Biology subjects

McGovern, D. P.

Publications and source records attributed to McGovern, D. P..

6 recordsLinked to original sources

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

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↗

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↗

bioRxiv2021

Stratification of Risk of Progression to Colectomy in Ulcerative Colitis using Measured and Predicted Gene Expression

An important goal of clinical genomics is to be able to estimate the risk of adverse disease outcomes. Between 5% and 10% of ulcerative colitis (UC) patients require colectomy within five years of diagnosis, but polygenic risk scores (PRS) utilizing findings from GWAS are unable to provide meaningful prediction of this adverse status. By contrast, in Crohns disease, gene expression profiling of GWAS-significant genes does provide some stratification of risk of progression to complicated disease in the form of a Transcriptional Risk Score (TRS). Here we demonstrate that both measured (TRS) and polygenic predicted gene expression (PPTRS) identify UC patients at 5-fold elevated risk of colectomy with data from the PROTECT clinical trial and UK Biobank population cohort studies, independently replicated in an NIDDK-IBDGC dataset. Prediction of gene expression from relatively small transcriptome datasets can thus be used in conjunction with transcriptome-wide association studies to stratify risk of disease complications.

genetics↗

bioRxiv2018

Inflammatory bowel disease microbiotas alter gut CD4 T-cell homeostasis and drive colitis in mice

To examine the functional contribution of Inflammatory Bowel Disease (IBD) microbes to immune homeostasis and colitis, we colonized unchallenged and colitis-susceptible germ-free mice with over twenty human intestinal microbiotas from healthy and IBD donors. Compared to healthy microbiotas, IBD microbiotas led to expanded ROR{gamma}t+Th17 cells and reduced ROR{gamma}t+Treg in the gut of unchallenged gnotobiotic mice and increased disease severity in colitis-susceptible mice. The proportions of ROR{gamma}t+Th17 and ROR{gamma}t+Treg induced by each microbiota were highly predictive of the human disease status and strongly correlated with disease severity in colitis-susceptible mice colonized with the same human microbiotas. The transmittable functional potential of IBD microbes suggests a mechanism for a microbial contribution to IBD pathogenesis and a potential route for its treatment and prevention.

immunology↗

bioRxiv2017

Reconciling age-related changes in behavioural and neural indices of human perceptual decision making

Ageing impacts on decision making behaviour across a wide range of cognitive tasks and scenarios. Computational modeling has proven highly valuable in providing mechanistic interpretations of these age-related differences; however, the extent to which model parameter differences accurately reflect changes to the underlying neural computations has yet to be tested. Here, we measured neural signatures of decision formation as younger and older participants performed motion discrimination and contrast-change detection tasks, and compared the dynamics of these signals to key parameter estimates from fits of a prominent accumulation-to-bound model (drift diffusion) to behavioural data. Our results indicate marked discrepancies between the age-related effects observed in the model output and the neural data. Most notably, while the model predicted a higher decision boundary in older age for both tasks, the neural data indicated no such differences. To reconcile the model and neural findings, we used our neurophysiological observations as a guide to constrain and adapt the model parameters. In addition to providing better fits to behaviour on both tasks, the resultant neurally-informed models furnished novel predictions regarding other features of the neural data which were empirically validated. These included a slower mean rate of evidence accumulation amongst older adults during motion discrimination and a beneficial reduction in between-trial variability in accumulation rates on the contrast-change detection task, which was linked to more consistent attentional engagement. Our findings serve to highlight how combining human brain signal measurements with computational modelling can yield unique insights into group differences in neural mechanisms for decision making.

neuroscience↗