Biology subjects

Perquin, M. N.

Publications and source records attributed to Perquin, M. N..

5 recordsLinked to original sources

bioRxiv2026

NTAD: A longitudinal neuroimaging dataset of Alzheimer's disease pathology

We introduce the New Therapeutics in Alzheimer's Disease (NTAD) dataset, a multi-modal and longitudinal imaging dataset from 70 biomarker-positive people with early dementia or Mild Cognitive Impairment (MCI) due to Alzheimer's Disease (AD), assessed over 2.5 years, and 35 healthy controls assessed at baseline. The data include simultaneous magneto- and electro-encephalography (M/EEG), 3-Tesla structural and functional magnetic resonance imaging (MRI), Amyloid-beta; positron emission tomography (PET), fluid proteomic biomarkers in cerebrospinal fluid and blood, and a battery of clinical and neuropsychological assessments. 11C UCB-J PET was undertaken for a subset of participants. For people with AD, assessments were repeated at approximately three weeks, 15 months, and 28 months after baseline. The data can be accessed through the Dementias Platform UK (DPUK), including pre-processed M/EEG and T1 MRI in pseudonymised BIDS format. With the pressing need to develop treatments for slowing, reversing, and preventing AD, these data provide an opportunity for identifying and validating novel biomarkers of Alzheimer's disease neurophysiology, as well as understanding its treatable pathology.

neuroscience↗

bioRxiv2026

No overlap in neurophysiological predictors of moment-to-moment fluctuations of behavioural variability and subjective attentional state

Behaviour fluctuates from moment to moment - often attributed to changes in subjective attentional states (e.g., mind wandering). Yet, it remains unclear how closely behavioural variability and subjective attentional state are related, and whether they share biological mechanisms. Using [~]2 hours of Metronome Response Task data, we combined magnetoencephalography, eye and head tracking, pupillometry, and thought probes to predict trial-to-trial fluctuations in both. Although they covaried weakly, this relationship was largely accounted for by time-on-task. Several markers including blink duration, pupil variability, and head movement predicted both measures. Dissociations also emerged: behavioural variability was linked to broadband functional connectivity and delta power, whereas off-taskness was predicted by theta, alpha, and beta power. Critically, predictive strength of behavioural variability and subjective reports were uncorrelated at the individual level, with substantial individual differences. For both outcomes, multimodal models outperformed univariate analyses. Our findings show that behavioural variability and subjective attentional state are largely dissociable, challenging the assumption that they share underlying process or that one causes the other.

neuroscience↗

bioRxiv2022

Variance (un)explained: Experimental conditions and temporal dependencies explain similarly small proportions of reaction time variability in perceptual and cognitive tasks

Any series of sensorimotor actions shows fluctuations in speed and accuracy from repetition to repetition, even when the sensory input and motor output requirements remain identical over time. Such fluctuations are particularly prominent in reaction time (RT) series from laboratory neurocognitive tasks. Despite their omnipresent nature, trial-to-trial fluctuations remain poorly understood. Here, we systematically analysed RT series from various neurocognitive tasks, quantifying how much of the total trial-to-trial RT variance can be explained with general linear models (GLMs) by three sources of variability that are frequently investigated in behavioural and neuroscientific research: 1) experimental conditions, employed to induce systematic patterns in variability, 2) short-term temporal dependencies as the autocorrelation between subsequent trials, and 3) long-term temporal trends over experimental blocks and sessions. Furthermore, we examined to what extent the explained variances by these sources are shared or unique. We analysed 1913 unique RT series from 30 different cognitive control and perception-based tasks. On average, the three sources together explained [~]8-17% of the total variance. The experimental conditions explained on average [~]2.5-3.5% but did not share explained variance with temporal dependencies. Thus, the largest part of the trial-to-trial fluctuations in RT remained unexplained by these three sources. Unexplained fluctuations may take on non-linear forms that are not picked up by GLMs. They may also be partially attributable to observable endogenous factors such as fluctuations in brain activity and bodily states. Still, some extent of randomness may be a feature of the neurobiological system rather than just nuisance. Public significance statementWhen we perform stereotyped repetitive sensorimotor actions, these nevertheless exhibit remarkable variability over time even under laboratory conditions. We show that most of this variability is not explained by linear models including two factors frequently studied in experimental psychology or cognitive neuroscience: the manipulations introduced by the experimenters and endogenous temporal dependencies that arise over multiple timescales. This implies that moment-to-moment fluctuations in typical behavioural data are largely unpredictable by linear models. Endogenous processes may also influence these fluctuations even in highly stable environments. It remains an empirical question to what extent exogenous and endogenous sources influence fluctuations non-linearly.

