►
From YouTube: DevoWorm (2021, Meeting 32): DZ-DL Review, Bacillaria Aneural Cognition, Differential Morphogenesis
Description
Reviewing the current state of DevoZoo, DevoLearn, and plans for Hacktoberfest. Bacillaria Aneural Psychophysics (models and simulation). Animal embryo review. Papers on brain pathway duplication as a product of genes and behavior, and wave-driven differential morphogenesis in Dictyostelium (plus parallels with Vertebrate embryogenesis).
Attendees: Bradly Alicea, Akshay Nair, and Mainak Deb.
A
A
A
Oh,
I
was
wondering
if
you
had
anything
you
wanted
to
present
today
today.
I
really
don't
have
anything
to
present.
Okay
thanks
yeah,
so
gsoc
is
over
and
in
the
books
for
another
year,
and
so
today
I'm
gonna.
We
will
talk
about
my
next
like
what
you
know.
Next
development
steps
are
for
the
sort
of
the
whole
infrastructure
of
what
we
have
in
terms
of
data,
open
data
and
machine
learning,
and
things
like
that.
A
So
if
people
are
watching
on
youtube,
you
can
get
a
sense
of
what
the
scope
of
what
we
have
now
is,
and
you
know
maybe
we'll
think
in
the
next
couple
months
about
like
what
gsoc
2022
should
look
like.
So
you
know
this
is
what
we
did
last
year.
We
reassessed
what
we
had
and
we
moved
forward
on
that.
So
we'll
do
that.
We
also
have
a
couple
of
other
features
that
I
have
on
different.
You
know
things
I
found
on
on
the
internet
and
in
the
literature.
A
A
A
A
All
right,
I'm
back.
Let
me
try
to
share
my
screen
again
all
right.
There
we
go
so
now
you
can
see
my
screen,
and
so
this
is
the
I
wanted
to
bring
a
couple
things
up
this
week
that
I
didn't
have
last
week.
So
this
is
the
devozu
interface,
and
this
was
the
product
of
usual
singh
last
year
for
his
gsoc
project
basically
took
what
we
had
in
terms
of
the
devo
zoo
and
he
built
another
resource
called
divorm
ai,
and
then
that
was
his
project.
A
So
what
is
divo
zoo,
devo
zoo?
Is
this
thing
we
operate
off,
evorum
github
io
and
it's
hosted
there
and
it's
it's
a
repository
of
data
for
different
types
of
embryos
and
developmental
data,
so
you
can
see
that
we
have
the
diva
worm
or
the
different.
We
have
different
species
where
we
have
data
for,
like
mostly
microscopic
well,
I
think
all
microscopy
data
a
lot
of
it
is
the
embryo.
I
think
all
of
it's
the
embryo.
Actually.
A
A
We
have
another
data
set
that
I
don't
know
exactly.
I
can't
remember
what
this
is,
but
you
learn
more
here
and
then
an
another
spin
and
spim
is
a
type
of
microscopy
where
it's
a
high
resolution
type
of
microscopy.
So
we
didn't
use
that
in
the
serious
project,
because
these
images
aren't
annotated
necessarily
so
this-
actually,
I
don't
think,
is
spin,
but
that's
okay,
so
this
is
there's
more
at
the
link.
A
So
this
these
are
the
microscopy
images
or
the
movies
that
we
have
that
we
link
to,
and
then
we
have,
these
data
sets
that
are
processed
their
csv
files
and
we
have
the
lineage
tree
cell
birth
and
death
timing,
differentiation,
tree
cell
position
and
gene
expression.
So
these
are
all
data
sets
that
were
collected
from
different
sources,
there's
those
that
are
annotated
and
have
variables
associated
with
them.
So
it's
like
you
can
pop
them
into
a
any
analysis
engine
you
want.
You
can
pop
them
into
like
a
python.
A
A
Eightfold
symmetry
that,
when
it
divides
it,
divides
into
like
actually
it's
four-fold
symmetry
divides
into
four
founder
cells,
and
then
those
founder
cells
form
symmetrical
parts
of
the
embryo,
and
then
it
gets
up
to
a
couple
hundred
cells,
and
then
it
has
it.
It
goes
through
a
different
developmental
phase.
A
It
becomes
this
long
tube
and
then
it
just
eventually
ends
up
being
this
mo
the
sissile
or
the
stationary
organism,
and
so
it
goes
through
a
number
of
different
stages
of
its
of
its
development,
and
this
is
the
first
stage
of
its
development.
So
we
have
early
embryogenesis
in
the
species,
and
this
is
a
microscopy
movie
that
this
is
the
these
are
these
are
csv
data,
and
then
this
is
the
movie.
We
also
have
some
data
for
fruit
fly
zebrafish
mouse
spider.
Even
we
have
movies
for
spider.
A
A
A
We
have
a
couple
of
data
sets
or
a
couple
of
repositories
of
virtual
organisms,
so
we
have
morphozones,
which
are
the
agents
that
we
use
in
the
morphozoic
platform,
and
so
there's
a
paper
and
a
repository
with
c
plus
plus
code
in
it.
