Biology subjects

Kok, P.

Publications and source records attributed to Kok, P..

18 recordsLinked to original sources

bioRxiv2026

The post-hoc montage of perception: deep layers of primary visual cortex encode postdictive percepts

One of the most puzzling aspects of perception is postdiction: later information can change how a previous stimulus is perceived [1,2]. This indicates that perception is not a livestream of the external world, but rather a post-hoc reconstruction. How does the brain revise perception? It has been proposed that recurrent processing in the sensory hierarchy may sustain earlier information long enough for later information to impact it [3]. We hypothesised that this allows feedback from higher-order multisensory regions to alter the representation of earlier visual stimuli in the primary visual cortex (V1) [4]. Here, we tested this hypothesis using two postdictive illusions [5], where the presence or absence of a tone determines whether an illusory flash is perceived, or an actually presented flash is perceptually suppressed, respectively. This allowed us to isolate neural signals reflecting illusory percepts from sensory inputs in retinotopic space. We collected 7T layer-specific fMRI data while participants (N=23) experienced the illusions. We found that postdictive illusions induced similar activity patterns as real percepts, specifically in the deep layers of V1, suggesting postdictive feedback. Informational connectivity analyses suggested that the source of this feedback was the Superior Temporal Cortex (STC). We conclude that the postdictive montage of perception is reflected in V1, implemented through a delaying feedback loop with higher-order sensory cortex. This extends the role V1 plays in perceptual inference: beyond receiving sensory inputs reflecting the present and predictions of the future, it is involved in the post-hoc revision of perception.

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bioRxiv2026

Paradoxical influences of prediction are resolved across time

It is widely thought that our brains use expectations to optimise perception, yet theoretical accounts disagree about the form of this optimisation. Bayesian accounts propose that perception is biased towards expected events, rapidly generating more veridical experiences, whereas cancellation accounts argue that unexpected inputs are perceptually prioritised as they are more informative. A recent opposing process theory reconciles these views by proposing a temporal reversal in prioritisation: perceptual processing is pre-emptively biased towards what is expected, followed by later enhancement of only particularly surprising inputs that are informative for learning and model updating. Here, we tested this account using time-resolved decoding of EEG data, while participants observed avatar action outcomes that were either expected or unexpected based on their own movements. Expectation effects on the neural representations of these action outcomes indeed unfolded over time in such a manner, with higher decoding for task-relevant expected outcomes starting before stimulus onset, followed by a later post-stimulus advantage for unexpected outcomes. These findings support the opposing process theory, demonstrating a reversal in prioritisation that is not predicted by current Bayesian or cancellation accounts. By exerting distinct influences across time, expectations can thus render perception veridical, while still allowing for the accurate perception of particularly unexpected events that are important for updating our beliefs or ongoing courses of action. Significance statementHow we perceive the world is shaped by our expectations. Yet it remains unclear how the brain can use these expectations to make perception both more accurate and more informative, given these demands require opposite influences of expectation on processing - upweighting versus downweighting the expected, respectively. Here, we show that this apparent conflict is resolved across time. The expected is enhanced before a stimulus appears by pre-activating what we expect, whereas unexpected inputs are enhanced later. This temporal reversal allows expectations to support both demands, rapidly generating generally more accurate perceptual experiences, while also remaining sensitive to unexpected information that is critical for learning and adaptive behaviour.

