Supercritical dynamics at the edge-of-chaos underlies optimal decision-making
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- dc.contributor.author Amil, Adrián F.
- dc.contributor.author Verschure, Paul F. M. J.
- dc.date.accessioned 2023-02-23T07:07:21Z
- dc.date.available 2023-02-23T07:07:21Z
- dc.date.issued 2021
- dc.description.abstract Critical dynamics, characterized by scale-free neuronal avalanches, is thought to underlie optimal function in the sensory cortices by maximizing information transmission, capacity, and dynamic range. In contrast, deviations from criticality have not yet been considered to support any cognitive processes. Nonetheless, neocortical areas related to working memory and decision-making seem to rely on long-lasting periods of ignition-like persistent firing. Such firing patterns are reminiscent of supercritical states where runaway excitation dominates the circuit dynamics. In addition, a macroscopic gradient of the relative density of Somatostatin (SST+) and Parvalbumin (PV+) inhibitory interneurons throughout the cortical hierarchy has been suggested to determine the functional specialization of low- versus high-order cortex. These observations thus raise the question of whether persistent activity in high-order areas results from the intrinsic features of the neocortical circuitry. We used an attractor model of the canonical cortical circuit performing a perceptual decision-making task to address this question. Our model reproduces the known saddle-node bifurcation where persistent activity emerges, merely by increasing the SST+/PV+ ratio while keeping the input and recurrent excitation constant. The regime beyond such a phase transition renders the circuit increasingly sensitive to random fluctuations of the inputs—i.e., chaotic—, defining an optimal SST+/PV+ ratio around the edge-of-chaos. Further, we show that both the optimal SST+/PV+ ratio and the region of the phase transition decrease monotonically with increasing input noise. This suggests that cortical circuits regulate their intrinsic dynamics via inhibitory interneurons to attain optimal sensitivity in the face of varying uncertainty. Hence, on the one hand, we link the emergence of supercritical dynamics at the edge-of-chaos to the gradient of the SST+/PV+ ratio along the cortical hierarchy, and, on the other hand, explain the behavioral effects of the differential regulation of SST+ and PV+ interneurons by acetylcholine in the presence of input uncertainty.
- dc.description.sponsorship This research was supported by the European Commission Horizon 2020 Grant Virtual Brain Cloud (number 826421), and by an FI-AGAUR scholarship to AFA from the Generalitat de Catalunya.
- dc.format.mimetype application/pdf
- dc.identifier.citation Amil PF, Verschure PFMJ. Supercritical dynamics at the edge-of-chaos underlies optimal decision-making. J Phys Complex. 2021;2:045017. DOI: 10.1088/2632-072X/ac3ad2
- dc.identifier.doi http://dx.doi.org/10.1088/2632-072X/ac3ad2
- dc.identifier.issn 2632-072X
- dc.identifier.uri http://hdl.handle.net/10230/55874
- dc.language.iso eng
- dc.publisher IOP Publishing Ltd.
- dc.relation.ispartof Journal of Physics: Complexity. 2021;2:045017.
- dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/826421
- dc.rights © 2021 The Author(s). Published by IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri https://creativecommons.org/licenses/by/4.0/
- dc.subject.keyword supercriticality
- dc.subject.keyword edge-of-chaos
- dc.subject.keyword attractor model
- dc.title Supercritical dynamics at the edge-of-chaos underlies optimal decision-making
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion