Network Simulation: Spontaneous Activity and Validation

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Network Simulation and Activity Dynamics

Explores neural network simulation, activity dynamics, and validation processes to ensure accurate predictions.

Scientific Computing in Neuroscience

Explores the history and tools of scientific computing in neuroscience, emphasizing the simulation of neurons and networks.

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.

Building Neural Networks: Assembly Strategies

Focuses on assembling neural network building blocks and dealing with data sparseness using various strategies and assumptions.

Neuroscience Data Analysis

Explores neuroscience data analysis, focusing on K+ and Na+ currents, Ca²+ currents, and data reproducibility.

In Silico Neuroscience: Data Reproducibility and Reusability

Emphasizes data reproducibility and reusability in in silico neuroscience, focusing on neuroinformatics tools and methods.

Structured Synaptic Connectivity

Explores the structured synaptic connectivity between hippocampal regions using techniques like mGRASP and modeling.

Modeling Neuronal Activity

Explores modeling neuronal activity, including firing rates, responses to stimuli, and network behavior.

Neural Signals and Signal Processing: Modeling and Simulation

Covers the fundamentals of neural signals and signal processing, focusing on modeling and simulation of neural systems.

Biological Scope and Computational Simulation

Explores connecting biological scope with computational simulation methods and discusses various simulation environments for modeling neural activity.