Cortico-cortical Communication Dynamics

Abstract

In principle, cortico-cortical communication dynamics is simple: neurons in one cortical area communicate by sending action potentials that release glutamate and excite their target neurons in other cortical areas. In practice, knowledge about cortico-cortical communication dynamics is minute. One reason is that no current technique can capture the fast spatio-temporal cortico-cortical evolution of action potential transmission and membrane conductances with sufficient spatial resolution. A combination of optogenetics and monosynaptic tracing with virus can reveal the spatio-temporal cortico-cortical dynamics of specific neurons and their targets, but does not reveal how the dynamics evolves under natural conditions. Spontaneous ongoing action potentials also spread across cortical areas and are difficult to separate from structured evoked and intrinsic brain activity such as thinking. At a certain state of evolution, the dynamics may engage larger populations of neurons to drive the brain to decisions, percepts and behaviors. For example, successfully evolving dynamics to sensory transients can appear at the mesoscopic scale revealing how the transient is perceived. As a consequence of these methodological and conceptual difficulties, studies in this field comprise a wide range of computational models, large-scale measurements (e.g., by MEG, EEG), and a combination of invasive measurements in animal experiments. Further obstacles and challenges of studying cortico-cortical communication dynamics are outlined in this critical review.

Efficient coding in the economics of human brain connectomics

“…For a channel communicating at 0.1% distortion (and across all distortions; Supporting Information Figure S6C ), biasing structural edge weights by the biological properties of metabolic and electrical signaling resulted in more efficient communication by reducing the number of redundant random walkers required ( Figure 4C ; t metabolic = 20.87, bootstrap 95% CI [18.72, 23.14], df = 1993.9; t electrical = 295.93, bootstrap 95% CI [281.19, 312.76], df = 1225.9, p < 0.001). While both metabolic and electrical signaling supported more efficient communication, electrical signaling was more efficient than metabolic signaling ( Deco et al, 2014 ; Sterling & Laughlin, 2015 ). Compared to rewired null networks preserving the degree sequence ( Supporting Information Figure S6D ), structural topology and metabolic resources support communication that prioritizes fidelity ( t topological,degree-preserving (2074.4) = 121.02, p < 0.001; t metabolic,degree-preserving (2025.8) = 87.78, p < 0.001), while myelination supports communication that prioritizes compression efficiency ( t electrical,degree-preserving (1208.3) = −122.62, p < 0.001).…”

“…Second, it is well known that brain signaling relies extensively on metabolic diffusion and devotes much of its metabolic resources to maintaining a chemical balance that supports neuron firing ( Attwell & Laughlin, 2001 ; Sterling & Laughlin, 2015 ). At the longer distances of the connectome, myelin in the white matter and cerebral cortex supports the speed and efficiency of electrical signaling in subcortical fiber tracts and in cortico-cortical communication ( Barbas & Rempel-Clower, 1997 ; Deco, Roland, & Hilgetag, 2014 ; Laughlin, 2001 ). Hence, modifying the connectome to bias random walk dynamics according to metabolic resources and myelin mimics biological investments in communication efficiency.…”