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Mattingley, J. B.

Publications and source records attributed to Mattingley, J. B..

At least 19 recordsLinked to original sources

Bridging Sensory Extraction and Decision Dynamics: Face Pareidolia Emergent from Bottom-Up and Top-Down Interactions

Face pareidolia-the illusory perception of faces in everyday objects-provides a unique window into how the human brain resolves visual ambiguity. Whether pareidolia arises from bottom-up sensory processing or top-down, expectation-driven feedback, is currently debated. Here we recorded electroencephalography (EEG) while participants viewed rapid serial visual presentation (RSVP) streams of images, each of which was an object-to-face morph generated along a 21-image continuum via text-to-image diffusion models. Time-resolved representational similarity analyses revealed a clear spatiotemporal dissociation, in which early occipitotemporal areas tracked physical feature changes linearly, while later frontocentral channels collapsed this structural gradient into a sharp, sigmoidal profile reflecting discrete categorical decisions (face-like versus object-like). To characterise information transmission between these regions, we implemented a novel transformation-based representational connectivity analysis. These analyses uncovered an initial feedforward flow of information that transferred and transformed posterior linear traces into anterior sigmoidal representations. Crucially, partitioning the image continuum revealed that unambiguous stimuli (faces or objects) were predominantly resolved via feedforward information flow, whereas ambiguous pareidolic images recruited prolonged top-down feedback. Furthermore, perceptual decision sensitivity was biased by animacy priors and directly predicted individual behavioural reaction times during the task. Together, the findings help reconcile prior debate by establishing that face pareidolia is neither a feedforward process nor an isolated top-down projection, but an active, multi-stage recurrent process driven by feedforward feature extraction and top-down categorical resolution.

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Exploring the role of prior exposure and image quality in neural and behavioural prediction effects

According to predictive processing theories, the brain achieves efficiency in perception by comparing current sensory inputs with stored representations of the external world. Previous research has shown that manipulations of expectation can alter neural processing of low-level visual features as well as more complex, naturalistic objects. It remains unclear, however, precisely how the effects of expectancy are altered through learning and changes in stimulus fidelity. Here, we characterised behaviour and neural activity patterns while systematically varying individuals prior exposure to object sequences and the quality of the stimuli therein. Participants viewed rapid image sequences while we recorded their brain activity using electroencephalography (EEG). The stimulus sequences were probabilistically structured such that the appearance of each object was either expected, unexpected, or random. Participants were faster and more accurate in detecting cued target stimuli when these were expected relative to unexpected or random. Multivariate analysis of EEG activity patterns time-locked to the appearance of object images revealed reliably reduced decoding accuracy for both expected and unexpected stimuli relative to random stimuli. These patterns were consistent across exposure and image quality conditions, though exploratory analyses suggested that subtle changes in neural prediction effects may be linked to exposure. The findings do not provide strong support that the brain differentially represents expected versus unexpected object information and suggest that exposure and image quality do not reliably interact with predictive processes in object recognition.

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A comparison of sharpening and dampening accounts of the role of expectation in shaping the neural fidelity of early visual representations

The natural environment is spatiotemporally structured, and the brain exploits this regularity to predict and prepare for upcoming sensory stimuli. Such predictive processing is thought to increase neural efficiency by reducing metabolic expenditure and altering the fidelity with which newly encountered stimuli are encoded. Competing theoretical frameworks propose this is achieved either through sharpening, whereby expected events are encoded more precisely, or dampening, whereby expected events are suppressed and encoded less precisely. Despite clear, opposing predictions, evidence in humans for each account remains mixed due to methodological and analytical inconsistencies. Here we addressed these issues using probabilistic visual paradigm combined with functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). We used population receptive field (pRF) mapping of fMRI data and inverted encoding of EEG data to compare the fidelity and timecourse of activity in visual areas in response to expected, unexpected, and random stimuli. Both methods produced a consistent pattern of results. Post hoc analysis of EEG data revealed that the apparent effect of expectancy was better explained by local spatiotemporal stimulus properties than the global expectancy manipulation. Although this pattern resembled sensory adaptation, it was more consistent with an expectation of temporal stability combined with dampening, in which both the aggregate response to expected features and their representational fidelity are suppressed. Taken together, our findings suggest that predictive processing may operate through dampening, with ecological advantages for high-fidelity encoding of unexpected sensory events.

