Biology subjects

Spaak, E.

Publications and source records attributed to Spaak, E..

At least 19 recordsLinked to original sources

bioRxiv2026

Colourful predictive templates in early visual cortex

Predictive processing theories suggest that our brain constantly predicts incoming sensory information, though the level of granularity and concrete sensory content of these predictions is debated. In this study, we investigate whether predictions in visual cortical areas carry information about colour before the onset of the anticipated stimulus. Thirty-seven human participants of both sexes viewed coloured disc stimuli presented in a predictable sequence, enabling the brain to form expectations about the upcoming colour, while the brain response was tracked with high spatiotemporal resolution (combined electro- and magnetoencephalography). A decoding model trained on a separate colour localizer dataset could successfully reconstruct the predicted colour during the pre-stimulus period, where only a grey placeholder was present. Thereby, our findings demonstrate that early visual regions of the brain form anticipatory representations of colour information, in the absence of external colour input, yet in a representational format similar to veridical sensory input. Significance StatementThe human brain continuously anticipates upcoming events, but the exact features and level of detail of these predictions is a topic of debate. Here we show that when a visual stream has a predictable sequence of colours, the brain pre-activates colour information in early visual cortex before the stimulus appears. Using high-temporal-resolution brain recordings and multivariate decoding analyses, we demonstrate that expected colours can be reconstructed from neural activity several hundreds of milliseconds before the anticipated stimulus is shown. These findings provide direct evidence that perceptual predictions contain concrete sensory content in terms of colour information. By clarifying the features that make up predictive representations, our work advances understanding of how expectations shape perception and guide attention in everyday vision.

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bioRxiv2025

Dynamic competition between selective attention and spatial prediction during visual search

During visual search, we rely on both selective attention and spatial predictions to guide our behavior. However, whether and how these mechanisms interact is largely unclear. Using a contextual cueing paradigm, we investigated whether learning and exploitation of spatial predictive context can occur outside attentional focus. Repeating search scenes enabled distractor context to serve as a contextual cue predicting target location. Participants searched for a target among distractors in two colors: the same as the target-to-be-searched (attended context) or a different color (ignored context). Halfway through the experiments, we changed the target color, thereby altering the attentional status of distractor contexts while maintaining their spatial predictiveness. In Experiment 1, where participants regularly switched between target colors, we found exploitation of spatial predictive context both within and outside attentional focus. However, in Experiment 2, where attention was more stably focused on one target color, only the attended predictive context was exploited before transfer. Intriguingly, after transfer, previously ignored predictive context showed immediate benefits, revealing latent learning. These findings demonstrate a dynamic competition between selective attention and spatial predictions: while learning occurs independently of attention, exploitation may require attentional selection. Our results suggest that selective attention gates the influence of spatial predictions on behavior, with gating strength determined by the stability of attentional control. Significance statementThis research addresses a fundamental question in cognitive science: can we learn from visual information we are not paying attention to? Our findings reveal a dynamic competition between selective attention and spatial prediction that can explain conflicting findings in the literature. We demonstrate that specifically the ability to exploit predictive spatial context depends critically on attentional stability. When required to flexibly switch attentional sets, we can benefit from both attended and unattended predictive information. However, when attention remains focused, unattended information is learned, but only becomes accessible when it is part of our attentional focus. These results reveal that the filtering operation of selective attention and the utilization of spatial prediction during visual search may actually compete dynamically, with selective attention ultimately constraining predictions influence on behavior. This advances our understanding of how these fundamental cognitive mechanisms interact under competition.

