BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Lida Kanari (University of Oxford) DTSTART:20251114T160000Z DTEND:20251114T170000Z DTSTAMP:20261025T134156Z UID:GEOTOP-A/112 DESCRIPTION:Title: From Neurons to Networks: Exploring the Brain Through Algebraic Topolog y\nby Lida Kanari (University of Oxford) as part of GEOTOP-A seminar\n \n\nAbstract\nHow can mathematics help us understand the brain? In recent years\, a field called topological data analysis (TDA) has offered powerfu l new ways to study complex systems (from protein shapes to brain networks ) by capturing their underlying structure. In neuroscience\, these tools h elp us uncover the hidden patterns that shape how brain cells connect and communicate. The Topological Morphology Descriptor (TMD\, [1])\, turns the branching shapes of neurons into mathematical “barcodes” that summari ze their structure. This approach allows us to classify\, cluster and comp are neurons across different types and species.\n\nIn this talk\, I will p resent recent results in the topological representation of brain cells\, f ocusing on neurons. I will then demonstrate how algebraic topology provide s insights into the relationships between single neurons and networks\, al lowing us to bridge different computational scales.\n\nA central question in neuroscience concerns the organizational principles that distinguish th e human brain from other species. Our findings [2] suggest that human neur ons are strikingly more complex than those in other animals. In particular \, human pyramidal cells\, the most abundant cell type in the cortex\, for m denser\, more interconnected networks. This greater dendritic complexity \, a unique characteristic of human neurons\, may underlie the enhanced co mputational power and cognitive flexibility of the human cortex.\n\n[1] Ka nari et al. 2018. A Topological representation of branching neuronal morph ologies\n\n[2] Kanari et al. 2025. Of mice and men: Dendritic architecture differentiates human from mouse neuronal networks\n LOCATION:https://researchseminars.org/talk/GEOTOP-A/112/ END:VEVENT END:VCALENDAR