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Semantic category and presentation frequency-based expectations are associated with distinct neural prediction effects.

Past work has indicated that expectation can modulate neural responses to visual stimuli, but it is unclear whether these effects remain consistent across different types of unexpected stimuli. Here, we measured and compared neural prediction effects associated with semantic category and presentation frequency-based expectations in real-world object stimuli. Participants (n = 35) viewed real-world object images in rapid serial visual presentation (RSVP) streams. Semantically unexpected stimuli occurred when a stimulus was presented in a semantically incongruent stream. Low-frequency violations occurred when a rarely presented stimulus was displayed in a semantically congruent stream. Multivariate pattern analysis of electroencephalography (EEG) was used to quantify and compare the degree of information represented in neural activity for stimuli in different prediction conditions. Semantically expected stimuli yielded lower decoding accuracy relative to random (unpredictable) stimuli (125-313 ms post-onset) while semantically unexpected stimuli exhibited increased decoding accuracy (199-238 ms & 523-559 ms). Low-frequency violations yielded decoding accuracy which was not significantly different from semantically expected stimuli. Exploratory analyses indicated that dissimilarity between expected and presented stimuli quantified in terms of higher-level stimulus features, but not low-level visual features, modulated the observed neural prediction effects. These results demonstrate that different types of prediction violations have distinct modulatory effects on neural responses, providing novel insight into the neural implementation of predictive processing.

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Late Integration of Prior Expectations During Precision Weighted Perceptual Decisions

Adaptive perceptual decision-making relies on the ability to combine sensory evidence with prior expectations in a precision-weighted manner. Although Bayesian inference provides a clear normative account of how such integration should occur, the neural mechanisms through which the brain represents and combines priors and likelihoods remain poorly understood. Across two preregistered experiments, we investigated how the precision of prior expectations and sensory likelihoods influences visual motion judgements and associated neural activity patterns during a random-dot motion estimation task. Neurotypical adult participants (N=80, 58 female) reported directions of visual motion stimuli, with motion coherence varying randomly across trials. Prior expectations were manipulated block-wise by varying the probabilities with which different motion directions were presented. Consistent with precision-weighted inference, response accuracy improved as coherence increased with robust response biases toward the expected motion direction. Neural activity measured using electroencephalography (EEG) revealed reliable effects of prior expectation on the univariate central-parietal positivity (CPP), consistent with reduced accumulation of sensory evidence under informative priors. Multivariate analysis using inverted-encoding models revealed robust effects of prior informativeness on motion-specific neural representations, but only late, during response planning stages. Together, these findings demonstrate that precision-weighted inference primarily occurs at late stages of the decision process and challenge predictive-processing accounts that emphasise early sensory processing. Significance StatementPerceptual decisions require combining uncertain sensory information with prior expectations about what is likely to occur. Although behaviour often follows this principle, it remains unclear how the brain integrates prior expectations with incoming sensory evidence. Using a visual motion task and concurrent brain imaging, we show that expectations do not alter early sensory processing but instead influence later stages of decision formation and action planning. Neural representations of sensory evidence primarily reflect stimulus reliability, whereas prior expectations selectively enhance representations during response preparation. These findings challenge influential theories proposing that expectations affect early sensory processing and instead highlight their contribution to later decision-related processes. This work advances understanding of how the brain uses experience to optimise perceptual decisions under uncertainty.

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A joint alpha power-phase dynamic shapes visual sensitivity

Perceptual experience is influenced by alpha-band oscillations (8-14 Hz) that dominate parietal and sensory cortices. However, there is uncertainty around the perceptual mechanisms that are affected by oscillatory power and phase. Previous work has linked power and phase to behaviour separately despite their theorised common effects via pulsed-inhibition, potentially misrepresenting or conflating their effects. Here we recorded brain activity using electroencephalography to investigate how alpha oscillations affect the psychometric function over visual contrast in both detection and discrimination tasks. We found that prestimulus power and phase predicted the strength of subsequent evoked neural responses and behavioural accuracy. We then combined power and phase into a joint model of pulsed-inhibition and estimated its effects within a signal detection model of behaviour. The model revealed response gain modulation of visual sensitivity in both tasks, and perceptual bias modulation in detection. Critically, oscillatory power suppressed visual sensitivity more strongly than phase, suggesting a sustained effect of alpha oscillations that is not accounted for by the pulsed-inhibition hypothesis. We conclude that alpha-band activity shapes visual perception by divisively suppressing sensory evidence and baseline sensory noise, with joint power-phase modelling revealing asymmetric contributions to visual sensitivity.