So
if
you
want
to
run
this,
this
is
a
cellular
automata
simulation
and
you
have
agents
that
form
these
that
you
know
they
can
do
a
lot
of
different
types
of
pattern
recognition,
but
they
also
form
like
developmental,
like
structures,
and
then
we
have
multi-cell
systems,
that's
even
less
developed.
A
This
needs
to
be
updated,
but
this
is
the
stuff
that
you
know
where
I
think
I
showed
this
in
one
of
the
lab
meetings
where
we
have
this
network
and
we
look
at
the
edges
of
the
network
to
determine
this.
The
structure
of
the
cells
and
we
look
at
how
they
go.
You
know
they
undergo
development
and
we
can
look
and
see
if
they
form
these
coherent
modules.
A
I
haven't
had
a
chance
to
do
it,
but
that's
one
aspect.
So
that's
the
devo
zoo
and
I
want
to
really.
I
know
that
I
was
at
a
meeting
recently
and
they
talked
about
like
resources
that
people
need.
They
were
talking
about,
people
who
you
know,
there's
a
biology
community
and
there's
a
computational
community
and
there
was
a
consensus
or
there
was
an
idea
brought
up
at
the
meeting
that
we
needed
a
resource
that
links
the
two
that
are
that's
data-driven,
something
that
emphasizes
model
organisms.
A
C
A
C
A
A
A
A
A
The
devozu
method,
so
this
is
the
devozu
part
divorm
academy,
so
we
actually
had
a
diva
learn
it
something
called
diva
worm
ml
almost
two
years
ago
now,
and
in
fact
I
think
it
started
on
this
day
two
years
ago.
So,
but
we
need
to
update
that.
I
haven't
done
it
in
a
while,
because
I've
been
haven't
had
time,
but
I
was
updating
it
earlier
this
year
and
something
I
think
we
should
put
together
a
little
bit
more
completely.
A
Last
time
I
ran
it.
I
like
had
week
by
week-
and
I
just
kind
of
used
this
time
to
do
the
course-
and
I
tried
to
get
a
couple
people
from
outside
our
usual
group.
So
they
came
in
and
you
know,
was
just
on
a
series
of
topics
that
were
you
know,
maybe
of
interest
to
biologists
and
people
interested
in
machine
learning.
So
we
had
people,
you
know
not
just
myself,
but
other
people
gave
lectures
as
well.
A
A
I
don't
know
how
this
works.
Okay
and
then
contact
us,
so
there's
a
contact
form
on
this,
so
this
is
kind
of
parallel
to
the
diva
website.
But
this
is
something
that
we
worked
out
for
a
json
project,
so
I
just
I
don't
I
mean
I
don't
have
much
else
to
say
about
it,
except
that
there's
that
so
we
have
these
two
things
that
were
done
last
summer.
Now
the
question
is:
is
how
do
we
integrate
what
we've
done
this
year
and
might
be
what
we've
done
in
past
years
more
effectively?
A
A
So
people
have
suggestions
about
that.
Let
me
know
you
know
we
will
be
working
on
it
over
the
course
of
this
year
and
then
next
year.
I'm
not
sure
what
our
plan
is.
If
it's
going
to
be
like,
if
we're
going
to
focus
on
doing
more
with
evil,
learn
in
terms
of
developing
it
or
try
to
develop
something
else
I
don't
want
to,
I
mean
we
could
go
in
a
new
direction.
More
like
you.
A
Some
of
the
other
projects
that
didn't
get
selected
this
year,
such
as
the
the
thing
on
well
the
vessel
area
project
we
could
do
that
or
that
I
think
we're
kind
of
people
are
working
on
the
the
axle
model
image
or
the
axolotl
atlas.
So
we'll
see
where
that
goes.
But
yeah
do
you
have
thoughts
about
that?
My
knock.
B
A
Yeah,
hopefully
yeah,
so
that
should
that
should
maybe
you
know
we
can
move
more
on
that
in
that
direction.
And
then,
if
we
had
that
we
would
have
a
new
dimension
to
a
lot
of
our
models.
So
we
have
a
lot
of
models
that
are
c
elegans
oriented,
and
then
we
have
the
basilaria
digital
vessel
area
thing.
That
was
actually
something
that
usual
worked
on
as
well,
so
that
was
his
project
in
2020
was
kind
of
a
hodgepodge,
but
it
you
know
it
came
out
pretty
well.
A
So
this
is
where
you're
tracking
these
small
organisms
and
then
they're
even
smaller
in
c
elegans,
and
then
of
course,
then
you
would
have
the
sphere.
You
would
have
the
axolotl
embryo
atlas.
I
guess
you
could
call
it,
and
that
would
be
a
third
thing
that
we'd
have
so
it
would
be
nice
to
have.
You
know
that
collection
of
things.
A
So
yeah,
I
don't
want
to
like
you
know
and
again
like
it's
things
that
we
can
like
update.
I
think
we
need
to
update
the
this
some
of
these
web
resources,
but
yeah.
So
a
few
links
need
to
be
updated,
yeah,
yeah
and
yeah.
