Intelligent Design

Rats’ whiskers: Another code found

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Discussed in a recent paper:

Did you know that a rat’s tactile sense requires analyzing a 16-dimensional stimulus space? How does that computation fit into a rat’s brain? Trying to simplify in a model what goes on in rat whiskers quickly gets deep into mathematical weeds. Their “generalized linear models” that analyzed pairs of covarying features showed some success. Nevertheless, they admit they have only (so to speak) scratched the surface.

“Coding properties of Vg neurons can be fully quantified only if the stimuli employed span the extent of the full stimulus space. Without claiming to have achieved complete presentation of a naturalistic stimulus space that incorporates the full spatial and temporal structure of natural objects available to an awake animal, the present work takes a significant step toward a more complete understanding of vibrissotactile encoding by relating neural activity to whisker motion in three spatial dimensions.”

It’s clear now (at least) that “individual Vg neurons simultaneously encode multiple features of the stimulus” and that “features are represented across a population and may be extracted by more central neurons that integrate information across many Vg neurons.”

Evolution News, “Rats! Another Code Found in Whiskers” at Evolution News and Science Today (September 16, 2021)

The paper is closed access.

From a 2016 article in Evolution News and Science Today on rats’ whiskers: “The closer you look at a biological phenomenon, the more complex and fascinating it gets. Most people probably figure that their pet dogs and cats use their facial whiskers to enhance their sense of touch. But would you have ever guessed that the twitching whiskers on mammals perform complex algorithms and do predictive coding?”

If only rats were less numerous and more likeable.

One Reply to “Rats’ whiskers: Another code found

  1. 1
    polistra says:

    “Active whisking” is a nice phrase and probably the key to the whole process. Something similar happens in the cochlea, where the muscle-like outer hair cells are constantly reconfiguring the sensory inner hair cells to optimize the signal-to-noise ratio.

    The resultant signal comes mainly from the activity, not the sensing.

    Analog computers used to simulate this type of active feedback with servomechanisms. I don’t think there’s any way to get there with digital software.

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