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Expectations about how others' actions unfold in the future are crucial for our everyday social interactions. The current study examined the development of the use of kinematic cues for action anticipation and prediction in 3-year-olds, 4-year-olds, 10-year-olds, and adults in two experiments. Participants observed a hand repeatedly reaching for either a close or far object. The motor kinematics of the hand varied depending on whether the hand reached for the close or far object. We assessed whether participants would use kinematic cues to visually anticipate (Experiment 1; N=98) and verbally predict (Experiment 2; N=80) which object the hand was going to grasp. We found that only adults, but not 3- to 10-year-olds, based their visual anticipations on kinematic cues (Experiment 1). This speaks against claims that action anticipations are based on simulating others' motor processes and instead provides evidence that anticipations are based on perceptual mechanisms. Interestingly, 10-year-olds used kinematic cues to correctly verbally predict the target object, and 4-year-olds learned to do so over the trials (Experiment 2). Thus, kinematic cues are used earlier in life for explicit action predictions than for visual action anticipations. This adds to a recent debate on whether or not an implicit understanding of others' actions precedes their ability to verbally reason about the same actions.

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Accumulating evidence suggests that individuals with autism spectrum disorder (ASD) show impairments in using contextual priors to predict others' actions and make intention inference. Yet less is known about whether and how children with ASD acquire contextual priors during action observation and how contextual priors relate to their action prediction and intention inference. To form proper contextual priors, individuals need to observe the social scenes in a reliable manner and focus on socially relevant information. By employing a data-driven scan path method and areas of interest (AOI)-based analysis, the current study investigated how contextual priors would relate to action prediction and intention understanding in 4-to-9-year-old children with ASD (N = 56) and typically developing (TD) children (N = 50) during free viewing of dynamic social scenes with different intentions. Results showed that children with ASD exhibited higher intra-subject variability when scanning social scenes and reduced attention to socially relevant areas. Moreover, children with high-level action prediction and intention understanding showed lower intra-subject variability and increased attention to socially relevant areas. These findings suggest that altered fixation patterns might restrain children with ASD from acquiring proper contextual priors, which has cascading downstream effects on their action prediction and intention understanding.

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Even though actions we observe in everyday life seem to unfold in a continuous manner, they are automatically divided into meaningful chunks, that are single actions or segments, which provide information for the formation and updating of internal predictive models. Specifically, boundaries between actions constitute a hub for predictive processing since the prediction of the current action comes to an end and calls for updating of predictions for the next action. In the current study, we investigated neural processes which characterize such boundaries using a repertoire of complex action sequences with a predefined probabilistic structure. Action sequences consisted of actions that started with the hand touching an object (T) and ended with the hand releasing the object (U). These action boundaries were determined using an automatic computer vision algorithm. Participants trained all action sequences by imitating demo videos. Subsequently, they returned for an fMRI session during which the original action sequences were presented in addition to slightly modified versions thereof. Participants completed a post-fMRI memory test to assess the retention of original action sequences. The exchange of individual actions, and thus a violation of action prediction, resulted in increased activation of the action observation network and the anterior insula. At U events, marking the end of an action, increased brain activation in supplementary motor area, striatum, and lingual gyrus was indicative of the retrieval of the previously encoded action repertoire. As expected, brain activation at U events also reflected the predefined probabilistic branching structure of the action repertoire. At T events, marking the beginning of the next action, midline and hippocampal regions were recruited, reflecting the selected prediction of the unfolding action segment. In conclusion, our findings contribute to a better understanding of the various cerebral processes characterizing prediction during the observation of complex action repertoires.

