[visionlist] PhD Fellowhisps: Motor Learning, Rehabilitation Robotics, Brain Machine Interface

Giulio Sandini giulio.sandini at iit.it
Mon Aug 27 16:08:58 GMT 2007

The Robotics, Brain and Cognitive Sciences (RBCS) Department of the Italian
Institute of Technology (IIT) is offering fellowships in the areas of HUMAN
INTERFACE. These fellowships are part of a multidisciplinary project aiming
at 'reading' the brain to understand and extract motor signals which may be
used to control an artificial limb. 


These two main streams of research will be developed jointly at RBCS
department of IIT under the responsibility of Giulio Sandini and two groups
of scientists coordinated by Thierry Pozzo (motor learning) Luciano Fadiga
(Brain Machine Interface) and including: Lorenzo Masia, Stefano Panzeri,
Alessandro Vato, Gytis Baranauskas, Davide Ricci and Franco Bertora, Marco


These projects addresse topics such as the design of microelectrode and
microelectronics devices for chronic in-vivo recording, electrophysiological
and brain signals recording, investigation of the coding/decoding issue,
functional identification of brain motor/premotor areas, and direct
connection to artificial actuators.


More specifically the nine  research themes proposed are (short abstract and
scientist in charge are included at the end of the message):

Research Stream: Brain Machine Interface

.         Theme 5.8: The Neural Interface Problem: Enhanced in-vivo
electrodes by nanomaterial coatings 

.         Theme 5.9: The Signal Treatment Problem 

.         Theme 5.10: The Brain Signal Decoding Problem

.         Theme 5.11: The Movements vs. Actions Problem

.         Theme 5.12: The Neurophysiology of the Human Brain 

.         Theme 5.13: The Role of Sensory Feedback in Brain Machine

.         Theme 5.14: Machinery for Functional Brain Analysis 

Research Stream: Human Behavior and Biomechanics

.         Theme 5.15: Learning by Observation in Humans and Robots (two
positions offered)

.         Theme 5.16: Robotics Rehabilitation


Interested applicants should refer to one of the following website to
download instructions on how to apply and/or contact directly the scientists
in charge (below) for more information regarding the individual research





Prof. Giulio Sandini

Italian Institute of Technology

Robotics, Brain and Cognitive Sciences Department

Phone: +39 010 7178101 - Fax +39 010 720321 


LIRA-Lab, University of Genova

Phone: +39 0103532779 - Fax: +39 010353.2948 





of the application material)

Research Stream : Brain Machine Interface

Theme 5.8 - The Neural Interface Problem: Enhanced in-vivo electrodes by
nanomaterial coatings

Tutor: Dr. Davide Ricci. 

N. of available positions: 1

Within the Brain Machine Interface research project of IIT, that has the
ultimate goal of extracting and decoding brain signals to drive artificial
actuators, a key issue is the investigation on how such brain signals can be
extracted from electrical recordings with the necessary temporal and spatial
resolutions. Nanomaterial coatings, such as carbon nanotubes, both
unmodified or bio-functionalized, offer the possibility to improve the
recording properties of traditional metal electrodes. Through direct
integration of nanomaterials in the electrode fabrication process, this
Ph.D. research project will deal with the following tasks: (1) designing
efficient, long-term recording microelectrodes; (2) investigating the
possibility to record signals from the surface of the cortex; (3)
investigating the problem of input impedance and making attempts to reduce
it without loss in signal-to-noise ratio;  (4) studying how to minimize
tissue reactions, such as glyosis.  The ideal candidate would have a
background in one or more of the following fields: material science,
electrochemistry, micromechanics, nanotechnology, physics.

