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O'Connell, R. G.

Publications and source records attributed to O'Connell, R. G..

At least 19 recordsLinked to original sources
bioRxiv2026

Neural latent representation of implicit perceptual decision confidence signatures from brain-wide intracranial EEG

Human perceptual decision confidence has been associated with brain-wide signalling, albeit with inconsistencies across studies. It remains unclear whether more robust neural latent representations exist, particularly for implicit confidence. We address this by applying complementary machine learning approaches to comprehensive, brain-wide intracranial electroencephalography (iEEG) data acquired without explicit confidence reports. Using explainable feature selection methods, we elucidated key spatiotemporal iEEG components, especially in the frontal cortex, that readily distinguished confidence characteristics related to decision correctness, difficulty, and speed, and that were transferable across motor modalities. Despite inconsistencies in the features identified across methods and conditions, dimensionality reductions revealed robust low-dimensional neural latent representations. Furthermore, their neural trajectories within a shared subspace enhanced the distinguishability of confidence characteristics. Overall, our results uncover low-dimensional spatial and temporal neural latent representations underlying human implicit perceptual decision confidence that are robust to analytical methods and decision conditions.

neuroscience↗
bioRxiv2026

Diminished Stimulus-Evoked Activity During Sustained Attention Without Behavioural Cost in ADHD

Attention-Deficit/Hyperactivity Disorder (ADHD) is often accompanied by attentional challenges, sleep difficulties and increased reports of daytime sleepiness, indicating potential links between attention and arousal mechanisms. Electroencephalographic (EEG) studies have shown that sleep-like wake slow wave (SW) activity during wakefulness, characterised by reduced cortical activity, corresponds with periods of inattention in both ADHD and neurotypical populations. However, it remains unclear whether group differences in waking SWs are consistent across different types of sustained attention tasks or may be context-dependent. The present study compared sustained attention performance and wake SW activity between adults with and without ADHD during a continuous visual target detection task. EEG data were collected while adults with (n = 52) and without ADHD (n = 49) completed a sustained attention paradigm. The task presented a continuous stream of rotating (anti-clockwise or clockwise) black-and-white checkerboard stimuli, and participants were required to detect infrequent targets that were marginally longer in duration than non-targets. Behavioural and neural measures (power spectra, steady-state visually evoked potentials (SSVEP), event-related potentials and SW density during wake) were analysed. No significant group differences were observed for task performance and wake SW activity. However, electrophysiological analyses revealed the ADHD group showed reduced P300, elevated beta-band power, and lower SSVEPs to target stimuli compared with the neurotypical group. These neural differences in the context of comparable performance suggest compensatory cortical recruitment in ADHD. The absence of SW differences further supports this, suggesting comparable performance and maintained arousal may reflect successful neural compensation in ADHD in this cognitive task. Significance StatementIndividuals with ADHD commonly experience attention differences, but emerging evidence suggests these difficulties may depend on task context. Using clinical diagnostic interviews, medication washout, and Bayesian statistics, we found strong evidence for comparable performance between ADHD and neurotypical adults on a sustained attention task. Notably, slow wave activity during wakefulness did not differ between groups, consistent with maintained arousal. Nevertheless, differences in brain activity, including altered target processing, increased cortical activation and reduced visual entrainment, suggested compensatory neural recruitment in ADHD. This context-dependent pattern has important theoretical and clinical implications: identifying task features that challenge or support performance in ADHD can reveal how individuals compensate neurally, and guide interventions that leverage task features to support attention in ADHD.

neuroscience↗
bioRxiv2026

Critical flicker fusion thresholds predict attentional blink magnitude

The critical flicker fusion (CFF) threshold is a psychophysical measure used to quantify the temporal resolution of the visual system and is known to vary across individuals. However, it is unclear if this measure is stimulus-specific, or if it may represent a more fundamental processing rate for visual perception in general. Here, we assess if individual variation in CFF is predictive of two features of visual processing that are dependent on temporal perception: the attentional blink and global motion sensitivity. In a non-clinical sample of 84 individuals, flicker fusion thresholds were predictive of the magnitude of the attentional blink. In contrast, we found no link between flicker fusion and global motion sensitivity in a sample of 79 individuals. Our results suggest that CFF reflects a visual processing rate that impacts other, more complex perceptual tasks.

neuroscience↗
bioRxiv2025

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.

