Attention sharpens the distinction between expected and unexpected percepts in the visual brain

Scene context and attention independently facilitate MEG decoding of object category

Many of the objects we encounter in our everyday environments would be hard to recognize without any expectations about these objects. For example, a distant silhouette may be perceived as a car because we expect objects of that size, positioned on a road, to be cars. Reflecting the influence of such expectations on visual processing, neuroimaging studies have shown that when objects are poorly visible, expectations derived from scene context facilitate the representations of these objects in visual cortex from around 300 ms after scene onset. The current magnetoencephalography (MEG) study tested whether this facilitation occurs independently of attention and task relevance. Participants viewed degraded objects alone or within scene context while they either attended the scenes (attended condition) or the fixation cross (unattended condition), also temporally directing attention away from the scenes. Results showed that at 300 ms after stimulus onset, multivariate classifiers trained to distinguish clearly visible animate vs inanimate objects generalized to distinguish degraded objects in scenes better than degraded objects alone, despite the added clutter of the scene background. Attention also modulated object representations at this latency, with better category decoding in the attended than the unattended condition. The modulatory effects of context and attention were independent of each other. Finally, data from the current study and a previous study were combined (N = 51) to provide a more detailed temporal characterization of contextual facilitation. These results extend previous work by showing that facilitatory scene-object interactions are independent of the specific task performed on the visual input.

Confidence and second-order errors in cortical circuits

Minimization of cortical prediction errors has been considered a key computational goal of the cerebral cortex underlying perception, action, and learning. However, it is still unclear how the cortex should form and use information about uncertainty in this process. Here, we formally derive neural dynamics that minimize prediction errors under the assumption that cortical areas must not only predict the activity in other areas and sensory streams but also jointly project their confidence (inverse expected uncertainty) in their predictions. In the resulting neuronal dynamics, the integration of bottom-up and top-down cortical streams is dynamically modulated based on confidence in accordance with the Bayesian principle. Moreover, the theory predicts the existence of cortical second-order errors, comparing confidence and actual performance. These errors are propagated through the cortical hierarchy alongside classical prediction errors and are used to learn the weights of synapses responsible for formulating confidence. We propose a detailed mapping of the theory to cortical circuitry, discuss entailed functional interpretations, and provide potential directions for experimental work.

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.

Disrupted interoceptive awareness by auditory distractor: Difficulty inferring the internal bodily states?

Recent studies have associated interoceptive awareness, the perception of internal bodily sensations, with a predictive mechanism of perception across all sensory modalities. According to the framework, volitional attention plays a pivotal role in interoceptive awareness by prioritizing interoceptive sensations over exteroceptive ones. Consequently, it is hypothesized that the presence of irrelevant stimuli would disrupt the attentional modulation and interoceptive awareness, which remains untested. In this study, we investigated if interoceptive awareness is diminished by unrelated auditory distractors to validate the proposed perceptual framework. A total of 30 healthy human volunteers performed the heartbeat counting task both with and without auditory distractors. Additionally, we measured participant's psychophysiological traits related to interoception, including the high-frequency component of heart rate variability (HF-HRV) and trait interoceptive sensibility. The results showed that interoceptive accuracy, confidence, and heartbeat intensity decreased in the presence of distractor sound. Moreover, individuals with higher HF-HRV and a greater tendency to worry about bodily states experienced a more pronounced distractor effect on interoceptive awareness. These results provide support for the perceptual mechanism of interoceptive awareness in terms of the predictive process, highlighting the impact of relative precision across interoceptive and exteroceptive signals on perceptual experiences.

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.

Neural representation of gestalt grouping and attention effect in human visual cortex

BACKGROUND

The brain aggregates meaningless local sensory elements to form meaningful global patterns in a process called perceptual grouping. Current brain imaging studies have found that neural activities in V1 are modulated during visual grouping. However, how grouping is represented in each of the early visual areas, and how attention alters these representations, is still unknown.

NEW METHOD

We adopted MVPA to decode the specific content of perceptual grouping by comparing neural activity patterns between gratings and dot lattice stimuli which can be grouped with proximity law. Furthermore, we quantified the grouping effect by defining the strength of grouping, and assessed the effect of attention on grouping.

RESULTS

We found that activity patterns to proximity grouped stimuli in early visual areas resemble these to grating stimuli with the same orientations. This similarity exists even when there is no attention focused on the stimuli. The results also showed a progressive increase of representational strength of grouping from V1 to V3, and attention modulation to grouping is only significant in V3 among all the visual areas.

COMPARISON WITH EXISTING METHODS

Most of the previous work on perceptual grouping has focused on how activity amplitudes are modulated by grouping. Using MVPA, the present work successfully decoded the contents of neural activity patterns corresponding to proximity grouping stimuli, thus shed light on the availability of content-decoding approach in the research on perceptual grouping.

