It’s not just an organ. Scientists have found that the shape of the brain is responsible for our thoughts, emotions, and behavior.

The complex human brain contains about 86 billion neurons interconnected by countless connections. For a long time, scientists believed that we needed to study this complex web to decipher the structured patterns that dictated our thoughts, feelings, and actions. But a new study calls that belief into question. According to The Conversation, it shows that the shape of the brain, including grooves, swirls, and convolutions, actually influences our neural activity patterns more than a multitude of connections.

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Traditionally, certain areas of the brain “light up” in response to certain thoughts or feelings. But research has shown that brain activity patterns associated with thoughts and emotions span nearly the entire organ, just as a musical note is produced by vibrations propagated by a violin string.

The connection between form and function emerged when scientists discovered the brain’s natural patterns of arousal supported by its anatomy, called “eigenmodes,” in which different parts of the brain resonate at the same frequency.

Imagine the notes a violin string could play. They arise from the resonant vibrations of the wire, determined by its physical properties such as length, density, and tension. Similarly, the brain has distinctive arousal patterns dictated by its physical and anatomical features. The challenge for the researchers was to determine which of these traits most determined these patterns.

Conventional thinking suggests that labyrinths of brain connections determine its activity. He sees the brain as a collection of different regions, each with a specific function, such as vision or speech, that communicate with each other through fibers known as axons.

An alternative view, embodied in a technique known as neural field theory, deviates from this concept. Similar to the ripple effect in a pond caused by raindrops, cellular excitatory focuses on the continuous movement of waves in the brain. Just as the shape of a pond influences ripples, the three-dimensional shape of the brain creates wave-like patterns of activity.

Comparing these two perspectives, the scientists examined their ability to illuminate more than 10,000 different maps of brain activity. These maps were generated from thousands of fMRI experiments performed while people were performing a variety of cognitive, emotional, sensory and motor tasks.

The authors aimed to interpret each map with its own mods based on brain connectivity and mods based on shape. The surprising finding was that the brain’s own shape modes provided a more accurate explanation for these different activation patterns. Computer simulations have confirmed this close relationship between brain form and function by showing fluctuating activity moving in the brain. The simplicity of this model, which only uses the shape of the brain to limit wave propagation, allowed a better understanding of brain activity than a more complex model that attempts to capture the intricate details of neuronal activity and interconnectivity.

The scientists also found that nearly all of the brain maps examined were associated with activity patterns that spanned nearly the entire brain. This once again refutes the traditional view that brain activity during task performance is limited to separate isolated areas. This suggests that traditional brain mapping techniques may only scratch the surface of the true complexity of brain functionality.

The data collected during the study provides a reassessment of current patterns of brain functioning. It is also important to examine how excitatory waves propagate throughout the brain, rather than focusing solely on signal transmission between individual regions. The metaphor of a ripple in a pool may more accurately represent the large-scale functionality of the brain than a telecommunications network. The research method, borrowed from centuries of physics and engineering research, considers how the structure of a system limits its function as represented by its modes. This approach is unconventional in neuroscience, where sophisticated statistical methods are used to measure brain activity without considering the physical and anatomical underpinnings of these models.

Using their mod, the scientists were able to use physical principles to understand how different patterns of activity are driven by brain anatomy. The ease of measuring brain shape eigenmodes against connectivity data has immediate practical benefits.

“This innovative approach opens new avenues for studying how the shape of the brain influences function during evolution and development, aging and disease,” the authors write.

Previously Focus He wrote about the next generation of interfaces that help people with paralysis communicate with each other. A new development in brain-machine interfaces is giving those suffering from lock-in syndrome a chance to reconnect with the world.