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The cerebellum causally supports social processing by generating internal models of social events based on statistical learning of behavioral regularities. However, whether the cerebellum is only involved in forming or also in using internal models for the prediction of forthcoming actions is still unclear. We used cerebellar transcranial Direct Current Stimulation (ctDCS) to modulate the performance of healthy adults in using previously learned expectations in an action prediction task. In a first learning phase of this task, participants were exposed to different levels of associations between specific actions and contextual elements, to induce the formation of either strongly or moderately informative expectations. In a following testing phase, which assessed the use of these expectations for predicting ambiguous (i.e. temporally occluded) actions, we delivered ctDCS. Results showed that anodic, compared to sham, ctDCS boosted the prediction of actions embedded in moderately, but not strongly, informative contexts. Since ctDCS was delivered during the testing phase, that is after expectations were established, our findings suggest that the cerebellum is causally involved in using internal models (and not just in generating them). This encourages the exploration of the clinical effects of ctDCS to compensate poor use of predictive internal models for social perception.

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BACKGROUND: Converging evidence points to impairments of the predictive function exerted by the cerebellum as one of the causes of the social cognition deficits observed in patients with cerebellar disorders. OBJECTIVE: We tested the neurorestorative effects of cerebellar transcranial direct current stimulation (ctDCS) on the use of contextual expectations to interpret actions occurring in ambiguous sensory sceneries in a sample of adolescents and young adults with congenital, non-progressive cerebellar malformation (CM). METHODS: We administered an action prediction task in which, in an implicit-learning phase, the probability of co-occurrence between actions and contextual elements was manipulated to form either strongly or moderately informative expectations. Subsequently, in a testing phase, we probed the use of these contextual expectations for predicting ambiguous (i.e., temporally occluded) actions. In a sham-controlled, within-subject design, participants received anodic or sham ctDCS during the task. RESULTS: Anodic ctDCS, compared to sham, improved patients' ability to use contextual expectations to predict the unfolding of actions embedded in moderately, but not strongly, informative contexts. CONCLUSIONS: These findings corroborate the role of the cerebellum in using previously learned contextual associations to predict social events and document the efficacy of ctDCS to boost social prediction in patients with congenital cerebellar malformation. The study encourages the further exploration of ctDCS as a neurorestorative tool for the neurorehabilitation of social cognition abilities in neurological, neuropsychiatric, and neurodevelopmental disorders featured by macro- or micro-structural alterations of the cerebellum.

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Social perception and communication differ between those with and without autism, even when verbal fluency and intellectual ability are equated. Previous work found that observers responded more quickly to an actor's points if the actor had chosen by themselves where to point instead of being directed where to point. Notably, this 'choice-advantage' effect decreased across non-autistic participants as the number of autistic-like traits and tendencies increased (Pesquita et al., 2016). Here, we build on that work using the same task to study individuals over a broader range of the spectrum, from autistic to non-autistic, measuring both response initiation and mouse movement times, and considering the response to each actor separately. Autistic and non-autistic observers viewed videos of three different actors pointing to one of two locations, without knowing that the actors were sometimes freely choosing to point to one target and other times being directed where to point. All observers exhibited a choice-advantage overall, meaning they responded more rapidly when actors were freely choosing versus when they were directed, indicating a sensitivity to the actors' postural cues and movements. Our fine-grained analyses found a more robust choice-advantage to some actors than others, with autistic observers showing a choice-advantage only in response to one of the actors, suggesting that both actor and observer characteristics influence the overall effect. We briefly explore existing actor characteristics that may have contributed to this effect, finding that both duration of exposure to pre-movement cues and kinematic cues of the actors likely influence the choice advantage to different degrees across the groups. Altogether, the evidence suggested that both autistic and non-autistic individuals could detect the choice-advantage signal, but that for autistic observers the choice-advantage was actor specific. Notably, we found that the influence of the signal, when present, was detected early for all actors by the non-autistic observers, but detected later and only for one actor by the autistic observers. Altogether, we have more accurately characterized the ability of social-perception in autistic individuals as intact, but highlighted that detection of signal is likely delayed/distributed compared to non-autistic observers and that it is important to investigate actor characteristics that may influence detection and use of their social-perception signals.

