Neural Signal Processing
Description: The auditory system activates of a complex network of billions of interconnected neurons. Modern neuroscience techniques enable us to access, characterize and model this activity. In order to increase this understanding and to design implantable auditory prostheses that interact with neural circuits, advanced statistical signal processing and machine learning approaches are required. This class will cover a range of techniques and their application to model auditory system. Neuroscience applications include modeling action potentials and firing rates, decoding, spike sorting, and field potential analysis.
1. Introduction
2. Fundamental Neurobiology
3. Modeling spike trains
4. Point processes
5. Classification
6. Clustering / Mixture models
7. Continuous Decoding
8. Spectral Analysis
Goals: Students will learn the fundamentals of how the activity of neurons represent information within in the brain, how this can be modelled, and how to decode underlying information from the resulting neural data. Outcome: Students completing the course should be able to: - Understand the fundamentals of neural information processing - Understand mathematically models of the electrophysiological behavior of neurons - Extract information from neural data
Prior Knowledge: Basics in mathematics.
Date: 29.‐31.03.2016
Place: tba
Course organiser: Jun.‐Prof. Waldo Nogueira
Credit: 15 hours
Registration: Zschau.christine@mh‐hannover.de
1. Introduction
2. Fundamental Neurobiology
3. Modeling spike trains
4. Point processes
5. Classification
6. Clustering / Mixture models
7. Continuous Decoding
8. Spectral Analysis
Goals: Students will learn the fundamentals of how the activity of neurons represent information within in the brain, how this can be modelled, and how to decode underlying information from the resulting neural data. Outcome: Students completing the course should be able to: - Understand the fundamentals of neural information processing - Understand mathematically models of the electrophysiological behavior of neurons - Extract information from neural data
Prior Knowledge: Basics in mathematics.
Date: 29.‐31.03.2016
Place: tba
Course organiser: Jun.‐Prof. Waldo Nogueira
Credit: 15 hours
Registration: Zschau.christine@mh‐hannover.de