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Prof. Dr. Stefan Rotter

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Professor of Computational Neuroscience
Bernstein Center Freiburg and Faculty of Biology
University of Freiburg
Hansastr. 9a
79104 Freiburg, Germany
Tel.: +49 (0)761 203-9316
Fax: +49 (0)761 203-9559
stefan.rotter@bio.uni-freiburg.de
 


Research Interests

My Computational Neuroscience Laboratory comprises a team of theoreticians from mathematics, physics, biology and various engineering sciences. We are interested in the relations between structure, dynamics and function of the neuronal networks of the brain, with a specific focus on the mammalian neocortex. Our work involves modeling and data analysis of (i) multi-scale neuronal network topology, (ii) spiking activity dynamics of recurrent networks, (iii) functional and/or structural synaptic plasticity and learning networks, as well as (iv) biological function and dysfunction of neuronal networks. Mathematical (deterministic and stochastic) as well as computational methods (large-scale numerical simulations) are employed. The goal is to develop a network-based theory of the brain which also supports a better understanding of the neuronal mechanisms underlying some brain diseases.
 

Research Topics

  • Computational neuroscience & brain theory
  • Relations between structure, dynamics & function in neuronal networks
  • Spiking activity dynamics in recurrent networks
  • Dynamic ensemble coding in structured networks
  • Dynamic graphs and self-organizing networks

 

Techniques

  • Stochastic modeling of neuronal activity (e.g. stochastic point processes)
  • Stochastic modeling of neuronal networks (e.g. dynamic graph models)
  • Advanced statistical data analysis (e.g. higher-order correlations)
  • Large-scale numerical simulations

 

Academic Background

  • 2003: Habilitation in Neurobiology/Biophysics, University of Freiburg
  • 1994: PhD (Dr. rer. nat.) in Physics, University of Tübingen
  • 1989 – 1992: PhD studies in Neuroscience, Max Planck Institute for Biological Cybernetics
    and University of Tübingen
  • 1989: Diploma (MSc) in Mathematics, University of Hamburg
  • 1982 – 1989: Studies in Mathematics and Physics, University of Regensburg (Germany),
    Brandeis University Waltham (USA) and University of Hamburg (Germany)
     

Research Positions

  • since 2008: Professor of Computational Neuroscience (full professor, W3)
    Faculty of Biology & Bernstein Center Freiburg, University of Freiburg
  • 2002 – 2008: Staff Scientist (tenured), Theoretical and Computational Neuroscience
    Institute for Frontier Areas of Psychology and Mental Health, Freiburg;
    Senior Scientist and Lecturer, Faculty of Biology, University of Freiburg
  • 1996 – 2002: Research Assistant (C1) of Theoretical Neurobiology and Biophysics
    Faculty of Biology, University of Freiburg
  • 1993 – 1996: Postdoctoral Research Fellow
    Max Planck Institute for Developmental Biology, Tübingen
  • 1989 – 1992: Research Associate
    Max Planck Institute for Biological Cybernetics, Tübingen
     

Professional Activities

  • since 2009: Founding Member and Managing Director of the Bernstein Center Freiburg
  • 2012: Instructional Development Award (IDA), together with Dr. Janina Kirsch
  • since 2012: Principal Investigator in the Cluster of Excellence BrainLinks-BrainTools,
    2015 - 2020 member of its Executive Board
  • since 2017: Member of the Steering Committee of the Bernstein Network Computational Neuroscience
  • 2015 – 2019: Member of the Executive Committee of the German Neuroscience Society (GNS) and Spokesperson of the Section Computational Neuroscience
  • since 2013: Appointed representative in the User Committee for large-scale IT infrastructures in the State of Baden-Württemberg (bwHPC, bwData), since 2020 elected spokesperson of the User Committee
  • since 2018: Co-spokesperson of the “NFDI Neuroscience” initiative
  • 2022 - 2024: Member of the DFG Review Board “206-03 Experimental and Theoretical Network Neuroscience

 

Publications

In German

 

