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Persons with and without autism process sensory information differently. Differences in sensory processing are directly relevant to social functioning and communicative abilities, which are known to be hampered in persons with autism. We collected functional magnetic resonance imaging data from 25 autistic individuals and 25 neurotypical individuals while they performed a silent gesture recognition task. We exploited brain network topology, a holistic quantification of how networks within the brain are organized to provide new insights into how visual communicative signals are processed in autistic and neurotypical individuals. Performing graph theoretical analysis, we calculated two network properties of the action observation network: 'local efficiency', as a measure of network segregation, and 'global efficiency', as a measure of network integration. We found that persons with autism and neurotypical persons differ in how the action observation network is organized. Persons with autism utilize a more clustered, local-processing-oriented network configuration (i.e. higher local efficiency) rather than the more integrative network organization seen in neurotypicals (i.e. higher global efficiency). These results shed new light on the complex interplay between social and sensory processing in autism. [ABSTRACT FROM AUTHOR]

In human communication, social intentions and meaning are often revealed in the way we move. In this study, we investigate the flexibility of human communication in terms of kinematic modulation in a clinical population, namely, autistic individuals. The aim of this study was twofold: to assess (a) whether communicatively relevant kinematic features of gestures differ between autistic and neurotypical individuals, and (b) if autistic individuals use communicative kinematic modulation to support gesture recognition. We tested autistic and neurotypical individuals on a silent gesture production task and a gesture comprehension task. We measured movement during the gesture production task using a Kinect motion tracking device in order to determine if autistic individuals differed from neurotypical individuals in their gesture kinematics. For the gesture comprehension task, we assessed whether autistic individuals used communicatively relevant kinematic cues to support recognition. This was done by using stick‐light figures as stimuli and testing for a correlation between the kinematics of these videos and recognition performance. We found that (a) silent gestures produced by autistic and neurotypical individuals differ in communicatively relevant kinematic features, such as the number of meaningful holds between movements, and (b) while autistic individuals are overall unimpaired at recognizing gestures, they processed repetition and complexity, measured as the amount of submovements perceived, differently than neurotypicals do. These findings highlight how subtle aspects of neurotypical behavior can be experienced differently by autistic individuals. They further demonstrate the relationship between movement kinematics and social interaction in high‐functioning autistic individuals. Lay Summary: Hand gestures are an important part of how we communicate, and the way that we move when gesturing can influence how easy a gesture is to understand. We studied how autistic and typical individuals produce and recognize hand gestures, and how this relates to movement characteristics. We found that autistic individuals moved differently when gesturing compared to typical individuals. In addition, while autistic individuals were not worse at recognizing gestures, they differed from typical individuals in how they interpreted certain movement characteristics. [ABSTRACT FROM AUTHOR]

Humans are unique in their ability to communicate information through representational gestures which visually simulate an action (eg. moving hands as if opening a jar). Previous research indicates that the intention to communicate modulates the kinematics (e.g., velocity, size) of such gestures. If and how this modulation influences addressees' comprehension of gestures have not been investigated. Here we ask whether communicative kinematic modulation enhances semantic comprehension (i.e., identification) of gestures. We additionally investigate whether any comprehension advantage is due to enhanced early identification or late identification. Participants (n = 20) watched videos of representational gestures produced in a more- (n = 60) or less-communicative (n = 60) context and performed a forced-choice recognition task. We tested the isolated role of kinematics by removing visibility of actor's faces in Experiment I, and by reducing the stimuli to stick-light figures in Experiment II. Three video lengths were used to disentangle early identification from late identification. Accuracy and response time quantified main effects. Kinematic modulation was tested for correlations with task performance. We found higher gesture identification performance in more- compared to less-communicative gestures. However, early identification was only enhanced within a full visual context, while late identification occurred even when viewing isolated kinematics. Additionally, temporally segmented acts with more post-stroke holds were associated with higher accuracy. Our results demonstrate that communicative signaling, interacting with other visual cues, generally supports gesture identification, while kinematic modulation specifically enhances late identification in the absence of other cues. Results provide insights into mutual understanding processes as well as creating artificial communicative agents. [ABSTRACT FROM AUTHOR]

