Gordon Pipa, Prof. Dr. rer. nat. - Publications

Neuroinformatics Institute for Cognitive Science, Osnabrück 
visual system and computational neuroscience

67 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2020 Clay V, König P, Kühnberger KU, Pipa G. Learning sparse and meaningful representations through embodiment. Neural Networks : the Official Journal of the International Neural Network Society. 134: 23-41. PMID 33279863 DOI: 10.1016/j.neunet.2020.11.004  0.389
2019 Kallioinen N, Pershina M, Zeiser J, Nosrat Nezami F, Pipa G, Stephan A, König P. Moral Judgements on the Actions of Self-Driving Cars and Human Drivers in Dilemma Situations From Different Perspectives. Frontiers in Psychology. 10: 2415. PMID 31749736 DOI: 10.3389/Fpsyg.2019.02415  0.426
2019 Sütfeld LR, Ehinger BV, König P, Pipa G. How does the method change what we measure? Comparing virtual reality and text-based surveys for the assessment of moral decisions in traffic dilemmas. Plos One. 14: e0223108. PMID 31596864 DOI: 10.1371/Journal.Pone.0223108  0.477
2018 Sütfeld LR, Gast R, König P, Pipa G. Response: Commentary: Using Virtual Reality to Assess Ethical Decisions in Road Traffic Scenarios: Applicability of Value-of-Life-Based Models and Influences of Time Pressure. Frontiers in Behavioral Neuroscience. 12: 128. PMID 29997485 DOI: 10.3389/Fnbeh.2018.00128  0.44
2018 Bergmann LT, Schlicht L, Meixner C, König P, Pipa G, Boshammer S, Stephan A. Autonomous Vehicles Require Socio-Political Acceptance-An Empirical and Philosophical Perspective on the Problem of Moral Decision Making. Frontiers in Behavioral Neuroscience. 12: 31. PMID 29541023 DOI: 10.3389/Fnbeh.2018.00031  0.449
2018 Faulhaber AK, Dittmer A, Blind F, Wächter MA, Timm S, Sütfeld LR, Stephan A, Pipa G, König P. Human Decisions in Moral Dilemmas are Largely Described by Utilitarianism: Virtual Car Driving Study Provides Guidelines for Autonomous Driving Vehicles. Science and Engineering Ethics. PMID 29357047 DOI: 10.1007/S11948-018-0020-X  0.45
2018 Leugering J, Pipa G. A Unifying Framework of Synaptic and Intrinsic Plasticity in Neural Populations. Neural Computation. 30: 945-986. PMID 29342400 DOI: 10.1162/Neco_A_01057  0.427
2017 Sütfeld LR, Gast R, König P, Pipa G. Using Virtual Reality to Assess Ethical Decisions in Road Traffic Scenarios: Applicability of Value-of-Life-Based Models and Influences of Time Pressure. Frontiers in Behavioral Neuroscience. 11: 122. PMID 28725188 DOI: 10.3389/Fnbeh.2017.00122  0.469
2017 Korndörferr C, Ullner E, García J, Pipa G. Cortical Spike Synchrony as a Measure of Input Familiarity. Neural Computation. 1-20. PMID 28599117 DOI: 10.1162/Neco_A_00987  0.459
2017 Nieters P, Leugering J, Pipa G. Neuromorphic computation in multi-delay coupled models Ibm Journal of Research and Development. 61: 8:7-8:9. DOI: 10.1147/Jrd.2017.2664698  0.389
2016 Shahi M, van Vreeswijk C, Pipa G. Serial Spike Time Correlations Affect Probability Distribution of Joint Spike Events. Frontiers in Computational Neuroscience. 10: 139. PMID 28066225 DOI: 10.3389/Fncom.2016.00139  0.396
2016 Kovac AD, Koall M, Pipa G, Toutounji H. Persistent Memory in Single Node Delay-Coupled Reservoir Computing. Plos One. 11: e0165170. PMID 27783690 DOI: 10.1371/Journal.Pone.0165170  0.765
2015 Schumacher J, Wunderle T, Fries P, Jäkel F, Pipa G. A Statistical Framework to Infer Delay and Direction of Information Flow from Measurements of Complex Systems. Neural Computation. 27: 1555-608. PMID 26079751 DOI: 10.1162/Neco_A_00756  0.565
2015 Toutounji H, Schumacher J, Pipa G. Homeostatic plasticity for single node delay-coupled reservoir computing. Neural Computation. 27: 1159-85. PMID 25826022 DOI: 10.1162/Neco_A_00737  0.766
2015 Aru J, Aru J, Priesemann V, Wibral M, Lana L, Pipa G, Singer W, Vicente R. Untangling cross-frequency coupling in neuroscience. Current Opinion in Neurobiology. 31: 51-61. PMID 25212583 DOI: 10.1016/J.Conb.2014.08.002  0.665
