Biology subjects

Haynes, J.-D.

Publications and source records attributed to Haynes, J.-D..

At least 19 recordsLinked to original sources

bioRxiv2026

Clutter does not affect the spatial tuning of * category representations in human object-selective cortex *

Natural vision is frequently impaired when the visual field is crowded with multiple competing objects. One common interpretation of this clutter interference is that large receptive fields in high-level visual cortex make it hard to separate objects from their surround. This view predicts less interference for spatially localized representations; therefore, classifiers trained under clutter might rely more on such localized representations. Here we tested this by measuring participants brain signals with fMRI while they viewed objects presented either alone or within cluttered arrays. Consistent with prior work, category decoding accuracy was significantly reduced in clutter. However, classifiers trained directly on cluttered displays were not spatially more localized. Instead, they generalized robustly across spatial positions, comparable to classifiers trained on isolated objects. This finding challenges the idea that clutter preferentially disrupts position-tolerant representations.

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bioRxiv2025

Visual working memory representations of naturalistic images in early visual cortex are not sensory-like

For a long time, working memory was considered to reflect sustained activity in prefrontal and parietal areas. This has been challenged by the "sensory recruitment model" according to which sensory areas are involved in maintaining working memory representations. The main support for this comes from the finding that working memory contents can be decoded from early sensory areas during memory delay periods. However, the availability of stimulus-related information in sensory regions does not reveal whether this information is encoded in a sensory format, i.e. in the same way as sensory stimuli. Alternatively, working memory contents could be encoded in independent formats or even potentially undergo dynamic changes throughout the delay. Here, we test this question directly by requiring participants to briefly memorise naturalistic object-scenes. We directly compared the way early visual regions encoded the contents during perception and working memory maintenance. As in previous studies, we found robust stimulus-related information in early visual cortex throughout the delay. However, despite continuously robust information, the encoding of memory contents in the later delay period did not occur in the same format as during pure perception. Thus, despite the fact that sensory areas have working-memory-related information, the format of this information is not strictly sensory-like throughout the delay.

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bioRxiv2024

Temporal dynamics and readout latency in perception and iconic memory

Following the offset of complex visual stimuli, rich stimulus information remains briefly available to the observer, reflecting a rapidly decaying iconic memory trace. Traditionally, iconic memory decay is assumed to begin with stimulus offset. Instead, here we found that available information begins decaying already when cues are presented in the final stage of stimulus presentation. Using closely spaced ("micro-timed") readout cues and a theoretical model of information availability, we observed that a cue has to be presented around 10-30 milliseconds before stimulus offset in order to access the full sensory information. We suggest that this does not reflect an early loss in sensory encoding, but instead it is a consequence of a latency in the processing of the cue which postpones the readout of the sensory representation by 10-30 milliseconds. Our analysis also shows that spatial proximity of items in complex arrays impacts sensory representation during both perceptual encoding and initial memory decay. Overall, these results provide a theoretical and empirical characterization of the readout from visual representations, and offer a detailed insight into the transition from perception into iconic memory.

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bioRxiv2024

Neural dynamics of visual working memory representation during sensory distraction

Recent studies have provided evidence for the concurrent encoding of sensory percepts and visual working memory contents (VWM) across visual areas; however, it has remained unclear how these two types of representations are concurrently present. Here, we reanalyzed an open-access fMRI dataset where participants memorized a sensory stimulus while simultaneously being presented with sensory distractors. First, we found that the VWM code in several visual regions did not fully generalize between different time points, suggesting a dynamic code. A more detailed analysis revealed that this was due to shifts in coding spaces across time. Second, we collapsed neural signals across time to assess the degree of interference between VWM contents and sensory distractors, specifically by testing the alignment of their encoding spaces. We find that VWM and feature-matching sensory distractors are encoded in coding spaces that do not fully overlap, but the separation decreases when distractors negatively impact behavioral performance in recalling the target. Together, these results indicate a role of dynamic coding and temporally stable coding spaces in helping multiplex perception and VWM within visual areas.

