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From YouTube: DevoWorm #17: Sphere contour selection, 13 open problems, cell migration network, sensory evolution
Description
Point cloud contour selection for embryo modeling, 13 open problems in theoretical biology and biomathematics, the role of Synaptopodin in cell migration and dynamic networks (towards tensegrity), and a community question on the evolution of sensory systems and associated cell biology. Attendees: Susan Crawford-Young, Karan Lohaan, Richard Gordon, and Bradly Alicea (Slack question from Jesse Parent)
A
A
A
B
B
C
Yeah
I'll
just
give
me
two
minutes.
Okay,
I
tried
do
different
things.
You
know
for
the
outlines
that
I'm
currently
working
with
so
to
generate,
you
know,
outlines
for
more
images.
More
than
just
eight
outlines.
You
know
I
I'm
trying
a
different
method
in
which
you
know.
Let's
say
there
are
two
outlines
of
the
interplay
and
I'll
show.
The
contour
is
my
screen.
B
C
Yeah
so
like
these
are
the
contours.
You
know
that
I
was
that
I'm
using
you
know
to
generate
my
3d
model,
so
what
I'm
doing
is
to
generate
more
of
these
contours.
You
know
I'm
trying
to
it's
like
I'm,
using
something
similar
to
an
average
function.
You
know
like
if
there's
a
function,
one
and
there's
a
function
two
so
it
to
compute.
Let's
say
another
contours
between
two
contours
that
are
there.
C
You
know
something
like
that
to
generate.
You
know
more
information,
more
more
points
for
the
3d
cloud,
3d
point
cloud:
you
know
that
I'll
be
generating,
so
it
uses
a
similar
transformation
formula.
You
know
like
if
I
want,
let's
say,
10
contours
between
two
particular
types.
So,
if
I
want
let's
say
this
these,
these
are
too
similar.
C
C
So,
for
that
you
know
I'm
using
some
more
functions
to
just
improve
the
you
know
to
smoothen
the
model
more.
You
know,
instead
of
just
two
blobs
of
images
put
together
it
and
they're
like
two
three
more
things
that
I'm
trying
out,
one
is
optical
flow
like
there
are
existing.
You
know,
3d
models
that
rely
on
optical
flow
diagrams.
So
it's
like
you
feed
the
image
to
a
neural
net,
and
you
know
it
gives
out
an
optical
flow
map
of
the
image.
C
Yeah
something
something
like
this-
you
know
so
the
object
that
is
moving
the
rate
at
which
it
is
moving.
You
know
the
motion
displays
the
pixel
intensity,
so
if
it's
like
really
brightly
colored
in
a
particular
way,
it's
going
to
you
know
show
the
particular
pixel
density.
So
this
is
another
thing.
You
know
that
I
I'm
trying
to
try
out
with
this
model.
C
After
that,
I
you
know,
generate
the
proper
number
of
like
to
smooth
in
all
these
contours
that
are
there
so
I'll
be
moving
on
to
that
next,
so
I'm
going,
the
thing
is
my
end.
Semester
exams
were
going
on
they're
still
going
on.
I
think
they'll
be
ending
by
16,
so
I'll
be
getting
more
time,
so
I
was
just
trying
this
also
because
some
exams
that
did
just
so
yeah
this
is
the
current
state.
C
Yeah
they're,
the
these
contours
make
up
the
3d
point
cloud
like
this
is
actually
a
number
of
points
that
you
know
I'm
using
further
down
here
to
generate
my
3d
model.
So
this
numpy
array
is
converted
from
x
y
to
x,
y
z
coordinates
using
a
transformation,
another
transformation
formula,
and
then
we
get
the
final
output.
So
the
thing
is,
this
thing
still
needs
some
more
contours.
C
So
for
that
you
know
I'm
generating
average
of
averages
of
these
like
two
three
adjacent
point
twos
so
just
to
you
know
smooth
in
the
model
that
is
there
otherwise
that
same
you
know
like
we
have
two
images:
plastic
together
and
the
from
one
particular
side.
You
know
it's,
it's
kind
of
it
looks
as
if
you
know
it's
been
stitched
together,
something
like
to
avoid
that
issue
altogether
I'll
be
using
this.
B
C
Yeah
yeah,
exactly
exactly
so
I'll,
be
having
like
more
than
like
at
least
I'm
I'm
currently
thinking
of
using
maybe
around
32
contours
like
between,
like
four
contours
between
each
contour,
that
is
existing
so
and
let's
see
how
that
turns
out,
I'm
still
trying
to
apply
the
proper
normally
function.
You
know
the
average
like
how
to
get
from
this
function
to
that
function
and
four
steps.
