Publications

Journal articles:

  • Ichim, A.M., Barzan, H., Moca, V.V., Nagy-Dabacan, A., Ciuparu, A., Hapca, A., Vervaeke, K., & Muresan, R.C. (2024)
    The gamma rhythm as a guardian of brain health. eLife, 13, e100238
    [https://doi.org/10.7554/eLife.100238]

  • Varga, L., Moca, V.V., Molnár, B., Perez-Cervera, L., Selim, M. K., Díaz-Parra, A., Moratal, D., Péntek, B., Sommer, W. H., Mureșan, R. C., Canals, S., & Ercsey-Ravasz, M. (2024)
    Brain dynamics supported by a hierarchy of complex correlation patterns defining a robust functional architecture. Cell Systems, 15(8), 770-786.e5.
    [https://doi.org/10.1016/j.cels.2024.07.003]

  • Gal, C., Țincaș, I., Moca, V.V., Ciuparu, A., Dan, E. L., Smith, M. L., Gliga, T., & Mureșan, R. C. (2024)
    Randomness impacts the building of specific priors, visual exploration, and perception in object recognition. Scientific Reports, 14(1)
    [https://doi.org/10.1038/s41598-024-59089-1]

  • Bakouh, N., Castaño-Martín, R., Metais, A., Dan, E.L., Balducci, E., Chhuon, C., Lepicka, J., Barcia, G., Losito, E., Lourdel, S., Planelles, G., Muresan, R.C., Moca, V.V., Kaminska, A., Bourgeois, M., Chemaly, N., Rguez, Y., Auvin, S., Huberfeld, G., … Blauwblomme, T. (2024)
    Chloride deregulation and GABA depolarization in MTOR related malformations of cortical development. Brain, awae262
    [https://doi.org/10.1093/brain/awae262]

  • Ardelean, E.-R., Bârzan, H., Ichim, A.-M., Mureşan, R.C., & Moca, V.V. (2023)
    Sharp detection of oscillation packets in rich time-frequency representations of neural signals. Frontiers in Human Neuroscience, 17
    [https://doi.org/10.3389/fnhum.2023.1112415]

  • Grosu G.F., Hopp A.V., Moca V.V., Bârzan H., Ciuparu A., Ercsey-Ravasz M., Winkel M., Linde H., Mureșan R.C. (2022)
    The fractal brain: scale-invariance in structure and dynamics. Cerebral Cortex
    [https://doi.org/10.1093/cercor/bhac363]

  • Moca V.V., Bârzan H., Nagy-Dăbâcan A., and Mureșan R.C. (2021)
    Time-frequency super-resolution with superlets. Nature Communications 12, 337
    [https://doi.org/10.1038/s41467-020-20539-9]

    The BioRxiv preprint:
    Moca V.V., Nagy-Dăbâcan A., Bârzan H., Mureșan R.C. (2019)
    Superlets: time-frequency super-resolution using wavelet sets, BioRxiv 583732
    [link]

  • Moca VV, Nikolic D, Singer W, Muresan RC (2014)
    Membrane Resonance Enables Stable and Robust Gamma Oscillations, Cereb Cortex 24:119-142
    [PDF]

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

  • Moca VV, Scheller B, Muresan RC, Daunderer M, Pipa G (2009)
    EEG under anesthesia-feature extraction with TESPAR, Comput Methods Programs Biomed 95: 191-202
    [preprint-PDF] [link]

  • Muresan RC, Jurjut OF, Moca VV, Singer W, Nikolic D (2008)
    The oscillation score: an efficient method for estimating oscillation strength in neuronal activity, J Neurophysiol 99: 1333-1353
    [link] [free code]

  • Nikolic D, Moca VV, Singer W, Muresan RC (2008)
    Properties of multivariate data investigated by fractal dimensionality, J Neurosci Methods 172: 27-33
    [personal PDF] [link]


PhD thesis:

  • Moca VV (2010)
    Methods for analysis and classification of bilogical signals.
    [PDF]


Conferences, poster and other talks:

