Biology subjects

Stokes, M. G.

Publications and source records attributed to Stokes, M. G..

At least 19 recordsLinked to original sources

bioRxiv2025

Human Beta Oscillations Reflect Magnitude and Fidelity of Priority Shifts in Working Memory.

Flexible prioritisation in working memory (WM) is supported by neural oscillations in frontal and sensory brain areas, but the roles of different oscillations remain poorly understood. Recordings in humans suggest an interplay between prefrontal slow frequency (2-8Hz) and posterior alpha-band (10Hz) oscillations regulating top-down control and retrieval of WM representations, respectively. Complementary work, primarily in non-human primates, suggests an additional role for beta (15-30Hz) oscillations in clearing or inhibiting stimuli from entering WM. Here we investigated the role of neural oscillations in prioritising WM content using electroencephalography (EEG) as participants (humans of any sex) performed a task requiring frequent priority switches between two memorized oriented bars. Behavioural performance revealed switch costs, which scaled with the angular distance between the two items, suggesting that priority shifts are modulated by shift magnitude. Time-frequency analyses revealed increased frontal theta (4-8Hz) and decreased central-parietal beta (15-25Hz) power during switches. Crucially, only beta power scaled with the magnitude of the priority shift and predicted the fidelity of neural decoding of the newly prioritized item during subsequent recall. Theta power, by contrast, was elevated on switch trials but did not vary with update magnitude or decoding strength, suggesting a more general role in signaling control demands. Our findings highlight a particular and previously overlooked role for beta-band oscillations in the flexible prioritisation of WM content. Significance StatementWorking memory permits flexible switching between mental representations, so we can focus on what is most relevant at the moment. Different brain rhythms in frontal control and sensory memory storage areas orchestrate switches but their respective roles remain unclear. Here, using EEG, we show that power reductions of [~]20Hz oscillations over central-parietal regions, usually associated with the motor system, closely track the magnitude of the required switch and the fidelity of the prioritized memory. In contrast, slower 4-8Hz (theta-band) activity over frontal regions increases during priority switches but tracks neither magnitude nor fidelity. Our findings suggest a unique function for central-parietal beta oscillations in the flexible control of working memory.

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bioRxiv2025

Alpha and Beta Oscillations Mediate the Effect of Motivation on Neural Coding of Cognitive Flexibility

Cognitive flexibility is crucial for adaptive human behaviour. Prior studies have analysed the effect of reward on cognitive flexibility; however, the neural mechanisms underlying these effects remain largely unknown. This study explores how reward influences neural oscillations and how these changes impact behavioural performance. Using time-frequency decomposition, we examined electroencephalographic data from participants engaged in rule-guided task-switching with varying reward prospects. Higher anticipated rewards lead to greater desynchronisation of alpha (8-12Hz) and beta (20-30Hz) oscillations, which in turn correlated with improved task performance. Both alpha power and event-related potential (ERP) coding of reward independently predicted reward-based performance improvements, suggesting distinct mechanisms supporting proactive control. These findings underscore the unique contributions of neural oscillations in mediating motivational effects on cognitive flexibility.

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bioRxiv2025

Working memory shapes neural geometry in human EEG over learning

Working memory has been traditionally studied as a passive storage for information. However, recent advances have suggested that working memory is prospective rather than retrospective, meaning that its content undergoes transformations that will support future behaviour. One perspective that underscores this notion conceptualises memory processes as a computational resource that can be used to reduce the complexity of computation at decision time. Here, we explore this perspective by examining whether the process of maintenance shapes neural geometry and leads to low-dimensional representations during storage and later decision time. We recorded EEG in 25 human participants who learnt to solve a XOR task. We hypothesised that separating task features by a working memory delay would result in participants temporally decomposing the XOR computation, by prospectively processing one of the task features early in trial time. In line with our predictions, participants transformed the first feature from a sensory to an abstract format and maintained this pre-processed information throughout the delay. This process was related to the low-dimensional representation required at decision time early in learning, a representation that has recently been shown to support later cross-generalisation. These results demonstrate that low-dimensional representations, elsewhere associated with slow learning, might also provide a mechanism for maintenance processes in working memory.