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Humans' capacity to predict actions and to socially categorize individuals is at the basis of social cognition. Such capacities emerge in early infancy. By 6 months of age, infants predict others' reaching actions considering others' epistemic state. At a similar age, infants are biased to attend to and interact with more familiar individuals, considering adult-like social categories such as the language people speak. We report that these two core processes are interrelated early on in infancy. In a belief-based action prediction task, 6-month-old infants (males and females) presented with a native speaker generated online predictions about the agent's actions, as revealed by the activation of participants' sensorimotor areas before the agent's movement. However, infants who were presented with a foreign speaker did not recruit their motor system before the agent's action. The eyetracker analysis provided further evidence that linguistic group familiarity influences how infants predict others' actions, as only infants presented with a native speaker modified their attention to the stimuli as a function of the agent's forthcoming behavior. The current findings suggest that infants' emerging capacity to predict others' actions is modulated by social cues, such as others' linguistic group. A facilitation to predict and encode the actions of native speakers relative to foreign speakers may explain, in part, why infants preferentially attend to, imitate, and learn from the actions of native speakers.

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Previous studies have shown that contextual information may aid in guessing the intention underlying others' actions in conditions of perceptual ambiguity. Here, we aimed to evaluate the temporal deployment of contextual influence on action prediction with increasing availability of kinematic information during the observation of ongoing actions. We used action videos depicting an actor grasping an object placed on a container to perform individual or interpersonal actions featuring different kinematic profiles. Crucially, the container could be of different colors. First, in a familiarization phase, the probability of co-occurrence between each action kinematics and color cues was implicitly manipulated to 80% and 20%, thus generating contextual priors. Then, in a testing phase, participants were asked to predict action outcome when the same action videos were occluded at five different timeframes of the entire movement, ranging from when the actor was still to when the grasp of the object was fully accomplished. In this phase, all possible action-contextual cues' associations were equally presented. The results showed that for all occlusion intervals, action prediction was more facilitated when action kinematics deployed in high- than low-probability contextual scenarios. Importantly, contextual priors shaped action prediction even in the latest occlusion intervals, where the kinematic cues clearly unveiled an action outcome that was previously associated with low-probability scenarios. These residual contextual effects were stronger in individuals with higher subclinical autistic traits. Our findings highlight the relative contribution of kinematic and contextual information to action understanding and provide evidence in favor of their continuous integration during action observation.

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BACKGROUND: Understanding and predicting others' behavior in a dynamic and rapidly changing world is a fundamental aspect of social interactions. However, it remains unclear as to whether children with autism spectrum disorder (ASD) could understand and predict goal-directed social actions. AIMS: To investigate the understanding of give-and-take interactions in children with ASD with the use of eye tracking. METHODS AND PROCEDURES: Experiment 1 and 2 investigated the understanding of giving and taking respectively in 5-to 8-year-old Chinese children with ASD and typically developing children by using the eye-tracking technology. OUTCOMES AND RESULTS: We found that children with ASD could predict actions, but they were less proficient in processing give-and-take interactions. Moreover, children with ASD showed impaired understanding of giving but not taking. CONCLUSIONS: These results indicate that the basic mechanisms of action prediction are intact in children with ASD whereas there may be deficits in the top-down social processing of the giving gesture.

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Developmental science has experienced a vivid debate on whether young children prioritize goals over means in their prediction of others' actions. Influential developmental theories highlight the role of goal objects for action understanding. Yet, recent infant studies report evidence for the opposite. The empirical evidence is therefore inconclusive. The current study advanced this debate by assessing preschool children's verbal predictions of others' actions. In five experiments (N = 302), we investigated whether preschool children and adults predict agents to move towards their previous goal (that is, show goal-related predictions) or predict agents to move along the same movement path that they pursued before. While Experiments 1a, 1b and 1c presented young children and adults with animated agents, Experiments 2a and 2b presented participants with human grasping action. An integrative analysis across experiments revealed that children were more likely to predict the agent to move along the same movement path, Z = -4.574, p ≤ 0.0001 (r = 0.304). That is, preschool children were more likely to predict that agents would move along the same trajectory even though this action would lead to a new goal object. Thus, our findings suggest that young children's action prediction relies on the detection of spatial and movement information. Overall, we discuss our findings in terms of theoretical frameworks that conceive of action understanding as an umbrella term that comprises different forms and facets in which humans understand others' actions. RESEARCH HIGHLIGHTS: We investigated whether preschool children predict agents to move towards their previous goal or to move along the same movement path that they pursued before. Unlike adults, preschool children predicted that agents would move along the same trajectory even though this action would lead to a new goal. Adults' goal-based predictions were affected from contextual details, whereas children systematically made path-based predictions. Young children's action prediction relies on the detection of spatial and movement information.

