Computational Neuroscience, Reservoir Computing, Language Acquisition & Songbirds

Quick outlook of my research

The best way to have the last updates about my research is to have look at the last batch of my preprints and papers on my HAL arxiv profile and my Google Scholar profile.

If you read only one paper of my work it should be this one. For a more general view, see the presentations slides about language processing with Reservoir Computing.

Who am I?

I am a Researcher at Inria in Bordeaux, France (started in February 2016). My research is at the "edge of chaos" of several fields: Computational Neuroscience, Bio-Inspired Machine Learning & Developmental Robotics. I am in the Mnemosyne team headed by Frédéric Alexandre, at the edge of 3 labs: Inria Bordeaux Sud-Ouest, LaBRI, Institute of Neurodegenerative Diseases (IMN).

My work mainly focus on Recurrent Neural Network modelling (especially to model prefrontal cortex), Language Acquisition (applied to Robotics) and exploration of brain codes of bird song syntax. For modelling, I mainly use Echo State Networks, which is part of the Reservoir Computing framework (here is an introduction to RC).

The common thread of my research aims at the exploration of the neural coding and the modelling of complex sequences processing, chunking, learning and production, for “syntax-based” sequences, and to apply these models to robotics (for future embodiment purposes). In particular, my artificial neural networks based models are were focused on dynamics of prefrontal cortex and basal ganglia.

In these models, I am interested in human (and robot) grammar learning and acquisition as well as the categorization of monkey motor action sequences. Besides, I worked on experimental protocols and on the analysis of neural codings of canary song. In order to better understand human language mechanisms, canary song is particularly interesting because it is very variable, it has a complex “syntax” and continues to evolve even during adult life.

Short bio

After obtaining my Ph.D. at the University of Lyon in January 2013 at the Stem Cell and Brain Research Institute (SBRI / INSERM 846) under the supervision of Peter Ford Dominey, I did post-doctorate internships at the University of Hamburg in 2013 and 2015 (Marie Curie Individual Fellowship) in the team of Stefan Wermter, and a post-doctorate internship (CNRS) in 2014 at the Paris-Saclay Neuroscience Institute (NeuroPSI) in the team of Catherine Del Negro and Jean-Marc Edeline.

Some news!

(sorry, not up to date! See my HAL arxiv profile and my Google Scholar profile instead.)

• March 2022

Presentation of our library ReservoirPy at Sorbonne Center for Artificial Intelligence (SCAI) : https://sed-paris.gitlabpages.inria.fr/ai-community/dev_talks/2022-03-22/

• February 2022

Presentation of our library ReservoirPy at Dataquitaine2022: https://www.dataquitaine.com/2022/conference-ia-ai-datascience-ro-bordeaux-2022#calendar

• January 2022

New major release of ReservoirPy! https://github.com/reservoirpy/reservoirpy

• October 2020

Nov 2/3: I am organising the SMILES workshop on Sensorimotor, Language and Embodiment of Symbols! It is a satellite online workshop of ICDL 2020.

• Nov 2018 to Sept 2020

Several papers out! Please check my Google Scholar for updated info.

• October 2018

Summary presentation of my research on language processing with Reservoir Computing and application to Human-Robot Interaction.

New papers from this summer:

• Strock, A., Rougier, N., & Hinaut, X. (2018). A Simple Reservoir Model of Working Memory with Real Values. Prooc. of IJCNN, Brasil, July 2018.

– Code: https://github.com/anthony-strock/ijcnn2018

• Hinaut, X. (2018). Which Input Abstraction is Better for a Robot Syntax Acquisition Model? Phonemes, Words or Grammatical Constructions? In 2018 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob).

– Supp. Mat. & Code: https://github.com/neuronalX/Hinaut2018_icdl-epirob

• Pagliarini, S., Hinaut, X., Leblois, A. (2018) A Bio-Inspired Model towards Vocal Gesture Learning in Songbird. In 2018 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob).

• December 2017

Organisation of a hackathon on Artificial Intelligence and Cognitive Science within the MindLaBDX association, in Bordeaux, France

• October 2017

Invited talk at "The role of the basal ganglia in the interaction between language and other cognitive functions" workshop at ENS Ulm, Paris, France.

• March 2017

Looking for a PhD candidate for SONNET project

• October 2016

Invited talk at IROS Workshop on Machine Learning Methods for High-Level Cognitive Capabilities in Robotics workshop.

• September 2016

Paper accepted at ICDL-epirob 2016 conference.

• August 2016

Paper accepted in RO-MAN 2016 conference: Using Natural Language Feedback in a Neuro-inspired Integrated Multimodal Robotic Architecture ResearchGate

• April 2016

Two papers accepted at ESANN 2016 conference:

Semantic Role Labelling for Robot Instructions using Echo State Networks ResearchGate

Activity recognition with echo state networks using 3D body joints and objects category ResearchGate

• February 2016

Starting a Researcher position ("Chargé de Recherche 2^ème classe", CR2) at INRIA (French Institute for Research in Computer Science and Automation) in the team Mnemosyne. The team is active in several labs: INRIA, IMN and LaBRI.

• December 2015

New workshop NIPS paper on a Bilingual Recurrent Neural Network learning English and French at the same time:

X. Hinaut, J. Twiefel, M. Petit, P.F. Dominey, S. Wermter (2015) A Recurrent Neural Network for Multiple Language Acquisition: Starting with English and French. Workshop on "Cognitive Computation: Integrating Neural and Symbolic Approaches", CoCo @ NIPS 2015. PDF

• September 2015

New journal paper on a the Production of sentences in English and Japanese with a Recurrent Neural Network:

X. Hinaut, Lance, C. Drouin, M. Petit, G. Pointeau, P.F. Dominey (2015) Cortico-Striatal Response Selection in Sentence Production: Insights from neural network simulation with Reservoir Computing. Brain and Language, vol. 150, Nov. 2015, pp. 54–68. doi:10.1016/j.bandl.2015.08.002 HTML (FREE until mid-October 2015)

• July 2015

NEW! IJCAI 2015 video:

"Humanoidly Speaking": How the Nao humanoid robot can learn the name of objects and interact with them through common speech.

IJCAI 2015 video competition link.

Software: Take a look at "Syntactic Reservoir Model" and "DOCKS" on the WTM team sofware webpage to download and try the source code to make the same experiment.