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bioRxiv2024

Frontopolar cortex stimulation induces prolonged disruption to counterfactual processing: insights from altered local field potentials

Frontopolar cortex (FPC) is a large, anterior sub-region of prefrontal cortex found in both humans and non-human primates (NHPs) and is thought to support monitoring the value of switching between alternative goals. However, the neuronal mechanisms underlying this function are unclear. Here we used multielectrode arrays to record the local field potentials (LFPs) in the FPC of two macaques performing a Wisconsin Card Sorting Test analogue and found that bursts of gamma and beta in FPC tracked counterfactual not current rule value. Moreover, we show that brief high-frequency microstimulation to a single trial causally affects both LFP activity in FPC, as well as rule-guided decision-making across successive trials. Following stimulation of FPC we observed reduced exploration of the counterfactual rule pre-rule-change, as well as a delayed adaptation to the newly relevant following post-rule-change. A similar, multi-trial time-course disturbance to beta and gamma activity within FPC was also induced following single-trial microstimulation. These findings conclusively link neuronal activity in FPC with behavioural monitoring of the value of counterfactual rules and provide neural mechanistic insights into how FPC supports rule-based decision-making. Significance statementIncreasing evidence from human and non-human primates has prompted theories linking FPC with the control of exploration during decision-making. However, it is current unclear how the neuronal activity within frontal pole supports exploratory decision-making processes. Here we show that rhythmic activity, in the beta and gamma bands, recorded from FPC is correlated both with outcome of the previous choice, and the value of switching to an alternative choice. Furthermore, we show that disrupting beta and gamma activity within FPC causally influences exploratory decision-making: initially decreasing exploration before impairing adaptation to abstract rule changes. Together these findings provide the first mechanistic insight into how the neuronal activity within FPC can support exploratory behaviour.

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bioRxiv2023

Ignorance is bliss: effects of noise and metaboliccost on cortical task representations

Cognitive flexibility requires both the encoding of task-relevant and the ignoring of task-irrelevant stimuli. While the neural coding of task-relevant stimuli is increasingly well understood, the mechanisms for ignoring task-irrelevant stimuli remain poorly understood. Here, we study how task performance and biological constraints jointly determine the coding of relevant and irrelevant stimuli in neural circuits. Using mathematical analyses and task-optimized recurrent neural networks, we show that neural circuits can exhibit a range of representational geometries depending on the strength of neural noise and metabolic cost. By comparing these results with recordings from primate prefrontal cortex (PFC) over the course of learning, we show that neural activity in PFC changes in line with a minimal representational strategy. Specifically, our analyses reveal that the suppression of dynamically irrelevant stimuli is achieved by activity-silent, sub-threshold dynamics. Our results provide a normative explanation as to why PFC implements an adaptive, minimal representational strategy.

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bioRxiv2023

Learning shapes neural geometry in the prefrontal cortex

The relationship between the geometry of neural representations and the task being performed is a central question in neuroscience1-6. The primate prefrontal cortex (PFC) is a primary focus of inquiry, as it can encode information with geometries that either rely on past experience7-13 or are experience agnostic3,14-16. One hypothesis is that PFC representations should evolve with learning4,17,18, from a format that supports exploration of all possible task rules to a format that minimises the encoding of task-irrelevant features4,17,18 and supports generalisation7,8. Here we test this idea by recording neural activity from PFC when learning a new rule ( XOR rule) from scratch. We show that PFC representations progress from being high dimensional, nonlinear and randomly mixed to low dimensional and rule selective. Upon generalising the rule to novel stimuli, these representations further evolve into an abstract, stimulus-invariant geometry. These findings reconcile previously conflicting accounts of PFC function by demonstrating how neural representations adapt across distinct stages of learning.

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bioRxiv2022

A recurrent neural network model of prefrontal brain activity during a working memory task

