Same Same, But Different: Brain Areas Underlying the Learning from Repetitive Episodic Prediction Errors.

Prediction errors (PEs) function as learning signals. It is yet unclear how varying compared to repetitive PEs affect episodic memory in brain and behavior. The current study investigated cerebral and behavioral effects of experiencing either multiple alternative versions ("varying") or one single alternative version ("repetitive") of a previously encoded episode. Participants encoded a set of episodes ("originals") by watching videos showing toy stories. During scanning, participants either experienced originals, one single or multiple alternative versions of the previously encoded episodes. Participants' memory performance was tested through recall of original objects. Varying and repetitive PEs revealed typical brain responses to the detection of mismatching information including inferior frontal and posterior parietal regions, as well as hippocampus, which is further linked to memory reactivation, and the amygdala, known for modulating memory consolidation. Furthermore, experiencing varying and repetitive PEs triggered distinct brain areas as revealed by direct contrast. Among others, experiencing varying versions triggered activity in the caudate, a region that has been associated with PEs. In contrast, repetitive PEs activated brain areas that resembled more those for retrieval of originally encoded episodes. Thus, ACC and posterior cingulate cortex activation seemed to serve both reactivating old and integrating new but similar information in episodic memory. Consistent with neural findings, participants recalled original objects less accurately when only presented with the same, but not varying, PE during fMRI. The current findings suggest that repeated PEs interact more strongly with a recalled original episodic memory than varying PEs.

Action Segmentation in the Brain: The Role of Object-Action Associations.

Motion information has been argued to be central to the subjective segmentation of observed actions. Concerning object-directed actions, object-associated action information might as well inform efficient action segmentation and prediction. The present study compared the segmentation and neural processing of object manipulations and equivalent dough ball manipulations to elucidate the effect of object-action associations. Behavioral data corroborated that objective relational changes in the form of (un-)touchings of objects, hand, and ground represent meaningful anchor points in subjective action segmentation rendering them objective marks of meaningful event boundaries. As expected, segmentation behavior became even more systematic for the weakly informative dough. fMRI data were modeled by critical subjective, and computer-vision-derived objective event boundaries. Whole-brain as well as planned ROI analyses showed that object information had significant effects on how the brain processes these boundaries. This was especially pronounced at untouchings, that is, events that announced the beginning of the upcoming action and might be the point where competing predictions are aligned with perceptual input to update the current action model. As expected, weak object-action associations at untouching events were accompanied by increased biological motion processing, whereas strong object-action associations came with an increased contextual associative information processing, as indicated by increased parahippocampal activity. Interestingly, anterior inferior parietal lobule activity increased for weak object-action associations at untouching events, presumably because of an unrestricted number of candidate actions for dough manipulation. Our findings offer new insights into the significance of objects for the segmentation of action.

Updating predictions in a complex repertoire of actions and its neural representation.

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.

Gray matter matters: Cognitive stability and flexibility in schizophrenia spectrum disorder.

Cognitive dysfunction constitutes a core characteristic of schizophrenia spectrum disorders (SZ). Specifically, deficits in updating generative models (i.e., cognitive flexibility) and shielding against distractions (i.e., cognitive stability) are considered critical contributors to cognitive impairment in these patients. Here, we examined the structural integrity of frontostriatal networks and their associations with reduced cognitive stability and flexibility in SZ patients. In a sample of 21 patients diagnosed with SZ and 22 healthy controls, we measured gray matter volume (GMV) using structural MRI. Further, cognitive stability and flexibility were assessed using a switch-drift paradigm, quantifying the successful ignoring of distracters and detection of rule switches. Compared to controls, patients showed significantly smaller GMV in the whole brain and three predefined regions of interest: the medial prefrontal cortex (mPFC), inferior frontal gyrus (IFG), and caudate nucleus (CN). Notably, GMV in these areas positively correlated with correct rule-switch detection but not with ignoring rule-compatible drifts. Further, the volumetric differences between SZ patients and controls were statistically explainable by considering the behavioral performance in the switch-drift task. Our results indicate that morphological abnormalities in frontostriatal networks are associated with deficient flexibility in SZ patients and highlight the necessity of minimizing neurodevelopmental and progressive brain atrophy in this population.

