Implantable devices for the stimulation of the central and peripheral nervous systems (NS) may lead to a revolution in the treatment of a variety of diseases. Ideally, brain dysfunctions and disorders in organs can be treated by a direct interaction with central neurons and peripheral nerves. Within an adaptive closed-loop, the intelligent controller recognizes pathological activity patterns and adapts stimulation accordingly to restore function. Importantly, while stimulation is always operated at the level of the NS, sensing may occur also in other organs (e.g. monitoring glucose concentration in the blood).
This is the vision, but to make it real, novel implantable devices must be conceived. Precise control of neuronal discharge and 'intelligent' operation, i.e. by smartly adapting stimulation to the varying neuronal responses must be realized. In essence, these devices must emulate and support the NS in supervising smart controls.
The goal of CIDES is to capture the neural dynamics of predictive decision-making and to reproduce this dynamic in a computational model. This information will be ready to be used in advanced neuromorphic devices able to generate efficient decision-making strategies in closed loop protocols. To this end, we will i) carry out neurophysiology recordings from multiple brain areas of animal models performing predictive decision-making tasks; ii) include modulation in the network neural activity after stimulation of the subthalamic nucleus; iii) develop an adaptive multi-area spiking neural network model that reproduces the experimental results.
The project results will advance our understanding of the brain's control processes and have a great potential impact on the electronics and biomedical European industry, paving the way to a new generation of brain-inspired processors (smart decision makers) for an efficient autonomous control of brain computer interfaces including closed-loop brain stimulators.
