  Determining how synaptic coupling within and between regions is modulated
during sensory processing is an important topic in neuroscience.
Electrophysiological recordings provide detailed information about neural
spiking but have traditionally been confined to a particular region or layer of
cortex. Here we develop new theoretical methods to study interactions between
and within two brain regions, based on experimental measurements of spiking
activity simultaneously recorded from the two regions. By systematically
comparing experimentally-obtained spiking statistics to (efficiently computed)
model spike rate statistics, we identify regions in model parameter space that
are consistent with the experimental data. We apply our new technique to dual
micro-electrode array in vivo recordings from two distinct regions: olfactory
bulb (OB) and anterior piriform cortex (PC). Our analysis predicts that: i)
inhibition within the afferent region (OB) has to be weaker than the inhibition
within PC, ii) excitation from PC to OB is generally stronger than excitation
from OB to PC, iii) excitation from PC to OB and inhibition within PC have to
both be relatively strong compared to presynaptic inputs from OB. These
predictions are validated in a spiking neural network model of the OB--PC
pathway that satisfies the many constraints from our experimental data. We find
when the derived relationships are violated, the spiking statistics no longer
satisfy the constraints from the data. In principle this modeling framework can
be adapted to other systems and be used to investigate relationships between
other neural attributes besides network connection strengths. Thus, this work
can serve as a guide to further investigations into the relationships of
various neural attributes within and across different regions during sensory
processing.