The significance of structural rich club hubs for the processing of hierarchical stimuli.

The brain's structural network follows a hierarchy that is described as rich club (RC) organization, with RC hubs forming the well-interconnected top of this hierarchy. In this study, we tested whether RC hubs are involved in the processing of hierarchically higher structures in stimulus sequences. Moreover, we explored the role of previously suggested cortical gradients along anterior-posterior and medial-lateral axes throughout the frontal cortex. To this end, we conducted a functional magnetic resonance imaging (fMRI) experiment and presented participants with blocks of digit sequences that were structured on different hierarchically nested levels. We additionally collected diffusion weighted imaging data of the same subjects to identify RC hubs. This classification then served as the basis for a region of interest analysis of the fMRI data. Moreover, we determined structural network centrality measures in areas that were found as activation clusters in the whole-brain fMRI analysis. Our findings support the previously found anterior and medial shift for processing hierarchically higher structures of stimuli. Additionally, we found that the processing of hierarchically higher structures of the stimulus structure engages RC hubs more than for lower levels. Areas involved in the functional processing of hierarchically higher structures were also more likely to be part of the structural RC and were furthermore more central to the structural network. In summary, our results highlight the potential role of the structural RC organization in shaping the cortical processing hierarchy.

Minor Changes Change Memories: Functional Magnetic Resonance Imaging and Behavioral Reflections of Episodic Prediction Errors.

Episodic memories can be modified, a process that is potentially driven by mnemonic prediction errors. In the present study, we used modified cues to induce prediction errors of different episodic relevance. Participants encoded episodes in the form of short toy stories and then returned for an fMRI session on the subsequent day. Here, participants were presented either original episodes or slightly modified versions thereof. Modifications consisted of replacing a single object within the episode and either challenged the gist of an episode (gist modifications) or left it intact (surface modifications). On the next day, participants completed a post-fMRI memory test that probed memories for originally encoded episodes. Both types of modifications triggered brain activation in regions we previously found to be involved in the processing of content-based mnemonic prediction errors (i.e., the exchange of an object). Specifically, these were ventrolateral pFC, intraparietal cortex, and lateral occipitotemporal cortex. In addition, gist modifications triggered pronounced brain responses, whereas those for surface modification were only significant in the right inferior frontal sulcus. Processing of gist modifications also involved the posterior temporal cortex and the precuneus. Interestingly, our findings confirmed the posterior hippocampal role of detail processing in episodic memory, as evidenced by increased posterior hippocampal activity for surface modifications compared with gist modifications. In the post-fMRI memory test, previous experience with surface modified, but not gist-modified episodes, increased erroneous acceptance of the same modified versions as originally encoded. Whereas surface-level prediction errors might increase uncertainty and facilitate confusion of alternative episode representations, gist-level prediction errors seem to trigger the clear distinction of independent episodes.

Fluctuations in alpha and beta power provide neural states favourable for contextually relevant anticipatory processes.

Cued sensory input occasionally fails to immediately ensue its respective trigger. Given that our environments are rich in sensory cues, we often end up processing other contextually relevant information in the meantime. The experimental design of the present study allowed us to investigate how such temporal delays and visual interferences may impact anticipatory processes. Thirty-four participants were trained to remember an individualised set of eight paired-up faces. These paired-up faces were presented pseudorandomly in sequences of unpaired face images. To keep participants engaged throughout the electroencephalography study, they were instructed to classify each face image, according to its sex, as fast as possible without compromising accuracy. We observed dissimilar modulations in alpha and beta power between the 6-s timeframe encompassing the onsets of predictive and expected images (temporal delay block) and the 6-s timeframe encompassing the predictive, interference and expected images (visual interference block). Furthermore, an expectation-facilitated reduction of the face-sensitive N170 component was only observed if an anticipated face image directly followed its corresponding predictive counterpart. This effect was no longer evident when the expected face was preceded by a distracting face image. Regardless of the block type, behavioural measures confirmed that anticipated faces were classified significantly faster and with fewer erroneous responses than faces not foretold by a predictive face. Collectively, these results demonstrate that whilst the brain continuously adjusts internal hierarchical generative models to account for temporal delays in stimulus onset and visual interferences, the higher levels, and subsequent predictions, fundamental for expectation-facilitated behaviours remain intact.

