Video Presentations:

National Academy of Science - Kalvi Frontiers of science meeting 2008

‘Neuronal Self Organization in Theory and Experiment: Plasticity in the Liquid State Machine’

Publications:

2008

(18) R. Vicente, L.L. Golo, C.R. Mirasso, I. Fischer, G. Pipa

‘Dynamical relaying can yield zero time lag neuronal synchrony despite long conduction delays’

PNAS, November 4, 2008, vol. 105, no. 44, 17157–17162 (download)

(17) G. Pipa, R. Vicente, A. Tikhonov

‘Auto-structure of presynaptic activity defines postsynaptic firing statistics and can modulate STDP-based structure formation and learning’ ;

Lecture Notes in Computer Science 5164, 413-422, Springer 2008, Artificial Neural Networks (download)

(16) E. Ullner, R. Vicente, G. Pipa, J. Garcıa-Ojalvo

‘Contour integration and synchronization in neuronal networks of the visual cortex’

Lecture Notes in Computer Science 5164, 703-712, Springer 2008, Artificial Neural Networks (download)

(15) A. Lazar, G. Pipa, J. Triesch

‘Predictive Coding in Cortical Microcircuits’

Lecture Notes in Computer Science 5164, 386-395, Springer 2008, Artificial Neural Networks

(14) Wu, W., Wheeler, D. W. , Staedler, E. S., Munk, M. H. J., Pipa, G.

’Behavioral performance modulates spike-field-coherence in monkey prefrontal cortex

Neuro Report, Vol 19 No, 2008, 235-238, (download)

2007

(13) G.Pipa, D. W. Wheeler, W. Singer, D. Nikolic

’NeuroXidence: A Non-parametric Test on Excess or Deficiency of Joint-Spike Events’

J.Comput.Neurosci. PM:18219568, DOI 10.1007/s10827-007-0065-3. (download)

download source code and example data

(12) R. Vicente, G. Pipa, I. Fischer, C. Mirasso

‘Zero-lag Long Range Synchronization of Neurons Is Enhanced by Dynamical Relaying’

ICANN2007 (download)

(11) Huang, D. and G. Pipa

‘Achieving synchronization of networks by an auxiliary hub’

Europhys. Lett. 77 5 (2007) 50010

doi: 10.1209/0295-5075/77/50010 (download)

(10) Lazar, A., G. Pipa and J. Triesch (first and second author contributed equally)

‘Fading Memory and Time Series Prediction in Recurrent Networks with Different Forms of Plasticity’

Neural Networks, Volume 20, Issue 3, April 2007, Pages 312-322 (download)

2006

(9) G. Pipa, A. Riehle, S. Grün

‘Validation of task-related excess of spike coincidences based on NeuroXidence’

Neurocomputing (2006), doi:10.1016/j.neucom.2006.10.142 (download)

(8) G. Pipa

Ph.D. thesis

‘Neuronal Code: Development of tools and hypotheses for understanding the role of synchronisation of neuronal activity’ (download Ph.D. thesis)

(7) Lazar A., Muresan R.C., Stadler E., Munk M., Pipa G. (2006)

‘Importance of electrophysiological signal features assessed by classification trees’

Neurocomputing (2006), doi:10.1016/j.neucom.2006.10.136 (download)

(6) Lazar A., Pipa G., Triesch J.

‘The combination of STDP and intrinsic plasticity yields complex dynamics in recurrent spiking networks’

Proceedings of the European Symposium on Artificial Neural Networks (ESANN 2006), Brugges, Belgium (download)

2005

(5) R. C. Muresan, G. Pipa, D. W. Wheeler

’Single-Unit Recordings Revisited: Activity in Recurrent Microcircuits’

Lecture Notes in Computer Science, Vol. 3696, Eds. W. Duch, J. Kacprzyk, E. Oja, et al., pp.153-160

ISSN:E0302-9743, Muresan ICANN 2005 (download)

(4) Muresan, R.C., G. Pipa, R.V. Florian and D.W. Wheeler (2005)

‘Coherence, Memory and Conditioning. A Modern Viewpoint’

Neural Information Processing - Letters and Reviews, Vol. 7, No. 2, pp. 19-28 (download)

2003

(3) G.Pipa and S.Grün

‘Non-Parametric significance estimation of joint-spike events by shuffling and resampling’

Neural Computing, Neurocomputing 52–54 (2003) 31 – 37, (download)

(2) G.Pipa, M. Diesmann, S.Grün

’Significance of Joint-Spike Events Based on Trial-Shuffling by Efficient, Combinatorial Methods’

Complexity 2003, Pages 79 – 86, (download)

(1) G.Pipa

Diploma thesis

‘Entwicklung und Untersuchung einer nicht-parametrischen Methode zur Schätzung der Signifikanz zeitlich koordinierter Spike-Aktivät’, (download)