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bioRxiv2025

Temporal confounds emulate multivariate fMRI measures of perceptual learning

Human perception inherently involves learning. We can experience the same stimulus completely differently depending on our prior knowledge. Understanding the neural basis of perception therefore requires measurements that capture these temporal dynamics. Multi-voxel pattern analysis (MVPA) approaches are widely used to characterise changes in neural representations over time. A popular example is the perceptual reorganisation paradigm, which investigates the neural correlates of enhanced recognition of distorted images after cueing with the undistorted version. Studies typically report increased representational similarity of these two images in early visual cortex. However, as these paradigms include an inherent ordering of stimuli that precludes trial randomisation or counterbalancing, they are vulnerable to temporal confounds common to fMRI. Here, we investigate how these confounds could influence current understanding of perceptual reorganisation. We tested different perceptual reorganisation paradigm designs derived from published fMRI studies, and found substantial design-driven order effects at the single-subject level for all paradigms. For certain designs, these effects artificially amplified neural indices of perceptual reorganisation at both the single-subject and group levels, emulating widespread signatures of perceptual reorganisation across the brain. To disentangle perceptual learning processes from measurement artefacts, we recommend (i) selecting designs that minimise the effect of stimulus order confounds on contrasts of interest, (ii) correcting for these confounds, and (iii) confirming results are perceptually driven via negative controls, e.g., stimuli or brain areas not expected to produce perceptual effects. Our work demonstrates how current understanding of perceptual learning mechanisms based on multivariate neuroimaging approaches could be influenced by non-obvious design confounds that misdirect interpretations towards distributed neural processing, and offers practical solutions to address this.

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bioRxiv2025

Tracking visual rhythms: a concert of sensory and motor simulation

When will I see something and what will it be? Temporal predictions are crucial for adaptive interaction with the environment and are typically accompanied by predictions about sensory content, yet these two types of what and when predictions are usually studied separately. Specifically, oscillatory phase-coupling (or entrainment) has been proposed to align our neural sensitivity with likely moments of stimulus appearance, however these accounts ignore that predictions about when something will appear are usually accompanied by predictions about what it will be. Thus, temporal predictions may not enhance all sensory processing but rather modulate particular channels encoding predicted content. We here demonstrate oscillatory phase-coupling in vision and show how it relates to content-specific encoding. In a magnetoencephalography (MEG) study, participants observed rhythmic Gabors at 1.33 or 2 Hz with predictable orientations. They judged the timing or orientation of a delayed probe which manipulated the requirement to covertly maintain the sequence rhythm. We found sustained oscillatory phase-coupling to the entrained rhythm in motor areas specifically when participants judged stimulus timing, where its extent was associated with perceptual performance. Meanwhile, neural decoding revealed content predictions in early visual areas ( what) that fluctuated in line with temporal predictions ( when). These temporally-specific content predictions appeared regardless of task instruction but were correlated and phase-aligned with the motor phase-coupling during timing judgements. These findings suggest that temporal predictions may be derived from motor readouts of temporally-specific sensory predictions, with broad implications for our understanding of entrainment and prediction, and how we represent time more generally.

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bioRxiv2024

Communication of perceptual predictions from the hippocampus to the deep layers of the parahippocampal cortex

Current evidence points to the hippocampus as an essential region coordinating learning and exploiting predictive relationships in the service of perception. However, it remains unclear whether the hippocampus drives the communication of predictions to the sensory cortex or acts as a recipient of predictions from else-where. Here, we collected sub-millimetre 7T fMRI data to investigate neural signals in the medial temporal lobe (MTL). We used layer-specific fMRI to infer the direction of communication between the hippocam-pus and cortex. Specifically, superficial layers of the MTL cortex project to the hippocampus, while deep MTL layers receive feedback projections. Participants performed a task in which auditory cues predicted abstract shapes. Crucially, we omitted the expected shape on 25% of trials, thus isolating the prediction signal from bottom-up input and allowing us to ask: In which direction are predictions communicated between the hippocampus and neocortex? Neural patterns in CA23, pre/parasubiculum and the parahippocampal cortex (PHC) reflected shape-specific predictions. Layer-specific informational connectivity analyses revealed that communication between CA23 and PHC was specific to the deep layers of PHC. These findings are in line with the hippocampus generating predictions through pattern completion in CA23 and feeding these pre-dictions back to the neocortex.

