select the most appropriate signal processing techniques for spectral analysis and for the analysis of spiking data.describe and use the most relevant signal processing techniques for spectral analysis and for the analysis of spiking data.read, interpret and design computer programs in MATLAB.compute the behavior of systems of linear differential equations.formulate, carry out, and write down mathematical computations in a correct way.interpret and apply methods and techniques of advanced calculus.interpret and apply the main concepts in linear algebra.Each topic (such as linear algebra, calculus, dynamical systems, Fourier decomposition, spike train analysis) will be covered by a theoretical introduction, followed by a demonstration on real data.Īt the end of the course students will be able to: The course has a strong practical component, where the emphasis is on the application of mathematical methods and analytical techniques. Students will learn mathematical foundations and methodologies for the analysis of neural signals, with a focus on computer-assisted analysis of neurophysiological data. The cloud environment SOWISO () will be used by students to learn, practice, and assess the mathematical methods and techniques taught in this course Foundations of information theory, encoding/decodingĪ short compendium of most of the topics covered during the course can be found in the following book: Wallish et al., Matlab for Neuroscientists (Second Edition), Elsevier.Analysis of single neuron and population activity.Analysis of neuronal spiking dataSpike sorting.Programming in MATLAB:Performing signal processing and statistics in MATLAB.Systems of linear differential equations.Calculus of functions of several variables.Mathematical methods for signal analysis:Linear algebra.The main subjects covered in the course will be:
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