Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Lecture

EFEL for Trace Analysis

Description

This lecture introduces the eFEL (eFeature Extraction Library) for automated analysis of neuronal traces, calculating spike count, spike height, and more. It covers defining features, creating objectives, and using an optimisation algorithm to find parameter values that match specified objectives.

In MOOC

Simulation Neurocience

Official source

Related concepts (32)

Neuroscience

Neuroscience is the scientific study of the nervous system (the brain, spinal cord, and peripheral nervous system), its functions and disorders. It is a multidisciplinary science that combines physiology, anatomy, molecular biology, developmental biology, cytology, psychology, physics, computer science, chemistry, medicine, statistics, and mathematical modeling to understand the fundamental and emergent properties of neurons, glia and neural circuits.

Computational neuroscience

Computational neuroscience (also known as theoretical neuroscience or mathematical neuroscience) is a branch of neuroscience which employs mathematical models, computer simulations, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system. Computational neuroscience employs computational simulations to validate and solve mathematical models, and so can be seen as a sub-field of theoretical neuroscience; however, the two fields are often synonymous.

Neuroinformatics

Neuroinformatics is the field that combines informatics and neuroscience. Neuroinformatics is related with neuroscience data and information processing by artificial neural networks. There are three main directions where neuroinformatics has to be applied: the development of computational models of the nervous system and neural processes.

Neural coding

Neural coding (or neural representation) is a neuroscience field concerned with characterising the hypothetical relationship between the stimulus and the individual or ensemble neuronal responses and the relationship among the electrical activity of the neurons in the ensemble. Based on the theory that sensory and other information is represented in the brain by networks of neurons, it is thought that neurons can encode both digital and analog information.

Statistical parameter

In statistics, as opposed to its general use in mathematics, a parameter is any measured quantity of a statistical population that summarises or describes an aspect of the population, such as a mean or a standard deviation. If a population exactly follows a known and defined distribution, for example the normal distribution, then a small set of parameters can be measured which completely describes the population, and can be considered to define a probability distribution for the purposes of extracting samples from this population.

Related lectures (31)

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.

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

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

Scientific Computing in Neuroscience

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

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

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

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