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Recent advances in behavioural and computational neuroscience, in cognitive robotics, and in the hardware implementation of large-scale neural networks, provide the opportunity for an accelerated understanding of brain functions and for the design of interactive robotic systems based on brain-inspired control systems. The BABEL project aims at advancing the understanding of neural and behavioural mechanisms in word learning, the validation of these principles in neuroanatomically grounded models, and real-time implementations of brain language models within the SpiNNaker neuromorphic architecture that will support comparisons with neuroimaging experiments. The scientific hypotheses and cortical language model will be validated by implementing a model of embodied active language learning on the humanoid robot iCub.

  • (i) To develop a theory of language learning at the neural circuit level and to build a neurocomputational model of the language cortex.
  • (ii) To carry out novel MEG, EEG and fMRI experiments to identify the neural correlates and mechanisms of the learning of words for objects and actions and design large-scale neuroanatomical models.
  • (iii) To extend the SpiNNaker technology to implement a scaled-up real-time model of the language cortex using more realistic spiking activity, and develop interfaces to connect it to the iCub robot.
  • (iv) To translationally apply these neuro-anatomical models and SpiNNaker system as controllers for language and action learning experiments with the humanoid robot iCub.





crnsno manchester university nofree university berlin

speaker name


Plymouth University and
Freie Universitate Berlin

Research Fellow;
Brain imaging, computational neuroscience

speaker name


Plymouth University

Research Fellow;
Spiking neural networks

speaker name


Plymouth University

Research Fellow;
robotic experiments

speaker name


Plymouth University

PhD Candidate;

speaker name

Rosario Tomasello

Plymouth University and Freie Universitate Berlin

Research Assistant;
Computational Neuroscience Modelling;


  • Giorgio Metta, University of Genoa and IIT, Italy
  • Luciano Fadiga, University of Ferrara and IIT, Italy
  • Linda Smith, Indiana University, USA




  • Kick-Off Meeting: Plymouth, 17-18 September 2012
  • Consortium Meeting 2: Berlin, 25-26 February 2013
  • Consortium Meeting 3: Manchester, 5-6 September 2013
  • Consortium Meeting 4: Manchester, 6-7 March 2014
  • Consortium Meeting 5: Berlin, 8-9 September 2014
  • Consortium Meeting 6: Plymouth, 2-3 March 2015
  • SpiNNaker Workshop: Manchester, November 2012
  • Researchers' Workshop: Plymouth, 17 June 2013
  • Researchers' Workshop: Plymouth, 15-16 January 2014
  • SpiNNaker Workshop: Manchester, 21-28 April 2014
  • Capocaccia Neuromorphic Engineering Workshop, Sardinia, 28 April-10th May 2014

The final project workshop will be in Manchester, on 7 October 2016. The BABEL Workshop on large-scale brain models for embodied language on robots using SpiNNaker will see talks from the project partners, as well as from invited speakers. Call for Participation here





The iCub

The robotic experiments will be based on the iCub humanoid robot platform available at the Plymouth lab. The iCub is an open source platform for developmental robotics (Metta et al. 2010), based on a child-like morphology, with 53 degrees of freedom. The iCub will be used for language comprehension experiments, using the speech recognition software and artificial vision processing routines previously used by the Plymouth team (Morse et al. 2010; Tikhanoff et al. 2011). These tools are currently integrated in the Aquila software, linked to the YARP software interface for the robot hardware.


The neuromorphic SpiNNaker system employs a lightweight address-event representation (AER) packet-switched communication system to allow up to a million ARM processors to cooperate in real-time implementations of point-neuron models. 2-processor SpiNNaker test chips were fabricated in 2009 and support models of up to a few thousand neurons. An advanced 18-processor SpiNNaker chip was developed in 2011. This machine development is supported under the EPSRC BIMPA grant EP/G015740/1. These machines provide the hardware platform for the work proposed here. In addition, BIMPA will deliver software systems supporting various neuron (e.g. Izhikevich model) and synapse (STDP, NMDA) models, mapping large-scale networks (using PyNN) onto the machine’s resources, thus providing a generic platform for real-time neural models.


Media files will be made available here during the project.


Open source software will be added to the icub.org repository and linked here.