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bioRxiv2025

Using magnetoencephalography to track the propagation of 40 Hz invisible spectral flicker

Brain stimulation with novel 40 Hz invisible spectral flicker (ISF) has been proposed as a therapy for Alzheimers disease, with leading hypotheses suggesting local promotion of glymphatic clearance of amyloid as the mechanism of action. Neural signals in the gamma range and their spatial propagation over the brain can be tracked using magnetoencephalography (MEG) with high temporal and good spatial detail. However, stimulation with 40 Hz ISF requires specialised hardware which causes electromagnetic interference (EMI) with MEG equipment. MEG measures the tiny magnetic fields of the brain, which are easily distorted by external magnetic fields. Using MEG to track the propagation of 40 Hz ISF requires multiple modifications to the experimental setup. These include, at least 1) an experimental design that promotes modulation of the neural signal, but not the artifact, 2) removal of all electronics not strictly necessary for light production from the stimulators, and 3) signal processing for 40 Hz EMI artifact suppression. Here, we present an MEG study on the cortical propagation of 40 Hz ISF. In two experiments, we investigate the modulation that visual and non-visual cognitive tasks have on the power and propagation of cortical activity induced by 40 Hz ISF. With the chosen experimental setup and design, the 40 Hz EMI artifact could not be entirely disentangled from the neural signal of interest, thus rendering inference on the spatial propagation of the 40 Hz signal impossible. Further improvements need to be implemented in a follow-up experimental design. We present potential solutions to allow for future investigation of 40 Hz ISF with MEG.

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bioRxiv2024

Saccade onset, not fixation onset, best explains early sensory responses across the human visual cortex during naturalistic vision

Visual processing is traditionally studied using static viewing paradigms in which researchers analyse brain responses to the onsets of a sequence of randomly selected stimuli. Translating this "stimulus onset" approach to active vision paradigms that allow for free eye-movements, researchers often consider fixation onsets as the events that trigger visual activity across the visual system. Here, we test this assumption by analysing a large-scale magnetoencephalography (MEG) dataset with simultaneously recorded eye movements of 5 participants who freely explored thousands of natural images, yielding approximately 200,000 gaze events. We show that saccade-related events, particularly peak saccade curvature, rather than fixation onsets, explain most variance in latency of the early sensory component M100. Further, comparing the classic M100 elicited by stimulus onsets with the M100s elicited during active vision revealed stark differences, both in response to saccade-related and fixation-onset events. This indicates that phenomena discovered using gold standard stimulus onset paradigms do not necessarily translate to natural vision. Our findings challenge the prevailing approach to studying vision in static paradigms and highlight the importance of internally generated and action-driven signals in the dynamics of natural sensory processing.

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bioRxiv2023

Perceptual Foundation and Extension to Phase Tagging for Rapid Invisible Frequency Tagging (RIFT)

Recent years have seen the emergence of a visual stimulation protocol called Rapid Invisible Frequency Tagging (RIFT) in cognitive neuroscience. In RIFT experiments, visual stimuli are presented at a rapidly and sinusoidally oscillating luminance, using high refresh rate projection equipment. Such stimuli result in strong steady-state responses in visual cortex, measurable extracranially using EEG or MEG. The high signal-to-noise ratio of these neural signals, combined with the alleged invisibility of the manipulation, make RIFT a potentially promising technique to study the neural basis of visual processing. In this study, we set out to resolve two fundamental, yet still outstanding, issues regarding RIFT; as well as to open up a new avenue for taking RIFT beyond frequency tagging per se. First, we provide robust evidence that RIFT is indeed subjectively undetectable, going beyond previous anecdotal reports. Second, we demonstrate that full-amplitude luminance or contrast manipulation offer the best tagging results. Third and finally, we demonstrate that, in addition to frequency tagging, phase tagging can reliably be used in RIFT studies, opening up new avenues for constructing RIFT experiments. Together, this provides a solid foundation for using RIFT in visual cognitive neuroscience.

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bioRxiv2023

Spatial predictive context speeds up visual search by biasing local attentional competition

The human visual system is equipped to rapidly and implicitly learn and exploit the statistical regularities in our environment. Within visual search, contextual cueing demonstrates how implicit knowledge of scenes can improve search performance. This is commonly interpreted as spatial context in the scenes becoming predictive of the target location, which leads to a more efficient guidance of attention during search. However, what drives this enhanced guidance is unknown. First, it is under debate whether the entire scene (global context) or more local context drives this phenomenon. Second, it is unclear how exactly improved attentional guidance is enabled by target enhancement and distractor suppression. In the present MEG experiment, we leveraged Rapid Invisible Frequency Tagging (RIFT) to answer these two outstanding questions. We found that the improved performance when searching implicitly familiar scenes was accompanied by a stronger neural representation of the target stimulus, at the cost specifically of those distractors directly surrounding the target. Crucially, this biasing of local attentional competition was behaviorally relevant when searching familiar scenes. Taken together, we conclude that implicitly learned spatial predictive context improves how we search our environment by sharpening the attentional field.

