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Publications

Articles

• Bilc M.I., Iacob A., Szekely-Copindean R.D., Kiss B., Stefan M.G., Muresan R.C., Pop C.F., Pitur S., Szentagotai-Tatar A., Vulturar R., MacLeod C., Miu A.C. (2023), Serotonin and emotion regulation: the impact of tryptophan depletion on emotional experience, neural and autonomic activity. Cognitive, Affective, & Behavioral Neuroscience 23, 1414–1427 (2023).
   [Link]

• Grosu G.F., Hopp A.V., Moca V.V., Barzan H., Ciuparu A., Ercsey-Ravasz M., Winkel M., Linde H., Muresan R.C. (2023), The fractal brain: scale-invariance in structure and dynamics. Cerebral Cortex 33(8):4574–4605.
   [Open access link]

• Ardelean E.R., Coporiie A., Ichim A.M., Dinsoreanu M., Muresan R.C. (2023), A study of autoencoders as a feature extraction technique for spike sorting. PLoS One 18(3):e0282810.
   [Open access link]

• Ardelean E.R., Ichim A.M., Dinsoreanu M., Muresan R.C. (2023), Improved space breakdown method – A robust clustering technique for spike sorting. Frontiers in Computational Neuroscience 17:1019637.
   [Open access link]

• Ardelean A.I., Ardelean E.R., Moca V.V., Muresan R.C., Dinsoreanu M. (2023), Burst detection in neuronal activity. Intelligent Computer Communication and Processing (ICCP), 2023 19th IEEE International Conference on, In press.
   [pdf]  

• Ardelean E.R., Terec R.D., Maries C.M., Moca V.V., Muresan R.C., Dinsoreanu M. (2023), Spike sorting using Superlets: Identifying feature importance through perturbation. Intelligent Computer Communication and Processing (ICCP), 2023 19th IEEE International Conference on, In press.
   [pdf]  

• Moisa O.M., Pop I., Ardelean E.R., Moca V.V., Muresan R.C., Dinsoreanu M. (2023), Symbolic Analysis Based Pipeline For EEG Data. Intelligent Computer Communication and Processing (ICCP), 2023 19th IEEE International Conference on, In press.
   [pdf]  

• Barzan H., Ichim A.M., Moca V.V., Muresan R.C. (2022), Time-Frequency Representations of Brain Oscillations: Which One Is Better? Frontiers in Neuroinformatics 16:871904, doi: 10.3389/fninf.2022.871904.
   [Open access link]

• Dumitru D.A., Ceuta E.B., Moca V.V., Muresan R.C., Dinsoreanu M. (2022), Extraction of Functional Brain Networks from EEG Signals in the Context of Visual Perception. Automation, Quality and Testing, Robotics (AQTR), 2022 IEEE International Conference on, pp. 1-6, doi: 10.1109/AQTR55203.2022.9801941.
   [pdf]   [IEEE Xplore link]

• Muresan D.B., Ciure R.D., Ardelean E.R., Moca V.V., Muresan R.C., Dinsoreanu M. (2022), Spike sorting using Superlets: Evaluation of a novel feature space for the discrimination of neuronal spikes. Intelligent Computer Communication and Processing (ICCP), 2022 18th IEEE International Conference on, In press.
   [pdf]  

• Salagean A., Pasc A.M., Ardelean E.R., Muresan R.C., Moca V.V., Dinsoreanu M., Potolea R., Lemnaru C. (2022), Local Field Potential Microstate Analysis. Intelligent Computer Communication and Processing (ICCP), 2022 18th IEEE International Conference on, In press.
   [pdf]  

• Moca V.V., Barzan H., Nagy-Dabacan A., Muresan R.C. (2021), Time-frequency super-resolution with superlets. Nature Communications 12, 337.
   [Open access link]

• Ciuparu A., Muresan R.C. (2021), Jittered sampling - a potential solution for detecting high frequencies in GCaMP recordings. Intelligent Computer Communication and Processing (ICCP), 2021 17th IEEE International Conference on, pp. 469-475.
   [pdf]   [IEEE Xplore link]

• Dodon A., Calugar M.A., Potolea R., Lemnaru C., Dinsoreanu M., Moca V.V., Muresan R.C. (2021), A generative adversarial approach for the detection of typical and drowned action potentials. Intelligent Computer Communication and Processing (ICCP), 2021 17th IEEE International Conference on, pp. 477-481.
   [pdf]   [IEEE Xplore link]

