Feature-specific prediction errors for visual mismatch

Facial feedback manipulation influences the automatic detection of unexpected emotional body expressions

Unexpected or changing facial expressions are known to be able to engage more automatic processing than frequently occurring facial expressions, thereby inducing a neural differential wave response known as expression mismatch negativity (EMMN). Recent studies have shown that EMMN can be modulated by the observer's facial feedback (i.e., feedback from their own facial movements). A similar EMMN activity has been discovered for body expressions, but thus far only a few emotion types have been investigated. It is unknown whether the EMMNs evoked by body expressions can be influenced by facial feedback. To explore this question, we recorded EEG activity of 29 participants in the reverse oddball paradigm. Here two unexamined categories of body expressions were presented, happy and sad, placed in two paired stimulus sequences: in one the happy body was presented with a probability of 80% (standards) while the sad body was presented with a probability of 20% (deviants), and in the other the probabilities were reversed. The facial feedback was manipulated by different pen holding conditions (i.e., participants holding the pen with the teeth, lips, or nondominant hand). The nonparametric cluster permutation test revealed significant happy and sad body-related EMMN (bEMMN) activities. The happy-bEMMN were more negative than sad-bEMMN within the range of 100-150 ms. Additionally, the bEMMN amplitude of both emotions is modulated by the facial feedback conditions. These results expand the range of emotional types applicable to bEMMN and provide evidence for the validity of the facial feedback hypothesis across emotional carriers.

The empirical status of predictive coding and active inference

Research on predictive processing models has focused largely on two specific algorithmic theories: Predictive Coding for perception and Active Inference for decision-making. While these interconnected theories possess broad explanatory potential, they have only recently begun to receive direct empirical evaluation. Here, we review recent studies of Predictive Coding and Active Inference with a focus on evaluating the degree to which they are empirically supported. For Predictive Coding, we find that existing empirical evidence offers modest support. However, some positive results can also be explained by alternative feedforward (e.g., feature detection-based) models. For Active Inference, most empirical studies have focused on fitting these models to behavior as a means of identifying and explaining individual or group differences. While Active Inference models tend to explain behavioral data reasonably well, there has not been a focus on testing empirical validity of active inference theory per se, which would require formal comparison to other models (e.g., non-Bayesian or model-free reinforcement learning models). This review suggests that, while promising, a number of specific research directions are still necessary to evaluate the empirical adequacy and explanatory power of these algorithms.

A multimodal cortical network of sensory expectation violation revealed by fMRI

The brain is subjected to multi-modal sensory information in an environment governed by statistical dependencies. Mismatch responses (MMRs), classically recorded with EEG, have provided valuable insights into the brain's processing of regularities and the generation of corresponding sensory predictions. Only few studies allow for comparisons of MMRs across multiple modalities in a simultaneous sensory stream and their corresponding cross-modal context sensitivity remains unknown. Here, we used a tri-modal version of the roving stimulus paradigm in fMRI to elicit MMRs in the auditory, somatosensory and visual modality. Participants (N = 29) were simultaneously presented with sequences of low and high intensity stimuli in each of the three senses while actively observing the tri-modal input stream and occasionally reporting the intensity of the previous stimulus in a prompted modality. The sequences were based on a probabilistic model, defining transition probabilities such that, for each modality, stimuli were more likely to repeat (p = .825) than change (p = .175) and stimulus intensities were equiprobable (p = .5). Moreover, each transition was conditional on the configuration of the other two modalities comprising global (cross-modal) predictive properties of the sequences. We identified a shared mismatch network of modality general inferior frontal and temporo-parietal areas as well as sensory areas, where the connectivity (psychophysiological interaction) between these regions was modulated during mismatch processing. Further, we found deviant responses within the network to be modulated by local stimulus repetition, which suggests highly comparable processing of expectation violation across modalities. Moreover, hierarchically higher regions of the mismatch network in the temporo-parietal area around the intraparietal sulcus were identified to signal cross-modal expectation violation. With the consistency of MMRs across audition, somatosensation and vision, our study provides insights into a shared cortical network of uni- and multi-modal expectation violation in response to sequence regularities.

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.

