Goalkeeper Game: A New Assessment Tool for Prediction of Gait Performance Under Complex Condition in People With Parkinson's Disease

Rafael B. Stern, Matheus Silva d'Alencar, Yanina L. Uscapi, Marco D. Gubitoso, Antonio C. Roque, André F. Helene and Maria Elisa Pimentel Piemonte

Background: People with Parkinson's disease (PD) display poorer gait performance when walking under complex conditions than under simple conditions. Screening tests that evaluate gait performance changes under complex walking conditions may be valuable tools for early intervention, especially if allowing for massive data collection.

Synaptic balance due to homeostatically self-organized quasicritical dynamics

Mauricio Girardi-Schappo, Ludmila Brochini, Ariadne A. Costa, Tawan T. A. Carvalho and Osame Kinouchi

Recent experiments suggested that a homeostatic regulation of synaptic balance leads the visual system to recover and maintain a regime of power-law avalanches. Here we study an excitatory/inhibitory (E/I) meanfield neuronal network that has a critical point with power-law avalanches and synaptic balance. When shortterm depression in inhibitory synapses and firing threshold adaptation are added, the system hovers around the critical point. This homeostatically self-organized quasicritical (SOqC) dynamics generates E/I synaptic current cancellation in fast timescales, causing fluctuation-driven asynchronous-irregular (AI) firing. We present the full phase diagram of the model without adaptation varying external input versus synaptic coupling. This system has a rich dynamical repertoire of spiking patterns: synchronous regular (SR), asynchronous regular (AR), synchronous irregular (SI), slow oscillations (SO), and AI. It also presents dynamic balance of synaptic currents, since inhibitory currents try and compensate excitatory currents over time, resulting in both of them scaling linearly with external input. Our model thus unifies two different perspectives on cortical spontaneous activity: both critical avalanches and fluctuation-driven AI firing arise from SOqC homeostatic adaptation and are indeed two sides of the same coin.

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