Concept

Pseudounipolar neuron

Related lectures (16)

Neuronal Anatomy: Structure and Function

Explores the types of neurons, their structures, and the role of ganglia in the nervous system.

Covers the processing of EMG reflex figures and Excel charts.

Neuron Types: Classification and Morphological Diversity

Delves into neuron types, classification, challenges in reconstruction, staining techniques, and artifact correction, highlighting the importance of understanding brain complexity.

Experimental Data Techniques: Caveats and Summary

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

Connecting a single neuron to the brain

Emphasizes the importance of connecting a single neuron to the entire brain to understand cascade events at a larger scale.

Dendrite as a Cable

Discusses dendrites as cables, covering the cable equation derivation and current conservation in coupled compartments.

Neuronal Dynamics: Aims and Challenges

Explores the aims and challenges in computational neuroscience, focusing on neuronal dynamics of cognition and mean-field arguments.

Building a Data Model to Support a Scientific Usecase

Explores building a data model for scientific usecases and the significance of tracking data origin and usage.

Single Neuron Data Collection Techniques

Covers the methods for studying single neurons, including morphology and electrophysiology profiling.

Leaky Integrate-and-Fire Model

Explores the Leaky Integrate-and-Fire Model in computational neuroscience, emphasizing single neuron dynamics.

Models and data

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

Reduction to 2 dimensions: Exploiting similarities

Explores reducing the Hodgkin-Huxley model to 2 dimensions by exploiting similarities between variables and discussing the nonlinear integrate-and-fire model.

Biological Scope and Computational Simulation

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

Policy Gradient Methods: Single Neuron Example

Covers policy gradient methods using a single neuron with binary output.

Neural System Organization

Explores the organization of the nervous system, including neuron structure, synapses, neurotransmitters, and neural circuits.

Finding Parameters: Neuron Simulation Optimization

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