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.

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.

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.

Prediction errors lead to updating of memories for conversations.

Previous research has established that the brain uses episodic memories to make continuous predictions about the world and that prediction errors, so the mismatch between generated predictions and reality, can lead to memory updating. However, it remains unclear whether prediction errors can stimulate updating in memories for naturalistic conversations. Participants encoded naturalistic dialogues, which were later presented in a modified form. We found that larger modifications were associated with increased learning of the modified statement. Moreover, memory for the original version of the statement was weakened after medium-strong prediction errors, which resulted from the interplay of modification extent and strength of previous memory. After strong prediction errors, both original and modification were well-remembered. Prediction errors thus play a role in keeping representations of statements and therefore socially relevant knowledge about others up to date.

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.

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.

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.

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.

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.

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.

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.

Positive and negative prediction error signals to violated expectations of face and place stimuli distinctively activate FFA and PPA.

Surprising scenarios can have different behavioural and neuronal consequences depending on the violation of the expectation. On the one hand, previous research has shown that the omission of a visual stimulus results in a robust cortical response representing that missing stimulus, a so-called negative prediction error. On the other hand, a large amount of studies revealed positive prediction error signals, entailing an increased neural response that can be attributed to the experience of a surprising, unexpected stimulus. However, there has been no evidence, so far, regarding how and when these prediction error signals co-occur. Here, we argue that the omission of an expected stimulus can and often does coincide with the appearance of an unexpected one. Therefore, we investigated whether positive and negative prediction error signals evoked by unpredicted cross-category stimulus transitions would temporally coincide during a speeded forced-choice fMRI paradigm. Foremost, our findings provide evidence of a behavioural effect regarding the facilitation of responses linked to expected stimuli. In addition, we obtained evidence for negative prediction error signals as seen in differential activation of FFA and PPA during unexpected place and face trials, respectively. Lastly, a psychophysiological interaction analysis revealed evidence for positive prediction error signals represented by context-dependent functional coupling between the right IFG and FFA or PPA, respectively, implicating a network that updates the internal representation after the appearance of an unexpected stimulus through involvement of this frontal area. The current results are consistent with a predictive coding account of cognition and underline the importance of considering the potential dual nature of expectation violations. Furthermore, our results put forward that positive and negative prediction error signalling can be directly linked to regions associated with the processing of different stimulus categories.

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.

Predictive Impact of Contextual Objects during Action Observation: Evidence from Functional Magnetic Resonance Imaging.

The processing of congruent stimuli, such as an object or action in its typical location, is usually associated with reduced neural activity, probably due to facilitated recognition. However, in some situations, congruency increases neural activity-for example, when objects next to observed actions are likely versus unlikely to be involved in forthcoming action steps. Here, we investigated using fMRI whether the processing of contextual cues during action perception is driven by their (in)congruency and, thus, informative value to make sense of an observed scene. Specifically, we tested whether both highly congruent contextual objects (COs), which strongly indicate a future action step, and highly incongruent COs, which require updating predictions about possible forthcoming action steps, provide more anticipatory information about the action course than moderately congruent COs. In line with our hypothesis that especially the inferior frontal gyrus (IFG) subserves the integration of the additional information into the predictive model of the action, we found highly congruent and incongruent COs to increase bilateral activity in action observation nodes, that is, the IFG, the occipitotemporal cortex, and the intraparietal sulcus. Intriguingly, BA 47 was significantly stronger engaged for incongruent COs reflecting the updating of prediction in response to conflicting information. Our findings imply that the IFG reflects the informative impact of COs on observed actions by using contextual information to supply and update the currently operating predictive model. In the case of an incongruent CO, this model has to be reconsidered and extended toward a new overarching action goal.

Impaired context-sensitive adjustment of behaviour in Parkinson's disease patients tested on and off medication: An fMRI study.