Tool mastering today - an interdisciplinary perspective.

Tools have coined human life, living conditions, and culture. Recognizing the cognitive architecture underlying tool use would allow us to comprehend its evolution, development, and physiological basis. However, the cognitive underpinnings of tool mastering remain little understood in spite of long-time research in neuroscientific, psychological, behavioral and technological fields. Moreover, the recent transition of tool use to the digital domain poses new challenges for explaining the underlying processes. In this interdisciplinary review, we propose three building blocks of tool mastering: (A) perceptual and motor abilities integrate to tool manipulation knowledge, (B) perceptual and cognitive abilities to functional tool knowledge, and (C) motor and cognitive abilities to means-end knowledge about tool use. This framework allows for integrating and structuring research findings and theoretical assumptions regarding the functional architecture of tool mastering via behavior in humans and non-human primates, brain networks, as well as computational and robotic models. An interdisciplinary perspective also helps to identify open questions and to inspire innovative research approaches. The framework can be applied to studies on the transition from classical to modern, non-mechanical tools and from analogue to digital user-tool interactions in virtual reality, which come with increased functional opacity and sensorimotor decoupling between tool user, tool, and target. By working towards an integrative theory on the cognitive architecture of the use of tools and technological assistants, this review aims at stimulating future interdisciplinary research avenues.

Where was the toaster? A systematic investigation of semantic construction in a new virtual episodic memory paradigm.

Retrieved memories of past events are often inaccurate. The scenario construction model (SCM) postulates that during encoding, only the gist of an episode is stored in the episodic memory trace and during retrieval, information missing from that trace is constructed from semantic information. The current study aimed to find behavioural evidence for semantic construction in a realistic, yet controlled setting by introducing a completely new paradigm and adjusted memory tests that measure semantic construction. Using a desktop virtual reality (VR), participants navigated through a flat in which some household objects appeared in unexpected rooms, creating conflicts between the experienced episode and semantic expectations. The manipulation of congruence enabled us to identify influences from semantic information in cases of episodic memory failure during recall. Besides, we controlled for objects to be task-relevant or task-irrelevant to the sequence of action. In addition to an established old/new recognition task we introduced spatial and temporal recall measures as possible superior memory measures quantifying semantic construction. The recognition task and the spatial recall revealed that both congruence and task-relevance predicted correct episodic memory retrieval. In cases of episodic memory failure, semantic construction was more likely than guessing and occurred more frequently for task-irrelevant objects. In the temporal recall object-pairs belonging to the same semantic room-category were temporally clustered together compared with object-pairs from different semantic categories (at the second retrieval delay). Taken together, our findings support the predictions of the SCM. The new VR paradigm, including the new memory measures appears to be a promising tool for investigating semantic construction.

Solidity Meets Surprise: Cerebral and Behavioral Effects of Learning from Episodic Prediction Errors.

How susceptible a memory is to later modification might depend on how stable the episode has been encoded. This stability was proposed to increase when retrieving information more (vs. less) often and in a spaced (vs. massed) practice. Using fMRI, we examined the effects of these different pre-fMRI retrieval protocols on the subsequent propensity to learn from episodic prediction errors. After encoding a set of different action stories, participants came back for two pre-fMRI retrieval sessions in which they encountered original episodes either 2 or 8 times in either a spaced or a massed retrieval protocol. One week later, we cued episodic retrieval during the fMRI session by using original or modified videos of encoded action stories. Recurrent experience of modified episodes was associated with increasing activity in the episodic memory network including hippocampal and cortical areas, when leading to false memories in a post-fMRI memory test. While this observation clearly demonstrated learning from episodic prediction errors, we found no evidence for a modulatory effect of the different retrieval protocols. As expected, the benefit of retrieving an episode more often was reflected in better memory for originally encoded episodes. In addition, frontal activity increased for episodic prediction errors when episodes had been less frequently retrieved pre-fMRI. A history of spaced versus massed retrieval was associated with increased activation throughout the episodic memory network, with no significant effect on behavioral performance. Our findings show that episodic prediction errors led to false memories. The history of different retrieval protocols was reflected in memory performance and brain responses to episodic prediction errors, but did not interact with the brain's episodic learning response.