For further details concerning the research project, please contact:
<mailto:davide.ricci at iit.it> davide.ricci at iit.it)


Theme 5.9 - The Signal Treatment Problem 

Tutor: Dr. Gytis Baranauskas

N. of available positions: 1

Any brain signal has to be amplified and processed before it can be used to
control a prosthetic device or a robotic manipulator. Moreover, the device
that amplifies and elaborates brain signals should be as small as possible.
We already have an integrated circuitry that is smaller than a finger nail
and that amplifies 64 independent neuronal signals. The goal of this largely
electronic engineering project is to build a single chip powered by
radio-waves that amplifies and processes signals from hundreds of neurons in
such a way that the chip output can be directly fed into the artificial
system driving a robotic arm. We expect to test this chip in animals as well
as in human patients. Thus, we are looking for a PhD student interested in
analog and digital microelectronics for biomedical applications and
preferentially with background in physics. The selected student will be
working in close collaboration with the project 5.8 team (see above).

For further details concerning the research project, please contact:
baranauskas at elet.polimi.it


Theme 5.10: The Brain Signal Decoding Problem 

Tutor: Prof. Stefano Panzeri

N. of available positions: 1

A fundamental question in the development of brain-machine-interfaces is how
to extract information about sensory stimulus or motor commands from a
single-trial observation of neuronal activity. This mathematical-analysis
PhD project will aim at addressing this question by investigating
systematically which features of different types of recordings of neural
activity (such as spike trains of well isolated neurons, field potentials,
multiple-unit activity or other) convey the most information about  sensory
stimuli or motor actions.

We will develop data analysis techniques based on the principles of
information theory and then apply them to recordings of brain activity
provided by our experimental collaborators, with the goal of determining how
best to decode these brain signals.  The ideal candidate for this PhD
studentship will a have a strong degree in a numerate discipline such as
physics, statistics, mathematics or computer science. No previous knowledge
of neuroscience is needed, although a strong motivation to contribute to
brain research is essential.

For more details concerning the research project, please contact:
<mailto:stefano.panzeri at manchester.ac.uk> stefano.panzeri at manchester.ac.uk


Theme 5.11: The Movements vs. Actions Problem 

Tutor: Prof. Luciano Fadiga 

N. of available positions: 1

Apart from very few exceptions, the research groups currently working at BMI
are doing their attempts by recording from the primary motor cortex. Their
goal is to decode directional tuning and individual muscles control signals.
We consider this approach quite risky. First of all because several
researchers are now disputing the idea that the motor cortex codes the
direction of reaching in absolute terms, second because recent
neurophysiological evidence shows that actions and not movements are mainly
coded by the brain. Within this field of research, one PhD student will be
involved in cortical electrophysiology to record single neurons' signals.
The aim is twofold: to study and understand the motor commands generated by
the brain during goal-directed acts and to set up long-term chronical
recording techniques, firstly in monkeys and then in humans. Backgrounds in
computer science, electronics and basic neuroscience are required.

For further details concerning the research project, please contact:
luciano.fadiga at iit.it


Theme 5.12: The Neurophysiology of the Human Brain

Tutor: Dr. Elisa Molinari

N. of available positions: 1

This work will concern brain imaging (functional magnetic resonance) to
investigate the cortical and subcortical activity of the motor system during
goal-directed actions. Through this project we will better understand the
functional correlates of motor planning/execution by analyzing data and
developing new single-subject analysis techniques. This will be done by
taking into account both the statistical significance and the intensity
(signal-to-noise ratio) of the activations. We are looking forward for one
PhD student which should be competent in physics, computer science and basic

For further details concerning the research project, please contact:
elisa.molinari at iit.it


Theme 5.13: The Role of Sensory Feedback in Brain Machine Interface.

Tutor: Dr. Alessandro Vato. 

N. of available positions: 1

Within this field of research we will study in animal models (and then in
human patients) the relevance of sensory afferents for controlling an
artificial effector. Somatosensory real-time feedback is fundamental for
motor planning and for executing "on-line" errors correction during
movements. In people with sensory motor disabilities, the sensory
information that cannot reach the brain, can be "substituted" through an
intact sensory channel (i.e. eyes or ears) different from the damaged one.
Alternatively, the damaged sensory pathway can be "replaced" trying to
achieve the same sensation in an artificial way. The goal of this project is
to design an encoder interface to stimulate the sensory cortex of behaving
rats conveying sensory information related to the state of an external
device. The encoder will be part of a Bidirectional Brain Machine Interface
System in which neural signals recorded directly from the rat's motor cortex
will control an external device and real-time feedback will be provided via
electrical stimulation of the sensory cortex. The candidate for this PhD
position will be required to have a background in computer science,
electronics and basic neuroscience.

