Publications by Christian Antonio Pozzorini

Simplification of spiking neural network models

Wulfram Gerstner, Henry Markram, Christian Antonio Pozzorini, James Gonzalo King, Eilif Benjamin Muller, Csaba Erö, Idan Segev, Willem Anna Mark Wybo, Christian Andreas Rössert

The simplification of neural network models is described. For example, a method for simplifying a neural network model includes providing the neural network model to be simplified, defining a first temporal filter for the conveyance of input from a neuron ...

2024

Simplification of neural network models

Wulfram Gerstner, Henry Markram, Christian Antonio Pozzorini, James Gonzalo King, Eilif Benjamin Muller, Csaba Erö, Idan Segev, Marc-Oliver Gewaltig, Willem Anna Mark Wybo, Christian Andreas Rössert

The simplification of neural network models is described. For example, a method for simplifying a neural network model includes providing the neural network model to be simplified, defining a first temporal filter for the conveyance of input from a neuron ...

2018

Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons

Wulfram Gerstner, Skander Mensi, Christian Antonio Pozzorini, Olivier Richard Hagens

The way in which single neurons transform input into output spike trains has fundamental consequences for network coding. Theories and modeling studies based on standard Integrate-and-Fire models implicitly assume that, in response to increasingly strong i ...

Public Library of Science2016

Automated High-Throughput Characterization of Single Neurons by Means of Simplified Spiking Models

Wulfram Gerstner, Skander Mensi, Christian Antonio Pozzorini, Richard Naud, Olivier Richard Hagens

Single-neuron models are useful not only for studying the emergent properties of neural circuits in large-scale simulations, but also for extracting and summarizing in a principled way the information contained in electrophysiological recordings. Here we d ...

Public Library of Science2015

Computational principles of single neuron adaptation

Christian Antonio Pozzorini

Cortical neurons continuously transform sets of incoming spike trains into output spike trains. This input-output transformation is referred to as single-neuron computation and constitutes one of the most fundamental process in the brain. A deep understand ...

EPFL2014

Temporal whitening by power-law adaptation in neocortical neurons

Wulfram Gerstner, Skander Mensi, Christian Antonio Pozzorini, Richard Naud

Spike-frequency adaptation (SFA) is widespread in the CNS, but its function remains unclear. In neocortical pyramidal neurons, adaptation manifests itself by an increase in the firing threshold and by adaptation currents triggered after each spike. Combini ...

Nature Publishing Group2013

Parameter extraction and classification of three cortical neuron types reveals two distinct adaptation mechanisms

Wulfram Gerstner, Skander Mensi, Carl Petersen, Christian Antonio Pozzorini, Michael Avermann, Richard Naud

Mensi S, Naud R, Pozzorini C, Avermann M, Petersen CCH, Gerstner W. Parameter extraction and classification of three cortical neuron types reveals two distinct adaptation mechanisms. J Neurophysiol 107: 1756-1775, 2012. First published December 7, 2011; do ...

American Physiological Society2012

Whole-embryo modeling of early segmentation in Drosophila identifies robust and fragile expression domains

Felix Naef, Christian Antonio Pozzorini, Jonathan Bieler

Segmentation of the Drosophila melanogaster embryo results from the dynamic establishment of spatial mRNA and protein patterns. Here, we exploit recent temporal mRNA and protein expression measurements on the full surface of the blastoderm to calibrate a d ...

2011