Articles in Journals

Under Review

  • Wei W, Merkt B, Rotter S
    Neuronal selectivity for multiple features in the primary visual cortex
    bioRxiv (pdf) 
  • Wei W, Rotter S
    The role of cortico-thalamic feedback for visual information processing
    bioRxiv (pdf) 

2025

  • Lu H, Frase L, Normann C, Rotter S
    Resolving inconsistent effects of tDCS on learning using a homeostatic structural plasticity model
    bioRxiv (pdf) 

2024

  • Schulze-Bonhage A, Nitsche MA, Rotter S, Focke NK, Rao VR
    Neurostimulation targeting the epileptic focus: Current understanding and perspectives for treatment
    Seizure 117: 183-192, 2024 (pdf)

2023

  • Anil S, Lu H, Rotter S, Vlachos A
    Repetitive transcranial magnetic stimulation (rTMS) triggers
    dose-dependent homeostatic rewiring in recurrent neuronal networks
    PLOS Computational Biology 19(11): e1011027, 2023 (pdf)

2022

  • Lu H, Gallinaro JV, Normann C, Rotter S, Yalçın I
    Time Course of Homeostatic Structural Plasticity in Response to Optogenetic Stimulation in Mouse Anterior Cingulate Cortex
    Cerebral Cortex 32(8): 1574-1592, 2022 (pdf | synopsis) 
  • Gallinaro J, Gašparović N, Rotter S 
    Homeostatic control of synaptic rewiring in recurrent networks induces the formation of stable memory engrams
    PLOS Computational Biology 18(2): e1009836, 2022 (pdf | synopsis)
  • Pfaffelhuber P, Rotter S, Stiefel J 
    Mean-field limits for non-linear Hawkes processes with excitation and inhibition 
    Stochastic Processes and their Applications 153: 57-78, 2022 (pdf)

2021

  • Spreizer S, Senk J, Rotter S, Diesmann M, Weyers B 
    NEST Desktop, an Educational Application for Neuroscience 
    eNeuro 8(6): ENEURO.0274-21.2021,2021 (pdf | synopsis)
  • Nejad MM, Rotter S, Schmidt R
    Basal ganglia and cortical control of thalamic rebound spikes
    European Journal of Neuroscience 54: 4295–4313, 2021 (pdf)

2020

  • Kordovan M, Rotter S
    Spike Train Cumulants for Linear-Nonlinear Poisson Cascade Models
    arXiv: 2001.05057 [q-bio.NC], 2020 (pdf)

2019 

  • Lagzi F, Atay FM, Rotter S
    Bifurcation analysis of the dynamics of interacting subnetworks of a spiking network
    Scientific Reports 9(1): 11397, 2019  (pdf)
  • Merkt B, Schüßler F, Rotter S
    Propagation of orientation selectivity in a spiking network model of layered primary visual cortex
    PLOS Computational Biology 15(7): e1007080, 2019 (pdf | synopsis)
  • Lu H, Gallinaro J, Rotter S
    Network remodeling induced by transcranial brain stimulation: A computational model of tDCS-triggered cell assembly formation
    Network Neuroscience 3(4): 924-943, 2019 (pdf | synopsis)

2018 

  • Buccino AP, Kordovan M, Bækø Ness TV, Merkt B, Häfliger PD, Fyhn M, Cauwenberghs G, Rotter S, Einevoll GT
    Combining biophysical modeling and deep learning for multi-electrode array neuron localization and classification
    Journal of Neurophysiology 120: 1212-1232, 2018 (pdf | synopsis)
  • Lennartz C, Schiefer J, Rotter S, Hennig J, LeVan P
    Sparse Estimation of Resting-State Effective Connectivity from fMRI Cross-Spectra
    Frontiers in Neuroscience 12: 287, 2018 (pdf | synopsis)
  • Gallinaro JV, Rotter S
    Associative properties of structural plasticity based on firing rate homeostasis in recurrent neuronal networks
    Scientific Reports 8: 3754, 2018 (pdf | synopsis) 
  • Schiefer J, Niederbühl A, Pernice V, Lennartz C, LeVan P, Hennig J, Rotter S
    From Correlation to Causation: Estimation of Effective Connectivity from Continuous Brain Signals based on Zero-Lag Covariance
    PLOS Computational Biology 14(3): e1006056, 2018 (pdf | synopsis)