C
C
D
B
C
E
B
B
I
just
have
some
names
here
and
some
topics,
so
the
idea
is,
we
have
introduction
type
of
developmental
network,
so
we
have,
like
you
know,
just
a
bunch
of
different
types
of
developmental
network
papers
that
would
profile
this
and
again.
These
are
just
like
names
that
I've
put
in
here,
as
is
you
know,
proposing
some
content,
so
we
can
see
what
it
looks
like.
B
B
B
I
think
it's
yeah,
I
think
it's
just
you
me
and
susan
who
aren't
starred.
So
this
is
the
sort
of
way
I'm
going
to
keep
track
of
this
okay
and
then
using
networks
to
resolve
dilemmas.
That's
the
last
part
which
would
be
kind
of
like
different,
open
questions
with
networks.
So
you
know
it's
not
as
focused
on
networks,
but
it's
maybe
you
how
to
use
networks
to
resolve
dilemmas,
and
in
that
category
I
put
dick's
idea
about
a
call
for
a
modern
test
of
donald
williamson
species,
fusion
hypothesis.
B
B
B
B
B
So
then,
that
would
be
probably
something
targeting
that
I
mean
there
could
be
like
a
specific
paper,
or
I
mean
the
way.
Some
of
these
special
issues
usually
work
is
they
give
like
a
an
overview
and
they
say
well,
we
cover
this
topic
and
that's
this.
These
papers
cover
this
topic,
but
yeah.
It
would
be
good
if.
B
E
B
B
B
E
B
A
A
A
G
A
A
B
B
B
So
this
is
the
list
that
I
have
well.
He
sent
me
a
list
of
like
13
ideas
or
questions.
I
guess
some
of
these
are
kind
of
deal.
I
kind
of
I
think
we're
addressing
now,
but
some
are
not
kind
of
kind
of
outstanding
for
a
while.
So
you
know
it's
good
to
revisit
these
and
see
where
we
are
with
them
and
maybe
get
some
ideas
of
what
you
know
where
we
might
go
with
this.
B
So
the
first
one
is
our
wolfram
prep
wolfram
patterns
closed
experience
with
one
deizing
lattices,
so
we
talked
about
the
izing
lattices,
I
think
in
january,
and
we
talked
about
this,
but
we've
never
really
gotten
on
with
it.
I
know
that
tom
expressed
some
interest
in
it.
Has
tom
contacted
you
dick
about
that,
since.
E
B
B
B
B
As
you
know,
if
you
were
to
unscroll
the
shell,
it
would
look
like
you
know
it
would
be
flat
and
you
could
see
the
pattern
and
then
you
look
at
that
pattern,
and
you
say
these
rules
follow
wolfram
patterns
and
these
are
the
cellular
automata
patterns
that
we
know
from
the
the
literature,
wolf
wolfram's
book
on
a
new
kind
of
science,
but
also
the
broader
literature
on
cellular
automata
rules,
and
so
this
is
something
that
we've
not
really
been
able
to.
You
know
get
a
really
good
result
on.
B
B
E
E
Yeah,
that's
an
interesting
part.
The
other
question,
of
course,
is
you
know
they.
They
have
pretty
patterns
which
look
like
some
of
the
wolfram
patterns,
but
do
they
really
follow
a
particular
that
particular
rule?
Because
if
they're
following
a
particular
rule,
it
would
seem
from
the
pattern
you
could
figure
out?
B
E
B
B
E
It's
done
with
transmission
electron
microscopy,
so
the
dark
is
the
silica
and
the
light
is
the
holes
in
between
the
silica
and
you
can
see
three
levels
of
structure
here.
What
are
called
the
straya?
Well,
in
the
middle,
you
see
the
the
midline
of
the
rafe,
except
this.
These
are
aberrant
ones
and
they
have
aberrant
rapes
like
this
one
and
they're
kind
of
interesting,
in
that
the
patterns
look
like
they
run
into
each
other.
E
They
come
off
of
the
reef
and
run
into
each
other
they're,
also
little
cross
dryer,
which
one
could
possibly
pick
up.
So
the
image
processing
problems
first
to
just
segment
this
into
the
aberrant,
wraith
astraya
and
maybe
the
cross
dryer
okay.
So
we
know
where
all
of
that
tomorrow
and
you
can
get
some
statistics
on
and
there
are
I
have
these
were
made
by
ryan
drumm
about
60
years
ago.
E
E
G
E
E
D
E
E
E
Now
another
problem
which
I
listed
there
is
this
one
g:
this
is
a
center
called
centric
diagram
and,
what's
weird
about
it,
is
that
some
of
the
striats,
the
straya,
are
in
groups
and
in
each
group,
they're
parallel
to
one
another
yeah
and
the
question
is
what
on
earth
rules
could
you
possibly
be
using
there
to
make
such
a
structure?
It's
the
only
picture.
I've
ever
seen
of
this
type.