CONCLUSIONS

Our work found that the content of the neural activity patterns during perceptual grouping can be decoded in the early visual areas under both attended and unattended task, and provide novel evidence that there is a cascade processing for proximity grouping through V1 to V3. The strength of grouping was larger in V3 than in any other visual areas, and the attention modulation to the strength of grouping was only significant in V3 among all the visual areas, implying that V3 plays an important role in proximity grouping.

Sound category habituation requires task-relevant attention

Introduction

Processing the wealth of sensory information from the surrounding environment is a vital human function with the potential to develop learning, advance social interactions, and promote safety and well-being.

Methods

To elucidate underlying processes governing these activities we measured neurophysiological responses to patterned stimulus sequences during a sound categorization task to evaluate attention effects on implicit learning, sound categorization, and speech perception. Using a unique experimental design, we uncoupled conceptual categorical effects from stimulus-specific effects by presenting categorical stimulus tokens that did not physically repeat.

Results

We found effects of implicit learning, categorical habituation, and a speech perception bias when the sounds were attended, and the listeners performed a categorization task (task-relevant). In contrast, there was no evidence of a speech perception bias, implicit learning of the structured sound sequence, or repetition suppression to repeated within-category sounds (no categorical habituation) when participants passively listened to the sounds and watched a silent closed-captioned video (task-irrelevant). No indication of category perception was demonstrated in the scalp-recorded brain components when participants were watching a movie and had no task with the sounds.

Discussion

These results demonstrate that attention is required to maintain category identification and expectations induced by a structured sequence when the conceptual information must be extracted from stimuli that are acoustically distinct. Taken together, these striking attention effects support the theoretical view that top-down control is required to initiate expectations for higher level cognitive processing.

Relative fluency (unfelt vs felt) in active inference

For a growing number of researchers, it is now accepted that the brain is a predictive organ that predicts the content of the sensorium and crucially the precision of-or confidence in-its own predictions. In order to predict the precision of its predictions, the brain has to infer the reliability of its own beliefs. This means that our brains have to recognise the precision of their predictions or, at least, their accuracy. In this paper, we argue that fluency is product of this recognition process. In short, to recognise fluency is to infer that we have a precise 'grip' on the unfolding processes that generate our sensations. More specifically, we propose that it is changes in fluency - from unfelt to felt - that are both recognised and realised when updating predictions about precision. Unfelt fluency orients attention to unpredicted sensations, while felt fluency supervenes on-and contextualises-unfelt fluency; thereby rendering certain attentional processes, phenomenologically opaque. As such, fluency underwrites the precision we place in our predictions and therefore acts upon our perceptual inferences. Hence, the causes of conscious subjective inference have unconscious perceptual precursors.

Testing cognitive theories with multivariate pattern analysis of neuroimaging data

Multivariate pattern analysis (MVPA) has emerged as a powerful method for the analysis of functional magnetic resonance imaging, electroencephalography and magnetoencephalography data. The new approaches to experimental design and hypothesis testing afforded by MVPA have made it possible to address theories that describe cognition at the functional level. Here we review a selection of studies that have used MVPA to test cognitive theories from a range of domains, including perception, attention, memory, navigation, emotion, social cognition and motor control. This broad view reveals properties of MVPA that make it suitable for understanding the 'how' of human cognition, such as the ability to test predictions expressed at the item or event level. It also reveals limitations and points to future directions.

Neural correlates of visual and tactile path integration and their task related modulation

Self-motion induces sensory signals that allow to determine travel distance (path integration). For veridical path integration, one must distinguish self-generated from externally induced sensory signals. Predictive coding has been suggested to attenuate self-induced sensory responses, while task relevance can reverse the attenuating effect of prediction. But how is self-motion processing affected by prediction and task demands, and do effects generalize across senses? In this fMRI study, we investigated visual and tactile self-motion processing and its modulation by task demands. Visual stimuli simulated forward self-motion across a ground plane. Tactile self-motion stimuli were delivered by airflow across the subjects' forehead. In one task, subjects replicated a previously observed distance (Reproduction/Active; high behavioral demand) of passive self-displacement (Reproduction/Passive). In a second task, subjects travelled a self-chosen distance (Self/Active; low behavioral demand) which was recorded and played back to them (Self/Passive). For both tasks and sensory modalities, Active as compared to Passive trials showed enhancement in early visual areas and suppression in higher order areas of the inferior parietal lobule (IPL). Contrasting high and low demanding active trials yielded supramodal enhancement in the anterior insula. Suppression in the IPL suggests this area to be a comparator of sensory self-motion signals and predictions thereof.

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.

