# Adaptive proximity to criticality underlies amplification of ultra-slow fluctuations during free recall

## TL;DR

The brain may use a delicate balance near a critical state to generate slow neural waves and transition into spontaneous thought.

## Contribution

A simple computational model shows how cortical networks near criticality can amplify slow fluctuations and switch to generative modes.

## Key findings

- A random recurrent network near criticality reproduces ultra-slow fluctuations seen in human visual cortex.
- Slight increases in network gain selectively amplify slow waves without destabilizing the system.
- The model matches intracranial EEG data during rest and free recall, supporting the role of criticality in spontaneous brain activity.

## Abstract

Ultra-slow fluctuations are a hallmark of spontaneous cortical activity. We examine the hypothesis that these dynamics arise from recurrent neuronal networks operating near a phase-transition point, a state marked by “critical slowing down”. In such networks, a subtle shift toward criticality should selectively amplify slow fluctuations, providing a lever that can switch the cortex from quiet rest into self-generated behavior. Using a simple random recurrent network, we reproduce this amplification effect. The resulting spectra closely match intracranial electroencephalography from human visual cortex recorded during rest and during category-specific visual free recall. In particular, the model captures the experimentally observed enhancement of slow fluctuations during recall. These simulations reveal a parsimonious mechanism that explains spontaneous ultra-slow activity and enables rapid transitions between spontaneous states, suggesting that dynamic tuning toward criticality may be a general strategy by which cortical networks enter a generative mode.

Our brains never stand completely still: even at rest, neural activity drifts in very slow waves that last seconds to minutes. Where do these sluggish rhythms come from, and how do they help us shift from quiet rest into free, creative thought? We explored these questions using a minimalist computational model. The model is a network of simple “neurons” whose connections can be strengthened or weakened by a single gain knob. When the gain is set just below a critical tipping point, the network exhibits “critical slowing down,” creating ultra-slow fluctuations like those measured in real brains. Nudging the gain only slightly higher selectively boosts the slowest waves without destabilizing the network. This two-step behavior reproduces human intracranial recordings: the power at slow frequencies rises markedly in visual cortex when people freely recall images compared with passive rest. Our results suggest that cortical circuits normally hover near criticality and can edge even closer on demand, using critical slowing to shift rapidly from baseline activity to a generative mode that supports recall and other spontaneous, free behavior.