Quantify biological shape through a reproducible three-dimensional morphometrics workflow in 3D Slicer and R. Participants connect image acquisition and resolution to segmentation and cleaning, collect landmarks and semilandmarks, and derive shape variables using Procrustes alignment and sliding procedures. Statistical exercises use principal components and regression to interpret size and shape variation; visualisations include deformations, morphings and heatmaps. Live sessions: 9–13 November, 13:00–18:00 daily, Europe/Madrid (CET, UTC+01:00). Total 30 hours: 25 live plus five independent.
Solve shape-analysis problems in R using measurements, landmarks and outlines. The programme develops data organisation and image processing before geometric transformations, alternative superimposition methods and Procrustes analysis. Participants visualise shape differences, test allometry and multivariate hypotheses, and compare principal-component, discriminant and regression approaches. Outline analysis introduces several Fourier representations and their statistical interpretation; participants can bring their own morphological datasets. Live sessions: 10, 11, 14, 15, 16, 17 and 18 Dece
Seminar · Computational Neuroscience
A specialized role for entorhinal attractor dynamics in combining path integration and landmarks during navigation
Malcolm Campbell · Harvard
Thu, Mar 9, 2023 · 15:00 UTC
During navigation, animals estimate their position using path integration and landmarks. In a series of two studies, we used virtual reality and electrophysiology to dissect how these inputs combine to generate the brain’s spatial representations. In the first study (Campbell et al., 2018), we focused on the medial entorhinal cortex (MEC) and its set of navigationally-relevant cell types, including grid cells, border cells, and speed cells. We discovered that attractor dynamics could explain an array of initially puzzling MEC responses to virtual reality manipulations. This theoretical framewo