The aim of the research line in Multiscale Brain Communication, within the CTNSC@UniFe, is twofold. On one side we are studying how the brain builds communicative and linguistic representations. On the other side we are designing new brain interfaces, specifically conceived for human use, to record and computationally decode neural signals. A particular focus of our line is on communication because we believe that many paralyzing pathologies require, at first, the restoring of an efficient communicative flow between the patient and the environment.
To this purpose we are studying the way by which the brain processes and understands the communicative behaviors of other individuals in order to efficiently decode the brain signals related to communicative intentions, we are applying innovative and possibly biologically-compatible technologies to the problem of automatic speech and action recognition (Speech and Communication Team) and we are designing a new generation of brain electrodes characterized by reduced invasiveness, improved resolution and sensitivity (Neural Interfaces Team).
In summary, with a critical focus on translational methodologies (single unit recordings, Micro-ECoG, fMRI, EEG, TMS), our research goal is to advance knowledge on brain functioning to help building the next generation of brain-computer interfaces. The group research activities span from basic research to applied one along three main research lines:
- Design of long-term and stable neural-tissue interfaces
- Research on brain centers and circuits involved in action/speech understanding
- Research on new efficient methods for automatic speech recognition
Our laboratories host state-of-the-art facilities for motion capture, neurophysiology, histology, cell culture, material science, electrochemical and electrical characterization.
- Neuronavigated Transcranial Magnetic Stimulation, High density Electroencephalography, Eye-tracking, Optical Motion Tracking and ElectroMagnetic Articulography
- Tethered and wireless multichannel neural recording and stimulation, Neuron Tracing Fluorescence Microscopy, Histology Sectioning Microtome, Primary Cells Culture facilities
- Galvanostats/Potentiostats, Chemical Synthesis and Polymerization, High Resolution Optical Microscopy, LCR meter, Electrometer, Dual Source Meter
(D. Ricci, E. Maggiolini, E. Castagnola, S. De Faveri)
Information transmission and processing within the brain takes place by electro-chemical signaling. For this reason, one of the most efficient ways to access this information is to connect electrodes to the brain. Finding the most appropriate technology for building electrodes to be used for long term implants in humans is a challenging issue, as available devices still lack the required biocompatibility, efficacy and versatility, for both recording and stimulation.
Legend A) 128 channel epicortical microelectrode array; B) nanostructured gold electrode; C) biocompatible synthetic hydrogel encapsulated gold microsphere microelectrode; D) bio-hybrid intracortical microelectrode encapsulated in autologous cells from the host organism; E) somatosensory evoked potentials recorded using fibrin hydrogel coated PEDOT-CNT ECoG electrodes
The Neural Interfaces Team is devoted to the development and exploitation of novel neural interfacing technologies by employing a highly multidisciplinary approach including expertise in the field of material science, nanotechnology, electronic engineering, biology and neurophysiology and taking advantage of state-of-the-art facilities: chemical and electrochemical lab, electronic characterization lab, cells culture lab, histology lab, neurophysiology labs.
Specifically, we are designing soft and flexible intracortical and epicortical microelectrode arrays with reduced impedance, higher charge transfer capability and biocompatibility thanks to the use of nanocomposite high surface area coatings and hydrogel encapsulation. In parallel, we develop techniques for the bio-hybrid electrode integration in the brain tissue by using autologous cells derived from the host organism. The acute and long-term biocompatibility, recording and stimulation performance of the developed devices is tested in-house by performing neurophysiological tests followed by immunofluorescence techniques. The goal of the Neural Interfaces Team is to advance fundamental research in brain machine interface devices and translate such knowledge focusing on acute and chronic clinical applications.
(D’Ausilio, L. Badino, R. Viaro, B. Tia)
Social interaction plays a central role in shaping our cognitive capacities during child development and throughout our life. Successful interaction requires the ability to send and receive information across individuals. In a sense, individuals might be conceptualized as processing units embedded within a multi-agent complex system and specialized for the interpretation of specific social messages. This fundamental capacity, ultimately enabling the emergence of cognition, is based on the function of a specific neural circuit allowing the fast and accurate decoding of others’ verbal and non-verbal messages during interaction.