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bioRxiv2024

Pre-stimulus alpha oscillations encode stimulus-specific visual predictions

Predictions of future events have a major impact on how we process sensory signals. However, it remains unclear how the brain keeps predictions online in anticipation of future inputs. Here, we combined magnetoencephalography (MEG) and multivariate decoding techniques to investigate the content of perceptual predictions and their frequency characteristics. Participants were engaged in a shape discrimination task, while auditory cues predicted which specific shape would likely appear. Frequency analysis revealed significant oscillatory fluctuations of predicted shape representations in the pre-stimulus window in the alpha band (10 - 11Hz). Furthermore, we found that this stimulus-specific alpha power was linked to expectation effects on shape discrimination. Our findings demonstrate that sensory predictions are embedded in pre-stimulus alpha oscillations and modulate subsequent perceptual performance, providing a neural mechanism through which the brain deploys perceptual predictions.

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bioRxiv2024

Expectations about presence enhance the influence of content-specific expectations on low-level orientation judgements

Will something appear and if so, what will it be? Perceptual expectations can concern both the presence and content of a stimulus. However, it is unclear how these different types of expectations interact with each other in biasing perception. Here, we tested how expectations about stimulus presence and content differently affect perceptual inference. Across separate online discovery (N=110) and replication samples (N=218), participants were asked to judge both the presence and content (orientation) of noisy grating stimuli. Crucially, preceding compound cues simultaneously and orthogonally predicted both whether a grating was likely to appear as well as what its orientation would be. We found that expectations of presence interacted with expectations of content, such that the latters effect on discrimination was larger when a stimulus was expected to appear than when it was not. This interaction was observed both when a grating was truly presented and when participants falsely perceived one. Confidence in having seen a grating on the other hand was independently affected by presence and content expectations. Further, modelling revealed higher sensitivity in distinguishing between grating presence and absence following absence cues than presence cues, demonstrating an asymmetry between gathering evidence in favour of stimulus presence and absence. Finally, evidence for overweighted predictions being associated with hallucination-like perception was inconclusive. In sum, our results provide nuance to popular predictive processing accounts of perception by showing that expectations of presence and content have distinct but interacting roles in shaping conscious perception.

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bioRxiv2023

Shared and diverging neural dynamics underlying false and veridical perception

We often mistake visual noise for meaningful images, which sometimes appear to be as convincing as veridical percepts. This suggests that there is considerable overlap between the mechanisms that underlie false and veridical perception. Yet, false percepts must arise at least in part from internally generated signals. Here, we apply multivariate analyses to human MEG data to study the overlap between veridical and false perception across two discrete stages of perceptual inference: discrimination of content (what did I see) and detection (did I see something?). To this end, participants performed a visual discrimination task requiring them to indicate the orientation of a noisy grating, as well as their confidence in having seen a grating. Importantly, on 50% of trials no gratings were presented (noise-only trials). On a subset of these noise-only trials, participants reported seeing a grating with high confidence, dubbed here false percepts. We found that a sensory signal reflecting the content of these false percepts was present both before and after stimulus onset. Uniquely, high confidence false, but not veridical, percepts were associated with increased pre-stimulus high alpha/low beta [11-14Hz] power, potentially reflecting enhanced reliance on top-down signalling on false percept trials. Later on, a shared neural code reflecting confidence in stimulus presence emerged for both false and veridical percepts, as revealed by cross-decoding. These findings suggest that false percepts arise through sensory-like signals reflecting both content and detection signals, similar to veridical percepts, with an increase in pre-stimulus alpha/beta power uniquely contributing to false percepts. Significance statementThe neural mechanisms underlying false percepts are likely different from those that underlie veridical perception, as the former are generated endogenously, whereas the latter are the result of an external stimulus. Yet, false percepts often get confused for veridical perception, suggesting a converging mechanism. This study explores the extent to which the mechanisms diverge and converge. We found that both high confidence false and veridical percepts were accompanied by content-specific stimulus-like orientation signals, as well as a shared signal reflecting perceptual confidence. In contrast, we found that false, but not veridical, percepts were preceded by increased high alpha/low beta [11-14 Hz] power, possibly reflecting a reliance on endogenous signals.

