Computational intelligence and Neuroscience

Hybrid Neuro-Symbolic Systems

The research activities are mainly concerned with Artificial Intelligence, Artificial Neural Networks, Neuro-Symbolic Hybrid Systems, with extensive applications in Video and Image processing, Behaviour-Based Robotics, Classification and Clustering. Furthermore, new and interesting theoretical aspects of Weightless Neural System are under investigation.

     

Referente:    Massimo De Gregorio

Collaborazioni:  F.M.G. França, COPPE – Universidade Federal do Rio de Janeiro
P.M.V. Lima, PPGI – Universidade Federal do Rio de Janeiro
S. Rossi, DIETI – Università degli Studi di Napoli “Federico II”
I. Aleksander, Department of Electrical and Electronic Engineering, Imperial College of London

Pubblicazioni: 2015-2014

  1. De Gregorio, M. Giordano, the extended version of Memory Transfer in DRASiW-like Systems has been accepted for publication in a special issue of the journal Neurocomputing, Elsevier.
  2. De Gregorio, M. Giordano, Apoptosis and Neurogenesis in DRASiW-like systems, to appear in Neurocomputing, Elsevier, 14 pages
  3. De Gregorio, M. Giordano, S. Rossi, M. Staffa, Experimenting WNN Support in Object Tracking Systems, to appear in Neurocomputing, Elsevier. 12 pages.
  4. De Gregorio, M. Giordano, Exploiting “mental” images in artificial neural network computation, to appear in Bringing Math to Life, Springer, 10 pages.
  5. De Gregorio, M. Giordano, Memory Transfer in DRASiW–like Systems, 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2015, Bruges, Belgium, 22-24 April 2015, pp. 25-30.
  6. De Gregorio, M. Giordano, S. Rossi, B. Siciliano, M. Staffa, Segmentation Performance in Tracking Deformable Objects Via WNNs, in proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2015, 26-30 May 2015, Seattle, WA, USA, 7 pages.
  7. De Gregorio, M. Giordano, A. Rossi, S. Rossi, M. Staffa, A. Tamburro, C. Vellucci, User Tracking in HRI Applications with the Human-in-the-loop, in proceedings of the 10th ACM/IEEE International Conference on Human-Robot Interaction, HRI 2015, Portland, OR, USA, 2-5 March 2015.
  8. De Gregorio, “Mental” images as Meta-Data?, Bringing Math To Life, BMTF 2014, 19-21 October 2014, Naples, Italy, Keynote.
  9. De Gregorio, W.R. de Oliveira, F.M.G. França, P.M.V. Lima, Advances on Weightless Neural Systems, 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning ESANN 2014, Bruges, Belgium, 23-25 April 2014, pp. 497-504.
  10. De Gregorio, M. Giordano, S. Rossi, M. Staffa, Can you follow that guy?, 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2014, Bruges, Belgium, 23-25 April 2014, pp. 511-516.
  11. De Gregorio, M. Giordano, Change Detection with Weightless Neural Networks, in proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPR 2014, 23-28 June 2014, Columbus, OH, USA, pp. 409-413.
  12. De Gregorio, M. Giordano, S. Rossi, B. Siciliano, M. Staffa, Tracking deformable objects with WISARD networks, INNOROBO 2014, Lyon, France, 4 pages.
  13. De Gregorio, M. Giordano, CwisarDH: a Change Detection method in Computer Vision and Video Processing based on Weightless Neural Networks, registered software, 2014.

Semantic Multimedia and Cognitive Multimodal Systems

The activities are focused on natural language processing, semantic multimedia and multimodal systems, text mining and knowledge extraction. In particular, we develop methods and techniques to extract semantic information from texts and, to realize multimodal interactive systems in particular in natural language. The main application domain are: Cognitive modelling for the fruition of Cultural Heritage, and development of audio-visual by Semantic Multimedia Mashups

               

Referente:       Francesco Mele

Antonio Calabrese, Istituto di Scienze Applicate e Sistemi Intelligenti del CNR; Oliviero Talamo, Istituto di Scienze Applicate e Sistemi Intelligenti del CNR;

Antonio Sorgente, Istituto di Scienze Applicate e Sistemi Intelligenti del CNR; Gianluca Coda, Istituto di Scienze Applicate e Sistemi Intelligenti del CNR;

Luigi Seraponte, Istituto di Scienze Applicate e Sistemi Intelligenti del CNR; Paolo Vanacore , Istituto di Scienze Applicate e Sistemi Intelligenti del CNR.

