<p><strong>Please
note
this
is
a
draft
on
which
we
are
seeking
feedback.
Substantial
changes
and
third
author
likely
be
added
to
the
next
version.</strong></p>
<p><br></p>
<p>The
hard
problem
of
consciousness
asks
why
there
something
it
like
conscious
organism.
We
address
from
1st
principles,
by
constructing
formalism
that
unifies
lower
higher
order
theories
consciousness.
assume
pancomputationalism
hold
environment
learns
organisms
exhibit
fit
behaviour
via
algorithm
call
natural
selection.
Selection
learn
classify
causes,
facilitating
adaptation.
Recent
experimental
mathematical
computer
science
elucidates
how.
Scaling
capacity
implies
progressively
``causal
identity''
reafference
P-consciousness,
then
self
awareness
A-consciousness,
meta
awareness.
use
resolve
in
precise
terms.
First,
deny
philosophical
zombie
all
circumstances
as
capable
P-conscious
being.
This
because
variable
presupposes
an
object
value
assigned.
Whether
X
causes
Y
depends
choice
X,
so
causality
learned
learning
such
Y,
not
presupposing
if
(presupposing
rather
than
inferring
abstractions
can
reduce
sample
efficiency
learning).
However,
discriminatory
process
requires
states
differentiated
value.
Without
objects,
variables
or
values,
only
quality.
By
mean
organism
attracted
repulsed
physical
state.
Learning
reduces
quality
into
objects
policies
classifying
cause
affect
(``representations''
just
triggered
phenomenal
content).
Where
selection
pressures
require
its
own
interventions,
policy
(a
``1st
causal
identity'')
has
persists
across
Thus
have
P-consciousness
allows
them
adapt
with
greater
efficiency,
infer
affect.
argue
neither
P
nor
A-consciousness
alone
remarkable,
but
when
gives
rise
obtain
``H-consciousness''
(what
Boltuc
argues
crux
problem).
occurs
<em>o</em>
<em>u</em>'s
prediction
<em>o</em>'s
interventions
``2nd
approximating
intent).
contents
2nd
identities,
predicting
another's
one's
identities
becomes
possible
know
what
one
knows
feels,
act
upon
information
communicate
meaning
Gricean
sense.
two
aspects
H-concsiousness,
acting
accord
hierarchy
simplify
classifiers
psychophysical
principle
causality.</p>
Abstract
Research
across
various
disciplines
shows
the
benefits
of
learning
and
memory
for
gaining
functionality
improving
performance.
It
is
increasingly
clear
that
can
be
found
in
both
physical
virtual
systems,
from
intelligent
life
forms
to
machines,
simple
organisms,
even
designed
chemical
systems.
We
are
interested
understanding
what
extent
embodiments
these
processes
synthesized
engineered
bottom
up
by
using
molecular
components.
In
this
perspective,
we
raise
attempt
answer
conceptual
questions
about
supramolecular
systems
as
smallest
units
capable
learning.
define
a
process
where
complex
system
interacting
components
modifies
itself
response
an
applied
stress
or
stimulus,
resulting
structural
changes
information
gain.
highlight
potential
chemistry
networks
design
meet
definition
encoding,
decoding,
storing
within
system′s
composition.
Understanding
basis
could
inform
development
materials
autonomously
acquire
new
properties
their
environment.
This
also
provide
insights
next‐generation
computing
physical,
rather
than
virtual,
Nature Communications,
Год журнала:
2024,
Номер
15(1)
Опубликована: Июнь 4, 2024
Abstract
Biological
systems
interact
directly
with
the
environment
and
learn
by
receiving
multimodal
feedback
via
sensory
stimuli
that
shape
formation
of
internal
neuronal
representations.
Drawing
inspiration
from
biological
concepts
such
as
exploration
processing
eventually
lead
to
behavioral
conditioning,
we
present
a
robotic
system
handling
objects
through
learning.
A
small-scale
organic
neuromorphic
circuit
locally
integrates
adaptively
processes
stimuli,
enabling
robot
intelligently
its
surroundings.
The
real-time
low-voltage
devices
synaptic
functionality
forms
associative
connections
thus
learns
avoid
potentially
dangerous
objects.
This
work
demonstrates
adaptive
neuro-inspired
circuitry
multifunctional
materials,
can
accommodate
efficient
bio-inspired
learning
for
advancing
intelligent
robotics.
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Фев. 6, 2024
Abstract
Inferring
and
understanding
the
underlying
connectivity
structure
of
a
system
solely
from
observed
activity
its
constituent
components
is
challenge
in
many
areas
science.
In
neuroscience,
techniques
for
estimating
are
paramount
when
attempting
to
understand
network
neural
systems
their
recorded
patterns.
To
date,
no
universally
accepted
method
exists
inference
effective
connectivity,
which
describes
how
node
mechanistically
affects
other
nodes.
Here,
focussing
on
purely
excitatory
networks
small
intermediate
size
continuous
dynamics,
we
provide
systematic
comparison
different
approaches
connectivity.
Starting
with
Hopf
neuron
model
conjunction
known
ground
truth
structural
reconstruct
system’s
matrix
using
variety
algorithms.
