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The process of understanding the minds of other people, such as their emotions and intentions, is mimicked when individuals try to understand an artificial mind. The assumption is that anthropomorphism, attributing human-like characteristics to non-human agents and objects, is an analogue to theory-of-mind, the ability to infer mental states of other people. Here, we test to what extent these two constructs formally overlap. Specifically, using a multi-method approach, we test if and how anthropomorphism is related to theory-of-mind using brain (Experiment 1) and behavioural (Experiment 2) measures. In a first exploratory experiment, we examine the relationship between dispositional anthropomorphism and activity within the theory-of-mind brain network (n = 108). Results from a Bayesian regression analysis showed no consistent relationship between dispositional anthropomorphism and activity in regions of the theory-of-mind network. In a follow-up, pre-registered experiment, we explored the relationship between theory-of-mind and situational and dispositional anthropomorphism in more depth. Participants (n = 311) watched a short movie while simultaneously completing situational anthropomorphism and theory-of-mind ratings, as well as measures of dispositional anthropomorphism and general theory-of-mind. Only situational anthropomorphism predicted the ability to understand and predict the behaviour of the film's characters. No relationship between situational or dispositional anthropomorphism and general theory-of-mind was observed. Together, these results suggest that while the constructs of anthropomorphism and theory-of-mind might overlap in certain situations, they remain separate and possibly unrelated at the personality level. These findings point to a possible dissociation between brain and behavioural measures when considering the relationship between theory-of-mind and anthropomorphism., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Brain regions associated with the processing of tangible rewards (such as money, food, or sex) are also involved in anticipating social rewards and avoiding social punishment. To date, studies investigating the neural underpinnings of social reward have presented feedback via static or dynamic displays of faces to participants. However, research demonstrates that participants find another type of social stimulus, namely, biological motion, rewarding as well, and exert effort to engage with this type of stimulus. Here we examine whether feedback presented via body gestures in the absence of facial cues also acts as a rewarding stimulus and recruits reward-related brain regions. To achieve this, we investigated the neural underpinnings of anticipating social reward and avoiding social disapproval presented via gestures alone, using a social incentive delay task. As predicted, the anticipation of social reward and avoidance of social disapproval engaged reward-related brain regions, including the nucleus accumbens, in a manner similar to previous studies' reports of feedback presented via faces and money. This study provides the first evidence that human body motion alone engages brain regions associated with reward processing in a similar manner to other social (i.e. faces) and non-social (i.e. money) rewards. The findings advance our understanding of social motivation in human perception and behavior., (Copyright © 2020. Published by Elsevier Inc.)

To what extent can humans form social relationships with robots? In the present study, we combined functional neuroimaging with a robot socializing intervention to probe the flexibility of empathy, a core component of social relationships, towards robots. Twenty-six individuals underwent identical fMRI sessions before and after being issued a social robot to take home and interact with over the course of a week. While undergoing fMRI, participants observed videos of a human actor or a robot experiencing pain or pleasure in response to electrical stimulation. Repetition suppression of activity in the pain network, a collection of brain regions associated with empathy and emotional responding, was measured to test whether socializing with a social robot leads to greater overlap in neural mechanisms when observing human and robotic agents experiencing pain or pleasure. In contrast to our hypothesis, functional region-of-interest analyses revealed no change in neural overlap for agents after the socializing intervention. Similarly, no increase in activation when observing a robot experiencing pain emerged post-socializing. Whole-brain analysis showed that, before the socializing intervention, superior parietal and early visual regions are sensitive to novel agents, while after socializing, medial temporal regions show agent sensitivity. A region of the inferior parietal lobule was sensitive to novel emotions, but only during the pre-socializing scan session. Together, these findings suggest that a short socialization intervention with a social robot does not lead to discernible differences in empathy towards the robot, as measured by behavioural or brain responses. We discuss the extent to which long-term socialization with robots might shape social cognitive processes and ultimately our relationships with these machines. This article is part of the theme issue 'From social brains to social robots: applying neurocognitive insights to human-robot interaction'.

Amidst the fourth industrial revolution, social robots are resolutely moving from fiction to reality. With sophisticated artificial agents becoming ever more ubiquitous in daily life, researchers across different fields are grappling with the questions concerning how humans perceive and interact with these agents and the extent to which the human brain incorporates intelligent machines into our social milieu. This theme issue surveys and discusses the latest findings, current challenges and future directions in neuroscience- and psychology-inspired human-robot interaction (HRI). Critical questions are explored from a transdisciplinary perspective centred around four core topics in HRI: technical solutions for HRI, development and learning for HRI, robots as a tool to study social cognition, and moral and ethical implications of HRI. Integrating findings from diverse but complementary research fields, including social and cognitive neurosciences, psychology, artificial intelligence and robotics, the contributions showcase ways in which research from disciplines spanning biological sciences, social sciences and technology deepen our understanding of the potential and limits of robotic agents in human social life. This article is part of the theme issue 'From social brains to social robots: applying neurocognitive insights to human-robot interaction'.

