Attention promotes the neural encoding of prediction errors

A dissociation between the effects of expectations and attention in selective visual processing

It is often claimed that probabilistic expectations affect visual perception directly, without mediation by selective attention. However, these claims have been disputed, as effects of expectation and attention are notoriously hard to dissociate experimentally. In this study, we used a new approach to separate expectations from attention. In four experiments (N = 60), participants searched for a target in a rapid serial visual presentation (RSVP) stream and had to identify a digit or a letter defined by a low-level cue (colour or shape). Expectations about the target's alphanumeric category were probabilistically manipulated. Since category membership is a high-level feature and since the target was embedded among many distractors that shared its category, targets from the expected category should not attract attention more than targets from the unexpected category. In the first experiment, these targets were more likely to be identified relative to targets from the unexpected category. Importantly, in the following experiments, we also included behavioural and electrophysiological indices of attentional guidance and engagement. This allowed us to examine whether expectations also modulated these or earlier attentional processes. Results showed that category-based expectations had no modulatory effects on attention, and only affected processing at later encoding-related stages. Alternative interpretation of expectation effects in terms of repetition priming or response bias were also ruled out. These observations provide new evidence for direct attention-independent expectation effects on perception. We suggest that expectations can adjust the threshold required for encoding expectations-congruent information, thereby affecting the speed with which target objects are encoded in working memory.

Adaptation in the visual system: Networked fatigue or suppressed prediction error signalling?

Our brains are constantly adapting to changes in our visual environments. Neural adaptation exerts a persistent influence on the activity of sensory neurons and our perceptual experience, however there is a lack of consensus regarding how adaptation is implemented in the visual system. One account describes fatigue-based mechanisms embedded within local networks of stimulus-selective neurons (networked fatigue models). Another depicts adaptation as a product of stimulus expectations (predictive coding models). In this review, I evaluate neuroimaging and psychophysical evidence that poses fundamental problems for predictive coding models of neural adaptation. Specifically, I discuss observations of distinct repetition and expectation effects, as well as incorrect predictions of repulsive adaptation aftereffects made by predictive coding accounts. Based on this evidence, I argue that networked fatigue models provide a more parsimonious account of adaptation effects in the visual system. Although stimulus expectations can be formed based on recent stimulation history, any consequences of these expectations are likely to co-occur (or interact) with effects of fatigue-based adaptation. I conclude by proposing novel, testable hypotheses relating to interactions between fatigue-based adaptation and other predictive processes, focusing on stimulus feature extrapolation phenomena.

Visual hallucinations originating in the retinofugal pathway under clinical and psychedelic conditions

Psychedelics like LSD (Lysergic acid diethylamide) and psilocybin are known to modulate perceptual modalities due to the activation of mostly serotonin receptors in specific cortical (e.g., visual cortex) and subcortical (e.g., thalamus) regions of the brain. In the visual domain, these psychedelic modulations often result in peculiar disturbances of viewed objects and light and sometimes even in hallucinations of non-existent environments, objects, and creatures. Although the underlying processes are poorly understood, research conducted over the past twenty years on the subjective experience of psychedelics details theories that attempt to explain these perceptual alterations due to a disruption of communication between cortical and subcortical regions. However, rare medical conditions in the visual system like Charles Bonnet syndrome that cause perceptual distortions may shed new light on the additional importance of the retinofugal pathway in psychedelic subjective experiences. Interneurons in the retina called amacrine cells could be the first site of visual psychedelic modulation and aid in disrupting the hierarchical structure of how humans perceive visual information. This paper presents an understanding of how the retinofugal pathway communicates and modulates visual information in psychedelic and clinical conditions. Therefore, we elucidate a new theory of psychedelic modulation in the retinofugal pathway.

Attention spotlight in V1-based cortico-cortical interactions in human visual hierarchy

Attention is often viewed as a mental spotlight, which can be scaled like a zoom lens at specific spatial locations and features a center-surround gradient. Here, we demonstrate a neural signature of attention spotlight in signal transmission along the visual hierarchy. fMRI background connectivity analysis was performed between retinotopic V1 and downstream areas to characterize the spatial distribution of inter-areal interaction under two attentional states. We found that, compared to diffused attention, focal attention sharpened the spatial gradient in the strength of the background connectivity. Dynamic causal modeling analysis further revealed the effect of attention in both the feedback and feedforward connectivity between V1 and extrastriate cortex. In a context which induced a strong effect of crowding, the effect of attention in the background connectivity profile diminished. Our findings reveal a context-dependent attention prioritization in information transmission via modulating the recurrent processing across the early stages in human visual cortex.

Orientation and contrast deviance examined: Contrast effects mimic deviant-related negativity yet neither produce the canonical neural correlate of prediction error

The visual mismatch negativity (vMMN) is a negative-going event-related potential (ERP) component that is largest somewhere between 100 and 300 ms after the onset of an unpredictable visual event (i.e., a deviant) in an otherwise predictable sequence of visual events (i.e., standards). Many have argued that the vMMN allows us to monitor our ever-changing visual environment for deviants critical to our survival. Recently, however, it has become unclear whether unpredicted changes in low-level features of visual input, like orientation, can evoke the vMMN. I address this by testing isolated orientation changes, to confirm recent findings, and isolated contrast changes, to determine whether other low-level features of visual input do not evoke the vMMN in a traditional oddball paradigm. Eighteen participants saw sequences of rare, unanticipated, and different deviant stimuli, interspersed among frequent, anticipated, and identical standard stimuli. Stimuli were Gabor patches. Neither deviant produced a vMMN. Therefore, changes in low-level visual properties of well-controlled stimuli-a stimulus in which one property can be manipulated while all others remain unaffected-like Gabor patches do not yield a vMMN.

Event Probabilities Have a Different Impact on Early and Late Electroencephalographic Measures Regarded as Metrics of Prediction

The oddball protocol has been used to study the neural and perceptual consequences of implicit predictions in the human brain. The protocol involves presenting a sequence of identical repeated events that are eventually broken by a novel "oddball" presentation. Oddball presentations have been linked to increased neural responding and to an exaggeration of perceived duration relative to repeated events. Because the number of repeated events in such protocols is circumscribed, as more repeats are encountered, the conditional probability of a further repeat decreases-whereas the conditional probability of an oddball increases. These facts have not been appreciated in many analyses of oddballs; repeats and oddballs have rather been treated as binary event categories. Here, we show that the human brain is sensitive to conditional event probabilities in an active, visual oddball paradigm. P300 responses (a relatively late component of visually evoked potentials measured with EEG) tended to be greater for less likely oddballs and repeats. By contrast, P1 responses (an earlier component) increased for repeats as a goal-relevant target presentation neared, but this effect occurred even when repeat probabilities were held constant, and oddball P1 responses were invariant. We also found that later, more likely oddballs seemed to last longer, and this effect was largely independent of the number of preceding repeats. These findings speak against a repetition suppression account of the temporal oddball effect. Overall, our data highlight an impact of event probability on later, rather than earlier, electroencephalographic measures previously related to predictive processes-and the importance of considering conditional probabilities in sequential presentation paradigms.