2017 

  • Müller O, Rotter S
    Neurotechnology: Current Developments and Ethical Issues
    Frontiers in Systems Neuroscience 11: 93, 2017 (pdf | synopsis)
  • Deniz T, Rotter S
    Joint statistics of strongly correlated neurons via dimensionality reduction
    Journal of Physics A: Mathematical and Theoretical 50(25): 254002, 2017 (pdf)
  • Deniz T, Rotter S
    Solving the two-dimensional Fokker-Planck equation for strongly correlated neurons
    Physical Review E 95: 012412, 2017 (pdf | synopsis)

2016 

  • Jovanović S, Rotter S
    Interplay between graph topology and correlations of third order in spiking neuronal networks
    PLOS Computational Biology 12(6): e1004963, 2016 (pdf | synopsis)

2015 

  • Lagzi F, Rotter S
    Dynamics of competition between subnetworks of spiking neuronal networks in the balanced state
    PLOS ONE 10(9): e0138947, 2015 (pdf | synopsis)
  • Sadeh S, Clopath C, Rotter S
    Emergence of functional specificity in balanced networks with synaptic plasticity
    PLOS Computational Biology 11(6): e1004307, 2015 (pdf | synopsis)
  • Sadeh S, Clopath C, Rotter S
    Processing of feature selectivity in cortical networks with specific connectivity
    PLOS ONE 10(6): e0127547, 2015 (pdf | synopsis)
  • Jovanović S, Hertz J, Rotter S
    Cumulants of Hawkes point processes
    Physical Review E 91: 042802, 2015 (pdf | synopsis)
  • Sadeh S, Rotter S
    Orientation selectivity in inhibition-dominated networks of spiking neurons: effect of single neuron properties and network dynamics
    PLOS Computational Biology 11(1): E1004045, 2015 (pdf | synopsis)

2014 

  • Lagzi F, Rotter S
    A Markov model for the temporal dynamics of balanced random networks of finite size
    Frontiers of Computational Neuroscience 8: 142, 2014 (pdf | synopsis)
  • Sadeh S, Rotter S
    Distribution of orientation selectivity in recurrent networks of spiking neurons with different random topologies
    PLOS ONE 9(12): e114237, 2014 (pdf | synopsis) 
  • Yim MY, Kumar A, Aertsen A, Rotter S
    Impact of correlated inputs to neurons: Modeling observations from in vivo intracellular recordings
    Journal of Computational Neuroscience 37(2): 293-304, 2014 (pdf | synopsis)
  • Sadeh S, Cardanobile S, Rotter S
    Mean-field analysis of orientation selectivity in inhibition-dominated networks of spiking neurons
    SpringerPlus 3(1): 148, 2014 (pdf | synopsis)
  • Kriener B, Helias M, Rotter S, Diesmann M, Einevoll GT
    How pattern formation in ring networks of excitatory and inhibitory spiking neurons depends on the input current regime
    Frontiers in Computational Neuroscience 7: 187, 2014 (pdf)
  • Sadeh S, Rotter S
    Statistics and geometry of orientation selectivity in primary visual cortex
    Biological Cybernetics 108: 631–653, 2014, published online 2013 (pdf | synopsis)

2013 

  • Pernice V, Deger M, Cardanobile S, Rotter S
    The relevance of network micro-structure for neural dynamics
    Frontiers in Computational Neuroscience 7: 72, 2013 (pdf | synopsis)
  • Reimer ICG, Staude B, Boucsein C, Rotter S
    A new method to infer higher-order spike correlations from membrane potentials
    Journal of Computational Neuroscience 35(2): 169-186, 2013 (pdf | synopsis)
  • Yim M-Y, Aertsen A, Rotter S
    Impact of intrinsic biophysical diversity on the activity of spiking neurons
    Physical Review E 87: 032710, 2013 (pdf | synopsis)
  • Pernice V, Rotter S
    Reconstruction of connectivity in sparse neural networks from spike train covariances
    Journal of Statistical Mechanics P03008, 2013 (pdf | synopsis)