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bioRxiv2024

Neural Correlates of Different Randomization Tasks

In some cases, when we are making decisions, the available choices can appear to be equivalent. When this happens, our choices appear not to be constrained by external factors and instead we can believe to be selecting "randomly". Furthermore, randomness is sometimes even explicitly required by task conditions such as in random sequence generation (RSG) tasks. This is a challenging task that involves the coordination of multiple cognitive processes, which can include the inhibition of habitual choice patterns and monitoring of the running choice sequence. It has been shown that random choices are strongly influenced by the way they are instructed. This raises the question whether the brain mechanisms underlying random selection also differ between different task instructions. To assess this, we measured brain activity while participants were engaging in three different variations of a sequence generation task: Based on previous work, participants were instructed to either (1) "generate a random sequence of choices", (2) "simulate a fair coin toss", or (3) "choose freely". Our results reveal a consistent frontoparietal activation pattern that is shared across all tasks. Specifically, increased activity was observed in bilateral inferior and right middle frontal gyrus, left pre-supplementary motor area, bilateral inferior parietal lobules and portions of anterior insular cortex in both hemispheres. Activity in the mental coin toss condition was higher in right dorsolateral prefrontal cortex, left (pre-) supplementary motor area, a portion of right inferior frontal gyrus, bilateral superior parietal lobules and bilateral anterior insula. Additionally, our multivariate analysis revealed a distinct region in the right frontal pole to be predictive of the outcome of choices, but only when randomness was explicitly instructed. These results emphasize that different randomization tasks involve both shared and unique neural mechanisms. Thus, even seemingly similar randomization behavior can be produced by different neural pathways.

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bioRxiv2023

Dopamine and neuromodulation shorten the latency from motor intention to execution in Parkinson's disease

The ability to initiate volitional action is fundamental to human behaviour. Loss of dopaminergic neurons in Parkinsons disease is associated with impaired action initiation, also termed akinesia. Both dopamine and subthalamic deep brain stimulation (DBS) can alleviate akinesia, but the underlying mechanisms are unknown. An important question is whether dopamine and DBS facilitate de novo build-up of neural dynamics for motor execution or accelerate existing cortical movement initiation signals through shared modulatory circuit effects. Answering these questions can provide the foundation for new closed-loop neurotherapies with adaptive DBS, but the objectification of neural processing delays prior to performance of volitional action remains a significant challenge. To overcome this challenge, we studied readiness potentials and trained brain signal decoders on invasive neurophysiology signals in 25 DBS patients (12 female) with Parkinsons disease during performance of self-initiated movements. Combined sensorimotor cortex electrocorticography (ECoG) and subthalamic local field potential (LFP) recordings were performed OFF therapy (N=22), ON dopaminergic medication (N=18) and ON subthalamic deep brain stimulation (N=8). This allowed us to compare their therapeutic effects on neural latencies between the earliest cortical representation of movement intention as decoded by linear discriminant analysis classifiers and onset of muscle activation recorded with electromyography (EMG). In the hypodopaminergic OFF state, we observed long latencies between motor intention and motor execution for readiness potentials and machine learning classifications. Both, dopamine and DBS significantly shortened these latencies, hinting towards a shared therapeutic mechanism for alleviation of akinesia. To investigate this further, we analysed directional cortico-subthalamic oscillatory communication with multivariate granger causality. Strikingly, we found that both therapies independently shifted cortico-subthalamic oscillatory information flow from antikinetic beta (13-35 Hz) to prokinetic theta (4-10 Hz) rhythms, which was correlated with latencies in motor execution. Our study reveals a shared brain network modulation pattern of dopamine and DBS that may underlie the acceleration of neural dynamics for augmentation of movement initiation in Parkinsons disease. Instead of producing or increasing preparatory brain signals, both therapies modulate oscillatory communication. These insights provide a link between the pathophysiology of akinesia and its therapeutic alleviation with oscillatory network changes in other non-motor and motor domains, e.g. related to hyperkinesia or effort and reward perception. In the future, our study may inspire the development of clinical brain computer interfaces based on brain signal decoders to provide temporally precise support for action initiation in patients with brain disorders.