For further details concerning the research project, please contact:
alessandro.vato at iit.it


Theme 5.14: Machinery for Functional Brain Analysis

Tutor: Dr. Franco Bertora

N. of available positions: 1

In addition, and in parallel with the preceding themes, there is at IIT an
ongoing program to investigate the frontiers of functional MRI.  Any fMRI of
the motor cortex has so far been performed on subjects confined in a
supine/prone position in the limited volume of a traditional scanner.  There
are reasons to think that the analysis of subjects performing motor tasks in
a more "natural" environment could produce different and more meaningful
results.  A study is currently in progress to determine the feasibility of a
scanner allowing functional brain analysis of a human adult in a standing or
sitting position.  We are looking for one PhD student with background in
physics, electronics, signal processing and MRI to explore the possibly
novel imaging techniques (MRI sequences, data acquisition modalities and
image reconstruction) to be included in the development of the scanner.

For further details concerning the research project, please contact:
franco.bertora at iit.it

Research Stream : Human Behavior and Biomechanics

Theme 5.15: Learning by Observation in Human and Robot

Tutor: Prof. Thierry Pozzo

No. of available positions: 2

The idea that observation can activate motor representation that do not
result from observer past executions (i.e., without sensory and motor signal
resulting from actual execution, as in the case of new motor abilities),
opens innovative learning methods for humans and robots. Ph.D. thesis work
will involve students in the fields of motor control (3D kinematic analysis,
optimization control) and robotic (machine learning.). 

The aim is twofold:  

-       To study biological motion recognition through several new
experimental paradigms that have been developed using the discovery of the
mirror system as a starting point and the idea of online action simulation
at observation. 

-       To implement the experimental results performed on human in robot
for learning by imitating human movements. For instance the perceived action
of a teacher can be mapped onto a set of existing primitives inside the

                Backgrounds in computer sciences, robotic and basic
behavioural neurosciences are required.

For further details concerning the research project, please contact:
thierry.pozzo at iit.it


Theme 5.16: Robotic Rehabilitation 

Tutor: Dr. Lorenzo Masia

No. Positions: 1

Since '80s the haptic interfaces has been used to characterize the human
upper limb impedance. These studies showed the great anisotropy of the
muscle-skeletal system: the inertia, the viscosity and the stiffness of the
arm change with the movement's direction. Also the analysis of the
interaction forces, that means that the forces caused from the dynamic
coupling between the arm's DOFs and the body's kinematics, gives another
anysotropy component that contrasts with the geometrical and cinematic
isotropy of the arm's trajectories (Morasso 1981). 

The pioneer of Robotic Rehabilitation is MIT-Manus; in this application a
customized robot was designed and developed in order to have high
back-drivability and soft and stable feel for the user. Using a visual
feedback to instruct people in following repetitive task observing their own
movements on a screen a greater reduction in impairment was observed in
exercised muscles on over 300 stroke patients; the outcomes leads to develop
adds-on for the pre-existing robots.

At IIT Human Behaviour Lab new devices have been developed by merging
experiences from ideas and know-how from different people who worked in the
above mentioned field. The main focuses of the present research are:

1)      impedance evaluation of human wrist  in passive and active movements
(hardware: IIT wrist robot)

2)      coordination between wrist and hand movements during grasping
(hardware: IIT wrist robot and hand robot)

3)      bimanual coordination in reaching and grasping by using a 6 DOF
robotic workstation for each arm (hardware: 2 X 2Dof planar robots "Braccio
di Ferro" each coupled with IIT wrist (3DOF)  and hand robot (1DOF))

4)      development of a multi-DOF (at least 5 DOF) haptic interface  for
multifinger grasping (hardware: to be designed  by the candidate)

The PhD students must develop experimental paradigms and control software to
acquire and analyze data for the point 1-2-3, mechanical design experience
is required for point 4.

For further details concerning the research project, please contact:
lorenzo.masia at iit.it


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