So
then
we
also
have
other
model
organisms,
so
I
mean
you
know
the
data
sets
are
always
you
know,
they're,
always
new
data
sets
coming
out
and
there's
stuff
that's
available,
that's
annotated!
A
So
that's
something
that
people
might
want
to
you
know
I
just
want
to
make
it
so
that
people
can
come
to
the
community,
find
things
that
that
might
be.
You
know,
might
encourage
them
to
do
some
good
work,
learning
or
research
oriented,
and
then
you
know
it
just
they
can
pick
it
up
and
move
with
it
pretty
quickly.
A
A
I
did
a
presentation
this
week.
It
was
at
so
this
is
the
presentation
here.
If
we
go
to
our
youtube
channel.
It's
right
here
is
game
theory
of
developmental
processes.
This
was
for
dynamics,
days
xl,
which
was
hosted
in
nice,
france
and
they
had
it
online
as
well.
So
no
need
to
go
to
france.
You
know
I
was
able
to
do
the
session.
A
C
A
Was
I
think
I
presented
this
a
couple
weeks
ago?
It's
where
we
had
the
you
know
the
different
models
of
game
theory,
starting
with,
like
you
know
this
idea
of
like
an
autogenetic
agent
or
a
developmental
agent,
making
the
point
that
this
is
different
from
like
the
kind
of
game,
theory,
funding,
economics
and
then
getting
into
the
different
types
of
games.
You
can
use
this
type
of
approach
on
so
we
have
some
things
that
we
published.
A
We
have
some
other
things
that
I
kind
of
cases
that
I've
made
up
for
the
talk
and
ultimately
I'd
like
to
put
out
a
preprint
on
this,
but
we're
not
there.
Yet.
I
have
it
like
in
a
not
a
very
good
draft
state,
so
we
can
talk
more
about
that
in
coming
weeks,
but
I
don't
have
anything
much
else
to
show
except
to
point
this
out
on
the
youtube
channel
and
then
there's
this
other.
A
A
A
A
replicator
is
like
basically
the
thing
that
replicates
like
genes
or
replicates
a
phenotype,
and
they
have
this.
It's
a
theoretical
concept
of
a
replicator
and
they
can
actually
model
replicators
and
using
differential
equations
in
this
pd
replicator
equation.
They
looked
at
the
long
time,
behavior
for
multi-level
selection
and
group
structured
populations.
A
They
also
talked
about
co-evolution
of
cooperation
and
synchronization.
So
this
is
where
we're
looking
at
migration
and
they're
looking
at
these
different
aspects
of
it.
They
also
have
this
talk
on
generalized
hamiltonian
dynamics
and
chaos.
So
this
is
on
evolutionary
games
in
evolutionary
games
on
networks.
A
A
So
this
is
where
they're
looking
at
this
type
of
chemical
system,
where
they're
looking
at
like
they're
treating
the
chemical
compounds
as
microoscillators
over
time.
So
when
they
say
dynamics
days
they
mean,
like
you,
know,
dynamically
dynamic,
behavior,
dynamical
systems,
that's
the
sort
of
the
thrust
of
this
conference.
So
this
is
a
pretty
good
session
and
then
I
was
in
there
with
them.
So
this
is
it's
a
nice
little
session.
A
So
these
are
things
you
would
really
need
to
have
a
high
powered
microscope
to
find
this
is
actually
an
ant
tunnel
and
an
ant
colony,
so
they're
visualizing
things
at
different
scales
here
again
is
the
yeah.
This
is
some
sort
of
binding
molecular
binding,
and
then
this
is
like
cells
being
innervated
by
motor
neurons.
A
So
this
is,
like
you
know,
it's
very
high
quality.
These
are.
These
are
animations
that
people
have
made
this
group
and
they're
using
this
type
of
3d
modeling,
where
they're
making
these
movies.
These
aren't
really
based.
Some
of
them
are
based
on
microscopy
images,
and
some
of
them
are
just
animations
of
processes.
A
So
I
think
some
of
these
are
really
nice.
Oh,
this
is
not
a
biological
image.
This
is
a
lab,
but
you
can
see
like
what
they're
doing
here
is
they're
building
these
three-dimensional
models
and
they're
kind
of
maybe
showing
a
little
bit
more
than
the
microscopy
they're,
showing
like
the
process,
and
you
know
it's
pretty
flashy.
A
So
what
I'm
thinking
about
is
like
I
know
this
has
been
a
long-standing
interest
to
the
group.
It's
like
building
something
something
similar
to
this
for
some
of
the
things
we're
talking
about
in
development
and
kind
of
using
microscopy
as
a
seed
for
that
so
like
we
have
the
microscopy
data
we
have
like.
You
know
we
could
build
like
a
skeleton
of
something
and
then
also
you
know
not
just
the
skeleton,
but
putting
that
in
a
larger
context.
A
A
Axolotl
atlas
would
be
like
a
meat
intermediate
step
there
or
we'd
have
like
this
thing.
You
could
explore
and
then
you
know
you
can
do
that
and
then
you
know
at
some
point.
We
would
build
this
sort
of
these
worlds,
these
developmental
worlds,
where
you
could
explore
them
with
you
know
a
headset
there's
the
oculus
headset,
where
you
can
actually
explore
things
that
you
build
in
a
virtual
world.