2012

  • Ambard M, Rotter S
    Support vector machine using synaptic kernels for spike pattern classification
    Frontiers in Computational Neuroscience 6: 78, 2012 (pfd | synopsis)
  • Deger M, Helias M, Rotter S, Diesmann M
    Spike-timing dependence of structural plasticity explains cooperative synapse formation in the neocortex
    PLOS Computational Biology 8(9): e1002689, 2012 (pdf | synopsis)
  • Cardanobile S, Pernice V, Deger M, Rotter S
    Inferring general relations between network characteristics from specific network ensembles
    PLOS ONE 7(6): e37911, 2012 (pdf | synopsis)
  • Reimer I, Staude B, Ehm W, Rotter S
    Modeling and analyzing higher-order correlations in non-Poissonian spike trains
    Journal of Neuroscience Methods 208: 18–33, 2012 (pdf | synopsis)
  • Pernice V, Staude B, Cardanobile S, Rotter S
    Recurrent interactions in spiking networks with arbitrary topology
    Physical Review E 85: 031916, 2012 (pdf | synopsis)

2011

  • Deger M, Helias M, Boucsein C, Rotter S
    Statistical properties of superimposed stationary spike trains
    Journal of Computational Neuroscience 32(3): 443-463, 2012; Epub ahead of print, 2011
  • Cardanobile S, Rotter S
    Emergent properties of interacting populations of spiking neurons
    Frontiers in Computational Neuroscience 5: 59, 2011 
  • Kumar A, Cardanobile S, Rotter S, Aertsen A
    The role of inhibition in generating and controlling Parkinson’s disease oscillations in the basal ganglia
    Frontiers in Systems Neuroscience 5: 86, 2011
  • Voges N, Aertsen A, Rotter S
    Structural models of cortical networks with long-range connectivity
    Mathematical Problems in Engineering 484812, 2011
  • Braun DA, Aertsen A, Paz R, Vaadia E, Rotter S, Mehring C
    Online adaptation and over-trial learning in macaque visuomotor control
    Frontiers in Computational Neuroscience 5: 27, 2011
  • Pernice V, Staude B, Cardanobile S, Rotter S
    How Structure Determines Correlations in Neuronal Networks
    PLOS Computational Biology 7(5): e1002059, 2011
  • Helias M, Deger M, Rotter S, Diesmann M
    Finite post synaptic potentials cause a fast neuronal response
    Focused Review, Frontiers in Neuroscience 5: 19, 2011

2010

  • Helias M, Deger M, Rotter S, Diesmann M
    Instantaneous non-linear processing by pulse-coupled threshold units
    PLOS Computational Biology 6(9): e10000929, 2010
  • Kumar A, Rotter S, Aertsen A
    Spiking activity propagation in neuronal networks - Reconciling different perspectives on neural coding
    Nature Reviews Neuroscience 11(9): 615-627, 2010
  • Deger M, Helias M, Cardanobile S, Atay F, Rotter S
    Nonequilibrium dynamics of stochastic point processes with refractoriness
    Physical Review E 82(2): 021129, 2010
  • Voges N, Schüz A, Aertsen A, Rotter S
    A modeler's view on the spatial structure of intrinsic horizontal connectivity in the neocortex
    Progress in Neurobiology 92(3): 277-292, 2010
  • Staude B, Grün S, Rotter S
    Higher-order correlations in non-stationary parallel spike trains: statistical modeling and inference
    Frontiers in Computational Neuroscience 4: 16, 2010
  • Jarvis S, Rotter S, Egert U
    Extending stability through hierarchical clusters in Echo State Networks
    Frontiers in Neuroinformatics 4: 11, 2010
  • Cardanobile S, Rotter S
    Multiplicatively interacting point processes and applications to neural modeling
    Journal of Computational Neuroscience 28(2): 267-284, 2010
  • Voges N, Guijarro C, Aertsen A, Rotter S
    Models of cortical networks with long-range patchy projections
    Journal of Computational Neuroscience 28(1): 137-154, 2010
  • Helias M, Deger M, Diesmann M, Rotter S
    Equilibrium and response properties of the integrate-and-fire neuron in discrete time
    Frontiers in Computational Neuroscience 3: 29, 2010