• Aldea R., Dinsoreanu M., Potolea R., Lemnaru C., Muresan R.C., Moca V.V. (2021), Weighted Principal Component Analysis based on statistical properties of features for spike sorting. Intelligent Computer Communication and Processing (ICCP), 2021 17th IEEE International Conference on, pp. 455-460.
   [pdf]   [IEEE Xplore link]

• Ciuparu A., Nagy-Dabacan A., Muresan R.C. (2020), Soft++, a multi-parametric non-saturating non-linearity that improves convergence in deep neural architectures. Neurocomputing, 384:376-388.
   [Open access link]

• de Calbiac H., Dabacan A., Muresan R., Kabashi E., Ciura S. (2020), Behavioral And Physiological Analysis In A Zebrafish Model Of Epilepsy. J. Vis. Exp. (Pending Publication), e58837, In-press.
   [Journal website link]

• Barzan H., Moca V.V., Ichim A.M., Muresan R.C. (2020), Fractional Superlets. EURASIP 28th European Signal Processing Conference (EUSIPCO), Amsterdam, 18-22 January, 2021, pages 2220-2224.
   [pdf]

• Palcu L.D., Supuran M., Lemnaru C., Dinsoreanu M., Potolea R., Muresan R.C. (2020), Discovering discriminative nodes for classification with deep graph convolutional methods. In M. Ceci et al. (Eds.): NFMCP 2019, Lecture Notes in Artificial Intelligence 11948, pp. 67–82, 2020, Springer Nature.
   [pdf]  [Link]

• Onofrei I., Salagean A., Sirca N., Moca V., Nagy-Dabacan A., Muresan R., Potolea R., Lemnaru C., Dinsoreanu M. (2020), Using Symbolic Analysis of Local Field Potentials for Anesthesia Depth Prediction. In 2020 IEEE 16th International Conference on Intelligent Computer Communication and Processing (ICCP), pp. 21-28.
   [pdf]   [IEEE Xplore link]

• Petrutiu V., Palcu L.D., Lemnaru C., Dinsoreanu M., Potolea R., Muresan R.C., Moca V.V. (2020), Enhancing the Classification of EEG Signals using Wasserstein Generative Adversarial Networks. In 2020 IEEE 16th International Conference on Intelligent Computer Communication and Processing (ICCP), pp. 29-34.
   [pdf]   [IEEE Xplore link]

• Gheorghiu M., Ciuparu A., Mimica B., Whitlock J., Muresan R.C. (2020), A machine learning approach to investigate fronto-parietal neural ensemble dynamics during complex behavior. IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR), doi:10.1109/AQTR49680.2020.9129986.
   [pdf]  [IEEE Xplore link]

• Barzan H., Ichim A.M., Muresan R.C. (2020), Machine learning-assisted detection of action potentials in extracellular multi-unit recordings. IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR), doi:10.1109/AQTR49680.2020.9130026.
   [pdf]  [IEEE Xplore link]

• Dan L., Dinsoreanu M., Muresan R.C. (2020), Accuracy of six interpolation methods applied on pupil diameter data. IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR), doi:10.1109/AQTR49680.2020.9129915.
   [pdf]  [IEEE Xplore link]

• Moca V.V., Nagy-Dabacan A., Barzan H., Muresan R.C. (2019), Superlets: time-frequency super-resolution using wavelet sets. BioRxiv 583732; doi:10.1101/583732
   [pdf]

• Jurjut O.F., Gheorghiu M., Singer W., Nikolić D., Muresan R.C. (2019), Hold Your Methods! How Multineuronal Firing Ensembles Can Be Studied Using Classical Spike-Train Analysis Techniques, Frontiers in Systems Neuroscience 13:21, doi:10.3389/fnsys.2019.00021.
   [pdf]

• Ichim A.M., Nagy-Dabacan A., Muresan R.C. (2019), A method for the measurement and interpretation of neuronal interactions: improved fitting of cross-correlation histograms using 1D-Gabor Functions. 2019 IEEE 15th International Conference on Intelligent Computer Communication and Processing (ICCP), pp. 525-528, doi: 10.1109/ICCP48234.2019.8959531.
   [pdf]  [IEEE Xplore link]

