Patrick Desrosiers

This study characterizes brain maturation in larval zebrafish using brain-wide imaging, revealing changes in functional connectivity, network organization, and cellular activity patterns.

The paper evaluates using indicator species from co-occurrence networks to predict biodiversity, finding they can reconstruct species assemblages but are often outperformed by climate-based models.

The paper develops a framework using deep learning and graph theory to analyze neuronal network maturation from DHM images, identifying key topological changes during in vitro development.

The paper shows that sustained neuronal hyperactivity in wild-type and AD-like mice leads to proteomic changes similar to AD pathology, including memory loss and increased Aβ42 secretion.

The paper shows functional connectivity gradients in zebrafish brains align with geometric eigenmodes when connectivity is local, but this alignment breaks down with more long-range connections.

This study profiles neural dynamics across species during anaesthesia, finding conserved dynamical changes and linking them to molecular mechanisms.

NeuroTorch is a Python library that enables neuroscientists to use biologically inspired ML models for neuroscience tasks, achieving high accuracy on benchmark datasets and real neuronal activity data.

The paper investigates the structural and genetic basis of functional brain networks in zebrafish using whole-brain imaging and genetic expression data, revealing similarities to mammalian networks.

This paper develops a network-based method to reconstruct biodiversity using indicator species, finding that latitudinal gradients affect species composition and interaction patterns, with higher complexity in tropical regions.