neuroscience↗
bioRxiv2025

Neural dynamics of covert habit activation and control in humans

The neuroscience of habits in humans presumes a competition between two systems: stimulus-response and goal-directed. But lacking strong causal manipulations for inducing habits in humans, researchers have struggled to understand the brain mechanisms supporting the development of stimulus-response associations over time and their interaction with goal-directed processes. To address this, we conducted a preregistered electroencephalography (EEG) study with 14 days of stimulus-response training and used tight temporal controls to isolate the functioning of each system. In line with our preregistered hypothesis, we found that the lateralized readiness potential (LRP) tracked covert activation of habitual responses, detectable on trials where inappropriate habits are overcome and behavior is classed as goal-directed. In exploratory analyses, the strength of this covert habitual activation was associated with the degree of inappropriate habit expression on separate trials where response preparation time was limited. Further, exploratory analyses suggested that frontal midline theta (FM{theta}) power was selectively elevated when extensively trained habits needed to be overridden, and that this elevation scaled with individual differences in habit expression. These data provide evidence consistent with a dual systems account in which habit expression reflects competition between distinct neural subsystems and offer a new window into the formation and override of habits.

neuroscience↗
bioRxiv2025

Neurally-Informed Models of Protracted Sequential Sampling of Long, Noise-free Stimuli

Perceptual decision behaviour is known to be well-captured by models based on sequential sampling and temporal integration, but doubts have been raised about the generality and identifiability of these operations. Here we used neurally-constrained modelling to probe their role and temporal extent in the uncertain case of perceptual judgments about long-duration stimuli with no physical noise but weak evidence. We found that accuracy steadily improved across four covertly-manipulated evidence durations, indicating protracted sampling, but these delayed behavioural reports alone were insufficient to establish the operation of integration or of a decision-terminating bound. We then elaborated the models to prescribe how they would generate decision variable signals as well as choices, and fit them additionally to the average dynamics of a centroparietal electroencephalographic signal ( CPP) that traces decision formation. This established the setting of a bound and ruled out some non-integration mechanisms. However, one extrema detection model, which evokes a stereotyped signal flagging the first bound-exceeding sample, rivalled the integration model in reproducing the evidence-dependent buildup dynamics of the CPP, alongside behavioural data. Moreover, the two models captured different features of neural motor preparation signals but neither captured all of them. We discuss the implications for the generality of integration and the technical challenges of neurally-informed modelling given limited behavioural data.

neuroscience↗
bioRxiv2025

Neurally-informed modelling unravels a single evidence accumulation process for choices and subsequent confidence reports

How is the content of our decision making processes translated into subjective confidence? Current computational models designed to account for choice- and confidence-reporting behaviour disagree on two fundamental questions: do choice and confidence reports arise from shared versus distinct evaluation processes and what stopping-rule is applied to evidence sampling for confidence reports? Here, we employed a neurally-informed modelling approach in which competing models were compared both based on their fits to behaviour and their ability to recapitulate human electrophysiological signatures of evidence accumulation. Participants made self-paced confidence reports after indicating perceptual choices on a random dot motion task. Model comparison based on behavioural data alone showed that boundary-based stopping rules for confidence reporting provided superior fits than time-based stopping rules. However, results were inconclusive when comparing models with a single evidence accumulation process dictating choice and confidence reports compared to models invoking distinct processes. Importantly, the single-process model markedly outperformed the other models in its ability to account for the observed neural evidence accumulation patterns, including the fact that signal amplitudes predicted reported confidence several hundred milliseconds before the initial choice had been reported. Our study demonstrates that choice behaviour, subjective confidence, and associated neural decision signals can be jointly explained by a model invoking a single process of evidence accumulation with separate boundaries for the initial choice and subsequent confidence reports. Significance StatementHow does the brain generate representations of subjective confidence from categorical decisions? While some models suggest that confidence arises from a read-out of the same information that determined the initial choice, others propose that confidence is determined by a distinct computational process. Definitively testing these alternative accounts has proven difficult because they often make similar predictions for behavioural data. Here, we employ a novel neurally-informed modelling method that evaluates models based on their ability to reproduce key neurophysiological signatures of choice and confidence in addition to behaviour. Our results indicate that choices and subjective confidence are determined by a shared sensory evidence accumulation process.

