Research Articles (peer-reviewed)⌗

  1. Neural sampling machine with stochastic synapse allows brain-like learning and inference
    S. Dutta, G. Detorakis, A. Khanna, B. Grisafe, E. Neftci, and S. Datta
    Nature Communications 13, 2571, 2022, DOI:10.1038/s41467-022-30305-8
    [Article]

  2. OpenPelt: Python Framework for Thermoelectric Temperature Control System Development
    R. Parise and G. Is. Detorakis
    The Journal of Open Source Software, 7(73), 4306, DOI:https://doi.org/10.21105/joss.04306
    [Article]

  3. Randomized Self Organizing Map
    N. P. Rougier and G. Is. Detorakis
    Neural Computation, 33(8), 2021, DOI:https://doi.org/10.1162/neco_a_01406 [Article]

  4. Stability analysis of a neural field self-organizing map
    G. Detorakis, A. Chaillet and N.P. Rougier
    The Journal of Mathematical Neuroscience, 10(20), 2020, DOI:https://doi.org/10.1186/s13408-020-00097-6
    [Article]

  5. GAIM: A C++ library for Genetic Algorithms and Island Models
    G. Detorakis, A. Burton
    The Journal of Open Source Software, 4(44), 1839, 2019, DOI:https://doi.org/10.21105/joss.01839
    [Article]

  6. Memory-efficient Synaptic Connectivity for Spike-Timing-Dependent Plasticity
    B. U. Pedroni, S. Joshi, S. Deiss, S. Sheik, G. Detorakis, S. Paul, C. Augustine, E. O. Neftci, G. Cauwenberghs
    Frontiers in Neuroscience, DOI: https://doi.org/10.3389/fnins.2019.00357
    [Article]

  7. Contrastive Hebbian Learning with Random Feedback Weights
    G. Detorakis, T. Bartley, E. Neftci
    Neural Networks 114, 2019, doi: https://doi.org/10.1016/j.neunet.2019.01.008
    [Article] [arXiv]

  8. Neural and Synaptic Array Transceiver: A Brain-Inspired Computing Framework for Embedded Learning
    G. Detorakis, S. Sheik, C. Augustine, S. Paul, B.U. Pedroni, N. Dutt, J. Krichmar, G. Cauwenberghs, E. Neftci
    Frontiers in Neuroscience, 2018
    [Article]

  9. Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines
    E. Neftci, S. Paul, C. Augustine, G. Detorakis
    Frontiers in Neuroscience 11, 2017, doi: https://doi.org/10.3389/fnins.2017.00324
    [Article]

  10. Robust stabilization of delayed neural fields with partial measurement and actuation
    A. Chaillet, G. Is. Detorakis, S. Palfi and S. Senova
    Automatica 83, 2017, doi: https://doi.org/10.1016/j.automatica.2017.05.011
    [Article]

  11. Closed-loop stimulation of a delayed neural fields model of parkinsonian STN-GPe network: a theoretical and computational study
    G. Is. Detorakis, A. Chaillet, S. Palfi and S. Senova
    Frontiers in Neuroscience 9(237), 2015, doi: https://doi.org/10.3389/fnins.2015.00237
    [Article]

  12. Structure of Receptive Fields in a Computational Model of Area 3b of Primary Sensory Cortex
    G. Is. Detorakis and N. P. Rougier
    Frontiers in Computational Neuroscience, 8, 2014, doi: https://doi.org/10.3389/fncom.2014.00076
    [Article]

  13. A Neural Field Model of the Somatosensory Cortex: Formation, Maintenance, and Reorganization of Ordered Topographic Maps
    G. Is. Detorakis and N.P. Rougier
    PLoS ONE 7(7):e40257, doi: https://doi.org/10.1371/journal.pone.0040257
    [Article]