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Sleep-like slow waves in wakefulness index post-stroke behavioural alterations

Increases in high-amplitude, low-frequency EEG oscillations during non-rapid eye movement (NREM) sleep serve as markers of neuronal silencing, which disrupts functional connectivity and is associated with a loss of awareness and responsiveness. Cortical slowing likewise occurs during wakefulness, upon sleep deprivation, and accompanies performance deterioration. Recent work has revealed similar oscillations (termed sleep-like slow waves) following stroke in brain regions close or connected to a brain lesion, offering a plausible but untested mechanism for stroke-related behavioural impairment. Here, we simultaneously recorded EEG and behavioural performance while 30 unilateral stroke patients (12 left hemisphere, 18 right hemisphere) and 27 age-matched healthy adults completed a computerised perceptual decision-making task. Sleep-like slow waves occurred more frequently in stroke patients relative to healthy controls. Furthermore, there was a significant correlation between slow wave occurrence and the accuracy and speed of perceptual reports in stroke patients, suggesting that variations in the occurrence of slow waves may contribute to cognitive heterogeneity post-stroke. Evidence that sleep-like slow waves predict deficits in perceptual decision-making following stroke indicates that stroke-induced lesions can destabilize cortical networks extending beyond the damaged regions, thereby contributing to broader cognitive impairments.

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Methodological choices strongly modulate the sensitivity and specificity of lesion-symptom mapping analyses

Lesion mapping results can vary substantially as a function of specific analysis parameters, but the extent to which individual methodological choices interact to modulate the sensitivity and specificity of results is not clear. Here, we employed a large-scale simulation approach to inform practical recommendations for lesion symptom mapping studies. Routine clinical imaging from 959 stroke survivors (mean age = 72.5, 49.3% female) was used to conduct 384,780 lesion mapping analyses based on simulated behavioural data. Each simulated analysis used different combinations of plausible sample inclusion criteria, analysis parameters (e.g., correction factors), analysis types (e.g., univariate vs. multivariate), and underlying target correlates. Simulated analysis accuracy (Dice similarity coefficient and percent coverage of target correlates) was compared across designs. Overall, analysis accuracy varied widely and was substantially modulated by the specific design used. Analyses that maximised lesion coverage by including large and diverse samples reliably outperformed analyses using more restricted samples. Analyses using direct total lesion volume controls outperformed analyses using other (or no) volume corrections across all accuracy measures. False discovery rate corrections yielded the best performance in terms of target coverage, while permutation corrections yielded the best Dice coefficients. While multivariate approaches were more accurate than univariate analyses in terms of Dice coefficient, univariate analyses generated higher target hit rates and percent target coverage. These results identify specific analysis designs suitable for studies aiming to maximise their sensitivity and/or specificity to underlying critical correlates, while highlighting the inferential strengths and weaknesses of these complementary approaches.

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Individual differences in perceptual capacity depend on aperiodic slope, not alpha oscillations

Visual processing is subject to strict capacity limitations that restrict the number of stimuli that can be individuated, that is, distinguished as separate objects, to around 3-4 items at a time. The neural mechanisms that give rise to this subitizing limit are unclear. Here, we tested an account of the subitizing limit that attributes it to the amount of information that can be processed within one cycle of the 8-14 Hz alpha oscillation. This account proposes that the subitizing limit should be correlated with an individuals alpha oscillation frequency. We pitted this account against one based on neural excitatory-inhibitory balance, as indexed by the slope of the aperiodic component of the electrophysiological power spectrum. To test these accounts, we had human participants (N=51; 37 females) complete a visual enumeration task while we measured their brain activity with electroencephalography (EEG). We extracted aperiodic and alpha-band activity from the pre-stimulus period and correlated these with model-based estimates of individuals subitizing capacity. Alpha oscillations were not correlated with subitizing capacity within-participants or as individual differences, but they were associated with other elements of enumeration performance, including baseline reaction times and the slope of the performance decrement outside the subitizing range. By contrast, individual differences in aperiodic slope reliably predicted individuals subitizing capacity. These results suggest that differences in neural excitatory:inhibitory balance are the source of individuation-related capacity limits, not alpha-frequency sampling. Significance StatementBusy, multi-element visual scenes are common in daily life. Human visual perception, however, is capacity limited, individuating only 3-4 objects at a time. The source of these capacity limitations is currently unknown. This work examines the neural correlates of perceptual capacity within and between individuals, comparing a rhythmic pulsed inhibition account with one based on the arhythmic balance of neural excitation and inhibition. Our results demonstrate that individuals with more arhythmic inhibition demonstrate greater perceptual capacity. These results help to explain how excitation and inhibition across populations of neurons sculpts the capacity of the neural system and suggest targets for future interventions to improve perceptual capacity with arhythmic brain stimulation.