  • Garagnani M. and Pulvermüller, F. (2013). Neuronal correlates of decisions to speak and act: spontaneous emergence and dynamic topographies in a computational model of frontal and temporal areas. Brain and Language, 127(1), 75-85. doi 10.1016/j.bandl.2013.02.001
  • Pezzulo G., Barsalou L.W., Cangelosi A., Fischer M.H., McRae K., Spivey M. (2013). Computational grounded cognition: A new alliance between grounded cognition and computational modelling. Frontiers in Psychology, 6(612), 1-11. doi 10.3389/fpsyg.2012.00612
  • Pulvermüller, F. (2013). How neurons make meaning: brain mechanisms for embodied and abstract-symbolic semantics.Trends in Cognitive Sciences, 17(9). doi 10.1016/j.tics.2013.06.004.
  • Zhong J., Cangelosi A., Wermter W. (2013). Towards a self-organizing pre-symbolic neural model representing sensorimotor primitives. Frontiers in Behavioral Neuroscience, 8, 22. doi 10.3389/fnbeh.2014.00022
  • Pulvermüller, F. (2013). Semantic embodiment, disembodiment or misembodiment? In search of meaning in modules and neuron circuits.Brain and Language, 127(1), 86-103. doi 10.1016/j.bandl.2013.05.015.
  • Pulvermüller, F. (2014). The syntax of action.Trends in Cognitive Sciences, 18(5), 219-220. doi 10.1016/j.tics.2014.01.001.
  • Pulvermüller, F., Garagnani, M. and Wennekers, T. (2014). Thinking in circuits: toward neurobiological explanation in cognitive neuroscience. Biol Cybern., 127(1), 75-85. doi 10.1007/s00422-014-0603-9.
  • Pulvermüller, F. and Garagnani, M. (2014). From sensorimotor learning to memory cells in prefrontal and temporal association cortex: A neurocomputational study of disembodiment. Cortex, 51, 1-21. doi 10.1016/j.cortex.2014.02.015.
  • Pulvermüller, F., Kiff, J. and Shtyrov, Y. (2013). Can language-action links explain language laterality?: An ERP study of perceptual and articulatory learning of novel pseudowords. Cortex, 48, 871-881. doi 10.1016/j.cortex.2011.02.006.
  • Pulvermüller, F., Moseley, R.L., Egorova, N., Shebani, Z. and Boulenger, V. (2014). Motor cognition–motor semantics: Action perception theory of cognition and communication. Neuropsychologia, 55, 71-84. doi 10.1016/j.neuropsychologia.2013.12.002.
  • Rumbell, T., Denham, S. L., Wennekers, T. (2013). A Spiking Self-Organizing Map Combining STDP, Oscillations and Continuous Learning. IEEE Transactions on Neural Networks and Learning Systems, 25(5), 894-907. doi 10.1109/TNNLS.2013.2283140
  • Smith, A. M. C., Yang, C., Ma, H., Culverhouse. P., Cangelosi, A. and Burdet, E. (2015). Novel Hybrid Adaptive Controller for Manipulation in Complex Perturbation Environments, Plos ONE. doi 10.1371/journal.pone.0129281
  • Golosio B and Cangelosi A. (2015). A cognitive neural architecture able to learn and communicate through natural language. PLoS ONE, 10(11). doi 10.1371/journal.pone.0140866
  • Wang X., Yang C., Ju Z., Ma H. and Fu M. (2016). Robot manipulator self-identification for surrounding obstacle detection. Multimedia, Tools and Application. doi 10.1007/s11042-016-3275-8. Pdf available here
  • Conti D., Di Nuovo S., Cangelosi A., Di Nuovo A. (2016). Lateral specialization in unilateral spatial neglect: a cognitive robotics model. Cognitive Processing -- International Quarterly of Cognitive Science. doi 10.1007/s10339-016-0761-x. Pdf available here
  • Liang, P., Yang, C., Wang, N., & Li, R. A Discrete Time Algorithm For Stiffness Extraction From sEMG and Its Application in Anti-disturbance Teleoperation (2016). Discrete Dynamics in Nature and Society. doi 10.1155/2016/6897030.
  • Yang, C., Wang, X., Cheng, L., & Ma, H. Neural-Learning-Based Telerobot Control With Guaranteed Performance (2016). IEEE Transactions on Cybernetics. doi 10.1109/TCYB.2016.2573837.
  • Tomasello R., Garagnani M., Wennekers T., Pulvermueller F. (2016). Brain connections of words, perceptions and actions: A neurobiological model of spatio-temporal semantic activation in the human cortex. Neuropsicologia. doi 10.1016/j.neuropsychologia.2016.07.004.
  • Stramandinoli F., Marocco D., Cangelosi A. (2017). Making sense of words: A robotic model for language abstraction. Autonomous Robots. doi 10.1007/s10514-016-9587-8.
  • Garagnani M., Lucchese G., Tomasello R., Wennekers T., Pulvermueller F. (2017). A Spiking Neurocomputational Model of High-Frequency Oscillatory Brain Responses to Words and Pseudowords. Frontiers in Computational Neuroscience. doi 10.3389/fncom.2016.00145.
  • Fletcher J.M., Wennekers T. (2017). From Structure to Activity: Using Centrality Measures to Predict Neuronal Activity. International Journal of Neural Systems. doi 10.1142/S0129065717500137.
  • Adams, S.V., Rast, A.D., Patterson, C., Galluppi, F., Brohan, K., Perez-Carrasco, J-A., Wennekers, T., Furber, S. and Cangelosi, A. (2014). Towards Real-World Neurorobotics: Integrated Neuromorphic Visual Attention. Accepted for publication and oral presentation in the 21st International Conference on Neural Information Processing (ICONIP2014), 3-6 November, Malaysia. Pre-print available here
  • Adams, S.V., Garagnani, M., Wennekers, T., Pulvermüller, F. and Cangelosi, A. (2014) Learning Visual-Motor Cell Assemblies for the iCub Robot using a Neuroanatomically grounded Neural Network. Accepted for publication and oral presentation in the IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind and Brain (SSCI-CCMB 2014), 9-12 December, Orlando, Florida. Pre-print available here
  • Klein, M., Cangelosi, A. and Wennekers, T. (2014). Learning bidirectional connections between areas with standard spike-timing-dependent plasticity. Proceedings of NCPW 2014. World Scientific. Pre-print available here
  • Rast, A. D., Stokes, A. B., Davies, S., Adams, S. V., Akolkar, H., Lester, D. R. and Furber, S. (2015). Transport-Independent Protocols for Universal AER Communications. 22nd International Conference on Neural Information Processing (ICONIP2015) (pp. 675-684). Springer International Publishing. Pre-print available here
  • De Azambuja R., Cangelosi A., Adams S. (2016). Diverse, noisy and parallel: A new spiking neural network Approach for humanoid robot control. Proceedings of IJCNN16 International Joint Conference on Neural Networks, Vancouver, IEEE Press Pre-print available here
  • Mohamed A., Yang C., Cangelosi A. (2016). Stereo Vision based Object Tracking Control for a Movable Robot Head. Proceedings of ICONS 2016: 4th IFAC International Conference on Intelligent Control and Automation Sciences, Reims, France Pre-print available here
  • Cangelosi A., Morse A., Di Nuovo A., Rucinski M., Stramandinoli F., Marocco M., De La Cruz V., Fischer K. (2016). Embodied language and number learning in developmental robots. In M.H. Fischer and Y. Coello (Eds.), Foundations of Embodied Cognition. Taylor & Francis Press Pre-print available here
  • Yang C., Liang P., Ajoudani A., Li Z., Bicchi A. (2016). Development of a Robotic Teaching Interface for Human to Human Skill Transfer. Proceedings of IROS2016 International Conference on Intelligent Robotics, Daejeon, IEEE Press Pre-print available here
  • De Azambuja R., Klein F., Stoelen M., Adams S., Cangelosi A. (2016). Graceful degradation under noise on brain inspired robot controllers. Proceedings of 23rd International Conference on Neural Information Processing (ICONIP 2016). Kyoto, October 2016 Pre-print available here



