when bleeding edge science gets it wrong

Bleeding edge science isn't always right, especially when it tries to figure out free will and how we think.

Everybody talks about the cutting edge when they want to say that something is the latest and greatest thing in science or technology. Fewer people talk about the bleeding edge, those experimental ideas and what ifs that could either unlock new potential fields of study or fail as dead ends. General relativity was one example of a once bleeding edge theory that survived and thrived. On the other hand, studies about free will — or rather, the lack thereof — by neuroscientist Benjamin Libet, is an example of a proposal that fared much worse…

One of the biggest problems in studying the human brain is the difficulty in proving correlation and causation in such a complex system, and this is exactly the mistake he made when researching decision making…

Crucially, the RP came a few tenths of a second before the volunteers said they had decided to move. Libet concluded that unconscious neural processes determine our actions before we are ever aware of making a decision.

Now, you might have noticed a little problem with his experiment. Where was the control? How exactly does a burst of neuron activity prove that a decision was made automatically? Neurons fire for all sorts of reasons so to immediately assign a deep meaning to one pattern of electrical activity is a little premature at best. After 25 years, a duo of scientists from New Zealand decided to go back and add the control to Libert's experiment to figure out if the RP he detected was really tied to decision-making.

While there was an RP before volunteers made their decision to move, the signal was the same whether or not they elected to tap. Miller concludes that the RP may merely be a sign that the brain is paying attention and does not indicate that a decision has been made.

Maybe the reasoning in the second study is a little stretched as noted by some observers and the RP really is the signal of a brain preparing for movement, but it does show that there's no tangible relationship between a decision and the signal. Simply put, Libet jumped to a sweeping conclusion that wasn't supported by the data he had. Oh well, happens to the best of us I suppose, as long as it's eventually caught and corrected.