E
B
D
B
B
E
D
B
E
B
B
E
E
E
B
A
I
was
just
looking
at
a
paper
about
the
corners
of
epithelial
cells
and
that's
where
you
get
a
huge
clump
of
actin
and
and
that
actually
moves
we'll
move
along
the
sound
as
so
you
get
two
corners
coming
together
and
the
other
ones
aren't
necessarily
affected.
Did
I
send
you
the
paper
rattling?
I
don't
know.
B
E
E
A
A
E
B
E
B
B
E
E
A
B
Yeah
so
then
the
last
four
projects
are,
you
know
this
williamson's
mosaic
or
organism
hypothesis.
This
is
another
bioinformatics
project
or
related
project,
and
then
there's
do
crack.
Diatom
valves
indicate
potential
pre-stress,
that's
probably
some
sort
of
image
processing
or
getting
making
inferences
from
image
processing.
E
B
E
B
E
E
E
B
E
E
B
D
E
Okay,
okay,
the
the
question
here
is,
if
I
wear
a
few
a
week,
say
a
week's
worth
of
shirts.
They
get
all
mixed
up
and
when
I
hang
them
up,
I
hang
them
so
that
I
won't
use
them
for
a
while.
So
I
put
them
to
the
right
hand,
side
of
the
closet
and
take
only
the
ones
on
the
left-hand
side,
and
this
led
to
an
interesting
question
at
least
interesting
to
me.
I
can't
find
any
answers
to
it,
and
that
is
if
you
have
a
line
of
objects,
a
number
of
them.
E
B
E
B
B
E
B
G
B
B
B
The
first
structure
is
formed
by
retrograde
flow
of
synaptopodin,
initiated
at
the
apical
junction,
creating
sarcomeric
stress,
fibers
that
lie
parallel
to
the
junction
and
insert
into
junction
complexes
of
the
apical
plane
retrograde
full
of
synaptic.
Potent
is
also
seen
at
veniculum
decorated,
basal
junctions.
So
this
is
this
synaptic
potent.
I
guess
it's
moving
around:
either
it's
flowing
or
moving
around.
A
If
you
go
to
the
very
end
of
the
paper,
they
have
have
some
pictures
of
of
the
junctions.
Basically,
the
cells
fit
together
and
they're
sort
of
the
gonna
are
larger
there.
They
are,
and
at
the
junctions
of
the
cells
at
the
corners,
you
can
see
where,
where
they've
pointed
out
the,
what
is
it
called?
It's
enough,
synaptopodin
synaptic
potent
complexes
and
when
a
cell
dies
in
the
middle
of
other
cells,
it's
a
confluent
tissue,
and
so
it
it
stays
together
like
it.
B
A
B
B
A
B
B
Yeah
yeah,
I
know
what
you
mean:
okay
yeah.
This
is
this
is
nice,
so
if
we
go
back
up
to
the
abstract,
their
findings
yeah,
so
that
that's
what
they
mean
by
this
first
part,
I
just
wanted
to
give
peop.
You
know
give
like
a
visual
understanding
of
it.
So
the
contractions
of
apical
stress
fibers,
is
associated
with
clustering
of
membrane
complexes
by
a
cyan
synaptic
potent
linkers.
So
that's
what
we're
seeing,
whereas
contractions
of
stress,
fibers,
inserted
at
the
apical
junction
by
a
head-on-synaptic
potent
linkers
results
in
junction
shortening.
B
So
there
are
changes
in
the
geometry
due
to
the
synaptopodin
upon
junction
maturation,
apical
stress
fibers
are
disassembled
in
mature
epithelial,
monolayer,
motorized
contractomere,
complex,
capable
of
walking.
The
junction
is
formed
at
junction,
vertices
and
tractomeer
motility
results
in
changes
in
junctional
length,
altering
the
overall
shape
of
the
cell
and
packing
geometry.
B
E
G
E
B
B
B
E
E
A
E
A
A
Yeah
that
might
make
another
paper
for
the
cell
cells
issue
yeah
and
and
there's
a
difference
between
short
cells
like
skin
cells
and
tall
columnar
cells
in
their
mechanical
reaction
to
things
I
even
I
have
a
paper
that
I
found
on
oh
okay,
so
I'm
looking
for
that.
Well
look
up
papers
on
wound
healing!
I
think
you'll
find
hundreds
of
them
yeah,
okay,
yep,
good
idea,
yeah!
Okay,
yes,.
B
B
B
B
So
my
answer
to
him
was:
this
is
quite
hard
to
approach
in
a
comprehensive
way
because
there's
so
much
diversity.
The
best
way
to
do
this
is
to
pick
a
specific
group
of
organisms
and
a
specific
sensory
system.