You
can
develop
on
a
standard
in
a
standard
language,
a
standard
platform
and
you
can
build
things
and
view
them
yeah
unity
framework.
A
B
D
A
C
A
A
A
This
is
get
data
from
susan's
ball
microscope.
I
think
that's
actually
like
a
continual
thing
here
that
I
I
put.
I
use
the
hold
category
for
things
that
are
continual
they
have
parts
that
we
have
to
hold
on.
So
I'm
going
to
wait,
I'm
going
to
say
that
we
have
the
micro
cross
could
be
data
here,
but
we
could
get
more
and
then
so
that's
that
this
fish
ladder
toy
model
of
life
in
a
lipid
world.
This
is
something
that
I
think
krishna
was
working
on.
A
This
acts
a
lot
of
embryo
animations
and
segmentation
on
something
that
akshay
was
is
working
on
just
told
us
about
this
analysis,
shape
of
shapes
of
polygonal
archaea
and
shaped
droplets.
This
is
something
I
think
that
my
knock
is
working
on
and
don't
worry
about
the
time
on
this.
Just
you
know
it's
just
like
in
progress.
A
It's
open.
You
know
we
can
keep
working
on
as
long
as
we
want
recruit
people
as
evil
and
contributors.
That's
something
that
is
probably
well
in
october.
Of
course,
there's
hecktoberfest,
and
so
this
is
a
thing
that
or
that
github
runs
to
get
people
to
work
on
different
repos,
so
we
might
be
doing
last
year
we
did
hacktoberfest
for
divalearn.
A
A
D
A
A
Advertise
it
last
year
I
advertised
it
a
bit
and
I
got
people
to
come
in
or
if
you
know,
people
in
your
classes
that
might
want
to
do
this.
You
know,
there's
a,
I
think.
You
know
we
can
advertise
it
there
and
then
you
know
if
they
make
like,
I
think
five
commits
and
get
them
accept,
pull
requests
and
get
them
accepted
as
commits.
D
D
We
could
actually
take
part
in
g-sword
also.
I
think
there
is
something
for
documentation
as
well,
so
I
I
think,
like
our
diva
learn,
maybe
I
mean
it's
good.
The
documentation
is
good.
The
existing
everything
is
good,
but
we
can
improve
it.
Obviously.
So
if,
if
we
are
it's
just
a
suggestion,
I'm
not.
I
don't.
B
B
A
Yeah,
I
think
I
I've
applied
actually
to
gsod.
Well,
we
actually
open
worm,
hosted
a
gsat
person
in
2019
and
it
created
a
continuous
integration
thing
and
which
you
know
is
something
that
I
don't
know
if
we
use
that
much,
but
that
that
wasn't
a
divorm
oriented
I've
applied
for
diva
worm
for
last
couple
years,
but
the
the
way
they
run
the
program
they
keep
changing
it.
So
it's
kind
of
hard
to
get
an
actual
person
to
do
that.
So
it's
yeah,
you
know,
but
I
no.
A
I
agree
that
I
think
bringing
people
in
in
terms
of
documentation
is
is
good
because
it
can
always
be
improved
yeah.
We
might
try
to
go
the
route
of
hacktoberfest
for
that.
If,
if
they're
people
who
you
know-
and
I
mean
this-
would
be
like
not
just
anyone,
because
not
everyone's
interested
in
documentation,
but
to
try
to
advertise
specifically
for
those
issues
in
places
where
people
might
be
but
yeah
yeah
so
and
then
you
know
yeah
and
and
we'll
keep
trying
with
g
sock
or
g
sod.
D
D
Around
that
time,
because,
like
this
is
the
trend
I'm
seeing
in
my
previous
organizations
also,
I
mean
I'm
still
in
touch
with
them,
but,
for
example,
if
you
take
kde
people
would
be
active
until
the
proposal
period,
then,
from
the
october
till
the
proposal
period,
then
they
you
know
suddenly
just
go.
Then
the
coming
months
is
just
the
project
is
absolutely
dead.
You
know,
so
we
could
actually
use
some
help
coming
months.
A
C
A
Yeah
put
that
in
as
an
issue
that
way
we
we
have
it
to
review
yeah.
So
then
that's
good
and
then
so
we
have
a
couple
of
things
here
in
the
action
items.
It's
game
theory
for
developmental
processes,
preprint,
which
you
saw
the
talk,
and
now
you
know
we
want
to
have
a
pre-print
there's.
Also
this
paper.
A
A
A
The
revised
annan's
bnn's
paper
is
something
that
myself
krishna
and
jesse
worked
on,
and
it's
something
that
we
submitted
to
the
a
life
conference
and
it
didn't
get
accepted,
but
it
you
know,
got
some
somewhat
semi-favorable
reviews,
so
that's
something
we
can
maybe
submit
somewhere
else
or
revise
it
again.
It's
on
on
the
archive
as
a
preprint
right
now,
but
I
think
there's
life
in
that
early
life
in
the
origins
of
development
theme
it's
kind
of
being
developed.
