Prestimulus feedback connectivity biases the content of visual experiences

Distinct Cortical Networks Subserve Spatio-temporal Sampling in Vision through Different Oscillatory Rhythms

Although visual input arrives continuously, sensory information is segmented into (quasi-)discrete events. Here, we investigated the neural correlates of spatiotemporal binding in humans with magnetoencephalography using two tasks where separate flashes were presented on each trial but were perceived, in a bistable way, as either a single or two separate events. The first task (two-flash fusion) involved judging one versus two flashes, whereas the second task (apparent motion: AM) involved judging coherent motion versus two stationary flashes. Results indicate two different functional networks underlying two unique aspects of temporal binding. In two-flash fusion trials, involving an integration window of ∼50 msec, evoked responses differed as a function of perceptual interpretation by ∼25 msec after stimuli offset. Multivariate decoding of subjective perception based on prestimulus oscillatory phase was significant for alpha-band activity in the right medial temporal (V5/MT) area, with the strength of prestimulus connectivity between early visual areas and V5/MT being predictive of performance. In contrast, the longer integration window (∼130 msec) for AM showed evoked field differences only ∼250 msec after stimuli offset. Phase decoding of the perceptual outcome in AM trials was significant for theta-band activity in the right intraparietal sulcus. Prestimulus theta-band connectivity between V5/MT and intraparietal sulcus best predicted AM perceptual outcome. For both tasks, phase effects found could not be accounted by concomitant variations in power. These results show a strong relationship between specific spatiotemporal binding windows and specific oscillations, linked to the information flow between different areas of the where and when visual pathways.

Bias in Prestimulus Motor Cortical Activity Determines Decision-making Error in Rodents

Decision-making is a complex process that involves the integration and interpretation of sensory information to guide actions. The rodent motor cortex, which is generally involved in motor planning and execution, also plays a critical role in decision-making processes. In perceptual delayed-response tasks, the rodent motor cortex can represent sensory cues, as well as the decision of where to move. However, it remains unclear whether erroneous decisions arise from incorrect encoding of sensory information or improper utilization of the collected sensory information in the motor cortex. In this study, we analyzed the rodent anterior lateral motor cortex (ALM) while the mice performed perceptual delayed-response tasks. We divided population activities into sensory and choice signals to separately examine the encoding and utilization of sensory information. We found that the encoding of sensory information in the error trials was similar to that in the hit trials, whereas choice signals evolved differently between the error and hit trials. In error trials, choice signals displayed an offset in the opposite direction of instructed licking even before stimulus presentation, and this tendency gradually increased after stimulus onset, leading to incorrect licking. These findings suggest that decision errors are caused by biases in choice-related activities rather than by incorrect sensory encoding. Our study elaborates on the understanding of decision-making processes by providing neural substrates for erroneous decisions.

Unravelling brain connectivity patterns in body dysmorphic disorder during decision-making on visual illusions: A graph theoretical approach

Body dysmorphic disorder (BDD) is characterized by an excessive preoccupation with perceived defects in physical appearance, and is associated with compulsive checking. Visual illusions are illusory or distorted subjective perceptions of visual stimuli, which are induced by specific visual cues or contexts. While previous research has investigated visual processing in BDD, the decision-making processes involved in visual illusion processing remain unknown. The current study addressed this gap by investigating the brain connectivity patterns of BDD patients during decision-making about visual illusions. Thirty-six adults - 18 BDD (9 female) and 18 healthy controls (10 female) - viewed 39 visual illusions while their EEG was recorded. For each image, participants were asked to indicate (1) whether they perceived the illusory features of the images; and (2) their degree of confidence in their response. Our results did not uncover group-level differences in susceptibility to visual illusions, supporting the idea that higher-order differences, as opposed to lower-level visual impairments, can account for the visual processing differences that have previously been reported in BDD. However, the BDD group had lower confidence ratings when they reported illusory percepts, reflecting increased feelings of doubt. At the neural level, individuals with BDD showed greater theta band connectivity while making decisions about the visual illusions, likely reflecting higher intolerance to uncertainty and thus increased performance monitoring. Finally, control participants showed increased left-to-right and front-to-back directed connectivity in the alpha band, which may suggest more efficient top-down modulation of sensory areas in control participants compared to individuals with BDD. Overall, our findings are consistent with the idea that higher-order disruptions in BDD are associated with increased performance monitoring during decision-making, which may be related to constant mental rechecking of responses.