2015 Gómez-Herrero G, Wu W, Rutanen K, Soriano MC, Pipa G, Vicente R. Assessing coupling dynamics from an ensemble of time series Entropy. 17: 1958-1970. DOI: 10.3390/E17041958  0.415
2015 Aswolinskiy W, Pipa G. RM-SORN: A reward-modulated self-organizing recurrent neural network Frontiers in Computational Neuroscience. 9. DOI: 10.3389/Fncom.2015.00036  0.366
2015 Schumacher J, Wunderle T, Fries P, Jakel F, Pipa G. A statistical framework to infer delay and direction of information flow frommeasurements of complex systems Neural Computation. 27: 1555-1608. DOI: 10.1162/NECO_a_00756  0.421
2014 Schmitz SK, Hasselbach PP, Ebisch B, Klein A, Pipa G, Galuske RA. Application of Parallel Factor Analysis (PARAFAC) to electrophysiological data. Frontiers in Neuroinformatics. 8: 84. PMID 25688205 DOI: 10.3389/Fninf.2014.00084  0.781
2014 Castellano M, Plöchl M, Vicente R, Pipa G. Neuronal oscillations form parietal/frontal networks during contour integration. Frontiers in Integrative Neuroscience. 8: 64. PMID 25165437 DOI: 10.3389/Fnint.2014.00064  0.574
2014 Toutounji H, Pipa G. Spatiotemporal computations of an excitable and plastic brain: neuronal plasticity leads to noise-robust and noise-constructive computations. Plos Computational Biology. 10: e1003512. PMID 24651447 DOI: 10.1371/Journal.Pcbi.1003512  0.78
2014 Ehinger BV, Fischer P, Gert AL, Kaufhold L, Weber F, Pipa G, König P. Kinesthetic and vestibular information modulate alpha activity during spatial navigation: a mobile EEG study. Frontiers in Human Neuroscience. 8: 71. PMID 24616681 DOI: 10.3389/Fnhum.2014.00071  0.517
2013 Haslinger R, Ba D, Galuske R, Williams Z, Pipa G. Missing mass approximations for the partition function of stimulus driven Ising models. Frontiers in Computational Neuroscience. 7: 96. PMID 23898262 DOI: 10.3389/Fncom.2013.00096  0.78
2013 Haslinger R, Pipa G, Lewis LD, Nikolić D, Williams Z, Brown E. Encoding through patterns: regression tree-based neuronal population models. Neural Computation. 25: 1953-93. PMID 23607564 DOI: 10.1162/Neco_A_00464  0.556
2013 Pipa G, Grün S, van Vreeswijk C. Impact of spike train autostructure on probability distribution of joint spike events. Neural Computation. 25: 1123-63. PMID 23470124 DOI: 10.1162/Neco_A_00432  0.628
2013 Schumacher J, Toutounji H, Pipa G. An analytical approach to single node delay-coupled reservoir computing Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8131: 26-33. DOI: 10.1007/978-3-642-40728-4_4  0.737
2013 Castellano M, Pipa G. Memory trace in spiking neural networks Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8131: 264-271. DOI: 10.1007/978-3-642-40728-4_33  0.487
2012 Haslinger R, Pipa G, Lima B, Singer W, Brown EN, Neuenschwander S. Context matters: the illusive simplicity of macaque V1 receptive fields. Plos One. 7: e39699. PMID 22802940 DOI: 10.1371/Journal.Pone.0039699  0.735
2012 Pipa G, Chen Z, Neuenschwander S, Lima B, Brown EN. Mapping of visual receptive fields by tomographic reconstruction. Neural Computation. 24: 2543-78. PMID 22734491 DOI: 10.1162/Neco_A_00334  0.69
2012 Schumacher J, Haslinger R, Pipa G. Statistical modeling approach for detecting generalized synchronization Physical Review E - Statistical, Nonlinear, and Soft Matter Physics. 85. DOI: 10.1103/Physreve.85.056215  0.368
2011 Scheller B, Castellano M, Vicente R, Pipa G. Spike train auto-structure impacts post-synaptic firing and timing-based plasticity. Frontiers in Computational Neuroscience. 5: 60. PMID 22203800 DOI: 10.3389/Fncom.2011.00060  0.546
2011 Wu W, Wheeler DW, Pipa G. Bivariate and Multivariate NeuroXidence: A Robust and Reliable Method to Detect Modulations of Spike-Spike Synchronization Across Experimental Conditions. Frontiers in Neuroinformatics. 5: 14. PMID 21897816 DOI: 10.3389/Fninf.2011.00014  0.674
