Over the past decade, there have been a
number of seminal theories on the conditions for
propagating information faithfully while maintaining
stability in neuronal networks. However, to maintain
mathematical tractability, these studies relied
heavily on principles borrowed from physics. While the
concepts are universally applicable to all neural
networks (sensory, motor, higher cognitive areas),
they are necessarily abstract and make simplifying
assumptions that appear far from biological
parameters. Testing these theories is very difficult
as it requires accurate information about the network
architecture and the precise control of the input to
the network. For example, assessing function in the
intact, in vivo
preparation is challenging as it has too many
variables that need to be controlled (e.g. whether the
animal is anesthetized, alert, moving, head-fixed,
etc.).
To overcome these limitations, we use the
culture preparation in combination with
microfabrication and stimulated our network using a
novel optogenetic stimulation technique. This allowed
us to vary systematically network density and
architecture, measure synaptic connections, and drive
the network with any specified input (see movie).
We showed that in neuronal cultures, synaptic
strengths scale with the network size to preserve
balance between excitation and inhibition, maintain
variable spiking statistics and reduce correlations in
spiking as predicted by theory and observed in the
intact brain (see Barral et al
(2016)).