Accounting for endogenous effects in decision-making with a non-linear diffusion decision model

The Drift-Diffusion Model (DDM) is widely accepted for two-alternative forced-choice decision paradigms thanks to its simple formalism and close fit to behavioral and neurophysiological data. However, this formalism presents strong limitations in capturing inter-trial dynamics at the single-trial level and endogenous influences. We propose a novel model, the non-linear Drift-Diffusion Model (nl-DDM), that addresses these issues by allowing the existence of several trajectories to the decision boundary. We show that the non-linear model performs better than the drift-diffusion model for an equivalent complexity. To give better intuition on the meaning of nl-DDM parameters, we compare the DDM and the nl-DDM through correlation analysis. This paper provides evidence of the functioning of our model as an extension of the DDM. Moreover, we show that the nl-DDM captures time effects better than the DDM. Our model paves the way toward more accurately analyzing across-trial variability for perceptual decisions and accounts for peri-stimulus influences.

Conscious interpretation: A distinct aspect for the neural markers of the contents of consciousness

Progress in the science of consciousness depends on the experimental paradigms and varieties of contrastive analysis available to researchers. Here we highlight paradigms where the object is represented in consciousness as a set of its features but the interpretation of this set alternates in consciousness. We group experimental paradigms with this property under the label "conscious interpretation". We compare the paradigms studying conscious interpretation of the already consciously perceived objects with other types of experimental paradigms. We review previous and recent studies investigating this interpretative aspect of consciousness and propose future directions. We put forward the hypothesis that there are types of stimuli with a hierarchy of interpretations for which the rule applies: conscious experience is drawn towards higher-level interpretation and reverting back to the lower level of interpretation is impossible. We discuss how theories of consciousness might incorporate knowledge and constraints arising from the characteristics of conscious interpretation.

Multiple-stage impairments of unfamiliar face learning in developmental prosopagnosia: Evidence from fMRI repetition suppression and multi-voxel pattern stability

Individuals with developmental prosopagnosia (DP) are characterized by severe face recognition deficits, yet it remains unknown how they are hindered in the process of unfamiliar face learning. Here we tracked the changes of neural activation during unfamiliar face repetition in DP with fMRI to reveal their neural deficits in learning unfamiliar faces. At the perceptual level, we found that the bilateral fusiform face area (FFA) in individuals with DP showed attenuated repetition suppression for faces, suggesting an inefficient perceptual analysis for learned faces. At the mnemonic level, individuals with DP showed decreased multi-voxel pattern stability for repeated faces in bilateral medial temporal lobe (MTL), suggesting an unstable mnemonic representation for learned faces. In addition, resting-state functional connectivity between the FFA and MTL was also disrupted in individuals with DP. Finally, the MTL's unstable mnemonic representation was associated with the impaired face recognition performance in DP. In sum, our study provides evidence that individuals with DP showed multi-stage neural deficits in unfamiliar face learning and sheds new light on how unfamiliar faces are learned in normal population.

Pre-stimulus Alpha Activity Modulates Face and Object Processing in the Intra-Parietal Sulcus, a MEG Study

Face perception is crucial in all social animals. Recent studies have shown that pre-stimulus oscillations of brain activity modulate the perceptual performance of face vs. non-face stimuli, specifically under challenging conditions. However, it is unclear if this effect also occurs during simple tasks, and if so in which brain regions. Here we used magnetoencephalography (MEG) and a 1-back task in which participants decided if the two sequentially presented stimuli were the same or not in each trial. The aim of the study was to explore the effect of pre-stimulus alpha oscillation on the perception of face (human and monkey) and non-face stimuli. Our results showed that pre-stimulus activity in the left occipital face area (OFA) modulated responses in the intra-parietal sulcus (IPS) at around 170 ms after the presentation of human face stimuli. This effect was also found after participants were shown images of motorcycles. In this case, the IPS was modulated by pre-stimulus activity in the right OFA and the right fusiform face area (FFA). We conclude that pre-stimulus modulation of post-stimulus response also occurs during simple tasks and is therefore independent of behavioral responses.

