How our brain manages the perfect balancing act

Our brain is remarkable for its unique ability to process information efficiently and to adapt flexibly to changing challenges. But how does it manage this balancing act between structure and chaos?

One central idea regarding this question is the concept of criticality. It describes a special state in which the brain operates on a fine line between strict structure and complete chaos. In this state, it can react optimally to external stimuli, transfer information efficiently and switch flexibly between different tasks.

Our brain is a perfect data machine

A more recent approach views our brain as a highly optimized system that stores and transmits information without wasting energy. Like a well-compressed file format, it reduces redundant signals and uses its resources with the utmost precision.
Until now, criticality and efficient coding were considered separate principles. However, a new study by the Dresden University Medicine shows that they could be more closely linked than previously thought.

The neural network

The team of researchers used a mathematical model to simulate a neural network that mimics the functioning of real brain cells. Unlike in previous studies, the network was not directly geared towards a critical state, but optimized to process information as efficiently as possible – similar to our brain in everyday life.

One key experiment involved varying the level of noise in the network. “Noise” refers to the amount of random interference in the system. The researchers hoped to find out how these disturbances affect the capabilities of the network.

The central question

Does the network develop signs of criticality when it is designed purely for optimal information processing?

The results of the simulation were unequivocal:

• Medium noise level, maximum performance: The network showed the best information processing at a moderate level of interference. At the same time, typical signatures of criticality were observed, including so-called “neural avalanches”. These cascades of activity follow a characteristic distribution of size and frequency.
• Too much or too little noise is detrimental: In the case of too low a noise level, the neurons synchronized too much, which limited the flexibility of the network. On the other hand, too much noise led to chaotic, inefficient activity patterns.

So peak performance and criticality emerged simultaneously – at a point of balance where precision and flexibility were perfectly aligned.

What do these results mean for our understanding of our brain?

The study provides innovative insights into the fundamental mechanisms of brain function. It answers a central question: Why does our brain show signs of criticality? The results suggest that criticality is not a random phenomenon, but a natural side effect of optimal information processing.

Evidently, our brain has evolutionarily adapted  to this precise balance between structure and chaos. This state not only enables efficient information processing, but also prepares our brain to flexibly respond to changing demands.

These findings could help to improve our understanding of how our brain works and inspire new approaches for the development of artificial intelligence and neural networks.

Contact:
Jun-Prof. Dr. Shervin Safavi
Computational Neuroscience
Clinic for Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden
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+49 351 45817367