The automatic detection of unexpected emotion and neutral body postures: A visual mismatch negativity study

The ability to automatically detect emotional changes in the environment is crucial for social interaction. In the visual system, expression-related mismatch negativity (EMMN) reflects the automatic processing of emotional changes in facial expression. However, body postures also carry visual emotional information that can be recognized effectively and processed automatically, although their processing mechanism remains unknown. In this study, the reverse oddball paradigm was used to investigate the mismatch responses of unexpected fear and neutral body postures. The nonparametric cluster permutation test revealed significant fear and neutral visual mismatch negativity (vMMN) activities, and the fear-related vMMN was enhanced prior (130-230 ms) to the neutral vMMN (180-230 ms). The body-sensitive N190 component may partially account for the vMMN obtained in this study. The fearful body posture evoked a greater N190 response over the neutral body, and amplitudes of N190 were more negative in the deviant condition than the standard condition. Additionally, the body-related visual mismatch oscillatory responses were associated with enhancement of the alpha band oscillation, especially for the fearful body posture. These results expanded the applicable scope of body posture cues corresponding to mismatch signals, objectively defined the electrophysiological activities evoked, and revealed the processing bias toward negative emotion.

Visual mismatch responses index surprise signalling but not expectation suppression

The ability to distinguish between commonplace and unusual sensory events is critical for efficient learning and adaptive behaviour. This has been investigated using oddball designs in which sequences of often-appearing (i.e., expected) stimuli are interspersed with rare (i.e., surprising) deviants. Resulting differences in electrophysiological responses following surprising compared to expected stimuli are known as visual mismatch responses (VMRs). VMRs are thought to index co-occurring contributions of stimulus repetition effects, expectation suppression (that occurs when one's expectations are fulfilled), and expectation violation (i.e., surprise) responses; however, these different effects have been conflated in existing oddball designs. To better isolate and quantify effects of expectation suppression and surprise, we adapted an oddball design based on Fast Periodic Visual Stimulation (FPVS) that controls for stimulus repetition effects. We recorded electroencephalography (EEG) while participants (N = 48) viewed stimulation sequences in which a single face identity was periodically presented at 6 Hz. Critically, one of two different face identities (termed oddballs) appeared as every 7th image throughout the sequence. The presentation probabilities of each oddball image within a sequence varied between 10 and 90%, such that participants could form expectations about which oddball face identity was more likely to appear within each sequence. We also included 'expectation neutral' 50% probability sequences, whereby consistently biased expectations would not be formed for either oddball face identity. We found that VMRs indexed surprise responses, and effects of expectation suppression were absent. That is, ERPs were more negative-going at occipitoparietal electrodes for surprising compared to neutral oddballs, but did not differ between expected and neutral oddballs. Surprising oddball-evoked ERPs were also highly similar across the 10-40% appearance probability conditions. Our findings indicate that VMRs which are not accounted for by repetition effects are best described as an all-or-none surprise response, rather than a minimisation of prediction error responses associated with expectation suppression.

Unreliable feedback deteriorates information processing in primary visual cortex

It is well-established that increased sensory uncertainty impairs perceptual decision-making and leads to degraded neural stimulus representations. Recently, we also showed that providing unreliable feedback to choices leads to changes in perceptual decision-making similar to those of increased stimulus noise: A deterioration in objective task performance, a decrease in subjective confidence and a lower reliance on sensory information for perceptual inference. To investigate the neural basis of such feedback-based changes in perceptual decision-making, in the present study, two groups of healthy human participants (n = 15 each) performed a challenging visual orientation discrimination task while undergoing functional magnetic resonance imaging (fMRI). Critically, one group received reliable feedback regarding their task performance in an intervention phase, whereas the other group correspondingly received unreliable feedback - thereby keeping stimulus information constant. The effects of feedback reliability on performance and stimulus representation in the primary visual cortex (V1) were studied by comparing the pre- and post-intervention test phases between the groups. Compared to participants who received reliable feedback, those receiving unreliable feedback showed a decline in task performance that was paralleled by reduced distinctness of fMRI response patterns in V1. These results show that environmental uncertainty can affect perceptual inference at the earliest cortical processing stages.

Social training reconfigures prediction errors to shape Self-Other boundaries

Selectively attributing beliefs to specific agents is core to reasoning about other people and imagining oneself in different states. Evidence suggests humans might achieve this by simulating each other’s computations in agent-specific neural circuits, but it is not known how circuits become agent-specific. Here we investigate whether agent-specificity adapts to social context. We train subjects on social learning tasks, manipulating the frequency with which self and other see the same information. Training alters the agent-specificity of prediction error (PE) circuits for at least 24 h, modulating the extent to which another agent’s PE is experienced as one’s own and influencing perspective-taking in an independent task. Ventromedial prefrontal myelin density, indexed by magnetisation transfer, correlates with the strength of this adaptation. We describe a frontotemporal learning network, which exploits relationships between different agents’ computations. Our findings suggest that Self-Other boundaries are learnable variables, shaped by the statistical structure of social experience.

