Neuronal Connectivity Patterns

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Structured Synaptic Connectivity in Hippocampal Regions

Explores synaptic connectivity in hippocampal regions, emphasizing the complexity of neuronal networks and the role of modeling approaches.

Introduction to Networks and Brain Networks

Introduces the fundamentals of network science, focusing on brain networks and their historical breakthroughs.

Statistical analysis of network data

Covers stochastic properties, network structures, models, statistics, centrality measures, and sampling methods in network data analysis.

In Silico Neuroscience: Network Simulation

Delves into simulating network dynamics in in silico neuroscience, covering spontaneous and evoked activity, in-vitro and in-vivo simulations, and sensitivity analysis.

Stochastic Block Model

Covers the Stochastic Block Model and its application in community detection, exploring its mathematical formulation and challenges.

Graphical Models: Probability Distributions and Factor Graphs

Covers graphical models for probability distributions and factor graphs representation.

Probabilistic method and its applications

Introduces the probabilistic method to prove existence results in graph theory.

Graphical Models: Representing Probabilistic Distributions

Covers graphical models for probabilistic distributions using graphs, nodes, and edges.

Message passing in graphical models

Explains message passing in graphical models and the matching problem in graph theory.

Networked Control Systems: Opportunities

Explores coordination in networked control systems, graph theory, and consensus algorithms.