• Gheorghiu M., Nagy-Dabacan A., Muresan R.C. (2019), Detecting non-redundant collective activity of neurons. 2019 IEEE 15th International Conference on Intelligent Computer Communication and Processing (ICCP), pp. 539-543, doi: 10.1109/ICCP48234.2019.8959815.
   [pdf]  [IEEE Xplore link]

• Ardelean E-R., Stanciu A., Dinsoreanu M., Potolea R., Lemnaru C., Moca V.V. (2019), Space Breakdown Method. A new approach for density-based clustering. 2019 IEEE 15th International Conference on Intelligent Computer Communication and Processing (ICCP), pp. 419-425, doi: 10.1109/ICCP48234.2019.8959795.
   [pdf]  [Conference website link]

• Palcu L-D., Supuran M., Lemnaru C., Dinsoreanu M., Potolea R., Muresan R.C. (2019), Breaking the interpretability barrier - a method for interpreting deep graph convolutional models. International Workshop NFMCP in conjunction with ECML-PKDD 2019, Wurzburg, Germany.
   [Workshop website link]

• de Calbiac H., Dabacan A., Marsan E., Tostivint H., Devienne G., Ishida S., Leguern E., Baulac S., Muresan R.C., Kabashi E., Ciura S. (2018), Depdc5 knockdown causes mTOR-dependent motor hyperactivity in zebrafish. Annals of Clinical and Translational Neurology, 5(5):510-523.
   [pdf]

• Dolean S., Dinsoreanu M., Muresan R.C., Geiszt A., Potolea R., Tincas I. (2018), A Scaled-Correlation Based Approach for Defining and Analyzing Functional Networks. In: Appice A., Loglisci C., Manco G., Masciari E., Ras Z. (eds) New Frontiers in Mining Complex Patterns. NFMCP 2017. Lecture Notes in Computer Science, vol 10785. Springer.
   [pdf]  [Journal website link]

• Nedelcu E., Portase R., Tolas R., Muresan R.C., Dinsoreanu M., Potolea R. (2017), Artifact detection in EEG using machine learning. Intelligent Computer Communication and Processing (ICCP), 2017 13th IEEE International Conference on, pp. 77-83.
   [pdf]  [IEEE Xplore link]

• Rus I.D., Marc O., Dinsoreanu M., Potolea R., Muresan R.C. (2017), Classification of EEG signals in an object recognition task. Intelligent Computer Communication and Processing (ICCP), 2017 13th IEEE International Conference on, pp. 391-395.
   [pdf]  [IEEE Xplore link]

• Dolean S., Geiszt A., Muresan R.C., Dinsoreanu M., Potolea R., Tincas I. (2017), A Scaled-Correlation based approach for generating and analyzing functional networks from EEG signals. Proceedings of International Workshop NFMCP in conjunction with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML-PKDD 2017), Sep 18-22, 2017, Skopje, Macedonia.
   [pdf]

• Ciuparu A. and Muresan R.C. (2016), Sources of bias in single-trial normalization procedures. European Journal of Neuroscience 43(7):861-869.
   [pdf]  [Supporting information]  [Journal website link]

• Dabacan A. and Muresan R.C. (2016), Robust analysis of non-stationary cortical responses: tracing variable frequency gamma oscillations and separating multiple component input modulations. Proceedings of MediTech 2016.
   [pdf]

• Dabacan A., Rusu C., Muresan R.C. (2016), Probing frequency response in neural networks using light. Novice Insights.
   [pdf]

• Dabacan, A., Rusu, C., Ciura, S., Kabashi, E., Muresan, R.C. (2015), Method for feature extraction from electrophysiological recordings of epileptic activity. Acta Electrotehnica, 56 (1-2), pp. 21-26.
   [pdf]

• Moca V.V., Nikolic D., Singer W., Muresan R.C. (2014), Membrane resonance enables stable and robust gamma oscillations. Cerebral Cortex 24(1):119-142.
   [pdf]  [link]

• Pampu N.C., Vicente R., Muresan R.C., Priesemann V., Siebenhühner F., Wibral M. (2013), Transfer Entropy as a tool for reconstructing interaction delays in neural signals, Proceedings of International Symposium on Signals, Circuits & Systems - ISSCS 2013, pp. 1-4.
   [pdf]