Top-down specific preparatory activations for selective attention and perceptual expectations

Proactive cognition brain models are mainstream nowadays. Within these, preparation is understood as an endogenous, top-down function that takes place prior to the actual perception of a stimulus and improves subsequent behavior. Neuroimaging has shown the existence of such preparatory activity separately in different cognitive domains, however no research to date has sought to uncover their potential similarities and differences. Two of these, often confounded in the literature, are Selective Attention (information relevance) and Perceptual Expectation (information probability). We used EEG to characterize the mechanisms that pre-activate specific contents in Attention and Expectation. In different blocks, participants were cued to the relevance or to the probability of target categories, faces vs. names, in a gender discrimination task. Multivariate Pattern (MVPA) and Representational Similarity Analyses (RSA) during the preparation window showed that both manipulations led to a significant, ramping-up prediction of the relevant or expected target category. However, classifiers trained with data from one condition did not generalize to the other, indicating the existence of unique anticipatory neural patterns. In addition, a Canonical Template Tracking procedure showed that there was stronger anticipatory perceptual reinstatement for relevance than for expectation blocks. Overall, the results indicate that preparation during attention and expectation acts through distinguishable neural mechanisms. These findings have important implications for current models of brain functioning, as they are a first step towards characterizing and dissociating the neural mechanisms involved in top-down anticipatory processing.

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.

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.

Dissociable effects of attention and expectation on perceptual sensitivity to action-outcomes

Self-generated sensations evoke attenuated neural response - physiological attenuation - and is perceived with less intensity - perceptual attenuation. This phenomenon is referred as sensory attenuation and is proposed to reflect the silencing of predicted sensations. The present study aimed to investigate the independent contribution of expectation and attention on sensory attenuation. The expectation associated with the stimulus feature and the focus of attention was manipulated independently by orthogonal cues. We found pronounced sensory attenuation at the unattended location when the stimulus was self-generated (Experiment 1). When the stimulus was externally-generated (Experiment 2), sensory attenuation was observed at the attended location. Sensory attenuation of expected action-outcome was not observed when the attention cue was uninformative (Experiment 3A). The findings corroborate the claim from Bayesian models that attention mediates sensory attenuation. The results also highlight the paradoxes in Bayesian proposals of perception-action interaction.

Reward learning and statistical learning independently influence attentional priority of salient distractors in visual search

Existing research demonstrates different ways in which attentional prioritization of salient nontarget stimuli is shaped by prior experience: Reward learning renders signals of high-value outcomes more likely to capture attention than signals of low-value outcomes, whereas statistical learning can produce attentional suppression of the location in which salient distractor items are likely to appear. The current study combined manipulations of the value and location associated with salient distractors in visual search to investigate whether these different effects of selection history operate independently or interact to determine overall attentional prioritization of salient distractors. In Experiment 1, high-value and low-value distractors most frequently appeared in the same location; in Experiment 2, high-value and low-value distractors typically appeared in distinct locations. In both experiments, effects of distractor value and location were additive, suggesting that attention-promoting effects of value and attention-suppressing effects of statistical location-learning independently modulate overall attentional priority. Our findings are consistent with a view that sees attention as mediated by a common priority map that receives and integrates separate signals relating to physical salience and value, with signal suppression based on statistical learning determined by physical salience, but not incentive salience.

Neuroscience and architecture: Modulating behavior through sensorimotor responses to the built environment

As we move through the world, natural and built environments implicitly guide behavior by appealing to certain sensory and motor dynamics. This process can be motivated by automatic attention to environmental features that resonate with specific sensorimotor responses. This review aims at providing a psychobiological framework describing how environmental features can lead to automated sensorimotor responses through defined neurophysiological mechanisms underlying attention. Through the use of automated processes in subsets of cortical structures, the goal of this framework is to describe on a neuronal level the functional link between the designed environment and sensorimotor responses. By distinguishing between environmental features and sensorimotor responses we elaborate on how automatic behavior employs the environment for sensorimotor adaptation. This is realized through a thalamo-cortical network integrating environmental features with motor aspects of behavior. We highlight the underlying transthalamic transmission from an Enactive and predictive perspective and review recent studies that effectively modulated behavior by systematically manipulating environmental features. We end by suggesting a promising combination of neuroimaging and computational analysis for future studies.

Hippocampal representations switch from errors to predictions during acquisition of predictive associations

We constantly exploit the statistical regularities in our environment to help guide our perception. The hippocampus has been suggested to play a pivotal role in both learning environmental statistics, as well as exploiting them to generate perceptual predictions. However, it is unclear how the hippocampus balances encoding new predictive associations with the retrieval of existing ones. Here, we present the results of two high resolution human fMRI studies (N = 24 for both experiments) directly investigating this. Participants were exposed to auditory cues that predicted the identity of an upcoming visual shape (with 75% validity). Using multivoxel decoding analysis, we find that the hippocampus initially preferentially represents unexpected shapes (i.e., those that violate the cue regularities), but later switches to representing the cue-predicted shape regardless of which was actually presented. These findings demonstrate that the hippocampus is involved both acquiring and exploiting predictive associations, and is dominated by either errors or predictions depending on whether learning is ongoing or complete.

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.

