Used to never get high, now I’m never sober
The secret behind the beautiful songs that birds sing has been decoded and reproduced for the first time.
One of the great challenges in neuroscience is to explain how collections of neural circuits produce the complex sequences of signals that result in behaviours such as animal communication, birdsong and human speech.
Among the best studied models in this area are birds such as zebra finches. These enthusiastic singers produce songs that consist of long but relatively simple sequences of syllables. These sequences have been well studied and their statistical properties calculated.
It turns out that these statistical properties can be accurately reproduced using a type of simulation called a Markov model in which each syllable is thought of as a state of the system and whose appearance in a song depends only on the statistical properties of the previous syllable. (…)
But other birds produce more complex songs and these are harder to explain. One of these is the Bengalese finch whose songs vary in seemingly unpredictable ways and cannot be explained a simple Markov model. Just how the Bengalese finch generates its song is a mystery.
Until now. (…) Instead of the simple one-to-one mapping between syllable and circuit that explains zebra finch song, they say that in Bengalese finches there is a many-to-one mapping, meaning that a given syllable can be produced by several neural circuits. That’s why the statistics are so much more complex, they say.
This type of model is called a hidden Markov model because the things that drives the observable part of the system–the song–remains hidden.