The human brain can simulate other people’s mental processes with Self-specific and Other-specific neural circuits, but it is not known how these circuits emerge. Here, the authors show that these circuits adapt to social experience, to determine whether a computation is attributed to Self or Other.

Cortical mapping of mismatch responses to independent acoustic features

Predictive coding is an influential theory of neural processing underlying perceptual inference. However, it is unknown to what extent prediction violations of different sensory features are mediated in different regions in auditory cortex, with different dynamics, and by different mechanisms. This study investigates the neural responses to synthesized acoustic syllables, which could be expected or unexpected, along several features. By using electrocorticography (ECoG) in rat auditory cortex (subjects: adult female Wistar rats with normal hearing), we aimed at mapping regional differences in mismatch responses to different stimulus features. Continuous streams of morphed syllables formed roving oddball sequences in which each stimulus was repeated several times (thereby forming a standard) and subsequently replaced with a deviant stimulus which differed from the standard along one of several acoustic features: duration, pitch, interaural level differences (ILD), or consonant identity. Each of these features could assume one of several different levels, and the resulting change from standard to deviant could be larger or smaller. The deviant stimuli were then repeated to form new standards. We analyzed responses to the first repetition of a new stimulus (deviant) and its last repetition in a stimulus train (standard). For the ECoG recording, we implanted urethane-anaesthetized rats with 8 × 8 surface electrode arrays covering a 3 × 3 mm cortical patch encompassing primary and higher-order auditory cortex. We identified the response topographies and latencies of population activity evoked by acoustic stimuli in the rat auditory regions, and mapped their sensitivity to expectation violations along different acoustic features. For all features, the responses to deviant stimuli increased in amplitude relative to responses to standard stimuli. Deviance magnitude did not further modulate these mismatch responses. Mismatch responses to different feature violations showed a heterogeneous distribution across cortical areas, with no evidence for systematic topographic gradients for any of the tested features. However, within rats, the spatial distribution of mismatch responses varied more between features than the spatial distribution of tone-evoked responses. This result supports the notion that prediction error signaling along different stimulus features is subserved by different cortical populations, albeit with substantial heterogeneity across individuals.

Combined expectancies: the role of expectations for the coding of salient bottom-up signals

The visual system forms predictions about upcoming visual features based on previous visual experiences. Such predictions impact on current perception, so that expected stimuli can be detected faster and with higher accuracy. A key question is how these predictions are formed and on which levels of processing they arise. Particularly, predictions could be formed on early levels of processing, where visual features are represented separately, or might require higher levels of processing, with predictions formed based on full object representations that involve combinations of visual features. In four experiments, the present study investigated whether the visual system forms joint prediction errors or whether expectations about different visual features such as color and orientation are formed independently. The first experiment revealed that task-irrelevant and implicitly learned expectations were formed independently when the features were separately bound to different objects. In a second experiment, no evidence for a mutual influence of both types of task-irrelevant and implicitly formed feature expectations was observed, although both visual features were assigned to the same objects. A third experiment confirmed the findings of the previous experiments for explicitly rather than implicitly formed expectations. Finally, no evidence for a mutual influence of different feature expectations was observed when features were assigned to a single centrally presented object. Overall, the present results do not support the view that object feature binding generates joint feature-based expectancies of different object features. Rather, the results suggest that expectations for color and orientation are processed and resolved independently at the feature level.

Out of Focus: Facial Feedback Manipulation Modulates Automatic Processing of Unattended Emotional Faces

Facial expressions provide information about an individual's intentions and emotions and are thus an important medium for nonverbal communication. Theories of embodied cognition assume that facial mimicry and resulting facial feedback plays an important role in the perception of facial emotional expressions. Although behavioral and electrophysiological studies have confirmed the influence of facial feedback on the perception of facial emotional expressions, the influence of facial feedback on the automatic processing of such stimuli is largely unexplored. The automatic processing of unattended facial expressions can be investigated by visual expression-related MMN. The expression-related MMN reflects a differential ERP of automatic detection of emotional changes elicited by rarely presented facial expressions (deviants) among frequently presented facial expressions (standards). In this study, we investigated the impact of facial feedback on the automatic processing of facial expressions. For this purpose, participants (n = 19) performed a centrally presented visual detection task while neutral (standard), happy, and sad faces (deviants) were presented peripherally. During the task, facial feedback was manipulated by different pen holding conditions (holding the pen with teeth, lips, or nondominant hand). Our results indicate that automatic processing of facial expressions is influenced and thus dependent on the own facial feedback.