A universal workflow for creation, validation and generalization of detailed neuronal models

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Publications associées (31)

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Online interoperable resources for building hippocampal neuron models via the Hippocampus Hub

Felix Schürmann, Armando Romani

To build biophysically detailed models of brain cells, circuits, and regions, a data-driven approach is increasingly being adopted. This helps to obtain a simulated activity that reproduces the experimentally recorded neural dynamics as faithfully as possi ...

2023

Molecular reconstruction and simulation of the Neuron-Glia-Vasculature system

Polina Shichkova

The outstanding information processing capacity of the brain relies on numerous molecular mechanisms. It is an extremely energy-expensive function, which involves specialization and collaboration of different cell types. A common framework to study the com ...

EPFL2023

Axonal projections from mouse whisker-related sensory cortex

Yanqi Liu

Neurons primarily communicate through release of neurotransmitter from presynaptic specialisations along their axonal arborisations. In order to understand the functional role of a specific neuron, it is therefore of great interest to know the structure of ...

EPFL2023

Brain dynamics uncovered using a machine-learning algorithm

Mackenzie Mathis

CEBRA is a machine-learning method that can be used to compress time series in a way that reveals otherwise hidden structures in the variability of the data. It excels at processing behavioural and neural data recorded simultaneously, and it can decode act ...

NATURE PORTFOLIO2023

Design and experimental investigation of a herringbone grooved gas bearing supported turbocharger

Jürg Alexander Schiffmann, Wanhui Liu

The design of an oil free turbocharger supported on herringbone grooved gas bearing was formulated as a multi-objective problem, which was solved by coupling a reduced order parametric model for gas bearing supported rotors with an evolutionary algorithm. ...

2023

Assemblies, synapse clustering and network topology interact with plasticity to explain structure-function relationships of the cortical connectome

Eilif Benjamin Muller, Michael Reimann, Marwan Muhammad Ahmed Abdellah, James Gonzalo King, András Ecker, Pramod Shivaji Kumbhar, Giuseppe Chindemi, Daniela Egas Santander, James Bryden Isbister, Ioannis Magkanaris, Sirio Bolaños Puchet, Jorge Blanco Alonso

Synaptic plasticity underlies the brain’s ability to learn and adapt. While experiments in brain slices have revealed mechanisms and protocols for the induction of plasticity between pairs of neurons, how these synaptic changes are coordinated in biologica ...

2024

Playing Brains: The Ethical Challenges Posed by Silicon Sentience and Hybrid Intelligence in DishBrain

Georg Michael Joachim Starke

The convergence of human and artificial intelligence is currently receiving considerable scholarly attention. Much debate about the resulting Hybrid Minds focuses on the integration of artificial intelligence into the human brain through intelligent brain- ...

2023

A dynamic attractor network model of memory formation, reinforcement and forgetting

Wulfram Gerstner, Chiara Gastaldi

Empirical evidence shows that memories that are frequently revisited are easy to recall, and that familiar items involve larger hippocampal representations than less familiar ones. In line with these observations, here we develop a modelling approach to pr ...

Public Library Science2023

Principles of Network Plasticity in Neocortical Microcircuits

András Ecker

Synaptic plasticity underlies our ability to learn and adapt to the constantly changing environment. The phenomenon of synapses changing their efficacy in an activity-dependent manner is often studied in small groups of neurons in vitro or indirectly throu ...

EPFL2023

Mini-review: Transcranial Alternating Current Stimulation and the Cerebellum

Friedhelm Christoph Hummel, Maximilian Jonas Wessel, Laurijn Rianne Draaisma

Oscillatory activity in the cerebellum and linked networks is an important aspect of neuronal processing and functional implementation of behavior. So far, it was challenging to quantify and study cerebellar oscillatory signatures in human neuroscience due ...

2023

Brain structure-function coupling is unique to individuals across multiple frequency bands: a graph signal processing study

Alessandra Griffa, Maria Giulia Preti

The relation between brain functional activity and the underlying structure is complex and varies depending on the specific brain region. Recently, we used graph signal processing to introduce the structural-decoupling index (SDI), a novel metric quantifyi ...

IEEE2022