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Label-Free Long-Term Methods for Live Cell Imaging of Neurons: New Opportunities

Publications associées (32)

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Cortical cell assemblies and their underlying connectivity: An in silico study

Michael Reimann, András Ecker, Sirio Bolaños Puchet, James Bryden Isbister, Daniela Egas Santander

Recent developments in experimental techniques have enabled simultaneous recordings from thousands of neurons, enabling the study of functional cell assemblies. However, determining the patterns of synaptic connectivity giving rise to these assemblies rema ...

2024

Cortical cell assemblies and their underlying connectivity: an in silico study

Michael Reimann, András Ecker, Sirio Bolaños Puchet, James Bryden Isbister, Daniela Egas Santander

2023

Mesoscopic description of hippocampal replay and metastability in spiking neural networks with short-term plasticity

Tilo Schwalger, Valentin Marc Schmutz

Bottom-up models of functionally relevant patterns of neural activity provide an explicit link between neuronal dynamics and computation. A prime example of functional activity patterns are propagating bursts of place-cell activities called hippocampal rep ...

PUBLIC LIBRARY SCIENCE2022

The development of novel fluorogenic probes and their use in live-cell imaging lead to a plethora of discoveries in biological research. Herein I report on novel red fluorogenic probes for live-cell super-resolution microscopy of various cellular organelle ...

EPFL2020

The interpretation of neuronal spike train recordings often relies on abstract statistical models that allow for principled parameter estimation and model selection but provide only limited insights into underlying microcircuits. In contrast, mechanistic m ...

2019

How single neuron properties shape chaotic dynamics and signal transmission in random neural networks

Wulfram Gerstner, Tilo Schwalger, Samuel Pavio Muscinelli

While most models of randomly connected neural networks assume single-neuron models with simple dynamics, neurons in the brain exhibit complex intrinsic dynamics over multiple timescales. We analyze how the dynamical properties of single neurons and recurr ...

2019

Data-driven reconstruction of a point neuron mouse brain

Csaba Erö

In this work, we present a semi-automatic method to reconstruct a mouse whole-brain model at the point-neuron level by integrating a wide array of biological data. Our process has three parts: cell position and type assignment, connectivity mapping, and si ...

EPFL2018

Nonlinear microscopy for temporally and spatially resolved label-free imaging of living cells

Marie Eve Pascale Didier

The human brain consists of approximately a hundred billion of neurons that communicate through a unique series of biochemical and electrical processes. When neuronal networks are solicited, electrochemical processes happen involving millions of cells with ...

EPFL2018

Point process generalized linear models (PP-GLMs) provide an important statistical framework for modeling spiking activity in single-neurons and neuronal networks. Stochastic stability is essential when sampling from these models, as done in computational ...

Public Library of Science2017

By live-cell imaging of biological samples dynamic cellular processes can be resolved. Fluorescence microscopy (FM) and atomic force microscopy (AFM) are both capable of imaging live cells. By combining these techniques structural as well as functional inf ...

EPFL2016