  • Ardelean, A.-I., Ardelean, E.-R., Moca, V.V., Mureşan, R.C., & Dînşoreanu, M. (2023)
    Burst detection in neuronal activity. 2023 IEEE 19th International Conference on Intelligent Computer Communication and Processing (ICCP), 349–356.
    [PDF] [https://doi.org/10.1109/ICCP60212.2023.10398703]

  • Ardelean, E.-R., Terec, R.-D., Marieş, C.-M., Moca, V.V., Mureşan, R.C., & Dînşoreanu, M. (2023)
    Spike sorting using Superlets: Identifying feature importance through perturbation. 2023 IEEE 19th International Conference on Intelligent Computer Communication and Processing (ICCP), 357–362.
    [PDF] [https://doi.org/10.1109/ICCP60212.2023.10398655]

  • Moisa, O.M., Pop, I., Ardelean, E.-R., Moca, V.V., Mureşan, R.C., & Dînşoreanu, M. (2023)
    Symbolic Analysis Based Pipeline for EEG Data. 2023 IEEE 19th International Conference on Intelligent Computer Communication and Processing (ICCP), 371–378.
    [PDF] [https://doi.org/10.1109/ICCP60212.2023.10398607]

  • Dumitru, D.A., Ceuta, E. B., Moca, V.V., Mureșan, R.C., & Dînșoreanu, M. (2022)
    Extraction of Functional Brain Networks from EEG Signals in the Context of Visual Perception. 2022 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR), 1–6.
    [PDF] [https://doi.org/10.1109/AQTR55203.2022.9801941]

  • Mureșan, D.B., Ciure, R.-D., Ardelean, E.R., Moca, V.V., Mureșan, R.C., & Dînșoreanu, M. (2022)
    Spike sorting using Superlets: Evaluation of a novel feature space for the discrimination of neuronal spikes. 2022 IEEE 18th International Conference on Intelligent Computer Communication and Processing (ICCP), 229–235.
    [PDF] [https://doi.org/10.1109/ICCP56966.2022.10053955]

  • 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.
    [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.Local Field Potential Microstate Analysis. 2022 IEEE 18th International Conference on Intelligent Computer Communication and Processing (ICCP), 221–227
    [PDF] [https://doi.org/10.1109/ICCP56966.2022.10053960]

  • Dumitru D.A., Ceuta E.B., Moca V.V., Mureșan R.C., Dînșoreanu M. (2022)
    Extraction of Functional Brain Networks from EEG Signals in the Context of Visual Perception. in 2022 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR), 1–6
    [PDF] [https://doi.org/10.1109/AQTR55203.2022.9801941]

  • Bârzan H., Ichim A.M., Moca V.V., Mureşan R.C. (2022)
    Time-Frequency Representations of Brain Oscillations: Which One Is Better? Frontiers in Neuroinformatics 16.
    [https://doi.org/10.3389/fninf.2022.871904]

  • Dodon A., Calugar A.M., Potolea R., Lemnaru C., Dînşoreanu M., Moca V.V., Mureșan R.C. (2021)
    A Generative Adversarial Approach for the Detection of Typical and Drowned Action Potentials. in 2021 IEEE 17th International Conference on Intelligent Computer Communication and Processing (ICCP), 477–481
    [PDF] [https://www.doi.org/10.1109/ICCP53602.2021.9733643]

  • Aldea R.I., Dinsoreanu M., Potolea R., Lemnaru C., Mureșanan R.C., Moca V.V. (2021)
    Weighted Principal Component Analysis based on statistical properties of features for Spike Sorting. in 2021 IEEE 17th International Conference on Intelligent Computer Communication and Processing (ICCP), 455–460
    [PDF] [https://www.doi.org/10.1109/ICCP53602.2021.9733683]

  • Barzan H, Moca VV , Ichim AM, Muresan RC (2020)
    Fractional Superlets. In: EURASIP 28th European Signal Processing Conference (EUSIPCO), Amsterdam, 18-22 January, 2021, pp. 2220-2224
    [PDF]

  • Onofrei I, Salagean A, Sirca N, Moca VV, Nagy-Dabacan A, Muresan RC, 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), In press, to appear on IEEEXplore

  • Petrutiu V, Palcu LD, Lemnaru C, Dinsoreanu M, Potolea R, Moca VV (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] [https://www.doi.org/10.1109/ICCP51029.2020.9266157]