The brain's sensitivity to and accentuation of unpredicted over predicted sensory signals plays a fundamental role in learning. According to recent theoretical models of the predictive coding framework, dopamine is responsible for balancing the interplay between bottom-up input and top-down predictions by controlling the precision of surprise signals that guide learning. Using functional MRI, we investigated whether patients with Parkinson's disease (PD) show impaired learning from prediction errors requiring either adaptation or stabilisation of current predictions. Moreover, we were interested in whether deficits in learning over a specific time scale would be accompanied by altered surprise responses in dopamine-related brain structures. To this end, twenty-one PD patients tested on and off dopaminergic medication and twenty-one healthy controls performed a digit prediction paradigm. During the task, violations of sequence-based predictions either signalled the need to update or to stabilise the current prediction and, thus, to react to them or ignore them, respectively. To investigate contextual adaptation to prediction errors, the probability (or its inverse, surprise) of the violations fluctuated across the experiment. When the probability of prediction errors over a specific time scale increased, healthy controls but not PD patients off medication became more flexible, i.e., error rates at violations requiring a motor response decreased in controls but increased in patients. On the neural level, this learning deficit in patients was accompanied by reduced signalling in the substantia nigra and the caudate nucleus. In contrast, differences between the groups regarding the probabilistic modulation of behaviour and neural responses were much less pronounced at prediction errors requiring only stabilisation but no adaptation. Interestingly, dopaminergic medication could neither improve learning from prediction errors nor restore the physiological, neurotypical pattern. Our findings point to a pivotal role of dysfunctions of the substantia nigra and caudate nucleus in deficits in learning from flexibility-demanding prediction errors in PD. Moreover, the data witness poor effects of dopaminergic medication on learning in PD.

Adult patients with ADHD differ from healthy controls in implicit, but not explicit, emotion regulation

Background: There is increasing evidence that people with attention-deficit/hyperactivity disorder (ADHD) are impaired in emotion regulation, but psychophysiological and functional MRI data on emotion processing in adult patients with ADHD are scarce. We investigated the neural correlates of reappraisal as one of the most efficient emotion-regulation strategies. Methods: We included 30 adult patients with ADHD and 35 healthy controls in our study. We applied a well-established reappraisal paradigm in functional MRI and assessed behavioural emotion-regulation strategies with standardized questionnaires. We hypothesized that patients with ADHD would demonstrate impaired reappraisal related to reduced activations in the frontoparietal cognitive control network. Results: Despite our hypothesis, we found no significant activation differences in the neural reappraisal network between patients with ADHD and controls. As well, both groups revealed similar reappraisal success on the immediate behavioural ratings in the scanner. Interestingly, patients with ADHD revealed significantly increased activations in the dorsal and ventral anterior cingulate cortex (ACC) compared to controls when viewing negative > neutral pictures. These ACC activations were significantly correlated with the prevalence of habitual use of reappraisal in patients with ADHD only. Limitations: Patients withdrew medication only 24 hours before the experiment; we investigated negative, but not positive, emotion processing and regulation. Conclusion: Although emotion dysregulation is regarded as a core symptom of ADHD, explicit reappraisal does not seem to be impaired in adult patients. However, increased activation of the ACC implies stronger implicit emotion regulation induced by negative stimuli. This might be explained by emotional hyperresponsivity in patients with ADHD compared with controls.

The role of the temporoparietal junction (TPJ) in action observation: Agent detection rather than visuospatial transformation.

Recognizing and understanding the actions of others is usually coupled with perceiving someone else's body movements from a third person perspective (3pp) whereas we perceive our own actions from a first person perspective (1pp). From a neural viewpoint, a recent finding is that perceiving actions from a 3pp as compared to a 1pp activates the temporoparietal junction, a brain region associated with visuospatial transformation and perspective taking but also with mental state inference and Theory of Mind (ToM). The present fMRI study characterizes the response profile of TPJ to elucidate its role in action observation. Participants observed naturalistic and pixelized object-directed actions from a 3pp and 1pp. Critically, in the pixelized condition the action goal could only be inferred from the movement kinematics. Both left and right TPJ revealed an interaction: Neural activity in TPJ was enhanced for 3pp vs. 1pp actions in the naturalistic but not pixelized condition. This finding contradicts theories proposing that TPJ is generally involved in transforming the action into the observer's perspective to match perceived body movements with visuomotor representations in the observer's motor system, which would be particularly required when actions can only be inferred from movement kinematics. Instead, our results support the theory that perceptual 3pp-selective cues trigger ToM-related processes such as detection of other agents and reasoning about an action's underlying mental states.