Identification of Neuropathic Pain Severity based on Linear and Non-Linear EEG Features

The lack of an integral characterization of chronic neuropathic pain (NP) has led to pharmacotherapy mismanagement and has hindered advances in clinical trials. In this study, we attempted to identify chronic NP by fusing psychometric (based on the Brief Inventory of Pain - BIP), and both linear and non-linear electroencephalographic (EEG) features. For this purpose, 35 chronic NP patients were recruited voluntarily. All the volunteers answered the BIP; and additionally, 22 EEG channels positioned in accordance with the 10/20 international system were registered for 10 minutes at resting state: 5 minutes with eyes open and 5 minutes with eyes closed. EEG Signals were sampled at 250 Hz within a bandwidth between 0.1 and 100 Hz. As linear features, absolute band power was obtained per clinical frequency band: delta (0.1~4 Hz), theta (4~8 Hz), alpha (8~12 Hz), beta (12~30 Hz) and gamma (30~100 Hz); considering five regions: prefrontal, frontal, central, parietal and occipital. As non-linear features, approximate entropy was calculated per channel and per clinical frequency band with addition of the broadband (0.1~100 Hz). Resulting feature vectors were grouped in line with the BIP outcome. Three groups were considered: low, moderate, and high pain. Finally, BIP-EEG patterns were classified in those three classes, achieving 96% accuracy. This result improves a previous work of a SVM classifier that used exclusively linear EEG features and showed an accuracy between 87% and 90% per class to predict central NP after spinal cord injury.

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.

Interoceptive sensibility predicts the ability to infer others' emotional states

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

Procedural Control Versus Resources as Potential Origins of Human Hyper Selectivity

In the current review, we argue that experimental results usually interpreted as evidence for cognitive resource limitations could also reflect functional necessities of human information processing. First, we point out that selective processing of only specific features, objects, or locations at each moment in time allows humans to monitor the success and failure of their own overt actions and covert cognitive procedures. We then proceed to show how certain instances of selectivity are at odds with commonly assumed resource limitations. Next, we discuss examples of seemingly automatic, resource-free processing that challenge the resource view but can be easily understood from the functional perspective of monitoring cognitive procedures. Finally, we suggest that neurophysiological data supporting resource limitations might actually reflect mechanisms of how procedural control is implemented in the brain.

Attention modulates repetition effects in a context of low periodicity

Stimulus repetition can result in a reduction in neural responses (i.e., repetition suppression) in neuroimaging studies. Predictive coding models of perception postulate that this phenomenon largely reflects the top-down attenuation of prediction errors. Electroencephalography research further demonstrated that repetition effects consist of sequentially ordered attention-independent and attention-dependent components in a context of high periodicity. However, the statistical structure of our auditory environment is richer than that of a fixed pattern. It remains unclear if the attentional modulation of repetition effects can be generalised to a setting which better represents the nature of our auditory environment. Here we used electroencephalography to investigate whether the attention-independent and attention-dependent components of repetition effects previously described in the auditory modality remain in a context of low periodicity where temporary disruption might be absent/present. Participants were presented with repetition trains of various lengths, with/without temporary disruptions. We found attention-independent and attention-dependent repetition effects on, respectively, the P2 and P3a event-related potential components. This pattern of results is in line with previous research, confirming that the attenuation of prediction errors upon stimulus repetition is first registered regardless of attentional state before further attenuation of attended but not unattended prediction errors takes place. However, unlike previous reports, these effects manifested on later components. This divergence from previous studies is discussed in terms of the possible contribution of contextual factors.

The Microstructure of Attentional Control in the Dorsal Attention Network

The top-down control of attention involves command signals arising chiefly in the dorsal attention network (DAN) in frontal and parietal cortex and propagating to sensory cortex to enable the selective processing of incoming stimuli based on their behavioral relevance. Consistent with this view, the DAN is active during preparatory (anticipatory) attention for relevant events and objects, which, in vision, may be defined by different stimulus attributes including their spatial location, color, motion, or form. How this network is organized to support different forms of preparatory attention to different stimulus attributes remains unclear. We propose that, within the DAN, there exist functional microstructures (patterns of activity) specific for controlling attention based on the specific information to be attended. To test this, we contrasted preparatory attention to stimulus location (spatial attention) and to stimulus color (feature attention), and used multivoxel pattern analysis to characterize the corresponding patterns of activity within the DAN. We observed different multivoxel patterns of BOLD activation within the DAN for the control of spatial attention (attending left vs. right) and feature attention (attending red vs. green). These patterns of activity for spatial and feature attentional control showed limited overlap with each other within the DAN. Our findings thus support a model in which the DAN has different functional microstructures for distinctive forms of top-down control of visual attention.

Evaluating the evidence for expectation suppression in the visual system

Reports of expectation suppression have shaped the development of influential predictive coding-based theories of visual perception. However recent work has highlighted confounding factors that may mimic or inflate expectation suppression effects. In this review, we describe four confounds that are prevalent across experiments that tested for expectation suppression: effects of surprise, attention, stimulus repetition and adaptation, and stimulus novelty. With these confounds in mind we then critically review the evidence for expectation suppression across probabilistic cueing, statistical learning, oddball, action-outcome learning and apparent motion designs. We found evidence for expectation suppression within a specific subset of statistical learning designs that involved weeks of sequence learning prior to neural activity measurement. Across other experimental contexts, whereby stimulus appearance probabilities were learned within one or two testing sessions, there was inconsistent evidence for genuine expectation suppression. We discuss how an absence of expectation suppression could inform models of predictive processing, repetition suppression and perceptual decision-making. We also provide suggestions for designing experiments that may better test for expectation suppression in future work.