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bioRxiv2023

Dynamic layer-specific processing in the prefrontal cortex during working memory

The dorsolateral prefrontal cortex (dlPFC) is reliably engaged in working memory (WM). Evidence from non-human primates indicates that the dlPFC comprises different cytoarchitectonic layers that play distinct roles in WM subprocesses; yet the functional role of the dlPFCs laminar circuitry in human WM is not well understood. In this study, participants completed a delayed-match-to-sample WM task while undergoing functional magnetic resonance imaging (fMRI) at ultra-high resolution, which allowed us to examine layer-specific responses of the dlPFC to manipulations in WM load and motor response. We conducted univariate and multivariate analyses across all periods of the WM task: encoding, delay and retrieval. First, we observed that superficial layers activate stronger than deep layers to higher WM load during the delay period. This aligns with earlier work showing preferential superficial layer activation to WM manipulation and as such may indicate lamina-specific activation of the frontoparietal network to heightened task demands more generally. Second, we found that superficial layers show higher decoding of WM load differences than deep layers during the retrieval period. In this context, we could show that decoding of WM load in the superficial layer exhibited dynamic changes across the encoding, delay and retrieval period of the task, indicative of separate WM control processes that occur on the WM content. Last, we found that superficial and deep layers are both non-differentially involved in the motor response, contradicting earlier findings of a preferential deep layer activation in humans. Taken together, our results provide new insights into the functional laminar circuitry of the dlPFC during WM and provide further support for a dynamic account of dlPFC coding.

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bioRxiv2023

Working memory and imagery in early visual cortex

It has been suggested that visual images are memorized across brief periods of time by vividly imagining them as if they still were there. In line with this, the contents of both working memory and visual imagery are known to be encoded already in early visual cortex. If these signals in early visual areas were indeed to reflect a combined imagery and memory code, one would predict them to be weaker for individuals with reduced visual imagery vividness. Here, we systematically investigated this question in two groups of participants. Strong and weak imagers were asked to remember images across brief delay periods. We were able to reliably reconstruct the memorized stimuli from early visual cortex during the delay. Importantly, in contrast to the prediction, the quality of reconstruction was equally accurate for both strong and weak imagers. The decodable information also closely reflected behavioral precision in both groups, suggesting it could contribute to behavioral performance, even in the extreme case of completely aphantasic individuals. Our data thus suggest that working memory signals in early visual cortex can be present even in the (near) absence of phenomenal imagery.

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bioRxiv2023

Encoding of continuous perceptual choices in human early visual cortex

Research on the neural mechanisms of perceptual decision-making has typically focused on simple categorical choices, say between two alternative motion directions. Studies on such discrete alternatives have often suggested that choices are encoded either in a motor-based or in an abstract, categorical format in regions beyond sensory cortex. However, many sensory features are graded rather than discrete, raising the question how choices are encoded when they span the full sensory continuum. Here we assessed this using motion stimuli that could vary anywhere between 0{degrees} and 360{degrees}. We employed a combination of neuroimaging and encoding models based on Gaussian Process Regression to assess how either stimuli or choices were encoded in brain responses. We found that single-voxel tuning patterns could be used to reconstruct the trial-by-trial physical direction of motion as well as the participants continuous choices. Importantly, these continuous choice signals were primarily observed in early visual areas. The tuning properties in this region generalized between choice encoding and stimulus encoding, even for reports that reflected pure guessing. We found only little information related to the decision outcome in regions beyond visual cortex, such as parietal cortex, possibly because our task did not involve differential motor preparation. This could suggest that decisions for continuous stimuli take can place already in sensory brain regions, potentially using similar mechanisms to the sensory recruitment in visual working memory.

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bioRxiv2022

Indirect decoding of behavior from brain signals via reconstruction of experimental conditions

The data acquired during a functional magnetic resonance imaging (fMRI) experiment usually comprise experimental conditions, brain signals and behavioral responses. This reflects the underlying causal flow where the experimental conditions evoke brain responses that in turn result in behavior. In multivariate analyses, a common approach is to focus on the second step of that chain and to decode behavioral responses from brain signals. However, a different approach would be to first reconstruct the experimental conditions from brain signals and in turn use these to predict behavior. While this indirect approach would go against the causal chain of events, it might work better under certain circumstances, especially when the experimental conditions evoke much stronger measurable brain signals than the overt motor behavior. Here we tested this question directly by assessing the various mappings between conditions, brain signals and behavior in an open dataset. We found that the path of first decoding experimental conditions works surprisingly well, even though in our example data set, it is still outperformed by directly decoding the behavior from brain responses.