Pre-Stimulus Alpha-Band Phase Gates Early Visual Cortex Responses

Alpha-band (8-13 Hz) oscillations have been shown to phasically inhibit perceptual reports in human observers, yet the underlying physiological mechanism of this effect is debated. According to contrasting models, based primarily on animal experiments, alpha activity is thought to either originate from specialized cells in the visual thalamus and periodically inhibit the relay of visual information to the primary visual cortex (V1) in a feedforward manner, or to propagate from higher visual areas back to V1 in a feedback manner. Human neurophysiological evidence in favor of either hypothesis, both, or neither, has been limited. To help address this issue, we explored the link between pre-stimulus alpha phase and visual electroencephalography (EEG) responses thought to arise from afferent input onto human V1. Specially-designed visual stimuli were used to elicit large amplitude C1 event-related potentials (ERP), with polarity, topography, and timing indicative of striate genesis. Single-trial circular-linear associations between pre-stimulus phase and post-stimulus global field power (GFP) during the C1 time window revealed significant effects peaking in the alpha frequency band. Control analyses ruling out the potential confound of post-stimulus data bleeding into the pre-stimulus window demonstrated that GFP amplitude decreases as pre-stimulus alpha phase deviates from an individual's preferred phase. These findings demonstrate an early locus - suggesting that the phase of pre-stimulus alpha oscillations could modulate visual processing by gating the feedforward flow of sensory input between the thalamus and V1, although other models are potentially compatible.

Efficient Prestimulus Network Integration of Fusiform Face Area Biases Face Perception during Binocular Rivalry

Ongoing fluctuations in neural excitability and connectivity influence whether or not a stimulus is seen. Do they also influence which stimulus is seen? We recorded magnetoencephalography data while 21 human participants viewed face or house stimuli, either one at a time or under bistable conditions induced through binocular rivalry. Multivariate pattern analysis revealed common neural substrates for rivalrous versus nonrivalrous stimuli with an additional delay of ∼36 msec for the bistable stimulus, and poststimulus signals were source-localized to the fusiform face area. Before stimulus onset followed by a face versus house report, fusiform face area showed stronger connectivity to primary visual cortex and to the rest of the cortex in the alpha frequency range (8-13 Hz), but there were no differences in local oscillatory alpha power. The prestimulus connectivity metrics predicted the accuracy of poststimulus decoding and the delay associated with rivalry disambiguation suggesting that perceptual content is shaped by ongoing neural network states.

Connectomics of human electrophysiology

We present both a scientific overview and conceptual positions concerning the challenges and assets of electrophysiological measurements in the search for the nature and functions of the human connectome. We discuss how the field has been inspired by findings and approaches from functional magnetic resonance imaging (fMRI) and informed by a small number of significant multimodal empirical studies, which show that the canonical networks that are commonplace in fMRI are in fact rooted in electrophysiological processes. This review is also an opportunity to produce a brief, up-to-date critical survey of current data modalities and analytical methods available for deriving both static and dynamic connectomes from electrophysiology. We review hurdles that challenge the significance and impact of current electrophysiology connectome research. We then encourage the field to take a leap of faith and embrace the wealth of electrophysiological signals, despite their apparent, disconcerting complexity. Our position is that electrophysiology connectomics is poised to inform testable mechanistic models of information integration in hierarchical brain networks, constructed from observable oscillatory and aperiodic signal components and their polyrhythmic interactions.

Long-term priors influence visual perception through recruitment of long-range feedback

Perception results from the interplay of sensory input and prior knowledge. Despite behavioral evidence that long-term priors powerfully shape perception, the neural mechanisms underlying these interactions remain poorly understood. We obtained direct cortical recordings in neurosurgical patients as they viewed ambiguous images that elicit constant perceptual switching. We observe top-down influences from the temporal to occipital cortex, during the preferred percept that is congruent with the long-term prior. By contrast, stronger feedforward drive is observed during the non-preferred percept, consistent with a prediction error signal. A computational model based on hierarchical predictive coding and attractor networks reproduces all key experimental findings. These results suggest a pattern of large-scale information flow change underlying long-term priors’ influence on perception and provide constraints on theories about long-term priors’ influence on perception.