Collaborazioni:  Francesco Cutugno, DIETI – Università degli Studi di Napoli “Federico II”; Antonio Origlia,  DIETI – Università degli Studi di Napoli “Federico II”

Pubblicazioni:

  1. Sorgente, A. Calabrese, G. Coda, P. Vanacore, F. Mele, Annotations by Complex Events to build Dialogue on Cultural Stories, “Artificial Intelligence for Cultural Heritage”, Workshop of the XIII AI*IA Symposium on Artificial Intelligence, Pisa, 2014
  2. Sorgente, G. Vettigli and F. Mele, An Italian Corpus for Aspect Based Sentiment Analysis of Movie Reviews, in Proceedings of CLiC-it 2014, The first Italian Computational Linguistics Conference, Pisa, 2014
  3. Vettigli, A. Sorgente, F.Mele, Extracting cause-effect relations in Natural Language Text, CLIN24- Computational Linguistics in The Netherlands, Leiden, 2014
  4. Bordoni , L. Ardissono , J. A. Barceló , A. Chella , M. de Gemmis, C. Gena , L. Iaquinta, P. Lops, F. Mele, C. Musto, F. Narducci, G. Semeraro, A. Sorgente, “ The contribution of AI to enhance understanding of Cultural Heritage”, Rivista Intelligenza Artificiale, IOS Press n.7 (2013) pp.101-112.
  5. Sorgente, N. Brancati, C. Giannone, F. M. Zanzotto, F. Mele, and R. Basili, Chatting to personalize and plan cultural itineraries,” in UMAP 2013 Extended Proceedings, Vol. 997  CEUR Workshop CEUR-WS.org, Rome, Italy, June 10-14, 2013
  6. Sorgente, G. Vettigli, F. Mele, Automatic extraction of cause-effect relations in natural language text. In Proceedings of the 7th International Workshop on Information Filtering (DART), Vol. 1109 CEUR Workshop CEUR-WS.org, 37-48, Turin, Italy, December 6, 2013
  7. Mele, A. Sorgente, OntoTimeFL – a formalism for temporal annotation and reasoning for Natural Language Text.In Lai, C., Semeraro, G., Vargiu, E., eds.: New Challenges in Distributed Information Filtering and Retrieval. Vol. 439 of Studies in Computational Intelligence, Springer Berlin Heidelberg 151-170, 2013
  8. Mele F., Sorgente A., Semantic mash-ups of multimedia cultural stories, Intelligenza Artificiale Journal IOS Press Issue Volume 6, Number 1 / 2012 pag. 19-40
  9. Mele F., Sorgente A., The temporal representation and reasoning of complex events, 26-esimo Convegno Italiano di Logica Computazionale, Pescara 31 Agosto – 2 Settembre 2011.
  • Mele, A.  Sorgente,  and  G:  Vettigli,  Artifact  as Species – A Formal Approach of the Evolutionary Design,  In Proceedings of the 3rd International Conference on Agents and Artificial Intelligence (ICAART), pp. 655-658, 2011
  • Mele F., Sorgente A., Vettigli G., Designing and Building Multimedia Cultural Stories Using Concepts of Film Theories and Logic Programming, AAAI Fall Symposium on Cognitive and Metacognitive Educational Systems, Arlington (USA), 11-13 Novembre 2010

Experimental and Computational Neuroscience

We study the neuronal activity from the synaptic function to biologically plausible neural networks by using experimental (electrophysiological) and computational techniques (computational models). The activity is carried by studying the function of the single neuron by electrophysiological techniques like patch-clamp and intra and extracellular recordings in single cell and in slices. In addition we model the synaptic activity and its integration on the dendrites and on the neuron.