How we perceive others in action is shaped by our prior experience. Many factors influence brain responses when observing others in action, including training in a particular physical skill, such as sport or dance, and also general development and aging processes. Here, we investigate how learning a complex motor skill shapes neural and behavioural responses among a dance-naïve sample of 20 young and 19 older adults. Across four days, participants physically rehearsed one set of dance sequences, observed a second set, and a third set remained untrained. Functional MRI was obtained prior to and immediately following training. Participants' behavioural performance on motor and visual tasks improved across the training period, with younger adults showing steeper performance gains than older adults. At the brain level, both age groups demonstrated decreased sensorimotor cortical engagement after physical training, with younger adults showing more pronounced decreases in inferior parietal activity compared to older adults. Neural decoding results demonstrate that among both age groups, visual and motor regions contain experience-specific representations of new motor learning. By combining behavioural measures of performance with univariate and multivariate measures of brain activity, we can start to build a more complete picture of age-related changes in experience-dependent plasticity.

Less than two decades after its inception, the burgeoning field of neuroaesthetics continues to grow in interest and momentum. Despite the biological and social importance of the human body and the attention people pay to its appearance in daily life, only recently has neuroaesthetic inquiry turned its attention to questions concerning the aesthetic appraisal of the human body. We review evidence illustrating that the complexity of aesthetic experience is reflected by dynamic interplay between brain systems involved in reward, perceptual and motor processing, with a focus on aesthetic perception involving the human body. We then evaluate work demonstrating how these systems are modulated by beholders' expertise or familiarity. Finally, we discuss seminal studies revealing the plasticity of behavioural and neural responses to beauty after perceptual and motor training. This research highlights the rich potential for neuroaesthetic inquiry to extend beyond its typical realm of the fine arts to address important questions regarding the relationship between embodiment, aesthetics and performing arts. We conclude by considering some of the criticisms and limitations of neuroaesthetics, and highlight several outstanding issues for future inquiry., (Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Successful social interactions depend on the ability to anticipate other people's actions. Current conceptualizations of brain function propose that causes of sensory input are inferred through their integration with internal predictions generated in the observer's motor system during action observation. Less is known concerning how action prediction changes with age. Previously we showed that internal action representations are less specific in older compared with younger adults at behavioral and neural levels. Here, we characterize how neural activity varies while healthy older adults aged 56-71 years predict the time-course of an unfolding action as well as the relation to task performance. By using fMRI, brain activity was measured while participants observed partly occluded actions and judged the temporal coherence of the action continuation that was manipulated. We found that neural activity in frontoparietal and occipitotemporal regions increased the more an action continuation was shifted backwards in time. Action continuations that were shifted towards the future preferentially engaged early visual cortices. Increasing age was associated with neural activity that extended from posterior to anterior regions in frontal and superior temporal cortices. Lower sensitivity in action prediction resulted in activity increases in the caudate. These results imply that the neural implementation of predicting actions undergoes similar changes as the neural process of executing actions in older adults. The comparison between internal predictions and sensory input seems to become less precise with age leading to difficulties in anticipating observed actions accurately, possibly due to less specific internal action models., (© 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.)

The way in which we perceive others in action is biased by one's prior experience with an observed action. For example, we can have auditory, visual, or motor experience with actions we observe others perform. How action experience via 1, 2, or all 3 of these modalities shapes action perception remains unclear. Here, we combine pre- and post-training functional magnetic resonance imaging measures with a dance training manipulation to address how building experience (from auditory to audiovisual to audiovisual plus motor) with a complex action shapes subsequent action perception. Results indicate that layering experience across these 3 modalities activates a number of sensorimotor cortical regions associated with the action observation network (AON) in such a way that the more modalities through which one experiences an action, the greater the response is within these AON regions during action perception. Moreover, a correlation between left premotor activity and participants' scores for reproducing an action suggests that the better an observer can perform an observed action, the stronger the neural response is. The findings suggest that the number of modalities through which an observer experiences an action impacts AON activity additively, and that premotor cortical activity might serve as an index of embodiment during action observation., (© The Author 2015. Published by Oxford University Press.)

