Probing scale interaction in brain dynamics through synchronization

Abstract

The mammalian brain operates in multiple spatial scales simultaneously, ranging from the microscopic scale of single neurons through the mesoscopic scale of cortical columns, to the macroscopic scale of brain areas. These levels of description are associated with distinct temporal scales, ranging from milliseconds in the case of neurons to tens of seconds in the case of brain areas. Here, we examine theoretically how these spatial and temporal scales interact in the functioning brain, by considering the coupled behaviour of two mesoscopic neural masses (NMs) that communicate with each other through a microscopic neuronal network (NN). We use the synchronization between the two NM models as a tool to probe the interaction between the mesoscopic scales of those neural populations and the microscopic scale of the mediating NN. The two NM oscillators are taken to operate in a low-frequency regime with different peak frequencies (and distinct dynamical behaviour). The microscopic neuronal population, in turn, is described by a network of several thousand excitatory and inhibitory spiking neurons operating in a synchronous irregular regime, in which the individual neurons fire very sparsely but collectively give rise to a well-defined rhythm in the gamma range. Our results show that this NN, which operates at a fast temporal scale, is indeed sufficient to mediate coupling between the two mesoscopic oscillators, which evolve dynamically at a slower scale. We also establish how this synchronization depends on the topological properties of the microscopic NN, on its size and on its oscillation frequency.

Complex network theory and the brain

“…At the microscopic scale, individual neurons exhibit action potentials that last about 1 ms, while the coordinated multiunit activity or local field potentials generated by the synchronization of multiple neurons operates on time scales up to tens of seconds. To study the interactions between these scales, Barardi et al [35] introduce a hybrid computational model in which two mesoscopic neural masses are coupled to each other through a microscopic neuronal network. The two neural mass oscillators are taken to operate in a lowfrequency regime with different peak frequencies and distinct dynamical behaviour.…”

Structural determinants of criticality in biological networks

“…In the brain however, the nature of synaptic activity is fundamentally different from the quasi-periodic activity of brain regions. The integration of local activity along the hierarchical structure of the brain incorporates active processing of information, not simply the linear summation of signals (Barardi et al, 2014 ). Additionally, the measured macroscopic properties of the brain often arise from analysis of functional activity, while microscale recordings sample the dynamics of actual neuronal architecture.…”

Fictive Scratching Patterns in Brain Cortex-Ablated, Midcollicular Decerebrate, and Spinal Cats

“…Asymmetrical models are conformed by extensor and flexor CPG modules working independently but are at odds with the half-center paradigm (Hägglund et al, 2013). Other concepts that include not only flexor and extensor motoneurons but also motoneuron pools controlling bi-articular muscles are being developed (Barardi et al, 2014). There are other models based on a two-layer longitudinal architecture of the CPG that propose a theoretical circuit that reproduces the sinusoidal shape of the dorsal cord potentials (Pérez et al, 2009).…”