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Related lectures (32)

Network Simulation and Activity Dynamics

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

Neural Network Activity: Modeling and Analysis

Explores neural network modeling, sensitivity analysis, and replicating experimental conditions to understand brain activity.

Attractor Networks and Spiking Neurons

Explores attractor networks, spiking neurons, memory data, and realistic networks in neural dynamics.

Finding Parameters: Neuron Simulation Optimization

Explores finding parameters for neuron models and the importance of multi-objective optimization.

Introduction to Computer Science: Three Domains

Covers scientific computing, process automation, and data management in computer science applications across different sectors.

Understanding Neuronal Morphologies: NeuroM Basics

Covers NeuroM basics, including checking neuron quality, extracting morphometrics, and visualizing neurons in different formats.

Computational Neuroscience: Biophysics

Covers modern neuroscience synthesis, biophysical modeling, and brain building blocks with practical applications.

Neural Networks: Hierarchical Models and Odor Taxis

Covers neural function, hierarchical models, odor taxis behaviors, and disparate circuit parameters in 18 slides.

AdEx model: Firing patterns and phase plane analysis

Explores the AdEx neuron model, analyzing firing patterns and phase planes.

Introduction into the module

Introduces nerve cells' electrical activity, focusing on spikes and synaptic potentials.

In Silico Neuroscience: Ion Channels and Neuronal Models

Explores detailed modeling of ion channels and neuronal morphologies in in silico neuroscience, covering neuron classification, ion channel kinetics, and experimental observations.

Neural Networks: Perceptron

Covers the main concepts of neural networks, including the Perceptron model and training algorithms.

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