Have you ever pondered over the intricate ways humans move? Or questioned how our brains coordinate and program these diverse actions? In this article, we’ll unravel the fascinating concept of “The Bayesian Brain”, inspired by Professor Daniel Wolpert’s enlightening TED talk.
Read more: Insights from the Bayesian Brain TheoryDelving into Movement Science:
Numerous scientific disciplines tirelessly explore human movement, each endeavoring to unlock the mysteries of the human brain and find practical applications for their discoveries. Professor Daniel Wolpert, both a neuroscientist and an engineer, has notably stood out in this field. In recognition of his pioneering research on computer models predicting brain function in relation to action, he was honored with the prestigious Golden Brain Award in 2010. His captivating TED talk further illuminates this subject, emphasizing the brain’s solution-driven capabilities.
The Brain’s Sole Task: Movement:
According to Professor Wolpert, the primary function of the human brain is to command movements. This spans from controlling major muscles required for walking or running, right down to the delicate facial muscles enabling us to speak and communicate. To underscore the complexity of this function, Professor Wolpert contrasts the human brain with a supercomputer. For instance, while a supercomputer might outsmart a human in a game of chess in determining the best move, the simple act of physically moving the chess piece—a task easily accomplished by a 5-year-old—proves overly intricate for a machine. And if this basic movement is challenging for a computer, imagine the difficulty posed by swifter or more intricate actions, such as cup stacking, demonstrated here: YouTube link.
Decoding Quick and Complex Movements:
So, how can humans perform such rapid and complicated motions? To shed light on this, Wolpert introduces a specific diagram, emphasizing that every action we undertake produces feedback, leading to our subsequent reactions. Consider the game of darts. You aim for the triple 20, but even the slightest muscle tension can deviate the dart. This deviation, termed as ‘Noise’ in the diagram, can also be influenced by the weight of an object (Task) and the feedback processed by nerves (Sensory Feedback). Athletes who masterfully navigate this ‘Noise’ are often top-tier sportspeople.
The Bayesian Brain Simplified:
In our everyday lives, we constantly strive to reduce the effects of this ‘Noise’. To explain this phenomenon, scientists often reference “The Bayesian Brain”, a term predominantly used in robotics and statistics. At its core, the Bayesian Brain represents how our brain manages uncertainties or ‘Noise’. Drawing from Bayesian theory, our brain relies on two information sources to dictate movements: data and memory. It acquires data through our senses, merging it with past experiences stored in our memory.
Tennis Illustrates the Bayesian Concept:
Imagine a tennis player anticipating a ball’s trajectory (Red Zone). From experience, she knows spin might alter its course (Green Zone). Combining her estimation (Belief) with her playing strategy, she decides where to strike the ball (Yellow Zone).
The Challenge of Predicting Movement:
While deducing a move might sound straightforward, the countless potential actions add layers of complexity. Despite these vast possibilities, our body’s movement, influenced by the Bayesian principle, remains surprisingly predictable. With continual training and human evolution, our motions steadily become more optimized.
Relevance in Real-World Scenarios:
The Bayesian Brain offers a comprehensive understanding of athlete movements. While sensory data remains consistent among individuals, seasoned athletes, due to their vast experience, can better anticipate the repercussions of specific movements. Chris van der Togt, a researcher from the Netherlands Institute for Neuroscience in Amsterdam, elaborates on this, emphasizing that our thought processes aren’t merely reflexive responses to external stimuli. Our memories guide our intentions and objectives, influencing decisions over minutes, days, or even years.
Stay tuned for further practical applications of these insights. For a deeper dive, watch Professor Daniel Wolpert’s TED talk here: YouTube link.