Background: Active dense implantable neural probes based on CMOS technology are an emerging neurotechnology to drastically enlarge the bandwidth of brain machine interfaces (BMIs). Current generations of these devices were demonstrated for high-resolution and large-scale recordings of neural activity in-vivo, but miss the capacity to electrically stimulate neural activity. Implementing such bi-directionality would open-up innovative perspectives for next generation of minimally invasive, low-power closed-loop neuroelectronic devices for neuroscience research and clinical applications in BMIs.
Description: The aim of this project is to realize and to study the performances of fully bi-directional active dense neural probes with hundreds to thousands of closely integrated electrode-pixels that can be flexibly configured for electrical recording and stimulation modalities. In tight collaboration with experienced researchers in CMOS circuit design, micro-/nano-structuring and in-vivo electrophysiology, the student will realize and characterize a complete platform prototype and evaluate in animal models the neuromodulation efficacy of different open-/closed-loop electrical stimulation modalities.
References:  Angotzi GN, Boi F, Lecomte A, Miele E, Malerba M, Zucca S, Casile A, Berdondini L, SiNAPS: An implantable active pixel sensor CMOS-probe for simultaneous large-scale neural recordings, Biosens Bioelectron. 2019 Feb 1;126:355-364.
doi: 10.1016/j.bios.2018.10.032 .
 Boi F, Perentos N, Lecomte A, Schwesig G, Zordan S, Sirota A, Berdondini L, Angotzi GN, Multi-shanks SiNAPS Active Pixel Sensor CMOS probe: 1024 simultaneously recording channels for high-density intracortical brain mapping, bioRxiv 2019.
Main Supervisor: Luca Berdondini. (Microtechnology for Neuroelectronics)
i. MSc or equivalent degree in Electronic/Electrical Engineering, Bioengineering or in Physics.
ii. Experience in CMOS circuit design
iii. Experience in numerical simulations
iv. Experience in bio-sensors/actuators
i. Background in biology/neuroscience or related areas
ii. Background in biophysics
iii. Skills in programming with Matlab/Python or similar tools
iv. Experience in electronic hardware development.
How to apply. Prospective students must submit using the online form the following documents
1) 2-page CV, which includes studies, expertise and achievements.
2) 1-page research statement, which includes the choice of a project from the list above and a justification of the choice. Only if robustly justified, the student may signal their interest also for a second project, but there is no guarantee that this will be taken into account by the selection panel.
3) A transcript of undergraduate and postgraduate studies.
4) A valid IELTS certificate, obtained no more than two years before the proposed registration date.
5) Contact details of two referees.
Deadline for application:.26th January 2022