Marc-Oliver Gewaltig

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Being able to replicate real experiments with computational simulations is a unique opportunity to refine and validate models with experimental data and redesign the experiments based on simulations. However, since it is technically demanding to model all ...

The mouse brain contains a rich diversity of inhibitory neuron types that have been characterized by their patterns of gene expression. However, it is still unclear how these cell types are distributed across the mouse brain. We developed a computational m ...

From the computational point of view, musculoskeletal control is the problem of controlling high degrees of freedom and dynamic multi-body system that is driven by redundant muscle units. A critical challenge in the control perspective of skeletal joints w ...

We present a solution to two important problems that arise in the simulation of large data-driven neural networks: (a) efficient loading of network descriptions and (b) efficient instantiation of the network by executing the model specification. To address ...

There have been many advances in the field of reinforcement learning in continuous control problems. Usually, these approaches use deep learning with artificial neural networks for approximation of policies and value functions. In addition, there have been ...

In studies of the visual system as well as in computer vision, the focus is often on contrast edges. However, the primate visual system contains a large number of cells that are insensitive to spatial contrast and, instead, respond to uniform homogeneous i ...

Despite vast numbers of studies of stained cells in the mouse brain, no current brain atlas provides region-by-region neuron counts. In fact, neuron numbers are only available for about 4% of brain of regions and estimates often vary by as much as 3-fold. ...

The dendritic tree of neurons plays an important role in information processing in the brain. While it is thought that dendrites require independent subunits to perform most of their computations, it is still not understood how they compartmentalize into f ...

The aim of the neurorobotic platform of the Human Brain Project is to offer scientists and technology developers a soft - ware and hardware infrastructure that allows them to connect pre-validated brain models to detailed simulations of ro- bot bodies and ...

Developing neuro-inspired computing paradigms that mimic nervous system function is an emerging field of research that fosters our model understanding of the biological system and targets technical applications in artificial systems. The computational powe ...

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 ...

Marc-Oliver Gewaltig

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Experimental and Computational Study on Motor Control and Recovery After Stroke: Toward a Constructive Loop Between Experimental and Virtual Embodied Neuroscience

A method to estimate the cellular composition of the mouse brain from heterogeneous datasets

Optimum trajectory learning in musculoskeletal systems with model predictive control and deep reinforcement learning

Towards Simulating Data-Driven Brain Models at the Point Neuron Level on Petascale Computers

Learning Continuous Muscle Control for a Multi-joint Arm by Extending Proximal Policy Optimization with a Liquid State Machine

Feed-forward and noise-tolerant detection of feature homogeneity in spiking networks with a latency code

A Cell Atlas for the Mouse Brain

Corrigendum: A Cell Atlas for the Mouse Brain

Electrical Compartmentalization in Neurons

The Neurorobotic Platform: A simulation environment for brain-inspired robotics

A visual tracking model implemented on the iCub robot as a use case for a novel neurorobotic toolkit integrating brain and physics simulation

Spiking Network Models and Theory: Overview

Spiking Network Models and Theory: Overview

NEST: The Neural Simulation Tool

Simplification of neural network models

NEST: The Neural Simulation Tool