Effects of a Brief Mindfulness-Based Attentional Intervention on Threat-Related Perceptual Decision-Making

Objectives

Threat-related cues and contexts facilitate perceptual decision-making, yet it is unclear whether this threat-driven tuning of perceptual decision-making is modifiable by top-down attentional control. Since state and dispositional mindfulness are linked to improved attentional control, we examined whether these factors assist the use of prior knowledge to detect threatening stimuli.

Methods

Participants were randomly assigned to a brief mindfulness-based intervention (N=32) or a physics lecture audio recording (N=31) and then asked to perform a task in which they used threatening and neutral cues to discriminate between threatening and neutral faces.

Results

Results showed that threatening cues led to faster and more sensitive perceptual decision-making, specifically for threatening faces. Furthermore, higher levels of dispositional mindfulness were associated with improved ability to use cues to discriminate between threatening and neutral stimuli in the group that underwent a brief mindfulness induction but not in the control group.

Conclusions

Our findings highlight how top-down attention-related dispositions and strategies can influence our ability to detect threats in our environment.

Can expectation suppression be explained by reduced attention to predictable stimuli?

The expectation-suppression effect - reduced stimulus-evoked responses to expected stimuli - is widely considered to be an empirical hallmark of reduced prediction errors in the framework of predictive coding. Here we challenge this notion by proposing that that expectation suppression could be explained by a reduced attention effect. Specifically, we argue that reduced responses to predictable stimuli can also be explained by a reduced saliency-driven allocation of attention. We base our discussion mainly on findings in the visual cortex and propose that resolving this controversy requires the assessment of qualitative differences between the ways in which attention and surprise enhance brain responses.

Both contextual regularity and selective attention affect the reduction of precision-weighted prediction errors but in distinct manners

Predictive coding model of perception postulates that the primary objective of the brain is to infer the causes of sensory inputs by reducing prediction errors (i.e., the discrepancy between expected and actual information). Moreover, prediction errors are weighted by their precision (i.e., inverse variance), which quantifies the degree of certainty about the variables. There is accumulating evidence that the reduction of precision-weighted prediction errors can be affected by contextual regularity (as an external factor) and selective attention (as an internal factor). However, it is unclear whether the two factors function together or separately. Here we used electroencephalography (EEG) to examine the putative interaction of contextual regularity and selective attention on this reduction process. Participants were presented with pairs of regular and irregular quartets in attended and unattended conditions. We found that contextual regularity and selective attention independently modulated the N1/MMN where the repetition effect was absent. On the P2, the two factors respectively interacted with the repetition effect without interacting with each other. The results showed that contextual regularity and selective attention likely affect the reduction of precision-weighted prediction errors in distinct manners. While contextual regularity finetunes our efficiency at reducing precision-weighted prediction errors, selective attention seems to modulate the reduction process following the Matthew effect of accumulated advantage.

Individual differences in the tendency to see the expected

Prior knowledge has been shown to facilitate the incorporation of visual stimuli into awareness. We adopted an individual differences approach to explore whether a tendency to 'see the expected' is general or method-specific. We administered a binocular rivalry task and manipulated selective attention, as well as induced expectations via predictive context, self-generated imagery, expectancy cues, and perceptual priming. Most prior manipulations led to a facilitated awareness of the biased percept in binocular rivalry, whereas strong signal primes led to a suppressed awareness, i.e., adaptation. Correlations and factor analysis revealed that the facilitatory effect of priors on visual awareness is closely related to attentional control. We also investigated whether expectation-based biases predict perceptual abilities. Adaptation to strong primes predicted improved naturalistic change detection and the facilitatory effect of weak primes predicted the experience of perceptual anomalies. Taken together, our results indicate that the facilitatory effect of priors may be underpinned by an attentional mechanism but the tendency to 'see the expected' is method-specific.

The influence of subcortical shortcuts on disordered sensory and cognitive processing

The very earliest stages of sensory processing have the potential to alter how we perceive and respond to our environment. These initial processing circuits can incorporate subcortical regions, such as the thalamus and brainstem nuclei, which mediate complex interactions with the brain's cortical processing hierarchy. These subcortical pathways, many of which we share with other animals, are not merely vestigial but appear to function as 'shortcuts' that ensure processing efficiency and preservation of vital life-preserving functions, such as harm avoidance, adaptive social interactions and efficient decision-making. Here, we propose that functional interactions between these higher-order and lower-order brain areas contribute to atypical sensory and cognitive processing that characterizes numerous neuropsychiatric disorders.

