Neurobiological constraints on learning: bug or feature?
Understanding how brains learn requires bridging evidence across scales—from behaviour and neural circuits to cells, synapses, and molecules. In our work, we use computational modelling and data analysis to explore how the physical properties of neurons and neural circuits constrain learning. These include limits imposed by brain wiring, energy availability, molecular noise, and the 3D structure of dendritic spines. In this talk I will describe one such project testing if wiring motifs from fly brain connectomes can improve performance of reservoir computers, a type of recurrent neural network. The hope is that these insights into brain learning will lead to improved learning algorithms for artificial systems.
Neural mechanisms of rhythmic motor control in Drosophila
All animal locomotion is rhythmic,whether it is achieved through undulatory movement of the whole body or the coordination of articulated limbs. Neurobiologists have long studied locomotor circuits that produce rhythmic activity with non-rhythmic input, also called central pattern generators (CPGs). However, the cellular and microcircuit implementation of a walking CPG has not been described for any limbed animal. New comprehensive connectomes of the fruit fly ventral nerve cord (VNC) provide an opportunity to study rhythmogenic walking circuits at a synaptic scale.We use a data-driven network modeling approach to identify and characterize a putative walking CPG in the Drosophila leg motor system.
Predicting traveling waves: a new mathematical technique to link the structure of a network to the specific patterns of neural activity
Imperial Neurotechnology 2022 - Annual Research Symposium
A diverse mix of neurotechnology talks and posters from researchers at Imperial and beyond. Visit our event page to find out more. The event is in-person but talk sessions will be broadcast via Teams.
NMC4 Short Talk: Maggot brain, mirror image? A statistical analysis of bilateral symmetry in an insect brain connectome
Neuroscientists have many questions about connectomes that revolve around the ability to compare networks. For example, comparing connectomes could help explain how neural wiring is related to individual differences, genetics, disease, development, or learning. One such question is that of bilateral symmetry: are the left and right sides of a connectome the same? Here, we investigate the bilateral symmetry of a recently presented connectome of an insect brain, the Drosophila larva. We approach this question from the perspective of two-sample testing for networks. First, we show how this question of “sameness” can be framed as a variety of different statistical hypotheses, each with different assumptions. Then, we describe test procedures for each of these hypotheses. We show how these different test procedures perform on both the observed connectome as well as a suite of synthetic perturbations to the connectome. We also point out that these tests require careful attention to parameter alignment and differences in network density in order to provide biologically meaningful results. Taken together, these results provide the first statistical characterization of bilateral symmetry for an entire brain at the single-neuron level, while also giving practical recommendations for future comparisons of connectome networks.
Mapping the brain’s remaining terra incognita
In this webinar, Dr Ye Tian and A/Prof Andrew Zalesky will present new research on mapping the functional architecture of the human subcortex. They used 3T and 7T functional MRI from more than 1000 people to map one of the most detailed functional atlases of the human subcortex to date. Comprising four hierarchical scales, the new atlas reveals the complex topographic organisation of the subcortex, which dynamically adapts to changing cognitive demands. The atlas enables whole-brain mapping of connectomes and has been used to optimise targeting of deep brain stimulation. This joint work with Professors Michael Breakspear and Daniel Margulies was recently published in Nature Neuroscience. In the second part of the webinar, Dr Ye Tian will present her current research on the biological ageing of different body systems, including the human brain, in health and degenerative conditions. Conducted in more than 30,000 individuals, this research reveals associations between the biological ageing of different body systems. She will show the impact of lifestyle factors on ageing and how advanced ageing can predict the risk of mortality. Associate Professor Andrew Zalesky is a Principal Researcher with a joint appointment between the Faculties of Engineering and Medicine at The University of Melbourne. He currently holds a NHMRC Senior Research Fellowship and serves as Associate Editor for Brain Topography, Neuroimage Clinical and Network Neuroscience. Dr Zalesky is recognised for the novel tools that he has developed to analyse brain networks and their application to the study of neuropsychiatric disorders. Dr Ye Tian is a postdoctoral researcher at the Department of Psychiatry, University of Melbourne. She received her PhD from the University of Melbourne in 2020, during which she established the Melbourne Subcortex Atlas. Dr Tian is interested in understanding brain organisation and using brain imaging techniques to unveil neuropathology underpinning neuropsychiatric disorders.