• Nikolic D., Muresan R.C., Feng W., Singer W. (2012), Scaled correlation analysis: a better way to compute a cross-correlogram. European Journal of Neuroscience 35(5): 742-762.
   [pdf]  [link]

• Moca V.V., Tincas I., Melloni L., Muresan R.C. (2011), Visual exploration and object recognition by lattice deformation. PLoS One 6(7): e22831.
   [pdf]  [link]

• Jurjut O.F., Nikolic D., Singer W., Yu S., Havenith M.N., Muresan R.C. (2011), Timescales of Multineuronal Activity Patterns Reflect Temporal Structure of Visual Stimuli. PLoS One 6(2): e16758.
   [pdf]  [link]

• Jurjut O.F., Nikolic D., Pipa G., Singer W., Metzler D., Muresan R.C. (2009), A color-based visualization technique for multi-electrode spike trains. Journal of Neurophysiology 102:3766-3778.
   [pdf]

• Moca V.V., Scheller B., Muresan R.C., Daunderer M., Pipa G. (2009), EEG under anesthesia - feature extraction with TESPAR. Computer Methods and Programs in Biomedicine 95:191-202.
   [pdf]

• Muresan R.C., Jurjut O.F., Moca V.V., Singer W., Nikolic D. (2008), The Oscillation Score: An Efficient Method for Estimating Oscillation Strength in Neuronal Activity. Journal of Neurophysiology 99:1333-1353.
   [pdf & free source code]

• Nikolic D., Moca V.V., Singer W. and Muresan R.C. (2008), Properties of multivariate data investigated by fractal dimensionality. Journal of Neuroscience Methods 172(1):27-33.
  [link]

• Muresan R.C., Singer W., Nikolic D. (2008), The InfoPhase Method or How to Read Neurons with Neurons. In V. Kurkova et al. (eds.): ICANN 2008, Part II, Lecture Notes in Computer Science 5164, pp. 498-507, Springer, Berlin / Heidelberg.
   [pdf] [link]

• Moca V.V., Nikolic D., and Muresan R.C. (2008), Real and Modeled Spike Trains: Where Do They Meet? In V. Kurkova et al. (eds.): ICANN 2008, Part II, Lecture Notes in Computer Science 5164, pp. 488-497, Springer, Berlin / Heidelberg.
   [pdf] [link]

• Muresan R.C. and Savin C. (2007), Resonance or Integration? Self-sustained Dynamics and Excitability of Neural Microcircuits. Journal of Neurophysiology 97:1911-1930.
   [pdf]

• Lazar A., Muresan R.C., Stadtler E., Munk M., Pipa G. (2007), Importance of electrophysiological signal features assessed by classification trees. Neurocomputing Vol. 70:2017-2021.
  [link]

• Florian R.V. and Muresan R.C. (2006), Phase precession and recession with STDP and anti-STDP. Lecture Notes in Computer Science, Vol. 4131, Eds. S. Kollias et al., pp. 718-727, Springer-Verlag Berlin Heidelberg.
  [link]

• Savin C., Ignat I. and Muresan R.C. (2006), Heterogeneous networks of spiking neurons: self-sustained activity and excitability. Proceedings of the IEEE 2nd International Conference on Intelligent Computer Communication and Processing (ICCP) 2006.
   [pdf]

• Savin C., Ignat I. and Muresan R.C. (2006), Resonance as an effective mechanism of dynamical stability in large microcircuits of spiking neurons. Computational Neuroscience Meeting, Edinburgh 2006.
   [pdf]

• Muresan R.C., Pipa G., Florian R.V., Wheeler D.W. (2005), Coherence, Memory and Conditioning. A Modern Viewpoint. Neural Information Processing - Letters and Reviews, Vol. 7, No. 2, pp. 19-28.
   [pdf]

• Muresan R.C., Pipa G., Wheeler D.W. (2005), 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, Springer-Verlag Berlin Heidelberg.
   [pdf]

• Muresan R.C. (2004), Scale Independence in the Visual System, in: "Rajapakse, Jagath C.; Wang, Lipo (Eds). Neural Information, Processing: Research and Development", Springer-Verlag, pp. 1-18.
   [pdf]