I
don't
know
what
we'll
do
with
this.
A
If
we'll
do
like
a
preprint
or
some
other
thing
updates
on
axolotl
data
analysis,
this
is
linked
to
the
thing
that
akshay
is
doing
next
steps
for
embryo
networks
and
multi-cell
systems.
This
is
again
this
stuff
that
was
done
at
networks.
2021.
That's
next
steps
for
that
which
I
don't
really
have
right
now
so
follow
up
on
origins
of
embryos.
It's
not
really
fruit.
A
A
A
Yeah,
that
would
be
great
yeah.
Thank
you,
yeah,
okay,
all
right,
and
then
let's
see
so
that's
that's
that
and
then,
of
course,
on
hold.
We
have
a
number
of
things
here,
I'm
not
going
to
go
through
all
of
them,
but
we
have
things
like
tutorials
and
getting
data
and
revisiting
some
things.
We
talk
about
the
meetings
and
then
this
create
embryo
model
in
blender.
A
A
So
this
is
yeah,
so
this
this
is
something
that's
like
kind
of
been
a
long-standing
thing,
so
we
want
to
put
like
create
an
embryo
model
and
put
it
into
a
blender
file,
but
we
also
maybe
want
to
do
things
like
visualizing,
the
embryo.
You
know,
embryogenesis,
you
know
taking
some
of
the
data
we've
had
as
a
cell
tracking
data
and
put
it
into
some
sort
of
context.
A
C
A
You
know
some
sort
of
embryo
model
where
you
have
you
know
in
a
3d
model,
where
you
have
the
cells
as
3d
objects,
and
then
you
know
visualization
like
what
I
just
showed
with
the
animus
3d
system
there
or
their
their
animations.
So
and
all
those
things
you
could
do
on
a
number
of
levels.
So
that's
that's
something
else.
Then
we
have
these
two
do
things.
These
are
things
that
kind
of
come
up
during
the
meetings.
A
We
have
the
boring
billions
paper,
abstract
book
topic.
We
have
this
kindle
book,
we
have
the
droplet
shapes,
which
is
there's
an
issue
over
here.
That's
very
similar.
I
don't
want
to
re.
I
don't
want
to
repeat
issues,
but
these
are.
I
think
these
are
a
little
bit
different,
but
anyways
yeah.
So
we
have
all
these
different.
This
is,
I
think,
is
the
drop,
what
shapes
in
broader
context.
So
again,
this
is
on
our
diva
worm.
A
A
A
This
is
a
paper
that
I'm
working
on
for
a
long
time,
and
this
is
the
psychophysical
world
of
the
motile
diatom
bacillary
paradoxa,
and
so
I
was
showing
the
divorm
ai
thing
earlier
and
I
talked
about
this
digital
basil
area
project.
So
this
project
is
something
that
was
done
like
two
years
ago.
Now
we
have
a
paper
on
it
in
our
paper
collection
of
our
things
that
we've
published
and
is
where
we
apply
deep
learning
and
different
types
of
biomechanical
analysis
to
the
best
area,
which
is
this
diatom.
A
So
it's
a
very
interesting
organism
in
terms
of
movement
and
what
we
were
doing
were
identifying
cells
and
doing
cell
segmentation,
identifying
the
trajectory
of
different
cells
moving
against
one
another,
and
all
that
this
paper
follows
up
on
that.
It's
more
speculative
and
it
talks
about
sort
of
what
the
potential
psychophysics
of
this
diatom
are.
So
what
do
you
mean
by
psychophysics?
A
And
what
I
mean
is
that
there's
there's
no
brain
in
basil
area,
but
it
does
have
these
properties
of
sort
of
what
we
call
non-neuronal
cognition,
and
so
we
talk
about
non-neuronal
cognition
in
this
paper.
We
talk
about
the
different
aspects
of
you
know
it's
a
metaphor,
but
it's
also
a
way
to
explain
some
of
the
mechanical
properties
of
the
of
the
colony
and
how
it's
moving
and
critically.
A
There
are
different
types
of
measures
you
can
use
and
different
types
of
techniques
that
we
use
in
measuring
perception
and
nervous
systems
that
can
help
us
understand
the
system.
It
doesn't
have
a
nervous
system.
The
system
has
this
sort
of
network
of
filaments
and
other
types
of
components
that
allowed
to
move
collectively,
and
so
the
question
is:
is
you
know
how
does
it
do
that?
Can
we
model
it
using
things
that
are
you
know
from
psychophysics
or
from
like
cognitive,
science
and
neuroscience?
A
A
You
know
different
other
organisms
with
a
similar
type
of
interpretation,
so
people
have
looked
at
slime,
molds
faisarum
in
terms
of
nominal
cognition,
they've
observed
different
types
of
learning.
Like
habituation,
they've
observed
this
sort
of
thing,
a
non-neuronal
cognition,
simple
chemical
systems
such
as
protocells
they've,
observed
dissociative
learning
and
habituation
in
different
types
of
minimal
cognition
systems.
A
A
So
we
kind
of
go
through
some
of
the
methods
that
you
might
use
and
again
there's
this
isn't
really
a
data-driven
paper.