Reproducible Science Articles (peer-reviewed)⌗

  1. Sustainable computational science: the ReScience initiative
    N.P. Rougier, K. Hinsen, F. Alexandre, T. Arildsen, L. Barba, F.C. Y. Benureau, C. Titus Brown, Pierre de Buyl, O. Caglayan, A.P. Davison, M.A. Delsuc, G. Detorakis, A.K. Diem, D. Drix, P. Enel, B. Girard, O. Guest, M.G. Hall, R.N. Henriques, X. Hinaut, K.S. Jaron, M. Khamassi, A. Klein, T. Manninen, P. Marchesi, D. McGlinn, C. Metzner, O.L. Petchey, H.E. Plesser, T. Poisot, K. Ram, Y. Ram, E. Roesch, C. Rossant, V. Rostami, A. Shifman, J. Stachelek, M. Stimberg, F. Stollmeier, F. Vaggi, G. Viejo, J. Vitay, A. Vostinar, R. Yurchak, T. Zito
    PeerJ Computer Science, 3, e142, 2017
    [Article]

  2. [Re] A Generalized Linear Integrate-And-Fire Neural Model Produces Diverse Spiking Behaviors
    G. Is. Detorakis
    The ReScience Journal, 2017, DOI: https://doi.org/10.5281/zenodo.1003214
    [Article]

  3. [Re] Multiple dynamical modes of thalamic relay neurons: rhythmic bursting and intermittent phase-locking
    G. Is. Detorakis
    The ReScience Journal, 2:1, 2016, DOI: https://doi.org/10.5281/zenodo.61697
    [Article]

International Conferences (peer-reviewed)⌗

  1. Inherent Weight Normalization in Stochastic Neural Networks
    G. Detorakis, S. Dutta, A. Khanna, M. Jerry, S. Datta, and E. Neftci
    33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada.
    [Article]

  2. A Recurrent Neural Network Based Model of Predictive Smooth Pursuit Eye Movement in Primates
    H. Kashyap, G. Detorakis, N. Dutt, J. Krichmar,and E. Neftci
    IJCNN 2018, Rio de Janeiro, Brazil.
    [Article]

  3. Incremental Stability of Spatiotemporal Delayed Dynamics and Application to Neural Fields
    G. Detorakis and A. Chaillet
    IEEE CDC 2017, Melbourne, Australia.
    [Article] [HAL]

  4. Event-Driven Random Backpropagation: Enabling Neuromorphic Deep Learning Machines
    E. Neftci, C. Augustine, S. Paul, G. Detorakis,
    IEEE ISCAS 2017, Baltimore, MD, USA.
    [Article]

  5. Forward Table-Based Presynaptic Event-Triggered Spike-Timing-Dependent Plasticity
    B. U. Pedroni, S. Sheik, S. Joshi, G. Detorakis, S. Paul, C. Augustine, E. Neftci, G. Cauwenberghs,
    IEEE BioCAS 2016, Shanghai, China.
    [Article]

  6. SPySort: Neuronal Spike Sorting with Python
    C. Pouzat and G.Is. Detorakis,
    Euroscipy 2014, Cambridge, United Kingdom.
    [Article]

  7. Self-Organizing Dynamic Neural Fields
    N. P. Rougier and G. Is. Detorakis
    3rd International Conference on Cognitive Neurodynamics, Hokkaido, Japan, 2011.
    [Article] [pdf]

International Conferences⌗

  1. A neural network model of predictive smooth pursuit eye movement in primates
    H.J. Kashyap, G. Detorakis, N. Dutt, J.L. Krichmar, E. Neftci
    SfN, San Diego (CA, USA)

  2. Random Contrastive Hebbian Learning as a Biologically Plausible Learning Scheme
    G. Detorakis, T. Bartley, and E. Neftci
    OCNS, Seattle (WA, USA), 2018

  3. Three-factor embedded learning on neuromorphic systems
    G. Detorakis, T. Bartley, R. Parise, S. Sheik, C. Augustine, S. Paul, B. U. Pedroni, N. Dutt, J.Krichmar, G. Cauwenberghs, and E. Neftci
    COSYNE, Denver (CO, USA), 2018

