Shape-shifting brain cells key to ultra-fast perception

Anyone who has ever tried and failed to swat a fly has experienced the speed of a tiny nervous system. Now, a new review brings together evidence that its secret lies partly in microscopic movements and shape changes within sensory cells and neurons, challenging conventional views of how brains process information.

Often modelled as fixed circuits carrying electrical signals, nervous systems also depend on physical movement. Whole-body motions and tiny changes within individual cells work together to sharpen perception and reduce processing delays.

Led by Professor Mikko Juusola, the international research team proposes a new framework for understanding how these movements work in tandem to power ultra-fast perception.

Many standard models treat sensory cells and neural circuits as physically static systems. Yet animals actively move to gather information, while the structures that sample and process it also move and change shape.

Drawing on visual experiments and biological computer models from earlier studies, the review argues that physical movement at multiple scales dynamically shapes sensory information. Research on insect vision shows that microscopic movements within sensory cells help them sample visual information more efficiently, supporting rapid and precise perception.

Professor Mikko Juusola said: “The key is the combined action of movement at different scales. Animals actively move to sense their surroundings, while the microscopic structures within their sensory cells and neurons also move and change shape. These processes work together to take in more information with minimal delay. We argue that they must have evolved together. This coordination may be what allows sensing, behaviour and thought to stay synchronised as an animal interacts with the world.” 

The review proposes that body movement and cellular shape changes evolved together, helping nervous systems overcome processing limits. This creates a continuous loop in which movement shapes incoming information, cellular adjustments refine it, and brain activity guides the next action.

Professor Aurel Lazar, of Columbia University and a co-author of the review, highlights how sensory signals acquire meaning as they are processed through brain networks. The review argues that semantic information—what signals represent in relation to an animal’s surroundings, memories and goals—plays an increasingly important role in neural coding.

“Fast sensing is only part of the story. Brain networks must also identify what sensory signals represent: which smell is present, which object is approaching, and what this means for the animal’s next action. As information passes through these networks, it is increasingly organised around objects, events and their significance for behaviour.”

Applying these biological principles could ultimately offer new directions for visual prostheses and healthcare, while inspiring energy-efficient artificial intelligence and robotic vision systems such as automated cars that adapt seamlessly to a moving world.