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To Predict the Future, the Brain Uses two Clocks:
That moment when you step on the gas pedal a split second before the light changes, or when you tap your toes even before the first piano note of Camila Cabello's "Havana" is struck. That's anticipatory timing.
One type relies on memories from past experiences. The other on rhythm. Both are critical to our ability to navigate and enjoy the world.
New University of California, Berkeley, research shows the neural networks supporting each of these timekeepers are split between two different parts of the brain, depending on the task at hand.
"Whether it's sports, music, speech or even allocating attention, our study suggests that timing is not a unified process, but that there are two distinct ways in which we make temporal predictions and these depend on different parts of the brain," said study lead author Assaf Breska, a postdoctoral researcher in neuroscience at UC Berkeley.
The findings, published online in the Proceedings of the National Academy of Sciences journal, offer a new perspective on how humans calculate when to make a move.
"Together, these brain systems allow us to not just exist in the moment, but to also actively anticipate the future," said study senior author Richard Ivry, a UC Berkeley neuroscientist.
[...] Both groups viewed sequences of red, white and green squares as they flashed by at varying speeds on a computer screen, and pushed a button the moment they saw the green square. The white squares alerted them that the green square was coming up.
In one sequence, the red, white and green squares followed a steady rhythm, and the cerebellar degeneration patients responded well to these rhythmic cues.
In another, the colored squares followed a more complex pattern, with differing intervals between the red and green squares. This sequence was easier for the Parkinson's patients to follow, and succeed at.
"We show that patients with cerebellar degeneration are impaired in using non-rhythmic temporal cues while patients with basal ganglia degeneration associated with Parkinson's disease are impaired in using rhythmic cues," Ivry said.
How about that? Background music can be helpful for concentration.
(Score: 2) by darkfeline on Tuesday December 04 2018, @08:17PM
Humans don't adapt to new patterns very well either. Most humans aren't capable of very much inference and aren't very trainable either.
We don't have a damn clue how our mind works, and we don't have a damn clue how artificial neural networks work either.
I find a lot of smart people can't avoid the subconscious feeling that there's something "special" about human intelligence, like there's a kind of "soul" behind them.
Spoilers, there's not. It's just a matter of building a big enough neural network and training it with the right environment and interfaces, and some natural/artificial selection, and time. It took evolution millions of year, I'm sure we can replicate it given a millennium if we don't destroy ourselves first.
Intelligence is in the eye of the beholder. We observe some inputs and outputs, and we call some of those intelligence and some of those not.
If a robot only says "Welcome to Corneria", that's not intelligence. If an AI tasked with surviving a game as long as possible figures out it can just pause the game, that looks an awful lot like what a young boy would do, experimentation followed by an "Ah ha!" moment and "technically I completed the task".
"But an AI trained to do X can't do Y!" Most humans can't either.
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