This
is
where
you
just
talk
about
a
lot
of
these
different
things
and
bring
them
to
this
audience,
so
we're
borrowing
from
the
neuroscience
literature
and
the
cognitive
science
of
literature,
we're
looking
at
things
like
predictive
processing
and
hebbian
learning,
and
also
you
know,
different
measurement
techniques
like
using
the
weber
factor
law,
which
is
a
a
law
of
light
stimulus
intensity.
A
A
Yeah,
so
this
is
a
draft
paper
and
I
don't
care
about
being
secretive
about
it.
This
is
something
where
yeah
we're
working
on
and
it's
not
really
all
done.
It's
not
done
yet,
but
it's
being
submitted
it'll
be
coming
out
as
a
preprint
in
the
near
future
as
soon
as
it's
finished
yeah,
so
that
I
don't
wanted
to
go
over
this
to
to
get
people
on
the
ground.
A
C
A
D
There
be
data
I
mean
I,
I
could
actually
volunteer
to
help
you
on
this,
but
I'm
not
sure
of
the
biology,
but
if,
if
there
is
something
that
needs
to
be,
you
know
simulations
or
something
which
needs
to
be
shown.
By
about
these
equations,
which
I
can
plot
or
I
mean
learn
through
behavior
of
these
atoms,
it
can
actually
help
you
so.
A
A
So
yeah
and
then
this
goes
through,
you
know
different
methods,
and
then
we
come
up
with
this
thing
that
you
know.
This
is
something
that's
novel
about
our
approaches.
We've
come
up
with
this
thing
called
a
collective
pattern
generator.
So
this
is
a
a
basilaria
colony
and
it's
being
exposed
to
light
and
they
get
exposed.
A
It's
quite
about
the
ends
of
the
rod
here.
But
you
have
these
points
that
are
like
intracellular
or
intracellular
connections
between
the
cells,
and
so
these
are
things
that
we're
sort
of
modeling
with
a
connectionist
network.
So
as
it
moves
the
network
kind
of
the
weights
of
the
network
change
here
in
between
these
nodes,
and
the
idea
is
that
you
know
the
intensity.
It
changes,
but
also
with
like
the
movement
of
the
colony
it
changes.
A
So
you
know
how
do
we
know
whether
it's
truly
intelligent
or
pseudo-intelligent
and
there's
this
discussion
here
on
this
and
then
that's
it
and
there's
some
ref.
Quite
a
few
references
here,
probably
we'll
add
more.
But
that's
that's
what
we
have
right
now.
So
just
you
know
this
is
for
people.
Anyone
in
the
group.
If
you
want
to
contribute
to
this,
let
me
know,
and
actually
I'll
get
back
with
you
on,
like
some
of
the
more
detailed
points
of
this.
A
Okay,
so
I
and
I
think,
we'll
move
on
to
papers
for
the
week
and
I'm
going
to
start
with
some
new
embryo
images
that
I
found
online.
So
there
are
a
couple
of
interesting
ones
here.
I
think
this
will
give
you
maybe
a
little
better
idea
of
some
of
the
organisms
we
talk
about
in
the
meetings,
so
the
first
one
is
axolotl
and
this
is
in
what
they
call
the
neuriola
stage.
So
this
is
a
pretty
early
point
in
axolotl
embryo
development.
A
This
is
where
it's
taking
the
head:
it's
kind
of
forming
its
neural
tube,
so
it's
forming
the
tube,
that's
going
to
form
the
brain
and
the
spinal
cord
here,
so
it's
folding
over,
and
so
these
are
the
neuralis
stages,
and
this
is
the
person
who
took
this
picture.
Dr
crystal
rogers-
and
this
is
it's
an
axolotl
embryo.
This
is
a
close-up
here
in
the
in
in
their
experimental
apparatus
and
then
there's
this
other
one,
which
is
a
six-year-old
zebra
fish
larvae,
and
this
is
from
the
zebra
fish
twitter
account.
A
A
A
A
So
this
is
where
they're
you
know,
they're
looking
at
this
embryo
and
how
it's
able
to
escape
a
predator,
so
they
actually
after
they
hatch,
they
form
these
tadpoles.
So
they
don't
form
the
full
amphibian.
Yet
they
have
these
tab.
This
tadpole
stage,
so
post-hatching
tadpoles
use
something
called
lateral
line,
neuromasts,
which
are
these
cells
along
the
sides
of
their
body
and
forms
a
line
down
the
body
and
these
cells
detect
water
motion.
A
A
We
ablated
neural
mass
function
with
this
gentamicin,
which
is
a
a
toxic
substance
to
assess
the
role
in
hatching
responses
to
disturbance
and
so
the
prior
to
vestibular
function.
This
normally
eliminated
the
hatching
response
to
a
complex
simulated
attack,
cue
egg
jiggling,
revealing
that
neuromast
mediated
early
mch.
So.
C
A
Where
they're
actually
introducing
this
this
predation,
which
is
where
some
predator
tries
to
break
into
the
egg
and
the
the
tadpoles,
can
detect
this
and
they're
able
to
respond
to
it.