neuroscience↗
bioRxiv2025

A Movement-Independent Signature of Urgency During Human Perceptual Decision Making

How does the brain adjust its decision processes to ensure timely decision completion? Computational modelling and electrophysiological investigations have pointed to dynamic urgency processes that serve to progressively reduce the quantity of evidence required to reach choice commitment as time elapses. To date, such urgency dynamics have been observed exclusively in neural signals that accumulate evidence for a specific motor plan. Across three complementary experiments, we show that a classic ERP component, the Contingent Negative Variation (CNV), also traces dynamic urgency but exhibits unique properties not observed in effector-selective signals. Firstly, it provides a representation of urgency alone, growing only as a function of time and not evidence strength. Secondly, when choice reports must be withheld until a response cue, the CNV peaks and decays long before response execution, mirroring the early termination dynamics of a motor-independent evidence accumulation signal. These properties suggest that the brain may use urgency signals not only to expedite motor planning but also to hasten cognitive deliberation. These data demonstrate that urgency processes operate in a variety of perceptual choice scenarios and that they can be monitored in a model-independent manner via non-invasive brain signals. Significance StatementComputational models suggest that, when decisions are time-constrained the brain progressively lowers the amount of evidence it requires to reach choice commitment, thus increasingly sacrificing accuracy for timely decision completion. To date, neurophysiological investigations have identified signatures of these urgency effects exclusively in areas of the brain that plan the decision-reporting actions. Here, we characterise a human electroencephalogram signature of urgency that exhibits several novel properties: it traces the urgency component of the decision and terminates upon choice commitment even when the decision-reporting action is deferred until later. These observations suggest that urgency can serve to hasten the deliberation process and not just the movements that a decision entails.

neuroscience↗
bioRxiv2025

Centroparietal signals track multiple rounds of evidence accumulation in an intermittent evidence task

Making decisions often requires the integration of multiple pieces of information. An extensive body of research has investigated the neural architecture underpinning evidence accumulation in perceptual tasks where information is continuously present, but less is known about how this neural architecture operates in situations affording only intermittent glimpses of an evidence source. In two electroencephalography (EEG) experiments, participants judged the direction of up to two pulses of motion evidence separated by gaps of varying duration. Our behavioural analysis found that participants used both pulses but underutilised the second, and showed no systematic decrease in accuracy as a function of gap duration. At the neural level, motor beta lateralisation tracked cumulative evidence across pulses, maintaining a sustained representation of the decision variable through the gap and until response. In contrast, the centroparietal positivity (CPP), a previously-characterised signature of evidence accumulation, built up transiently to a peak that scaled with each pulses contribution to the decision variable (i.e. the absolute belief update it produced), falling back to baseline in between pulses. These patterns were recapitulated in a model where pulse-information transiently integrated at the CPP level is fed to and maintained at a bounded motor level. In this model, the evidence in the second pulse is only integrated to the extent that the evidence in the first pulse falls short of the bound, or not integrated at all if a bound has already been hit.

neuroscience↗
bioRxiv2025

The role of human intraparietal sulcus in evidence accumulation revealed by EEG and model-informed fMRI

Sequential sampling models propose that the repeated sampling of sensory information is a fundamental component of perceptual decision-making. Electroencephalographic investigations in humans have demonstrated motor-independent representations of evidence accumulation, but such observations have seldom been made in neuroimaging studies exploring the neuroanatomical origins of evidence accumulation. Here, we aimed to reveal the neuroanatomical locus of sensory evidence accumulation in the human brain by regressing an electrophysiological marker of evidence accumulation (centroparietal positivity, CPP) against changes in blood oxygen level-dependent (BOLD) signal during perceptual decision-making. Our cross-modal imaging approach revealed a cluster within left intraparietal sulcus (IPS), located within putative lateral intraparietal area (region hIP3), for which BOLD signals scaled in relation to the slope of the CPP. Furthermore, the drift rate parameter of a drift diffusion model parametrically modulated BOLD activity within an overlapping region of left IPS. In contrast, parametric modulation by reaction time revealed a distributed fronto-parietal network, demonstrating the utility of our approach for isolating a discrete neuroanatomical locus of evidence accumulation. Together, our findings provide strong support for intraparietal sulcus involvement in the accumulation of sensory evidence during human perceptual decision-making.

neuroscience↗
bioRxiv2024

Regressing Away Common Neural Choice Signals does not make them Artifacts. Comment on Frömer et al (2024, Nature Human Behaviour)

