With Java enabled you will find colored dots moving about below. (There is a Youtube video alternative beside it for viewers without Java.) The
dots show the origin of autism as described in
The Sparseness Adaptation Syndrome.
( Return to Introduction )
Each colored dot below stands for a person, family
or tribe (more accurately, their genes). All the dots are basically the
same, making similar random movements. The time scale is arbitrary. The
colors show histories -- the average number of neighbors near
each dot, figured over the dot's lifetime. The blue dots () show people who have had few neighbors on average.
Autistic traits collect in these loners because greater distance from
neighbors means smaller demand for social ability. This frees genes
and brain parts used in social contact to shift to other uses -- to
object-related uses, for example.
The simulator buttons should be
fairly obvious. Click away! And think. Beside the applet is a narrated Youtube video of the applet running. (Turn on your speakers before clicking it.) Reload this page to restart the video. Click here to watch the video directly on Youtube.
Things to Notice
Click NEW to start a fresh history.
Notice the dots changing from red to green to
blue: Even where individuals are the same their histories come to
differ radically, and in a way that fosters autism.
see that the green and blue dots usually appear first near the
population surface? Which is likely to need social ability more often, a
red "dot" or a blue one?
Notice that a dot's color does not change
instantly when it enters a new level of sparseness or crowding: A dot's
color depends not just on where it is, but on its entire evolutionary
Do the blue dots always stay in sparse areas, or can they
exist in crowds? What might this have to do with autism today?
dots often or ever change back, for example from green to red?
that blue dots, unrealistically, prevail in the long run. What realistic
changes in the model might alter this? (For a clue see the note below on
All the dots here are like clones, with identical
behaviors on average. Their color shows only the history of their
distance from neighbors. However, organisms that actually exist are
adapted to their circumstances, as the paper explores in some depth.
If organisms are adapted to their circumstances, and if long-term
adaptations show in genes, then the circumstance of prolonged distance
from neighbors will show in genes. For this reason, when the model
is taken to represent events on the scale of thousands and millions of
years the dot colors do represent expected genetic differences between
gene pools. The spectrum of red, green and blue dot colors thus also
shows an expected autism spectrum. Perhaps the most important point
illustrated by the model is that even in a population of identical
individuals symmetry is broken: The sameness is unlikely to last,
and an autism spectrum is the expected result.
Surely many autistic people could
not survive at rugged frontiers. Profound autism appears to be, if
anything, maladaptive. Doesn't this contradict the Sparseness-Adaptation Theory of
It is possible to make up thousands of Just So stories about adaptation.
What makes the Sparseness-Adaptation Theory of Autism different from any of these?
to this theory shouldn't there be a high incidence of autism among Inuit
people in the Arctic? Ask
Sparseness-Adaptation Theory of Autism predicts gender-related behavioral
differences on average. Doesn't this make it a sexist theory? Ask
the Sparseness-Adaptation Theory of Autism just more Godless Darwinism? Ask
The model is kept simple in order to underscore
that autism's evolution need not depend on complexities.
Some of the
realistic complications one might add to the model, for example giving
dots different mobilities and giving areas varied capacities to sustain
life can actually make autism more pronounced, as later simulations may
Later simulations may also allow dot histories to affect their
behavior, and provide more explicitly for birth, death and gene flow
between pools. Some of these changes can increase population stirring
and thus moderate effects of the population surface, as discussed in the
Is any realistic change in the model likely to give all
gene pools identical neighbor-distance histories?
The starting distributions and all the
individual movements are Gaussian-distributed. All 100 dots have the
same chances of moving any particular distance or direction.
distance and time scales are not fixed: The movements can stand for
movements of a few feet or thousands of miles, occurring in moments or
Each dot neighborhood is about 5 times the diameter of a
dot. Arithmetic averaging of neighbor number is computed over each dot's
lifetime. Fixed square bins are used in the
computation. Click bins to view them along with color-coding showing
the local population density. (The tiny nameless
button exposes and hides other buttons: hist displays a distance-from-center
histogram, and loop starts new
simulations every two minutes or so at the middle speed.)
Using fixed bins introduces
errors that are most
pronounced at the start of a simulation, before the dots have had a chance to move
between bins. To minimize these artifacts, all the dots are given
identical starting histories roughly equivalent to exposure to the mean
initial population density for the average amount of time it takes a dot
to wander to a neighboring bin -- about a second at the middle
A fast nearest-neighbor algorithm that capitalized on
the similarity of successive dot positions would help. (Please contact author if you know of one!)
Website text and applet Copyright 2001 - 2012 by Gregory B. Yates.
All Rights Reserved.