The project staff will collaborate with the industry advisors to support the impact and knowledge transfer of the BABEL research results and technologies to R&D areas in robotics, automation and microeletronics.

The companies and institutions directly involved in the BABEL impact strategy, through the role of indutry advisors of their senior staff, are HONDA, TSMUK, ARM and Cogniscience. In addition, the collaboration with the IIT will focus on open source developments of the BABEL results.



HONDA RESEARCH INSTITUTE EUROPE (Advisor Edgar Koerner, President of HRI EU). This is one of three fundamental research institutes of Honda worldwide. In Europe, the Instute aims for a better understanding and successful application of intelligent systems in an engineering and a business context, with specific focus in (i) Brain-like Intelligence; (ii) Evolutionary and Learning Technology; (iii) Embodied Brain-like Intelligence. In BABEL the collaboration with HONDA will focus on the application of the project results and technology in the car industry and humanoid and mobility robotics.



TMSUK Japan (Advisors Yoichi Tamamoto, Chiefe Executive and Founder, and Junji Matsuo, European R&D Officer). This is one of the leading international companies in service robotics. TMSUK was established in 2000, in Fukuoka, Japan, and since then it has developed over 30 robot platforms for search and rescue, telecomms, medical/dentist training and care companions.Such platforms are sold to government agencies, private companies and reserach institutions. In BABEL the collaboration with TMSUK will focus on the application of the project results and technology in the service robotics industry.



ARM Ltd (Advisor Ian Phillips, Principal Staff Engineer). ARM Ltd. This is a UK company based in Cambridge, with ~£400m revenue and 2,000 employees world-wide. Known as the world’s leading supply of System-on-Chip Intellectual Property (SOC-IP), its 32-bit RISC CPU family powers more than 95% of the smart electronic products which pervade our lives today. In BABEL the collaboration with ARM will focus on the application of the project results and technology in microelectronics and neuromorphic engineering.



Cogniscience Ltd (Steve Furber, Founder). This is a University of Manchester spin-out company established to commercialize the IP arising from the SpiNNaker project. This company is positioned to supply SpiNNaker hardware to support any exploitation of the results of the BABEL project that require the use of SpiNNaker hardware.



IIT (Advisor Giorgio Metta, Director of iCub Facility). The Italian Institute of Technology aims to promote Italy's technological development and advanced education, consistent with national policies for scientific and technological development, with particular emphasis on robotics, neuroscience, biomedical technology and nanotechnology. In BABEL the collaboration with the IIT iCub Facility and the Department of Robotics, Brain and Cognitive Sciences will focus on the application of the project results and technology in open source for humanoid robotics.


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