Real-world expectations and their affective value modulate object processing

It is well known that expectations influence how we perceive the world. Yet the neural mechanisms underlying this process remain unclear. Studies about the effects of prior expectations have focused so far on artificial contingencies between simple neutral cues and events. Real-world expectations are however often generated from complex associations between contexts and objects learned over a lifetime. Additionally, these expectations may contain some affective value and recent proposals present conflicting hypotheses about the mechanisms underlying affect in predictions. In this study, we used fMRI to investigate how object processing is influenced by realistic context-based expectations, and how affect impacts these expectations. First, we show that the precuneus, the inferotemporal cortex and the frontal cortex are more active during object recognition when expectations have been elicited a priori, irrespectively of their validity or their affective intensity. This result supports previous hypotheses according to which these brain areas integrate contextual expectations with object sensory information. Notably, these brain areas are different from those responsible for simultaneous context-object interactions, dissociating the two processes. Then, we show that early visual areas, on the contrary, are more active during object recognition when no prior expectation has been elicited by a context. Lastly, BOLD activity was shown to be enhanced in early visual areas when objects are less expected, but only when contexts are neutral; the reverse effect is observed when contexts are affective. This result supports the proposal that affect modulates the weighting of sensory information during predictions. Together, our results help elucidate the neural mechanisms of real-world expectations.

The Intricate Interplay of Spatial Attention and Expectation: a Multisensory Perspective

Attention (i.e., task relevance) and expectation (i.e., signal probability) are two critical top-down mechanisms guiding perceptual inference. Attention prioritizes processing of information that is relevant for observers’ current goals. Prior expectations encode the statistical structure of the environment. Research to date has mostly conflated spatial attention and expectation. Most notably, the Posner cueing paradigm manipulates spatial attention using probabilistic cues that indicate where the subsequent stimulus is likely to be presented. Only recently have studies attempted to dissociate the mechanisms of attention and expectation and characterized their interactive (i.e., synergistic) or additive influences on perception. In this review, we will first discuss methodological challenges that are involved in dissociating the mechanisms of attention and expectation. Second, we will review research that was designed to dissociate attention and expectation in the unisensory domain. Third, we will review the broad field of crossmodal endogenous and exogenous spatial attention that investigates the impact of attention across the senses. This raises the critical question of whether attention relies on amodal or modality-specific mechanisms. Fourth, we will discuss recent studies investigating the role of both spatial attention and expectation in multisensory perception, where the brain constructs a representation of the environment based on multiple sensory inputs. We conclude that spatial attention and expectation are closely intertwined in almost all circumstances of everyday life. Yet, despite their intimate relationship, attention and expectation rely on partly distinct neural mechanisms: while attentional resources are mainly shared across the senses, expectations can be formed in a modality-specific fashion.

Evaluating the neurophysiological evidence for predictive processing as a model of perception

For many years, the dominant theoretical framework guiding research into the neural origins of perceptual experience has been provided by hierarchical feedforward models, in which sensory inputs are passed through a series of increasingly complex feature detectors. However, the long-standing orthodoxy of these accounts has recently been challenged by a radically different set of theories that contend that perception arises from a purely inferential process supported by two distinct classes of neurons: those that transmit predictions about sensory states and those that signal sensory information that deviates from those predictions. Although these predictive processing (PP) models have become increasingly influential in cognitive neuroscience, they are also criticized for lacking the empirical support to justify their status. This limited evidence base partly reflects the considerable methodological challenges that are presented when trying to test the unique predictions of these models. However, a confluence of technological and theoretical advances has prompted a recent surge in human and nonhuman neurophysiological research seeking to fill this empirical gap. Here, we will review this new research and evaluate the degree to which its findings support the key claims of PP.

Shared Physiological Correlates of Multisensory and Expectation-Based Facilitation

Perceptual performance in a visual task can be enhanced by simultaneous multisensory information, but can also be enhanced by a symbolic or amodal cue inducing a specific expectation. That similar benefits can arise from multisensory information and within-modality expectation raises the question of whether the underlying neurophysiological processes are the same or distinct. We investigated this by comparing the influence of the following three types of auxiliary probabilistic cues on visual motion discrimination in humans: (1) acoustic motion, (2) a premotion visual symbolic cue, and (3) a postmotion symbolic cue. Using multivariate analysis of the EEG data, we show that both the multisensory and preceding visual symbolic cue enhance the encoding of visual motion direction as reflected by cerebral activity arising from occipital regions ∼200–400 ms post-stimulus onset. This suggests a common or overlapping physiological correlate of cross-modal and intramodal auxiliary information, pointing to a neural mechanism susceptive to both multisensory and more abstract probabilistic cues. We also asked how prestimulus activity shapes the cue–stimulus combination and found a differential influence on the cross-modal and intramodal combination: while alpha power modulated the relative weight of visual motion and the acoustic cue, it did not modulate the behavioral influence of a visual symbolic cue, pointing to differences in how prestimulus activity shapes the combination of multisensory and abstract cues with task-relevant information.

