Eilif Benjamin Muller

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Cortical dynamics underlie many cognitive processes and emerge from complex multi-scale interactions, which are challenging to study in vivo. Large-scale, biophysically detailed models offer a tool which can complement laboratory approaches. We present a m ...

Voltage-sensitive dye imaging (VSDI) is a powerful technique for interrogating membrane potential dynamics in assemblies of cortical neurons, but with effective resolution limits that confound interpretation. To address this limitation, we developed an in ...

The anatomy and physiology of monosynaptic connections in rodent hippocampal CA1 have been extensively studied in recent decades. Yet, the resulting knowledge remains disparate and difficult to reconcile. Here, we present a data-driven approach to integrat ...

Previous studies based on the 'Quantal Model' for synaptic transmission suggest that neurotransmitter release is mediated by a single release site at individual synaptic contacts in the neocortex. However, recent studies seem to contradict this hypothesis ...

The function of the neocortex is fundamentally determined by its repeating microcircuit motif, but also by its rich, hierarchical, interregional structure with a highly specific laminar architecture. The last decade has seen the emergence of extensive new ...

The CA1 region of the hippocampus is one of the most studied regions of the rodent brain, thought to play an important role in cognitive functions such as memory and spatial navigation. Despite a wealth of experimental data on its structure and function, i ...

Pyramidal cells (PCs) form the backbone of the layered structure of the neocortex, and plasticity of their synapses is thought to underlie learning in the brain. However, such long-term synaptic changes have been experimentally characterized between only a ...

Anatomically and biophysically detailed data-driven neuronal models have become widely used tools for understanding and predicting the behavior and function of neurons. Due to the increasing availability of experimental data from anatomical and electrophys ...

Every neuron is part of a network, exerting its function by transforming multiple spatiotemporal synaptic input patterns into a single spiking output. This function is specified by the particular shape and passive electrical properties of the neuronal memb ...

Increasing availability of comprehensive experimental datasets and of high-performance computing resources are driving rapid growth in scale, complexity, and biological realism of computational models in neuroscience. To support construction and simulation ...

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 ...

In connectomics, the study of the network structure of connected neurons, great advances are being made on two different scales: that of macro- and meso-scale connectomics, studying the connectivity between populations of neurons, and that of micro-scale c ...

Typical responses of cortical neurons to identical sensory stimuli appear highly variable. It has thus been proposed that the cortex primarily uses a rate code. However, other studies have argued for spike-time coding under certain conditions. The potentia ...

Neurons are thought to act as parts of assemblies with strong internal excitatory connectivity. Conversely, inhibition is often reduced to blanket inhibition with no targeting specificity. We analyzed the structure of excitation and inhibition in the MICrO ...

Computer-implemented methods, software, and systems for determining functional synapses from given structural touches between cells in a neuronal circuit are described. One computer-implemented method for determining functional synapses from predetermined ...

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 ...

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for reconstructing and simulating neocortical microcircuitry. In one aspect, a method includes providing a model of neural tissue, the model including differ ...

Eilif Benjamin Muller

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Modeling and simulation of neocortical micro- and mesocircuitry. Part II: Physiology and experimentation

In silico voltage-sensitive dye imaging reveals the emergent dynamics of cortical populations

Data-driven integration of hippocampal CA1 synaptic physiology in silico

Estimating the Readily-Releasable Vesicle Pool Size at Synaptic Connections in the Neocortex

Modeling and Simulation of Neocortical Micro- and Mesocircuitry. Part I: Anatomy

Community-based reconstruction and simulation of a full-scale model of region CA1 of rat hippocampus

A calcium-based plasticity model for predicting long-term potentiation and depression in the neocortex

HippoUnit: A software tool for the automated testing and systematic comparison of detailed models of hippocampal neurons based on electrophysiological data

The physiological variability of channel density in hippocampal CA1 pyramidal cells and interneurons explored using a unified data-driven modeling workflow

The SONATA data format for efficient description of large-scale network models

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

A null model of the mouse whole-neocortex micro-connectome

Cortical reliability amid noise and chaos

Specific inhibition and disinhibition in the higher-order structure of a cortical connectome

Structural to functional synaptic conversion

Simplification of spiking neural network models

Reconstruction and simulation of neocortical microcircuitry

Simplification of neural network models