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A common algorithm for confidence judgements across visual, auditory and audio-visual decisions

Most studies investigating the computational basis of decision confidence have focused on simple visual perceptual tasks, leaving open questions about how confidence is formed in decisions involving other sensory modalities or those requiring the integration of information across modalities. To address these gaps, we used computational modelling to analyse confidence judgements in perceptual decisions involving visual, auditory, and audio-visual stimuli. Drawing on research into visual confidence, we adapted models from the literature to evaluate their fit to our data, comparing three popular classes: unscaled evidence strength, scaled evidence strength, and Bayesian models. Our results show that the scaled evidence strength models consistently outperformed the other model classes across all tasks and could also be used to predict behaviour in the audio-visual task from the unidimensional auditory and visual model fits. These findings suggest that confidence judgements across different perceptual decisions rely on a shared algorithm that dynamically accounts for both sensory uncertainty and evidence strength, without the computation of posterior probabilities. Additionally, we investigated the algorithms used for multidimensional (audio-visual) confidence judgements specifically, showing that participants integrated both the visual and auditory dimensions of the stimulus, rather than relying solely on the most informative modality, and used a modality-independent measure of sensory uncertainty to adjust their confidence. Overall, our findings provide evidence for a common algorithm underlying confidence judgements across modalities and demonstrate the broad applicability of the scaled evidence strength algorithm, even in tasks requiring the integration of distinct sensory information.

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Low-level features predict perceived similarity for naturalistic images

The mechanisms by which humans perceptually organise individual regions of a visual scene to generate a coherent scene representation remain largely unknown. Our perception of statistical regularities has been relatively well-studied in simple stimuli, and explicit computational mechanisms that use low-level image features (e.g., luminance, contrast energy) to explain these perceptions have been described. Here, we investigate to what extent observers can effectively use such low-level information present in isolated naturalistic scene regions to facilitate associations between said regions. Across two experiments, participants were shown an isolated standard patch, then required to select which of two subsequently presented patches came from the same scene as the standard (2AFC). In Experiment 1, participants were consistently above chance when performing such association judgements. Additionally, participants responses were well-predicted by a generalised linear multilevel model (GLMM) employing predictors based on low-level feature similarity metrics (specifically, pixel-wise luminance and phase-invariant structure correlations). In Experiment 2, participants were presented with thresholded image regions, or regions reduced to only their edge content. Their performance was significantly poorer when they viewed unaltered image regions. Nonetheless, the model still correlated well with participants judgments. Our findings suggest that image region associations can be reduced to low-level feature correlations, providing evidence for the contribution of such basic features to judgements made on complex visual stimuli.

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Investigating orientation adaptation following naturalistic film viewing

Humans display marked changes to their perceptual experience of a stimulus following prolonged or repeated exposure to a preceding stimulus. A well-studied example of such perceptual adaptation is the tilt-aftereffect. Here, prolonged exposure to one orientation leads to a shift in the perception of subsequent orientations. Such a capacity to adapt suggests the visual system is dynamically tuned to our current visual environment. However, it remains unclear to what extent adaptation occurs in response to systematic features in naturalistic scenes. We therefore investigated orientation adaptation in response to natural viewing of filtered live-action film stimuli. Within a session, participants freely viewed 45 minutes of a film which had been filtered to include increased contrast energy within a specified orientation band (0{degrees}, 45{degrees}, 90{degrees}, or 135{degrees}; i.e., the adaptor). To measure adaptation effects, the film was intermittently interrupted to have participants perform a simple orientation judgement task. Having participants complete behavioural trials throughout the testing session, including 45 minutes of total adaptation time, allowed investigation of the accumulation of response biases and changes in such biases over the course of the session. We found participants exhibited stronger adaptation effects in response to cardinal adaptors compared to obliques. However, overall adaptation effects were weaker than those observed under typical tilt-aftereffect paradigms. Further, within a single session, adaptation effects developed inconsistently. The current findings therefore demonstrate a resistance to adaptation in response to naturalistic viewing conditions, suggesting barriers to understanding perceptual adaptation as experienced in nature.

