Lectures related to Spike Response Model (SRM)

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.

Models and data MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons

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

AdEx: Adaptive exponential integrate-and-fire MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons

Covers the AdEx model, firing patterns, adaptation, and parameter estimation.

Likelihood of Spike Train in GLM MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons

Covers the Generalized Linear Model (GLM) in computational neuroscience.

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

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

Modeling in vitro data MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons

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

Comparison of Noise Models MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons

Compares diffusive noise and escape noise models in computational neuroscience, discussing simulation, calculation, and model fitting.

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.

Scientific Computing in Neuroscience

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

Stochastic spike firing in integrate-and-fire models MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons

Explores stochastic spike firing in integrate-and-fire models and its impact on neural coding.

Understanding Noise in Electrical Systems

Explores noise sources, Fluctuation-Dissipation Theorem, amplifier noise, interference effects, and quantization error in electrical systems.

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.

Generalized Integrate-and-Fire Models MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons

Explores the Generalized Integrate-and-Fire Model and the Nonlinear Integrate-and-Fire Model.

Data Augmentation: Deep Learning

Explores data augmentation as a key regularization method in deep learning, covering techniques like translations, rotations, and artistic style transfer.

Noise in Data Acquisition

Explores noise sources in data acquisition, including thermal, shot, and amplifier noise, as well as the effects of ADC noise.

Interspike Intervals & Renewal Processes MOOC: Neuronal Dynamics - Computational Neuroscience of Single Neurons

Explores interspike intervals, renewal processes, and escape noise experiments in neuronal dynamics.

Image Processing Techniques Log in to Mediaspace to watch this video

Covers image processing techniques including noise addition, filtering, and image enhancement using various filters and tools.

Electrical Metrology Log in to Mediaspace to watch this video

Explores different types of noise in electrical systems and their impact on electronic devices.

Noise in Microelectronics Log in to Mediaspace to watch this video

Explores the impact of noise in microelectronics on various circuit stages and devices.

Noise Calculation in Circuits Log in to Mediaspace to watch this video

Covers noise analysis in circuits, including small-signal and input-referred noise, with examples of amplifiers and filters.