Same but different: The latency of a shared expectation signal interacts with stimulus attributes

Predictive coding theories assert that perceptual inference is a hierarchical process of belief updating, wherein the onset of unexpected sensory data causes so-called prediction error responses that calibrate erroneous inferences. Given the functionally specialised organisation of visual cortex, it is assumed that prediction error propagation interacts with the specific visual attribute violating an expectation. We sought to test this within the temporal domain by applying time-resolved decoding methods to electroencephalography (EEG) data evoked by contextual trajectory violations of either brightness, size, or orientation within a bound stimulus. We found that following ∼170 ms post stimulus onset, responses to both size violations and orientation violations were decodable from physically identical control trials in which no attributes were violated. These two violation types were then directly compared, with attribute-specific signalling being decoded from 265 ms. Temporal generalisation suggested that this dissociation was driven by latency shifts in shared expectation signalling between the two conditions. Using a novel temporal bias method, we then found that this shared signalling occurred earlier for size violations than orientation violations. To our knowledge, we are among the first to decode expectation violations in humans using EEG and have demonstrated a temporal dissociation in attribute-specific expectancy violations.

Modelling decision-making biases

Biases are a fundamental aspect of everyday life decision-making. A variety of modelling approaches have been suggested to capture decision-making biases. Statistical models are a means to describe the data, but the results are usually interpreted according to a verbal theory. This can lead to an ambiguous interpretation of the data. Mathematical cognitive models of decision-making outline the structure of the decision process with formal assumptions, providing advantages in terms of prediction, simulation, and interpretability compared to statistical models. We compare studies that used both signal detection theory and evidence accumulation models as models of decision-making biases, concluding that the latter provides a more comprehensive account of the decision-making phenomena by including response time behavior. We conclude by reviewing recent studies investigating attention and expectation biases with evidence accumulation models. Previous findings, reporting an exclusive influence of attention on the speed of evidence accumulation and prior probability on starting point, are challenged by novel results suggesting an additional effect of attention on non-decision time and prior probability on drift rate.

Neuronal responses to omitted tones in the auditory brain: A neuronal correlate for predictive coding

Prediction provides key advantages for survival, and cognitive studies have demonstrated that the brain computes multilevel predictions. Evidence for predictions remains elusive at the neuronal level because of the complexity of separating neural activity into predictions and stimulus responses. We overcome this challenge by recording from single neurons from cortical and subcortical auditory regions in anesthetized and awake preparations, during unexpected stimulus omissions interspersed in a regular sequence of tones. We find a subset of neurons that responds reliably to omitted tones. In awake animals, omission responses are similar to anesthetized animals, but larger and more frequent, indicating that the arousal and attentional state levels affect the degree to which predictions are neuronally represented. Omission-sensitive neurons also responded to frequency deviants, with their omission responses getting emphasized in the awake state. Because omission responses occur in the absence of sensory input, they provide solid and empirical evidence for the implementation of a predictive process.

Attention is required for canonical brain signature of prediction error despite early encoding of the stimuli

Prediction error is a basic component of predictive-coding theory of brain processing. According to the theory, each stage of brain processing of sensory information generates a model of the current sensory input; subsequent input is compared against the model and only if there is a mismatch, a prediction error, is further processing performed. Recently, Smout and colleagues found that a signature of prediction error, the visual (v) mismatch negativity (MMN), for a fundamental property of visual input-its orientation-was absent without endogenous attention on the stimuli. This is remarkable because the weight of evidence for MMNs from audition and vision is that they occur without endogenous attention. To resolve this discrepancy, we conducted an experiment addressing 2 alternative explanations for Smout and colleagues' finding: that it was from a lack of reproducibility or that participants' visual systems did not encode the stimuli when attention was on something else. We conducted a similar experiment to that of Smout and colleagues. We showed 21 participants sequences of identically oriented Gabor patches, standards, and, unpredictably, otherwise identical, Gabor patches differing in orientation by ±15°, ±30°, and ±60°, deviants. To test whether participants encoded the orientation of the standards, we varied the number of standards preceding a deviant, allowing us to search for a decrease in activity with the number of repetitions of standards-repetition suppression. We diverted participants' attention from the oriented stimuli with a central, letter-detection task. We reproduced Smout and colleagues' finding of no vMMN without endogenous attention, strengthening their finding. We found that our participants showed repetition suppression: They did encode the stimuli preattentively. We also found early processing of deviants. We discuss various explanations why the earlier processing did not extend into the vMMN time window, including low precision of prediction.

Cortical Tracking of Continuous Speech Under Bimodal Divided Attention

Speech processing often occurs amid competing inputs from other modalities, for example, listening to the radio while driving. We examined the extent to which dividing attention between auditory and visual modalities (bimodal divided attention) impacts neural processing of natural continuous speech from acoustic to linguistic levels of representation. We recorded electroencephalographic (EEG) responses when human participants performed a challenging primary visual task, imposing low or high cognitive load while listening to audiobook stories as a secondary task. The two dual-task conditions were contrasted with an auditory single-task condition in which participants attended to stories while ignoring visual stimuli. Behaviorally, the high load dual-task condition was associated with lower speech comprehension accuracy relative to the other two conditions. We fitted multivariate temporal response function encoding models to predict EEG responses from acoustic and linguistic speech features at different representation levels, including auditory spectrograms and information-theoretic models of sublexical-, word-form-, and sentence-level representations. Neural tracking of most acoustic and linguistic features remained unchanged with increasing dual-task load, despite unambiguous behavioral and neural evidence of the high load dual-task condition being more demanding. Compared to the auditory single-task condition, dual-task conditions selectively reduced neural tracking of only some acoustic and linguistic features, mainly at latencies >200 ms, while earlier latencies were surprisingly unaffected. These findings indicate that behavioral effects of bimodal divided attention on continuous speech processing occur not because of impaired early sensory representations but likely at later cognitive processing stages. Crossmodal attention-related mechanisms may not be uniform across different speech processing levels.