Priors learnt from lifetime experiences influence perception. The authors show that when perception is congruent with a long-term prior, there is increased top-down input in the ventral visual stream, whereas bottom-up input is enhanced when perception is incongruent with prior.

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.

Alpha-band cortico-cortical phase synchronization is associated with effective connectivity in the motor network

OBJECTIVE

Communication-through-coherence proposes that the phase synchronization (PS) of neural oscillations between cortical areas supports neural communication. In this study, we exploited transcranial magnetic stimulation (TMS)-evoked potentials (TEPs) to test this hypothesis at the macroscale level, i.e., whether PS between cortical areas supports interarea communication. TEPs are electroencephalographic (EEG) responses time-locked to TMS pulses reflecting interarea communication, as they are generated by the transmission of neural activity from the stimulated area to connected regions. If interarea PS is important for communication, it should be associated with the TEP amplitude in the connected areas.

METHODS

TMS was delivered over the left primary motor cortex (M1) of fourteen healthy volunteers, and 70-channel EEG was recorded. Early TEP components were source-localized to identify their generators, i.e., distant brain regions activated by M1 through effective connections. Next, linear regressions were used to test the relationship between the TEP amplitude and the pre-stimulus PS between the M1 and the connected regions in four frequency bands (range 4-45 Hz).

RESULTS

Pre-stimulus interarea PS in the alpha-band was positively associated with the amplitude of early TEP components, namely, the N15 (ipsilateral supplementary motor area), P25 (contralateral M1) and P60 (ipsilateral parietal cortex).

CONCLUSIONS

Alpha-band PS predicts the response amplitude of the distant brain regions effectively connected to M1.

SIGNIFICANCE

Our study supports the role of EEG-PS in interarea communication, as theorized by communication-through-coherence.

The role of attention and explicit knowledge in perceiving bistable auditory input

The auditory system frequently encounters ambiguous sound input that can be perceived in multiple ways. The current study investigated the role of explicit knowledge in modulating how sounds are represented in auditory memory for a bistable sound sequence that could be perceived equally as integrated or segregated. We hypothesized that the dominant percept of the bistable sequence would suppress representation of the alternative perceptual organization as a function of how much top-down knowledge the listener had about the structure of the sequence. Performance measures and event-related brain potentials were compared when participants had explicit knowledge about one perceptual organization in the first half of the experiment to when they had explicit knowledge of both in the second half. We hypothesized that knowledge would modify the brain response to the alternative percept of the bistable sequence. However, that did not occur. When participants were performing one task, with no explicit knowledge of the bistable structure of the sequence, both integrated and segregated percepts were represented in auditory working memory. This demonstrates that explicit knowledge about the sounds is not a necessary factor for deriving and maintaining representations of multiple sound organizations within a complex sound environment. Passive attention operates in parallel with active or selective attention to maintain consistent representations of the environment, representations that may or may not be useful for task performance. It suggests a highly adaptive system useful in everyday listening situations where the listener has no prior knowledge about how the sound environment is structured.

New methods for oscillation analyses push new theories of discrete cognition

Classical ways of analyzing neural time series data has led to static views on cognition, in which the cognitive processes are linked to sustained neural activity and interpreted as stationary states. The core analytical focus was on slow power modulations of neural oscillations averaged across many experimental trials. Whereas this custom analytical approach reduces the complexity and increases the signal-to-noise ratio, it may disregard or even remove important aspects of the underlying neural dynamics. Novel analysis methods investigate the instantaneous frequency and phase of neural oscillations and relate them to the precisely controlled timing of brief successive sensory stimuli. This enables to capture how cognitive processes unfold in discrete windows within and across oscillatory cycles. Moreover, several recent studies analyze the oscillatory power modulations on single experimental trials. They suggest that the power modulations are packed into discrete bursts of activity, which occur at different rates and times, and with different durations from trial-to-trial. Here, we review the current work that made use of these methodological advances for neural oscillations. These novel analysis perspectives emphasize that cognitive processes occur in discrete time windows, instead of sustained, stationary states. Evidence for discretization was observed for the entire range of cognitive functions from perception and attention to working memory, goal-directed thought and motor actions, as well as throughout the entire cortical hierarchy and in subcortical regions. These empirical observations create demand for new psychological theories and computational models of cognition in the brain, which integrate its discrete temporal dynamics.