Fromer et al (2024, Nature Human Behaviour) apply a deconvolution method to correct for component overlap in the event-related potential. They report that this method eliminates signatures of sensory evidence accumulation from response-aligned measurements of the centro-parietal positivity (CPP), suggesting that these signatures arise artifactually.. Here, we argue that the analysis and interpretation of their perceptual choice data are critically flawed. We demonstrate with simulations that the deconvolution analyses used by the authors are not designed to reliably test for the presence or absence of bounded accumulation signals.

neuroscience↗
bioRxiv2023

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.

neuroscience↗
bioRxiv2023

Signatures of time interval reproduction in the human electroencephalogram (EEG).

Accurate timing is essential for coordinating our actions in everyday tasks such as playing music and sport. Although an extensive body of research has examined the human electrophysiological signatures underpinning timing, the specific dynamics of these signals remain unclear. Here, we recorded electroencephalography (EEG) while participants performed a variant of a time interval reproduction task that has previously been administered to macaques, and examined how task performance was predicted by the dynamics of three well known EEG signals: limb-selective motor preparation in the mu/beta band (8-30Hz), the Contingent Negative Variation (CNV) and the Centro-Parietal Positivity (CPP) evidence accumulation signal. In close correspondence with single unit recordings in macaques, contralateral mu/beta signals indicated that participants reproduced intervals by adjusting the starting level and build-up rate of motor preparation to reach a response triggering threshold at the desired time. The CNV showed a highly similar pattern with the exception that its pre-response amplitude was increased for faster reproductions. This pattern of results suggests that, rather than tracing a veridical temporal accumulator as had been suggested in earlier work, the CNV more closely resembles a dynamic anticipatory signal. In contrast, the CPP did not exhibit any relationship with reproduction time suggesting that the evidence accumulation processes guiding perceptual decisions are not involved in generating representations of elapsed time. Our findings highlight close similarities in the dynamics exhibited by intracranial and non-invasive motor preparation signals during interval reproduction while indicating that the CNV traces a functionally distinct process whose precise role remains to be understood.

neuroscience↗
bioRxiv2023

Neurophysiology of perceptual decision-making and its alterations in attention deficit hyperactivity disorder (ADHD)

Despite the prevalence of ADHD, efforts to develop a detailed understanding of the neuropsychology of this neurodevelopmental condition are complicated by the diversity of interindividual presentations and the inability of current clinical tests to distinguish between its sensory, attentional, arousal or motoric contributions. Identifying objective methods that can decompose the clinical heterogeneity of ADHD is a long-held goal that is hoped to advance our understanding of etiological processes and potentially aid the development of personalized treatment approaches. Here, we examine key neuropsychological components of ADHD within an electrophysiological (EEG) perceptual decision-making paradigm that is capable of isolating distinct neural signals of several key information processing stages necessary for sensory-guided actions from attentional selection to motor responses. We show that compared to typically developing children, children with ADHD displayed slower and less accurate performance, which was driven by the atypical dynamics of discrete electrophysiological signatures of attentional selection, the accumulation of sensory evidence, and strategic adjustments reflecting urgency of response. These findings offer an integrated account of decision-making in ADHD and establish discrete neural signals that can be used to understand the wide range of neuropsychological performance variations in individuals with ADHD. Significance StatementThe efficacy of diagnostic and therapeutic pathways in ADHD is limited by our incomplete understanding of its neurological basis. One promising avenue of research is the search for basic neural mechanisms that may contribute to the variety of cognitive challenges associated with ADHD. We developed a mechanistic account of differences in a fundamental cognitive process by integrating across neurocognitive, neurophysiological (i.e., EEG), and computational levels of analysis. We detected distinct neural changes in ADHD that explained altered performance (e.g., slowed and less accurate responses). These included changes in neural patterns of attentional selection, sensory information processing, and response preparation. These findings enhance our understanding of the neurophysiological profile of ADHD and may offer potential targets for more effective, personalized interventions.