How Our Perception and Confidence Are Altered Using Decision Cues

Understanding how individuals utilize social information while making perceptual decisions and how it affects their decision confidence is crucial in a society. To date, very little has been known about perceptual decision-making in humans and the associated neural mediators under social influence. The present study provides empirical evidence of how individuals are manipulated by others' decisions while performing a face/car identification task. Subjects were significantly influenced by what they perceived as the decisions of other subjects, while the cues, in reality, were manipulated independently from the stimulus. Subjects, in general, tend to increase their decision confidence when their individual decision and the cues coincide, while their confidence decreases when cues conflict with their individual judgments, often leading to reversal of decision. Using a novel statistical model, it was possible to rank subjects based on their propensity to be influenced by cues. This was subsequently corroborated by an analysis of their neural data. Neural time series analysis revealed no significant difference in decision-making using social cues in the early stages, unlike neural expectation studies with predictive cues. Multivariate pattern analysis of neural data alludes to a potential role of the frontal cortex in the later stages of visual processing, which appeared to code the effect of cues on perceptual decision-making. Specifically, the medial frontal cortex seems to play a role in facilitating perceptual decision preceded by conflicting cues.

Challenges to the Modularity Thesis Under the Bayesian Brain Models

Modularity assumption is central to most theoretical and empirical approaches in cognitive science. The Bayesian Brain (BB) models are a class of neuro-computational models that aim to ground perception, cognition, and action under a single computational principle of prediction-error minimization. It is argued that the proposals of BB models contradict the modular nature of mind as the modularity assumption entails computational separation of individual modules. This review examines how BB models address the assumption of modularity. Empirical evidences of top-down influence on early sensory processes is often cited as a case against the modularity thesis. In the modularity thesis, such top-down effects are attributed to attentional modulation of the output of an early impenetrable stage of sensory processing. The attentional-mediation argument defends the modularity thesis. We analyse this argument using the novel conception of attention in the BB models. We attempt to reconcile classical bottom-up vs. top-down dichotomy of information processing, within the information passing scheme of the BB models. Theoretical considerations and empirical findings associated with BB models that address the modularity assumption is reviewed. Further, we examine the modularity of perceptual and motor systems.

Exploring the role of expectations and stimulus relevance on stimulus-specific neural representations and conscious report

Subjective experience can be influenced by top-down factors, such as expectations and stimulus relevance. Recently, it has been shown that expectations can enhance the likelihood that a stimulus is consciously reported, but the neural mechanisms supporting this enhancement are still unclear. We manipulated stimulus expectations within the attentional blink (AB) paradigm using letters and combined visual psychophysics with magnetoencephalographic (MEG) recordings to investigate whether prior expectations may enhance conscious access by sharpening stimulus-specific neural representations. We further explored how stimulus-specific neural activity patterns are affected by the factors expectation, stimulus relevance and conscious report. First, we show that valid expectations about the identity of an upcoming stimulus increase the likelihood that it is consciously reported. Second, using a series of multivariate decoding analyses, we show that the identity of letters presented in and out of the AB can be reliably decoded from MEG data. Third, we show that early sensory stimulus-specific neural representations are similar for reported and missed target letters in the AB task (active report required) and an oddball task in which the letter was clearly presented but its identity was task-irrelevant. However, later sustained and stable stimulus-specific representations were uniquely observed when target letters were consciously reported (decision-dependent signal). Fourth, we show that global pre-stimulus neural activity biased perceptual decisions for a ‘seen’ response. Fifth and last, no evidence was obtained for the sharpening of sensory representations by top-down expectations. We discuss these findings in light of emerging models of perception and conscious report highlighting the role of expectations and stimulus relevance.

Reduced prediction error responses in high-as compared to low-uncertainty musical contexts

Theories of predictive processing propose that prediction error responses are modulated by the certainty of the predictive model or precision. While there is some evidence for this phenomenon in the visual and, to a lesser extent, the auditory modality, little is known about whether it operates in the complex auditory contexts of daily life. Here, we examined how prediction error responses behave in a more complex and ecologically valid auditory context than those typically studied. We created musical tone sequences with different degrees of pitch uncertainty to manipulate the precision of participants' auditory expectations. Magnetoencephalography was used to measure the magnetic counterpart of the mismatch negativity (MMNm) as a neural marker of prediction error in a multi-feature paradigm. Pitch, slide, intensity and timbre deviants were included. We compared high-entropy stimuli, consisting of a set of non-repetitive melodies, with low-entropy stimuli consisting of a simple, repetitive pitch pattern. Pitch entropy was quantitatively assessed with an information-theoretic model of auditory expectation. We found a reduction in pitch and slide MMNm amplitudes in the high-entropy as compared to the low-entropy context. No significant differences were found for intensity and timbre MMNm amplitudes. Furthermore, in a separate behavioral experiment investigating the detection of pitch deviants, similar decreases were found for accuracy measures in response to more fine-grained increases in pitch entropy. Our results are consistent with a precision modulation of auditory prediction error in a musical context, and suggest that this effect is specific to features that depend on the manipulated dimension-pitch information, in this case.

