2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

  • Brankack, J and Kukushka, V I and Vyssotski, A L and Draguhn, A EEG gamma frequency and sleep–wake scoring in mice: Comparing two types of supervised classifiers, Brain Research, 1322: 59-71, 2010 pdf
  • D'Souza, P and Liu, S C and Hahnloser, R H R Perceptron learning rule derived from spike-frequency adaptation and spike-time-dependent plasticity, Proceedings of the National Academy of Sciences of the United States of America, 107:(10) 4722-4727, 2010 pdf
  • Fiete, I R and Senn, W and Wang, C Z H and Hahnloser, R H R Spike time-dependent plasticity and heterosynaptic competition organize networks to produce long scale-free sequences of neural activity, Neuron, 65:(4) 563-576, 2010 pdf
  • Hahnloser, R H R and Kotowicz, A Auditory representations and memory in birdsong learning, Current Opinion in Neurobiology, 20:(3) 332-339, 2010 pdf
  • Hanuschkin, A. and Kunkel, S. and Helias, M. and Morrison, A. and Diesmann, M. A general and effcient method for incorporating precise spike times in globally time-driven simulations, Frontiers in Neuroinformatics, 4:(13), 2010
  • Jacobo D. Sitt, Ezequiel M. Arneodo, Franz Goller, and Gabriel B. Mindlin Physiologically driven avian vocal synthesizer, Physical Review E, 81:(3) 031927, 2010
  • Kotowicz, A and Rutishauser, U and Koch, C Time course of target recognition in visual search, Frontiers in Human Neuroscience, 4: 31, 2010 pdf
  • Ondracek, J M and Willuhn, I and Steiner, H and West, A R Interactions between procedural learning and cocaine exposure alter spontaneous and cortically evoked spike activity in the dorsal striatum, Frontiers in Neuroscience, 4: online, 2010
  • Sepp Kollmorgen, Nora Nortmann, Sylvia Schröder, Peter König Influence of low-level stimulus features, task dependent factors, and spatial biases on overt visual attention, PLoS computational biology, 6:(5) e1000791, 2010

2009

2008

2007

  • A Hanuschkin, D Wortmann, and S Bluegel Image potential and field states at Ag(100) and Fe(110) surfaces, Physical Review B, 76:(16) 165417, 2007
  • Hahnloser, R.H. Cross-intensity functions and the estimate of spike-time jitter, Biological Cybernetics, 96:(5) 497-506, 2007 pdf
  • Hahnloser, R.H.R. and Fee, M.S. Sleep-related spike bursts in HVC are driven by the nucleus interface of the nidopallium, Journal of Neurophysiology, 97:(1) 423-435, 2007 pdf
  • Hetzler, B.E. and Ondracek, J.M. Baclofen alters flash-evoked potentials in Long-Evans rats, Pharmacology Biochemistry and Behavior , 84:(4) 727-740, 2007 pdf
  • Weber, A.P. and Hahnloser, R.H. Spike correlations in a songbird agree with a simple Markov population model, PLoS Computational Biology, 3:(12) e249 doi:10.1371/journal.pcbi.0030249, 2007 pdf

2006

  • Hahnloser, R.H.R. and Kozhevnikov, A. and Fee, M.S. Sleep-related neural activity in a premotor and a basal-ganglia pathway of the songbird.of birdsong., Journal of Neurophysiology, 96:(2) 794-812, 2006 pdf
  • Wang, Claude Z.H. and Chang, M.H. and Yang, J.W. and Sun, J.J. and Lee, H.C. and Shyu, B.C. Layer IV of the Primary Somatosensory Cortex has the Highest Complexity under Anesthesia and Cortical Complexity is Modulated by Specific Thalamic Inputs, Brain Research, 1082:(1) 102-114, 2006 pdf

2005

  • Danóczy, M and Hahnloser, R.H.R. Efficient estimation of hidden state dynamics from spike trains , NIPS Proceedings, 17:, 2005 pdf
  • Kissinger, Thomas and Kotowicz, Andreas and Kurz, Oliver and Ginelli , Francesco and Hinrichsen, Haye Nonequilibrium wetting of finite samples, Journal of Statistical Mechanics: Theory and Experiment, 2005 pdf

2004

  • Fee, Michale and Kozhevnikov, Alex and Hahnloser, Richard Neural mechanisms of vocal sequence generation in the songbird., Behavioral Neurobiology of Birdsong 153-170, 2004
  • Fiete, I and Hahnloser, R and Fee, M and Seung, S Temporal sparseness of the premotor drive is important for rapid learning in a neural network model of birdsong., Journal of Neurophysiology, 92:(4) 2274-82, 2004 pdf

2003

  • Stoop, R. and Buchli, J. and Keller, G. and Steeb, W.-H. Stochastic Resonance in Pattern Recognition by a Holographic Neuron , Physical Review E, 67: 061918-1-061918-6, 2003 pdf

2002

  • Hahnloser, RH and Douglas, RJ and Hepp, K Attentional recruitment of inter-areal recurrent networks for selective gain control., Neural Computation, 14:(7) 1669-89, 2002 pdf
  • S. Reimann, A. Tupak Can constrained percolation be approximated by Bernoulli percolation?, Journal of Physics A: Mathematical and General, 35:(48) 10219, 2002

2001

  • Rasche, C. and Hahnloser, R. Silicon Synaptic Depression, Biological Cybernetics, 84:(1) 57-62, 2001 pdf
  • S. Reimann, J. Bendisch On global site-percolation on the correlated honeycomb lattice, Physica A: Statistical Mechanics and its Applications, 296:(3-4) 391-404, 2001

2000

  • Hahnloser, Richard and Sarpeshkar, R. and Mahowald, Misha and Douglas, Rodney J. and Seung, S. Digital selection and analog amplification co-exist in an electronic circuit inspired by neocortex, Nature, 405: 947-951, 2000 pdf

1999

  • Hahnloser, R and Douglas, R and Mahowald, M and Hepp, K Feedback interactions between neuronal pointers and maps for attentional processing, Nature Neuroscience, 2: 746-752, 1999 pdf
  • Mudra, R. and Hahnloser, R. and Douglas, R.J. Neuromorphic Active Vision Used in Simple Navigation Behavior for a Robot, Proceedings of the 7th International Conference on Microelectronics for Neural Networks, 1: 32-36, 1999 pdf

1998

  • Hahnloser, R.H.R. Generating Network Trajectories Using Gradient Descent in State Space, IJCNN - International Joint Conference on Neural Networks 2373-2377, 1998
  • Hahnloser, Richard H.R. Learning Algorithms Based on Linearization, Network, Computation in Neural Systems, 9(3): 363-380, 1998
  • Hahnloser, Richard H.R. About the Piecewise Analysis of Networks of Linear Threshold Neurons, Neural Networks, 11: 691-697, 1998 pdf
  • S. Reimann On the design of artificial auto-associative neuronal networks, Neural Networks, 11:(4) 611-621, 1998
  • S. Reimann Oscillation and pattern formation in a system of self-regulating cells, Physica D: Nonlinear Phenomena, 114:(3-4), 1998

1997

  • S. Reimann Symmetry and network structure, Neural Processing Letters, 6:(1) 1-10, 1997