Ignore the glitch but mind the switch: Positive effects of methylphenidate on cognition in attention deficit hyperactivity disorder are related to prediction gain.

Neuropsychological symptoms such as inattention and distractibility constitute a core characteristic of attention deficit hyperactivity disorder (ADHD). Here, we tested the hypothesis that attentional dysfunctions result from a deficit in neural gain modulation, which translates into difficulty in predictively weighting relevant sensory input while ignoring distraction. We compared thirty-seven hitherto untreated adults diagnosed with ADHD and thirty-eight healthy participants with a serial switch-drift task that requires internal models of predictable digit sequences to be either updated or stabilized. Switches between sequences that had to be indicated by key presses and digit omissions within a sequence (drifts) that should be ignored varied by stimulus-bound surprise quantified as Shannon information. To investigate whether catecholaminergic modulation by increasing extracellular norepinephrine and dopamine levels leads to an amelioration in prediction gain, participants were tested twice, with patients receiving a single dose of methylphenidate, a norepinephrine/dopamine reuptake inhibitor, in the second session. Patients and controls differed in both updating and stabilizing, depending on the respective event surprise. Specifically, patients showed difficulty in detecting expectable switches, while having greater difficulty to ignore surprising distractions. Thus, underconfident prior beliefs in ADHD may fail to appropriately weight expected relevant input, whereas the gain of neural responses to unexpected irrelevant distractors is increased. Methylphenidate improved both flexibility and stability of prediction and had a positive effect on selective responding over time. Our results suggest that ADHD is associated with an impairment in the use of prior expectations to optimally weight sensory inputs, which is improved by increasing catecholaminergic neurotransmission.

Interindividual differences in interoception modulate behavior and brain responses in emotional inference.

Emotional experiences are proposed to arise from contextualized perception of bodily responses, also referred to as interoceptive inferences. The recognition of emotions benefits from adequate access to one's own interoceptive information. However, direct empirical evidence of interoceptive inferences and their neural basis is still lacking. In the present fMRI study healthy volunteers performed a probabilistic emotion classification task with videotaped dynamically unfolding facial expressions. In a first step, we aimed to determine functional areas involved in the processing of dynamically unfolding emotional expressions. We then tested whether individuals with higher interoceptive accuracy (IAcc), as assessed by the Heartbeat detection task (HDT), or higher interoceptive sensitivity (IS), as assessed by the Multidimensional Assessment of Interoceptive Awareness, Version 2 (MAIA-2), benefit more from the contextually given likelihood of emotional valence and whether brain regions reflecting individual IAcc and/or IS play a role in this. Individuals with higher IS benefitted more from the biased probability of emotional valence. Brain responses to more predictable emotions elicited a bilateral activity pattern comprising the inferior frontal gyrus and the posterior insula. Importantly, individual IAcc scores positively covaried with brain responses to more surprising and less predictable emotional expressions in the insula and caudate nucleus. We show for the first time that IAcc score is associated with enhanced processing of interoceptive prediction errors, particularly in the anterior insula. A higher IS score seems more likely to be associated with a stronger weighting of attention to interoceptive changes processed by the posterior insula and ventral prefrontal cortex.

What Happened When? Cerebral Processing of Modified Structure and Content in Episodic Cueing.

Episodic memories are not static but can change on the basis of new experiences, potentially allowing us to make valid predictions in the face of an ever-changing environment. Recent research has identified prediction errors during memory retrieval as a possible trigger for such changes. In this study, we used modified episodic cues to investigate whether different types of mnemonic prediction errors modulate brain activity and subsequent memory performance. Participants encoded episodes that consisted of short toy stories. During a subsequent fMRI session, participants were presented videos showing the original episodes, or slightly modified versions thereof. In modified videos, either the order of two subsequent action steps was changed or an object was exchanged for another. Content modifications recruited parietal, temporo-occipital, and parahippocampal areas reflecting the processing of the new object information. In contrast, structure modifications elicited activation in right dorsal premotor, posterior temporal, and parietal areas, reflecting the processing of new sequence information. In a post-fMRI memory test, the participants' tendency to accept modified episodes as originally encoded increased significantly when they had been presented modified versions already during the fMRI session. After experiencing modifications, especially those of the episodes' structure, the recognition of originally encoded episodes was impaired as well. Our study sheds light onto the neural processing of different types of episodic prediction errors and their influence on subsequent memory recall.