Referente:          Vito di Maio

Collaborazioni:  Silvia Santillo, Istituto di Scienze Applicate e Sistemi Intelligenti del CNR.

Francesco Ventriglia, Istituto di Scienze Applicate e Sistemi Intelligenti del CNR; Petr Lansky, Istituto di Fisiologia dell’Accademia delle Scienze della Repubblica Ceca.

Pubblicazioni:

  1. Bartesaghi, V. Di Maio, T. Gessi, S. Marchionni (1998). Topographic organization of the dorsal hippocampal commissure. European Journal of Neuroscience, (suppl) 10: 19.21.
  2. Ventriglia, V. Di Maio (2000). A Brownian simulation model of glutamate synaptic diffusion in the femto-seconds time scale. Biological Cybernetics 83: 93-109.
  3. Ventriglia, V. Di Maio (2000). A Brownian model of glutamate diffusion in excitatoory synapses of hippocampus. Biosystems 58: 67-74.
  4. Ventriglia, V. Di Maio (2002). Stochastic fluctuation of the synaptic function. Biosystems 67: 287-294.
  5. Ventriglia, V. Di Maio (2003). Synaptic fusion pore parameters and AMPA recpetors activation investigated by Brownian simulation of glutamate diffusion. Biological Cybernetics 88: 201-209.
  6. Di Maio, F. Marciano (2003). Automatic classification of neural spike activity: an application of minimum distance classifiers. Cybernetics and Systems 34: 173-192.
  7. Rodriguez, P. Lansky, V. Di Maio (2003). Vesicular mechanisms and estimates of firing probability in a network of spiking neurons Physica D 181: 132-145.
  8. Ventriglia, V. Di Maio (2003). Stochastic fluctuations of the quantal EPSC amplitude in computer simulated excitatory sinapses of hippocampus. Biosystems 71: 195-204.
  9. Di Maio, P. Lansky P., R. Rodriguez (2004). Different types of noise in leaky-integrate and fire model of neuronal dynamics with discrete periodical input. General Physiology and Biophysics 23:21-28.
  10. Bartesaghi, V. Di Maio, T. Gessi (2005). Topographic distribution of the medial entorhinal cortex by dorsal psalterium projections. Journal Comparative Neurology 487:283-299.
  • Ventriglia, V. Di Maio (2005) Neural code and irregular spike trains. In: Brain Vision and Artificial Intelligence, (De Gregorio, Di Maio, Frucci and Musio Eds), Lectur Notes in Computer Science pp 89-98, Springer.
  1. Ventriglia, V. Di Maio (2006) Multisynaptic activity in a pyramidal neuron model and neural code. Biosystems 86: 18-26.
  2. Di Maio (2007) Excitatory synaptic interaction on dendritic tree. In: Brain, Vision and Arificial Intelligence 2007, (F. Mele, G. Ramella, S. Santillo, F. Ventriglia Eds), Lectur Notes in Computer Science, pp 388-397, Springer.
  3. Di Maio (2008) Regulation of information passing by synaptic transmission: a short review. Brain Research 1225:26-38.
  4. Di Maio and Carlo Musio (2008) Brain and Vision, Editorial. Brain Research 1225:1-2.
  5. Ventriglia and V. Di Maio (2013) Effect of AMPARs trafficking and Glutamate-Receptor binding probability on stocastic variability of EPSC. Biosystems 112: 298–304
  • Ventriglia and V. Di Maio (2013) Glutamate-AMPA interaction in a model of synaptic transmission. Brain Research 1536:168-176.
  • Santillo, A. Schiano-Moriello and V. Di Maio (2014) Electrophysiological variability in the SH-SY5Y cellular line. General Physiology and Biophysics 33:121-129.
  1. Di Maio, F. Ventriglia and S. Santillo (2015) A Model of Dopamine Modulated Glutamatergic Synapse. Biosystems, (in press).