When multiple items are held in short-term memory, cues that retrospectively prioritise one item over another (retro-cues) can facilitate subsequent recall. However, the neural and computational underpinnings of this effect are poorly understood. One recent study recorded neural signals in the macaque lateral prefrontal cortex (LPFC) during a retro-cueing task, contrasting delay-period activity before (pre-cue) and after (post-cue) retrocue onset. They reported that in the pre-cue delay, the individual stimuli were maintained in independent subspaces of neural population activity, whereas in the post-cue delay, the prioritised items were rotated into a common subspace, potentially allowing a common readout mechanism. To understand how such representational transitions can be learnt through error minimisation, we trained recurrent neural networks (RNNs) with supervision to perform an equivalent cued-recall task. RNNs were presented with two inputs denoting conjunctive colour-location stimuli, followed by a pre-cue memory delay, a location retrocue, and a post-cue delay. We found that the orthogonal-to-parallel geometry transformation observed in the macaque LPFC emerged naturally in RNNs trained to perform the task. Interestingly, the parallel geometry only developed when the cued information was required to be maintained in short-term memory for several cycles before readout, suggesting that it might confer robustness during maintenance. We extend these findings by analysing the learning dynamics and connectivity patterns of the RNNs, as well as the behaviour of models trained with probabilistic cues, allowing us to make predictions for future studies. Overall, our findings are consistent with recent theoretical accounts which propose that retrocues transform the prioritised memory items into a prospective, action-oriented format. Author SummaryMany real-world scenarios require us to manipulate the contents of memory to guide behaviour. For example, when grocery shopping, initially we might keep all the items from our shopping list in mind (i.e., in our short-term memory). However, once we spot the dairy aisle, we might want to extract, or prioritise, the items from our list that belong to this category. The question of how such prioritisation of memory items is achieved in the brain is a topic of active research. A recent study in monkeys provided evidence that initially, individual memory items are kept from interfering with one another by being encoded by different brain activity patterns. However, following a contextual cue (akin to the dairy aisle sign), the short-term memory representations of the prioritised items are reconfigured into a format that collapses across the irrelevant differences and highlights aspects relevant for action. In this study, we modelled the emergence of these representational changes in an artificial neural network model. Our results help explain how such processes can be learnt from experience and why they might emerge in the biological brain.

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bioRxiv2021

Optimal information loading into working memory in prefrontal cortex

Working memory involves the short-term maintenance of information and is critical in many tasks. The neural circuit dynamics underlying working memory remain poorly understood, with different aspects of prefrontal cortical (PFC) responses explained by different putative mechanisms. By mathematical analysis, numerical simulations, and using recordings from monkey PFC, we investigate a critical but hitherto ignored aspect of working memory dynamics: information loading. We find that, contrary to common assumptions, optimal loading of information into working memory involves inputs that are largely orthogonal, rather than similar, to the persistent activities observed during memory maintenance, naturally leading to the widely observed phenomenon of dynamic coding in PFC. Using a novel, theoretically principled metric, we show that PFC exhibits the hallmarks of optimal information loading. We also find that optimal loading emerges as a general dynamical strategy in task-optimized recurrent neural networks. Our theory unifies previous, seemingly conflicting theories of memory maintenance based on attractor or purely sequential dynamics, and reveals a normative principle underlying dynamic coding.

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bioRxiv2021

Neural reinstatement tracks object-based attentional selection in working memory

Attention can be allocated in working memory (WM) to select and privilege relevant content. It is unclear whether attention selects individual features or whole objects in WM. Here, we used behavioural measures, eye-tracking and electroencephalography (EEG) to test the hypothesis that attention spreads between an objects features in WM. Twenty-six participants completed a WM task that asked them to recall the angle of one of two oriented, coloured bars after a delay while EEG and eye-tracking data was collected. During the delay, an orthogonal incidental task cued the colour of one item for a match/mismatch judgement. On congruent trials (50%), the cued item was probed for subsequent orientation recall; on incongruent trials (50%), the other memory item was probed. As predicted, selecting the colour of an object in WM brought other features of the cued object into an attended state as revealed by EEG decoding, oscillatory -power, gaze bias and improved orientation recall performance. Together, the results show that attentional selection spreads between an objects features in WM, consistent with object-based attentional selection. Analyses of neural processing at recall revealed that the selected object was automatically compared with the probe, whether it was the target for recall or not. This provides a potential mechanism for the observed benefits of non-predictive cueing in WM, where a selected item is prioritised for subsequent decision-making.

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bioRxiv2021

Multiple and Dissociable Effects of Sensory History on Working-Memory Performance

AO_SCPLOWBSTRACTC_SCPLOWBehavioural reports of sensory information are biased by stimulus history. The nature and direction of such serial-dependence biases can differ between experimental settings - both attractive and repulsive biases towards previous stimuli have been observed. How and when these biases arise in the human brain remains largely unexplored. They could occur either via a change in sensory processing itself and/or during post-perceptual processes such as maintenance or decision-making. To address this, we analysed behavioural and magnetoencephalographic data from a working-memory task in which participants were sequentially presented with two randomly oriented gratings, one of which was cued for recall at the end of the trial. Behavioural responses showed evidence for two distinct biases: 1) a within-trial repulsive bias away from the previously encoded orientation on the same trial, and 2) a between-trial attractive bias towards the task-relevant orientation on the previous trial. Multivariate classification of stimulus orientation revealed that neural representations during stimulus encoding were biased away from the previous grating orientation, regardless of whether we considered the within- or between-trial prior orientation - despite opposite effects on behaviour. These results suggest that repulsive biases occur at the level of sensory processing and can be overridden at post-perceptual stages to result in attractive biases in behaviour.

