Learning
should
be
adjusted
according
to
the
surprise
associated
with
observed
outcomes
but
calibrated
statistical
context.
For
example,
when
occasional
changepoints
are
expected,
surprising
weighted
heavily
speed
learning.
In
contrast,
uninformative
outliers
expected
occur
occasionally,
less
influential.
Here
we
dissociate
from
degree
which
they
demand
learning
using
a
predictive
inference
task
and
computational
modeling.
We
show
that
P300,
stimulus-locked
electrophysiological
response
previously
adjustments
in
behavior,
does
so
conditionally
on
source
of
surprise.
Larger
P300
signals
predicted
greater
changing
context,
context
where
was
indicative
one-off
outlier
(oddball).
Our
results
suggest
provides
signal
is
interpreted
by
downstream
processes
differentially
order
appropriately
calibrate
across
complex
environments.
Abstract
Transcutaneous
vagus
nerve
stimulation
(tVNS)
is
a
non‐invasive
neurostimulation
technique
that
currently
being
tested
as
potential
treatment
for
myriad
of
neurological
and
psychiatric
disorders.
However,
the
working
mechanisms
underlying
tVNS
are
poorly
understood
it
remains
unclear
whether
activates
every
participant.
Finding
biological
marker
imperative,
can
help
guide
research
on
clinical
applications
inform
researchers
optimal
sites
parameters
to
further
optimize
efficacy.
In
this
narrative
review,
we
discuss
five
biomarkers
review
available
evidence
these
markers
both
invasive
tVNS.
While
some
hold
promise
from
theoretical
perspective,
none
provide
clear
definitive
indications
increases
vagal
activity
or
augments
in
locus
coeruleus‐noradrenaline
network.
We
conclude
by
providing
several
recommendations
how
tackle
challenges
opportunities
when
researching
effects
Instantaneous
brain
states
have
consequences
for
our
sensation,
perception,
and
behaviour.
Fluctuations
in
arousal
neural
desynchronization
likely
pose
perceptually
relevant
states.
However,
their
relationship
relative
impact
on
perception
is
unclear.
We
here
show
that,
at
the
single-trial
level
humans,
local
sensory
cortex
(expressed
as
time-series
entropy)
versus
pupil-linked
differentially
perceptual
processing.
While
we
recorded
electroencephalography
(EEG)
pupillometry
data,
stimuli
of
a
demanding
auditory
discrimination
task
were
presented
into
high
or
low
via
real-time
closed-loop
setup.
Desynchronization
distinctly
influenced
stimulus-evoked
activity
shaped
behaviour
displaying
an
inverted
u-shaped
relationship:
States
intermediate
elicited
minimal
response
bias
fastest
responses,
while
gave
rise
to
highest
sensitivity.
Our
results
speak
model
which
independent
global
jointly
optimise
processing
performance.
Decision
bias
is
traditionally
conceptualized
as
an
internal
reference
against
which
sensory
evidence
compared.
Instead,
we
show
that
individuals
implement
decision
by
shifting
the
rate
of
accumulation
toward
a
bound.
Participants
performed
target
detection
task
while
recorded
EEG.
We
experimentally
manipulated
participants'
criterion
for
reporting
targets
using
different
stimulus-response
reward
contingencies,
inducing
either
liberal
or
conservative
bias.
Drift
diffusion
modeling
revealed
strategy
biased
target-present
choices.
Moreover,
resulted
in
stronger
midfrontal
pre-stimulus
2-6
Hz
(theta)
power
and
suppression
8-12
(alpha)
posterior
cortex.
Alpha
turn
was
linked
to
output
activity
visual
cortex,
expressed
through
59-100
(gamma)
power.
These
findings
observers
can
intentionally
control
cortical
excitability
strategically
bound
maximizes
reward.
Decisions
are
often
made
by
accumulating
ambiguous
evidence
over
time.
The
brain’s
arousal
systems
activated
during
such
decisions.
In
previous
work
in
humans,
we
found
that
evoked
responses
of
decisions
reported
rapid
dilations
the
pupil
and
track
a
suppression
biases
accumulation
decision-relevant
(de
Gee
et
al.,
2017).
Here,
show
this
arousal-related
decision
bias
acts
on
both
conservative
liberal
biases,
generalizes
from
humans
to
mice,
perceptual
memory-based
challenging
sound-detection
tasks,
impact
spontaneous
or
experimentally
induced
choice
was
reduced
under
high
phasic
arousal.
Similar
occurred
when
drawn
memory.
All
these
behavioral
effects
were
explained
biases.
Our
results
point
general
principle
interplay
between
decision-making.
Learning
should
be
adjusted
according
to
the
surprise
associated
with
observed
outcomes
but
calibrated
statistical
context.
For
example,
when
occasional
changepoints
are
expected,
surprising
weighted
heavily
speed
learning.
In
contrast,
uninformative
outliers
expected
occur
occasionally,
less
influential.
Here
we
dissociate
from
degree
which
they
demand
learning
using
a
predictive
inference
task
and
computational
modeling.
We
show
that
P300,
stimulus-locked
electrophysiological
response
previously
adjustments
in
behavior,
does
so
conditionally
on
source
of
surprise.
Larger
P300
signals
predicted
greater
changing
context,
context
where
was
indicative
one-off
outlier
(oddball).
Our
results
suggest
provides
signal
is
interpreted
by
downstream
processes
differentially
order
appropriately
calibrate
across
complex
environments.