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by Keyword: Chaos


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Amil, Adrián F., Puigbó, J.-Y., Verschure, P., (2020). Cholinergic control of chaos and evidence sensitivity in a neocortical model of perceptual decision-making Biomimetic and Biohybrid Systems 9th International Conference, Living Machines 2020 (Lecture Notes in Computer Science) , Springer International Publishing (Freiburg, Germany) 12413, 92-96

Perceptual decision-making in the brain is commonly modeled as a competition among tuned cortical populations receiving stimulation according to their perceptual evidence. However, the contribution of evidence on the decision-making process changes through time. In this regard, the mechanisms controlling the sensitivity to perceptual evidence remain unknown. Here we explore this issue by using a biologically constrained model of the neocortex performing a dual-choice perceptual discrimination task. We combine mutual and global GABAergic inhibition, which are differentially regulated by acetylcholine (ACh), a neuromodulator linked to enhanced stimulus discriminability. We find that, while mutual inhibition determines the phase-space separation between two stable attractors representing each stimulus, global inhibition controls the formation of a chaotic attractor in-between the two, effectively protecting the weakest stimulus. Hence, under low ACh levels, where global inhibition dominates, the decision-making process is chaotic and less determined by the difference between perceptual evidences. On the contrary, under high ACh levels, where mutual inhibition dominates, the network becomes very sensitive to small differences between stimuli. Our results are in line with the putative role of ACh in enhanced stimulus discriminability and suggest that ACh levels control the sensitivity to sensory inputs by regulating the amount of chaos.

Keywords: Acetylcholine, Cortical model, Decision-making, Chaos


Andrzejak, R. G. , Ruzzene, G., Malvestio, I., Schindler, K., Schöl, E., Zakharova, A., (2018). Mean field phase synchronization between chimera states Chaos 28, (9), 091101

We study two-layer networks of identical phase oscillators. Each individual layer is a ring network for which a non-local intra-layer coupling leads to the formation of a chimera state. The number of oscillators and their natural frequencies is in general different across the layers. We couple the phases of individual oscillators in one layer to the phase of the mean field of the other layer. This coupling from the mean field to individual oscillators is done in both directions. For a sufficient strength of this interlayer coupling, the phases of the mean fields lock across the two layers. In contrast, both layers continue to exhibit chimera states with no locking between the phases of individual oscillators across layers, and the two mean field amplitudes remain uncorrelated. Hence, the networks’ mean fields show phase synchronization which is analogous to the one between low-dimensional chaotic oscillators. The required coupling strength to achieve this mean field phase synchronization increases with the mismatches in the network sizes and the oscillators’ natural frequencies.

Keywords: Chaos, Complex networks, Oscillators, Synchronisation