The brain is a highly complex organ and ubiquitous in our daily lives. However, little is understood about it or its functions. Undertaking the study of this organ is a challenging and fascinating endeavour and can spawn new technologies and alternative methods of treatment of diseases.

Research at the Institute of Computational and Systems Neuroscience encompasses theoretical, data-analytic and simulation approaches to develop multi-scale models of the brain. It is our firm belief that progress in understanding a complex system like the brain can only be achieved through this multi-faceted approach.

Directors: Prof. Dr. Sonja Grün and Prof. Dr. Markus Diesmann

Research groups at IAS-6

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Research Strategy

Research at IAS-6/ INM-10 follows a scientifc loop, where experimental data, theories and simulation are building up on each other. In collaboration the single working groups combine different expertise in one common scientific area - computational neuroscience. Find out more regarding our research strategy in our Research Overview.

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Computational Neurophysics group

The focus of the group of Markus Diesmann are bottom-up approaches in order to integrate physiological and anatomical data into models, in particular model development, theory of neuronal networks, and correlation dynamics. This also requires the development of simulation technology for neural networks.

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Statistical Neuroscience group

The research group of Sonja Grün at the Institute for Computational and Systems Neuroscience focuses on the development of analysis strategies and tools that uncover concerted activity in electrophysiological signals from the brain.

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Computation in Neural Circuits group

Investigation of mechanisms underlying neural computation through the development of models on the level of networks of spiking neurons. The group of Abigail Morrison applies a predominantly top-down approach to discover functional constraints on structure, plasticity and dynamics, particularly with respect to learning and memory.

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Theory of Multi-scale Neuronal Networks group

The focus of the group of Moritz Helias is the investigation of mechanisms that shape the activity in neuronal networks on multiple spatial scales. The group builds theoretical descriptions from the microscopic level of single cells and synapses to effective equations capturing interacting brain areas.

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Theoretical Neuroanatomy group

The work group led by Sacha van Albada studies the architecture and connectivity of brain circuits as the basis for neural network models at the resolution of neurons and synapses that relate structure to dynamics.

News and Events

NEST Conference 2024

We organize the annual NEST Conference which provides an opportunity for the NEST Community to meet, exchange success stories, swap advice, learn about current developments in and around NEST spiking network simulation and its application.

PLENA 2024: Pucón Learning and AI Summit

We are co-organizer of the Pucón Learning and AI Summit (PLENA) 2024 taking place in Pucón, Chile, on April 8-12 2024.

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Latest Publications

A modular and adaptable analysis pipeline to compare slow cerebral rhythms across heterogeneous datasets

Gutzen R., De Bonis G., De Luca C., Pastorelli E., Capone C., Mascaro ALA., Resta F., Manasanch A., Pavone FS., Sanchez-Vives MV., Mattia M., Grün S., Paolucci PS., Denker M.
Cell Reports Methods
10.1016/j.crmeth.2023.100681

Neuronal Population Activity in Macaque Visual Cortices Dynamically Changes through Repeated Fixations in Active Free Viewing
Sequence learning in a spiking neuronal network with memristive synapses Neuromorphic Computing and Engineering
Runtime Construction of Large-Scale Spiking Neuronal Network Models on GPU Devices
NMDA-driven dendritic modulation enables multitask representation learning in hierarchical sensory processing pathways