Event-Related Potentials Index Prediction Error Signalling During Perceptual Processing of Emotional Facial Expressions

Humans use socially relevant stimuli to guide perceptual processing of the surrounding environment, with emotional stimuli receiving preferential attention due to their social importance. Predictive coding theory asserts this cognitive process occurs efficiently by combining predictions about what is to be perceived with incoming sensory information, generating prediction errors that are then used to update future predictions. Recent evidence has identified differing neural activity that demonstrates how spatial and feature-based attention may interact with prediction, yet how emotion-guided attention may influence this relationship remains unknown. In the present study, participants viewed a display of two faces in which attention, prediction, and emotion were manipulated, and responded to a face expressing a specific emotion (anger or happiness). The N170 was found to be enhanced by unpredictable as opposed to predictable stimuli, indicating that it indexes general prediction error signalling processes. The N300 amplitudes were also enhanced by unpredictable stimuli, but they were also affected by the attentional status of angry but not happy faces, suggesting that there are differences in prediction error processes indexed by the N170 and N300. Overall, the findings suggest that the N170 and N300 both index violations of expectation for spatial manipulations of stimuli in accordance with prediction error responding processes.

The effect of perceptual expectation on processing gain, attention and the perceptual decision bias in children and adolescents with Autism Spectrum Disorder (ASD)

Perceptual expectations influence perception, attention and the perceptual decision bias during visuospatial orienting, which is impaired in individuals with Autism Spectrum Disorder (ASD). In this study, we investigated whether during visuospatial orienting, perceptual expectations in ASD differentially influence perception, attention and the perceptual decision bias relative to neurotypical controls (NT). Twenty-three children and adolescents with ASD and 23 NT completed a visuospatial orienting task, which compared the effect of a valid relative to an invalid perceptual expectation on target detection (cue validity effect). Group differences were calculated regarding the cue validity effect on neural correlates of processing gain (N1a amplitude) and attention (N1pc amplitude), the perceptual decision bias and mean reaction time (RT). In ASD relative to NT, findings showed a reduced processing gain for validly relative to invalidly cued targets and increased attentional response following invalidly relative to validly cued targets. Increased attention correlated with faster performance across groups. Increased processing correlated with a higher perceptual decision bias and faster mean RT in NT, but not in ASD. Results suggest that during visuospatial orienting, perceptual expectations in ASD may drive changes in sensory processing and stimulus-driven attention, which may differentially guide behavioural responses.

Using expectation violation models to improve the outcome of psychological treatments

Expectations are a central maintaining mechanism in mental disorders and most psychological treatments aim to directly or indirectly modify clinically relevant expectations. Therefore, it is crucial to examine why patients with mental disorders maintain dysfunctional expectations, even in light of disconfirming evidence, and how expectation-violating situations should be created in treatment settings to optimize treatment outcome and reduce the risk of treatment failures. The different psychological subdisciplines offer various approaches for understanding the underlying mechanisms of expectation development, persistence, and change. Here, we convey recommendations on how to improve psychological treatments by considering these different perspectives. Based on our expectation violation model, we argue that the outcome of expectation violation depends on several characteristics: features of the expectation-violating situation; the dynamics between the magnitude of expectation violation and cognitive immunization processes; dealing with uncertainties during and after expectation change; controlled and automatic attention processes; and the costs of expectation changes. Personality factors further add to predict outcomes and may offer a basis for personalized treatment planning. We conclude with a list of recommendations derived from basic psychology that could contribute to improved treatment outcome and to reduced risks of treatment failures.

Pain, from perception to action: A computational perspective

Pain is driven by sensation and emotion, and in turn, it motivates decisions and actions. To fully appreciate the multidimensional nature of pain, we formulate the study of pain within a closed-loop framework of sensory-motor prediction. In this closed-loop cycle, prediction plays an important role, as the interaction between prediction and actual sensory experience shapes pain perception and subsequently, action. In this Perspective, we describe the roles of two prominent computational theories-Bayesian inference and reinforcement learning-in modeling adaptive pain behaviors. We show that prediction serves as a common theme between these two theories, and that each of these theories can explain unique aspects of the pain perception-action cycle. We discuss how these computational theories and models can improve our mechanistic understandings of pain-centered processes such as anticipation, attention, placebo hypoalgesia, and pain chronification.

Explaining neural activity in human listeners with deep learning via natural language processing of narrative text

Deep learning (DL) approaches may also inform the analysis of human brain activity. Here, a state-of-art DL tool for natural language processing, the Generative Pre-trained Transformer version 2 (GPT-2), is shown to generate meaningful neural encodings in functional MRI during narrative listening. Linguistic features of word unpredictability (surprisal) and contextual importance (saliency) were derived from the GPT-2 applied to the text of a 12-min narrative. Segments of variable duration (from 15 to 90 s) defined the context for the next word, resulting in different sets of neural predictors for functional MRI signals recorded in 27 healthy listeners of the narrative. GPT-2 surprisal, estimating word prediction errors from the artificial network, significantly explained the neural data in superior and middle temporal gyri (bilaterally), in anterior and posterior cingulate cortices, and in the left prefrontal cortex. GPT-2 saliency, weighing the importance of context words, significantly explained the neural data for longer segments in left superior and middle temporal gyri. These results add novel support to the use of DL tools in the search for neural encodings in functional MRI. A DL language model like the GPT-2 may feature useful data about neural processes subserving language comprehension in humans, including next-word context-related prediction.

From Loss of Control to Social Exclusion: ERP Effects of Preexposure to a Social Threat in the Cyberball Paradigm

Previous studies indicated that the onsets of different social threats, such as threats to ”belonging” and “control”, are inconsistent with the subjective beliefs of social participation and require readjustment of expectations. Because a common cognitive system is assumed to be involved, the adjustment triggered by the experience of a single social threat should affect the processing of subsequent social interactions. We examined how preexposure to a loss of control affected social exclusion processing by using the Cyberball paradigm. An event-related brain component (P3) served as a probe for the state of the expectancy system, and self-reports reflected the subjective evaluations of the social threats. In the control group (n = 23), the transition to exclusion elicited a significant P3 effect and a high threat to belonging in the self-reports. Both effects were significantly reduced when the exclusion was preceded by preexposure to a loss of control (EG1_disc, n = 23). These effects, however, depend on the offset of the preexposure. In case of a continuation (EG2_cont, n = 24), the P3 effect was further reduced, but the threat to belonging was restored. We conclude that the P3 data are consistent with predictions of a common expectancy violation account, whereas self-reports are supposed to be affected by additional processes.

Adding noise is a confounded nuisance

A wide variety of research and clinical assessments involve presenting speech stimuli in the presence of some kind of noise. Here, I selectively review two theoretical perspectives and discuss ways in which these perspectives may help researchers understand the consequences for listeners of adding noise to a speech signal. I argue that adding noise changes more about the listening task than merely making the signal more difficult to perceive. To fully understand the effects of an added noise on speech perception, we must consider not just how much the noise affects task difficulty, but also how it affects all of the systems involved in understanding speech: increasing message uncertainty, modifying attentional demand, altering affective response, and changing motivation to perform the task.