As
for
the
analog,
slash
discrete
distinction,
discrete
being
another
word
for
digital,
there
actually
are
different
modes
of
neural
transmission
and
intracellular
communication.
That
can
be
understood
using
that
lens,
I'm
going
to
put
together
some
resources
on
this.
So
this
I
think
we've
talked
about
the
different
modes
of
neurotransmission
in
this
group.
B
This
is
a
review
by
t
ryan
gregory,
who
does
a
lot
of
stuff
on
genomes
and
he
wrote
a
paper
back
in
2008.
This
is
evolution,
education
and
outreach.
So
this
is
a
nice
sort
of
introductory
article
education,
oriented
and
talks
about
the
evolution
of
complex
organs.
So
this
is
just
a
very
broad
overview
of
complex
organs
and
how
they
evolve.
B
B
And
so
you
know
when
people
are
trying
to
explain
the
origins
of
different
things
in
the
tree
of
life
and
they
had
to
kind
of
hypothesize.
They
ended
up
hypothesizing
on
common
ancestry,
and
then
you
know
people
had
to
take.
You
know
anatomical
evidence
and
compare
it
and
then,
when
we
got
genomic
evidence,
it
became
a
little
bit
easier
to
find
homologies
and
things
like
that.
B
Deep
homologies,
because
you're
looking
sometimes
across
multiple
taxa
and
multiple
plates,
so
150
years
of
scientific
investigation
has
yielded
a
conceptual
framework,
abundant
data
and
a
range
of
analytical
tools
capable
of
addressing
this
question.
This
article
reviews
the
various
direct
and
indirect
evolutionary
processes
that
contribute
to
the
origins
of
complex
organs.
So
they
use
the
evolution
of
eyes
in
this
as
a
case
study
and
addresses
a
lot
of
the
common
misconceptions
about
complex
organ
evolution.
B
Still,
while
few
non-specialists
have
trouble
acknowledging
small-scale
evolutionary
processes,
such
as
the
evolution
of
antibiotic
resistance
within
populations
of
bacteria,
they
often
remain
uncertain
as
to
how
similar
mechanisms
could
account
for
complex
structures
such
as
eyes
and
wings,
and
so
there's
a
fair
amount
of
literature
on
this.
The
eyes,
of
course,
being
part
of
the
brain,
the
wings
being
another
example
of
this
sort
of
you
know
evolutionary
diversification.
B
So
this
kind
of
goes
over
the
evolution
of
organs
complex
as
complex
systems,
so
this
paper
is
not
about
complexity
per
se,
but
about
the
evolution
of
complex
organs,
biological
structures
with
several
intricate
integrally,
interacting
parts
that
function
in
a
sophisticated
manner.
So
the
eye
is
actually
very
famous.
B
So
direct
adaptation
by
natural
selection,
so
darwin
famously
noted
that
if
it
could
be
demonstrated
that
any
complex
organ
existed,
which
could
not
possibly
have
been
formed
by
numerous
successive
slave
modifications,
my
theory
would
absolutely
break
down.
And
of
course
this
is
something
that's
been.
B
B
So
this
is
something
that
we
have
to
remember
is
that
it's
not
so
much
that
there's
this,
it's
just
that
they're
related
by
descent.
It's
that
natural
selection
is
actively
acting
in
every
lineage
to
modify
these
things.
This
is
why
you
have
such
a
diversity
of
eyes,
because
you
have
a
diversity
of
conditions
under
which
the
organisms
exist.
There
are
diversity
of
historical
contingencies
that
lock
certain
phenotypes
in
over
others,
and
then
you
know
you
observe
this
diversity
in
the
natural
world
and
you
observe
sort
of
the
endpoints
of
that
process.
B
B
Here
of
how
gene
duplication
acts
to
as
an
underlying
mechanism
for
this
diversification,
you
get
gene
duplication
and
then
you
get
the
divergence
of
different
clades
or
lineages,
and
then
they
have
so
on
this
lineage.
Here
you
have
a
gene,
duplication
here
and
then
two
here
and
then
something
in
the
tetrapods
clade,
that's
specific
to
that
clade.
B
B
This
is
from
another
paper
here,
where
they
talk
about
how
there's
a
progression
of
mutations
that
occurs
on
this
tree
and
it
results
in
different
types
of
of
phenotype.
But
it's
not
just
gradual
change.
It's
that
these
mutations
can
change
the
way
of
the
the
complex
trig
functions.
So
this
is
a
complex
trait
this
ancestral
corticoid
receptor,
and
so
you
can
introduce
a
number
of
mutations
at
different
sites
and
you
can
get
different.
You
can
get
different
outcomes.
B
For
example,
this
s106p
mutation
goes
from
the
ancestral
corticoid
receptor
to
something
that
only
binds
doc,
which
is
this
thing
here.
