Regular Article - Statistical and Nonlinear Physics
Network configurations of pain: an efficiency characterization of information transmission
Instituto de Física de La Plata (IFLP), Universidad Nacional de La Plata, CONICET CCT-La Plata, Diagonal 113 entre 63 y 64, 1900, La Plata, Argentina
2 Instituto de Física, Universidade Federal de Alagoas (UFAL), BR 104 Norte km 97, 57072-970, Maceió, Brazil
Accepted: 24 December 2020
Published online: 25 January 2021
Recent studies have shown that gamma-band oscillations are directly related to pain intensity. Pain can be exacerbated or diminished via deactivation or activation of inhibitory interneurons in the dorsal horn. We consider a biologically plausible network model with different proportion of inhibitory neurons to emulate gamma elicited activity during pain processes. We perform an analysis using graph theory to gain further insight in the functional state of the circuitry underlying nociceptive process, considering all the possible gamma elicited configurations of pain when changing the number of inhibitory neurons. The probability distribution of the signal associated with each node or neuron is estimated through the Bandt and Pompe approach. We evaluate the Jensen–Shannon distance between all the possible pairs of nodes/neurons, characterizing the different network configurations by calculating the closeness centrality. Thus, by building the graph properties through the node strength distributions and using an information theoretical approach, we characterize the dynamics of the network configurations of pain. This allows us to identify the nonlinear dynamical structure underlying the nociceptive process. Importantly, our findings show that a network configuration with a of inhibitory neurons boosts information transmission of the complex network circuitry associated with the pain processing.
© The Author(s), under exclusive licence to EDP Sciences, SIF and Springer-Verlag GmbH Germany, part of Springer Nature 2021