Capturing the dynamical repertoire of single neurons with generalized linear models

A key problem in computational neuroscience is to find simple, tractable models that are nevertheless flexible enough to capture the response properties of real neurons. Here we examine the capabilities of recurrent point process models known as Poisson generalized linear models (GLMs). These models...

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Bibliographische Detailangaben

Hauptverfasser:	Weber, Alison I, Pillow, Jonathan W
Format:	Artikel
Sprache:	eng
Schlagworte:	Quantitative Biology - Neurons and Cognition
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