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bioRxiv2022

Cortical activity during naturalistic music listening reflects short-range predictions based on long-term experience

Expectations shape our experience of music. However, the internal model upon which listeners form melodic expectations is still debated. Do expectations stem from Gestalt-like principles or statistical learning? If the latter, does long-term experience play an important role, or are short-term regularities sufficient? And finally, what length of context informs contextual expectations? To answer these questions, we presented human listeners with diverse naturalistic compositions from Western classical music, while recording neural activity using MEG. We quantified note-level melodic surprise and uncertainty using various computational models of music, including a state-of-the-art transformer neural network. A time-resolved regression analysis revealed that neural activity over fronto-temporal areas tracked melodic surprise particularly around 200 ms and 300-500 ms after note onset. This neural surprise response was dissociated from sensory-acoustic and adaptation effects. Neural surprise was best predicted by computational models that incorporated long-term statistical learning - rather than by simple, Gestalt-like principles. Yet, intriguingly, the surprise reflected primarily short-range musical contexts of less than ten notes. We present a full replication of our novel MEG results in an openly available EEG dataset. Together, these results elucidate the internal model that shapes melodic predictions during naturalistic music listening.

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bioRxiv2022

Seeing sounds: Neural mechanisms underlying auditory contributions to visual detection

Sounds enhance the detection of visual stimuli while concurrently biasing an observers decisions. To investigate the neural mechanisms that underlie such multisensory interactions, we decoded time-resolved signal detection theory (SDT) sensitivity and criterion parameters from neural activity using magnetoencalography, while participants performed a visual detection task. Using temporal generalization analysis, we found that sounds improve visual detection by enhancing the maintenance of the most informative perceptual samples over time. In parallel, criterion decoding analyses revealed that sounds evoke patterns of activity that resembled the patterns evoked by an actual visual stimulus. These two complementary mechanisms of audiovisual interaction differed in terms of their automaticity: Whereas the sound-induced enhancement in visual information maintenance depended on participants being actively engaged in a detection task, sounds evoked visual activity patterns in the visual cortex in a bottom-up fashion, challenging the classical assumption that sound- induced reductions in criterion correspond to decision-level biases.

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bioRxiv2021

Reducing the efforts to create reproducible analysis code with FieldTrip

The analysis of EEG and MEG data typically requires a lengthy and complicated sequence of analysis steps, often requiring large amounts of computations, which are ideally represented in analysis scripts. These scripts are often written by researchers without formal training in computer science, resulting in the quality and readability of these analysis scripts to be highly dependent on individual coding expertise and style. Even though the computational outcomes and interpretation of the results can be correct, the inconsistent style and quality of analysis scripts make reviewing the details of the analysis difficult for other researchers that are either involved in the study or not, and the quality of the scripts might compromise the reproducibility of obtained results. This paper describes the design and implementation of a strategy that allows complete reproduction of MATLAB-based scripts with little extra efforts on behalf of the user, which we have implemented as part of the FieldTrip toolbox. Starting from the researchers idiosyncratic pipeline scripts, this new functionality allows researchers to automatically create and publish analysis pipeline scripts in a standardized format, along with all relevant intermediate data. We demonstrate the functionality and validate its effectiveness by applying it to the analysis of a recently published MEG study.

