Neuron

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Related lectures (32)

Page 3 of 4

Finding Parameters: Neuron Simulation Optimization

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

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.

Models and data

Covers the optimization of neuron models for coding and decoding in computational neuroscience.

Principles of Simulation Neuroscience

Covers the principles of Simulation Neuroscience, focusing on dense reconstruction from sparse data and iteratively reconstructing and testing models.

Neural Networks: Training and Activation

Explores neural networks, activation functions, backpropagation, and PyTorch implementation.

Introduction to the CA1 microcircuit

Covers the introduction to the CA1 microcircuit and its diverse neuronal components, connectivity, and electrical properties.

Dose Management in Electron Microscopy

Explores the challenges and solutions for managing electron dose in microscopy, emphasizing the importance of accurate dose tracking and analysis.

Neuroscience Data Analysis

Explores neuroscience data analysis, emphasizing structured data, computational tools, and the trend of computational neuroscience as a service.

Morphological Profiles

Covers the diversity of morphological features in neurons and methods to increase the dataset.

Experimental Data Techniques: Caveats and Summary

Explores the study of single neurons, challenges in classification, and obtaining high-resolution data.