Then
the
l
one
one
one
q
mutation
can
be
added
to
that
and
it
was
it
results
in
a
more
general
receptor,
so
doc
and
cortisol
can
both
bind
to
this
receptor
now.
What's
interesting
is
that
you
can
go
down
another
path
and
you
can
find
that
you
can
actually
have
a
mutation
that
takes
this
ancestral,
corticoid
receptor
and
turns
it
into
sort
of
a
null
receptor.
B
Nothing
binds
to
the
receptor,
so
it
doesn't
really
have
a
function,
but
it
will
maybe
stick
around
and
you
might
encounter
another
mutation,
this
s106p
mutation,
when
that
mutation
is
added
to
this
genotype.
Here
you
end
up
with
the
same
genotype
or
the
same
phenotype
that
you
would
have
through
this
pathway.
So
you
can
see
that
there's
this
convergent
evolution
with
well,
actually,
you
can
have
the
mutations
in
a
little
bit
different
order
and
they
result
in
the
same
phenotype.
B
But
you
have
this
situation
where
it
becomes
a
specialized
thing
and
then
a
generalized
thing
and
then
something
that's
null
and
then
a
generalized
thing.
So
you
have
these
different
pathways
of
evolution
that
can
be
observed,
and
so
these
are.
This
is
a
hormone
receptor
pair
example,
but
this
also
works
for
the
eye
and
then
there's
this
idea
of
acceptation,
which
is
where
you
have
sort
of
things
that
are
used
for
other
things.
B
B
As
has
been
pointed
out
many
times,
a
rudimentary
version
of
a
wing
could
not
be
useful
in
flight
because
it
would
be
unable
to
generate
sufficient
lift
only
when
the
wing
reached
a
sufficient
size
and
strength.
Could
it
be
useful
for
enabling
powered
flight,
meaning
the
natural
selection
could
not
favor
variants
within
a
population
on
the
basis
of
flightability
alone
during
the
early
stages
of
wing
evolution.
B
So
you
know
to
get
this
initial
trait.
You
know
you
wouldn't
necessarily
have
it
serving
the
function
of
flight,
but
it
would
serve
a
different
purpose,
so
it
had
a
primary
adaptation.
So
bird
feathers,
for
example,
probably
originated
for
thermal
regulation,
and
so
you
know
the
rudimentary
wings
may
have
been
useful
for
other
things
and
then
eventually
those
things
combined
and
form
something
that
was
suitable
for
flight.
The
same
thing
with
bats
in
bats.
Early
skin,
flaps,
probably
would
have
been
functional
for
gliding,
but
not
empowered
flight
and
insects
has
been
hypothesized.
B
That
early
wings
were
used
for
skimming
across
the
surface
of
water,
and
then
you
add
on
other
adaptations
or
other
mutations
to
the
genotype,
and
you
end
up
with
this
complex
phenotype,
that's
capable
of
doing
something
and
then
we're,
of
course
we're
looking
at
this
from
the
modern
day.
So
we're
seeing
the
bird
fly,
we
think
well,
the
wings
were
directly
selected
on
to
adapt
for
flight
and
that's
actually
probably
not
the
case.
B
So
this
is
something
worth
keeping
in
mind,
and
so
this
is
again
this
kind
of
goes
through
excitation,
secondary
adaptation,
there's
also
scaffolding,
so
many
organs
having
been
built
up
in
overall
complexity
by
direct
adaptation,
exception
and
collage
and
further
specialize
their
secondary
adaptation
exhibit
a
level
of
integration
to
the
point
that
their
components
are
interdependent
on
one
another.
So
this
is
an
example
of
scaffolding.
B
You're
just
building
one
trade
onto
other
traits
and
again
this
is
sort
of
this-
is
historical
contingency
in
action
where
you're
building
upon
different
traits
and
you're
building
upon
traits.
You
know
maybe
on
two
or
three
layers:
deep,
where
you
have
you
know
complex
traits
of
just
a
merged
de
novo,
they
emerge
from
precursor
organs
or
precursors,
and
so
this
is
something
of
like
how
the
eye
has
evolved.
B
B
I
know
jesse
is
interested
in
scaffolding
in
the
context
of
cognitive
science
and
the
context
of
cognition,
and
it's
a
similar
thing.
I
don't
know
if
you
can
make
that
direct
connection,
but
you
know
maybe
it's
worth
talking
about,
and
so
actually
he
gets
into
trade-offs,
constraints
and
historical
contingency.
Here
it
calls
it
non-adaptation
and
non-adaptation
just
simply
means
that
this
is
not
an
adaptation.
This
is
actually
the
the
sort
of
options
that
you're
locked
into
going
forward
in
evolution,
so
there
they
serve
as
constraints
again.
You
know
you
have
four
limbs.
B
Maybe
that
locks
you
into
wings
or
four
limbs.
