Biology subjects

Olivers, C. N. L.

Publications and source records attributed to Olivers, C. N. L..

16 recordsLinked to original sources

bioRxiv2026

Repetition Dissociates Pointer and Content-based Representations in Visual Working Memory: Contrasting the CDA with Multivariate Shape Decoding

Memorizing a new phone number or address is hard at first, but becomes easier with repetition, as information shifts from working memory to long-term memory. Here we investigated how repetition affects the storage and transition of different aspects of mnemonic information by comparing univariate neural markers of active object storage with multivariate decoding of memory content. Thirty participants encoded lateralized stimuli from a continuous shape space into memory. Memory items were repeated six times in a row to induce learning. In line with earlier work, EEG recordings revealed that repetition led to a reduction in contralateral delay activity (CDA), a measure of active storage that has been taken to reflect a pointer-like representation of the individual object or its original source. In contrast, shape decoding during the retention and also after an impulse perturbation remained constant across repetitions. These results suggest that learning over repetitions reflects the abolishment of active and individuated object memory representations while passive, source-independent memory representations are retained. HighlightsO_LIWe recorded EEG as participants maintained a shape item, drawn form a continuous shape space, in working memory. These memory items repeated six times in a row before they changed to a new item. C_LIO_LIWe replicated the well-known CDA decrement effect from repetition, a process thought to index participants shift from relying on working memory to long term memory. C_LIO_LIMultivariate decoding of shape identity was stable across repetitions, neither decreasing nor reliably increasing with repetition. This was true both after encoding and also following a task irrelevant ping. C_LIO_LIThese results dissociate the popular CDA ERP, a measure of memory load, from actual working memory content decodable via multivariate approaches. C_LI

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bioRxiv2025

When do peripherally encoded memories generalize in visual working memory?

Visual working memory has been shown to transition from location-specific to spatially generalized representations. It remains unclear what the time course of this generalization is and to which information processing stages and signals it is linked - specifically whether it is tied to sensory or report stages. Here we used EEG to investigate spatial generalisation of peripherally encoded stimuli before and after an item was selected for report. Thirty healthy participants memorized two orientations presented serially at fifteen degrees eccentricity to the left and right of central fixation. One of the two items was subsequently cued as task relevant. During the delays, impulse signals were inserted to trace memoranda in potentially activity-reduced states. We observed that prior to the cue, patterns of activity transitioned from location-specific spatially generalized states from approximately 400-600 ms after onset in broadband voltage but not in oscillatory alpha signals. The picture was more mixed after the selection cue, with some evidence for locations-specific and spatially generalized codes in both alpha and broadband voltage. We conclude that the first stages of spatial generalization occur at sensory, pre-report levels of processing, while late stages are associated with selecting response-relevant spatial features.

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bioRxiv2024

Effects of context changes on memory reactivation

While the influence of context on long-term memory (LTM) is well-documented, its effects on the interaction between working memory (WM) and LTM remain less understood. In this study, we explored these interactions using a delayed match-to-sample task, where participants (6 Male, 16 Female) encountered the same target object across six consecutive trials, facilitating the transition from WM to LTM. During half of these target repetitions, the background color changed. We measured the WM storage of the target using the contralateral delay activity (CDA) in electroencephalography (EEG). Our results reveal that task-irrelevant context changes trigger the reactivation of long-term memories in WM. This reactivation may be attributed to content-context binding in WM and hippocampal pattern separation. Significance StatementUnderstanding the mechanisms of memory updating in response to changing contexts is vital because context plays a pivotal role in shaping long-term memories. This study demonstrates, for the first time, that an irrelevant context change triggers the reactivation of learned memories in visual working memory. This observation underscores the importance of multi-memory interactions during context updating. Challenging traditional memory models that postulate mandatory reactivation of long-term memories upon each use, our results instead reveal a selective reactivation process, especially during transitions to new environments. This finding elucidates the adaptive nature of memories and enhances our understanding of memory storage and retrieval processes.