2009

  • Gürel T, Rotter S, Egert U
    Functional identification of biological neural networks using reservoir adaptation for point processes
    Journal of Computational Neuroscience 29(1-2): 279-299, 2010; Epub ahead of print, 2009
  • Staude B, Rotter S, Grün S
    CuBIC: cumulant based inference of higher-order correlations in massively parallel spike trains
    Journal of Computational Neuroscience 29(1-2): 327-350, 2010; Epub ahead of print, 2009
  • Rickert J, Riehle A, Aertsen A, Rotter S, Nawrot MP
    Dynamic encoding of movement direction in motor cortical neurons
    The Journal of Neuroscience 29(44): 13870-13882, 2009
  • Kriener B, Helias M, Aertsen A, Rotter S
    Correlations in spiking neuronal networks with distance dependent connections
    Journal of Computational Neuroscience 27(2): 177-200, 2009

2008

  • Helias M, Rotter S, Gewaltig M-O, Diesmann M
    Structural plasticity controlled by calcium based correlation detection
    Frontiers in Computational Neuroscience 2: 7, 2008
  • Atmanspacher H, Rotter S
    Interpreting neurodynamics: concepts and facts
    Cognitive Neurodynamics 2(4): 297-318, 2008
  • Kumar A, Rotter S, Aertsen A
    Conditions for propagating synchronous spiking and asynchronous firing rates in a cortical network model
    The Journal of Neuroscience 28(20): 5268-5280, 2008
  • Kriener B, Tetzlaff T, Aertsen A, Diesmann M, Rotter S
    Correlations and population dynamics in cortical networks
    Neural Computation 20: 2185-2226,  2008
  • Staude B, Rotter S, Grün S
    Can spike coordination be differentiated from rate covariation?
    Neural Computation 20: 1973-1999, 2008
  • Tetzlaff T, Rotter S, Stark E, Abeles M, Aertsen A, Diesmann M
    Dependence of neuronal correlations on filter characteristics and marginal spike-train statistics
    Neural Computation 20: 2133-2184, 2008
  • Nawrot MP, Boucsein C, Rodriguez Molina V, Riehle A, Aertsen A, Rotter S
    Measurement of variability dynamics in cortical spike trains
    Journal of Neuroscience Methods 169: 374-390, 2008
  • Kumar A, Schrader S, Aertsen A, Rotter S
    The high-conductance state of cortical networks
    Neural Computation 20(1): 1-43, 2008

2007

  • Gürel T, Egert U, Kandler S, De Raedt L, Rotter S
    Predicting spike activity in neuronal cultures
    In: Si J, Sun R (eds), Proceedings of the IEEE International Joint Conference on Neural Networks, Orlando, FL, 2007
  • Ehm W, Staude B, Rotter S
    Decomposition of neuronal assembly activity via empirical de-Poissonization
    Electronic Journal of Statistics 1: 473-495, 2007
  • Gürel T, De Raedt L, Rotter S
    Mining structure-activity relations in biological neural networks using NeuronRank
    Hammer B, Hitzler P (eds), Perspectives of Neural-Symbolic Integration,
    Springer-Series in Computational Intelligence, volume 77, chapter 3, 47-63, 2007
  • Shin S-L, Rotter S, Aertsen A, De Schutter E
    Stochastic description of complex and simple spike firing in cerebellar Purkinje cells
    European Journal of Neuroscience 25(3): 785-794, 2007
  • Nawrot MP, Boucsein C, Rodriguez Molina V, Aertsen A, Grün S, Rotter S
    Serial interval statistics of spontaneous activity in cortical neurons
    Neurocomputing 70: 1717-1722, 2007
  • Voges N, Aertsen A, Rotter S
    Statistical analysis of spatially embedded networks: From grid to random node positions
    Neurocomputing 70: 1833-1837, 2007
  • Gürel T, De Raedt L, Rotter S
    Ranking the neurons for mining structure-activity relations in biological neural networks: NeuronRank
    Neurocomputing 70: 1897-1901, 2007
  • Kremkow J, Kumar A, Rotter S, Aertsen A
    Emergence of population synchrony in a layered network model of the cat visual cortex
    Neurocomputing 70: 2069-2073, 2007

