AI Is Helping Scientists Explain the Brain
The brain is often called a black box but any neuroscientist who has looked inside knows that’s a sobering understatement. Technological advances are making our neural circuitries increasingly accessible, allowing us to closely watch any number of neurons in action. And yet the mystery of the brain only deepens. What’s the meaning embedded in the collective chorus of spiking neurons? How does their activity turn light and soundwaves into our subjective experience of vision and hearing? What computations do neurons perform and what are the broad governing principles they follow? The brain is not a black box—it’s an alien world, where the language and local laws have yet to be cracked, and intuitions go to die.
Could artificial intelligence figure it out for us? Perhaps. But a recent recognition is that even our newest, most powerful tools that have achieved great success in AI technology are stumbling at decoding the brain. Machine learning algorithms, such as artificial neural networks, have solved many complex tasks. They can predict the weather and the stock market or recognize objects and faces, and crucially, they do so without us telling them the rules. They should, at least in theory, be able to learn the hidden patterns in brain activity data by themselves and tell us a story of how the brain operates. And they do brain.