Action, gesture, and sign represent unique aspects of human communication that use form and movement to convey meaning. Researchers typically use manual coding of video data to characterize naturalistic, meaningful movements at various levels of description, but the availability of markerless motion-tracking technology allows for quantification of the kinematic features of gestures or any meaningful human movement. We present a novel protocol for extracting a set of kinematic features from movements recorded with Microsoft Kinect. Our protocol captures spatial and temporal features, such as height, velocity, submovements/strokes, and holds. This approach is based on studies of communicative actions and gestures and attempts to capture features that are consistently implicated as important kinematic aspects of communication. We provide open-source code for the protocol, a description of how the features are calculated, a validation of these features as quantified by our protocol versus manual coders, and a discussion of how the protocol can be applied. The protocol effectively quantifies kinematic features that are important in the production (e.g., characterizing different contexts) as well as the comprehension (e.g., used by addressees to understand intent and semantics) of manual acts. The protocol can also be integrated with qualitative analysis, allowing fast and objective demarcation of movement units, providing accurate coding even of complex movements. This can be useful to clinicians, as well as to researchers studying multimodal communication or human–robot interactions. By making this protocol available, we hope to provide a tool that can be applied to understanding meaningful movement characteristics in human communication. [ABSTRACT FROM AUTHOR]

Actions may be used to directly act on the world around us, or as a means of communication. Effective communication requires the addressee to recognize the act as being communicative. Humans are sensitive to ostensive communicative cues, such as direct eye gaze (Csibra & Gergely, 2009). However, there may be additional cues present in the action or gesture itself. Here we investigate features that characterize the initiation of a communicative interaction in both production and comprehension. We asked 40 participants to perform 31 pairs of object-directed actions and representational gestures in more- or less- communicative contexts. Data were collected using motion capture technology for kinematics and video recording for eye-gaze. With these data, we focused on two issues. First, if and how actions and gestures are systematically modulated when performed in a communicative context. Second, if observers exploit such kinematic information to classify an act as communicative. Our study showed that during production the communicative context modulates space-time dimensions of kinematics and elicits an increase in addressee-directed eye-gaze. Naïve participants detected communicative intent in actions and gestures preferentially using eye-gaze information, only utilizing kinematic information when eye-gaze was unavailable. Our study highlights the general communicative modulation of action and gesture kinematics during production but also shows that addressees only exploit this modulation to recognize communicative intention in the absence of eye-gaze. We discuss these findings in terms of distinctive but potentially overlapping functions of addressee directed eye-gaze and kinematic modulations within the wider context of human communication and learning. [ABSTRACT FROM AUTHOR]

During natural conversation, people must quickly understand the meaning of what the other speaker is saying. This concerns not just the semantic content of an utterance, but also the social action (i.e., what the utterance is doing—requesting information, offering, evaluating, checking mutual understanding, etc.) that the utterance is performing. The multimodal nature of human language raises the question of whether visual signals may contribute to the rapid processing of such social actions. However, while previous research has shown that how we move reveals the intentions underlying instrumental actions, we do not know whether the intentions underlying fine-grained social actions in conversation are also revealed in our bodily movements. Using a corpus of dyadic conversations combined with manual annotation and motion tracking, we analyzed the kinematics of the torso, head, and hands during the asking of questions. Manual annotation categorized these questions into six more fine-grained social action types (i.e., request for information, other-initiated repair, understanding check, stance or sentiment, self-directed, active participation). We demonstrate, for the first time, that the kinematics of the torso, head and hands differ between some of these different social action categories based on a 900 ms time window that captures movements starting slightly prior to or within 600 ms after utterance onset. These results provide novel insights into the extent to which our intentions shape the way that we move, and provide new avenues for understanding how this phenomenon may facilitate the fast communication of meaning in conversational interaction, social action, and conversation. [ABSTRACT FROM AUTHOR]