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Self-initiated movements are accompanied by an efference copy, a motor command sent from motor regions to the sensory cortices, containing a prediction of the movement's sensory outcome. Previous studies have proposed pre-motor event-related potentials (ERPs), including the readiness potential (RP) and its lateralized sub-component (LRP), as potential neural markers of action feedback prediction. However, it is not known how specific these neural markers are for voluntary (active) movements as compared to involuntary (passive) movements, which produce much of the same sensory feedback (tactile, proprioceptive) but are not accompanied by an efference copy. The goal of the current study was to investigate how active and passive movements are distinguishable from premotor electroencephalography (EEG), and to examine if this change of neural activity differs when participants engage in tasks that differ in their expectation of sensory outcomes. Participants made active (self-initiated) or passive (finger moved by device) finger movements that led to either visual or auditory stimuli (100 ms delay), or to no immediate contingency effects (control). We investigated the time window before the movement onset by measuring pre-movement ERPs time-locked to the button press. For RP, we observed an interaction between task and movement. This was driven by movement differences in the visual and auditory but not the control conditions. LRP conversely only showed a main effect of movement. We then used multivariate pattern analysis to decode movements (active vs. passive). The results revealed ramping decoding for all tasks from around -800 ms onwards up to an accuracy of approximately 85% at the movement. Importantly, similar to RP, we observed lower decoding accuracies for the control condition than the visual and auditory conditions, but only shortly (from -200 ms) before the button press. We also decoded visual vs. auditory conditions. Here, task is decodable for both active and passive conditions, but the active condition showed increased decoding shortly before the button press. Taken together, our results provide robust evidence that pre-movement EEG activity may represent action-feedback prediction in which information about the subsequent sensory outcome is encoded.

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The ability to predict others' actions is one of the main pillars of social cognition. We investigated the processes underlying this ability by pitting motor representations of the observed movements against visual familiarity. In two pre-registered eye-tracking experiments, we measured the gaze arrival times of 16 dogs (Canis familiaris) who observed videos of a human or a conspecific executing the same goal-directed actions. On the first trial, when the human agent performed human-typical movements outside dogs' specific motor repertoire, dogs' gaze arrived at the target object anticipatorily (i.e., before the human touched the target object). When the agent was a conspecific, dogs' gaze arrived to the target object reactively (i.e., upon or after touch). When the human agent performed unusual movements more closely related to the dogs' motor possibilities (e.g., crawling instead of walking), dogs' gaze arrival times were intermediate between the other two conditions. In a replication experiment, with slightly different stimuli, dogs' looks to the target object were neither significantly predictive nor reactive, irrespective of the agent. However, when including looks at the target object that were not preceded by looks to the agents, on average dogs looked anticipatorily and sooner at the human agent's action target than at the conspecific's. Looking times and pupil size analyses suggest that the dogs' attention was captured more by the dog agent. These results suggest that visual familiarity with the observed action and saliency of the agent had a stronger influence on the dogs' looking behaviour than effector-specific movement representations in anticipating action targets.

