Modeling the influences of non-local connectomic projections on geometrically constrained cortical dynamics

The function and dynamics of the cortex are fundamentally shaped by the specific wiring configurations of its constituent axonal fibers, also known as the connectome. However, many dynamical properties of macroscale cortical activity are well captured by instead describing the activity as propagating waves across the cortical surface, constrained only by the surface’s two-dimensional geometry. It thus remains an open question why the local geometry of the cortex can successfully capture macroscale cortical dynamics, despite neglecting the specificity of Fast-conducting, Non-local Projections (FNPs) which are known to mediate the rapid and non-local propagation of activity between remote neural populations. Here we address this question by conducting a range of investigations using a mathematical model of macroscale cortical activity, in which cortical populations interact both by a continuous sheet and by an additional set of FNPs wired independently of the sheet’s geometry. By simulating the model across a range of external inputs, timescales, and idealized connectome topologies, we demonstrate that the addition of FNPs strongly shape the model dynamics of rapid, stimulus-evoked responses on fine millisecond timescales, but contribute relatively little to slower, spontaneous fluctuations over longer order-of-seconds timescales, which increasingly resemble geometrically constrained dynamics without FNPs. Our results suggest that the discrepant views regarding the relative contributions of local (geometric) and non-local (connectomic) cortico-cortical interactions are context-dependent: While FNPs specified by the connectome are needed to capture rapid communication between specific distant populations (as per the rapid processing of sensory inputs), they play a relatively minor role in shaping slower spontaneous fluctuations (as per resting-state functional magnetic resonance imaging).Author summary: Despite the complex wiring patterns found in the cortical connectome, many dynamical properties of macroscale cortical activity can be surprisingly well explained by treating the cortex simply as a two-dimensional surface on which activity propagates as traveling waves. Here, we aim to investigate why the local geometry of the cortex sufficiently captures many such properties, despite omitting the specifically wired long-range projections informed by connectomic data. Accordingly, we developed a mathematical model of macroscale cortical activity that incorporates both local interactions along the cortical sheet and rapid non-local interactions via an independently wired connectome of specific long-range projections. Simulations of this model across a range of conditions show that specific long-range projections are crucial for reproducing rapid, stimulus-evoked responses on short timescales of tens of milliseconds, but contribute relatively little to slower, spontaneous fluctuations over longer timescales of the order of seconds. Our findings provide a plausible mechanistic account for why different experiments, capturing different temporal scales of cortical activity and spatial precision of the input drive, can arrive at different conclusions regarding the relative influences of geometry and the non-local connectome in shaping the spatiotemporal properties of macroscale cortical activity.