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bioRxiv2020

Temporal prediction elicits rhythmic pre-activation of relevant sensory cortices

Being able to anticipate events before they happen facilitates stimulus processing. The anticipation of the contents of events is thought to be implemented by the elicitation of prestimulus templates in sensory cortex. In contrast, the anticipation of the timing of events is typically associated with entrainment of neural oscillations. It is so far unknown whether and in which conditions temporal expectations interact with feature-based expectations, and, consequently, whether entrainment modulates the generation of content-specific sensory templates. In this study, we investigated the role of temporal expectations in a sensory discrimination task. We presented participants with rhythmically interleaved visual and auditory streams of relevant and irrelevant stimuli while measuring neural activity using magnetoencephalography. We found no evidence that rhythmic stimulation induced prestimulus feature templates. However, we did observe clear anticipatory rhythmic pre-activation of the relevant sensory cortices. This oscillatory activity peaked at behaviourally relevant, in-phase, intervals. Our results suggest that temporal expectations about stimulus features do not behave similarly to explicitly cued, non-rhythmic, expectations; yet elicit a distinct form of modality-specific pre-activation. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=165 SRC="FIGDIR/small/347005v3_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@fce8corg.highwire.dtl.DTLVardef@1c16c3corg.highwire.dtl.DTLVardef@1a90d62org.highwire.dtl.DTLVardef@1adaa17_HPS_FORMAT_FIGEXP M_FIG C_FIG The brain extracts temporal regularities from the environment to anticipate upcoming events. Furthermore, with prior knowledge about their contents, the brain is thought to leverage this by instantiating anticipatory sensory templates. We investigated if sensory templates occur in response to a rhythmic stimulus stream with predictable temporal structure. We found that temporal rhythmic predictions did not induce sensory templates, but rather modulated the excitability in early sensory cortices.

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bioRxiv2020

Scene context impairs perception of semantically congruent objects

Visual scene context is well-known to facilitate the recognition of scene-congruent objects. Interestingly, however, according to the influential theory of predictive coding, scene congruency should lead to reduced (rather than enhanced) processing of congruent objects, compared to incongruent ones, since congruent objects elicit reduced prediction error responses. We tested this counterintuitive hypothesis in two online behavioural experiments with human participants (N = 300). We found clear evidence for impaired perception of congruent objects, both in a change detection task measuring response times as well as in a bias-free object discrimination task measuring accuracy. Congruency costs were related to independent subjective congruency ratings. Finally, we show that the reported effects cannot be explained by low-level stimulus confounds, response biases, or top-down strategy. These results provide convincing evidence for perceptual congruency costs during scene viewing, in line with predictive coding theory. Statement of RelevanceThe theory of the Bayesian brain, the idea that our brain is a hypothesis-testing machine, has become very influential over the past decades. A particularly influential formulation is the theory of predictive coding. This theory entails that stimuli that are expected, for instance because of the context in which they appear, generate a weaker neural response than unexpected stimuli. Scene context correctly predicts congruent scene elements, which should result in lower prediction error. Our study tests this important, counterintuitive, and hitherto not fully tested, hypothesis. We find clear evidence in favour of it, and demonstrate that these congruency costs are indeed evident in perception, and not limited to one particular task setting or stimulus set. Since perception in the real world is never of isolated objects, but always of entire scenes, these findings are important not just for the Bayesian brain hypothesis, but for our understanding of real-world visual perception in general.

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bioRxiv2020

Phasic modulation of visual representations during sustained attention

Sustained attention has long been thought to benefit perception in a continuous fashion, but recent evidence suggests that it affects perception in a discrete, rhythmic way. Periodic fluctuations in behavioral performance over time, and modulations of behavioral performance by the phase of spontaneous oscillatory brain activity point to an attentional sampling rate in the theta or alpha frequency range. We investigated whether such discrete sampling by attention is reflected in periodic fluctuations in the decodability of visual stimulus orientation from magnetoencephalographic (MEG) brain signals. In this exploratory study, human subjects attended one of two grating stimuli while MEG was being recorded. We assessed the strength of the visual representation of the attended stimulus using a support vector machine (SVM) to decode the orientation of the grating (clockwise vs. counterclockwise) from the MEG signal. We tested whether decoder performance depended on the theta/alpha phase of local brain activity. While the phase of ongoing activity in visual cortex did not modulate decoding performance, theta/alpha phase of activity in the FEF and parietal cortex, contralateral to the attended stimulus did modulate decoding performance. These findings suggest that phasic modulations of visual stimulus representations in the brain are caused by frequency- specific top-down activity in the fronto-parietal attention network.

