[Comp-neuro] PhD position at the Advanced Robotics Department @ IIT

thierry nieus thierry.nieus at iit.it
Tue Aug 13 12:57:46 CEST 2013


Dear comp-neuro comunity,

A PhD position is available at the Italian Institute of Technology for a
joint project between the Advanced Robotics Department and the Neuroscience
Brain Technology Department.

The PhD student will be supervised by Ferdinando Cannella (team leader the
 Advanced Robotics Department) and she/he will also benefit of the
co-supervision of a team of computational neuroscientists.

Details about the call can be found below:


20. Exploration Of Haptic Sensation And Its Use In Detecting Peripheral
Neuropathy

Development of a Novel Touch Based Gripper for Detecting Peripheral
Neuropathy


Touch and related capabilities, such as kinaesthesia, are probably the most
underrated human abilities. Most researches, in fact, have concentrated on
the visual and audio aspects of the sensory systems, but touch in daily
life plays a fundamental role in all our actions; losing part of this
sensitivity causes a problem in accomplishing even simple tasks. Moreover,
nowadays, the touch is widely used to screen neurological diseases.
Improving the accuracy, sensitivity and repeatability of the physical
inspections would improve the recognition of such peripheral neuropathies.
The core of this proposal is to determine a simple and objective (above all
not influenced by the doctor skill and experience) test that highlights the
patient diseases (as dysfunction of the recurrent pyramidal circuit,
neuromuscular junction, primary motor neuron diseases, etc.). One of the
straightforward connections between the brain and the environment is the
Motor Cortex (cxM1) which controls complex movements by activation of the
motor neurons. Thus, the idea is to simulate the healthy human grasping by
building a human upper limb model (with its tactile sensor feedback)
controlled by a network structure of the primary motor cortex model. Till
now there have been numerous theories attempting to explain such sequence
of operations in terms of a variety of motor control models; in fact, the
accomplishment of a movement is a rather complex task: the simplest
movement as pointing a given point in the space requires a non-trivial
sequence of operations. Another point is that a realistic model should be
able to encode and decode the ascending tactile signals; moreover,
considering the tactile feedback, the model must be bidirectional
brain-muscle-brain. In the last decades, there have been several successful
results in linking the information flow from neural cells to fingertip
tactile sensitivity and arm movements: in Lukashin et al. (Lukashin 1996)
the movement of an arm was accomplished by six independent muscles governed
by an artificial neural network model which input layer received spikes of
single cell recordings; Cisek et al. (Cisek 1998) proposed a model of the
cortical-spinal circuitry designed to cope with a wide range of movements
in linking the information from neural cells to movements: Gerling et al.
(Gerling 2013) modeled a 3D finite element fingertip linking all the
previous models of touch: skin mechanics to neural firing rate, neural
dynamics to action potential elicitation and mechanoreceptor populations to
psychophysical discrimination; Bologna et al. (Bologna 2013) modeled the
fine touch with peripheral-to-central neurotransmission closed loop.

The novelty of this work is to reproduce the two human fingers grasping
with a network structure of the primary motor cortex model that controls
the upper limb model (with its tactile sensor feedback). Thus, the aim is
to build a robotic arm (fingertip-hand-arm-brain) with not only the same
structure (skin, bones, muscles, tendons, etc.), but, above all, with the
same neurological system (mechanoreceptors, proprioceptors, brain cells,
etc.) of human upper limb. This arm simulator will be able to reproduce the
kinematic behaviour of a healthy human arm and it will serve as reference
for further comparison with ill people; in Valente et al. (Valente 2012) a
reference scale for peripheral neuropathy was established. By building a
close-loop brain-arm-brain, the project aims to setup a realistic
simulation environment able to improve medical doctors’ diagnosis (e.g.
brain diseases can be tested altering the circuit).

The work is divided in three parts: the first part is about assembling
several test rigs for collecting the experimental data to determine the
mechanical properties, kinematic characteristics and the parameters for
models. The second one will concern the building of a real time kinematic
simulation of fingertip, hand, forearm and arm 3D finite element/multibody
models with acquired data based on 3D virtual visualization and validation
with experimental data. The third part consists in designing the physical
robotic simulator.

This activity will evolve along different research paths in collaboration
with the Neuroscience and Brain Technologies Department (with Thierry
Nieus) and the CNR of Palermo (with Michele Migliore) as well as with other
research centers in Europe (Université Pierre et Marie Curie of Paris with
Angelo Arleo).

The successful candidate is expected to have an excellent background in
mathematical modelling. Knowledge of mechanics, computer science,
biomedical measurements, statistics, electronics and control are also
required. Basic knowledge of neuroscience is considered as a plus.

For further details concerning this research project, please contact:
ferdinando.cannella at iit.it

Lukashin, A. V., Amirikian, B. R., and Georgopoulos, A. P., A Simulated
Actuator Driven by Motor Cortical Signals. Neuro Report, 1996.

Cisek, P. Grossberg, S., and Bullock, D., A Cortico-Spinal Model of
Reaching and Proprioception under Multiple Task Constraints. The Journal of
Cognitive Neuroscience, 1998.

Gerling, G. Rivest, I., Lesniak, D., Scanlon, J., Wan, L., Validating a
Population Model of Tactile Mechanotransduction of Slowly Adapting Type I
Afferents at Levels of Skin Mechanics, Single-unit Response and
Psychophysic., IEEE Transactions on Haptics, 2013.

Bologna L., Pinoteau J., Passot J-B., Garrido, J.A., Vogel, J., Ros Vidal,
E., Arleo A., A Closed-Loop Neurobotic System for Fine Touch Sensing.
Journal of Neural Eng., 2013

M. Valente, F. Cannella, L. Scalise, M. Memeo, P. Liberini and D. Caldwell,
Tactile Sensibility Through Tactile Display: Effect of the Array Density
and Clinical Use. Haptics: Perception, Devices, Mobility, and
Communication, 2012.

For further details concerning this research project and/or any questions
or doubts about the application procedure as well as moving to and living
in Genoa, etc. , please contact: ferdinando.cannella at iit.it


Full details of the call and the application procedure can be found at:
http://www.iit.it/phdschool


PLEASE NOTE THE DEADLINE FOR APPLICATION: 20th SEPTEMBER, 11:59am, ITALIAN
TIME


To apply, please visit the following link:

http://www.studenti.unige.it/postlaurea/dottorati/XXIX/bandoGeneraleEN


Applications are considered for the subsequent selection ONLY if received
ELECTRONICALLY on the UNIVERSITY of GENOA's website strictly by the
deadline.


Dr Ferdinando Cannella



Team Leader

Advanced Robotics Department

Istituto Italiano di Tecnologia

[Italian Institute of Technology]

Via Morego, 30

16163 Genova (Italy)

t: + 39 010 71 781 562

m: +39 338 96 76 884

f: + 39 010 71 781 232

http://www.iit.it/en/research/departments/advanced-robotics.html
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