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bioRxiv2022

Performance reserves in brain-imaging-based phenotype prediction

Machine learning studies have shown that various phenotypes can be predicted from structural and functional brain images. However, in most such studies, prediction performance ranged from moderate to disappointing. It is unclear whether prediction performance will substantially improve with larger sample sizes or whether insufficient predictive information in brain images impedes further progress. Here, we systematically assess the effect of sample size on prediction performance using sample sizes far beyond what is possible in common neuroimaging studies. We project 3-9 fold improvements in prediction performance for behavioral and mental health phenotypes when moving from one thousand to one million samples. Moreover, we find that moving from single imaging modalities to multimodal input data can lead to further improvements in prediction performance, often on par with doubling the sample size. Our analyses reveal considerable performance reserves for neuroimaging-based phenotype prediction. Machine learning models may benefit much more from extremely large neuroimaging datasets than currently believed.

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bioRxiv2021

Categorical working memory codes in human visual cortex

Working memory contents are represented in neural activity patterns across multiple regions of the cortical hierarchy. It has remained unclear to which degree this reflects a specialization for different levels of abstraction. Here, we demonstrate that for color stimuli categorical codes are already present at the level of extrastriate visual cortex (V4 and VO1). Interestingly, this categorical coding was observed during working memory, but not during perception.

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bioRxiv2021

Lifelong musical activity is associated with multi-domain cognitive and brain benefits in older adults

1AO_SCPLOWBSTRACTC_SCPLOWRegular musical activity as a highly-stimulating lifestyle activity is proposed to be protective against age-related cognitive decline and Alzheimers disease (AD). This study investigated associations between lifelong regular musical instrument playing, late-life cognitive abilities and brain morphology in older adults. We show that musical activity over the life course is associated with better global cognition, working memory, executive functions, language, and visuospatial abilities accounting for reserve proxies. Playing music is not significantly associated with gray matter volume in regions most affected by aging and AD. Selectively in the musically active participants, multi-domain cognitive abilities were enhanced with preserved gray matter volume in frontal and temporal regions. Our correlational findings suggest that playing a musical instrument may improve the recruitment of existing brain resources to facilitate late-life cognitive capacities. We propose that engaging in regular musical activity could serve as a low-threshold multimodal enrichment strategy that may promote cognitive resilience in advanced age.

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bioRxiv2021

Confusions regarding stochastic fluctuations and accumulators in spontaneous movements

Experiments on choice-predictive brain signals have played an important role in the debate on free will. In a seminal study, Benjamin Libet and colleagues found that a negative-going EEG signal, the readiness potential (RP), can be observed over motor-related brain regions hundreds of ms before the retrospectively reported time of the conscious decision to move. If the onset of the readiness potential is taken as an indicator of the "brains decision to move" this could mean that this decision to move is made early, by unconscious brain activity, rather than later, at the time when the subject believes to have decided. However, an alternative kind of interpretation, involving ongoing stochastic fluctuations, has recently been brought to light. One such model, the stochastic decision model (SDM), takes its inspiration from accumulator models of perceptual decision making. It suggests that the RP originates from an accumulation of ongoing stochastic fluctuations. In this view the decision happens only at a much later stage when an accumulated noisy signal (plus imperative) reaches a threshold. Here we clarify a number of confusions regarding both the evidence for the stochastic decision model as well as the interpretation that it offers. We will explore several points that we feel are in need of clarification: (a) that the empirical evidence for the role of stochastic fluctuations is so far only indirect; (b) that the relevance of evidence from animal studies is unclear; (c) that a model that is deterministic during the accumulation stage can explain the data in a similar way; (d) that the primary focus in the literature has been on the role of random fluctuations whereas the deterministic aspects of the model have been largely ignored; (e) that contrary to the original interpretation the deterministic component of the model is the dominant input into the accumulator; (f) that there is confusion regarding the role of "imperative" and "evidence" in the SDM and its link to perceptual decision making; and finally (g) as with other stochastic accumulator processes the question of whether the decision happens early or late depends on the nature of the noise fluctuations, specifically, whether they reflect "absolute" or "epistemic" randomness. Our aim is not to rehabilitate the role of the RP in the free will debate. Rather we aim to address some confusions regarding the evidence for accumulators playing a role in these preparatory brain processes.