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bioRxiv2020

No exploitation of temporal predictive context during visual search

The human visual system can rapidly extract regularities from our visual environment, generating predictive context. It has been shown that spatial predictive context can be used during visual search. We set out to see whether observers can additionally exploit temporal predictive context, using an extended version of a contextual cueing paradigm. Though we replicated the contextual cueing effect, repeating search scenes in a structured order versus a random order yielded no additional behavioural benefit. This was true both for participants who were sensitive to spatial predictive context, and for those who were not. We argue that spatial predictive context during visual search is more readily learned and subsequently exploited than temporal predictive context, potentially rendering the latter redundant. In conclusion, unlike spatial context, temporal context is not automatically extracted and used during visual search.

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bioRxiv2020

Rapid invisible frequency tagging reveals nonlinear integration of auditory and visual semantic information

During communication in real-life settings, the brain integrates information from auditory and visual modalities to form a unified percept of our environment. In the current magnetoencephalography (MEG) study, we used rapid invisible frequency tagging (RIFT) to generate steady-state evoked fields and investigated the integration of audiovisual information in a semantic context. We presented participants with videos of an actress uttering action verbs (auditory; tagged at 61 Hz) accompanied by a gesture (visual; tagged at 68 Hz, using a projector with a 1440 Hz refresh rate). Integration difficulty was manipulated by lower-order auditory factors (clear/degraded speech) and higher-order visual factors (congruent/incongruent gesture). We identified MEG spectral peaks at the individual (61/68 Hz) tagging frequencies. We furthermore observed a peak at the intermodulation frequency of the auditory and visually tagged signals (fvisual - fauditory = 7 Hz), specifically when lower-order integration was easiest because signal quality was optimal. This intermodulation peak is a signature of nonlinear audiovisual integration, and was strongest in left inferior frontal gyrus and left temporal regions; areas known to be involved in speech-gesture integration. The enhanced power at the intermodulation frequency thus reflects the ease of lower-order audiovisual integration and demonstrates that speech-gesture information interacts in higher-order language areas. Furthermore, we provide a proof-of-principle of the use of RIFT to study the integration of audiovisual stimuli, in relation to, for instance, semantic context.

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bioRxiv2020

A Bayesian and efficient observer model explains concurrent attractive and repulsive history biases in visual perception

Perceptual decisions can be repelled away from (repulsive adaptation) or attracted towards recent visual experience (attractive serial dependence). It is currently unclear whether and how these repulsive and attractive biases interact during visual processing and what computational principles may underlie these history dependencies. In the current study, we disentangle repulsive and attractive biases by exploring the respective timescales over which current visual processing is influenced by previous experience. Across four experiments, we find that perceptual decisions about stimulus orientation are concurrently attracted towards the short-term perceptual history and repelled from stimuli experienced up to minutes into the past. We show that the temporal pattern of short-term attraction and long-term repulsion cannot be captured by an ideal Bayesian observer model alone. Instead, it is well captured by an ideal observer model with efficient encoding and Bayesian decoding of visual information in a slowly changing environment. Concurrent attractive and repulsive history biases in perceptual decisions may thus be the consequence of the need for visual processing to simultaneously satisfy constraints of both efficiency and stability.

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bioRxiv2019

Familiarity increases processing speed in the visual system

Familiarity with a stimulus leads to an attenuated neural response to the stimulus. Alongside this attenuation, recent studies have also observed a truncation of stimulus-evoked activity for familiar visual input. One proposed function of this truncation is to rapidly put neurons in a state of readiness to respond to new input. Here, we examined this hypothesis by presenting human participants with target stimuli that were embedded in rapid streams of familiar or novel distractor stimuli at different speeds of presentation, while recording brain activity using magnetoencephalography (MEG) and measuring behavioral performance. We investigated the temporal and spatial dynamics of signal truncation and whether this phenomenon bears relationship to participants ability to categorize target items within a visual stream. Behaviorally, target categorization performance was markedly better when the target was embedded within familiar distractors, and this benefit became more pronounced with increasing speed of presentation. Familiar distractors showed a truncation of neural activity in the visual system, and this truncation was strongest for the fastest presentation speeds. Moreover, neural processing of the target was stronger when it was preceded by familiar distractors. Taken together, these findings suggest that truncation of neural responses for familiar items may result in stronger processing of relevant target information, resulting in superior perceptual performance.\n\nSignificance statementThe visual response to familiar input is attenuated more rapidly than for novel input. Here we find that this truncation of the neural response for familiar input is strongest for very fast image presentations. We also find a tentative function for this truncation: the neural response to a target image that is embedded within distractors is much greater when the distractors are familiar than when they are novel. Similarly, target categorization performance is much better when the target is embedded within familiar distractors, and this advantage is most obvious for very fast image presentations. This suggests that neural truncation helps to rapidly put neurons in a state of readiness to respond to new input.

