When taking simple decisions, neurons in the brain apply the same statistical trick used by Alan Turing to help break Germany's Enigma code during World War II, a new study reveals.
As depicted in the film "The Imitation Game," Alan Turing and his team of codebreakers devised the statistical technique to help them decipher German military messages encrypted with the Enigma machine.
Finding pairs of messages encrypted with the same Enigma settings was critical to unlocking the code. Turing's statistical test, in essence, decided as efficiently as possible if any two messages were a pair.
"Neurons in the brains of rhesus monkeys do the same thing when faced with decisions," said Michael Shadlen, professor of neuroscience at Columbia University.
In his study, Dr Shadlen and co-first authors Shinichiro Kira and Tianming Yang recorded the activity of neurons in the brains of two monkeys as they made a simple decision.
To make the correct decision - the one that brought a reward - the monkeys had to weigh different clues encoded in the eight symbols that flashed onto the screen.
The monkeys had to think fast. Each symbol appeared for only 250 milliseconds.
Each symbol contributed a positive value (reward is in the left spot) or negative value (reward is in the right spot) to the accumulated evidence, which was represented in the neuron's firing rate.
More reliable symbols had a larger impact on the firing rate than less reliable symbols.
Just as in the Turing's code breaking, once a positive or negative threshold was reached, the decision was deemed complete and the monkey indicated its choice.
Assuming that humans have the same capabilities, it means our brains are weighing probabilities and making rational decisions in very short periods of time.
"These types of decisions are mostly unconscious on our part. They are decisions like, 'I'm going to pick up a book,' or 'I'm going to walk toward the left of the coffee table, not the right,'" Dr Shadlen added.
"We make lots of these decisions every day, and it turns out, we are making them by using the laws of probability in a way that statisticians think is optimal," the authors concluded.
The results were detailed in the journal Neuron.
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