2011 Pipa G, Munk MH. Higher Order Spike Synchrony in Prefrontal Cortex during Visual Memory. Frontiers in Computational Neuroscience. 5: 23. PMID 21713065 DOI: 10.3389/Fncom.2011.00023  0.736
2011 Pérez T, Garcia GC, Eguíluz VM, Vicente R, Pipa G, Mirasso C. Effect of the topology and delayed interactions in neuronal networks synchronization. Plos One. 6: e19900. PMID 21637767 DOI: 10.1371/Journal.Pone.0019900  0.442
2011 Gerhard F, Haslinger R, Pipa G. Applying the multivariate time-rescaling theorem to neural population models. Neural Computation. 23: 1452-83. PMID 21395436 DOI: 10.1162/Neco_A_00126  0.693
2011 Gerhard F, Pipa G, Lima B, Neuenschwander S, Gerstner W. Extraction of Network Topology From Multi-Electrode Recordings: Is there a Small-World Effect? Frontiers in Computational Neuroscience. 5: 4. PMID 21344015 DOI: 10.3389/Fncom.2011.00004  0.76
2011 Uhlhaas PJ, Pipa G, Neuenschwander S, Wibral M, Singer W. A new look at gamma? High- (>60 Hz) γ-band activity in cortical networks: function, mechanisms and impairment. Progress in Biophysics and Molecular Biology. 105: 14-28. PMID 21034768 DOI: 10.1016/J.Pbiomolbio.2010.10.004  0.725
2011 Vicente R, Wibral M, Lindner M, Pipa G. Transfer entropy--a model-free measure of effective connectivity for the neurosciences. Journal of Computational Neuroscience. 30: 45-67. PMID 20706781 DOI: 10.1007/S10827-010-0262-3  0.617
2011 Lazar A, Pipa G, Triesch J. Emerging Bayesian priors in a self-organizing recurrent network Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6792: 127-134. DOI: 10.1007/978-3-642-21738-8_17  0.494
2010 Haslinger R, Pipa G, Brown E. Discrete time rescaling theorem: determining goodness of fit for discrete time statistical models of neural spiking. Neural Computation. 22: 2477-506. PMID 20608868 DOI: 10.1162/Neco_A_00015  0.545
2010 Gerhard F, Haslinger R, Pipa G. Goodness-of-fit tests for neural population models: the multivariate time-rescaling theorem Bmc Neuroscience. 11. DOI: 10.1186/1471-2202-11-S1-P46  0.699
2009 Lazar A, Pipa G, Triesch J. SORN: a self-organizing recurrent neural network. Frontiers in Computational Neuroscience. 3: 23. PMID 19893759 DOI: 10.3389/Neuro.10.023.2009  0.615
2009 Pipa G, Städtler ES, Rodriguez EF, Waltz JA, Muckli LF, Singer W, Goebel R, Munk MH. Performance- and stimulus-dependent oscillations in monkey prefrontal cortex during short-term memory. Frontiers in Integrative Neuroscience. 3: 25. PMID 19862343 DOI: 10.3389/Neuro.07.025.2009  0.767
2009 Jurjut OF, Nikolić D, Pipa G, Singer W, Metzler D, MureÅŸan RC. A color-based visualization technique for multielectrode spike trains. Journal of Neurophysiology. 102: 3766-78. PMID 19846620 DOI: 10.1152/Jn.00758.2009  0.541
2009 Uhlhaas PJ, Pipa G, Lima B, Melloni L, Neuenschwander S, Nikoli? D, Singer W. Neural synchrony in cortical networks: history, concept and current status. Frontiers in Integrative Neuroscience. 3: 17. PMID 19668703 DOI: 10.3389/Neuro.07.017.2009  0.667
2009 Scheller BCA, Daunderer M, Pipa G. General anesthesia increases temporal precision and decreases power of the brainstem auditory-evoked response-related segments of the electroencephalogram Anesthesiology. 111: 340-355. PMID 19602953 DOI: 10.1097/Aln.0B013E3181Acf7C0  0.323
2009 Moca VV, Scheller B, Mureşan RC, Daunderer M, Pipa G. EEG under anesthesia-Feature extraction with TESPAR Computer Methods and Programs in Biomedicine. 95: 191-202. PMID 19371961 DOI: 10.1016/J.Cmpb.2009.03.001  0.313
2009 Haslinger R, Lima B, Pipa G, Brown EN, Neuenschwander S. The effect of global context on the encoding of natural scenes Bmc Neuroscience. 10. DOI: 10.1186/1471-2202-10-S1-P306  0.688