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bioRxiv2023

Predictions and errors are distinctly represented across V1 layers

Predictive processing frameworks of cortical functioning propose that neural populations in different cortical layers serve distinct roles in representing the world. There are distinct testable theories within this framework that we examined with a 7T fMRI study, where we contrasted responses in primary visual cortex (V1) to expected (75% likely) and unexpected (25%) Gabor orientations. Multivariate decoding analyses revealed an interaction between expectation and layer, such that expected events could be decoded with comparable accuracy across layers, while unexpected events could only be decoded in superficial laminae. These results are in line with predictive processing accounts where expected virtual input is injected into deep layers, while superficial layers process the error with respect to expected signals. While this account of cortical processing has been popular for decades, such distinctions have not previously been demonstrated in the human sensory brain. We discuss how both prediction and error processes may operate together to shape our unitary perceptual experiences.

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bioRxiv2022

Perceptual expectations and false percepts generate stimulus-specific activity in distinct layers of the early visual cortex

Perception has been proposed to result from the integration of feedforward sensory signals with internally generated feedback signals. The latter are believed to play an important role in driving false percepts, i.e., seeing things that are not actually there. Feedforward and feedback influences on perception can be studied using layer-specific fMRI, which we used here to interrogate neural activity underlying high confidence false percepts while healthy participants (N=25) performed a perceptual orientation discrimination task. Orientation-specific BOLD activity in the deep and superficial layers of V2 reflected perceptual expectations induced by predictive auditory cues. However, these expectations did not influence participants perception. Instead, high confidence false percepts were reflected by orientation-specific activity in the middle input layers of V2, suggesting a feedforward signal contributing to false percepts. The prevalence of high confidence false percepts was related to everyday hallucination severity in a separate online sample (N=100), suggesting a possible link with abnormal perceptual experiences. These results reveal a feedforward mechanism underlying false percepts, reflected by spontaneous stimulus-like activity in the input layers of the visual cortex, independent of top-down perceptual expectations.

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bioRxiv2021

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 found that the hippocampus initially preferentially represented unexpected shapes (i.e., those that violated the cue regularities), but later switched to representing the cue-predicted shape regardless of which was actually presented. These findings demonstrate that the hippocampus in involved both acquiring and exploiting predictive associations, and switches between these modes depending on whether learning is ongoing or complete.

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bioRxiv2020

Prior expectations of motion direction modulate early sensory processing

Perception is a process of inference, integrating sensory inputs with prior expectations. However, little is known regarding the temporal dynamics of this integration. It has been proposed that expectation plays a role early in the perceptual process, by biasing early sensory processing. Alternatively, others suggest that expectations are integrated only at later, post-perceptual decision-making stages. The current study aimed to dissociate between these hypotheses. We exposed male and female human participants (N=24) to auditory cues predicting the likely direction of upcoming noisy moving dot patterns, while recording millisecond-resolved neural activity using magnetoencephalography (MEG). First, we found that participants reports of the moving dot directions were biased towards the direction predicted by the auditory cues. To investigate when expectations affected sensory representations, we used inverted encoding models to decode the direction represented in early sensory signals. Strikingly, the auditory cues modulated the direction represented in the MEG signal as early as 150ms after visual stimulus onset. This early neural modulation was related to perceptual effects of expectation: participants with a stronger perceptual bias towards the predicted direction also revealed a stronger reflection of the predicted direction in the MEG signal. For participants with this perceptual bias, a trial-by-trial correlation between decoded and perceived direction already emerged prior to visual stimulus onset ([~]-150ms), suggesting that the pre-stimulus state of the visual cortex influences sensory processing. Together, these results suggest that prior expectations can influence perception by biasing early sensory processing, making expectation a fundamental component of the neural computations underlying perception. Significance statementPerception can be thought of as an inferential process in which our brains integrate sensory inputs with prior expectations to make sense of the world. This study investigated whether this integration occurs early or late in the process of perception. We exposed human participants to auditory cues which predicted the likely direction of visual moving dots, while recording neural activity with millisecond resolution using magnetoencephalography (MEG). Participants perceptual reports of the direction of the moving dots were biased towards the predicted direction. Additionally, the predicted direction modulated the neural representation of the moving dots just 150 ms after they appeared. This suggests that prior expectations affected sensory processing at very early stages, playing an integral role in the perceptual process.