So
that's
what
they're
talking
about
in
here
now
the
key
to
this
paper.
The
reason
I
pull
it
up
is
because
you
have
these
nice
images
of
the
tadpole
embryo.
A
And
then
there's
some
other.
This
is
the
hatching
response
here,
but
then
there's
some
other
images
here
where
they
actually
trace
out
some
of
the
tissues
and
some
of
the
anatomical
features.
So
these
are
the
nares
which
will
become
the
nose.
The
super
orbital
area,
which
is
above
the
eye-
and
you
can
see
these
things
forming
here,
so
you
can
see
that
all
right,
so
that's
the
new
embryo
images.
A
So
this
is
a
something
from
a
developmental
biologist
who's
not
really
impressed
with
genomics
as
it
stands
today
so
making
this
comment.
This
notion
that
genomes
build
cells,
tissues
bodies.
I
understand
that
by
repeating
this
mantra,
we
get
to
believe
it
without
questions,
but
it
jars
us
with
the
reality
of
a
developing
embryo
cells,
use
genes
and
are
not
directed
by
genes.
C
C
A
A
So
they
review
these
these
different
things
and
they
kind
of
come
to
this
new
hypothesis
on
one
mechanism
that
may
contribute
to
nervous
system
evolution,
and
that
is
brain
pathway,
duplication.
So
you
start
off
with
a
brain
pathway
in
development
and
those
brain
pathways
in
organisms
that
evolve.
They
don't
just
generate
new
pathways.
A
They
tend
to
take
pathways
and
duplicate
them.
So
this
is
something
that
happens
in
the
genes,
so
in
in
genetic
evolution
you
get
like
gene
duplications
or
other
things
where
you
get
things
expressed
twice
in
the
same
brain,
and
so
this
is
one
way
that
evolution
uses
to
produce
more
complexity.
In
the
brain,
so
like
gene
duplication,
we
propose
that
whole
brain
pathways
can
duplicate
and
the
duplicated
pathway
diverges
to
take
on
new
functions.
A
So,
but
they
have
different
totally
different
brain
pathways
for
this
humans
have
a
speech
bunch
of
speech,
areas
that
are
connected
and
birds
have
a
bunch
of
song
areas
that
are
connected
and
they
have
actually
looked
at
this.
This
group
of
people
have
looked
at
this
problem
and
they've
seen
you
know
they.
Don't
these
pathways
don't
look
anything
alike,
but
they've
actually
been
able
to
dissect
sort
of
the
common
ancestry
of
these,
and
so
they're
able
to
make
these
homologous
comparisons
between
what's
going
on
in
birds
and
humans,
so
explaining
these
complex
pathways.
A
A
A
So
this
is
an
example
here,
more
or
pictures
of
the
evolution
of
the
song
system
and
parrots
owing
to
sequential
pathway,
duplications,
the
ancestral
motor
pathway,
which
is
this
light
green
area
with
the
posterior
motor
connections
and
black
arrows
and
the
anterior
motor
connections
and
white
arrows.
And
so
this
shows
how
this
this
whole
entire
circuit
sort
of
comes
together
in
evolution.
A
This
paracore
song
system
proposed
to
evolve,
evolved
out
of
the
pre-existing
motor
pathways
through
duplication.
The
parrot
shell
song
system,
yellow,
which
are
these
areas
proposed
to
have
evolved
out
of
a
partial
duplication
of
the
core
song
system.
So
these
different
areas
that
these
different
have
different
functions
and
have
evolved
out
of
a
core
and
then
they
they
kind
of
expand
their
there.
A
A
A
This
is
based
on
a
paper
and
frontiers
and
ecology
and
evolution.
Communal
feasts
might
help
placazola
digest
their
food
faster
than
they
would
in
the
solo
case.
So
they
form
these
groups,
they
feed
on
a
common
resource
and
they
form
these
fronts
that
then
consume
the
food.
They
cooperate
basically
to
consume
the
food
and
it
helps
the
entire
group
placazoa,
but
they
point
out
that
social
eating
does
not
necessarily
mean
the
creatures
are.
Cooperative.
A
A
A
A
A
And
it's
a
sort
of
a
mold,
so
it's
not
you
know
it's
not
a
very.
I
guess
it's
a
complex
organism.
It's
has
a
sort
of
it
exhibits,
a
sort
of
collective
behavior,
and
you
know
this
is
then
of
course,
they're
saying
that
this
location
works
in
this
it
it
it's
a
parent,
indictation,
but
also
vertebrates.
A
Important
among
these
waveforms
is
a
3d
spiral
or
scroll
wave,
which
has
been
proposed
previously
to
have
a
twisted
variant,
the
turbine
wave.
So
this
is
where
we
talk
about
these
different
forms
of
sort
of
you
have
one
of
these
collective
organisms.
It's
a
collection
of
cells
and
their
morphogenesis
exhibits.
These
type
of
waves
that
go
through
and
coordinate
things.
A
It's
a
well-known
physics,
wave
they've
classified
different
types
of
waves
in
excitable
medium
and
then
there's
this
turbine
wave,
which
is
a
variant
of
it
urine.
