  Neuromorphic computing is an emerging technology that support event-driven
data processing for applications requiring efficient online inference and/or
control. Recent work has introduced the concept of neuromorphic communications,
whereby neuromorphic computing is integrated with impulse radio (IR)
transmission to implement low-energy and low-latency remote inference in
wireless Internet-of-Things (IoT) networks. In this paper, we introduce
neuromorphic integrated sensing and communications (N-ISAC), a novel solution
that enables efficient online data decoding and radar sensing. N-ISAC leverages
a common IR waveform for the dual purpose of conveying digital information and
of detecting the presence or absence of a radar target. A spiking neural
network (SNN) is deployed at the receiver to decode digital data and to detect
the radar target using directly the received signal. The SNN operation is
optimized by balancing performance metrics for data communications and radar
sensing, highlighting synergies and trade-offs between the two applications.
