A5043692408- Neural dynamics and brain function
- Advanced Memory and Neural Computing
- stochastic dynamics and bifurcation
- Functional Brain Connectivity Studies
- Neuroscience and Neural Engineering
- Neural Networks and Applications
- Photoreceptor and optogenetics research
- EEG and Brain-Computer Interfaces
- Neuroscience and Neuropharmacology Research
- Neural Networks and Reservoir Computing
- Visual perception and processing mechanisms
- Cell Image Analysis Techniques
- Nonlinear Dynamics and Pattern Formation
- Neurobiology and Insect Physiology Research
- Distributed and Parallel Computing Systems
- RNA regulation and disease
- Advanced Thermodynamics and Statistical Mechanics
- Scientific Computing and Data Management
- Animal Behavior and Reproduction
- CCD and CMOS Imaging Sensors
- Protein Structure and Dynamics
- Advanced Neuroimaging Techniques and Applications
- Gene Regulatory Network Analysis
- Research Data Management Practices
- Animal Vocal Communication and Behavior
Forschungszentrum Jülich
2016-2025
RWTH Aachen University
2016-2025
Ernst Ruska Centre
2021-2025
Jülich Aachen Research Alliance
2015-2024
KTH Royal Institute of Technology
2016
RIKEN Center for Brain Science
2007-2014
University of Freiburg
1996-2013
Bernstein Center for Computational Neuroscience Freiburg
2005-2013
RIKEN Center for Computational Science
2009-2012
RIKEN
2009-2011
In the past decade, cell-type specific connectivity and activity of local cortical networks have been characterized experimentally to some detail. parallel, modeling has established as a tool relate network structure dynamics. While available comprehensive maps ( Thomson, West, et al. 2002; Binzegger 2004) used in various computational studies, prominent features simulated such spontaneous firing rates do not match experimental findings. Here, we analyze properties these compile an...
The balanced random network model attracts considerable interest because it explains the irregular spiking activity at low rates and large membrane potential fluctuations exhibited by cortical neurons in vivo. In this article, we investigate to what extent is also compatible with experimentally observed phenomenon of spike-timing-dependent plasticity (STDP). Confronted plethora theoretical models for STDP available, reexamine experimental data. On basis, propose a novel update rule,...
It has been proposed that cortical neurons organize dynamically into functional groups (cell assemblies) by the temporal structure of their joint spiking activity. Here, we describe a novel method to detect conspicuous patterns coincident spike activity among simultaneously recorded single neurons. The statistical significance these unitary events is evaluated joint-surprise. tested and calibrated on basis simulated, stationary trains independently firing neurons, which were inserted under...
The availability of efficient and reliable simulation tools is one the mission-critical technologies in fast-moving field computational neuroscience. Research indicates that higher brain functions emerge from large complex cortical networks their interactions. number elements (neurons) combined with high connectivity (synapses) biological network specific type interactions impose severe constraints on explorable system size previously have been hard to overcome. Here we present a collection...
Correlations in spike-train ensembles can seriously impair the encoding of information by their spatio-temporal structure. An inevitable source correlation finite neural networks is common presynaptic input to pairs neurons. Recent theoretical and experimental studies demonstrate that spike correlations recurrent are considerably smaller than expected based on amount shared input. By means a linear network model simulations leaky integrate-and-fire neurons, we show shared-input efficiently...
The CoCoMac database contains the results of several hundred published axonal tract-tracing studies in macaque monkey brain. combined are used for constructing macro-connectome. Here we discuss redevelopment and compare it to six connectome-related projects: two online resources that provide full access raw tracing data rodents, a connectome viewer advanced 3D graphics, partial but highly detailed rat connectome, brain management system generates custom connectivity matrices, software...
Abstract State-of-the-art techniques allow researchers to record large numbers of spike trains in parallel for many hours. With enough such data, we should be able infer the connectivity among neurons. Here develop a method reconstructing neuronal circuitry by applying generalized linear model (GLM) cross-correlations. Our estimates connections between neurons units postsynaptic potentials and amount recordings needed verify connections. The performance inference is optimized counting...
While oscillations of the local field potential (LFP) are commonly attributed to synchronization neuronal firing rate on same time scale, their relationship coincident spiking in millisecond range is unknown. Here, we present experimental evidence reconcile notions synchrony at level and mesoscopic scale. We demonstrate that only intervals significant spike cannot be explained basis rates, spikes better phase locked LFP than predicted by locking individual spikes. This effect enhanced...
The digital neuromorphic hardware SpiNNaker has been developed with the aim of enabling large-scale neural network simulations in real time and low power consumption. Real-time performance is achieved 1 ms integration steps, thus applies to networks for which faster scales dynamics can be neglected. By slowing down simulation, shorter steps hence scales, are often biologically relevant, incorporated. We here describe first full-scale a cortical microcircuit biological on SpiNNaker. Since...
Cortical activity has distinct features across scales, from the spiking statistics of individual cells to global resting-state networks. We here describe first full-density multi-area network model cortex, using macaque visual cortex as a test system. The represents each area by microcircuit with area-specific architecture and layer- population-resolved connectivity between areas. Simulations reveal structured asynchronous irregular ground state. In metastable regime, reproduces...
State-of-the-art software tools for neuronal network simulations scale to the largest computing systems available today and enable investigations of large-scale networks up 10 % human cortex at a resolution individual neurons synapses. Due an upper limit on number incoming connections single neuron, connectivity becomes extremely sparse this scale. To manage computational costs, simulation ultimately targeting brain needs fully exploit sparsity. Here we present two-tier connection...
Brain-scale networks exhibit a breathtaking heterogeneity in the dynamical properties and parameters of their constituents. At cellular resolution, entities theory are neurons synapses over past decade researchers have learned to manage with efficient data structures. Already early parallel simulation codes stored distributed fashion such that synapse solely consumes memory on compute node harboring target neuron. As petaflop computers some 100,000 nodes become increasingly available for...
Correlated neuronal activity is a natural consequence of network connectivity and shared inputs to pairs neurons, but the task-dependent modulation correlations in relation behavior also hints at functional role. Correlations influence gain postsynaptic amount information encoded population decoded by readout synaptic plasticity. Further, it affects power spatial reach extracellular signals like local-field potential. A theory correlated accounting for recurrent as well fluctuating external...
Cortical networks that have been found to operate close a critical point exhibit joint activations of large numbers neurons. However, in motor cortex the awake macaque monkey, we observe very different dynamics: massively parallel recordings 155 single-neuron spiking activities show weak fluctuations on population level. This priori suggests operates noncritical regime, which models, has be suboptimal for computational performance. here, opposite: The dispersion correlations across neurons...
Abstract Cortical network structure has been extensively characterized at the level of local circuits and in terms long-range connectivity, but seldom a manner that integrates both these scales. Furthermore, while connectivity cortex is known to be related its architecture, this knowledge not used derive comprehensive cortical map. In study, we integrate data on architecture axonal tracing into consistent multi-scale framework one hemisphere macaque vision-related cortex. The model predicts...
Due to rapid advances in multielectrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity both basic research and clinical applications. Proper understanding LFP requires detailed mathematical modeling incorporating anatomical electrophysiological features neurons near electrode, as well synaptic inputs from entire network. Here we propose hybrid scheme combining efficiency commonly used simplified point-neuron network models with...
Abstract In recent years, brain research has indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration modelling at multiple scales—from molecules to the whole brain. Major are emerging intersection of neuroscience with technology computing. This science combines high-quality research, across scales, culture multidisciplinary large-scale collaboration, translation into applications. As pioneered in Europe’s Human Brain Project...