- Antoine Grimaldi, Amélie Gruel, Camille Besnainou, Jean-Nicolas Jérémie, Jean Martinet, Laurent U Perrinet
- read the paper online or in PDF
- Video Abstract
- join the Zotero group to add and discuss more items
- code for paper (including revisions): https://github.com/SpikeAI/2022_polychronies-review
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.