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bioRxiv2023

Comparing Neural Correlates of Memory Encoding and Maintenance for Foveal and Peripheral Stimuli

Visual working memory is believed to rely on top-down attentional mechanisms that sustain active sensory representations in early visual cortex. However, both bottom-up sensory input and top-down attentional modulations thereof have been shown to be biased towards the fovea, at the expense of the periphery, and initially peripheral percepts may even be assimilated by foveal processing. This raises the question whether and how visual working memory differs for central and peripheral input. To address this, we conducted a delayed orientation recall task in which an orientation stimulus was presented either at the center of the screen or at 15{degrees} eccentricity to the left or right. Response accuracy, electroencephalographic (EEG) activity and gaze position were recorded from 30 participants. Accuracy was slightly but significantly higher for foveal versus peripheral memories. Orientation decoding analyses of the EEG signals revealed a clear dissociation between early sensory and later maintenance signals. While sensory signals were clearly decodable for the central location, they were not for peripheral locations. In contrast, maintenance signals were decodable to an equal extent for both foveal and peripheral memories, suggesting comparable top-down components regardless of eccentricity. Moreover, while memory representations were initially spatially specific and reflected in voltage fluctuations, later in the maintenance period they generalized across locations, as emerged in alpha oscillations, thus revealing a dynamic transformation within memory. Moreover, these transformed representations remained accessible through sensory impulse-driven perturbations, unveiling the underlying memory state. The eccentricity-driven dissociation between disparate sensory and common maintenance representations indicates that storage activity patterns as measured by EEG reflect signals beyond primary visual cortex.

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bioRxiv2022

A matter of availability: Neural representations of task-relevant stimulus features are sharper when stimuli are memorized rather than perceived.

Our visual environment is relatively stable over time and an optimized visual system ought to capitalize on this by not devoting any representational resources to objects that are still present. Subjective experience, however, suggests that externally available (i.e., perceived) information is more strongly represented in neural signals than memorized information. To distinguish between these possibilities, we use EEG multivariate pattern analysis to quantify the strength of representation of task-relevant features (color or spatial frequency) in anticipation of a change-detection task. Perceptual availability was manipulated between experimental blocks by either keeping the stimulus on the screen during a two second delay period (perception) or removing it shortly after its initial presentation for the same time period (memory). We find that task-relevant (i.e., attended) memorized features are more strongly represented than irrelevant features. More importantly, we find significantly weaker representations for available (perceived and attended) features than for unavailable (memorized and attended) features. Contrary to what subjective experience suggests, our findings demonstrate that vividly perceived and attended stimuli elicit weaker neural representations (in terms of detectable multivariate information) than stimuli maintained in visual working memory. We hypothesize that an efficient visual system spends little of its limited resources on the internal representation of information that is externally available anyway.

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bioRxiv2020

Memory for stimulus durations is not bound to spatial information

Different theories have been proposed to explain how the human brain derives an accurate sense of time. One specific class of theories, intrinsic clock theories, postulate that temporal information of a stimulus is represented much like other features such as color and location, bound together to form a coherent percept. Here we explored to what extent this holds for temporal information after it has been perceived and is held in working memory for subsequent comparison. We recorded EEG of participants who were asked to time stimuli at lateral positions of the screen followed by comparison stimuli presented in the center. Using well-established markers of working memory maintenance, we investigated whether the usage of temporal information evoked neural signatures that were indicative of the location where the stimuli had been presented, both during maintenance and during comparison. Behavior and neural measures including the contralateral delay activity, lateralized alpha suppression and decoding analyses through time all supported the same conclusion: the representation of location was strongly involved during perception of temporal information, but when temporal information was to be used for comparison it no longer showed a relation to spatial information. These results support a model where the initial perception of a stimulus involves intrinsic computations, but that this information is subsequently translated to a stimulus-independent format to be used to further guide behavior.

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bioRxiv2020

Neural repetition suppression modulates time perception: evidence from electrophysiology and pupillometry

Human time perception is malleable and subject to many biases. For example, it has repeatedly been shown that stimuli that are physically intense or that are unexpected seem to last longer. Two hypotheses have been proposed to account for such biases: one states that these temporal illusions are the result of heightened arousal which speeds up neural clock dynamics, whereas the alternative magnitude coding account states that the magnitude of sensory responses causally modulates perceived durations. Common experimental paradigms used to study temporal biases can not dissociate between these accounts, as arousal and sensory magnitude covary and modulate each other. Here, we present two temporal discrimination experiments where flashing stimuli demarcated the start and end of a to-be-timed interval. These stimuli could either be in the same or in a different location, which led to different sensory responses due to neural repetition suppression. Crucially, changes and repetitions were fully predictable, allowing us to explore effects of sensory response magnitude without changes in arousal or surprise. Intervals with changing markers were perceived as lasting longer than those with repeating markers. We measured EEG (Experiment 1) and pupil size (Experiment 2), and found that temporal perception related to changes in event-related potentials (P2) and pupil constriction, both of which have been related to responses in the sensory cortex. Conversely, correlates of surprise and arousal (P3 amplitude and pupil dilation) were unaffected by stimulus repetitions and changes. These results demonstrate that sensory magnitude affects time perception even under constant levels of arousal.

