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TRENTOOL is an implementation of transfer entropy and mutual information analysis based on Wiener’s causality principle, aiming at the detection of model-free neuronal interactions in neural networks.
TRENTOOL is an implementation of transfer entropy and mutual information analysis based on Wiener’s causality principle, aiming at the detection of model-free neuronal interactions in neural networks.
Preprint of the forthcoming book chapter ‘Extracellular spikes and current-source density’ featuring the numerical framework biophysics for the calculation of extracellular potentials from transmembrane currents in multi-compartment neuron models, using the line-source method (Holt & Koch, J Comp Neurosci 1999).
LFPy is a Python package for calculation of extracellular potentials from multicompartment neuron models. It relies on the NEURON simulator and uses the Python interface it provides.
The Elements of Statistical Learning: Data Mining, Inference, and Prediction.
Download the book PDF (corrected 5th printing) here:
Intracranial recordings (ECoG) from nonprimary auditory cortex in the human superior temporal gyrus were reconstructed in to speech sounds.
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Machine Learning LFP Noise Wavelets Modelling Information Theory Dimensionality Reduction Neural Networks Clustering Brain Interfaces Neurophysiology Statistical Analysis Spike Sorting Brain Research
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