You
can't
necessarily
evolve
like
a
thousand
limbs
coming
out
of
that
single
set
of
two
limbs.
You
know
I'm
just
giving
a
silly
example,
but
that's
that's
sort
of
the
idea
that
they
and
sometimes
people
call
that
the
hopeful
monster
and
that's
where
you
have
these
gigantic
evolutionary
changes.
It's
usually
in
the
context
of
development,
that's
considered
to
be
very
unlikely
and
the
idea
was
to
contrast
that
with
sort
of
a
gradualism
that
is
built,
you
know
one
thing
is
built
upon
another.
B
B
So
this
let
the
light
sensitive
cell
is
not
connected
to
a
nervous
system
of
any
kind,
but
instead
includes
a
psilium
which
can
be
stimulated
to
move
the
larva
in
response
to
light.
So
this
is
a
very
simple
light.
Sensing
organ
b
is
this
here
in
the
same
box
jellyfish
species
where
they
have
complex
upper
and
lower
eyes
of
retinas,
and
so
they
actually.
This
is
where
they
build
a.
B
This
is
a
complex
eye
as
opposed
to
these
light
sensing
cells,
and
this
has
a
lot
more
structure
to
it,
and
so
this
is
at
the
end
of
a
sensory
club
called
the
ropalium
which
goes
to
the
central
nervous
system
and
then
c
is
this
simple
eyespot
found
in
the
larva
of
the
trematode,
which
consists
of
one
pigment
cell
in
one
photoreceptor
cell?
So
this
is
the
receptor
cell.
This
is
the
pigment
cell.
B
This
kind
of
looks
like
something
you
might
find
in
a
more
complex
eye,
but
it's
definitely
you
know
that
relationship
is
already
there
in
this
flatworm
or
this
I
shouldn't
say
already
there,
but
it's
it's.
You
can
see
a
a
version
of
this
that's
much
simpler
than
what
you
might
see
in
other
eyes,
where
you
have
receptor
and
pigment
cells
and
then
d,
a
slightly
more
complex,
visual
organ
involving
a
simple
pigment
cell,
but
multiple
receptor
cells
found
on
the
two
trebelli
and
flatworm
in
this
species.
B
The
pigment
cell
is
cup
shaped
such
that
information
about
the
direction
of
light
can
be
obtained
by
comparing
input
from
the
different
receptors.
So
this
is
an
integrator
integration
organ,
and
so
you
have
these
receptor
cells
here
that
come
into
this
pigment
cell
and
they
have
different
sources.
So
this
is
kind
of
like
a
complex
nervous
system
where
you
have
multiple
synapses
on
a
neuron,
and
so
you
see
this,
and
so
this
is
how
this
works.
By
integrating
light
sources.
B
B
This
is
another
example
chambered
eyes
versus
compound
eyes.
So
this
is
where
you
get
this.
These
are
in
different
clades,
so
chambered,
eyes
and
compound
eyes
are
different
sort
of
solutions
to
vision
in
in
different
org
and
different
clades,
and
so
you
see
this
so
this
is.
I
think
this
is
a
a
pit
eye
and
this
is
found
in
nautilus
as
well
as
many
flatworms
and
anoints.
B
The
basic
compound
eye
is
b
here,
and
so
you
can
see
that
there
are
different
types
of
eye
that
evolve
and
they
evolve
in
basic.
You
know
in
different
ways:
you
can
have
different
families
of
of
this
type
of
eye
and
they
they
have
different
ways
of
functioning,
and
so
you
can
see
this
diversity
in
action
here,
and
so
this
shows
an
example.
Distribution
of
I
types
across
major
taxa.
B
So
then,
we're
putting
now
we're
putting
these
eyes
on
a
phylogeny
we're
going
from
nigeria's
through
this
out
group
or
this
comparator
group,
and
then
we're
looking
in
the
in
group
we're
looking
as
far
a
field
as
vertebrates,
insects,
crustaceans,
mollusks,
anioids,
and
then
we
have
all
of
these
different
types
of
eyes,
and
you
can
see
there
in
vertebrates.
You
have
a
diversity
of
eyes,
but
it's
nowhere
near
the
diversity.
B
Okay.
So
the
second
paper
I
want
to
talk
about
is
this
paper
origin
now
an
evolution
of
cell
types.
So
this
is
just
kind
of
highlighting
a
paper
that
came
out
in
2016
and
they
talk
about
this.
This
is
about
cell
types
and
how
they're
the
basic
building
blocks
of
multicellular
organisms
and
are
extensively
diversified
animals.
B
So
with
all
these
complex
phenotypes,
you
need
they're
get
built
with
complex
cell
types,
and
we
saw
examples
of
that
in
the
eye
where
you
have
different
cell
types,
that
are
your
basic
cell
types
within
your
specialized
cell
types
and
it's
kind
of
hard
to
know.