  4. Embedded Learning on Neuromorphic Systems: Towards a Unified Computing Framework
    G. Detorakis, T. Bartley, R. Parise, S. Sheik, C. Augustine, S. Paul, B. Pedroni, N. Dutt, J. Krichmar, G. Cauwenberghs and E. Neftci
    NICE, Portland (OR, USA), 2018

  5. Embedded learning on neuromorphic systems: Towards a unified computing framework
    G. Detorakis, T. Bartley, R. Parise, C. Augustine, S. Paul, E. Neftci
    IEED ICCAD HALO Workshop, Irvine (CA, USA), 2017

  6. NeuroLachesis: A Neuromorphic Framework
    G. Detorakis, D. Barsever, E. Neftci
    Scipy 2017, Austin (TX, USA)

  7. Robust stabilization of delayed neural fields by proportional feedback using input-to-state stability and small gain theorem
    A. Chaillet, G. Is. Detorakis, S. Palfi, S. Senova
    ICMNS 2016, Juan-les-Pins, France

  8. Closed-loop disruption of oscillations in a targeted frequency band for a delayed neural field STN-GPe model
    G.Is. Detorakis and A. Chaillet
    FENS Featured Regional Meeting 2015, Thessaloniki, Greece

  9. Incremental stability of delayed neural fields: a unifying framework for endogenous and exogenous sources of pathological oscillations
    G.Is. Detorakis and A. Chaillet
    CNS, Prague, Czech Republic, 2015

  10. Closed-loop regulation of the activity of delayed neural fields with only partial measurement and stimulation
    G.Is. Detorakis and A. Chaillet
    ICMNS, Antibes - Juan les Pins, France, 2015

  11. A global stability analysis for delayed neural fields
    G.Is. Detorakis, A. Chaillet and I. Haidar
    BCCN 2014, Göttingen, Germany

  12. A computational view of the primary somatosensory cortex G.Is. Detorakis and N.P. Rougier
    CNS Annual Meeting, Paris, France, 2013

  13. Neural Fields and Cortical Plasticity
    G.Is. Detorakis and N.P. Rougier
    BCCN, Freiburg, Germany, 2011

Minor Conferences⌗

  1. Embedded learning on neuromorphic systems: Towards a unified computing framework
    G. Detorakis, C. Augustine, S. Paul, E. Neftci
    24th Joint Symposium on Neural Computation, San Diego(CA, USA), 2017

  2. On the relation between neuronal size and extracellular spike amplitude and its consequence on extracellular recordings interpretation
    C. Pouzat and G. Is. Detorakis
    MathStatNeuro Workshop, Nice(France), 2015

  3. SPySort
    C. Pouzat and G. Is. Detorakis
    GDR Multielectrode systems and signal processing for Neuroscience, Gif-sur-Yvette(France), 2014

  4. Skin Topographic Maps in SI
    G.Is. Detorakis and N.P. Rougier
    Progress in Neural Field Theory, Reading, United Kingdom, 2012

  5. Skin Topographic Maps in SI
    G.Is. Detorakis and N.P. Rougier
    Workshop on Cognitive and Dynamics in Neural Systems: Mathematical and Computational Modeling (CONAS), Lyon, France, 2012

Book Chapters⌗

  1. ISS-stabilization of delayed neural fields by small-gain arguments
    A. Chaillet, G. Is. Detorakis, S. Palfi, and S. Senova
    Delays and Interconnections: Methodology, Algorithms and Applications, Springer, 2019
  1. Optogenetics to unravel the mechanisms of Parkinsonian symptoms and to optimize deep brain stimulation
    A. Chaillet, D. Da Silva, G. Detorakis, C. Pouzat, S. Senova
    ERCIM News, Special issue on cyber-physical systems, number 97, April 2014