Neural Signals and Connectomes

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (29)

Connectivity-Informed Brain Activity Interpretation Log in to Mediaspace to watch this video

Explores integrating brain connectivity to decode and interpret brain activity using graph signal processing and spectral residual networks.

Statistical Analysis of Network Data Log in to Mediaspace to watch this video

Introduces network data structures, models, and analysis techniques, emphasizing permutation invariance and Erdős-Rényi networks.

Sparsest Cut: ARV Theorem Log in to Mediaspace to watch this video

Covers the proof of the Bourgain's ARV Theorem, focusing on the finite set of points in a semi-metric space and the application of the ARV algorithm to find the sparsest cut in a graph.

Graph Theory Fundamentals Log in to Mediaspace to watch this video

Explores fundamental graph theory concepts, Erdős' results, Chromatic Lemma, and Union Bound theorem in graph theory.

Expander Graphs: Properties and Eigenvalues Log in to Mediaspace to watch this video

Explores expanders, Ramanujan graphs, eigenvalues, Laplacian matrices, and spectral properties.

Neuronal Connectivity Patterns Log in to Mediaspace to watch this video

Explores neuronal connectivity patterns, connection probabilities, and experimental techniques used to study synaptic connectivity.

Interlacing Families and Ramanujan Graphs Log in to Mediaspace to watch this video

Explores interlacing families of polynomials and 1-sided Ramanujan graphs, focusing on their properties and construction methods.

Distances and Motif Counts Log in to Mediaspace to watch this video

Explores distances on graphs, cut norms, spanning trees, blockmodels, metrics, norms, and ERGMs in network data analysis.

Sparsest Cut and Concurrent Flow Log in to Mediaspace to watch this video

Covers sparsest cut, NP-completeness, Bougains Theorem, and concurrent flow in graphs.

Page 2 of 2