You
know
people
have
tried
sort
of
categorizing
cell
types,
because
you
can
have
a
lot
of
different
receptor
cell
types
that
are
highly
specialized
across
species,
especially
but
also
in
species.
B
Where
there's
a
certain
you
know
they
specialize
for
a
certain
function
like
species
that
have
different
different
colored
cones,
and
so
you
know
those
cells
have
to
be
specialized
they're,
not
necessarily
different
cell
types,
but
those
cells
are
specialized
and
then
in
evolution
they
may
actually
become
different
cell
types.
People
have
tried
using
phenotypes,
but
phenotypes
are
really
insufficient
for
understanding
cell
types.
You
really
need
to
have
a
lot
of
molecular
profiling,
which
is
done
in.
B
It's
kind
of
hard
to
make
the
distinction,
and
so,
as
a
result,
the
number
of
cell
type
that
people
have
made
estimates
of
the
number
of
cell
types
and-
and
that
ranges
widely.
So
here
they
talk
about
some
of
these
cell
types.
Despite
recent
advances
in
characterizing
cell
types,
classification
schemes
remain
ambiguous.
B
B
This
makes
emergent
sister
cell
types
distinct,
enables
our
independent
evolution
and
regulates
cell
type,
specific
traits
termed
apomiers,
and
so
you
can
see
these
in.
You
know
people
look
for
these
different
differences
and
they
and
they
use
firewood
genetics
to
sort
of
sort.
This
out,
we
discuss
the
distinction
between
developmental
and
evolutionary
lineages,
so
we
talk
about
developmental
lineages
in
the
group.
These
are
cell
lineages,
but
these
also
exist
as
evolutionary
lineages
because
they
may
exist
between
species,
and
so
they
have
to
distinguish
this,
and
so
there
any
pictures
in
this
paper.
B
B
At
least
the
ancestral
form
of
this
trait
convergence
is
where
you
evolve:
the
same
type
of
function
in
two
different
lineages,
so
this
might
be
bats
and
birds,
and
then
concerted
evolution
is
where
it's
across
all
members
of
the
same
clade
and
maybe
they're
all
sort
of
co-evolving
or
they're,
all
evolving,
a
similar
trait,
and
so
you
know
instead
of
diverging,
like
you
might
see,
divergence
and
a
number
of
of
different
types
of
wing.
You
might
see
concerted
evolution
and
they're
all
kind
of
in
that
same
clade
there.
B
The
traits
are
a
little
bit
different,
but
they're
all
evolving
in
the
same
direction.
Perhaps
so
this
is
so
they
kind
of
go
through
different
cell
types.
This
is
an
example
of
regulatory
signature
of
a
cell
type
identity,
so
they
show
this
example
of
these
transcription
factor
clusters,
and
so
you
see
this
actually
in
cellular
reprogramming.
This
is
important.
They've
identified
four
or
five
different
transcription
factors
that,
when
introduced
into
the
cell,
can
change
the
fate
of
a
cell.
You
see
this
in
development
with
other
transcription
factors.
B
Different
developmental
changes
can
be
triggered,
and
so
so
it
is
with
cell
type.
As
cell
types
of
margin,
development-
and
we
have
these
changes
and
transcription
factor
regulation-
and
this
results
in
a
change
in
cell
type-
and
so
this
is
just
the
identity
of
a
cell,
so
identity
of
a
cell
is
just
what
it
identifies
as
so,
you
know,
with
different
functions
can
be
fluid
and
different
cell
types
can
be
fluid.
So
you
know
it
depends
on
the
on
the
developmental
system.
B
If
you
have
what
they
call
a
regulative
form
of
development,
which
is
something
like
mammals,
then
you
can
see
this
kind
of
you
know:
signaling
will
sort
of
influence
the
cell
to
have
a
certain
fate
or
to
have
another
fade,
and
so
but
another
species
in
mosaic
development.
You
have
cells
that
have
a
fixed
identity
throughout
their
life
history,
and
so
that's
something
to
keep
in
mind.
B
Our
model
implicates
the
independent
control
gene
expression,
which
we
linked
to
cell
type
identity,
may
be
mechanistically
dissociated
from
self-phenotype,
so
the
phenotype
may
not
reflect
what
the
cell
is
doing
in
terms
of
its
function
and
it's.
It
is
hard,
in
fact,
to
identify
phenotype
exactly
because
sometimes
it's
very
cryptic
and
it's
hard
to
understand
what
the
cells
are
doing.
Sometimes
they're
in
a
transition
transitional
state.
So,
for
example,
visceral
muscles
and
drosophila
melanogaster
also
express
these
transcription
factors.
