Using genetic variants as a treatment decision aid for the optimization of antipsychotic treatments: a critical appraisal of the literature.

The group in Canada has extensively studied the factors (known as biomarkers) that can influence how people respond to anti-psychotic drugs, including if patients will develop side-effects. Our group in Liverpool has experience with compiling and analysing the large amounts of evidence required to prove a link between the biomarkers, and the patient’s response. The […]

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Predicting life history traits for data-poor ray species

Fisheries are the main global threat to elasmobranchs (sharks and rays). Elasmobranchs commonly display conservative life history traits (slow growth, long life, late sexual maturity and low fecundity), making them extremely vulnerable to non-natural mortalities. However, there is significant variation, with some species exhibiting life history traits more resilient to exploitation. In order to assess […]

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Impacts of warming on boreal peatland microbial community structure and function

Peatlands, a type of wetland containing a thick organic layer of partially decayed plant material, are the largest terrestrial carbon stocks. Climatic changes, including warming, could result in a lowering of the water table in peatlands, increasing oxygen availability to microbes and mesofauna allowing faster break down of the organic material and consequent release of […]

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Exploring the Risk Factors for Sequential or Concurrent Dengue and Zika Outbreaks in a Naïve Population

Arboviruses pose an ever-growing concern as the habitat of vectors expand alongside climate change. The outcome of outbreaks is often heavily influenced by the immune status of the population. Different pathogens can either protect against others or increase susceptibility and morbidity depending on infection timings and how closely related the pathogens are. A good example […]

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Social Media and Canadian Women’s Physical Activity Participation: Developing a New Methodology for Understanding Digital Health

The proposed research will explore how Canadian women’s interactions with health and fitness content on Instagram impacts upon physical activity participation. This research is sorely needed because, while social media is increasingly pertinent to the formation of everyday health practices, this dimension is seldom explored. In addition, this project will pilot a novel method, developed […]

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Ecophysiological consequences of environmental variability

Environmental variability is a fundamental component of adaptation; it is usually associated with modifications in the organism’s observable traits, particularly for those with limited plasticity. We will use a bioenergetic model as a framework to understand this variance in the organism’s traits. We will focus on the effect of individual physiological differences, which are represented […]

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Constrained Variational Ehrenfest

A first principles approach to molecular dynamics is crucial to understanding photo-chemical reactions. These reactions take place involving multiple electronic states, in other words, they undergo non-adiabatic dynamics. The problem is analogous to the many body problem where significant entanglement between the motion of electrons and nuclei is present. In this project we will develop […]

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Réseaux de neurones à décharges avec contraintes matérielles pour applications en périphérie

Ce projet de recherche a pour but d’améliorer la technologie des réseaux de neurones, pilier important de l’intelligence artificielle moderne, en s’inspirant du cerveau. Le but principal est d’être capable de réduire la consommation énergétique suffisamment pour pouvoir en profiter sur des appareils à énergie limités, tel que des téléphones cellulaires. Le cerveau, malgré ses […]

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Decoding the neural correlates of dynamic decision-making in humans

This research project will combine computational modeling, machine learning (ML) algorithms and whole-brain neural recordings (magnetoencephalography, MEG) to shed light on how the mechanisms underlying dynamic decision making are implemented in the human brain. Specifically, we will use the statistical framework of information theory to characterize inter-areal neural coupling and the direction of information flow […]

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Decoding the neural dynamics of emotion-related human memory optimization using AI-informed multivariate techniques

Episodic memory, our fascinating ability to encode and mentally relive past experiences, lies at the core of human cognition. It allows individuals not only to recall past events, but it is crucial in planning and guiding future behavior. However, among all of our daily-life experiences, only some events will be transformed into lasting memories, particularly […]

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Analyzing noise compensation properties of trained recurrent neural networks

Reliability is a fundamental requirement for computational systems, brains and artificial models alike: a system should respond the same way for repeated presentations of the same stimulus. However, the brain has two features that can threaten its reliability: intrinsic stochasticity and chaos. Stochasticity takes the form of random fluctuations affecting the reliability of components of […]

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