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bioRxiv2019

Flexible working memory through selective gating and attentional tagging

Working memory is essential for intelligent behavior as it serves to guide behavior of humans and nonhuman primates when task-relevant stimuli are no longer present to the senses. Moreover, complex tasks often require that multiple working memory representations can be flexibly and independently maintained, prioritized, and updated according to changing task demands. Thus far, neural network models of working memory have been unable to offer an integrative account of how such control mechanisms are implemented in the brain and how they can be acquired in a biologically plausible manner. Here, we present WorkMATe, a neural network architecture that models cognitive control over working memory content and learns the appropriate control operations needed to solve complex working memory tasks. Key components of the model include a gated memory circuit that is controlled by internal actions, encoding sensory information through untrained connections, and a neural circuit that matches sensory inputs to memory content. The network is trained by means of a biologically plausible reinforcement learning rule that relies on attentional feedback and reward prediction errors to guide synaptic updates. We demonstrate that the model successfully acquires policies to solve classical working memory tasks, such as delayed match-to-sample and delayed pro-saccade/antisaccade tasks. In addition, the model solves much more complex tasks including the hierarchical 12-AX task or the ABAB ordered recognition task, which both demand an agent to independently store and updated multiple items separately in memory. Furthermore, the control strategies that the model acquires for these tasks subsequently generalize to new task contexts with novel stimuli. As such, WorkMATe provides a new solution for the neural implementation of flexible memory control. Author SummaryWorking Memory, the ability to briefly store sensory information and use it to guide behavior, is a cornerstone of intelligent behavior. Existing neural network models of Working Memory typically focus on how information is stored and maintained in the brain, but do not address how memory content is controlled: how the brain can selectively store only stimuli that are relevant for a task, or how different stimuli can be maintained in parallel, and subsequently replaced or updated independently according to task demands. The models that do implement control mechanisms are typically not trained in a biologically plausible manner, and do not explain how the brain learns such control. Here, we present WorkMATe, a neural network architecture that implements flexible cognitive control and learns to apply these control mechanisms using a biologically plausible reinforcement learning method. We demonstrate that the model acquires control policies to solve a range of both simple and more complex tasks. Moreover, the acquired control policies generalize to new situations, as with human cognition. This way, WorkMATe provides new insights into the neural organization of Working Memory beyond mere storage and retrieval.

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bioRxiv2019

Humans can efficiently look for, but not select multiple visual objects

The human brain recurrently prioritizes task-relevant over task-irrelevant visual information. A central, question is whether multiple objects can be prioritized simultaneously. To answer this, we let observers search for two colored targets among distractors. Crucially, we independently varied the number of target colors that observers anticipated, and the number of target colors actually used to distinguish the targets in the display. This enabled us to dissociate the preparation of selection mechanisms from the actual engagement of such mechanisms. Multivariate classification of electroencephalographic activity allowed us to track selection of each target separately across time. The results revealed only small neural and behavioral costs associated with preparing for selecting two objects, but substantial costs when engaging in selection. Further analyses suggest this cost is the consequence of neural competition resulting in limited parallel processing, rather than a serial bottleneck. The findings bridge diverging theoretical perspectives on capacity limitations of feature-based attention.

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bioRxiv2019

The Role of Proactive and Reactive Cognitive Control for Target Selection in Multiple-Target Search

Cognitive control can involve proactive (preparatory) and reactive (corrective) mechanisms. Using a gaze-contingent eye tracking paradigm combined with fMRI, we investigated the involvement of these different modes of control and their underlying neural networks, when switching between different targets in multiple-target search. Participants simultaneously searched for two possible targets presented among distractors, and selected one of them. In one condition, only one of the targets was available in each display, so that the choice was imposed, and reactive control would be required. In the other condition, both targets were present, giving observers free choice over target selection, and allowing for proactive control. Switch costs emerged only when targets were imposed and not when target selection was free. We found differential levels of activity in the frontoparietal control network depending on whether target switches were free or imposed. Furthermore, we observed core regions of the default mode network to be active during target repetitions, indicating reduced control on these trials. Free and imposed switches jointly activated parietal and posterior frontal cortices, while free switches additionally activated anterior frontal cortices. These findings highlight unique contributions of proactive and reactive control during visual search.

