regions (insula, thalamus, dorsal striatum), visual-motor association areas, prefrontal regions (inferior frontal cortex, dorsomedial prefrontal cortex), and the right superior temporal gyrus. Within these regions, increased age was associated with greater frontal activation to voices, but not faces. Results suggest that processing facial and vocal stimuli elicits activation in common areas of the brain in adolescents, but that age-related changes in response within these regions may vary by modality.

Human voice attractiveness processing: Electrophysiological evidence

Voice attractiveness plays a significant role in social interaction and mate choice. However, how listeners perceive attractive voices and whether this process is mandatory, is poorly understood. The current study explores this question using event-related brain potentials. Participants listened to syllables spoken by male and female voices with high or low attractiveness while completing an implicit (voice un-related) tone detection task or explicitly judging voice attractiveness. In both tasks, attractive male voices elicited a larger N1 than unattractive voices. However, an effect of voice attractiveness on the late positive complex (LPC) was only seen in the explicit task but it was present to both same- and opposite-sex voices. Taken together, voice attractiveness processing during early stages appears to be rapid and mandatory and related to mate selection, whereas during later elaborated processing, voice attractiveness is strategic and aesthetics-based, requiring attentional resources.

To believe or not to believe? How voice and accent information in speech alter listener impressions of trust

Our decision to believe what another person says can be influenced by vocally expressed confidence in speech and by whether the speaker–listener are members of the same social group. The dynamic effects of these two information sources on neurocognitive processes that promote believability impressions from vocal cues are unclear. Here, English Canadian listeners were presented personal statements ( She has access to the building) produced in a confident or doubtful voice by speakers of their own dialect (in-group) or speakers from two different “out-groups” (regional or foreign-accented English). Participants rated how believable the speaker is for each statement and event-related potentials (ERPs) were analysed from utterance onset. Believability decisions were modulated by both the speaker’s vocal confidence level and their perceived in-group status. For in-group speakers, ERP effects revealed an early differentiation of vocally expressed confidence (i.e., N100, P200), highlighting the motivational significance of doubtful voices for drawing believability inferences. These early effects on vocal confidence perception were qualitatively different or absent when speakers had an accent; evaluating out-group voices was associated with increased demands on contextual integration and re-analysis of a non-native representation of believability (i.e., increased N400, late negativity response). Accent intelligibility and experience with particular out-group accents each influenced how vocal confidence was processed for out-group speakers. The N100 amplitude was sensitive to out-group attitudes and predicted actual believability decisions for certain out-group speakers. We propose a neurocognitive model in which vocal identity information (social categorization) dynamically influences how vocal expressions are decoded and used to derive social inferences during person perception.

Is the voice an auditory face? An ALE meta-analysis comparing vocal and facial emotion processing

This meta-analysis compares the brain structures and mechanisms involved in facial and vocal emotion recognition. Neuroimaging studies contrasting emotional with neutral (face: N = 76, voice: N = 34) and explicit with implicit emotion processing (face: N = 27, voice: N = 20) were collected to shed light on stimulus and goal-driven mechanisms, respectively. Activation likelihood estimations were conducted on the full data sets for the separate modalities and on reduced, modality-matched data sets for modality comparison. Stimulus-driven emotion processing engaged large networks with significant modality differences in the superior temporal (voice-specific) and the medial temporal (face-specific) cortex. Goal-driven processing was associated with only a small cluster in the dorsomedial prefrontal cortex for voices but not faces. Neither stimulus- nor goal-driven processing showed significant modality overlap. Together, these findings suggest that stimulus-driven processes shape activity in the social brain more powerfully than goal-driven processes in both the visual and the auditory domains. Yet, whereas faces emphasize subcortical emotional and mnemonic mechanisms, voices emphasize cortical mechanisms associated with perception and effortful stimulus evaluation (e.g. via subvocalization). These differences may be due to sensory stimulus properties and highlight the need for a modality-specific perspective when modeling emotion processing in the brain.

