Directed cliques in neuronal networks and persistent homology representations

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• Martina Scolamiero (KTH - Royal Institute of Technology)
• Thursday 08 August 2024, 11:00-12:00
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HTA - Hypergraphs: Theory and Applications

This talk will be divided in two parts. In the first part we investigate the connectivity of directed networks representing brain microcircuits at the level of neurons and synapses. In particular we investigate the role of directed cliques within in-silico reconstructions of striatum, the input stage of the basal ganglia. Directed cliques turn out to be interesting motifs, to understand changes in the connectivity of striatum when modelling the impact of Parkinson disease progression at the neuron level [1]. Simplicial structures are the basis for investigating more complex patterns in weighted networks, as the ones given by persistent homology. In the second part of the talk we will discuss stable ranks with learnable parameters as a convenient framework to extract features from persistent homology that can be used for statistical analysis and machine learning [2]. [1] The impact of Parkinson’s disease on striatal network connectivity and cortico-striatal drive: an in-silico study I Carannante, M Scolamiero, JJJ Hjorth, A Kozlov, B Bekkouche, L Guo,  Arvind Kumar, Wojciech Chachólski, Jeanette Hellgren Kotaleski. Network Neuroscience, 1-35. Wasserstein distances and stable homological invariants of data J Agerberg, A Guidolin, I Ren, M Scolamiero - arXiv preprint arXiv:2301.06484, 2023.

This talk is part of the Isaac Newton Institute Seminar Series series.

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