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bioRxiv2019

Previously reward-associated stimuli capture spatial attention in the absence of changes in the corresponding sensory representations as measured with MEG

Studies of selective attention typically consider the role of task goals or physical salience, but recent work has shown that attention can also be captured by previously reward-associated stimuli, even if they are currently task-irrelevant. One theory underlying this value-driven attentional capture (VDAC) is that reward-associated stimulus representations may undergo plasticity in sensory cortex, thereby automatically capturing attention during early processing. To test this, we used magnetoencephalography to probe whether stimulus location and identity representations in sensory cortex are modulated by reward learning. We furthermore investigated the time-course of these neural effects, and their relationship to behavioural VDAC. Male and female human participants first learned stimulus-reward associations. Next, we measured VDAC in a separate task by presenting these stimuli in the absence of reward contingency, and probing their effects on the processing of separate target stimuli presented at different time lags. Using time-resolved multivariate pattern analysis, we found that learned value modulated the spatial selection of previously rewarded stimuli in posterior visual and parietal cortex from [~]260ms after stimulus onset. This value modulation was related to the strength of participants behavioural VDAC effect and persisted into subsequent target processing. Furthermore, we found a spatially invariant value signal from [~]340ms. Importantly, learned value did not influence cortical signatures of early processing (i.e., earlier than [~]200ms), nor did it influence the decodability of the identity of previously rewarded stimuli. Our results suggest that VDAC is underpinned by learned value signals which modulate spatial selection throughout posterior visual and parietal cortex. We further suggest that VDAC can occur in the absence of changes in early visual processing in cortex. Significance statementAttention is our ability to focus on relevant information at the expense of irrelevant information. It can be affected by previously learned but currently irrelevant stimulus-reward associations, a phenomenon termed "value-driven attentional capture" (VDAC). The neural mechanisms underlying VDAC remain unclear. It has been speculated that reward learning induces visual cortical plasticity which modulates early visual processing to capture attention. Although we find that learned value modulates spatial signals in visual cortical areas, an effect which correlates with VDAC, we find no relevant signatures of changes in early visual processing in cortex.

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bioRxiv2019

Implicit learning and exploitation of regularities involve hippocampal and prefrontal theta activity

Observers rapidly and seemingly automatically learn to predict where to expect relevant items when those items are repeatedly presented in the same spatial context. This form of statistical learning in visual search has been studied extensively using a paradigm known as contextual cueing. The neural mechanisms underlying the learning and exploiting of such regularities remain unclear. We sought to elucidate these by examining behaviour and recording neural activity using magneto-encephalography (MEG) while observers were implicitly acquiring and exploiting statistical regularities. Computational modelling of behavioural data suggested that after repeated exposures to a spatial context, participants behaviour was marked by an abrupt switch to an exploitation strategy of the learnt regularities. MEG recordings showed that the initial learning phase was associated with larger hippocampal theta band activity for repeated scenes, while the subsequent exploitation phase showed larger prefrontal theta band activity for these repeated scenes. Strikingly, the behavioural benefit of repeated exposures to certain scenes was inversely related to explicit awareness of such repeats, demonstrating the implicit nature of the expectations acquired. This elucidates how theta activity in the hippocampus and prefrontal cortex underpins the implicit learning and exploitation of spatial statistical regularities to optimize visual search behaviour.

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