Corrigendum: Seeing What I Did (Not): Cerebral and Behavioral Effects of Agency and Perspective on Episodic Memory Re-activation.

[This corrects the article DOI: 10.3389/fnbeh.2021.793115.].

Effects of DRD2/ANKK1 and COMT Val158Met polymorphisms on stabilization against and adaptation to unexpected events.

Genetic variations affecting dopaminergic neuromodulation such as the DRD2/ANKK1 and the COMT Val158Met polymorphisms contribute to goal-directed behavior that requires a balance between stabilization and updating of current states and behaviors. Dopamine is also thought to be relevant for encoding of surprise signals to sensory input and adaptive learning. A link between goal-directed behavior and learning from surprise is therefore plausible. In the present fMRI study, we investigated whether DRD2 and COMT polymorphisms are related to behavioral responses and neural signals in the caudate nucleus and dlPFC during updating or stabilizing internal models of predictable digit sequences. To-be-detected switches between sequences and to-be-ignored digit omissions within a sequence varied by information-theoretic quantities of surprise and entropy. We found that A1 noncarriers and Val-carriers showed a lower response threshold along with increased caudate and dlPFC activation to surprising switches compared with A1-carriers and Met-homozygotes, whose dlPFC activity increased with decreasing switch surprise. In contrast, there were overall smaller differences in behavioral and neural modulation by drift surprise. Our results suggest that the impact of dopamine-relevant polymorphisms in the flexibility-stability trade-off may result in part from the role of dopamine in encoding the weight afforded to events requiring updating or stabilization.

White matter fiber microstructure is associated with prior hospitalizations rather than acute symptomatology in major depressive disorder.

BACKGROUND: Eighty percent of all patients suffering from major depressive disorder (MDD) relapse at least once in their lifetime. Thus, understanding the neurobiological underpinnings of the course of MDD is of utmost importance. A detrimental course of illness in MDD was most consistently associated with superior longitudinal fasciculus (SLF) fiber integrity. As similar associations were, however, found between SLF fiber integrity and acute symptomatology, this study attempts to disentangle associations attributed to current depression from long-term course of illness. METHODS: A total of 531 patients suffering from acute (N = 250) or remitted (N = 281) MDD from the FOR2107-cohort were analyzed in this cross-sectional study using tract-based spatial statistics for diffusion tensor imaging. First, the effects of disease state (acute v. remitted), current symptom severity (BDI-score) and course of illness (number of hospitalizations) on fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity were analyzed separately. Second, disease state and BDI-scores were analyzed in conjunction with the number of hospitalizations to disentangle their effects. RESULTS: Disease state (pFWE < 0.042) and number of hospitalizations (pFWE< 0.032) were associated with decreased FA and increased MD and RD in the bilateral SLF. A trend was found for the BDI-score (pFWE > 0.067). When analyzed simultaneously only the effect of course of illness remained significant (pFWE < 0.040) mapping to the right SLF. CONCLUSIONS: Decreased FA and increased MD and RD values in the SLF are associated with more hospitalizations when controlling for current psychopathology. SLF fiber integrity could reflect cumulative illness burden at a neurobiological level and should be targeted in future longitudinal analyses.

Association of brain white matter microstructure with cognitive performance in major depressive disorder and healthy controls: a diffusion-tensor imaging study.

