  Why do neurons communicate through spikes? By definition, spikes are
all-or-none neural events which occur at continuous times. In other words,
spikes are on one side binary, existing or not without further details, and on
the other can occur at any asynchronous time, without the need for a
centralized clock. This stands in stark contrast to the analog representation
of values and the discretized timing classically used in digital processing and
at the base of modern-day neural networks. As neural systems almost
systematically use this so-called event-based representation in the living
world, a better understanding of this phenomenon remains a fundamental
challenge in neurobiology in order to better interpret the profusion of
recorded data. With the growing need for intelligent embedded systems, it also
emerges as a new computing paradigm to enable the efficient operation of a new
class of sensors and event-based computers, called neuromorphic, which could
enable significant gains in computation time and energy consumption -- a major
societal issue in the era of the digital economy and global warming. In this
review paper, we provide evidence from biology, theory and engineering that the
precise timing of spikes plays a crucial role in our understanding of the
efficiency of neural networks.