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

  • Moca VV, Klein L, Klon-Lipok J, Singer W, Muresan RC (2018)
    Enhancement of gamma oscillations co-occurs with an increase in the complexity of cortical dynamics. 11th FENS Forum of Neuroscience, Berlin
    [Poster]

  • Gal C, Moca VV, Tincas I, Gliga T, Smith M, Muresan RC (2018)
    Task predictability determines knowledge acquisition during object recognition. 41st European Conference on Visual Perception 26-30, Trieste, Italy, P237A.
    [Poster]

  • Moca VV and Muresan RC (2013)
    Discriminating legitimate oscillations from broadband transients In (CNS Meeting 2013) Paris, France
    BMC Neuroscience 14 (Issue 1 Supplement)
    [Abstract] [Poster]

  • Tincas I, Moca VV, Muresan RC (2011)
    Pupil dilation and visual object recognition, In: XI International Conference on Cognitive Neuroscience (ICON XI) Frontiers in Human Neuroscience
    [abstract-link]

  • Moca VV, Muresan RC (2011)
    Emergence of beta/gamma oscillations: ING, PING, and what about RING? In: (CNS Meeting 11) Stockholm, Sweden: BMC Neuroscience 12(Suppl 1), p. 230
    [poster-PDF] [abstract-link]

  • Moca VV, Scheller B, Muresan RC, Daunderer M, Pipa G (2009)
    EEG processing with TESPAR for depth of anesthesia detection, In: (CNS Meeting 09) Berlin Germany: BMC Neuroscience 10 (Suppl 1), p. 68
    [poster-PDF] [abstract-link]

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

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

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

  • Moca VV, Nikolic D, Muresan RC (2008)
    Real and modeled spike trains: Where do they meet? In: Kurkov� V, Neruda R, Koutn�k J, editors, Proceedings of the 18th ICANN (2). Prague, Czech Republic: Springer, volume 5164 of Lecture Notes in Computer Science, pp. 488-497
    [abstract-link]

  • Moca VV, Scheller B, Pipa G, Lupu E (2007)
    TESPAR - towards biomedical applications, In: 1st International Conference on Advancements of Medicine and Health Care through Technology, MediTech2007. pp. 281-286

  • Moca VV (2006)
    EEG under anesthesia - learning from human experience, Max Planck Society, Ringberg retreat, Germany.

  • Moca VV (2006)
    TESPAR and EEG under anesthesia FIGGS end of term seminar, Frankfurt Institute for Advanced Studies, Frankfurt, Germany.

  • Moca VV (2006)
    TESPAR a biometric time domain approach to speaker recognition, Acta Technica Napocensis 47: 57-62

  • Moca VV, Lupu E, Pop PG (2005)
    TESPAR coding method evaluation in speaker recognition experiments, In: Trends in Speech Technology Proceedings of the 3rd Conference Speech Technology and Human-Computer-Dialogue: SpeD 2005. Cluj-Napoca, Romania, pp. 201-212. ISBN 973-27-1178-7

  • Moca VV (2005)
    TESPAR a robust voice biometric, In: Verificatori biometrici workshop Cluj-Napoca. Cluj-Napoca, Romania, ISBN 973-656-918-7.

  • Lupu E, Moca VV, Pop PG (2004)
    Application for TESPAR coding study and speaker recognition experiments, In: Scientific bulletin POLITEHNICA University of Timisoara, Proceedings of Symposium on Electronics and Telecomunicetions Etc 2004. Timisoara, Romania, volume 1, pp. 279-282, ISSN 1583-3380

  • Lupu E, Moca VV, Pop PG (2004)
    Environment for speaker recognition using speech coding, In: Proceedings of Communications. Bucharest, Romania, volume 1, pp. 199-204. ISBN 973-640-036-0

  • Lupu E, Moca VV, Pop PG (2003)
    TESPAR coding study for speaker recognition, In: The 30th session of scientific presentations "Modern technologies in the XXI Century" Bucharest. Bucharest, Romania, pp. 214-221, ISBN 973-640-012-3.

Updated: November 2024