Biology subjects

de Lange, F.

Publications and source records attributed to de Lange, F..

18 recordsLinked to original sources

bioRxiv2026

Lexical surprisal drives pupil dilation during continuous story listening

The pupil famously adjusts its dilation in response to light, but its role extends far beyond this basic sensory function. Its fluctuations index arousal and mental effort, beyond luminance-related dynamics, making it a sensitive marker of internal cognitive states. A growing body of work shows that these pupil-linked signals extend beyond the visual domain. However, which processes drive pupil responses in more naturalistic settings remains unclear as most evidence comes from tightly controlled paradigms that strip away the richness of real-world experience. Language offers a uniquely powerful window into this question, as it can allow us to create rich paradigms without having any visual, i.e. luminance, confounds. Moreover, language comprehension hinges on continuous prediction: listeners constantly generate expectations about upcoming input, and the discrepancy between expectation and actual input - contextual prediction error, or surprisal - carries measurable cognitive costs. Here, we tested the hypothesis that pupil-linked arousal indexes these linguistic surprisal signals during naturalistic listening. We recorded pupil responses while volunteers listened to naturalistic spoken stories in darkness, which were either intact or reversed. Reversed speech preserves the acoustics of the signal while destroying its intelligibility. Pupil dilation selectively tracked lexical surprisal within a late window of 1,700 to 2,350 milliseconds following word onset, in forward, but not control, backward speech. These findings indicate that pupil-linked arousal is tuned to global, context-dependent processing, tracking the cognitive cost of updating a predictive model during naturalistic listening.

neuroscience↗

bioRxiv2026

Generative and discriminative recurrence employ opposing strategies for robust vision

Recurrence is thought to enhance the robustness of biological vision, but how it achieves this feat is largely unknown. Perceptual robustness can be implemented through either lateral connections supporting local integration within a processing stage or feedback connections drawing on broader context from higher stages, and through either a discriminative objective optimising task-relevant classification or a generative objective learning to reconstruct the causes of visual input. But do these different types of recurrence engage distinct computational strategies? As this question is difficult to test in vivo, we endowed convolutional neural networks with varying recurrent architectures and training objectives, and evaluated the consequences for internal representations and behaviour across noise levels. Two distinct computational strategies emerged. Generative feedback followed a reductionist strategy, with representations becoming lower-dimensional through denoising, achieving robustness at moderate noise levels without noise training. Both discriminative lateral and feedback recurrence followed an expansionist strategy, increasing dimensionality to sharpen discriminability without denoising, but requiring noise training to achieve robustness. These dissociable signatures reflect fundamentally different computational mechanisms of robust vision and provide testable predictions for which form of recurrence the brain employs.

neuroscience↗

bioRxiv2025

Predictive Neural Signals during Natural Mandarin Speech Comprehension

Language comprehension requires the continuous transformation of speech into a hierarchy of linguistic units, from phonemes to syllables to words. Because speech unfolds rapidly, listeners are thought to predict upcoming content to keep pace. Previous research has provided empirical evidence for predictive processes operating at multiple linguistic levels during naturalistic listening, including words and phonemes. However, it remains unclear whether prediction also operates concurrently at other levels, such as syllabic and phrasal representation. Here we use Mandarin Chinese to examine the neural signatures of predictive processing across multiple levels of linguistic granularity during natural speech comprehension. Mandarin comprises four representational levels: phoneme, sub-syllabic, character and word, and its lexical identity is largely constrained at the sub-syllabic level, potentially redistributing predictive weight across linguistic representations. We recorded magnetoencephalography (MEG) data while 34 native Mandarin speakers (21 females) listened to a naturalistic audiobook and applied linear regression modeling to examine how linguistic features modulated neural activity. We found that the brain activity of listeners segmented speech into hierarchical units, and that surprisal modulated responses simultaneously across sub-syllabic, character and word levels. In contrast to findings from Indo-European languages, however, we did not observe unique surprisal effects at the lowest, phonemic level. Furthermore, the surprisal of lexical tone in Mandarin modulated brain activity only when integrated with its phonological components. These findings suggest that predictive processing during Mandarin speech comprehension operates concurrently across multiple (though not necessarily all) levels of linguistic granularity, with its implementation shaped by language-specific structural properties. Significance statementLanguage comprehension involves segmenting a continuous acoustic stream into multiple linguistic units, from phonemes to words, and generating predictions at these levels. However, direct neural evidence remains limited regarding how segmentation and prediction operate simultaneously across levels of linguistic granularity, particularly outside Indo-European languages. Using temporal response function analysis of magnetoencephalography data recorded during naturalistic Mandarin listening, we show that predictive processing occurs across multiple levels of linguistic granularity. Specifically, we find evidence for prediction-related neural responses at sub-syllabic, character, and word levels, but not a reliable unique effect at the phonemic level. These results indicate that predictive processing also operates during Mandarin speech comprehension, and its neural implementation is shaped by language-specific structural properties.