2006 and earlier

  • Rickert J, Cardoso de Oliveira S, Vaadia E, Aertsen A, Rotter S, Mehring C
    Encoding of movement direction in different frequency ranges of motor cortical local field potentials
    The Journal of Neuroscience     25(39): 8815-8824, 2005
  • Boucsein C, Nawrot MP, Rotter S, Aertsen A, Heck D
    Controlling synaptic input patterns in vitro by dynamic photo stimulation
    Journal of Neurophysiology     94(4): 2948-2958, 2005
  • Kuhn A, Aertsen A, Rotter S
    Neuronal integration of synaptic input in the fluctuation-driven regime
    The Journal of Neuroscience 24(10): 2345-2356, 2004
  • Mehring C, Rickert J, Vaadia E, Cardoso de Oliveira S, Aertsen A, Rotter S
    Inference of hand movements from local field potentials in monkey motor cortex
    Nature Neuroscience 6(12): 1253-1254, 2003
  • Gütig R, Aharonov R, Rotter S, Sompolinsky H
    Learning input correlations through nonlinear temporally asymmetric Hebbian plasticity
    The Journal of Neuroscience 23(9): 3697-3714, 2003
  • Nawrot MP, Aertsen A, Rotter S
    Elimination of response latency variability in neuronal spike trains
    Biological Cybernetics 88(5): 321-334, 2003
  • Gütig R, Aertsen A, Rotter S
    Analysis of higher-order neuronal interactions based on conditional inference
    Biological Cybernetics 88(5): 352-359, 2003
  • Mehring C, Rickert J, Cardoso de Oliveira S, Vaadia E, Aertsen A, Rotter S
    Hints for a topographic map of tuning properties in primate motor cortex
    1st International IEEE EMBS Conference on Neural Engineering 28-31, 2003
  • Kuhn A, Aertsen A, Rotter S
    Higher-order statistics of input ensembles and the response of simple model neurons
    Neural Computation 15(1): 67-101, 2003
  • Egert U, Knott T, Schwarz C, Nawrot M, Brandt A, Rotter S, Diesmann M
    MEA-Tools: an open source toolbox for the analysis of multi-electrode data with Matlab
    Journal of Neuroscience Methods 117(1): 33-42, 2002
  • Kuhn A, Rotter S, Aertsen A
    Correlated input spike trains and their effects on the response of the leaky integrate-and-fire neuron
    Neurocomputing 44-46: 121-126, 2002
  • Gütig R, Aertsen A, Rotter S
    Statistical significance of coincident spikes: Count-based versus rate-based statistics
    Neural Computation 14(1): 121-153, 2002
  • Diesmann M, Gewaltig M-O, Rotter S, Aertsen A
    State space analysis of synchronous spiking in cortical networks
    Neurocomputing 38-40: 565-571, 2001
  • Nawrot M, Aertsen A, Rotter S
    Single-trial estimation of neuronal firing rates - From single neuron spike trains to population activity
    Journal of Neuroscience Methods 94(1): 81-92, 1999
  • Rotter S, Diesmann M
    Exact digital simulation of time-invariant linear systems with applications to neuronal modeling
    Biological Cybernetics 81(5/6): 381-402, 1999
  • Reimann S, Fuster JM, Gierer A, Mayer-Kress G, Neumann T, Roelfsema P, Rotter S, Schöner G, Stephan A, Vaadia E, Walter H
    Emergent properties of natural and artificial systems
    Zeitschrift für Naturforschung 53c(7/8): 770-774, 1998
  • Rotter S, Aertsen A
    Accurate spike synchronization in cortex
    Zeitschrift für Naturforschung 53c(7/8): 686-690, 1998
  • Baier H, Rotter S, Korsching S
    Connectional topography in the zebrafish olfactory system: Random positions but regular spacing of sensory neurons projecting to an individual glomerulus
    Proceedings of the National Academy of Sciences (USA) 91: 11646-11650, 1994
  • Aertsen A, Vaadia E, Abeles M, Ahissar E, Bergman H, Karmon B, Lavner Y, Margalit E, Nelken I, Rotter S
    Dynamics of coherence in cortical neural activity: Experimental observations and functional interpretations
    International Journal of Neural Systems (Suppl.) 105-114, 1992
  • Aertsen A, Vaadia E, Abeles M, Ahissar E, Bergman H, Karmon B, Lavner Y, Margalit E, Nelken I, Rotter S
    Neural interactions in the frontal cortex of a behaving monkey: Signs of dependence on stimulus context and behavioral state
    Journal für Hirnforschung 32: 735-743, 1991
     

