Amplitude and phase coupling optimize information transfer between brain networks that function at criticality

Avramiea, Arthur-Ervin; Masood, Anas; Mansvelder, Huibert D.; Linkenkaer‐Hansen, Klaus

doi:10.1101/2021.03.15.435461

Cited by 2 publications

(1 citation statement)

References 74 publications

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“…The versatility of neuronal response to the oscillatory state found in the critical state may bring with it unwanted variability (Avramiea et al, 2020), which creates the incentive for moving away from criticality. Modulating the criticality of local networks may contribute to their participation or exclusion from the functional repertoire of brain activity (Avramiea et al, 2021).…”

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Regulation of critical brain dynamics and its functional implications

Avrămiea¹

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Evidence of criticality at various levels of neuronal organization has accumulated over the past 2 decades. However, little is known of how criticality affects brain function, whether the critical state is always optimal for information processing, and whether the brain can change its operating point with regards to criticality so as to accommodate varying information processing requirements. Therefore, the aim of this thesis is to elucidate mechanisms that regulate brain criticality and to understand their impact on local and global information processing. We empirically validated that the brain can control the level of criticality via neuromodulation, with implications on perception. Then, we relied on computational modeling to gain full control on the parameters that determine criticality, and tested the implications of the level of criticality on two theories of brain function. Last, since excitation/inhibition balance is known to be a crucial determinant of criticality, which can vary across individuals, but also within subjects across time with neuromodulation, we developed a method to non-invasively estimate the functional E/I ratio.

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Regulation of critical brain dynamics and its functional implications

Avrămiea¹

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Supercritical dynamics at the edge-of-chaos underlies optimal decision-making

Amil

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2021

J. Phys. Complex.

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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.

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Amplitude and phase coupling optimize information transfer between brain networks that function at criticality

Cited by 2 publications

References 74 publications

Regulation of critical brain dynamics and its functional implications

Regulation of critical brain dynamics and its functional implications

Supercritical dynamics at the edge-of-chaos underlies optimal decision-making

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