Individual identity and affective valence in marmoset calls: in vivo brain imaging with vocal sound playback

As with humans, vocal communication is an important social tool for nonhuman primates. Common marmosets (Callithrix jacchus) often produce whistle-like 'phee' calls when they are visually separated from conspecifics. The neural processes specific to phee call perception, however, are largely unknown, despite the possibility that these processes involve social information. Here, we examined behavioral and whole-brain mapping evidence regarding the detection of individual conspecific phee calls using an audio playback procedure. Phee calls evoked sound exploratory responses when the caller changed, indicating that marmosets can discriminate between caller identities. Positron emission tomography with [18F] fluorodeoxyglucose revealed that perception of phee calls from a single subject was associated with activity in the dorsolateral prefrontal, medial prefrontal, orbitofrontal cortices, and the amygdala. These findings suggest that these regions are implicated in cognitive and affective processing of salient social information. However, phee calls from multiple subjects induced brain activation in only some of these regions, such as the dorsolateral prefrontal cortex. We also found distinctive brain deactivation and functional connectivity associated with phee call perception depending on the caller change. According to changes in pupillary size, phee calls from a single subject induced a higher arousal level compared with those from multiple subjects. These results suggest that marmoset phee calls convey information about individual identity and affective valence depending on the consistency or variability of the caller. Based on the flexible perception of the call based on individual recognition, humans and marmosets may share some neural mechanisms underlying conspecific vocal perception.

Neural systems for evaluating speaker (Un)believability

Our voice provides salient cues about how confident we sound, which promotes inferences about how believable we are. However, the neural mechanisms involved in these social inferences are largely unknown. Employing functional magnetic resonance imaging, we examined the brain networks and individual differences underlying the evaluation of speaker believability from vocal expressions. Participants (n = 26) listened to statements produced in a confident, unconfident, or "prosodically unmarked" (neutral) voice, and judged how believable the speaker was on a 4-point scale. We found frontal-temporal networks were activated for different levels of confidence, with the left superior and inferior frontal gyrus more activated for confident statements, the right superior temporal gyrus for unconfident expressions, and bilateral cerebellum for statements in a neutral voice. Based on listener's believability judgment, we observed increased activation in the right superior parietal lobule (SPL) associated with higher believability, while increased left posterior central gyrus (PoCG) was associated with less believability. A psychophysiological interaction analysis found that the anterior cingulate cortex and bilateral caudate were connected to the right SPL when higher believability judgments were made, while supplementary motor area was connected with the left PoCG when lower believability judgments were made. Personal characteristics, such as interpersonal reactivity and the individual tendency to trust others, modulated the brain activations and the functional connectivity when making believability judgments. In sum, our data pinpoint neural mechanisms that are involved when inferring one's believability from a speaker's voice and establish ways that these mechanisms are modulated by individual characteristics of a listener. Hum Brain Mapp 38:3732-3749, 2017. © 2017 Wiley Periodicals, Inc.

Criticism hurts everybody, praise only some: Common and specific neural responses to approving and disapproving social-evaluative videos

Social evaluation is a ubiquitous feature of daily interpersonal interactions and can produce strong positive or negative emotional reactions. While previous research has highlighted neural correlates of static or dynamic facial expressions, little is known about neural processing of more naturalistic social interaction simulations or the modulating role of inter-individual differences such as trait fear of negative/positive evaluation. The present fMRI study investigated neural activity of 37 (21 female) healthy participants while watching videos of posers expressing a range of positive, negative, and neutral statements tapping into several basic and social emotions. Unpleasantness ratings linearly increased in response to positive to neutral to negative videos whereas arousal ratings were elevated in both emotional video conditions. At the whole brain level, medial prefrontal and rostral anterior cingulate cortex activated strongly in both emotional conditions which may be attributed to the cognitive processing demands of responding to complex social evaluation. Region of interest analysis for basic emotion processing areas revealed enhanced amygdala activation in both emotional conditions, whereas anterior and posterior insula showed stronger activity during negative evaluations only. Individuals with high fear of positive evaluation were characterized by increased posterior insula activity during positive videos, suggesting heightened interoception. Taken together, these results replicate and extend studies that used facial expression stimuli and reveal neurobiological systems involved in processing of more complex social-evaluative videos. Results also point to vulnerability factors for social-interaction related psychopathologies.

Functional Segregation of the Human Dorsomedial Prefrontal Cortex

The human dorsomedial prefrontal cortex (dmPFC) has been implicated in various complex cognitive processes, including social cognition. To unravel its functional organization, we assessed the dmPFC's regional heterogeneity, connectivity patterns, and functional profiles. First, the heterogeneity of a dmPFC seed, engaged during social processing, was investigated by assessing local differences in whole-brain coactivation profiles. Second, functional connectivity of the ensuing dmPFC clusters was compared by task-constrained meta-analytic coactivation mapping and task-unconstrained resting-state correlations. Third, dmPFC clusters were functionally profiled by forward/reverse inference. The dmPFC seed was thus segregated into 4 clusters (rostroventral, rostrodorsal, caudal-right, and caudal-left). Both rostral clusters were connected to the amygdala and hippocampus and associated with memory and social cognitive tasks in functional decoding. The rostroventral cluster exhibited strongest connectivity to the default mode network. Unlike the rostral segregation, the caudal dmPFC was divided by hemispheres. The caudal-right cluster was strongly connected to a frontoparietal network (dorsal attention network), whereas the caudal-left cluster was strongly connected to the anterior midcingulate cortex and bilateral anterior insula (salience network). In conclusion, we demonstrate that a dmPFC seed reflecting social processing can be divided into 4 separate functional modules that contribute to distinct facets of advanced human cognition.