We
argue
that
this
organism,
scroll
or
concentric
wave
territory
containing
press
poor,
impress
cell
types.
So
these
are
two
different
types
of
cell
in
this
organism.
A
A
A
A
Their
pioneering
observations
by
john
bonner
and
other
people,
brian
shafer,
in
the
60s
and
70s,
demonstrated
that
the
chemotaxis
to
c,
amp
and
c
signal
relay,
which
is
this
tax
chemotaxis,
are
where
cells
respond
to
these
chemical
signals
and
move
accordingly,
and
so
we've
talked
about.
I
think
about
chemotaxis
a
little
bit
in
this
group
where
they
have
a
chemical
signal,
and
there
are
these
waves
that
are
controlled
by
these
molecular
components.
A
And
the
chemotaxis
follows
this,
so
it
it's,
it
sort
of
coordinates
the
movement
of
the
cells,
so
this
mediates
aggregation,
and
so
so
they
kind
of
go
through
this
whole
model.
Here
of
what
they're
talking
about
they,
some
people
propose
that
this,
what
they
call
a
slug,
which
is
the
actual
you
know
collective,
is
organized
by
a
twisted
scroll
wave.
So
these
waves
actually
are
well
characterized
and
they
also
serve
to
organize
the
entire
colony
or
what
they
call
slug.
A
And
so
I
don't
know
what
how
they
make
the
connection
to
vertebrates,
but
this
is
a
picture
of
the
scroll
waves
and
other
types
of
waves
that
they
talk
about
here.
So
these
are.
This
is
a
type
of
reaction
we
haven't
talked.
Maybe
we've
talked
about
a
little
bit
in
the
group
called
the
bellazov
javatinsky
reaction,
which
is
where
you
can
do
this
with
a
chemical
medium
where
you
have
some
chemicals
and
you
can
create
a
reaction
that
generates
these
patterns
here,
these
wave
patterns
and
their
concentric
wave
patterns
that
come
out
from
a
source.
A
So
you
end
up
with
this
sort
of
reaction
where
there's
all
these
this
pattern
formation,
but
it
isn't
life.
That's
doing
this,
it's
just
a
chemical
reaction,
so
you
see
these
waves,
so
they
talk
about
waveforms
here
where
they
have.
They
illustrate
the
waveforms
in
a
simple
excitable
media.
So
in
the
chemical
case
it's
an
excitable
medium.
When
you
have
cells,
you
can
also
have
these
excitable
media
that
are
organized
in
this
wave.
So
here
in
this
example
here
anything
in
f.
A
A
A
These
are
relevant
sections
of
expanded,
spherical
waves.
So
this
is
here
it's
an
example
from
a
where
they
have
these
concentric
centers
and
then
okay.
So
this
is
the
a
is
the
concentric
ring
wave,
a
relayed
initiated
by
a
point
source
pacemaker.
So
this
is
a
pacemaker
cell.
That's
generating
this
pattern
and
then
b
is
where
you
have
other
cells
that
are
controlling
this
spiral
wave,
and
so
you
can
see
this.
This
is
a
little
bit
different
in
b.
A
All
right-
and
so
I'm
trying
to
figure
out
where
they
talk
about
vertebrates.
I
think
that
might
be
at
the
end.
Okay,
here
we
go.
The
simple
morphogenetic
system
may
provide
general
inspiration
indicating
general
principles
for
embryonic
development,
so
this
is
where
they're
expanding
it
out
to
embryogenesis.
A
There
is
not
much
evidence
that
waves
coupled
oscillators
and
relaying
are
important.
The
development
of
metazoan
animals,
so
this
is
something
that
we've
talked
about
with
respect
to
differentiation
waves
in
development,
an
early
model
proposed
a
progressive
phase
shift
between
two
traveling
waves
originating
at
the
organizer
as
a
mechanism
providing
positional
information
in
the
vertebrate
gastrula.
So
this
is
where
you
have
these
waves
that
are
organizing
things
and
they're
providing
positional
information.
A
So
we've
talked
about
positional
information
as
well,
and
this
basically
gives
some
sort
of
spatial
exp.
You
know
making
things
spatially
explicit
in
the
embryo
as
it
starts
to
matter
and
so
another
early
study
actually
detected
synchronized
oscillatory
morphogenetic
movement
in
the
chicken
gastro
and
another
study
detected
scaling
controlled
by
a
regulative
phase
gradient
as
predicted
in
the
goodwin
colon
model.
So
there
you
know,
there's
there's
a
sort
of
connection
between
vertebrate
embryogenesis
and
what's
going
on
in
the
dick
distillery.
A
Okay,
so
actually
has
to
go
well.
Thank
you
for
attending
akshay,
and
so
I
guess
that's
our
meeting.
Thank
you
for
attending
akshay
and
minak
and
I'll
be
back.
We
actually
won't
be
meeting
next
week,
I'll
be
taking
the
week
off,
but
then
the
week
after
we'll
be
talking
about
we'll
be
trying
to
move
forward
on
some
of
these
issues,
preparing
for
oktoberfest
talking
about
more
papers,
and
maybe
people
will
present
things
as
they
have
time.