Intelligence
is
a
human
construct
to
represent
the
ability
achieve
goals.
Given
this
wide
berth,
intelligence
has
been
defined
countless
times,
studied
in
variety
of
ways
and
represented
using
numerous
measures.
Understanding
ultimately
requires
theory
quantification,
both
which
have
proved
elusive.
I
develop
framework
–
Theory
Intelligences
(TIS)
that
applies
across
all
systems
from
physics,
biology,
humans
AI.
TIS
likens
calculus,
differentiating,
correlating
integrating
information.
operates
at
many
levels
scales
distils
these
into
parsimonious
macroscopic
centered
on
solving,
planning
their
optimization
accomplish
Notably,
can
be
expressed
informational
units
or
relative
goal
difficulty,
latter
as
complexity
system
(individual
benchmarked)
ability.
present
general
equations
for
its
components,
simple
expression
evolution
traits.
The
measures
developed
here
could
serve
gauge
different
facets
any
step-wise
transformation
argue
proxies
such
environment,
technology,
society
collectives
are
essential
possible
evolutionary
transitions
intelligence,
particularly
humans.
conclude
with
testable
predictions
offer
several
speculations.
Schemas
are
rich
and
complex
knowledge
structures
about
the
typical
unfolding
of
events
in
a
context.
For
example,
schema
lovely
dinner
at
restaurant.
central
psychology
neuroscience.
Here,
we
suggest
that
reinforcement
learning
(RL),
computational
theory
structure
world
relevant
goal-oriented
behavior,
underlies
learning.
We
synthesize
literature
schemas
RL
to
offer
three
principles
might
govern
schemas:
via
prediction
errors,
constructing
hierarchical
using
RL,
dimensionality
reduction
through
simplified
abstract
representation
world.
then
orbito-medial
prefrontal
cortex
is
involved
both
due
its
involvement
guiding
memory
reactivation
interactions
with
posterior
brain
regions.
Finally,
hypothesize
amount
underlie
gradients
along
ventral-dorsal
posterior-anterior
axes
cortex.
More
specific
detailed
representations
engage
ventral
parts,
while
abstraction
shift
toward
dorsal
anterior
parts
medial
PLoS ONE,
Год журнала:
2024,
Номер
19(1), С. e0296681 - e0296681
Опубликована: Янв. 19, 2024
Context-dependence
is
fundamental
to
risky
monetary
decision-making.
A
growing
body
of
evidence
suggests
that
temporal
context,
or
recent
events,
alters
risk-taking
at
a
minimum
three
timescales:
immediate
(e.g.
trial-by-trial),
neighborhood
group
consecutive
trials),
and
global
task-level).
To
examine
context
effects,
we
created
novel
choice
set
with
intentional
structure
in
which
option
values
shifted
between
multiple
levels
value
magnitude
("contexts")
several
times
over
the
course
task.
This
allowed
us
whether
effects
each
timescale
were
simultaneously
present
behavior
potential
mechanistic
role
arousal,
an
established
correlate
risk-taking,
context-dependency.
We
found
was
sensitive
immediate,
neighborhood,
decreased
following
large
(vs.
small)
outcome
amounts,
increased
positive
(but
not
negative)
shifts
when
cumulative
earnings
exceeded
expectations.
quantified
arousal
skin
conductance
responses,
related
timescale,
increasing
earnings,
suggesting
physiological
captures
task-level
assessment
performance.
Our
results
both
replicate
extend
prior
research
by
demonstrating
decision-making
consistently
dynamic
timescales
extends
some,
but
all
context-dependence.
Trends in Neurosciences,
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 1, 2024
The
orbitofrontal
cortex
(OFC)
and
ventromedial-prefrontal
(vmPFC)
play
a
key
role
in
decision-making
encode
task
states
addition
to
expected
value.
We
review
evidence
suggesting
connection
between
value
state
representations
argue
that
OFC
/
vmPFC
integrate
stimulus,
context,
outcome
information.
Comparable
encoding
principles
emerge
late
layers
of
deep
reinforcement
learning
(RL)
models,
where
single
nodes
exhibit
similar
forms
mixed-selectivity,
which
enables
flexible
readout
relevant
variables
by
downstream
neurons.
Based
on
these
lines
evidence,
we
suggest
outcome-maximization
leads
complex
representational
spaces
are
insufficiently
characterized
linear
signals
have
been
the
focus
most
prior
research
topic.
Major
outstanding
questions
concern
OFC/
across
tasks,
task-irrelevant
aspects,
hippocampus-PFC
interactions.
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2023,
Номер
unknown
Опубликована: Янв. 2, 2023
Abstract
Difficult
decisions
typically
involve
mental
effort,
which
scales
with
the
deployment
of
cognitive
(e.g.,
mnesic,
attentional)
resources
engaged
in
processing
decision-relevant
information.
But
how
does
brain
regulate
effort?
A
possibility
is
that
optimizes
a
resource
allocation
problem,
whereby
amount
invested
balances
its
expected
cost
(i.e.
effort)
and
benefit.
Our
working
assumption
subjective
decision
confidence
serves
as
benefit
term
hence
“metacognitive”
nature
control.
Here,
we
present
computational
model
for
online
metacognitive
control
or
oMCD.
Formally,
oMCD
Markov
Decision
Process
optimally
solves
ensuing
problem
under
agnostic
assumptions
about
inner
workings
underlying
system.
We
demonstrate
this
makes
quasi-optimal
policy
broad
class
processes,
including
-but
not
limited
to-
progressive
attribute
integration
.
disclose
oMCD’s
main
properties
(in
terms
choice,
response
time),
show
they
reproduce
most
established
empirical
results
field
value-based
making.
