Determine how the stimulus characteristics are reflected in the spiking activity of neural afferents, and the relationship between spiking activity and elicited sensations.

Understand the basic principle of tactile encoding and define effective ways to implement it in a neuroprosthetic device, by defining optimal stimulation protocols (both invasive and non-invasive) to elicit appropriate perception.

Examine how rats execute motor strategies to optimize sensory inputs and the neuronal coding of vibration features at multiple stages of peripheral and cortical processing.

To develop, and implement in robots, a biologically-inspired mathematical model of how spatiotemporal patterns of tactile information can be efficiently encoded and recalled for the selection of action and control of behavior.

Develop information theoretic methods, based on the new concept of intersection information, to measure how much tactile information carried by a spiking neural code is used to implement specific behaviors in perceptual-guided tasks.

Using information-theoretic computational analyses of real spike trains, based on the concept of intersection information, we will determine how information about tactile stimuli is carried by neuronal populations, from peripheral to central at various levels, and how the representation at a given stage of processing is read out to give rise to progressively determining the final percept and its use for the task.

This project aims to improve current population spiking models of peripheral tactile responses such that they can be directly coupled to an appropriate touch sensor and deliver realistic tactile feedback in real-time.

The goal of this activity the development of spiking skin for sensory feedback on prosthetic devices.

Improved residual peripheral nerve stimulation by means of novel soft intraneural electrodes. The fellow will develop new soft electrodes (based on PDMS or polyimide) to improve coupling between neural tissue and stimulating electrodes.

Using both, tactile and visual feedback, a robot should learn to operate various kinds of switches, knobs, etc.

Implementation of spiking tactile neural encoding on a humanoid robot, development of decoding strategies for perception and behavior generation.

Implementation of spiking tactile system on a 7-DoF manipulator and development of manipulation algorithms for stable grasping of objects of different shape and softness.

Development of a novel artificial sensitive skin based on different physical transduction technologies of the tactile physical contact with spike-based neural encoding

Identification of neural network architectures for reproducing biological receptive field responses and implementation in neuromorphic hardware.