Violated Expectations for Spatial and Feature Attributes of Visual Trajectories Modulate Event-Related Potential Amplitudes across the Visual Processing Hierarchy

During visual perception the brain must combine its predictions about what is to be perceived with incoming relevant information. The present study investigated how this process interacts with attention by using event-related potentials that index these cognitive mechanisms. Specifically, this study focused on examining how the amplitudes of the N170, N2pc, and N300 would be modulated by violations of expectations for spatial and featural attributes of visual stimuli. Participants viewed a series of shape stimuli in which a salient shape moved across a set of circular locations so that the trajectory of the shape implied the final position and shape of the stimulus. The final salient stimuli occurred in one of four possible outcomes: predictable position and shape, predictable position but unpredictable shape, unpredictable position but predictable shape, and unpredictable position and shape. The N170 was enhanced by unpredictable positions and shapes, whereas the N300 was enlarged only by unpredictable positions. The N2pc was not modulated by violations of expectation for shapes or positions. Additionally, it was observed post-hoc that the P1pc amplitude was increased by unpredictable shapes. These findings revealed that incorrect prediction increases neural activity. Furthermore, they suggest that prediction and attention interact differently in different stages of visual perception, depending on the type of attention being engaged: The N170 indexes initial prediction error signalling irrespective of the type of information (spatial or featural) in which error occurs, followed by the N300 as a marker of prediction updating involving reorientation of spatial attention.

Brain-heart interactions are modulated across the respiratory cycle via interoceptive attention

Respiration and heartbeat continuously interact within the living organism at many different levels, representing two of the main oscillatory rhythms of the body and providing major sources of interoceptive information to the brain. Despite the modulatory effect of respiration on exteroception and cognition has been recently established in humans, its role in shaping interoceptive perception has been scarcely investigated so far. In two independent studies, we investigated the effect of spontaneous breathing on cardiac interoception by assessing the Heartbeat Evoked Potential (HEP) in healthy humans. In Study 1, we compared HEP activity for heartbeats occurred during inhalation and exhalation in 40 volunteers at rest. We found higher HEP amplitude during exhalation, compared to inhalation, over fronto-centro-parietal areas. This suggests increased brain-heart interactions and improved cortical processing of the heartbeats during exhalation. Further analyses revealed that this effect was moderated by heart rate changes. In Study 2, we tested the respiratory phase-dependent modulation of HEP activity in 20 volunteers during Exteroceptive and Interoceptive conditions of the Heartbeat Detection (HBD) task. In these conditions, participants were requested to tap at each heartbeat, either listened to or felt, respectively. Results showed higher HEP activity and higher detection accuracy at exhalation than inhalation in the Interoceptive condition only. Direct comparisons of Interoceptive and Exteroceptive conditions confirmed stronger respiratory phase-dependent modulation of HEP and accuracy when attention was directed towards the interoceptive stimuli. Moreover, HEP changes during the Interoceptive condition were independent of heart physiology, but were positively correlated with higher detection accuracy at exhalation than inhalation. This suggests a link between optimization of cortical processing of cardiac signals and detection of heartbeats across the respiratory cycle. Overall, we provide data showing that respiration shapes cardiac interoception at the neurophysiological and behavioural levels. Specifically, exhalation may allow attentional shift towards the internal bodily states.

Selection history and task predictability determine the precision expectations in attentional control

Predictive processing frameworks have demonstrated the central role that prediction plays in a range of cognitive processes including bottom-up and top-down mechanisms of attention control. However, relatively little is understood about how predictive processes interact with the third main determinant of attentional priority - selection history. In this experiment, participants developed a history of either color or shape selection while we observed the impact of these histories in an additional singleton search task using behavioral measures and ERP measures of attentional control. Throughout the experiment, participants were encouraged to predict the upcoming display, but prediction errors were either high or low depending on session. Persistent group differences in our results showed that selection history contributes to the precision weighting of a stimulus, and that this is mediated by overall prediction error. Color-singleton distractors captured attention and required greater suppression when participants had a history of color selection; however, these participants gained large benefits when the upcoming stimuli were highly predictable. We suggest that selection history modulates the precision expectations for a feature in a persistent and implicit way, producing an attentional bias that predictability can help to counteract, but cannot prevent or eliminate entirely.

The time-course of feature-based attention effects dissociated from temporal expectation and target-related processes

Selective attention prioritises relevant information amongst competing sensory input. Time-resolved electrophysiological studies have shown stronger representation of attended compared to unattended stimuli, which has been interpreted as an effect of attention on information coding. However, because attention is often manipulated by making only the attended stimulus a target to be remembered and/or responded to, many reported attention effects have been confounded with target-related processes such as visual short-term memory or decision-making. In addition, attention effects could be influenced by temporal expectation about when something is likely to happen. The aim of this study was to investigate the dynamic effect of attention on visual processing using multivariate pattern analysis of electroencephalography (EEG) data, while (1) controlling for target-related confounds, and (2) directly investigating the influence of temporal expectation. Participants viewed rapid sequences of overlaid oriented grating pairs while detecting a "target" grating of a particular orientation. We manipulated attention, one grating was attended and the other ignored (cued by colour), and temporal expectation, with stimulus onset timing either predictable or not. We controlled for target-related processing confounds by only analysing non-target trials. Both attended and ignored gratings were initially coded equally in the pattern of responses across EEG sensors. An effect of attention, with preferential coding of the attended stimulus, emerged approximately 230 ms after stimulus onset. This attention effect occurred even when controlling for target-related processing confounds, and regardless of stimulus onset expectation. These results provide insight into the effect of feature-based attention on the dynamic processing of competing visual information.

A Revised Framework for the Investigation of Expectation Update Versus Maintenance in the Context of Expectation Violations: The ViolEx 2.0 Model

Expectations are probabilistic beliefs about the future that shape and influence our perception, affect, cognition, and behavior in many contexts. This makes expectations a highly relevant concept across basic and applied psychological disciplines. When expectations are confirmed or violated, individuals can respond by either updating or maintaining their prior expectations in light of the new evidence. Moreover, proactive and reactive behavior can change the probability with which individuals encounter expectation confirmations or violations. The investigation of predictors and mechanisms underlying expectation update and maintenance has been approached from many research perspectives. However, in many instances there has been little exchange between different research fields. To further advance research on expectations and expectation violations, collaborative efforts across different disciplines in psychology, cognitive (neuro)science, and other life sciences are warranted. For fostering and facilitating such efforts, we introduce the ViolEx 2.0 model, a revised framework for interdisciplinary research on cognitive and behavioral mechanisms of expectation update and maintenance in the context of expectation violations. To support different goals and stages in interdisciplinary exchange, the ViolEx 2.0 model features three model levels with varying degrees of specificity in order to address questions about the research synopsis, central concepts, or functional processes and relationships, respectively. The framework can be applied to different research fields and has high potential for guiding collaborative research efforts in expectation research.