Finally,
discuss
possible
connections
between
prominent
neurocognitive
theories
effort
regulation.
Frontiers in Neuroscience,
Год журнала:
2023,
Номер
17
Опубликована: Сен. 5, 2023
For
adaptive
real-time
behavior
in
real-world
contexts,
the
brain
needs
to
allow
past
information
over
multiple
timescales
influence
current
processing
for
making
choices
that
create
best
outcome
as
a
person
goes
about
their
everyday
life.
The
neuroeconomics
literature
on
value-based
decision-making
has
formalized
such
choice
through
reinforcement
learning
models
two
extreme
strategies.
These
strategies
are
model-free
(MF),
which
is
an
automatic,
stimulus–response
type
of
action,
and
model-based
(MB),
bases
cognitive
representations
world
causal
inference
environment-behavior
structure.
emphasis
examining
neural
substrates
decision
been
striatum
prefrontal
regions,
especially
with
regards
“here
now”
decision-making.
Yet,
dichotomy
does
not
embrace
all
dynamic
complexity
involved.
In
addition,
despite
robust
research
role
hippocampus
memory
spatial
learning,
its
contribution
just
starting
be
explored.
This
paper
aims
better
appreciate
advance
successor
representation
(SR)
candidate
mechanism
encoding
state
hippocampus,
separate
from
reward
representations.
To
this
end,
we
review
relates
hippocampal
sequences
SR
showing
implementation
agents
improves
performance.
also
enables
perform
multiscale
temporal
biologically
plausible
manner.
Altogether,
articulate
framework
striatal
prefrontal-focused
account
mechanisms
underlying
various
time-related
concepts
self
cumulates
person’s
life
course.
How
do
I
decide
which
restaurant
to
eat
at?
form
and
update
the
beliefs
about
world
that
shape
my
behavior,
from
food
preferences
career
path?
The
brain
makes
decisions
large
small
our
lives
experience.
Most
of
these
are
based
on
learned
expectations
world,
or
beliefs,
updated
dynamically
according
ongoing
In
this
article
we
examine
cognitive,
computational,
neural
mechanisms
underlie
learning
decision
making.
We
first
summarize
key
advances
in
understanding
decision-making
research
separately
then
re-evaluate
findings
within
a
general
computation-centered
framework.
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Март 12, 2024
Abstract
Creative
thinking
is
composed
of
a
generation
phase,
where
individuals
form
candidate
ideas,
and
an
evaluation
monitor
the
quality
their
in
terms
both
originality
adequacy,
to
select
best
one.
Here,
we
conceptualize
creative
as
specific
type
decision-making,
participants
attribute
subjective
values
ideas
guide
choice.
Yet,
while
preferences
have
been
focus
many
studies
classical
involvement
decision-making
remains
largely
unexplored.
Combining
tasks
rating
tasks,
present
study
demonstrates
that
assign
these
depend
on
relative
balance
ideas’
which
determined
by
individual
predicts
abilities.
Using
functional
Magnetic
Resonance
Imaging,
found
human
reward
system
encodes
value
Default
Mode
Executive
Control
Networks,
rather
than
being
split
into
idea
evaluation,
respectively
reflect
adequacy
ideas.
Interestingly,
connectivity
Networks
with
correlates
individuals’
preferences.
These
results
bridge
gap
current
literature
providing
new
evidence
regarding
neural
bases
for
monitoring
add
valuation
incomplete
behavioral
accounts
creativity,
offering
perspectives
influence
Abstract
Social
information
can
be
used
to
optimize
decision‐making.
However,
the
simultaneous
presentation
of
multiple
sources
advice
lead
a
distinction
bias
in
judging
validity
information.
While
involvement
event‐related
potential
(ERP)
components
social
processing
has
been
studied,
how
they
are
modulated
by
(mis)judging
an
advisor's
remains
unknown.
In
two
experiments
participants
performed
decision‐making
task
with
highly
accurate
or
inaccurate
cues.
Each
experiment
consisted
initial,
learning,
and
test
phase.
During
learning
phase,
three
cues
were
simultaneously
presented
them
had
assessed.
The
effect
different
cue
constellations
on
ERPs
was
investigated.
subsequent
willingness
follow
oppose
tested.
Results
demonstrated
over
underestimating
accuracy
most
uncertain
P2
amplitude
significantly
increased
during
when
advisors
disagreement
as
compared
all
agreement,
regardless
validity.
Further,
larger
P3
outcome
found
more
informative
As
such,
related
smallest
amplitude.
findings
hint
at
possible
role
predictability
This
study
provides
novel
insights
into
judgment
Human Brain Mapping,
Год журнала:
2024,
Номер
45(6)
Опубликована: Апрель 15, 2024
Abstract
Humans
regularly
assess
the
quality
of
their
judgements,
which
helps
them
adjust
behaviours.
Metacognition
is
ability
to
accurately
evaluate
one's
own
and
it
assessed
by
comparing
objective
task
performance
with
subjective
confidence
report
in
perceptual
decisions.
However,
for
preferential
decisions,
assessing
metacognition
preference‐based
decisions
difficult
because
depends
on
goals
rather
than
criterion.
Here,
we
develop
a
new
index
that
integrates
choice,
reaction
time,
quantify
trial‐by‐trial
metacognitive
sensitivity
preference
judgements.
We
found
dorsomedial
prefrontal
cortex
(dmPFC)
right
anterior
insular
were
more
activated
when
participants
made
bad
evaluations.
Our
study
suggests
crucial
role
dmPFC‐insula
network
representing
online