neuroscience↗
bioRxiv2023

The speed of sight: individual variation in critical flicker fusion thresholds

The critical flicker fusion threshold is a psychophysical measure commonly used to quantify visual temporal resolution; the fastest rate at which a visual system can discriminate visual signals. Critical flicker fusion thresholds vary substantially among species, reflecting different ecological niches and demands. However, it is unclear how much variation exists in flicker fusion thresholds between healthy individuals of the same species, or how stable this attribute is over time within individuals. In this study, we assessed both inter- and intra-individual variation in critical flicker fusion thresholds in a cohort of healthy human participants within a specific age range, using two common psychophysical methods and three different measurements during each session. The resulting thresholds for each method were highly correlated. We found a between-participant maximum difference of roughly 30 Hz in flicker fusion thresholds and we estimated a 95% prediction interval of 21 Hz. We used random-effects models to compare between- and within-participant variance and found that approximately 80% of variance was due to between-individual differences, and about 10% of the variance originated from within-individual differences over three sessions. Within-individual thresholds did not differ significantly between the three sessions in males, but did in females (P<0.001 for two methods and P<0.05 for one method), indicating that critical flicker fusion thresholds may be more variable in females than in males.

ecology↗
bioRxiv2023

Prior probability cues bias sensory encoding with increasing task exposure

When observers have prior knowledge about the likely outcome of their perceptual decisions, they exhibit robust behavioural biases in reaction time and choice accuracy. Computational modelling typically attributes these effects to strategic adjustments in the criterion amount of evidence required to commit to a choice alternative - usually implemented by a starting point shift - but recent work suggests that expectations may also fundamentally bias the encoding of the sensory evidence itself. Here, we recorded neural activity with EEG while participants performed a contrast discrimination task with valid, invalid, or neutral probabilistic cues across multiple testing sessions. We measured sensory evidence encoding via contrast-dependent steady-state visual-evoked potentials (SSVEP), while a read-out of criterion adjustments was provided by effector-selective mu-beta band activity over motor cortex. In keeping with prior modelling and neural recording studies, cues evoked substantial biases in motor preparation consistent with criterion adjustments, but we additionally found that the cues produced a significant modulation of the SSVEP during evidence presentation. While motor preparation adjustments were observed in the earliest trials, the sensory-level effects only emerged with extended task exposure. Our results suggest that, in addition to strategic adjustments to the decision process, probabilistic information can also induce subtle biases in the encoding of the evidence itself.

neuroscience↗
bioRxiv2023

Intracranial electroencephalography reveals effector-independent evidence accumulation dynamics in multiple human brain regions

Neural representations of perceptual decision formation that are abstracted from specific motor requirements have previously been identified in humans using non-invasive electrophysiology, however, it is currently unclear where these originate in the brain. Here, we capitalized on the high spatiotemporal precision of intracranial EEG to localize such abstract decision signals. Presurgical epilepsy patients judged the direction of random-dot stimuli and responded either with a speeded button press (N=23), or vocally, after a randomized delay (N=11). We found a widely distributed motor-independent network of regions where high-frequency activity exhibited key characteristics consistent with evidence accumulation, including a gradual build-up that was modulated by the strength of the sensory evidence, and an amplitude that predicted subjects choice accuracy and response time. Our findings offer a new view on the brain networks governing human decision making.

neuroscience↗
bioRxiv2023

Confidence is predicted by pre- and post-choice decision signal dynamics

It is well established that ones confidence in a choice can be influenced by new evidence encountered after commitment has been reached, but the processes through which post-choice evidence is sampled remain unclear. To investigate this, we traced the pre- and post-choice dynamics of electrophysiological signatures of evidence accumulation (Centro-parietal Positivity, CPP) and motor preparation (mu/beta band) to determine their sensitivity to participants confidence in their perceptual discriminations. Pre-choice CPP amplitudes scaled with confidence both when confidence was reported simultaneously with choice, or when reported 1-second after the initial direction decision. When additional evidence was presented during the post-choice delay period, the CPP continued to evolve after the initial choice, with a more prolonged build-up on trials with lower confidence in the alternative that was finally endorsed, irrespective of whether this entailed a change-of-mind. Further investigation established that this pattern was accompanied by earlier post-choice CPP peak latency, earlier lateralisation of motor preparation signals toward the ultimately chosen response, and faster confidence reports when participants indicated high certainty that they had made a correct or incorrect initial choice. These observations are consistent with confidence-dependent stopping theories according to which post-choice evidence accumulation ceases when a criterion level of confidence in a choice alternative has been reached. Our findings have implications for current models of choice confidence, and predictions they may make about EEG signatures.

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