The objective of this project (FP7-ICT- 2007- FET Proactive 3: Bio-ICT Convergence), is to develop a full biohybrid rehabilitation and substitution methodology; replacing the aged cerebellar brain circuit with a biomimetic chip bidirectionally interfaced to the inputs and outputs of the system.
Information processing will interface with the cerebellum to actuate a normal, real-time functional behavioural recovery, providing a proof-of-concept test for the functional rehabilitation of more complex neuronal systems. The model neuronal system chosen is the cerebellar microcircuit involved in the conditioning of the motor eyeblink response. Localized experimental or clinical damage to this microcircuit disrupts irreversibly the eyeblink conditioning while aging invariably compromises the acquisition and retention of the eyeblink response.
Using the aged rat as an experimental model the plan is to integrate a biomimetic chip to rehabilitate a discrete sensory-motor learning function lost in the senescent cerebellar microcircuit, through the development of multiple enabling technologies. Novel electrodes will be developed to both detect the stimulus and trigger the eyeblink response. The stimulus signals will be extracted from background neuronal activity and undergo conditioning, processing, and interpretation in a silicon chip which mimics the function of the deficient cerebellar circuit. The output from this biomimetic chip will then trigger the eyeblink response by way of implanted stimulation electrodes.
Complete success would be achieved through a real-time demonstration of functional recovery of the lost motor learning response in aged rats. Advances in any or all of the component technologies, their integration and clinical implementation, and improved understanding of the neuronal circuit would represent incomplete but valuable progress in the treatment of deficient neuronal systems.
Within the project, SPECS is responsible for extending the cerebellar microcircuit model´s functionality to satisfy behavioural adaptation and learning in a real-world environment. We will construct a real-time synthetic model of the cerebellar circuit underlying classical conditioning that will be interfaced to the afferent and efferent systems of a senescent cerebellum in order to restore its function. To make the model advantageous in terms of the hybrid project, we plan to construct the model as a self-contained section of the cerebellum.
In particular, we will focus on four tasks:
- Simulate the dynamics of the cerebellar network in the context of its afferent and efferent structures to which it is interfaced and assess its properties under variable real-world conditions
- Evaluate the relationship between the parameters of the model and its ability to support conditioning to a range of CS-US Inter Stimulus Intervals (ISI).
- Develop procedures for on-line tuning of the model’s parameters.
- Develop a real-time energy efficient implementation suitable for implantation.
see more on RENACHIP at
BBC: Will we ever …have Cyborg Brains? http://www.bbc.com/future/story/20121218-will-we-ever-have-cyborg-brains
UPF: SPECS breakthrough in neuroprosthetics it’s a step forward in understanding the brain circuit critical in learning and memory https://www.upf.edu/dtic/en/actualitat/0553.html
Ivan Herreros, Andrea Giovannucci, Aryeh H. Taub, Roni Hogri, Ari Magal, Sim Bamford, Robert Prueckl and Paul F. M. J. Verschure (2014), “A cerebellar neuroprosthetic system: computational architecture and in vivo test”, Frontiers in Bioengeeniring and Biotechnology. Bionics Biomimetics, 21 May 2014 doi: 10.3389/fbioe.2014.00014 http://journal.frontiersin.org/Journal/10.3389/fbioe.2014.00014/abstract