• Muresan R.C. and Ignat I. (2004), The "Neocortex" Neural Simulator. A Modern Design. Proceedings of the International Conference on Intelligent Engineering Systems 2004.
   [pdf]

• Muresan R.C. and Ignat I. (2004), Principles of Design for Large Scale Neural Simulators. Proceedings of the International Conference on Automation, Quality and Testing, Robotics 2004.
   [pdf]

• Muresan R.C. (2004), The Coherence Theory: Simple Attentional Modulation Effects. Neurocomputing, Vol. 58-60C, Special Issue: Computational Neuroscience: Trends in Research 2004 Edited by E. De Schutter, pp. 949-955, 2004.
   [pdf]

• Muresan R.C. (2003), Pattern Recognition Using Pulse-Coupled Neural Networks and Discrete Fourier Transforms. Neurocomputing, vol. 51C, pp. 487-493.
   [pdf]

• Muresan R.C. (2003), RetinotopicNET: An Efficient Simulator for Retinotopic Visual Architectures. Proceedings of the European Symposium on Artificial Neural Networks, Bruges, April 23-25 2003, pp. 247-254.
   [pdf]

• Muresan R.C. (2002), Visual Scale Independence in a Network of Spiking Neurons. Proceedings of 9th International Conference on Neural Information Processing Proceedings (ICONIP), Singapore, Vol. 4, pp. 1739-1743.
   [pdf]

• Muresan R.C. (2002), Complex Object Recognition Using a Biologically Plausible Neural Model, In: Mastorakis NE (eds), Advances in Simulation, Systems Theory and Systems Engineering, pp. 163-168, ISBN ISBN 960 8052 70X.
   [pdf]

Abstracts, posters and talks

• Ichim A.M., Barzan H., Moca V.V., Vervaeke K., Muresan R.C. (2022), Blue flicker stimulation enhances gamma rhythms in mouse visual cortex. 31st Annual Computational Neuroscience Meeting, CNS*2022, Melbourne, Australia. In press.
   [pdf]  

• Dan E.L., Moca V.V., Dinsoreanu M., Muresan R.C. (2022), Gaze lateralization bias during free visual exploration of faces. 31st Annual Computational Neuroscience Meeting, CNS*2022, Melbourne, Australia. In press.
   [pdf]  

• Moca V.V., Muresan R.C. (2019), Precise time-frequency localization of transient gamma band oscillations, Joint Mid-Term Symposium of JTCs 2017: Synaptic Dysfunction & Ethical, Legal, and Social Aspects (ELSA) of Neuroscience, Lisbon, Portugal.
   [Workshop website link]

• Gheorghiu M., Mimica B., Whitlock J., Muresan R.C. (2017), Theta/alpha coordination of pre-motor and parietal networks during free behavior in rats, BMC Neuroscience 2017, 18 (Suppl 1):P182.
   [pdf]

• Dabacan A., Barzan H., Gheorghiu M., Muresan R. (2017), Modulation of oscillatory activity and synchrony in V1 as a function of stimulus features, European Conference on Visual Perception (ECVP 2017), Berlin, Germany, P58.
   [pdf]

• Dabacan A., Muresan R.C. (2016), Effects of periodic stimulation on cortical circuits as a function of stimulated population properties. Society for Neuroscience Annual Meeting, 12-16 November, San Diego, Accepted poster.
  

• Dabacan A., Ciura S., Kabashi E., de Calbiac H., Muresan, R.C. (2015), Novel perspective on field recordings in zebrafish models of epilepsy, (CNS Meeting 2014) Prague Czech Republic: BMC Neuroscience 16(Suppl 1), P171.
   [pdf]

• Dabacan A., Muresan R.C. (2014), Optogenetic manipulation of neural circuits. Plenary talk, SNN International conference.
  