neuroscience↗

bioRxiv2025

Narrative Context Shifts Gaze from Visual to Semantic Salience

Humans make over a hundred thousand eye movements daily to gather visual information. But what determines where we look? Current computational models typically link gaze behaviour to visual features of isolated images, but we know that eye movements are also strongly shaped by cognitive goals: Observers gather information that helps them to understand, rather than just represent, the world. Within this framework, observers should focus more on information that updates ones understanding of the environment, and less on what is purely visually salient. Here we tested this hypothesis using a free-viewing paradigm of narratives where we experimentally manipulated the meaningfulness of temporal context by either presenting pictures in a coherent, i.e. correct, order, or in a temporally shuffled order. We developed a novel approach to quantify which visual information is semantically salient (i.e., important for understanding): we separately obtained language narratives for images in stories, and computed the contextual surprisal of visual objects using a large language model. The ability of this semantic saliency model in explaining gaze behaviour was compared to a state-of-the art model of visual saliency (DeepGaze-II). We found that individuals looked relatively more often and more quickly at semantically salient objects when images were presented in coherent compared to shuffled order. In contrast, visual salience did not better account for gaze behaviour in coherent than shuffled order. These findings highlight how internal contextual models guide visual sampling and demonstrate that language models could offer a powerful tool for capturing gaze behavior in richer, meaningful settings.

neuroscience↗

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.

neuroscience↗

bioRxiv2024

Subjective confidence modulates individual BOLD patterns of predictive processing

Humans are adept at extracting and learning sequential patterns from sensory input. This ability enables predictions about future states, resulting in anticipation both on a behavioral and neural level. Stimuli deviating from predictions usually evoke higher neural and hemodynamic activity than predicted stimuli. This difference indicates increased surprise, or prediction error signaling in the context of predictive coding. However, interindividual differences in learning performance and uncertainty have rarely been taken into account. Under Bayesian formulations of cortical function, surprise should be strongest if a subject makes incorrect predictions with high confidence. In the present study, we studied the impact of subjective confidence on imaging markers of predictive processing. Participants viewed visual object sequences of varying predictability over multiple days. After each day, we instructed them to complete partially presented sequences and to rate their confidence in the decision. During fMRI scanning, participants saw sequences that either confirmed predictions, deviated from them, or were random. We replicated findings of increased BOLD responses to surprising input in the ventral visual stream. In line with our hypothesis, response magnitude increased with the level of confidence after the training phase. Interestingly, the activity difference between predictable and random input also scaled with confidence: In the anterior cingulate, we found tentative evidence that predictable sequences elicited higher activity for low levels of confidence, but lower activity for high levels of confidence. In summary, we showed that confidence is a crucial moderator of the link between predictive processing and BOLD activity.

neuroscience↗

bioRxiv2023

Modulation of motion signals across the visual cortical hierarchy during bistable perception

Top-down influences play a central role in perception. In multi-stable sensory phenomena subjective interpretation fluctuates spontaneously over time and the perceptual switches reflect internally driven representations engaging perceptual decision-making. Using functional magnetic resonance imaging (fMRI), we investigated how perceptual states are represented across early visual areas during perception of a bistable moving plaid. While subjects maintained central fixation, perception of the stimulus--two superimposed, obliquely oriented moving gratings--spontaneously alternated between component motion (2 gratings sliding obliquely over each other) and pattern motion (a single coherent pattern moving laterally). Direction-selective clusters were reliably modulated by perceptual state across both early (V1) and higher-order (V2 and the human medial temporal complex (hMT+)) visual regions. Pattern modulation was significantly stronger in primary visual cortex (V1) than in higher-order areas, suggesting that coherent percept formation engages mechanisms beyond simple bottom-up feature integration. Enhanced V1 modulation points to a prominent role for top-down influences from higher-order regions, consistent with predictive coding frameworks in which higher-level areas convey predictions to lower levels to disambiguate sensory input and drive perceptual inference under ambiguous conditions. Eye tracking confirmed that reflexive eye movement direction did not predict perceptual state, excluding an oculomotor confound. Interpretation of the results in light of current knowledge of the physiology of motion integration in early visual areas suggests circuits at which feedback would be predicted to act.

