Leaky Integrate-and-Fire Model

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Explores modeling in vitro data for computational neuroscience, including predicting subthreshold voltage and spike times.

Escape noise

Explores escape noise in computational neuroscience, covering stochastic intensity, interspike intervals, likelihood functions, noise model comparison, and rate versus temporal codes.

Neuronal Dynamics: Aims and Challenges

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

Attractor Networks and Spiking Neurons

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

Biophysical Understanding of Neuronal Behavior

Explores the biophysical understanding of neuronal behavior, focusing on action potentials, neuron modeling challenges, and dendritic inhibition.

Scientific Computing in Neuroscience

Explores scientific computing in neuroscience, emphasizing the simulation of neurons and networks using tools like NEURON, NEST, and BRIAN.

Single Neuron Data Collection Techniques

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

Understanding Neuronal Morphologies: NeuroM Basics

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

Firing Threshold in 2D Models

Explores firing thresholds in 2D neuron models, pulse input, delayed spike initiation, and the FitzHugh-Nagumo model.

Biophysical Understanding of Neuronal Electrical Behavior

Explores the biophysical understanding of neuronal electrical behavior, including challenges in modeling neurons, the generation of action potentials, and the impact of dendritic structure on firing patterns.