Regenerative Virtual Therapy: The Use of Multisensory Technologies and Mindful Attention for Updating the Altered Representations of the Bodily Self

The term “regenerative medicine” (RM) indicates an emerging trend in biomedical sciences that aims at replacing, engineering, or regenerating human cells, tissues, or organs to restore or establish normal function. So far, the focus of RM has been the physical body. Neuroscience, however, is now suggesting that mental disorders can be broadly characterized by a dysfunction in the way the brain computes and integrates the representations of the inner and outer body across time [bodily self-consciousness (BSC)]. In this perspective, we proposed a new kind of clinical intervention, i.e., “Regenerative Virtual Therapy” (RVT), which integrates knowledge from different disciplines, from neuroscience to computational psychiatry, to regenerate a distorted or faulty BSC. The main goal of RVT was to use technology-based somatic modification techniques to restructure the maladaptive bodily representations behind a pathological condition. Specifically, starting from a Bayesian model of our BSC (i.e., body matrix), we suggested the use of mindful attention, cognitive reappraisal, and brain stimulation techniques merged with high-rewarding and novel synthetic multisensory bodily experience (i.e., a virtual reality full-body illusion in sync with a low predictabIlity interoceptive modulation) to rewrite a faulty experience of the body and to regenerate the wellbeing of an individual. The use of RVT will also offer an unprecedented experimental overview of the dynamics of our bodily representations, allowing the reverse-engineering of their functioning for hacking them using advanced technologies.

Attention and prediction modulations in expected and unexpected visuospatial trajectories

Humans are constantly exposed to a rich tapestry of visual information in a potentially changing environment. To cope with the computational burden this engenders, our perceptual system must use prior context to simultaneously prioritise stimuli of importance and suppress irrelevant surroundings. This study investigated the influence of prediction and attention in visual perception by investigating event-related potentials (ERPs) often associated with these processes, N170 and N2pc for prediction and attention, respectively. A contextual trajectory paradigm was used which violated visual predictions and neglected to predetermine areas of spatial interest, to account for the potentially unpredictable nature of a real-life visual scene. Participants (N = 36) viewed a visual display of cued and non-cued shapes rotating in a five-step predictable trajectory, with the fifth and final position of either the cued or non-cued shape occurring in a predictable or unpredictable spatial location. To investigate the predictive coding theory of attention we used factors of attention and prediction, whereby attention was manipulated as either cued or non-cued conditions, and prediction manipulated in either predictable or unpredictable conditions. Results showed both enhanced N170 and N2pc amplitudes to unpredictable compared to predictable stimuli. Stimulus cueing status also increased N170 amplitude, but this did not interact with stimulus predictability. The N2pc amplitude was not affected by stimulus cueing status. In accordance with previous research these results suggest the N170 is in part a visual prediction error response with respect to higher-level visual processes, and furthermore the N2pc may index attention reorientation. The results demonstrate prior context influences the sensitivity of the N170 and N2pc electrophysiological responses. These findings add further support to the role of N170 as a prediction error signal and suggest that the N2pc may reflect attentional reorientation in response to unpredicted stimulus locations.

Preparatory delta phase response is correlated with naturalistic speech comprehension performance

While human speech comprehension is thought to be an active process that involves top-down predictions, it remains unclear how predictive information is used to prepare for the processing of upcoming speech information. We aimed to identify the neural signatures of the preparatory processing of upcoming speech. Participants selectively attended to one of two competing naturalistic, narrative speech streams, and a temporal response function (TRF) method was applied to derive event-related-like neural responses from electroencephalographic data. The phase responses to the attended speech at the delta band (1-4 Hz) were correlated with the comprehension performance of individual participants, with a latency of - 200-0 ms relative to the onset of speech amplitude envelope fluctuations over the fronto-central and left-lateralized parietal electrodes. The phase responses to the attended speech at the alpha band also correlated with comprehension performance but with a latency of 650-980 ms post-onset over the fronto-central electrodes. Distinct neural signatures were found for the attentional modulation, taking the form of TRF-based amplitude responses at a latency of 240-320 ms post-onset over the left-lateralized fronto-central and occipital electrodes. Our findings reveal how the brain gets prepared to process an upcoming speech in a continuous, naturalistic speech context.

Corticothalamic Pathways in Auditory Processing: Recent Advances and Insights From Other Sensory Systems

The corticothalamic (CT) pathways emanate from either Layer 5 (L5) or 6 (L6) of the neocortex and largely outnumber the ascending, thalamocortical pathways. The CT pathways provide the anatomical foundations for an intricate, bidirectional communication between thalamus and cortex. They act as dynamic circuits of information transfer with the ability to modulate or even drive the response properties of target neurons at each synaptic node of the circuit. L6 CT feedback pathways enable the cortex to shape the nature of its driving inputs, by directly modulating the sensory message arriving at the thalamus. L5 CT pathways can drive the postsynaptic neurons and initiate a transthalamic corticocortical circuit by which cortical areas communicate with each other. For this reason, L5 CT pathways place the thalamus at the heart of information transfer through the cortical hierarchy. Recent evidence goes even further to suggest that the thalamus via CT pathways regulates functional connectivity within and across cortical regions, and might be engaged in cognition, behavior, and perceptual inference. As descending pathways that enable reciprocal and context-dependent communication between thalamus and cortex, we venture that CT projections are particularly interesting in the context of hierarchical perceptual inference formulations such as those contemplated in predictive processing schemes, which so far heavily rely on cortical implementations. We discuss recent proposals suggesting that the thalamus, and particularly higher order thalamus via transthalamic pathways, could coordinate and contextualize hierarchical inference in cortical hierarchies. We will explore these ideas with a focus on the auditory system.