Previous research on aesthetic preferences demonstrates that people are more likely to judge a stimulus as pleasing if it is familiar. Although general familiarity and liking are related, it is less clear how motor familiarity, or embodiment, relates to a viewer's aesthetic appraisal. This study directly compared how learning to embody an action impacts the neural response when watching and aesthetically evaluating the same action. Twenty-two participants trained for 4 days on dance sequences. Each day they physically rehearsed one set of sequences, passively watched a second set, listened to the music of a third set, and a fourth set remained untrained. Functional MRI was obtained prior to and immediately following the training period, as were affective and physical ability ratings for each dance sequence. This approach enabled precise comparison of self-report methods of embodiment with nonbiased, empirical measures of action performance. Results suggest that after experience, participants most enjoy watching those dance sequences they danced or observed. Moreover, brain regions involved in mediating the aesthetic response shift from subcortical regions associated with dopaminergic reward processing to posterior temporal regions involved in processing multisensory integration, emotion, and biological motion., (© 2014 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals Inc. on behalf of The New York Academy of Sciences.)

When watching another person's actions, a network of sensorimotor brain regions, collectively termed the action observation network (AON), is engaged. Previous research suggests that the AON is more responsive when watching familiar compared with unfamiliar actions. However, most research into AON function is premised on comparisons of AON engagement during different types of task using univariate, magnitude-based approaches. To better understand the relationship between action familiarity and AON engagement, here we examine how observed movement familiarity modulates AON activity in humans using dynamic causal modeling, a type of effective connectivity analysis. Twenty-one subjects underwent fMRI scanning while viewing whole-body dance movements that varied in terms of their familiarity. Participants' task was to either predict the next posture the dancer's body would assume or to respond to a non-action-related attentional control question. To assess individuals' familiarity with each movement, participants rated each video on a measure of visual familiarity after being scanned. Parametric analyses showed more activity in left middle temporal gyrus, inferior parietal lobule, and inferior frontal gyrus as videos were rated as increasingly familiar. These clusters of activity formed the regions of interest for dynamic causal modeling analyses, which revealed attenuation of effective connectivity bidirectionally between parietal and temporal AON nodes when participants observed videos they rated as increasingly familiar. As such, the findings provide partial support for a predictive coding model of the AON, as well as illuminate how action familiarity manipulations can be used to explore simulation-based accounts of action understanding., (Copyright © 2015 Gardner et al.)

Humans automatically imitate other people's actions during social interactions, building rapport and social closeness in the process. Although the behavioral consequences and neural correlates of imitation have been studied extensively, little is known about the neural mechanisms that control imitative tendencies. For example, the degree to which an agent is perceived as human-like influences automatic imitation, but it is not known how perception of animacy influences brain circuits that control imitation. In the current fMRI study, we examined how the perception and belief of animacy influence the control of automatic imitation. Using an imitation-inhibition paradigm that involves suppressing the tendency to imitate an observed action, we manipulated both bottom-up (visual input) and top-down (belief) cues to animacy. Results show divergent patterns of behavioral and neural responses. Behavioral analyses show that automatic imitation is equivalent when one or both cues to animacy are present but reduces when both are absent. By contrast, right TPJ showed sensitivity to the presence of both animacy cues. Thus, we demonstrate that right TPJ is biologically tuned to control imitative tendencies when the observed agent both looks like and is believed to be human. The results suggest that right TPJ may be involved in a specialized capacity to control automatic imitation of human agents, rather than a universal process of conflict management, which would be more consistent with generalist theories of imitative control. Evidence for specialized neural circuitry that "controls" imitation offers new insight into developmental disorders that involve atypical processing of social information, such as autism spectrum disorders.

Cook et al. overstate the evidence supporting their associative account of mirror neurons in humans: most studies do not address a key property, action-specificity that generalizes across the visual and motor domains. Multivariate pattern analysis (MVPA) of neuroimaging data can address this concern, and we illustrate how MVPA can be used to test key predictions of their account.

Seeing Suzie bite an apple or reading the sentence 'Suzie munched the apple' both convey a similar idea. But is there a common neural basis for action comprehension when generated through video or text? The current study used functional magnetic resonance imaging to address this question. Participants observed videos or read sentences that described two categories of actions: eating and cleaning. A conjunction analysis of video and sentence stimuli revealed that cleaning actions (compared to eating actions) showed a greater response in dorsal frontoparietal regions, as well as within the medial fusiform gyrus. These findings reveal supramodal representations of perceived actions in the human brain, which are specific to action categories and independent of input modality (video or written words). In addition, some brain regions associated with cleaning and eating actions showed an interaction with modality, which was manifested as a greater sensitivity for video compared with sentence stimuli. Together, this pattern of results demonstrates both supramodal and modality-sensitive representations of action categories in the human brain, a finding with implications for how we understand other people's actions from video and written sources.