Pre-stimulus alpha-band power and phase fluctuations originate from different neural sources and exert distinct impact on stimulus-evoked responses

Ongoing oscillatory neural activity before stimulus onset influences subsequent visual perception. Specifically, both the power and the phase of oscillations in the alpha-frequency band (9-13 Hz) have been reported to predict the detection of visual stimuli. Up to now, the functional mechanisms underlying pre-stimulus power and phase effects on upcoming visual percepts are debated. Here, we used magnetoencephalography recordings together with a near-threshold visual detection task to investigate the neural generators of pre-stimulus power and phase and their impact on subsequent visual-evoked responses. Pre-stimulus alpha-band power and phase opposition effects were found consistent with previous reports. Source localization suggested clearly distinct neural generators for these pre-stimulus effects: Power effects were mainly found in occipital-temporal regions, whereas phase effects also involved prefrontal areas. In order to be functionally relevant, the pre-stimulus correlates should influence post-stimulus processing. Using a trial-sorting approach, we observed that only pre-stimulus power modulated the Hits versus Misses difference in the evoked response, a well-established post-stimulus neural correlate of near-threshold perception, such that trials with stronger pre-stimulus power effect showed greater post-stimulus difference. By contrast, no influence of pre-stimulus phase effects were found. In sum, our study shows distinct generators for two pre-stimulus neural patterns predicting visual perception, and that only alpha power impacts the post-stimulus correlate of conscious access. This underlines the functional relevance of prestimulus alpha power on perceptual awareness, while questioning the role of alpha phase.

Reaction times predict dynamic brain representations measured with MEG for only some object categorisation tasks

Behavioural categorisation reaction times (RTs) provide a useful way to link behaviour to brain representations measured with neuroimaging. In this framework, objects are assumed to be represented in a multidimensional activation space, with the distances between object representations indicating their degree of neural similarity. Faster RTs have been reported to correlate with greater distances from a classification decision boundary for animacy. Objects inherently belong to more than one category, yet it is not known whether the RT-distance relationship, and its evolution over the time-course of the neural response, is similar across different categories. Here we used magnetoencephalography (MEG) to address this question. Our stimuli included typically animate and inanimate objects, as well as more ambiguous examples (i.e., robots and toys). We conducted four semantic categorisation tasks on the same stimulus set assessing animacy, living, moving, and human-similarity concepts, and linked the categorisation RTs to MEG time-series decoding data. Our results show a sustained RT-distance relationship throughout the time course of object processing for not only animacy, but also categorisation according to human-similarity. Interestingly, this sustained RT-distance relationship was not observed for the living and moving category organisations, despite comparable classification accuracy of the MEG data across all four category organisations. Our findings show that behavioural RTs predict representational distance for an organisational principle other than animacy, however further research is needed to determine why this relationship is observed only for some category organisations and not others.

Spontaneous Network Coupling Enables Efficient Task Performance without Local Task-Induced Activations

Neurobehavioral studies in humans have long concentrated on changes in local activity levels during repetitive executions of a task. Spontaneous neural coupling within extended networks has latterly been found to also influence performance. Here, we intend to uncover the underlying mechanisms, the relative importance, and the interaction between spontaneous coupling and task-induced activations. To do so, we recorded two groups of healthy participants (male and female) during rest and while they performed either a visual perception or a motor sequence task. We demonstrate that, for both tasks, stronger activations during the task as well as greater network coupling through spontaneous α rhythms at rest predict performance. However, high performers present an absence of classical task-induced activations and, instead, stronger spontaneous network coupling. Activations were thus a compensation mechanism needed only in subjects with lower spontaneous network interactions. This challenges classical models of neural processing and calls for new strategies in attempts to train and enhance performance.SIGNIFICANCE STATEMENT Our findings challenge the widely accepted notion that task-induced activations are of paramount importance for behavior. This will have an important impact on interpretations of human neurobehavioral research. They further link the widely used techniques of quantifying network communication in the brain with classical neuroscience methods and demonstrate possible ways of how network communication influences human behavior. Traditional training methods attempt to enhance neural activations through task repetitions. Our findings suggest a more efficient neural target for learning: enhancing spontaneous neural interactions. This will be of major interest for a large variety of scientific fields with very broad applications in schools, work, and others.