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Evidence for auditory stimulus-specific adaptation but not deviance detection in larval zebrafish brains

Animals receive a constant stream of sensory input, and detecting changes in this sensory landscape is critical to their survival. One signature of change detection in humans is the auditory mismatch negativity (MMN), a neural response to unexpected stimuli that deviate from a predictable sequence. This process requires the auditory system to adapt to specific repeated stimuli while remaining sensitive to novel input (stimulus-specific adaptation). MMN was originally described in humans, and equivalent responses have been found in other mammals and birds, but it is not known to what extent this deviance detection circuitry is evolutionarily conserved. Here we present the first evidence for stimulus-specific adaptation in the brain of a teleost fish, using whole-brain calcium imaging of larval zebrafish at single-neuron resolution with selective plane illumination microscopy. We found frequency-specific responses across the brain with variable response amplitudes for frequencies of the same volume, and created a loudness curve to model this effect. We presented an auditory oddball stimulus in an otherwise predictable train of pure tone stimuli, and did not find a population of neurons with specific responses to deviant tones that were not otherwise explained by stimulus-specific adaptation. Further, we observed no deviance responses to an unexpected omission of a sound in a repetitive sequence of white noise bursts. These findings extend the known scope of auditory adaptation and deviance responses across the evolutionary tree, and lay groundwork for future studies to describe the circuitry underlying auditory adaptation at the level of individual neurons.

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Violated predictions enhance the representational fidelity of visual features in perception

Predictive coding theories argue that recent experience establishes expectations that generate prediction errors when violated. In humans, brain imaging studies have revealed unique signatures of violated predictions in sensory cortex, but the perceptual consequences of these effects remain unknown. We had observers perform a dual-report task on the orientation of a briefly presented target grating within predictable or random sequences, while we recorded pupil size as an index of surprise. Observers first made a speeded response to categorize the orientation of the target grating (clockwise or counterclockwise from vertical), then reproduced its orientation without time pressure by rotating a bar. This allowed us to separately assess response speed and precision for the same stimuli. Critically, on half the trials, the target orientation deviated from the spatiotemporal structure established by the preceding gratings. Observers responded faster and more accurately to unexpected gratings, and pupillometry provided physiological evidence of observers surprise in response to these events. In a second experiment, we cued the spatial location and timing of the grating and found the same pattern of results, demonstrating that unexpected orientation information is sufficient to produce faster and more precise responses, even when the location and timing of the relevant stimuli are fully expected. These findings indicate that unexpected events are prioritized by the visual system both in terms of processing speed and representational fidelity.

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Causal evidence for increased theta and gamma phase consistency in a parieto-frontal network during the maintenance of visual attention

Endogenous visuo-spatial attention is under the control of a fronto-parietal network of brain regions. One key node in this network, the intra-parietal sulcus (IPS), plays a crucial role in maintaining endogenous attention, but little is known about its ongoing physiology and network dynamics during different attentional states. Here, we investigated the reactivity of the left IPS in response to brain stimulation under different states of selective attention. We recorded electroencephalography (EEG) in response to single pulses of transcranial magnetic stimulation (TMS) of the IPS, while participants (N=44) viewed bilateral random-dot motion displays. Individual MRI-guided TMS pulses targeted the left IPS, while the left primary somatosensory cortex (S1) served as an active control site. In separate blocks of trials, participants were cued to attend covertly to the motion display in one hemifield (left or right) and to report brief coherent motion targets. The perceptual load of the task was manipulated by varying the degree of motion coherence of the targets. Excitability, variability and information content of the neural responses to TMS were assessed by analysing TMS-evoked potential (TEP) amplitude and inter-trial phase clustering (ITPC), and by performing multivariate decoding of attentional state. Results revealed that a left posterior region displayed reduced variability in the phase of theta and gamma oscillations following TMS of the IPS, but not of S1, when attention was directed contralaterally, rather than ipsilaterally to the stimulation site. Under these same conditions, a right frontal cluster also displayed reduced theta variability and increased amplitude of TEPs after TMS of the IPS but not S1. Reliable decoding of attentional state was achieved after TMS pulses of both S1 and IPS. Taken together, our findings suggest that endogenous control of visuo-spatial attention leads to changes in the intrinsic oscillatory properties of the IPS and its associated fronto-parietal network.