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bioRxiv2020

Prior expectations evoke stimulus templates in the deep layers of V1

The way we perceive the world is strongly influenced by our expectations. In line with this, much recent research has revealed that prior expectations strongly modulate sensory processing. However, the neural circuitry through which the brain integrates external sensory inputs with internal expectation signals remains unknown. In order to understand the computational architecture of the cortex, we need to investigate the way these signals flow through the cortical layers. This is crucial because the different cortical layers have distinct intra- and interregional connectivity patterns, and therefore determining which layers are involved in a cortical computation can inform us on the sources and targets of these signals. Here, we used ultra-high field (7T) functional magnetic resonance imaging (fMRI) to reveal that prior expectations evoke stimulus templates selectively in the deep layers of the primary visual cortex. These results shed light on the neural circuit underlying perceptual inference.

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bioRxiv2019

Content-based dissociation of hippocampal involvement in prediction

It has recently become clear that one of the key functions of the hippocampus is to predict future inputs. In line with this, previous research has revealed prediction-related signals in the hippocampus for complex visual objects, such as fractals and abstract shapes. Based on this, it has been suggested that the hippocampus may generate perceptual expectations, especially when relying on rapidly learned predictive associations between arbitrary stimuli. However, it is currently unknown whether the hippocampus implements general-purpose computations that subserve all associative predictions, regardless of stimulus properties, or whether the involvement of the hippocampus is stimulus-dependent. To investigate this, we exposed male and female human participants to complex auditory cues predicting either the shape of a complex object (Experiment 1) or the orientation of a simple line grating (Experiment 2). We measured brain activity using high-resolution functional magnetic resonance imaging (fMRI), in combination with inverted encoding models to reconstruct shape and orientation representations in visual cortex and the hippocampus. Our results revealed that expectations about shape and orientation evoked distinct representations in the hippocampus. For complex shapes, the hippocampus represented which shape was expected, potentially serving as a source of top-down predictions. In contrast, for simple gratings, the hippocampus represented only unexpected orientations, more reminiscent of a prediction error. We discuss several potential explanations for this dissociation, concluding that the computational role of the hippocampus in predictive processing depends upon the nature and complexity of stimuli.\n\nSignificance StatementTo deal with the noisy and ambiguous sensory signals received by our brain, it is crucial to use prior knowledge of the world to guide perception. Previous research suggests that the hippocampus is involved in predicting upcoming visual stimuli based on prior knowledge. In the current study, we show that hippocampal prediction is specific to expectations of complex objects, whereas for simple features the hippocampus generates an opposite prediction error signal instead. These findings demonstrate that the computational role of the hippocampus can be content-sensitive and refine our understanding of the involvement of memory systems in predictive processing.

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bioRxiv2018

Stimulus prediction in the hippocampus

Perception can be cast as a process of inference, in which bottom-up signals are combined with top-down predictions in sensory systems. However, the source of these top-down predictions, especially when complex and multisensory, remains largely unknown. We hypothesised that the hippocampus -- which rapidly learns arbitrary associations and has bidirectional connections with sensory systems -- may be involved. We exposed humans to auditory cues predicting visual shapes, while measuring high-resolution fMRI signals in visual cortex and the hippocampus. Using multivariate reconstruction methods, we discovered a dissociation between these regions: representations in visual cortex were dominated by whichever shape was presented, whereas representations in the hippocampus (CA3 and subiculum, but not CA1) reflected only which shape was predicted by the cue. The strength of hippocampal predictions correlated across participants with the amount of expectation-related facilitation in visual cortex. These findings are consistent with the possibility that the hippocampus supplies predictions to sensory systems.