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bioRxiv2021

Integrating reward information for prospective behaviour

Value-based decision-making is often studied in a static context, where participants decide which option to select from those currently available. However, everyday life often involves an additional dimension: deciding when to select to maximise reward. Recent evidence suggests that agents track the latent reward of an option, updating changes in their latent reward estimate, to achieve appropriate selection timing (latent reward tracking). However, this strategy can be difficult to distinguish from one in which the optimal selection time is estimated in advance, allowing an agent to wait a pre-determined amount of time before selecting, without needing to monitor an options latent reward (distance-to-goal tracking). Here we show that these strategies can in principle be dissociated. Human brain activity was recorded using electroencephalography (EEG) while female and male participants performed a novel decision task. Participants were shown an option and decided when to select it, as its latent reward changed from trial-to-trial. While the latent reward was uncued, it could be estimated using cued information about the options starting value and value growth rate. We then used representational similarity analysis to assess whether EEG signals more closely resembled latent reward tracking or distance-to-goal tracking. This approach successfully dissociated the strategies in this task. Starting value and growth rate were translated into a distance-to-goal signal, far in advance of selecting the option. Latent reward could not be independently decoded. These results demonstrate the feasibility of using high temporal resolution neural recordings to identify internally computed decision variables in the human brain. Significance StatementReward-seeking behaviour involves acting at the right time. However, the external world does not always tell us when an action is most rewarding, necessitating internal representations that guide action timing. Specifying this internal neural representation is challenging because it might stem from a variety of strategies, many of which make similar predictions about brain activity. This study used a novel approach to test whether alternative strategies could be dissociated in principle. Using representational similarity analysis, we were able to distinguish between candidate internal representations for selection timing. This shows how pattern analysis methods can be used to measure latent decision information in non-invasive neural data.

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bioRxiv2020

Decoding visual colour from scalp electroencephalography measurements

Recent advances have made it possible to decode various aspects of visually presented stimuli from patterns of scalp EEG measurements. As of recently, such multivariate methods have been commonly used to decode visual-spatial features such as location, orientation, or spatial frequency. In the current study, we show that it is also possible to track visual colour processing by using Linear Discriminant Analysis on patterns of EEG activity. Building on other recent demonstrations, we show that colour decoding: (1) reflects sensory qualities (as opposed to, for example, verbal labelling) with a prominent contribution from posterior electrodes contralateral to the stimulus, (2) conforms to a parametric coding space, (3) is possible in multi-item displays, and (4) is comparable in magnitude to the decoding of visual stimulus orientation. Through subsampling our data, we also provide an estimate of the approximate number of trials and participants required for robust decoding. Finally, we show that while colour decoding can be sensitive to subtle differences in luminance, our colour decoding results are primarily driven by measured colour differences between stimuli. Colour decoding opens a relevant new dimension in which to track visual processing using scalp EEG measurements, while bypassing potential confounds associated with decoding approaches that focus on spatial features.

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bioRxiv2020

A hierarchy of functional states in working memory

Extensive research has examined how information is maintained in working memory (WM), but it remains unknown how WM is used to guide behaviour. We addressed this question by combining human electrophysiology with pattern analyses, cognitive modelling, and a task requiring maintenance of two WM items and priority shifts between them. This enabled us to discern neural states coding for immediately and prospectively task-relevant items, and to examine their contribution to WM-based decisions. We identified two qualitatively different states: a functionally active state encoded only immediately task-relevant items and closely tracked the quality of evidence integration on the current trial. In contrast, prospectively relevant items were encoded in a functionally latent state that did not engage with ongoing processing but tracked memory precision at longer time scales. These results delineate a hierarchy of functional states, whereby latent memories supporting general maintenance are transformed into active decision-circuits to guide flexible behaviour.