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Inverted encoding of neural responses to audiovisual stimuli reveals super-additive multisensory enhancement

A central challenge for the brain is how to combine separate sources of information from different sensory modalities to optimally represent objects and events in the external world, such as combining someones speech and lip movements to better understand them in a noisy environment. At the level of individual neurons, audiovisual stimuli often elicit super-additive interactions, where the neural response is greater than the sum of auditory and visual responses. However, investigations using electroencephalography (EEG) to record brain activity have revealed inconsistent interactions, with studies reporting a mix of super- and sub-additive effects. A possible explanation for this inconsistency is that standard univariate analyses obscure multisensory interactions present in EEG responses by overlooking multivariate changes in activity across the scalp. To address this shortcoming, we investigated EEG responses to audiovisual stimuli using inverted encoding, a population tuning approach that uses multivariate information to characterise feature-specific neural activity. Participants (n = 41) completed a spatial localisation task for both unisensory stimuli (auditory clicks, visual flashes) and combined audiovisual stimuli (spatiotemporally congruent clicks and flashes). To assess multivariate changes in EEG activity, we used inverted encoding to recover stimulus location information from event-related potentials (ERPs). Participants localised audiovisual stimuli more accurately than unisensory stimuli alone. For univariate ERP analyses we found an additive multisensory interaction. By contrast, multivariate analyses revealed a super-additive interaction [~]180 ms following stimulus onset, such that the location of audiovisual stimuli was decoded more accurately than that predicted by maximum likelihood estimation. Our results suggest that super-additive integration of audiovisual information is reflected within multivariate patterns of activity rather than univariate evoked responses.

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Effects of oscillation phase on discrimination performance in a visual tilt illusion

Neural oscillations reflect fluctuations in the relative excitation/inhibition of neural systems1-5 and are theorised to play a critical role in several canonical neural computations6-9 and cognitive processes10-14. These theories have been supported by findings that detection of visual stimuli fluctuates with the phase of oscillations at the time of stimulus onset15-23. However, null results have emerged in studies seeking to demonstrate these effects in visual discrimination tasks24-27, raising questions about the generalisability of these phenomena to wider neural processes. Recently, we suggested that methodological limitations may mask effects of oscillation phase in higher-level sensory processing28. Thus, to test the generality of phasic influences requires a task that requires stimulus discrimination but depends on early sensory processing. Here, we examined the influence of oscillation phase in the visual tilt illusion, in which an oriented centre grating is perceived titled away from the orientation of a surround grating29. This illusion is produced by lateral inhibitory interactions in early visual processing30-32. We presented centre gratings at participants titrated subjective vertical angle and had participants report whether the grating appeared tilted leftward or rightward of vertical on each trial while measuring their brain activity with EEG. We observed a robust fluctuation in orientation perception across different phases of posterior alpha and theta oscillations, consistent with fluctuating illusion magnitude across the oscillatory cycle. These results confirm that oscillation phase affects complex processing involved in stimulus discrimination, consistent with their purported role in canonical computations that underpin cognition.

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Neurophysiological mechanisms underlying post-stroke deficits in contralesional perceptual processing

Slowed responding to sensory inputs presented in contralesional space is pervasive following unilateral cerebral stroke, but the causal neurophysiological pathway by which this occurs remains unclear. To this end, here we leverage a perceptual decision-making framework to disambiguate information processing stages between sensation and action in 30 unilateral stroke patients (18 right hemisphere, 12 left hemisphere) and 27 neurologically healthy adults. By recording neural activity using electroencephalography (EEG) during task performance, we show that the relationship between strokes in either hemisphere and slowed contralesional response times is sequentially mediated by weaker target selection signals in the contralateral hemisphere (the N2c ERP), and subsequently delayed evidence accumulation signals (the centroparietal positivity). Notably, asymmetries in CPP and response times across hemispheres are associated with everyday functioning. Together, these data suggest a plausible neurophysiological pathway by which post-stroke contralesional slowing arises and highlight the utility of neurophysiological assessments for tracking clinically relevant behaviour.

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