D
B
B
B
B
This
is
what
they
call
a
model
sensory
system,
and
so
this
kind
of
is
a
review
of
electro's
reception,
and
you
know
some
of
the,
so
it
was
first
discovered
in
weekly
electric
fish,
which
are
fish
fresh
water
fish
in
in
the
tropics,
and
there
are
a
lot
of
different
species,
and
then
they
found
this
in
other
types
of
living.
Vertebrates
different
systems,
though
the
systems
have
diversified,
and
so.
D
B
B
In
the
sort
of
the
trunk
of
the
tree
of
animals,
so
metazoans
or
animals
basil
was
that
sort
of
the
common
ancestor
of
animals
and
they're,
focusing
here
in
nigeria,
so
nigeria,
when
traditionally
viewed
as
the
most
basal
animals
with
complex
organ-like
multicellular
structures
dedicated
to
sensory
perception.
So
these
are
sort
of
the
there's,
an
early
divergence
from
that
common
ancestor
hydaria,
and
they
have
these.
They
retain
these
sort
of
ancestral
forms.
B
Here
we
discussed
sense
organ
regulatory
genes,
including
cyanocalculus,
brain
3
and
isabsen,
that
are
expressed
in
cydarian
sense
organs.
Two
they
assess
the
sensory
features
of
the
planula
polyp
and
medusa
life,
history
stages
and
three.
They
discuss
the
physiological
molecular
data
that
suggests
sensory,
neural
processes
and
sponges.
So
these
are
all-
or
you
know,
organisms
that
don't
really
have
you
know
complex
or
central
nervous
systems,
but
they
do
have
these
sort
of
neural
signaling
aspects
and
they
have
sensory
organs.
So
this
is
something
that
you
know.
B
B
And
then
this
paper
is
on
a
short
history
of
nearly
every
sense,
the
evolutionary
history
of
vertebrate
sensory
cell
types.
So
this
is
a
nice
paper
that
goes
through
all
of
the
sensor,
different
types
of
major
sensory
cell
types
found
in
vertebrates,
their
phylogenetic
distribution
and
presents
a
scenario
for
the
evolutionary
history
of
various
sensory
cell
types
involved
in
several
cell
type,
diversification
and
fusion
events,
and
so
this
is
again
it
tells
you
something
about
all
these
different
sensory
cell
types
and
you
know
like
so.
B
For
example,
they
go
through
a
selection
of
sensory
cells,
the
vertebrate
sensory.
This
is
a
rod.
This
is
a
hair
cell,
an
innervating
neuron.
This
is
a
mechanosensory
cell
insects.
This
is
an
external
sense
organ,
and
then
this
is
a
sheath
cell
on
a
hair.
I
think
with
this
is
the
direction
of
the
stimulus,
that's
stimulating
this
hair
and
it's
coming
down
into
the
sheath
cell.
So
you
can
see
like
all
these
different.
You
know
relationships
between
the
the
well
and
see
they
show
the
direction
of
this
sensory
stimulus
as
well.
B
So
you
can
see
the
connection
now
between
sensory
stimuli
and
these
cells
and
then
understanding
what
the
output
of
those
cells
are,
if
it's
continuous
or
discrete,
and
that's
something
we
can
talk
about
at
another
time
and
then.
Finally,
this
paper
on
development
and
evolutionary
the
development
and
evolution
of
sensory
cells
and
organs.
This
is
an
editorial
from
in
developmental
biology
and
this
kind
of
goes
through
some
nice
papers,
debt
level,
rent
who's,
a
nice
who's,
an
author
who's
done
a
number
of
papers
on
this
and
they've.
B
B
New
conceptual
approaches
are
urgently
needed
to
allow
us
to
frame
testable
hypotheses
for
the
evolution
of
sensory
cells
and
organs.
I
think
we
could
also
use
computational
methods
for
it
too,
just
to
see
like
what
you
know:
the
diversity
of
these
kind
of
cells
yields
in
terms
of
behaviors
or
outputs
and
then
looking
at
maybe
a
different
hypothetical
outputs
or
different
hypothetical
cell
types.
You
know
what's
going
on
at
the
molecular
level,
what's
going
at
the
cellular
level,
what
what
are
the
stimuli?
What
does
it
look
like
when
you
stimulate
these
cells
at
different?
B
B
This
was
from
a
workshop
in
2016,
so
this
kind
of
goes
through
some
of
the
papers.
Todd
oakley
contributed
something
here
that
highlights
the
duplication
and
divergence
of
genes
cell
types
and
organs,
but
these
only
form
part
of
the
picture
and
there's
an
importance
of
rearrangements
and
co-options
of
pre-existing
components.
So
in
complex
nervous
systems,
things
often
get
rearranged
and
co-opted
for
different
purposes.
So
this
is
kind
of
like
exactation.