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bioRxiv2019

Comparing the prioritisation of items and feature-dimensions in visual working memory

Selective attention can be directed not only to external sensory inputs, but also to internal sensory representations held within visual working memory (VWM). To date, this has been studied predominantly following retrospective cues directing attention to particular items, or their locations in memory. In addition to item-level attentional prioritisation, recent studies have shown that selectively attending to feature dimensions in VWM can also improve memory recall performance. However, no study to date has directly compared item-based and feature-based attention in VWM, nor their neural bases. Here, we compared the benefits of retrospective cues (retro-cues) that were directed either at a multi-feature item or at a feature-dimension that was shared between two spatially segregated items. Behavioural results revealed qualitatively similar attentional benefits in both recall accuracy and response time, but also showed that cueing benefits were larger following item cues. Concurrent EEG measurements further revealed a similar attenuation of posterior alpha oscillations following both item and feature retro-cues when compared to non-informative, neutral retro-cues. We argue that attention can act flexibly to prioritise the most relevant information - at either the item or the feature-level - to optimise ensuing memory-based task performance, and we discuss the implications of the observed commonalities and differences between item-level and feature-level prioritisation in VWM.

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bioRxiv2019

Drifting codes within a stable coding scheme for working memory

Working memory (WM) is important to maintain information over short time periods to provide some stability in a constantly changing environment. However, brain activity is inherently dynamic, raising a challenge for maintaining stable mental states. To investigate the relationship between WM stability and neural dynamics, we used electroencephalography to measure the neural response to impulse stimuli during a WM delay. Multivariate pattern analysis revealed representations were both stable and dynamic: there was a clear difference in neural states between time-specific impulse responses, reflecting dynamic changes, yet the coding scheme for memorized orientations was stable. This suggests that a stable subcomponent in WM enables stable maintenance within a dynamic system. A stable coding scheme simplifies readout for WM-guided behaviour, whereas the low-dimensional dynamic component could provide additional temporal information. Despite having a stable subspace, WM is clearly not perfect - memory performance still degrades over time. Indeed, we find that even within the stable coding scheme, memories drift during maintenance. When averaged across trials, such drift contributes to the width of the error distribution.

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bioRxiv2019

Impulse responses reveal unimodal and bimodal access to visual and auditory working memory

It is unclear to what extent sensory processing areas are involved in the maintenance of sensory information in working memory (WM). Previous studies have thus far relied on finding neural activity in the corresponding sensory cortices, neglecting potential activity-silent mechanisms such as connectivity-dependent encoding. It has recently been found that visual stimulation during visual WM maintenance reveals WM-dependent changes through a bottom-up neural response. Here, we test whether this impulse response is uniquely visual and sensory-specific. Human participants (both sexes) completed visual and auditory WM tasks while electroencephalography was recorded. During the maintenance period, the WM network was perturbed serially with fixed and task-neutral auditory and visual stimuli. We show that a neutral auditory impulse-stimulus presented during the maintenance of a pure tone resulted in a WM-dependent neural response, providing evidence for the auditory counterpart to the visual WM findings reported previously. Interestingly, visual stimulation also resulted in an auditory WM-dependent impulse response, implicating the visual cortex in the maintenance of auditory information, either directly, or indirectly as a pathway to the neural auditory WM representations elsewhere. In contrast, during visual WM maintenance only the impulse response to visual stimulation was content-specific, suggesting that visual information is maintained in a sensory-specific neural network, separated from auditory processing areas.\n\nSignificance StatementWorking memory is a crucial component of intelligent, adaptive behaviour. Our understanding of the neural mechanisms that support it has recently shifted: rather than being dependent on an unbroken chain of neural activity, working memory may rely on transient changes in neuronal connectivity, which can be maintained efficiently in activity-silent brain states. Previous work using a visual impulse stimulus to perturb the memory network has implicated such silent states in the retention of line orientations in visual working memory. Here, we show that auditory working memory similarly retains auditory information. We also observed a sensory-specific impulse response in visual working memory, while auditory memory responded bi-modally to both visual and auditory impulses, possibly reflecting visual dominance of working memory.

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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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bioRxiv2017

Intrinsic neuronal dynamics predict distinct functional roles during working memory

Working memory (WM) is characterized by the ability to maintain stable representations over time; however, neural activity associated with WM maintenance can be highly dynamic. We explore whether complex population coding dynamics during WM relate to the intrinsic temporal properties of single neurons in lateral prefrontal cortex (lPFC), the frontal eye fields (FEF) and lateral intraparietal cortex (LIP) of two monkeys (Macaca mulatta). We found that cells with short timescales carried memory information relatively early during memory encoding in lPFC; whereas long timescale cells played a greater role later during processing, dominating coding in the delay period. We also observed a link between functional connectivity at rest and intrinsic timescale in FEF and LIP. Our results indicate that individual differences in the temporal processing capacity predicts complex neuronal dynamics during WM; ranging from rapid dynamic encoding of stimuli to slower, but stable, maintenance of mnemonic information.

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