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bioRxiv2019

High-pass filtering artifacts in multivariate classification of neural time series data

0.BackgroundTraditionally, EEG/MEG data are high-pass filtered and baseline-corrected to remove slow drifts. Minor deleterious effects of high-pass filtering in traditional time-series analysis have been well-documented, including temporal displacements. However, its effects on time-resolved multivariate pattern classification analyses (MVPA) are largely unknown. New MethodTo prevent potential displacement effects, we extend an alternative method of removing slow drift noise - robust detrending - with a procedure in which we mask out all cortical events from each trial. We refer to this method as trial-masked robust detrending. ResultsIn both real and simulated EEG data of a working memory experiment, we show that both high-pass filtering and standard robust detrending create artifacts that result in the displacement of multivariate patterns into activity silent periods, particularly apparent in temporal generalization analyses, and especially in combination with baseline correction. We show that trial-masked robust detrending is free from such displacements. Comparison with Existing Method(s)Temporal displacement may emerge even with modest filter cut-off settings such as 0.05 Hz, and even in regular robust detrending. However, trial-masked robust detrending results in artifact-free decoding without displacements. Baseline correction may unwittingly obfuscate spurious decoding effects and displace them to the rest of the trial. ConclusionsDecoding analyses benefits from trial-masked robust detrending, without the unwanted side effects introduced by filtering or regular robust detrending. However, for sufficiently clean data sets and sufficiently strong signals, no filtering or detrending at all may work adequately. Implications for other types of data are discussed, followed by a number of recommendations.

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bioRxiv2018

Beta and theta oscillations differentially support free versus forced control over target selection in visual search

Many important situations require human observers to simultaneously search for more than one object. Despite a long history of research into visual search, the behavioral and neural mechanisms associated with multiple-target search are poorly understood. Here we test the novel theory that the efficiency of looking for multiple targets critically depends on the mode of cognitive control the environment affords to the observer. We used an innovative combination of EEG and eye tracking while participants searched for two targets, within two different contexts: Either both targets were present in the search display and observers were free to prioritize either one of them, thus enabling proactive control over selection; or only one of the two targets would be present in each search display, which requires reactive control to reconfigure selection when the wrong target is prioritized. During proactive control, both univariate and multivariate signals of beta-band (15-35 Hz) power suppression prior to display onset predicted switches between target selections. This signal originated over midfrontal and sensorimotor regions and has previously been associated with endogenous state changes. In contrast, imposed target selections requiring reactive control elicited prefrontal power enhancements in the delta/theta-band (2-8 Hz), but only after display onset. This signal predicted individual differences in associated oculomotor switch costs, reflecting reactive reconfiguration of target selection. The results provide compelling evidence that multiple target representations are differentially prioritized during visual search, and for the first time reveal distinct neural mechanisms underlying proactive and reactive control over multiple-target search.\n\nSignificance StatementSearching for more than one object in complex visual scenes can be detrimental for search performance. While perhaps annoying in daily life, this can have severe consequences in professional settings such as medical and security screening. Previous research has not yet resolved whether multiple-target search involves changing priorities in what people attend to, and how such changes are controlled. We approached these questions by concurrently measuring cortical activity and eye movements using EEG and eye tracking, while observers searched for multiple possible targets. Our findings provide the first unequivocal support for the existence of two modes of control during multiple-target search, which are expressed in qualitatively distinct time-frequency signatures of the EEG both before and after visual selection.

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bioRxiv2018

Current and future goals are represented in opposite patterns in object-selective cortex

Adaptive behavior requires the separation of current from future goals in working memory. We used fMRI of object-selective cortex to determine the representational (dis)similarities of memory representations serving current and prospective perceptual tasks. Participants remembered an object drawn from three possible categories as the target for one of two consecutive visual search tasks. A cue indicated whether the target object should be looked for first (currently relevant), second (prospectively relevant), or if it could be forgotten (irrelevant). Prior to the first search, representations of current, prospective and irrelevant objects were similar, with strongest decoding for current representations compared to prospective (Experiment 1) and irrelevant (Experiment 2). Remarkably, during the first search, prospective representations could also be decoded, but revealed anti-correlated voxel patterns compared to currently relevant representations of the same category. We propose that the brain separates current from prospective memories within the same neuronal ensembles through opposite representational patterns.