The Speech and Communication Team investigates these aspects by employing a highly multidisciplinary approach including expertise in the fields of neuroscience, psychology, computer science and engineering and using a mixture of cutting-edge neurophysiological (micro-electrocorticography, single unit recordings, micro-stimulation, electroencephalography and transcranial magnetic stimulation), behavioral (eye-tracking, body motion capture) and computational techniques (machine learning, multivariate analyses, nonlinear data analyses).
Image caption: A Electroencephalography (EEG); B: Wireless electromyography (EMG); C: Machine-learning papers; D: Transcranial Magnetic Stimulation (TMS)
Specifically, we investigate the brain mechanisms allowing us to understand and use verbal (Speech Perception Network) and non-verbal (Action Perception Network, Syntax of Action) communication in everyday life. In parallel, we design computational systems capable of human-like performance in understanding verbal (Automatic Speech Recognition) and non-verbal interactions (Non-verbal Sensorimotor Communication).
The goal of the Speech and Communication Team is to advance fundamental research on how the brain makes us capable of smooth social interactions and to design automatic brain-inspired systems that will allow natural human-machine interaction.
- Translational Neurophysiology on Humans – Miran Skrap - Neurochirurgia, Ospedale di Udine
- Ultraflexible electrode arrays - Guglielmo Fortunato – CNR-IMM - Roma
- Glassy carbon electrode arrays - Sam Kassegne - San Diego State University - USA
- Marmoset motor cortex mapping – Atsushi Iriki – RIKEN Brain Science Institute – Saitama – Japan
- Action perception and motor control - Thierry Pozzo – CTNSC@IIT and INSERM - U1093 Cognition, Action, and Sensorimotor Plasticity, Dijon, France
- Motor intention understanding - Cristina Becchio – RBCS@IIT and Università di Torino, Italy
- Broca’s area contribution to action Sequencing – Etienne Olivier – Université Catholique de Louvain, Belgium
- Neuroelectrical correlates of the action syntax - Daniela Sammler - Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- The shared syntax of action, music and language - Stefan Kölsch - University in Bergen, Norway
- Language and action system interactions - Thomas Bever – University of Arizona, USA
- Computational investigation of action primitives - Yiannis Aloimonos - University of Maryland, USA
- The syntax of action, objects affordances and language - Katerina Pastra - Cognitive Systems Research Institute and Institute for Language and Speech Processing, Athens, Greece
- Object affordances in humans and robots - Jose Santos-Victor - Instituto Superior Técnico, Institute of Systems and Robotics, Lisboa, Portugal
- Motor contribution to speech perception - Nuria Sebastian Galles, Universitat Pompeu Fabra, Barcelona, Spain
- The motor system in speech and language perception - Friedemann Pulvermüller - Institut für Deutsche und Niederländische Philologie, Berlin, Germany
- Automatic speech recognition for robotics- Giorgio Metta – iCub@IIT
- Articulatory automatic speech recognition and acoustic inversion – Raman Arora – Center for Language and Speech Processing, Johns Hopkins University
- Machine learning techniques for automatic speech recognition – Lorenzo Rosasco – Laboratory for Computational and Statistical Learning, MIT/IIT
- Goal-directed sensorimotor coordination in group interaction - Andrea Gaggioli and Giuseppe Riva – Università Cattolica di Milano and IRCCS Istituto Auxologico Italiano, Milano, Italy
- Sensorimotor signaling - Giovanni Pezzulo - Institute of Cognitive Sciences and Technologies (ISTC-CNR), Roma
- Recurrence quantification analyses of multi-agent behavior - Moreno Coco - University of Edinburgh, UK
- Sensorimotor entrainment to musical ensembles - Gualtiero Volpe and Antonio Camurri – University of Genova
- Complex social interaction in musical ensembles - Peter Keller - University of Western Sydney, Australia