Transylvanian Institute of Neuroscience | TINS


Publications

2022

  • 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]

2021

  • 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]

  • Wandres M., Pfarr S., Molnar B., Schollkopf U., Ercsey-Ravasz M., Sommer W.H., Korber C. (2021), Alcohol and sweet reward are encoded by distinct meta-ensembles. Neuropharmacology, vol. 195, 108496.
     [pdf]    [Journal link]

  • Sandor B., Schneider B., Lazar Z.I., Ercsey-Ravasz M. (2021), A Novel Measure Inspired by Lyapunov Exponents for the Characterization of Dynamics in State-Transition Networks. Entropy 23, 103.
     [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]

  • Ravasz L., Kekesi K.A., Mittli D., Ivilinov Todorov M., Borhegy Z., Ercsey-Ravasz M., Tyukodi B., Wang J., Bartfai T., Eberwine J., Juhasz G., (2021), Cell Surface Protein mRNAs Show Differential Transcription in Pyramidal and Fast-Spiking Cells as Revealed by Single-Cell Sequencing. Cerebral Cortex, 31:731–745.
    [Open access link]

  • Volpi R., Malagò L., (2021), Natural alpha embeddings. Information Geometry 4(1), 3-29.
     [pdf]    [Journal website link]

  • Volpi R., Thakur U., Malagò L., (2021), Changing the geometry of representations: α-embeddings for nlp tasks. Entropy 23(3), 287.
    [Open access link]

2020

  • 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]

2019

  • Moca V.V., Nagy-Dăbâcan A., Bârzan 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]

  • Lervåg A., Dolean D., Tincas I., Melby-Lervåg M. (2019), Socioeconomic background, nonverbal IQ and school absence affects the development of vocabulary and reading comprehension in children living in severe poverty. Developmental Science 00:e12858, https://doi.org/10.1111/desc.12858.
     [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]  [IEEE Xplore 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]

2018

  • Molnár B., Molnár F., Varga M., Toroczkai Z., Ercsey-Ravasz M. (2018), A continuous-time MaxSAT solver with high analog performance. Nature Communications 9 (1), 4864.
     [pdf]

  • 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]

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

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

  • Gheorghiu M., Whitlock J., Muresan R.C., Mimica B. (2018), Visualization of pre-motor and parietal network activity patterns during free behavior in rats. BMC Neuroscience 19(Suppl 2):P33.


All publications of TINS labs