Today we look at

*how*the dendritic length of these neurons dictates the frequencies they are most sensitive to. But first we need to understand what the NL does.

(source) |

When you hear a noise, you can tell what direction it is coming from (for the most part).

There are several ways the brain can hone in on the direction of a sound. One of those ways is called the 'inter-aural time difference.' That means the difference between when a sound hits one ear and when it hits the other.

Incidentally, birds like the boring-old-chicken and the pretty-cool-barn-owl are particularly good at sound localization. The NL in these birds is where this computation takes place.

Figure 1a, Wang and Rubel (2008) |

Figure 2a, Wang and Rubel (2008) |

*Biological Cybernetics*, Grau-Serrat et al., (2003) try to answer this question.

"Computational neuroscience is a discipline that aims to understand how information is processed in the nervous system by developing formal models at many different structural scales...The end product of an computational analysis should be a sufficiently specified model, internally consistent and complete enough to enable formal mathematical characterization or computer simulation." Grau-Serrat et. al., 2003I thought these passages from their introduction made an excellent summary of computational neuroscience.

They found a remarkably simple answer:

The lower the frequency, the longer the dendrites need to be to show good time discrimination.

In their computational model, making the dendrites longer generally improved time discrimination, but for every frequency there was a certain dendritic length that was 'long enough'. Adding more dendrite after a certain length didn't improve the time discrimination.

Figure 3, Grau-Serrat et al., 2003 |

In summary, the dendritic gradient of the NL is predicted if the system follws two rules:

- Keep the dendrites as short as possible.
- Make the dendrites long enough to accurately discriminate time differences.

So there you have it, the mystery of the NL dendritic gradient, solved by computational neuroscience.

Note: I know this is a pretty complex system, and I am definitely simplifying. If you know a lot about the auditory brainstem, please don't hesitate to correct/expand on what I've written here in a comment. Also if you don't know a lot about this system and have a question, write it in the comments section and I'll try my best to answer it.

© TheCellularScale

Wang Y, & Rubel EW (2008). Rapid regulation of microtubule-associated protein 2 in dendrites of nucleus laminaris of the chick following deprivation of afferent activity. Neuroscience, 154 (1), 381-9 PMID: 18440716

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