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:
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@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@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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