Modulation of the Primary Auditory Thalamus When Recognizing Speech with Background Noise

Recognizing speech in background noise is a strenuous daily activity, yet most humans can master it. An explanation of how the human brain deals with such sensory uncertainty during speech recognition is to-date missing. Previous work has shown that recognition of speech without background noise involves modulation of the auditory thalamus (medial geniculate body; MGB): there are higher responses in left MGB for speech recognition tasks that require tracking of fast-varying stimulus properties in contrast to relatively constant stimulus properties (e.g., speaker identity tasks) despite the same stimulus input. Here, we tested the hypotheses that (1) this task-dependent modulation for speech recognition increases in parallel with the sensory uncertainty in the speech signal, i.e., the amount of background noise; and that (2) this increase is present in the ventral MGB, which corresponds to the primary sensory part of the auditory thalamus. In accordance with our hypothesis, we show, by using ultra-high-resolution functional magnetic resonance imaging (fMRI) in male and female human participants, that the task-dependent modulation of the left ventral MGB (vMGB) for speech is particularly strong when recognizing speech in noisy listening conditions in contrast to situations where the speech signal is clear. The results imply that speech in noise recognition is supported by modifications at the level of the subcortical sensory pathway providing driving input to the auditory cortex.SIGNIFICANCE STATEMENT Speech recognition in noisy environments is a challenging everyday task. One reason why humans can master this task is the recruitment of additional cognitive resources as reflected in recruitment of non-language cerebral cortex areas. Here, we show that also modulation in the primary sensory pathway is specifically involved in speech in noise recognition. We found that the left primary sensory thalamus (ventral medial geniculate body; vMGB) is more involved when recognizing speech signals as opposed to a control task (speaker identity recognition) when heard in background noise versus when the noise was absent. This finding implies that the brain optimizes sensory processing in subcortical sensory pathway structures in a task-specific manner to deal with speech recognition in noisy environments.

Automatic Sensory Predictions: A Review of Predictive Mechanisms in the Brain and Their Link to Conscious Processing

The human brain has the astonishing capacity of integrating streams of sensory information from the environment and forming predictions about future events in an automatic way. Despite being initially developed for visual processing, the bulk of predictive coding research has subsequently focused on auditory processing, with the famous mismatch negativity signal as possibly the most studied signature of a surprise or prediction error (PE) signal. Auditory PEs are present during various consciousness states. Intriguingly, their presence and characteristics have been linked with residual levels of consciousness and return of awareness. In this review we first give an overview of the neural substrates of predictive processes in the auditory modality and their relation to consciousness. Then, we focus on different states of consciousness - wakefulness, sleep, anesthesia, coma, meditation, and hypnosis - and on what mysteries predictive processing has been able to disclose about brain functioning in such states. We review studies investigating how the neural signatures of auditory predictions are modulated by states of reduced or lacking consciousness. As a future outlook, we propose the combination of electrophysiological and computational techniques that will allow investigation of which facets of sensory predictive processes are maintained when consciousness fades away.

Early alpha/beta oscillations reflect the formation of face-related expectations in the brain

Although statistical regularities in the environment often go explicitly unnoticed, traces of implicit learning are evident in our neural activity. Recent perspectives have offered evidence that both pre-stimulus oscillations and peri-stimulus event-related potentials are reliable biomarkers of implicit expectations arising from statistical learning. What remains ambiguous, however, is the origination and development of these implicit expectations. To address this lack of knowledge and determine the temporal constraints of expectation formation, pre-stimulus increases in alpha/beta power were investigated alongside a reduction in the N170 and a suppression in peri-/post-stimulus gamma power. Electroencephalography was acquired from naive participants who engaged in a gender classification task. Participants were uninformed, that eight face images were sorted into four reoccurring pairs which were pseudorandomly hidden amongst randomly occurring face images. We found a reduced N170 for statistically expected images at left parietal and temporo-parietal electrodes. Furthermore, enhanced gamma power following the presentation of random images emphasized the bottom-up processing of these arbitrary occurrences. In contrast, enhanced alpha/beta power was evident pre-stimulus for expected relative to random faces. A particularly interesting finding was the early onset of alpha/beta power enhancement which peaked immediately after the depiction of the predictive face. Hence, our findings propose an approximate timeframe throughout which consistent traces of enhanced alpha/beta power illustrate the early prioritisation of top-down processes to facilitate the development of implicitly cued face-related expectations.

The N300: An Index for Predictive Coding of Complex Visual Objects and Scenes

Predictive coding models can simulate known perceptual or neuronal phenomena, but there have been fewer attempts to identify a reliable neural signature of predictive coding for complex stimuli. In a pair of studies, we test whether the N300 component of the event-related potential, occurring 250–350-ms poststimulus-onset, has the response properties expected for such a signature of perceptual hypothesis testing at the level of whole objects and scenes. We show that N300 amplitudes are smaller to representative (“good exemplars”) compared with less representative (“bad exemplars”) items from natural scene categories. Integrating these results with patterns observed for objects, we establish that, across a variety of visual stimuli, the N300 is responsive to statistical regularity, or the degree to which the input is “expected” (either explicitly or implicitly) based on prior knowledge, with statistically regular images evoking a reduced response. Moreover, we show that the measure exhibits context-dependency; that is, we find the N300 sensitivity to category representativeness when stimuli are congruent with, but not when they are incongruent with, a category pre-cue. Thus, we argue that the N300 is the best candidate to date for an index of perceptual hypotheses testing for complex visual objects and scenes.

Keeping the Breath in Mind: Respiration, Neural Oscillations, and the Free Energy Principle

Scientific interest in the brain and body interactions has been surging in recent years. One fundamental yet underexplored aspect of brain and body interactions is the link between the respiratory and the nervous systems. In this article, we give an overview of the emerging literature on how respiration modulates neural, cognitive and emotional processes. Moreover, we present a perspective linking respiration to the free-energy principle. We frame volitional modulation of the breath as an active inference mechanism in which sensory evidence is recontextualized to alter interoceptive models. We further propose that respiration-entrained gamma oscillations may reflect the propagation of prediction errors from the sensory level up to cortical regions in order to alter higher level predictions. Accordingly, controlled breathing emerges as an easily accessible tool for emotional, cognitive, and physiological regulation.

How Native Background Affects Human Performance in Real-World Visual Object Detection: An Event-Related Potential Study

Visual processing refers to the process of perceiving, analyzing, synthesizing, manipulating, transforming, and thinking of visual objects. It is modulated by both stimulus-driven and goal-directed factors and manifested in neural activities that extend from visual cortex to high-level cognitive areas. Extensive body of studies have investigated the neural mechanisms of visual object processing using synthetic or curated visual stimuli. However, synthetic or curated images generally do not accurately reflect the semantic links between objects and their backgrounds, and previous studies have not provided answers to the question of how the native background affects visual target detection. The current study bridged this gap by constructing a stimulus set of natural scenes with two levels of complexity and modulating participants' attention to actively or passively attend to the background contents. Behaviorally, the decision time was elongated when the background was complex or when the participants' attention was distracted from the detection task, and the object detection accuracy was decreased when the background was complex. The results of event-related potentials (ERP) analysis explicated the effects of scene complexity and attentional state on the brain responses in occipital and centro-parietal areas, which were suggested to be associated with varied attentional cueing and sensory evidence accumulation effects in different experimental conditions. Our results implied that efficient visual processing of real-world objects may involve a competition process between context and distractors that co-exist in the native background, and extensive attentional cues and fine-grained but semantically irrelevant scene information were perhaps detrimental to real-world object detection.

