2021 BRN Discussion, page-294

https://ui.adsabs.harvard.edu/link_gateway/2017LPICo1989.8080T/PUB_PDF

ON NEUROMORPHIC ARCHITECTURES FOR EFFICIENT, ROBUST, AND ADAPTABLE AUTONOMY IN LIFE DETECTION AND OTHER DEEP SPACE MISSIONS.

Conclusions:
NAs, paired with new radiation re-sistant forms of memory, offer solutions for extreme au-tonomy. To leverage the inherent advantages of neuro-morphic computation over traditional computing and enable a host of deep space missions, in particular for life detection, it is desirable to have a (a) neuromorphic hardware implementation qualified for space flight, in addition to (b) specifically designed neuromorphic al-gorithms. Event based sensors for strand sequencingand end-to-end learning networks represent examples of promising avenues of research. NASA’s interest in con-sidering secondary payloads on essentially all future planetary science missions offers opportunities to demonstrate neuromorphic solutions for deep space, with the vision of developing brain-like systems that can go where no human brain has gone before.