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Previous studies have identified that the posterior cerebellum, which plays a role in processing temporal sequences in social events, is consistently and robustly activated when we predict future action sequences based on personality traits (Haihambo Haihambo et al. Social Cognitive and Affective Neuroscience 17(2), 241-251, 2022) and intentions (Haihambo et al. Cognitive, Affective, and Behavioral Neuroscience 23(2), 323-339, 2023). In the current study, we investigated whether these cerebellar areas are selectively activated when we predict the sequences of (inter)actions based on protagonists' preferences. For the first time, we also compared predictions based on person-to-person interactions or single person activities. Participants were instructed to predict actions of one single or two interactive protagonists by selecting them and putting them in the correct chronological order after being informed about one of the protagonists' preferences. These conditions were contrasted against nonsocial (involving objects) and nonsequencing (prediction without generating a sequence) control conditions. Results showed that the posterior cerebellar Crus 1, Crus 2, and lobule IX, alongside the temporoparietal junction and dorsal medial prefrontal cortex were more robustly activated when predicting sequences of behavior of two interactive protagonists, compared to one single protagonist and nonsocial objects. Sequence predictions based on one single protagonist recruited lobule IX activation in the cerebellum and more ventral areas of the medial prefrontal cortex compared to a nonsocial object. These cerebellar activations were not found when making predictions without sequences. Together, these findings suggest that cerebellar mentalizing areas are involved in social mentalizing processes which require temporal sequencing, especially when they involve social interactions, rather than behaviors of single persons.

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Fast prediction of the mode of action (MoA) for bioactive compounds would immensely foster bioactivity annotation in compound collections and may early on reveal off-targets in chemical biology research and drug discovery. Morphological profiling, e.g., using the Cell Painting assay, offers a fast, unbiased assessment of compound activity on various targets in one experiment. However, due to incomplete bioactivity annotation and unknown activities of reference compounds, prediction of bioactivity is not straightforward. Here we introduce the concept of subprofile analysis to map the MoA for both, reference and unexplored compounds. We defined MoA clusters and extracted cluster subprofiles that contain only a subset of morphological features. Subprofile analysis allows for the assignment of compounds to, currently, twelve targets or MoA. This approach enables rapid bioactivity annotation of compounds and will be extended to further clusters in the future.

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This study examined the ability of children with autism spectrum disorder (ASD) to generate joint intention-based action prediction in a joint action task. Children were presented with a series of videos in which two actors either played with blocks based on joint intention (social condition) or played with blocks independently (nonsocial condition). In the familiarization stage, two actors demonstrated how they played with blocks three times. In the test stage, one actor left the scene, and another actor grasped a block and asked where she should place it. Children's gaze behavior was assessed by an eye tracker. After watching videos, children were asked to answer two questions: an action prediction question and an intention understanding question. The results showed that in the implicit eye movement task, children with ASD and typically developing (TD) children exhibited location-based anticipatory gaze under both conditions. However, in terms of explicit behavioral responses, TD children showed higher accuracy in response to action prediction questions and intention understanding questions than children with ASD in the social condition, while no significant group difference was found in the nonsocial condition. These results indicate that children with ASD have difficulty understanding joint intention and that their action prediction is primarily driven by bottom-up sensory inputs.

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In sports, understanding others' actions represents a fundamental skill that allows players to predict the outcome of teammates' and opponents' actions and counteract them properly. While it is well known that motor expertise sets better premises for predicting the result of an observed sports action, it remains untested whether this principle applies to a team where players cover different positions that imply different motor repertoires. To test this hypothesis, we selected rugby as a paradigmatic example in which only one or two players out of 22 train and perform placed kicks. We administered a placed kick outcome prediction task to three groups of participants, namely, rugby kickers, rugby non-kickers, and controls, thus spanning over different combinations of motor expertise and visual experience. Kickers outperformed both their non-kicking teammates and controls in overall prediction accuracy. We documented how the viewpoint of observation, the expertise of the observed kicker, and the position of the kick on the court influenced the prediction performance across the three groups. Finally, we revealed that within rugby players, the degree of motor expertise (but not the visual experience) causally affects accuracy, and such a result stands even after accounting for the level of visual experience. These findings extend the role of motor expertise in decoding and predicting others' behaviors to sports teammates, among which every member is equipped with a position-specific motor repertoire, advocating for new motor training procedures combining the gestures to-be-performed with those to-be-faced.