Books

  • Grün S, Rotter S (eds)
    Analysis of Parallel Spike Trains
    Springer Series in Computational Neuroscience, Volume 7, 2010
    ISBN 978-1-4419-5674-3
  • Rotter S
    Wechselwirkende stochastische Punktprozesse als Modell für neuronale Aktivität in Neocortex der Säugetiere
    Reihe Physik, Bd. 21
    Verlag Harri Deutsch, Thun, Frankfurt am Main, 1994
    ISBN 3-8171-1375-7

 

Book Chapters, Editorials, etc.

  • Rotter S
    Neuronal Spike Trains and Stochastic Point Processes. Why George Gerstein’s Papers are Still Worth Reading. 
    Chapter 2 In: Aertsen A, Grün S, Maldonado PE, Palm G (eds): Introducing Computation to Neuroscience. Selected Papers of George Gerstein, Springer Series in Computational Neuroscience, 2023 (pdf | synopsis)
  • Wachtler T, Bauer P, Denker M, Grün S, Hanke M, Klein J, Oeltze-Jafra S, Ritter P, Rotter S, Scherberger H, Stein A, Witte OW
    NFDI-Neuro: building a community for neuroscience research data management in Germany
    Neuroforum, 2020 (pdf)
  • Rotter S Computational Tools - Innovative Algorithms for Neuronal Data Analysis Thinking in the Future. Bernstein Feature, 31, 2019 (pdf)
  • Rotter S Understanding the Plasticity of the Brain through Models and Simulations Thinking in the Future. Bernstein Feature, 33, 2019 (pdf)
  • Rosskothen-Kuhl N, Hofmann UG, Rotter S, Kral A, Hubka P, Schnupp JW
    Next generation cochlear implants require microsecond binaural synchronization.
    41st International Engineering in Medicine and Biology Conference (EMBC), 2019 
  • Rosskothen-Kuhl N, Rotter S, Hofmann U, Hubka P
    Identifying functional biomarkers for responsive control of cochlear implants
    52nd Annual Conference of the German Society for Biomedical Engineering (BMT), 2018 
  • Schiefer J, Rotter S
    Estimation of cerebral network structure
    Proceedings of the 3rd bwHPC-Symposium, Heidelberg, 2016 
  • Niederbühl A, Pernice V, Rotter S
    Inferring causation from correlation in sparse networks
    ECML 2014, Neural Connectomics Workshop – From Imaging to Connectivity. Nancy, France, 2014 (pdf)
  • Jarvis S, Rotter S, Egert U
    Increased robustness and intermittent dynamics in structured Reservoir Networks with feedback
    European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning,
    ESANN 2011 proceedings    , 111-116, 2011
  • Atmanspacher H, Rotter S
    On determinacy or its absence in the brain
    In: Swinburne R (ed)
    Free Will and Modern Science, 84-101
    Oxford University Press, 2011
  • Staude B, Grün S, Rotter S
    Higher-order correlations and cumulants
    In: Grün S, Rotter S (eds)
    Analysis of Parallel Spike Trains
    Springer Series in Computational Neuroscience, Volume 7, 2010
  • Cardanobile S, Rotter S
    Simulation of stochastic point processes with defined properties
    In: Grün S, Rotter S (eds)