Generating predictions during action observation is essential for efficient navigation through our social environment. With age, the sensitivity in action prediction declines. In younger adults, the action observation network (AON), consisting of premotor, parietal and occipitotemporal cortices, has been implicated in transforming executed and observed actions into a common code. Much less is known about age-related changes in the neural representation of observed actions. Using fMRI, the present study measured brain activity in younger and older adults during the prediction of temporarily occluded actions (figure skating elements and simple movement exercises). All participants were highly familiar with the movement exercises whereas only some participants were experienced figure skaters. With respect to the AON, the results confirm that this network was preferentially engaged for the more familiar movement exercises. Compared to younger adults, older adults recruited visual regions to perform the task and, additionally, the hippocampus and caudate when the observed actions were familiar to them. Thus, instead of effectively exploiting the sensorimotor matching properties of the AON, older adults seemed to rely predominantly on the visual dynamics of the observed actions to perform the task. Our data further suggest that the caudate played an important role during the prediction of the less familiar figure skating elements in better-performing groups. Together, these findings show that action prediction engages a distributed network in the brain, which is modulated by the content of the observed actions and the age and experience of the observer.

Much research has been carried out to understand how human brains make sense of another agent in motion. Current views based on human adult and monkey studies assume a matching process in the motor system biased toward actions performed by conspecifics and present in the observer's motor repertoire. However, little is known about the neural correlates of action cognition in early ontogeny. In this study, we examined the processes involved in the observation of full body movements in 4-month-old infants using functional near-infrared spectroscopy to measure localized brain activation. In a 2 × 2 design, infants watched human or robotic figures moving in a smooth, familiar human-like manner, or in a rigid, unfamiliar robot-like manner. We found that infant premotor cortex responded more strongly to observe robot-like motion compared with human-like motion. Contrary to current views, this suggests that the infant motor system is flexibly engaged by novel movement patterns. Moreover, temporal cortex responses indicate that infants integrate information about form and motion during action observation. The response patterns obtained in premotor and temporal cortices during action observation in these young infants are very similar to those reported for adults. These findings thus suggest that the brain processes involved in the analysis of an agent in motion in adults become functionally specialized very early in human development.

During social interactions, how do we predict what other people are going to do next? One view is that we use our own motor experience to simulate and predict other people's actions. For example, when we see Sally look at a coffee cup or grasp a hammer, our own motor system provides a signal that anticipates her next action. Previous research has typically examined such gaze and grasp-based simulation processes separately, and it is not known whether similar cognitive and brain systems underpin the perception of object-directed gaze and grasp. Here we use functional magnetic resonance imaging to examine to what extent gaze- and grasp-perception rely on common or distinct brain networks. Using a 'peeping window' protocol, we controlled what an observed actor could see and grasp. The actor could peep through one window to see if an object was present and reach through a different window to grasp the object. However, the actor could not peep and grasp at the same time. We compared gaze and grasp conditions where an object was present with matched conditions where the object was absent. When participants observed another person gaze at an object, left anterior inferior parietal lobule (aIPL) and parietal operculum showed a greater response than when the object was absent. In contrast, when participants observed the actor grasp an object, premotor, posterior parietal, fusiform and middle occipital brain regions showed a greater response than when the object was absent. These results point towards a division in the neural substrates for different types of motor simulation. We suggest that left aIPL and parietal operculum are involved in a predictive process that signals a future hand interaction with an object based on another person's eye gaze, whereas a broader set of brain areas, including parts of the action observation network, are engaged during observation of an ongoing object-directed hand action.

Social interaction and comprehension of non-verbal behaviour requires a representation of people's bodies. Research into the neural underpinnings of body representation implicates several brain regions including extrastriate and fusiform body areas (EBA and FBA), superior temporal sulcus (STS), inferior frontal gyrus (IFG) and inferior parietal lobule (IPL). The different roles played by these regions in parsing familiar and unfamiliar body postures remain unclear. We examined the responses of this body observation network to static images of ordinary and contorted postures by using a repetition suppression design in functional neuroimaging. Participants were scanned whilst observing static images of a contortionist or a group of objects in either ordinary or unusual configurations, presented from different viewpoints. Greater activity emerged in EBA and FBA when participants viewed contorted compared to ordinary body postures. Repeated presentation of the same posture from different viewpoints lead to suppressed responses in the fusiform gyrus as well as three regions that are characteristically activated by observing moving bodies, namely STS, IFG and IPL. These four regions did not distinguish the image viewpoint or the plausibility of the posture. Together, these data define a broad cortical network for processing static body postures, including regions classically associated with action observation.