Cognitive deficits are central attendant symptoms of major depressive disorder (MDD) with a crucial impact in patients' everyday life. Thus, it is of particular clinical importance to understand their pathophysiology. The aim of this study was to investigate a possible relationship between brain structure and cognitive performance in MDD patients in a well-characterized sample. N = 1007 participants (NMDD = 482, healthy controls (HC): NHC = 525) were selected from the FOR2107 cohort for this diffusion-tensor imaging study employing tract-based spatial statistics. We conducted a principal component analysis (PCA) to reduce neuropsychological test results, and to discover underlying factors of cognitive performance in MDD patients. We tested the association between fractional anisotropy (FA) and diagnosis (MDD vs. HC) and cognitive performance factors. The PCA yielded a single general cognitive performance factor that differed significantly between MDD patients and HC (P < 0.001). We found a significant main effect of the general cognitive performance factor in FA (Ptfce-FWE = 0.002) in a large bilateral cluster consisting of widespread frontotemporal-association fibers. In MDD patients this effect was independent of medication intake, the presence of comorbid diagnoses, the number of previous hospitalizations, and depressive symptomatology. This study provides robust evidence that white matter disturbances and cognitive performance seem to be associated. This association was independent of diagnosis, though MDD patients show more pronounced deficits and lower FA values in the global white matter fiber structure. This suggests a more general, rather than the depression-specific neurological basis for cognitive deficits.

Cerebral and behavioral signs of impaired cognitive flexibility and stability in schizophrenia spectrum disorders.

BACKGROUND: Manifold cognitive deficits have been reported in schizophrenia spectrum disorders, including disturbances in flexible updating to altered circumstances as well as stabilization deficits in the face of distractors. In this functional magnetic resonance imaging study, we examined the neural correlates of these deficits as two complementary components of predictive processing. METHODS: In 22 patients with schizophrenia spectrum disorders and 22 healthy matched control participants, we applied a serial predictive switch-drift task to assess flexibility as successful detection of prediction-rule switches, and stability as successfully ignoring distractors ("drifts"). RESULTS: Patients compared with controls less reliably detected rule switches and also less efficiently inhibited drifts. A reduced striatal response to switches or drifts correlated with weaker switch-drift-discrimination in patients, suggesting impaired gating of prediction errors. The increase in activity in anterior cingulate cortex and hippocampus for detected vs. undetected switches was reduced in patients compared to controls, which may reflect impaired behavioral adaptation following prediction errors. The comparison between shielding against distractions and undetected switches showed increased activity in the inferior frontal cortex and posterior insula in controls but not in patients. CONCLUSION: Our results suggest new insights into the specific disruption of predictive flexibility and stability in schizophrenia spectrum disorders, which is characterized by impaired striatal gating and inadequate cortical encoding of predictive errors.

Interoceptive sensibility predicts the ability to infer others' emotional states.

Emotional sensations and inferring another's emotional states have been suggested to depend on predictive models of the causes of bodily sensations, so-called interoceptive inferences. In this framework, higher sensibility for interoceptive changes (IS) reflects higher precision of interoceptive signals. The present study examined the link between IS and emotion recognition, testing whether individuals with higher IS recognize others' emotions more easily and are more sensitive to learn from biased probabilities of emotional expressions. We recorded skin conductance responses (SCRs) from forty-six healthy volunteers performing a speeded-response task, which required them to indicate whether a neutral facial expression dynamically turned into a happy or fearful expression. Moreover, varying probabilities of emotional expressions by their block-wise base rate aimed to generate a bias for the more frequently encountered emotion. As a result, we found that individuals with higher IS showed lower thresholds for emotion recognition, reflected in decreased reaction times for emotional expressions especially of high intensity. Moreover, individuals with increased IS benefited more from a biased probability of an emotion, reflected in decreased reaction times for expected emotions. Lastly, weak evidence supporting a differential modulation of SCR by IS as a function of varying probabilities was found. Our results indicate that higher interoceptive sensibility facilitates the recognition of emotional changes and is accompanied by a more precise adaptation to emotion probabilities.

Touching events predict human action segmentation in brain and behavior.

Recognizing the actions of others depends on segmentation into meaningful events. After decades of research in this area, it remains still unclear how humans do this and which brain areas support underlying processes. Here we show that a computer vision-based model of touching and untouching events can predict human behavior in segmenting object manipulation actions with high accuracy. Using this computational model and functional Magnetic Resonance Imaging (fMRI), we pinpoint the neural networks underlying this segmentation behavior during an implicit action observation task. Segmentation was announced by a strong increase of visual activity at touching events followed by the engagement of frontal, hippocampal and insula regions, signaling updating expectation at subsequent untouching events. Brain activity and behavior show that touching-untouching motifs are critical features for identifying the key elements of actions including object manipulations.