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bioRxiv2018

Unattended but actively stored: EEG dynamics reveal a dissociation between selective attention and storage in working memory

Selective attention plays a prominent role in prioritizing information in working memory (WM), improving performance for attended representations. However, it remains unclear what the consequences of selection are for the maintenance of unattended WM representations, and whether this results in information loss. Here we tested the hypothesis that within WM, selectively attending to an item and the decision to stop storing other items involve independent mechanisms. We recorded EEG while participants performed a WM recall task in which the item most likely to be tested was cued retrospectively. By manipulating retro-cue reliability (i.e. the ratio of valid to invalid cue trials) we varied the incentive to retain uncued items. Contralateral alpha power suppression, a proxy for attention, indicated that, initially, the cued item was attended equally following high and low reliability cues, but attention was sustained throughout the delay period only after high reliability cues. Furthermore, contralateral delay activity (CDA), a proxy for storage, indicated that non-cued items were dropped sooner from WM after highly reliability cues than after cues with low reliability. These results show that attention and storage in WM are distinct processes that can behave differently depending on the relative importance of WM representations, as expressed in dissociable EEG signals.

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bioRxiv2017

Working memory implements distinct maintenance mechanisms depending on task goals

Working memory is the function by which we temporarily maintain information to achieve current task goals. Models of working memory typically debate where this information is stored, rather than how it is stored. Here we ask instead what neural mechanisms are involved in storage, and how these mechanisms change as a function of task goals. Participants either had to reproduce the orientation of a memorized bar (continuous recall task), or identify the memorized bar in a search array (visual search task). The sensory input and retention interval were identical in both tasks. Next, we used decoding and forward modeling on multivariate electroencephalogram (EEG) and time-frequency decomposed EEG to investigate which neural signals carry more informational content during the retention interval. In the continuous recall task, working memory content was preferentially carried by induced oscillatory alpha-band power, while in the visual search task it was more strongly carried by the distribution of evoked (consistently elevated and non-oscillatory) EEG activity. To show the independence of these two signals, we were able to remove informational content from one signal without affecting informational content in the other. Finally, we show that the tuning characteristics of both signals change in opposite directions depending on the current task goal. We propose that these signals reflect oscillatory and elevated firing-rate mechanisms that respectively support location-based and object-based maintenance. Together, these data challenge current models of working memory that place storage in particular regions, but rather emphasize the importance of different distributed maintenance signals depending on task goals.\n\nSignificance statement (120 words)Without realizing, we are constantly moving things in and out of our minds eye, an ability also referred to as working memory. Where did I put my screwdriver? Do we still have milk in the fridge? A central question in working memory research is how the brain maintains this information temporarily. Here we show that different neural mechanisms are involved in working memory depending on what the memory is used for. For example, remembering what a bottle of milk looks like invokes a different neural mechanism from remembering how much milk it contains: the first one primarily involved in being able to find the object, and the other one involving spatial position, such as the milk level in the bottle.

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bioRxiv2016

Multivariate EEG analyses support high-resolution tracking of feature-based attentional selection

The primary electrophysiological marker of feature-based selection is the N2pc, a lateralized posterior negativity emerging around 180-200 ms. As it relies on hemispheric differences, its ability to discriminate the locus of focal attention is severely limited. Here we demonstrate that multivariate analyses of raw EEG data provide a much more fine-grained spatial profile of feature-based target selection. When training a pattern classifier to determine target position from EEG, we were able to decode target positions on the vertical midline, which cannot be achieved using standard N2pc methodology. Next, we used a forward encoding model to construct a channel tuning function that describes the continuous relationship between target position and multivariate EEG in an eight-position display. This model can spatially discriminate individual target positions in these displays and is fully invertible, enabling us to construct hypothetical topographic activation maps for target positions that were never used. When tested against the real pattern of neural activity obtained from a different group of subjects, the constructed maps from the forward model turned out statistically indistinguishable, thus providing independent validation of our model. Our findings demonstrate the power of multivariate EEG analysis to track feature-based target selection with high spatial and temporal precision.\n\nSignificance StatementFeature-based attentional selection enables observers to find objects in their visual field. The spatiotemporal profile of this process is difficult to assess with standard electrophysiological methods, which rely on activity differences between cerebral hemispheres. We demonstrate that multivariate analyses of EEG data can track target selection across the visual field with high temporal and spatial resolution. Using a forward model, we were able to capture the continuous relationship between target position and EEG measurements, allowing us to reconstruct the distribution of cortical activity for target locations that were never shown during the experiment. Our findings demonstrate the existence of a temporally and spatially precise EEG signal that can be used to study the neural basis of feature-based attentional selection.

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