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Related lectures (32)

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Hodgkin-Huxley Model: Neuronal Excitability

Explores the Hodgkin-Huxley model, action potential phases, ion dynamics, cable theory, and compartmental modeling in neuronal excitability.

Neuroscience Data Analysis

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

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Building Neural Networks: Assembly Strategies

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

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In Silico Neuroscience: Network Assembly

Explores assembling in silico neuroscience networks, defining space, and dealing with sparse data to reconstruct brain regions.

In Silico Neuroscience: Data Reproducibility and Reusability

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

Network Simulation and Activity Dynamics

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

Neuron Classification: Types and Challenges

Explores neuron classification, highlighting the importance of understanding brain complexity and the challenges in defining cell types.

Network Simulation: Spontaneous Activity and Validation

Covers spontaneous brain network activity, neural simulation, and validation, emphasizing the importance of in-vitro and in-vivo conditions for accurate network modeling.