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C y b e r R a t
A Brain-Chip Interface for High-resolution Bi-directional Communication
The CyberRat project will have a strong and direct impact both on basic neuroscience, on the field of brain-machine interfacing and on the therapy of neurological disorders.
Neuroscience. Although it is difficult to precisely predict to what extent the new CyberRat technology will foster neuroscience research, it is reasonable to expect that it will have a large impact. Measurements of brain activity “in vivo” will be possible with high-resolution (one order of magnitude higher than actual multi-site techniques), thus opening a new window to investigate neuronal networks processing. Simultaneous bi-directional communication between brain and electronics will offer to the neuroscientist the possibility to develop new experimental paradigms to study brain circuits. At the neuronal networks level, recording/stimulation closed loop experiments will help to understand the basis of networks processing and of synaptic plasticity. Through multiple implantation of the chips in different brain regions, high-resolution bi-directional measurements will be possible at the “whole” brain level, thus offering the possibility to investigate brain circuits with unprecedented detail.
Brain machine interfacing. A major paradigm in the field is that new technologies are needed that allow (i) high-resolution and (ii) bi-directional communication with (iii) multiple brain regions and offering the possibility to record/stimulate (iv) different types of signals (either spikes or field potentials) in large populations of neurons. CyberRat was thought to match these requirements. The main strategy is the use of capacitively coupled recording and stimulation circuitry to interface electronics with nervous tissue instead of microelectrodes or microwires, thus taking the greatest advantage from highly integrated CMOS circuitry. High-resolution interfacing with large populations of neurons and in multiple brain regions will enable to finely decode brain activity to control artificial actuators (such as artificial limbs) with unprecedented efficiency. Through bi-directional communication it will be possible to establish a feed back closed loop between brain and machine. This will allow to directly train the brain to control the actuators with high efficiency, while actual approaches must rely on low-efficiecncy visual or tactile feed back. Similarly, feedback
stimulation may provide sensory inputs to the brain by pressure sensors placed in an artificial limb, thus transforming the actuator into a near-physiological new part of the body. In the direction of neuroprosthetics, high-resolution bi-directional communication will also provide new means to rescue sensory impairments, such as blindness or deafness, by interactively interfacing the auditory or the visual cortex with artificial sensors. CyberRat will greatly help the field of brain-machine (and particularly brain-computer) interfacing in two ways: (i) by offering an efficient way of communication between brain and machine and (ii) by helping neruoscientists to better investigate brain function and to close the gap between computational models and real physiological mechanisms of neuronal information processing. In this way, besides Bidirectional interfaces, CyberRat will strongly impact also other topics of interest that were highlighted by the BioICT Convergence, such as the development of Novel computing paradigms or Biomimetic and Biohybrid artefacts inspired to the neuronal networks in the living brain.
Therapy of neurological disorders. It is extremely important to underline that the CyberRat technology may have direct application in the therapy of common neurological diseases such as Parkinson or Epilepsy. Actual therapies based on the chronic stimulation of brain regions (such as Deep Brain Stimulation for Parkinson) through implanted electrodes will take great advantage from our technology. The possibility to implant and interface a chip with deep brain structures allowing for high-resolution bi-directional communication will greatly enhance the efficacy of the therapy and reduce serious side effects. We will assess this possibility during the project using a Parkinson animal model.
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