Enhanced Sensory Coding in Mouse Vibrissal and Visual Cortex through TRPA1

Transient receptor potential ankyrin 1 (TRPA1) is a non-selective cation channel, broadly expressed throughout the body. Despite its expression in the mammalian brain, little is known about the contribution of TRPA1 to cortical function. Here, we characterize how TRPA1 affects sensory information processing in two cortical areas in mice: the primary vibrissal (whisker) somatosensory cortex (vS1) and the primary visual cortex (V1). In vS1, local activation of TRPA1 by allyl isothiocyanate (AITC) increases the ongoing activity of neurons and their evoked response to vibrissal stimulation, producing a positive gain modulation. The gain modulation is reversed by TRPA1 inhibitor HC-030031 and is absent in TRPA1 knockout mice. Similarly, in V1, TRPA1 activation increases the gain of direction and orientation selectivity. Linear decoding of V1 population activity confirms faster and more reliable encoding of visual signals under TRPA1 activation. Overall, our findings reveal a physiological role for TRPA1 in enhancing sensory signals in the mammalian cortex.

Space, time and number: common coding mechanisms and interactions between domains

Space, time and number are key dimensions that underlie how we perceive, identify and act within the environment. They are interconnected in our behaviour and brain. In this study, we examined interdependencies between these dimensions. To this end, left- and right-handed participants performed an object collision task that required space–time processing and arithmetic tests that involved number processing. Handedness of the participants influenced collision detection with left-handers being more accurate than right-handers, which is in line with the premise that hand preference guides individual differences as a result of sensorimotor experiences and distinct interhemispheric integration patterns. The data further showed that successful collision detection was a predictor for arithmetic achievement, at least in right-handers. These findings suggest that handedness plays a mediating role in binding information processing across domains, likely due to selective connectivity properties within the sensorimotor system that is guided by hemispheric lateralisation patterns.

Evidence accumulation during perceptual decision-making is sensitive to the dynamics of attentional selection

The ability to select and combine multiple sensory inputs in support of accurate decisions is a hallmark of adaptive behaviour. Attentional selection is often needed to prioritize task-relevant stimuli relative to irrelevant, potentially distracting stimuli. As most studies of perceptual decision-making to date have made use of task-relevant stimuli only, relatively little is known about how attention modulates decision making. To address this issue, we developed a novel 'integrated' decision-making task, in which participants judged the average direction of successive target motion signals while ignoring concurrent and spatially overlapping distractor motion signals. In two experiments that varied the role of attentional selection, we used regression to quantify the influence of target and distractor stimuli on behaviour. Using electroencephalography, we characterised the neural correlates of decision making, attentional selection and feature-specific responses to target and distractor signals. While targets strongly influenced perceptual decisions and associated neural activity, we also found that concurrent and spatially coincident distractors exerted a measurable bias on both behaviour and brain activity. Our findings suggest that attention operates as a real-time but imperfect filter during perceptual decision-making by dynamically modulating the contributions of task-relevant and irrelevant sensory inputs.

Perception of the difference between past and present stimulus: A rare orientation illusion may indicate incidental access to prediction error-like signals

A popular model for sensory processing, known as predictive coding, proposes that incoming signals are iteratively compared with top-down predictions along a hierarchical processing scheme. At each step, error signals arising from differences between actual input and prediction are forwarded and recurrently minimized by updating internal models to finally be “explained away”. However, the neuronal mechanisms underlying such computations and their limitations in processing speed are largely unknown. Further, it remains unclear at which step of cortical processing prediction errors are explained away, if at all. In the present study, human subjects briefly viewed the superposition of two orthogonally oriented gratings followed by abrupt removal of one orientation after either 33 or 200 milliseconds. Instead of strictly seeing the remaining orientation, observers report rarely but highly significantly an illusory percept of the arithmetic difference between previous and actual orientations. Previous findings in cats using the identical paradigm suggest that such difference signals are inherited from first steps of visual cortical processing. In light of early modeling accounts of predictive coding, in which visual neurons were interpreted as residual error detectors signaling the difference between actual input and its temporal prediction based on past input, our data may indicate continued access to residual errors. Such strategy permits time-critical perceptual decision making across a spectrum of competing internal signals up to the highest levels of processing. Thus, the occasional appearance of a prediction error-like illusory percept may uncover maintained flexibility at perceptual decision stages when subjects cope with highly dynamic and ambiguous visual stimuli.

Reward uncertainty attributes incentive value to reward proximal cues, while amphetamine sensitization reverts attention to more predictive reward distal cues

Slot-machine gambling incorporates numerous audiovisual cues prior to and during reward delivery (e.g. spinning wheels, flashing lights, celebratory sounds). Over time, these cues may motivate playing and even elicit cravings and relapse in those affected by gambling disorder. Animal studies suggest a heightened attraction to these cues despite diminished predictive ability under reward uncertainty, as evidenced by sign-tracking behavior in rats. Repeated amphetamine administration may also enhance the incentive value attributed to cues. Here, we explored the impact of reward uncertainty and prior amphetamine sensitization on the relative attractiveness and conditioned reinforcing properties of serial Pavlovian cues with different degrees of predictive and incentive value in rats. Animals were sensitized through repeated injections of amphetamine (1-4 mg/kg) or saline and then trained in a Pavlovian autoshaping task involving two sequential lever-auditory cue combinations (CS1, CS2) under Certain (100%-1) or Uncertain (50%-1-2-3) reward conditions. Subsequently, we evaluated the impact of acute amphetamine exposure on cue attraction. Our results suggest that Uncertainty alone enhanced attraction towards the reward-proximal CS2. However, combined sensitization and Uncertainty reversed cue preference relative to Uncertainty alone, enhancing attraction towards the more predictive reward-distal CS1. Both cues acquired conditioned reinforcing properties, despite the CS2 being otherwise ignored in all groups besides Uncertainty. However, combined sensitization and Uncertainty increased the reinforcing value of both cues and doubled the amount of interaction with the CS1 lever per presentation. Our results imply competitive mechanisms for attributing incentive value to gambling-related cues between reward uncertainty, prior amphetamine sensitization, and acute amphetamine administration.