    Analysis of Parallel Spike Trains
    Springer Series in Computational Neuroscience, Volume 7, 2010
  • Fukai T, Ikegaya Y, Rotter S
    Analysis and modeling of massively parallel neural signals
    Neural Networks, Special Issue 23(6): 667-668, 2010
  • Aertsen A, Diesmann M, Gewaltig M-O, Grün S, Rotter S
    Neural Dynamics in Cortical Networks – Precision of Joint-Spiking Events
    In: Complexity in Biological Information Processing, 193-207
    Wiley, Chichester, 2001
  • Rotter S, Aertsen A
    Cortical Dynamics – Experiments and Models
    Lehnertz K, Arnhold J, Grassberger P, Elger CE (eds) Chaos in Brain? 3-12
    World Scientific, Singapore, 2000
  • Grün S, Rotter S
    Concepts of Neuronal Cooperativity in the Cortex
    In: Elsner N, Eysel U (eds) From Molecular Neurobiology to Clinical Neuroscience, 358-363
    Thieme, Stuttgart, 1999
  • Aertsen A, Diesman M, Gewaltig M-O, Heck D, Rotter S
    Dynamische Organisation von Hirnaktivität – Mechanismen und Funktion
    In: Experimentelle und theoretische Hirnforschung: II. Sinneswahrnehmung, sensomotorische Koordination, neuronale Informationsverarbeitung
    Freiburger Universitätsblätter 135: 93-115
    Rombach, Freiburg, 1997
  • Rotter S
    Biophysical Aspects of Cortical Networks
    In: Torre V, Conti F (eds) Proceedings of the NATO ASI: Neurobiology – Ionic Channels, Neurons, and the Brain, 355-369
    Plenum, New York, 1996
  • Rotter S, Heck D, Aertsen A
    Spatio-temporal patterns of activity in cortical networks
    In: Bower JM (ed) Computational Neuroscience – Trends in Research 1995, 261-266
    Academic Press, San Diego, 1996
  • Rotter S, Aertsen A
    A point process approach to cortical networks
    In: Kappen B, Gielen S (eds) Neural Networks: Artificial Intelligence and Industrial Applications, 59-62
    Springer, Berlin, Heidelberg, New York, 1995
  • Rotter S, Aertsen A, Vaadia E
    Neuronal interaction in the cortex – quantitative characterization by cross-interval statistics
    In: Aertsen A (ed) Brain Theory: Spatio-Temporal Aspects of Brain Function, 231-239
    Elsevier, Amsterdam, 1993
  • Heck D, Rotter S, Aertsen A
    Spike generation in cortical neurons: Probabilistic threshold function shows intrinsic and long-lasting dynamics
    In: Aertsen A (ed) Brain Theory: Spatio-Temporal Aspects of Brain Function, 241-249
    Elsevier, Amsterdam, 1993
  • Hellwig B, Rotter S
    On the relation between cyto- and myeloarchitectonics in the human cerebral cortex
    In: Aertsen A (ed) Brain Theory: Spatio-Temporal Aspects of Brain Function, 281-289
    Elsevier, Amsterdam, 1993

Patents

  • Aertsen A, Boucsein C, Heck D, Nawrot M, Rotter S
    Dynamic Simultaneous Multisite Photostimulation (DSMP)
    Patent No. ZEE20050629 with German Patent and Trade Mark Office (GPTO)
    Patent No. 05.019878.7 with European Patent Office (EPO)