Observation of human actions recruits a well-defined network of brain regions, yet the purpose of this action observation network (AON) remains under debate. Some authors contend that this network has developed to respond specifically to observation of human actions. Conversely, others suggest that this network responds in a similar manner to actions prompted by human and non-human cues, and that one's familiarity with the action is the critical factor that drives this network. Previous studies investigating human and non-human action cues often confound novelty and stimulus form. Here, we used a dance-learning paradigm to assess AON activity during observation of trained and untrained dance cues where a human model was present or absent. Results show that individual components of the AON respond differently to the human form and to dance training. The bilateral superior temporal cortex responds preferentially to videos with a human present, regardless of training experience. Conversely, the right ventral premotor cortex responds more strongly when observing sequences that had been trained, regardless of the presence of a human. Our findings suggest that the AON comprises separate and dissociable components for motor planning and observing other people's actions.

Research on action simulation identifies brain areas that are active while imagining or performing simple overlearned actions. Are areas engaged during imagined movement sensitive to the amount of actual physical practice? In the present study, participants were expert dancers who learned and rehearsed novel, complex whole-body dance sequences 5 h a week across 5 weeks. Brain activity was recorded weekly by fMRI as dancers observed and imagined performing different movement sequences. Half these sequences were rehearsed and half were unpracticed control movements. After each trial, participants rated how well they could perform the movement. We hypothesized that activity in premotor areas would increase as participants observed and simulated movements that they had learnt outside the scanner. Dancers' ratings of their ability to perform rehearsed sequences, but not the control sequences, increased with training. When dancers observed and simulated another dancer's movements, brain regions classically associated with both action simulation and action observation were active, including inferior parietal lobule, cingulate and supplementary motor areas, ventral premotor cortex, superior temporal sulcus and primary motor cortex. Critically, inferior parietal lobule and ventral premotor activity was modulated as a function of dancers' ratings of their own ability to perform the observed movements and their motor experience. These data demonstrate that a complex motor resonance can be built de novo over 5 weeks of rehearsal. Furthermore, activity in premotor and parietal areas during action simulation is enhanced by the ability to execute a learned action irrespective of stimulus familiarity or semantic label.

What does it mean to "know" what an object is? Viewing objects from different categories (e.g., tools vs. animals) engages distinct brain regions, but it is unclear whether these differences reflect object categories themselves or the tendency to interact differently with objects from different categories (grasping tools, not animals). Here we test how the brain constructs representations of objects that one learns to name or physically manipulate. Participants learned to name or tie different knots and brain activity was measured whilst performing a perceptual discrimination task with these knots before and after training. Activation in anterior intraparietal sulcus, a region involved in object manipulation, was specifically engaged when participants viewed knots they learned to tie. This suggests that object knowledge is linked to sensorimotor experience and its associated neural systems for object manipulation. Findings are consistent with a theory of embodiment in which there can be clear overlap in brain systems that support conceptual knowledge and control of object manipulation. (Contains 2 tables and 6 figures.)

Watching other people move elicits engagement of a collection of sensorimotor brain regions collectively termed the Action Observation Network (AON). An extensive literature documents more robust AON responses when observing or executing familiar compared to unfamiliar actions, as well as a positive correlation between amplitude of AON response and an observer's familiarity with an observed or executed movement. On the other hand, emerging evidence shows patterns of AON activity counter to these findings, whereby in some circumstances, unfamiliar actions lead to greater AON engagement than familiar actions. In an attempt to reconcile these conflicting findings, some have proposed that the relationship between AON response amplitude and action familiarity is nonlinear in nature. In the present study, we used an elaborate guitar training intervention to probe the relationship between movement familiarity and AON engagement during action execution and action observation tasks. Participants underwent fMRI scanning while executing one set of guitar sequences with a scanner-compatible bass guitar and observing a second set of sequences. Participants then acquired further physical practice or observational experience with half of these stimuli outside the scanner across 3 days. Participants then returned for an identical scanning session, wherein they executed and observed equal numbers of familiar (trained) and unfamiliar (untrained) guitar sequences. Via region of interest analyses, we extracted activity within AON regions engaged during both scanning sessions, and then fit linear, quadratic and cubic regression models to these data. The data best support the cubic regression models, suggesting that the response profile within key sensorimotor brain regions associated with the AON respond to action familiarity in a nonlinear manner. Moreover, by probing the subjective nature of the prediction error signal, we show results consistent with a predictive coding account of AON engagement during action observation and execution that also takes into account effects of changes in neural efficiency. [ABSTRACT FROM AUTHOR]