neuroscience↗

bioRxiv2020

Directional biases in whole hand motion perception revealed by mid-air tactile stimulation

Human machine interfaces are increasingly designed to reduce our reliance on the dominantly used senses of vision and audition. Many emerging technologies are attempting to convey complex spatiotemporal information via tactile percepts shown to be effective in the visual domain, such as shape and motion. Despite the intuitive appeal of touch as a method of feedback, we do not know to what extent the hand can substitute for the retina in this way. Here we ask whether the tactile system can be used to perceive complex whole hand motion stimuli, and whether it exhibits the same kind of established perceptual biases as reported in the visual domain. Using ultrasound stimulation, we were able to project complex moving dot percepts onto the palm in mid-air, over 30cm above an emitter device. We generated dot kinetogram stimuli involving motion in three different directional axes ( Horizontal, Vertical, and Oblique) on the ventral surface of the hand. We found clear evidence that participants were able to discriminate tactile motion direction. Furthermore, there was a marked directional bias in motion perception: participants were better and more confident at discriminating motion in the vertical and horizontal axes of the hand, compared to those stimuli moving obliquely. This pattern directly mirrors the perceptional biases that have been robustly reported in the visual field, termed the Oblique Effect. These data show the existence of biases in motion perception that transcend sensory modality. Furthermore, we extend the Oblique Effect to a whole hand scale, using motion stimuli presented on the broad and relatively low acuity surface of the palm, away from the densely innervated and much studied fingertips. These findings also highlight targeted ultrasound stimulation as a versatile means by which to convey potentially complex spatial and temporal information without the need for a user to wear or touch a device. This ability is particularly attractive as a potential feedback mechanism for application in contact-free human machine interfaces.

neuroscience↗

bioRxiv2019

Examining temporal structures in reaction time

Human performance shows substantial endogenous variability over time, and this variability is a robust marker of individual differences. Of growing interest to psychologists is the realisation that variability is not fully random, but often exhibits temporal dependencies. However, their measurement and interpretation come with several controversies. Furthermore, their potential benefit for studying individual differences in healthy and clinical populations remains unclear. Here we gather new and archival datasets featuring 11 sensorimotor and cognitive tasks across 526 participants, to examine individual differences in temporal structures. We first investigate intra-individual repeatability of the most common measures of temporal structures - to test their potential for capturing stable individual differences. Secondly, we examine inter-individual differences in these measures using: 1) task performance assessed from the same data, 2) meta-cognitive ratings of on-taskness from thought probes occasionally presented throughout the task, and 3) self-assessed attention-deficit related traits. Across all datasets, autocorrelation at lag 1 and Power Spectra Density slope showed high intra-individual repeatability across sessions and correlated with task performance. The Detrended Fluctuation Analysis slope showed the same pattern, but less reliably. The long-term component (d) of the ARFIMA(1,d,1) model showed poor repeatability and no correlation to performance. Overall, these measures failed to show external validity when correlated with either mean subjective attentional state or self-assessed traits between participants. Thus, some measures of serial dependencies may be stable individual traits, but their usefulness in capturing individual differences in other constructs typically associated with variability in performance seems limited. We conclude with comprehensive recommendations for researchers.

neuroscience↗