We
show
that,
sparse
non-linear
delays,
combining
lagged-cross-correlation
(LCC)
approach
recently
published
derivative-based
covariance
analysis
provides
most
reliable
estimation
matrix.
also
that
linear
networks,
LCC
has
comparable
performance
based
transfer
entropy,
at
drastically
lower
computational
cost.
highlight
works
best
decreases
larger
less
networks.
Applying
dynamics
without
time
find
it
does
not
outperform
methods.
Employing
model,
then
use
estimated
as
basis
forward
simulation
order
recreate
under
certain
conditions,
method,
LCC,
results
higher
trace-to-trace
correlations
than
methods
noise-driven
systems.
Finally,
apply
empirical
biological
data.
subset
nervous
nematode
C.
Elegans
.
computationally
simple
performs
better
another
published,
more
expensive
reservoir
computing-based
method.
Our
comparatively
can
be
used
reliably
estimate
directed
presence
spatio-temporal
delays
noise.
concrete
suggestions
scenario
common
research,
where
only
neuronal
set
neurons
known.
Behavioral Ecology,
Год журнала:
2024,
Номер
35(3)
Опубликована: Апрель 1, 2024
Some
cognitive
abilities
are
suggested
to
be
the
result
of
a
complex
social
life,
allowing
individuals
achieve
higher
fitness
through
advanced
strategies.
However,
most
evidence
is
correlative.
Here,
we
provide
an
experimental
investigation
how
group
size
and
composition
affect
brain
development
in
guppy
(
Evolution & Development,
Год журнала:
2024,
Номер
26(4)
Опубликована: Фев. 23, 2024
Abstract
Nervous
system
is
one
of
the
key
adaptations
underlying
evolutionary
success
majority
animal
groups.
Ctenophores
(or
comb
jellies)
are
gelatinous
marine
invertebrates
that
were
probably
first
lineage
to
diverge
from
rest
animals.
Due
phylogenetic
position
and
multiple
unique
adaptations,
noncentralized
nervous
jellies
has
been
in
center
debate
around
origin
kingdom
whether
it
happened
only
once
or
twice.
Here,
we
discuss
latest
findings
ctenophore
neuroscience
challenges
on
way
build
a
clear
picture
system.
Brain and Behavior,
Год журнала:
2024,
Номер
14(5)
Опубликована: Апрель 29, 2024
Abstract
Background
Living
in
a
social
dominance
hierarchy
presents
different
benefits
and
challenges
for
dominant
subordinate
males
females,
which
might
turn
affect
their
cognitive
needs.
Despite
the
extensive
research
on
group‐living
species,
there
is
still
knowledge
gap
regarding
how
status
impacts
brain
morphology
abilities.
Methods
Here,
we
tested
male
female
dominants
subordinates
of
Neolamprologus
pulcher
,
cichlid
fish
species
with
size‐based
hierarchy.
We
ran
three
executive
function
tests
flexibility
(reversal
learning
test),
self‐control
(detour
working
memory
(object
permanence
followed
by
region
size
measurements.
Results
Performance
was
not
influenced
or
sex.
However,
exhibited
brain–body
slope
that
relatively
steeper
than
subordinates.
Furthermore,
individual
performance
reversal
detour
correlated
morphology,
some
trade‐offs
among
major
regions
like
telencephalon,
cerebellum,
optic
tectum.
Conclusion
As
individuals’
growth
strategies
varied
depending
without
affecting
functions,
associated
yield
potential
effect
cognition
instead.
Overall,
findings
highlight
importance
studying
just
to
understand
better
individual's
ecology
shape
its
cognition.
PLoS ONE,
Год журнала:
2025,
Номер
20(1), С. e0315623 - e0315623
Опубликована: Янв. 22, 2025
Not
all
corals
are
attached
to
the
substrate;
some
taxa
solitary
and
free-living,
allowing
them
migrate
into
preferred
habitats.
However,
lifestyle
of
these
mobile
corals,
including
how
they
move
navigate
for
migration,
remains
largely
obscure.
This
study
investigates
specific
biomechanics
Cycloseris
cyclolites
,
a
free-living
coral
species,
during
phototactic
behaviour
in
response
blue
white
light
stimuli.
Our
results
indicate
strong
positive
with
86.7%
(n
=
15)
samples
moving
towards
source,
while
only
20%
responded
similarly
(400–700
nm).
Locomotion,
characterised
by
periodic
pulses
lasting
1–2
hours,
involved
distances
up
220
mm
trials,
whereas
significantly
shorter
were
observed
trials
(2,
5
8
mm).
Trails
two
sources
reinforced
preference
over
white,
consistently
away
from
(11,
15
3mm).
High-resolution
time-laps
captured
forward
motion
that
appeared
driven
three
key
factors:
tissue
inflation,
which
increased
contact
surface
area
lift
friction;
ventral
foot/pads,
adjusting
substrate
interaction/friction;
contraction
twisting
lateral
peripheral
tissues,
propelled
coordinated
manner
resembling
pulsed
swimming
jellyfish.
findings
provide
new
insights
mobility
mechanisms,
emphasising
role
inflation
active
locomotion,
potential
implications
neural
systems,
vision
habitat
selection.