Response dependence of reversal-related ERP components in perception of ambiguous figures

Perceptual multi-stability is characterized by alternating interpretations of an unchanging stimulus input. The reversal negativity (RN) and reversal positivity (RP) ERP components show differences in electrophysiological responses between trials on which participants experience a perceptual reversal of a multi-stable stimulus versus trials without a reversal (i.e., stable). However, it is unclear to what extent these two ERP components reflect reversal-related perceptual processing rather than task and response processes. To address this, we varied task and response requirements while measuring the RN and RP. In the standard reversal task, participants indicated whether they saw a perceptual reversal on each trial. In contrast, in the identity task participants reported perceived identity of the stimulus (e.g., face or vase) without any reference to reversals. In some blocks, reversal trials required a response whereas in other blocks stable trials required a response. We found that the RN appeared independently of task and response style. However, the early latency RP component was only present when participants responded manually. For non-response trials, a component was found during the same latency as the RP but with inverted polarity. Our results suggest that the early RP component is dependent on response-related processes rather than being a pure neural signature of perceptual processes related to endogenous perceptual reversals.

Endogenous activity modulates stimulus and circuit-specific neural tuning and predicts perceptual behavior

Perception reflects not only sensory inputs, but also the endogenous state when these inputs enter the brain. Prior studies show that endogenous neural states influence stimulus processing through non-specific, global mechanisms, such as spontaneous fluctuations of arousal. It is unclear if endogenous activity influences circuit and stimulus-specific processing and behavior as well. Here we use intracranial recordings from 30 pre-surgical epilepsy patients to show that patterns of endogenous activity are related to the strength of trial-by-trial neural tuning in different visual category-selective neural circuits. The same aspects of the endogenous activity that relate to tuning in a particular neural circuit also correlate to behavioral reaction times only for stimuli from the category that circuit is selective for. These results suggest that endogenous activity can modulate neural tuning and influence behavior in a circuit- and stimulus-specific manner, reflecting a potential mechanism by which endogenous neural states facilitate and bias perception.

Prestimulus feedback connectivity biases the content of visual experiences

Ongoing fluctuations in neural excitability and in networkwide activity patterns before stimulus onset have been proposed to underlie variability in near-threshold stimulus detection paradigms-that is, whether or not an object is perceived. Here, we investigated the impact of prestimulus neural fluctuations on the content of perception-that is, whether one or another object is perceived. We recorded neural activity with magnetoencephalography (MEG) before and while participants briefly viewed an ambiguous image, the Rubin face/vase illusion, and required them to report their perceived interpretation in each trial. Using multivariate pattern analysis, we showed robust decoding of the perceptual report during the poststimulus period. Applying source localization to the classifier weights suggested early recruitment of primary visual cortex (V1) and ∼160-ms recruitment of the category-sensitive fusiform face area (FFA). These poststimulus effects were accompanied by stronger oscillatory power in the gamma frequency band for face vs. vase reports. In prestimulus intervals, we found no differences in oscillatory power between face vs. vase reports in V1 or in FFA, indicating similar levels of neural excitability. Despite this, we found stronger connectivity between V1 and FFA before face reports for low-frequency oscillations. Specifically, the strength of prestimulus feedback connectivity (i.e., Granger causality) from FFA to V1 predicted not only the category of the upcoming percept but also the strength of poststimulus neural activity associated with the percept. Our work shows that prestimulus network states can help shape future processing in category-sensitive brain regions and in this way bias the content of visual experiences.