neuroscience↗

bioRxiv2023

The energy metabolic footprint of predictive processing in the human brain

Our expectations about the world influence how we interpret visual information, improving the speed and accuracy of perception. However, the underlying neural activity requires energy which is strictly limited in the brain. While predictive processing is a prevalent framework to explain perception, it remains unclear whether it also serves energy-efficient processing. Here, we employed metabolic brain imaging to quantify oxygen consumption during visual perception under varying levels of input predictability and subjective uncertainty. For three days, we presented participants with object sequences that were either predictable or unpredictable, and assessed their performance and confidence in predicting follow-up objects from partial sequences. On the fourth day, we first tested for behavioral consequences of predictability. We found that subjects detected predictable objects quicker than unpredictable ones. We then quantified cortical oxygen consumption during passive viewing of predictable, unpredictable or surprising sequences. Despite highly similar sensory load, predictable visual input elicited reduced oxygen metabolism when subjects were confident, across both sensory and higher cognitive areas. Crucially, this summed up to cortical energy savings of up to 12%, or 118 mol oxygen per minute, given average brain size. In contrast, cost increases due to surprising input were restricted to a network of fronto-parietal areas. In summary, we found that predictive processing enhances behavioral performance and notably reduces signaling costs, moderated by subjective confidence. This suggests that examining energy efficiency alongside behavioral performance may uncover novel computational strategies of human cognition and behavior.

neuroscience↗

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.

neuroscience↗

bioRxiv2022

Probabilistic forward replay of anticipated stimulus sequences in human primary visual cortex and hippocampus

The ability to recognize and predict future spatiotemporal sequences is vital for perception. It has been proposed that the brain makes intelligent guesses about future inputs by forward replaying these events. However, it is unknown whether and how this mechanism incorporates the probabilistic structure that is inherent to naturalistic environments. Here we tested forward replay in human V1 and hippocampus using a probabilistic cueing paradigm. Participants were exposed to two visual moving dot sequences (A and B) that shared the same starting point. Each stimulus sequence was paired with either a high or a low tone that predicted which sequence would follow with 80% cue validity (probabilistic context) or 50% cue validity (random context). We found that after exposure, the auditory cue together with the starting point triggered simultaneous forward replay of both the likely (A) and the less likely (B) stimulus sequence. Crucially, forward replay preserved the probabilistic relationship of the environment, such that the likely sequence was associated with greater anticipatory V1 activity compared to the less likely stimulus sequence. Analogous to V1, forward replay in hippocampus was also found to preserve the probabilistic cue-sequence relationship. Further, the anterior hippocampus was found to represent the predicted stimulus sequence, irrespective of the input, while the posterior hippocampus revealed a prediction error-like signal that was only observed when predictions were violated. These findings show how mnemonic and sensory areas coordinate predictive representations in probabilistic contexts to improve perceptual processing.

neuroscience↗

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.

neuroscience↗

bioRxiv2020

Object selection by automatic spreading of top-down attentional signals in V1

What is selected when attention is directed to a specific location of the visual field? Theories of object-based attention have suggested that when spatial attention is directed to part of an object, attention does not simply enhance the attended location but automatically spreads to enhance all locations that comprise the object. Here, we tested this hypothesis by reconstructing the distribution of attention from population neuronal activity patterns in V1 using functional magnetic resonance imaging (fMRI) and population-based receptive field mapping. We find that attention spreads from a spatially cued location to the underlying object - and enhances all spatial locations that comprise the object. Importantly, this spreading was also evident when the object was not task-relevant. These data suggest that attentional selection automatically operates at an object level, facilitating the reconstruction of coherent objects from fragmented representations in early visual cortex.

neuroscience↗

bioRxiv2020

Prestimulus alpha power is related to the strength of stimulus representation

Spatial attention can modulate behavioural performance and is associated with several electrophysiological markers. In this study, we used multivariate pattern analysis in electrophysiology data to investigate the effects of covert spatial attention on the quality of stimulus processing and underlying mechanisms. Our results show that covert spatial attention led to (i) an anticipatory alpha power desynchronization; (ii) enhanced stimuli identity information. Moreover, we found that alpha power fluctuations in anticipation of the relevant stimuli boosted and prolonged the coding of stimulus identity.

