Fabrication of flexible shank-electrodes for long-term multi-area electrophysiological recordings in the prefrontal areas of behaving rats

While some work has been done in the past on quantitative analyses of the temporal and spatial dynamics of local field potentials in the rodent neocortex, there is more to be investigated about the interesting patterns observed in the temporal dynamics of the local field potentials recorded from the prefrontal areas and how they relate to the activities of the single units nearby.

To obtain stable recordings from same set of single units up to several months with minimal damage to the tissue, we are currently establishing a protocol for manufacturing flexible electrode shanks with 32-64 channels of very low impedances, inspired by NeuroRoots (Ferro et al 2018, bioRxiv). We would like to use this technology to perform simultaneous recordings from the multiple layers of prefrontal areas of rats such as layer 2/3 and layer 5 of anterior cingulate cortex (ACC), prelimbic cortex (PrL) and infralimbic cortex (IL), while the animal is in a cue discrimination task.

Project Description

Initially, the student will help to establish a protocol to reliably manufacture and assemble the devices, and to test them in acute single-area recordings in vivo. Next stages will involve extending the recordings to multiple areas and developing interfaces with the data acquisition system for these multi-areal recordings. We also would like to incorporate a magnetic layer on the electrode pads to post-surgically locate them with magnetic resonance imaging (MRI).

Depending on the motivation and interests of the student, this project gives them the opportunity to learn among a variety of skills including microfabrication techniques, efficiently interfacing multichannel electrode arrays with data acquisition systems, rodent brain surgery for acute/chronic electrode implants or analysis of in vivo electrophysiology data.

Recommended Background

Background in physical sciences or engineering is strongly preferred; any background on in vivo electrophysiology is bonus. Experience with Python would be very helpful if the student is interested in the analysis of electrophysiology data.

The student will have the opportunity to work in a cleanroom environment for microfabrication in case of a master thesis. For semester projects, this is not possible due to logistical reasons.