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bioRxiv2017

Eye movement-related confounds in neural decoding of visual working memory representations

The study of visual working memory (VWM) has recently seen revitalization with the emergence of new insights and theories regarding its neural underpinnings. One crucial ingredient responsible for this progress is the rise of neural decoding techniques. These techniques promise to uncover the representational contents of neural signals, as well as the underlying code and the dynamic profile thereof. Here, we aimed to contribute to the field by subjecting human volunteers to a combined VWM/imagery task, while recording and decoding their neural signals as measured by MEG. At first sight, the results seem to provide evidence for a persistent, stable representation of the memorandum throughout the delay period. However, control analyses revealed that these findings can be explained by subtle, VWM-specific eye movements. As a potential remedy, we demonstrate the use of a functional localizer, which was specifically designed to target bottom-up sensory signals and as such avoids eye movements, to train the neural decoders. This analysis revealed a sustained representation for approximately 1 second, but no longer throughout the entire delay period. We conclude by arguing for more awareness of the potentially pervasive and ubiquitous effects of eye movement-related confounds.\n\nSignificance statementVisual working memory is an important aspect of higher cognition and has been subject of much investigation within the field of cognitive neuroscience. Over recent years, these studies have increasingly relied on the use of neural decoding techniques. Here, we show that neural decoding may be susceptible to confounds induced by stimulus-specific eye movements. Such eye movements during working memory have been reported before, and may in fact be a common phenomenon. Given the widespread use of neural decoding and the potentially contaminating effects of eye movements, we therefore believe that our results are of significant relevance for the field.

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bioRxiv2017

Stimulus familiarity and expectation jointly modulate neural activity in the visual ventral stream

Prior knowledge about the visual world can change how a visual stimulus is processed. Two forms of prior knowledge are often distinguished: stimulus familiarity (i.e., whether a stimulus has been seen before) and stimulus expectation (i.e., whether a stimulus is expected to occur, based on the context). Neurophysiological studies in monkeys have shown suppression of spiking activity both for expected and for familiar items in object-selective inferotemporal cortex (IT). It is an open question, however, if and how these types of knowledge interact in their modulatory effects on the sensory response. In order to address this issue and to examine whether previous findings generalize to non-invasively measured neural activity in humans of both sexes, we separately manipulated stimulus familiarity and expectation, while non-invasively recording human brain activity using magnetoencephalography (MEG). We observed independent suppression of neural activity by familiarity and expectation, specifically in the lateral occipital complex (LOC), the putative human homologue of monkey IT. Familiarity also led to sharpened response dynamics, which was predominantly observed in early visual cortex. Together, these results show that distinct types of sensory knowledge jointly determine the amount of neural resources dedicated to object processing in the visual ventral stream.

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bioRxiv2017

Prior expectations induce pre-stimulus sensory templates

Perception can be described as a process of inference, integrating bottom-up sensory inputs and top-down expectations. However, it is unclear how this process is neurally implemented. It has been proposed that expectations lead to pre-stimulus baseline increases in sensory neurons tuned to the expected stimulus, which in turn affects the processing of subsequent stimuli. Recent fMRI studies have revealed stimulus-specific patterns of activation in sensory cortex as a result of expectation, but this method lacks the temporal resolution necessary to distinguish pre- from post-stimulus processes. Here, we combined human MEG with multivariate decoding techniques to probe the representational content of neural signals in a time-resolved manner. We observed a representation of expected stimuli in the neural signal well before they were presented, demonstrating that expectations indeed induce a pre-activation of stimulus templates. These results suggest a mechanism for how predictive perception can be neurally implemented.

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