# HG changeset patch
# User Robert McIntyre <rlm@mit.edu>
# Date 1398649959 14400
# Node ID fc116e960f56f495cdc627011203d839aedbb9a0
# Parent  cfbcd2b11087656b9ad2b37858198ede9811c2c9
more elaboration

diff -r cfbcd2b11087 -r fc116e960f56 thesis/cortex.org
--- a/thesis/cortex.org	Sun Apr 27 21:50:25 2014 -0400
+++ b/thesis/cortex.org	Sun Apr 27 21:52:39 2014 -0400
@@ -3216,15 +3216,17 @@
 ** COMMENT Digression: Learning touch sensor layout through free play
 
    In the previous section I showed how to compute actions in terms of
-   body-centered predicates which relied on the average touch
-   activation of pre-defined regions of the worm's skin. What if,
-   instead of receiving touch pre-grouped into the six faces of each
-   worm segment, the true topology of the worm's skin was unknown?
-   This is more similar to how a nerve fiber bundle might be
-   arranged. While two fibers that are close in a nerve bundle /might/
-   correspond to two touch sensors that are close together on the
-   skin, the process of taking a complicated surface and forcing it
-   into essentially a circle requires some cuts and rearrangements.
+   body-centered predicates, but some of those predicates relied on
+   the average touch activation of pre-defined regions of the worm's
+   skin. What if, instead of receiving touch pre-grouped into the six
+   faces of each worm segment, the true topology of the worm's skin
+   was unknown? This is more similar to how a nerve fiber bundle might
+   be arranged inside an animal. While two fibers that are close in a
+   nerve bundle /might/ correspond to two touch sensors that are close
+   together on the skin, the process of taking a complicated surface
+   and forcing it into essentially a circle requires that some regions
+   of skin that are close together in the animal end up far apart in
+   the nerve bundle.
    
    In this section I show how to automatically learn the skin-topology of
    a worm segment by free exploration. As the worm rolls around on the