• Moca V.V., Muresan R.C. (2013), Discriminating legitimate oscillations from broadband transients, (CNS Meeting 2013) Stockholm Sweden: BMC Neuroscience 14(Suppl 1), P286.
   [pdf] [link]

• Tincas I., Moca V.V. & Muresan R.C. (2013), Visual sampling and integration of information in object recognition. Poster presented at the Association for the Scientific Study of Consciousness (ASSC 17), San Diego CA, USA, July 12-15 2013.
   [pdf]

• Tincas I., Moca V.V., Muresan R.C. (2011), Pupil dilation and visual object recognition, (ICON XI 2011) Palma de Mallorca, Spain: Frontiers in Human Neuroscience, doi:10.3389/conf.fnhum.2011.207.00473.
   [link]

• Moca V.V., Muresan R.C. (2011), Emergence of beta/gamma oscillations: ING, PING, and what about RING?, (CNS Meeting 2011) Stockholm Sweden: BMC Neuroscience 12 (Suppl 1), p. 230.
   [pdf] [link]

• Muresan R.C. (2011), Visual Exploration and Object Recognition with the "Dots" Stimuli, invited talk at Castle Ringberg retreat of the Max Planck Institute for Brain Research, Tegernsee, Germany, September 2011.

• Jurjut O.F., Nikolic D., Singer W., Weber C., Muresan R.C. (2010), Quantifying the stimulus-specificity and time-locking of spatiotemporal spike patterns. 40th Annual Meeting of the Society for Neuroscience, San Diego, USA, November 13 -17, 2010.

• Muresan R.C. (2010), Looking into the brain: where modeling, experiment and analysis meet, invited talk at Diaspora in Cercetarea Stiintifica si Invatamantul Superior din Romania, Workshop Exploratoriu: "Noi perspective de investigare a creierului", Bucharest, Romania, September 2010.

• Muresan R.C. (2009), Combined Approaches to Understanding the Brain, invited talk at Seminari di Neuroscienze e Scienze Psichologiche e Psichiatriche, University of Verona, Verona, Italy.
  

• Muresan R.C., Tincas I., Moca V.V., Melloni L. (2009), Probing the visual system with visual hypotheses, (CNS Meeting 09) Berlin Germany: BMC Neuroscience 10 (Suppl 1), p. 356.
   [pdf] [link]

• Moca V.V., Scheller B., Muresan R.C., Daunderer M., Pipa G. (2009), EEG processing with TESPAR for depth of anesthesia detection, (CNS Meeting 09) Berlin Germany: BMC Neuroscience 10 (Suppl 1), p. 68.
   [pdf] [link]

• Muresan R.C., Tincas I., Moca V.V., Melloni L. (2009), Vision by inference: visual recognition under uncertainty, (ASSC XIII) Berlin Germany, p. 195.
   [link]

• Moca V.V., Scheller B., Muresan R.C., Daunderer M., Pipa G. (2009), Importance of EEG frequency bands in the assessment of depth of anesthesia, (ASSC XIII) Berlin Germany, p. 187.
   [link]

• Muresan R.C. (2009), Investigating Brain Function from Multiple Perspectives: Modeling, Experiment, Analysis, invited talk at AHFMR Polaris Mini Workshop on Brain Dynamics, Canadian Centre for Behavioural Neuroscience, Lethbridge, Canada.
  

• Tincas I., Visu-Petra L., Benga O. (2009), Regulation and anxiety in preschoolers: Contributions from temperament and attentional control. SRCD Biennial Meeting, April 2-4, Denver, Colorado, USA.
   [link]

• Muresan R.C. (2008), Dynamics of self-sustained microcircuits examined with regular-spiking readouts, (CNS Meeting 08) Portland (Oregon), USA: BMC Neuroscience 9 (Suppl 1), p. 37.
   [pdf] [link]

• Jurjut O.F., Nikolic D., Singer W., Metzler D., Muresan R.C. (2008), Multidimensional Patterns of Neuronal Activity: How do we see them?, (CNS Meeting 08) Portland (Oregon), USA: BMC Neuroscience 9 (Suppl 1), p. 128.
   [pdf] [link]

• Jurjut O.F., Nikolic D., Singer W., Metzler D., Muresan R.C. (2008), Exploring Parallelly Recorded Spike Trains, (Cosyne 08) Salt Lake City, USA, I-33.
  [pdf]

• Muresan R.C. (2007), Do I integrate or do I resonate? That is the question! Coherent Behavior in Neural Networks (CoBeNN) Mallorca, Spain, P23.
   [pdf]

• Jurjut O.F., Nikolic D., Metzler D., Singer W., Muresan R.C. (2007), Vizualizing Multi-dimensional Neuronal Data, Coherent Behavior in Neuronal Networks (CoBeNN) Mallorca, Spain, P16.