PROJECT SUMMARY
Much work has been done to characterize the structural underpinnings of neuromodulatory systems and how
these architectural features shape neuromodulator action. Yet, although, neuromodulators primarily signal
through volume transmission which requires them to traverse the extracellular space (ECS) from release site to
target receptor, neuromodulatory diffusion through the ECS has received little attention. We know from
computational models that ECS diffusion is dependent on factors such as volume fraction, tissue tortuosity and
ECS geometry. Simulations so far have mainly focused on synaptic diffusion and synaptic spillover
mechanisms whereas neuromodulation functions at much larger spatiotemporal scales than that: even
neuromodulator diffusion through just layer IV in macaque cortex, for example, requires molecules to travel
distances up to 0.5 mm from release site to target receptor. Factors related to tissue porosity become
increasingly more important at such distances but current computer models like the common simulation engine
MCell are only equipped to study molecular diffusion at the nanometer scale. Consequently, we need updated
computational models capable of simulating the diffusion of neuromodulators across greater spatial and
temporal ranges capable of incorporating measures that become relevant at that macroscale. For this, I
propose to develop a hybrid model which will achieve this critical functionality by combining existing MCell
capabilities with large-scale algorithms from models of bulk diffusion. Because ECS diffusion is thought to vary
with brain regions which to date has not been systematically evaluated, I will then, with this multiscale model,
simulate diffusion of acetylcholine, noradrenaline, and dopamine across different regions of macaque cortex to
test how factors such as tissue granularity or tissue anisotropy affect common diffusion metrics (e.g.,
concentrations, diffusion rates, effective diffusion coefficients, and diffusion tensor). Since neuromodulatory
networks have been linked to virtually every brain function, understanding the dynamics of neuromodulator
diffusion across the brain is an important step in understanding normal brain function. Furthermore, because
changes in ECS dynamics and in neuromodulatory systems have been observed throughout development and
normal aging or with neuropathology like stroke-related ischemia and dementia, identifying key parameters that
determine signaling outcomes, but also the active processes by which they can be modified, may be key for
the advancement in diagnostics and therapeutics.
