Optogenetic technologies have been the subject of great excitement within the scientific community for their ability to demystify complex neurophysiological pathways in the central (CNS) and peripheral nervous systems (PNS). The excitement surrounding optogenetics has also extended to the clinic with a trial for ChR2 in the treatment of retinitis pigmentosa currently underway and additional trials anticipated for the near future. In this work, we identify the cause of loss-of-expression in response to transdermal illumination of an optogenetically active peroneal nerve following an anterior compartment (AC) injection of AAV6-hSyn-ChR2(H134R) with and without a fluorescent reporter. Using Sprague Dawley Rag2−/− rats and appropriate controls, we discover optogenetic loss-of-expression is chiefly elicited by ChR2-mediated immunogenicity in the spinal cord, resulting in both CNS motor neuron death and ipsilateral muscle atrophy in both low and high Adeno-Associated Virus (AAV) dosages. We further employ pharmacological immunosuppression using a slow-release tacrolimus pellet to demonstrate sustained transdermal optogenetic expression up to 12 weeks. These results suggest that all dosages of AAV-mediated optogenetic expression within the PNS may be unsafe. Clinical optogenetics for both PNS and CNS applications should take extreme caution when employing opsins to treat disease and may require concurrent immunosuppression. Future work in optogenetics should focus on designing opsins with lesser immunogenicity.
Next generation invasive neural interfaces require fully implantable wireless systems that can record from a large number of channels simultaneously. However, transferring the recorded data from the implant to an external receiver emerges as a significant challenge due to the high throughput. To address this challenge, this paper presents a neural recording system-on-chip that achieves high resource and wireless bandwidth efficiency by employing on-chip feature extraction. An energy-area efficient 10-bit 20 kS/s front-end amplifies and digitizes the neural signals within the LFP and AP bands. The raw data from each channel is decomposed into spectral features using a Compressed Hadamard Transform (CHT) processor. The selection of the features to be computed is tailored through a machine learning algorithm, such that the overall data rate is reduced by 80% without compromising classification performance. Moreover, the CHT feature extractor allows waveform reconstruction on the receiver side for monitoring or additional post-processing. The proposed approach was validated through in vivo and offline experiments. The prototype fabricated in 65nm CMOS also includes wireless power and data receiver blocks to demonstrate the energy and area efficiency of the complete system. The overall signal chain consumes 2.6 µW and occupies 0.021 mm 2 per channel, pointing towards its feasibility for thousand-channel single-die neural recording systems.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.