What if the key to unlocking learning, memory, and even preventing Alzheimer’s disease lies in a single, measurable brain state? A new theory proposed by Keith Hengen, associate professor of biology at Washington University in St. Louis, suggests just that. In a recent paper published in Neuron, Hengen and co-author Woodrow Shew, a physicist at the University of Arkansas, argue that the brain’s optimal performance depends on a state known as “criticality.” This concept, borrowed from physics, could offer a unified framework for understanding not only how the brain learns and remembers, but also how neurological diseases undermine its function.

The idea of brain criticality may sound abstract, but its implications are striking. According to Hengen, the brain becomes a powerful learning machine only when it operates at the edge of criticality — a tipping point between order and chaos. This delicate balance enables the brain to be flexible, adaptable, and ready to process new information. “Brains need to reach criticality to think, remember and learn,” Hengen explains.

This notion challenges the traditional view that the brain is a static network of hard-wired circuits. Instead, Hengen suggests that nearly everything the brain does is shaped by experience. A healthy brain, then, is one that can learn anything — a property that emerges when it hovers near criticality. I found this detail striking: the same mathematical principles that describe avalanches and earthquakes may also govern our thoughts and memories.

Physicists like Shew have long studied criticality in natural systems. A classic example is a sand pile — as more grains are added, the pile becomes steeper until it suddenly collapses. Just before this collapse, the system is at a critical point. In the brain, this translates to a specific state where neural activity is neither too ordered nor too chaotic. Remarkably, this state looks the same whether observed in milliseconds or hours, in a few neurons or an entire brain region. This scale-invariance, as Shew describes, aligns with our intuitive sense of how the brain operates across time and space.

What makes this theory especially compelling is its measurable nature. Hengen and Shew have developed mathematical tools to assess how close a brain is to criticality using fMRI technology. This could revolutionize how we understand and diagnose brain disorders. Rather than focusing solely on damaged regions or protein buildup, as is common in Alzheimer’s research, the criticality framework emphasizes the brain’s overall computational state.

In Alzheimer’s disease, for instance, Hengen argues that the core issue may not be the presence of tau proteins or neuron loss alone, but the gradual erosion of criticality. The brain becomes less able to adapt and process information, even if it appears functionally intact in early stages. “The brain has remarkable compensatory abilities that can mask functional problems even as criticality begins to erode,” he notes. This could explain why symptoms often emerge only after significant damage has occurred.

Collaborating with neurologist David M. Holtzman, Hengen has shown that tau protein buildup directly disrupts criticality. This link offers a new diagnostic angle: by measuring criticality through fMRI, clinicians may be able to detect early signs of cognitive decline long before symptoms manifest. Combined with advanced blood tests, this approach could identify individuals at risk and open the door to early interventions.

Another intriguing application of this theory lies in early childhood development. Working with Deanna Barch, a professor of psychiatry and brain sciences at WashU, Hengen is exploring how criticality at birth may influence cognitive abilities later in life. Some children, he suggests, are naturally closer to criticality, which could make them more adept learners. While many external factors affect educational outcomes, criticality might help explain some of the variability between children in a way that’s both measurable and actionable.

The theory also sheds new light on the role of sleep. In a recent study with physicist Ralf Wessel, Hengen found that sleep helps restore the brain’s critical state. Being awake and active gradually pushes the brain away from criticality, while sleep acts as a reset. This insight could have therapeutic implications, especially for neurodegenerative diseases like Alzheimer’s. People who experience chronic sleep disruption — due to shift work or insomnia — are at higher risk for cognitive decline. Hengen believes that targeted sleep-based therapies might help restore criticality and support cognitive function.

In fact, early experiments in mice bred to exhibit Alzheimer’s symptoms have shown promising results. After undergoing a sleep intervention designed to reinforce criticality, these mice became faster learners. While more research is needed, the findings suggest that restoring criticality could enhance memory and learning, even in the context of brain disease.

Looking ahead, Hengen hopes to explore how criticality relates to individual talents and cognitive strengths. He speculates that someone with a strong aptitude for art, for example, might be closer to criticality in brain regions tied to creativity. This raises fascinating questions about latent abilities and how they might be identified and nurtured.

Ultimately, the theory of brain criticality offers a unifying model that bridges biology, physics, and neuroscience. While much work remains, Hengen and Shew believe they are on the cusp of a paradigm shift in how we understand the mind. Their collaboration, nurtured by the interdisciplinary environment at Washington University, is gaining attention. Hengen recently presented his ideas at a TEDx talk and earned recognition at a university research pitch competition.

As the scientific community begins to engage with this theory, its potential to transform diagnostics, education, and therapy becomes increasingly clear. The brain’s sweet spot — its critical point — may hold the answers to some of our most pressing neurological challenges.

Read more at sciencedaily.com