2009 Pipa G, Neuenschwander S, Lima B, Chen Z, Brown EN. A comparison of spike time prediction and receptive field mapping with point process generalized linear models, Wiener-Voltera kernels, and spike-triggered averaging methods Bmc Neuroscience. 10. DOI: 10.1186/1471-2202-10-S1-P270  0.704
2009 Wu W, Pipa G. Detection of task-related synchronous firing patterns Bmc Neuroscience. 10. DOI: 10.1186/1471-2202-10-S1-P262  0.494
2009 Pipa G, Vicente R, Gollo L, Mirasso C, Fischer I. A mechanism for achieving zero-lag long-range synchronization of neural activity Bmc Neuroscience. 10: P240. DOI: 10.1186/1471-2202-10-S1-P240  0.384
2009 Pipa G, van Vreeswijk C, Grun S. Auto-structure of spike trains matters for testing on synchronous activity Bmc Neuroscience. 10. DOI: 10.1186/1471-2202-10-S1-P239  0.411
2009 Wibral M, Vicente R, Triesch J, Pipa G. Using transfer entropy to measure the patterns of information flow though cortex: application to MEG recordings from a visual Simon task Bmc Neuroscience. 10: P232. DOI: 10.1186/1471-2202-10-S1-P232  0.721
2009 Wibral M, Vicente R, Pipa G. Imaging the Effective Connectivity behind Frontal Control Processes in a Simon Task using Transfer Entropy Neuroimage. 47: S169. DOI: 10.1016/S1053-8119(09)71820-8  0.552
2008 Vicente R, Gollo LL, Mirasso CR, Fischer I, Pipa G. Dynamical relaying can yield zero time lag neuronal synchrony despite long conduction delays. Proceedings of the National Academy of Sciences of the United States of America. 105: 17157-62. PMID 18957544 DOI: 10.1073/Pnas.0809353105  0.388
2008 Pipa G, Wheeler DW, Singer W, Nikolić D. NeuroXidence: reliable and efficient analysis of an excess or deficiency of joint-spike events. Journal of Computational Neuroscience. 25: 64-88. PMID 18219568 DOI: 10.1007/S10827-007-0065-3  0.7
2008 Wu W, Wheeler DW, Staedtler ES, Munk MH, Pipa G. Behavioral performance modulates spike field coherence in monkey prefrontal cortex. Neuroreport. 19: 235-8. PMID 18185115 DOI: 10.1097/Wnr.0B013E3282F49B29  0.782
2008 Lazar A, Pipa G, Triesch J. Predictive coding in cortical microcircuits Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5164: 386-395. DOI: 10.1007/978-3-540-87559-8_40  0.487
2007 Lazar A, Pipa G, Triesch J. Fading memory and time series prediction in recurrent networks with different forms of plasticity. Neural Networks : the Official Journal of the International Neural Network Society. 20: 312-22. PMID 17556114 DOI: 10.1016/J.Neunet.2007.04.020  0.651
2007 Huang D, Pipa G. Achieving synchronization of networks by an auxiliary hub Epl. 77. DOI: 10.1209/0295-5075/77/50010  0.35
2007 Wu W, Pipa G. How specific is synchronous neuronal firing? Bmc Neuroscience. 8. DOI: 10.1186/1471-2202-8-S2-P50  0.455
2007 Vicente R, Pipa G, Fischer I, Mirasso CR. Zero-lag long-range synchronization of Hodgkin-Huxley neurons is enhanced by dynamical relaying Bmc Neuroscience. 8. DOI: 10.1186/1471-2202-8-S2-P42  0.367
2007 Pipa G, Riehle A, Grün S. Validation of task-related excess of spike coincidences based on NeuroXidence Neurocomputing. 70: 2064-2068. DOI: 10.1016/J.Neucom.2006.10.142  0.634
2007 Lazǎr A, Mureşan R, Städtler E, Munk MHJ, Pipa G. Importance of electrophysiological signal features assessed by classification trees Neurocomputing. 70: 2017-2021. DOI: 10.1016/J.Neucom.2006.10.136  0.388
2005 Mureşan RC, Pipa G, Wheeler DW. Single-unit recordings revisited: Activity in recurrent microcircuits Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3696: 153-159.  0.535
2003 Pipa G, Grün S. Non-parametric significance estimation of joint-spike events by shuffling and resampling Neurocomputing. 52: 31-37. DOI: 10.1016/S0925-2312(02)00823-8  0.596
2003 Pipa G, Diesmann M, Grün S. Significance of joint-spike events based on trial-shuffling by efficient combinatorial methods Complexity. 8: 79-86. DOI: 10.1002/Cplx.10085  0.62
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