Inhibition in selective attention

Our ability to focus on goal-relevant aspects of the environment is critically dependent on our ability to ignore or inhibit distracting information. One perspective is that distractor inhibition is under similar voluntary control as attentional facilitation of target processing. However, a rapidly growing body of research shows that distractor inhibition often relies on prior experience with the distracting information or other mechanisms that need not rely on active representation in working memory. Yet, how and when these different forms of inhibition are neurally implemented remains largely unclear. Here, we review findings from recent behavioral and neuroimaging studies to address this outstanding question. We specifically explore how experience with distracting information may change the processing of that information in the context of current predictive processing views of perception: by modulating a distractor's representation already in anticipation of the distractor, or after integration of top-down and bottom-up sensory signals. We also outline directions for future research necessary to enhance our understanding of how the brain filters out distracting information.

Neural dynamics of the attentional blink revealed by encoding orientation selectivity during rapid visual presentation

The human brain is inherently limited in the information it can make consciously accessible. When people monitor a rapid stream of visual items for two targets, they typically fail to see the second target if it occurs within 200–500 ms of the first, a phenomenon called the attentional blink (AB). The neural basis for the AB is poorly understood, partly because conventional neuroimaging techniques cannot resolve visual events displayed close together in time. Here we introduce an approach that characterises the precise effect of the AB on behaviour and neural activity. We employ multivariate encoding analyses to extract feature-selective information carried by randomly-oriented gratings. We show that feature selectivity is enhanced for correctly reported targets and suppressed when the same items are missed, whereas irrelevant distractor items are unaffected. The findings suggest that the AB involves both short- and long-range neural interactions between visual representations competing for access to consciousness.

People often fail to perceive the second of two brief visual targets, a phenomenon known as the attentional blink (AB). Here the authors modelled behaviour and brain activity to show that the AB arises from short- and long-range interactions between representations of elementary visual features.

Beat-based and Memory-based Temporal Expectations in Rhythm: Similar Perceptual Effects, Different Underlying Mechanisms

Predicting the timing of incoming information allows the brain to optimize information processing in dynamic environments. Behaviorally, temporal expectations have been shown to facilitate processing of events at expected time points, such as sounds that coincide with the beat in musical rhythm. Yet, temporal expectations can develop based on different forms of structure in the environment, not just the regularity afforded by a musical beat. Little is still known about how different types of temporal expectations are neurally implemented and affect performance. Here, we orthogonally manipulated the periodicity and predictability of rhythmic sequences to examine the mechanisms underlying beat-based and memory-based temporal expectations, respectively. Behaviorally and using EEG, we looked at the effects of beat-based and memory-based expectations on auditory processing when rhythms were task-relevant or task-irrelevant. At expected time points, both beat-based and memory-based expectations facilitated target detection and led to attenuation of P1 and N1 responses, even when expectations were task-irrelevant (unattended). For beat-based expectations, we additionally found reduced target detection and enhanced N1 responses for events at unexpected time points (e.g., off-beat), regardless of the presence of memory-based expectations or task relevance. This latter finding supports the notion that periodicity selectively induces rhythmic fluctuations in neural excitability and furthermore indicates that, although beat-based and memory-based expectations may similarly affect auditory processing of expected events, their underlying neural mechanisms may be different.

The Predictive Processing Model of EMDR

Eye Movement Desensitization and Reprocessing Therapy (EMDR) is an effective treatment for Post-traumatic Stress Disorder (PTSD). The Adaptive Information Processing Model (AIP) guides the development and practice of EMDR. The AIP postulates inadequately processed memory as the foundation of PTSD pathology. Predictive Processing postulates that the primary function of the brain is prediction that serves to anticipate the next moment of experience in order to resist the dissipative force of entropy thus facilitating continued survival. Memory is the primary substrate of prediction, and is optimized by an ongoing process of precision weighted prediction error minimization that refines prediction by updating the memories on which it is based. The Predictive Processing model of EMDR postulates that EMDR facilitates the predictive processing of traumatic memory by overcoming the bias against exploration and evidence accumulation. The EMDR protocol brings the traumatic memory into an active state of re-experiencing. Defensive responding and/or low sensory precision preclude evidence accumulation to test the predictions of the traumatic memory in the present. Sets of therapist guided eye movements repeatedly challenge the bias against evidence accumulation and compel sensory sampling of the benign present. Eye movements reset the theta rhythm organizing the flow of information through the brain, facilitating the deployment of both overt and covert attention, and the mnemonic search for associations. Sampling of sensation does not support the predictions of the traumatic memory resulting in prediction error that the brain then attempts to minimize. The net result is a restoration of the integrity of the rhythmic deployment of attention, a recalibration of sensory precision, and the updating (reconsolidation) of the traumatic memory. Thus one prediction of the model is a decrease in Attention Bias Variability, a core dysfunction in PTSD, following successful treatment with EMDR.

What is the effect of bodily illusions on corticomotoneuronal excitability? A systematic review

Background

This systematic review aimed to summarise and critically appraise the evidence for the effect of bodily illusions on corticomotoneuronal excitability.

Methods

Five databases were searched, with two independent reviewers completing study inclusion, risk of bias, transcranial magnetic stimulation (TMS) reporting quality, and data extraction. Included studies evaluated the effect of an illusion that altered perception of the body (and/or its movement) on excitability of motor circuitry in healthy, adult, human participants. Studies were required to: use TMS to measure excitability and/or inhibition; report quantitative outcomes (e.g., motor evoked potentials); compare the illusion to a control or active comparison condition; evaluate that an illusion had occurred (e.g., measured illusion strength/presence).

Results

Of 2,257 studies identified, 11 studies (14 experiments) were included, evaluating kinaesthetic illusions (n = 5), a rubber hand illusion (RHI) paradigm (n = 5), and a missing limb illusion (n = 1). Kinaesthetic illusions (induced via vision/tendon vibration) increased corticomotoneuronal excitability. Conflicting effects were found for traditional, visuotactile RHIs of a static hand. However, embodying a hand and then observing it move (“self-action”) resulted in decreased corticomotoneuronal excitability and increased silent period duration (a measure of Gamma-Aminobutynic acid [GABA]_B-mediated intracortical inhibition in motor cortex), with the opposite occurring (increased excitability, decreased inhibition) when the fake hand was not embodied prior to observing movement (“other-action”). Visuomotor illusions manipulating agency had conflicting results, but in the lower risk study, illusory agency over movement resulted in a relative decrease in corticomotoneuronal excitability. Last, an illusion of a missing limb reduced corticomotoneuronal excitability.

Conclusion

While evidence for the effect of bodily illusions on corticomotoneuronal excitability was limited (only 14 experiments) and had a high risk of bias, kinaesthetic illusions and illusions of embodying a hand (and seeing it move), had consistent effects. Future investigations into the role of embodiment and the illusion strength on corticomotoneuronal excitability and inhibition are warranted.