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bioRxiv2020

Suppress me if you can: neurofeedback of the readiness potential

Voluntary movements are usually preceded by a slow, negative-going brain signal over motor areas, the so-called readiness potential (RP). To date, the exact nature and causal role of the RP in movement preparation have remained heavily debated. One important open question is whether people can exert conscious control over their RP, for example by learning to suppress it. If people were able to initiate spontaneous movements without eliciting an RP, this would challenge the idea that the RP is a necessary stage of the causal chain leading up to a voluntary movement. We tested the ability of participants to control the magnitude of their RP in a neurofeedback experiment. Participants performed self-initiated movements and after every movement they were provided with immediate feedback about the magnitude of their RP. They were asked to find a mental strategy to perform voluntary movements such that the RPs were as small as possible. We found no evidence that participants were able to to willfully modulate or suppress their RPs while still eliciting voluntary movements. This suggests that the RP might be an involuntary component of voluntary action over which people cannot exert conscious control.

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bioRxiv2019

Prospective and retrospective contributions to intention awareness in voluntary action

Spontaneous, voluntary actions are often accompanied by motor intentions, that is the experience of \"being about to move\". The emergence of this experience is contentiously discussed, culminating in two opposing views of motor intention. While prospective theorists hold that an intention to move genuinely precedes the action, retrospective theorists suggest that an intention is reconstructed only after action execution. As such, both theories offer radically different predictions about the possibility of voluntary control over action intention. We assess here the respective contributions of prospective and retrospective factors in motor intention awareness in a real-time EEG setup. Participants performed self-paced movements with intermittent interruption by cues, signalling to either move or not to move. Cues were triggered by a brain-computer interface upon detection of either the presence or absence of a readiness potential (RP), a signal known to precede self-paced voluntary actions. Subsequently, participants reported their intention to move at the time of the cue. We found that participants were more likely to report an intention to move when the cue was followed by a movement than no movement, highlighting the effect of retrospection on awareness of intention. Interestingly, however, an intention to move was also more frequently reported when the cue was elicited by an RP, compared to when no RP was present, suggesting that awareness of intention is also informed by motor preparation processes, congruent with prospective theories. Overall, our findings show that intention awareness in voluntary action relies on both prospective and retrospective components, and we describe here how these two factors are dynamically integrated over time.

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bioRxiv2019

Inverse Transformed Encoding Models - a solution to the problem of correlated trial-by-trial parameter estimates in fMRI decoding

Techniques of multivariate pattern analysis (MVPA) can be used to decode the discrete experimental condition or a continuous modulator variable from measured brain activity during a particular trial. In functional magnetic resonance imaging (fMRI), trial-wise response amplitudes are sometimes estimated from the measured signal using a general linear model (GLM) with one onset regressor for each trial. When using rapid event-related designs with trials closely spaced in time, those estimates are highly variable and serially correlated due to the temporally extended shape of the hemodynamic response function (HRF). Here, we describe inverse transformed encoding modelling (ITEM), a principled approach of accounting for those serial correlations and decoding from the resulting estimates, at low computational cost and with no loss in statistical power. We use simulated data to show that ITEM outperforms the current standard approach in terms of decoding accuracy and analyze empirical data to demonstrate that ITEM is capable of visual reconstruction from fMRI signals.

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bioRxiv2018

The context-dependent nature of the neural implementation of intentions

Many studies have identified networks in parietal and prefrontal cortex that are involved in intentional action. Yet, knowledge about what these networks exactly encoded is still scarce. In this study we look into the content of those processes. We ask whether the neural representations of intentions are context- and reason-invariant, or whether these processes depend on the context we are in, and the reasons we have for choosing an action. We use a combination of functional magnetic resonance imaging and multivariate decoding to directly assess the context- and reason-dependency of the processes underlying intentional action. We were able to decode action decisions in the same context and for the same reasons from the fMRI data, in line with previous decoding studies. Furthermore, we could decode action decisions across different reasons for choosing an action. Importantly, though, decoding decisions across different contexts was at chance level. These results suggest that for voluntary action, there is considerable context-dependency in intention representations. This suggests that established invariance in neural processes may not reflect an essential feature of a certain process, but that this stable character could be dependent on invariance in the experimental setup, in line with predictions from situated cognition theory.

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