Predictive cues reduce but do not eliminate intrinsic response bias

Predictive cues induce large changes in people's choices by biasing responses towards the expected stimulus category. At the same time, even in the absence of predictive cues, humans often exhibit substantial intrinsic response biases. Despite the ubiquity of both of these biasing effects, it remains unclear how predictive cues interact with intrinsic bias. To understand the nature of this interaction, we examined data across three previous experiments that featured a combination of neutral cues (revealing intrinsic biases) and predictive cues. We found that predictive cues decreased the intrinsic bias to about half of its original size. This result held both when bias was quantified as the criterion location estimated using signal detection theory and as the probability of choosing a particular stimulus category. Our findings demonstrate that predictive cues reduce but do not eliminate intrinsic response bias, testifying to both the malleability and rigidity of intrinsic biases.

Feature-specific prediction errors for visual mismatch

Predictive coding (PC) theory posits that our brain employs a predictive model of the environment to infer the causes of its sensory inputs. A fundamental but untested prediction of this theory is that the same stimulus should elicit distinct precision weighted prediction errors (pwPEs) when different (feature-specific) predictions are violated, even in the absence of attention. Here, we tested this hypothesis using functional magnetic resonance imaging (fMRI) and a multi-feature roving visual mismatch paradigm where rare changes in either color (red, green), or emotional expression (happy, fearful) of faces elicited pwPE responses in human participants. Using a computational model of learning and inference, we simulated pwPE and prediction trajectories of a Bayes-optimal observer and used these to analyze changes in blood oxygen level dependent (BOLD) responses to changes in color and emotional expression of faces while participants engaged in a distractor task. Controlling for visual attention by eye-tracking, we found pwPE responses to unexpected color changes in the fusiform gyrus. Conversely, unexpected changes of facial emotions elicited pwPE responses in cortico-thalamo-cerebellar structures associated with emotion and theory of mind processing. Predictions pertaining to emotions activated fusiform, occipital and temporal areas. Our results are consistent with a general role of PC across perception, from low-level to complex and socially relevant object features, and suggest that monitoring of the social environment occurs continuously and automatically, even in the absence of attention.

Expectation and attention increase the integration of top-down and bottom-up signals in perception through different pathways

Perception likely results from the interplay between sensory information and top-down signals. In this electroencephalography (EEG) study, we utilised the hierarchical frequency tagging (HFT) method to examine how such integration is modulated by expectation and attention. Using intermodulation (IM) components as a measure of nonlinear signal integration, we show in three different experiments that both expectation and attention enhance integration between top-down and bottom-up signals. Based on a multispectral phase coherence (MSPC) measure, we present two direct physiological measures to demonstrate the distinct yet related mechanisms of expectation and attention, which would not have been possible using other amplitude-based measures. Our results link expectation to the modulation of descending signals and to the integration of top-down and bottom-up information at lower levels of the visual hierarchy. Meanwhile, the results link attention to the modulation of ascending signals and to the integration of information at higher levels of the visual hierarchy. These results are consistent with the predictive coding account of perception.

Dissociating the impact of attention and expectation on early sensory processing

Most studies that focus on understanding how top-down knowledge influences behavior attempt to manipulate either 'attention' or 'expectation' and often use the terms interchangeably. However, having expectations about statistical regularities in the environment and the act of willfully allocating attention to a subset of relevant sensory inputs are logically distinct processes that could, in principle, rely on similar neural mechanisms and influence information processing at the same stages. In support of this framework, several recent studies attempted to isolate expectation from attention, and advanced the idea that expectation and attention both modulate early sensory processing. Here, we argue that there is currently insufficient empirical evidence to support this conclusion, because previous studies have not fully isolated the effects of expectation and attention. Instead, most prior studies manipulated the relevance of different sensory features, and as a result, few existing findings speak directly to the potentially separable influences of expectation and attention on early sensory processing. Indeed, recent studies that attempt to more strictly isolate expectation and attention suggest that expectation has little influence on early sensory responses and primarily influences later 'decisional' stages of information processing.

Organizational principles of multidimensional predictions in human auditory attention

Anticipating the future rests upon our ability to exploit contextual cues and to formulate valid internal models or predictions. It is currently unknown how multiple predictions combine to bias perceptual information processing, and in particular whether this is determined by physiological constraints, behavioral relevance (task demands), or past knowledge (perceptual expertise). In a series of behavioral auditory experiments involving musical experts and non-musicians, we investigated the respective and combined contribution of temporal and spectral predictions in multiple detection tasks. We show that temporal and spectral predictions alone systematically increase perceptual sensitivity, independently of task demands or expertise. When combined, however, spectral predictions benefit more to non-musicians and dominate over temporal ones, and the extent of the spectrotemporal synergistic interaction depends on task demands. This suggests that the hierarchy of dominance primarily reflects the tonotopic organization of the auditory system and that expertise or attention only have a secondary modulatory influence.