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Humans take a teleological stance when observing others' actions, interpreting them as intentional and goal directed. In predictive processing accounts of social perception, this teleological stance would be mediated by a perceptual prediction of an ideal energy-efficient reference trajectory with which a rational actor would achieve their goals within the current environmental constraints. Hudson and colleagues (2018 Proc. R. Soc. B 285, 20180638. (doi:10.1098/rspb.2018.0638)) tested this hypothesis in a series of experiments in which participants reported the perceived disappearance points of hands reaching for objects. They found that these judgements were biased towards the expected efficient reference trajectories. Observed straight reaches were reported higher when an obstacle needed to be overcome than if the path was clear. By contrast, unnecessarily high reaches over empty space were perceptually flattened. Moreover, these perceptual biases increased the more the environmental constraints and expected action trajectories were explicitly processed. These findings provide an important advance to our understanding of the mechanisms underlying social perception. The current replication tests the robustness of these findings and whether they uphold in an online setting.

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For the past fifteen years, observation of actions has proved to be effective in the motor rehabilitation of stroke. Despite this, no evidence has ever been provided that this practice is able to activate the efferent motor system of a limb unable to perform the observed action due to stroke. In fact, transcranial magnetic stimulation cannot easily be used in these patients, and the fMRI evidence is inconclusive. This creates a logical problem, as the effectiveness of action observation in functional recovery is attributed to its ability to evoke action simulation, up to sub-threshold muscle activation (i.e., motor resonance), in healthy individuals. To provide the necessary proof-of-concept, patients with severe upper limb function impairments and matched control participants were submitted to a verified action prediction paradigm. They were asked to watch videos showing gripping movements towards a graspable or an ungraspable object, and to press a button the instant the agent touched the object. The presence of more accurate responses for the graspable object trials is considered an indirect evidence of motor resonance. Participants were required to perform the task in two sessions which differed in the hand used to respond. Despite the serious difficulty of movement, 8 out of 18 patients were able to perform the task with their impaired hand. We found that the responses given by the paretic hand showed a modulation of the action prediction time no different from that showed by the non-paretic hand, which, in turn, did not differ from that showed by the matched control participants. The present proof-of-concept study shows that action observation involves the efferent motor system even when the hand used to respond is unable to perform the observed action due to a cortical lesion, providing the missing evidence to support the already established use of Action Observation Training (AOT) in motor rehabilitation of stroke.

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Predicting actions is a fundamental ability that helps us to comprehend what is happening in our environment and to interact with others. The motor system was previously identified as source of action predictions. Yet, which aspect of the statistical likelihood of upcoming actions the motor system is sensitive to remains an open question. This EEG study investigated how regularities in observed actions are reflected in the motor system and utilized to predict upcoming actions. Prior to measuring EEG, participants watched videos of action sequences with different transitional probabilities. After training, participants' brain activity over motor areas was measured using EEG while watching videos of action sequences with the same statistical structure. Focusing on the mu and beta frequency bands we tested whether activity of the motor system reflects the statistical likelihood of upcoming actions. We also explored two distinct aspects of the statistical structure that capture different prediction processes, expectancy and predictability. Expectancy describes participants' expectation of the most likely action, whereas predictability represents all possible actions and their relative probabilities. Results revealed that mu and beta oscillations play different roles during action prediction. While the mu rhythm reflected anticipatory activity without any link to the statistical structure, the beta rhythm was related to the expectancy of an action. Our findings support theories proposing that the motor system underlies action prediction, and they extend such theories by showing that multiple forms of statistical information are extracted when observing action sequences. This information is integrated in the prediction generated by the neural motor system of which action is going to happen next.

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Response process data collected from human-computer interactive items contain detailed information about respondents' behavioural patterns and cognitive processes. Such data are valuable sources for analysing respondents' problem-solving strategies. However, the irregular data format and the complex structure make standard statistical tools difficult to apply. This article develops a computationally efficient method for exploratory analysis of such process data. The new approach segments a lengthy individual process into a sequence of short subprocesses to achieve complexity reduction, easy clustering and meaningful interpretation. Each subprocess is considered a subtask. The segmentation is based on sequential action predictability using a parsimonious predictive model combined with the Shannon entropy. Simulation studies are conducted to assess the performance of the new method. We use a case study of PIAAC 2012 to demonstrate how exploratory analysis for process data can be carried out with the new approach.

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