neuroscience↗

bioRxiv2019

Visual working memory representations in visual and parietal cortex do not remap after eye movements

It has been suggested that our visual system does not only process stimuli that are directly available to our eyes, but also has a role in maintaining information in VWM over a period of seconds. It remains unclear however what happens to VWM representations in the visual system when we make saccades. Here, we tested the hypothesis that VWM representations are remapped within the visual system after making saccades. We directly compared the content of VWM for saccade and no-saccade conditions using MVPA of delay-related activity measured with fMRI. We found that when participants did not make a saccade, VWM representations were robustly present in contralateral early visual cortex. When making a saccade, VWM representations degraded in contralateral V1-V3 after the saccade shifted the location of the remembered grating to the opposite visual field. However, contrary to our hypothesis we found no evidence for the representations of the remembered grating at the saccadic target location in the opposite visual field, suggesting that there is no evidence for remapping of VWM in early visual cortex. Interestingly, IPS showed persistent VWM representations in both the saccade and no-saccade condition. Together, our results indicate that VWM representations in early visual cortex are not remapped across eye movements, potentially limiting the role of early visual cortex in VWM storage. HighlightsO_LIVisual working memory (VWM) representations do not remap after making saccades C_LIO_LIEye movement degrade VWM representations in early visual cortex, limiting the role of early visual cortex in VWM storage C_LIO_LIParietal cortex shows persistent VWM representations across saccades C_LI

neuroscience↗

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.

neuroscience↗

bioRxiv2018

Dissociable laminar profiles of concurrent bottom-up and top-down modulation in the human visual cortex

Recent developments in human neuroimaging make it possible to non-invasively measure neural activity from different cortical layers. This can potentially reveal not only which brain areas are engaged by a task, but also how. Specifically, bottom-up and top-down responses are associated with distinct laminar profiles. Here, we measured lamina-resolved fMRI responses during a visual task designed to induce concurrent bottom-up and top-down modulations via orthogonal manipulations of stimulus contrast and feature-based attention. BOLD responses were modulated by both stimulus contrast (bottom-up) and by engaging feature-based attention (top-down). Crucially, these effects operated at different cortical depths: Bottom-up modulations were strongest in the middle cortical layer, while top-down modulations were strong at all depths, being significantly stronger in deep and superficial layers compared to bottom-up effects. As such, we demonstrate that laminar activity profiles can discriminate between concurrent top-down and bottom-up processing, and are diagnostic of how a brain region is activated.

neuroscience↗

bioRxiv2018

Stimulus predictability does not modulate bottom-up attentional capture

Attention can be involuntarily captured by physically salient stimuli, a phenomenon known as bottom-up attention. Typically, these salient stimuli occur unpredictably in time and space. Therefore, in a series of three behavioral experiments, we investigated the extent to which such bottom-up attentional capture is a function of ones prior expectations. In the context of an exogenous cueing task, we systematically manipulated participants spatial (Experiment 1) or temporal (Experiment 2 and 3) expectations about an uninformative cue, and examined the extent of attentional capture by the cue. We anticipated larger attentional capture for unexpected compared to expected cues. However, while we observed robust attentional capture in all experiments, we did not find any evidence for a modulation of attentional capture by prior expectation. This underscores the automatic and reflexive nature of bottom-up attention.

neuroscience↗

bioRxiv2017

Differential temporal dynamics during visual imagery and perception

Visual perception and imagery rely on similar representations in the visual cortex. During perception, visual activity is characterized by distinct processing stages, but the temporal dynamics underlying imagery remain unclear. Here, we investigated the dynamics of visual imagery in human participants using magnetoencephalography. We show that, contrary to perception, the onset of imagery is characterized by broad temporal generalization. Furthermore, there is consistent overlap between imagery and perceptual processing around 150 ms and from 300 ms after stimulus onset, presumably reflecting completion of the feedforward sweep and perceptual stabilization respectively. These results indicate that during imagery either the complete representation is activated at once and does not include low-level visual areas, or the order in which visual features are activated is less fixed and more flexible than during perception. These findings have important implications for our understanding of the neural mechanisms of visual imagery.

neuroscience↗