Lectures related to Physiology of CA1 cells

Reconstruction and simulation strategies MOOC: Simulation Neurocience

Explores reconstruction and simulation strategies in Simulation Neuroscience, emphasizing building components, workflows, validation, neuron diversity, microcircuit anatomy, and virtual tissue volumes.

Scientific Computing in Neuroscience

Explores the history and tools of scientific computing in neuroscience, emphasizing the simulation of neurons and networks.

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.

Rall's Cable Model MOOC: Simulation Neurocience

Explores Rall's cable model, synaptic potential spread in dendrites, and compartmental modeling for neural simulations.

Neurophysiological Data Analysis

Covers neurophysiological data analysis, including AP detection, firing rate computation, and spectral analysis, with a focus on predicting cell classes.

Role of the hippocampus MOOC: Simulating a hippocampus micro-circuit

Delves into the hippocampus's role in memory, space, and time encoding, and its implications in brain pathologies.

Threshold in the Hodgkin-Huxley Model MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons

Explores the firing threshold in the Hodgkin-Huxley model and the behavior of neurons under different current inputs.

Neurosciences I: Molecular Neuroscience and Neurodegeneration

Covers molecular neuroscience, neurodegeneration, cell types, neuron structure, and history of neuroscience breakthroughs.

Modelling principles for CA1 Microcircuit simulation MOOC: Simulating a hippocampus micro-circuit

Explores principles of data-driven modeling for simulating hippocampus microcircuits.

Action Potentials and Electrical Excitability

Explores the generation and propagation of action potentials in neurons, including the historical significance of Hodgkin & Huxley's work.

Reversal potential and Nernst equation MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons

Explores the reversal potential and Nernst equation in computational neuroscience, focusing on ion channels and neuron biophysics.

Neural Signals and Signal Processing: Modeling and Simulation

Covers the fundamentals of neural signals and signal processing, focusing on modeling and simulation of neural systems.

In Silico Neuroscience: Data Reproducibility and Reusability

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

Head direction cells MOOC: Neuronal Dynamics 2- Computational Neuroscience: Neuronal Dynamics of Cognition

Delves into head direction cells, encoding animal heading and persisting in the dark.

Escape noise MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons

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

Parameter estimation MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons

Explores parameter estimation in neuron models, focusing on quadratic optimization and linear fit.

Helping Humans: Neuroprosthetics MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons

Explores the application of computational neuroscience in neuroprosthetics, focusing on predicting intended arm movements based on spike times and the importance of systematic parameter optimization.

Theory of Decision Dynamics MOOC: Neuronal Dynamics 2- Computational Neuroscience: Neuronal Dynamics of Cognition

Explores decision dynamics in computational neuroscience, focusing on competitive models and effective 2-dimensional interactions between populations.

Three definitions of rate code MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons

Discusses three definitions of rate code in computational neuroscience, emphasizing temporal averaging, interspike intervals, and FANO factor.

Spike Response Model (SRM)MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons

Covers the Spike Response Model (SRM) in computational neuroscience and its relation to the adaptive leaky integrate-and-fire model.