Connectivity-based parcellation: Critique and implications

Regional specialization and functional integration are often viewed as two fundamental principles of human brain organization. They are closely intertwined because each functionally specialized brain region is probably characterized by a distinct set of long-range connections. This notion has prompted the quickly developing family of connectivity-based parcellation (CBP) methods in neuroimaging research. CBP assumes that there is a latent structure of parcels in a region of interest (ROI). First, connectivity strengths are computed to other parts of the brain for each voxel/vertex within the ROI. These features are then used to identify functionally distinct groups of ROI voxels/vertices. CBP enjoys increasing popularity for the in-vivo mapping of regional specialization in the human brain. Due to the requirements of different applications and datasets, CBP has diverged into a heterogeneous family of methods. This broad overview critically discusses the current state as well as the commonalities and idiosyncrasies of the main CBP methods. We target frequent concerns faced by novices and veterans to provide a reference for the investigation and review of CBP studies.

State-based functional connectivity changes associate with cognitive decline in amnestic mild cognitive impairment subjects

Episodic memory (EM) dysfunction is a central characteristic of amnestic mild cognitive impairment (aMCI) subjects, and has a high risk of converting to Alzheimer's disease (AD). However, it is unknown how the EM network is modulated when a situation is switched. Twenty-six aMCI and twenty-two cognitively normal (CN) subjects were enrolled in this study. All of the subjects completed multi-dimensional neuropsychological tests and underwent functional magnetic resonance imaging scans during a resting-state and an episodic memory retrieval task state. The EM network was constructed using a seed-based functional connectivity (FC) approach. AMCI subjects showed poorer cognitive performances in the episodic memory and executive function. We demonstrated that connectivity of the left posterior parahippocampal gyrus (LpPHG) connected to the left ventral medial prefrontal cortex and the right postcentral gyrus (RPCG) was significantly decreased in aMCI subjects compared to CN subjects. Meanwhile, there was increased connectivity of the LpPHG to the right dorsal medial prefrontal cortex (RDMPFC), RPCG, left inferior parietal cortex, and bilateral superior parietal lobe in all of the subjects that changed from a resting-state to a task-state. Interestingly, the changed LpPHG-RDMPFC connectivity strength was significantly correlated with EM scores and executive function in the aMCI subjects. As a result, general brain regions are functionally organized and integrated into the EM network, and this strongly suggests that more cognitive resources are mobilized to meet the challenge of cognitive demand in the task state. These findings extend our understanding of the underlying mechanisms of EM deficits in aMCI subjects.

Subspecialization in the human posterior medial cortex

The posterior medial cortex (PMC) is particularly poorly understood. Its neural activity changes have been related to highly disparate mental processes. We therefore investigated PMC properties with a data-driven exploratory approach. First, we subdivided the PMC by whole-brain coactivation profiles. Second, functional connectivity of the ensuing PMC regions was compared by task-constrained meta-analytic coactivation mapping (MACM) and task-unconstrained resting-state correlations (RSFC). Third, PMC regions were functionally described by forward/reverse functional inference. A precuneal cluster was mostly connected to the intraparietal sulcus, frontal eye fields, and right temporo-parietal junction; associated with attention and motor tasks. A ventral posterior cingulate cortex (PCC) cluster was mostly connected to the ventromedial prefrontal cortex and middle left inferior parietal cortex (IPC); associated with facial appraisal and language tasks. A dorsal PCC cluster was mostly connected to the dorsomedial prefrontal cortex, anterior/posterior IPC, posterior midcingulate cortex, and left dorsolateral prefrontal cortex; associated with delay discounting. A cluster in the retrosplenial cortex was mostly connected to the anterior thalamus and hippocampus. Furthermore, all PMC clusters were congruently coupled with the default mode network according to task-unconstrained but not task-constrained connectivity. We thus identified distinct regions in the PMC and characterized their neural networks and functional implications.