Publications de Idan Segev | EPFL Graph Search

Simplification of spiking neural network models

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

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

Statistical Emulation of Neural Simulators: Application to Neocortical L2/3 Large Basket Cells

Idan Segev, Werner Alfons Hilda Van Geit, Oren Amsalem

Many scientific systems are studied using computer codes that simulate the phenomena of interest. Computer simulation enables scientists to study a broad range of possible conditions, generating large quantities of data at a faster rate than the laboratory ...

FRONTIERS MEDIA SA2022

The Role of Hub Neurons in Modulating Cortical Dynamics

Henry Markram, Felix Schürmann, Idan Segev, Oren Amsalem, Eyal Gal, Michael London

Many neurodegenerative diseases are associated with the death of specific neuron types in particular brain regions. What makes the death of specific neuron types particularly harmful for the integrity and dynamics of the respective network is not well unde ...

2021

An efficient analytical reduction of detailed nonlinear neuron models

Felix Schürmann, Idan Segev, Pramod Shivaji Kumbhar, Michael Emiel Gevaert, Oren Amsalem, Guy Eyal

Detailed conductance-based nonlinear neuron models consisting of thousands of synapses are key for understanding of the computational properties of single neurons and large neuronal networks, and for interpreting experimental results. Simulations of these ...

Nature Research2020

Simplification of neural network models

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

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

Rich cell-type-specific network topology in neocortical microcircuitry

Henry Markram, Eilif Benjamin Muller, Srikanth Ramaswamy, Michael Reimann, Idan Segev, Eyal Gal, Michael London

Uncovering structural regularities and architectural topologies of cortical circuitry is vital for understanding neural computations. Recently, an experimentally constrained algorithm generated a dense network reconstruction of a similar to 0.3-mm(3) volum ...

Nature Publishing Group2017

Comprehensive Morpho-Electrotonic Analysis Shows 2 Distinct Classes of L2 and L3 Pyramidal Neurons in Human Temporal Cortex

Lida Kanari, Idan Segev, Guy Antoine Atenekeng Kahou, Guy Eyal, Yair Deitcher

There have been few quantitative characterizations of the morphological, biophysical, and cable properties of neurons in the human neocortex. We employed feature-based statistical methods on a rare data set of 60 3D reconstructed pyramidal neurons from L2 ...

2017

Timed Synaptic Inhibition Shapes NMDA Spikes, Influencing Local Dendritic Processing and Global I/O Properties of Cortical Neurons

Henry Markram, Eilif Benjamin Muller, Idan Segev, Giuseppe Chindemi, Michael Doron

The NMDA spike is a long-lasting nonlinear phenomenon initiated locally in the dendritic branches of a variety of cortical neurons. It plays a key role in synaptic plasticity and in single-neuron computations. Combining dynamic system theory and computatio ...

2017

Comments and General Discussion on “The Anatomical Problem Posed by Brain Complexity and Size: A Potential Solution”

Sean Lewis Hill, Idan Segev

This article gathers together different opinions on the current status and future directions of the study of the brain, taking as a working document the article “The anatomical problem posed by brain complexity and size: a potential solution” http://journa ...

Frontiers Research Foundation2016

BluePyOpt: Leveraging Open Source Software and Cloud Infrastructure to Optimise Model Parameters in Neuroscience

Henry Markram, Felix Schürmann, Eilif Benjamin Muller, Idan Segev, Werner Alfons Hilda Van Geit, Jean-Denis Georges Emile Courcol, Giuseppe Chindemi, Michael Emiel Gevaert

At many scales in neuroscience, appropriate mathematical models take the form of complex dynamical systems. Parametrising such models to conform to the multitude of available experimental constraints is a global nonlinear optimisation problem with a comple ...

Frontiers Research Foundation2016