If the mind controls the brain, then there is free will and its corollaries, dignity and responsibility. You are king in your skull-sized kingdom and the architect of your destiny. If, on the other hand, the brain controls the mind, an incendiary conclusion follows: There can be no free will, no praise, no punishment and no purgatory. In this webinar, Professor George Paxinos will discuss his highly respected work on the construction of human and experimental animal brain atlases. He has discovered 94 brain regions, 64 homologies and published 58 books. His first book, The Rat Brain in Stereotaxic Coordinates, is the most cited publication in neuroscience and, for three decades, the third most cited book in science. Professor Paxinos will also present his recently published novel, A River Divided, which was 21 years in the making. Neuroscience principles were used in the formation of charters, such as those related to the mind, soul, free will and consciousness. Environmental issues are at the heart of the novel, including the question of whether the brain is the right ‘size’ for survival. Professor Paxinos studied at Berkeley, McGill and Yale and is now Scientia Professor of Medical Sciences at Neuroscience Research Australia and The University of New South Wales in Sydney.

Neuroscientists routinely perform experiments aimed at recording or manipulating neural activity, uncovering physiological processes underlying brain function or elucidating aspects of brain anatomy. Understanding how the brain generates behaviour ultimately depends on merging the results of these experiments into a unified picture of brain anatomy and function. We present BrainGlobe, a new initiative aimed at developing common Python tools for computational neuroanatomy. These include cellfinder for fast, accurate cell detection in whole-brain microscopy images, brainreg for aligning images to a reference atlas, and brainrender for visualisation of anatomically registered data. These software packages are developed around the BrainGlobe Atlas API. This API provides a common Python interface to download and interact with reference brain atlases from multiple species (including human, mouse and larval zebrafish). This allows software to be developed agnostic to the atlas and species, increasing adoption and interoperability of software tools in neuroscience.

Over the past years, genetic studies have uncovered hundreds of genetic variants to be associated with complex brain disorders. While this really represents a big step forward in understanding the genetic etiology of brain disorders, the functional interpretation of these variants remains challenging. We aim to help with the functional characterization of variants through transcriptomic data analysis. For instance, we rely on brain transcriptome atlases, such as Allen Brain Atlases, to infer functional relations between genes. One example of this is the identification of signaling mechanisms of steroid receptors. Further, by integrating brain transcriptome atlases with neuropathology and neuroimaging data, we identify key genes and pathways associated with brain disorders (e.g. Parkinson's disease). With technological advances, we can now profile gene expression in single-cells at large scale. These developments have presented significant computational developments. Our lab focuses on developing scalable methods to identify cells in single-cell data through interactive visualization, scalable clustering, classification, and interpretable trajectory modelling. We also work on methods to integrate single-cell data across studies and technologies.