Epilepsia,
Год журнала:
2023,
Номер
64(4), С. 1074 - 1086
Опубликована: Фев. 2, 2023
Abstract
Objective
Understanding
fluctuations
in
seizure
severity
within
individuals
is
important
for
determining
treatment
outcomes
and
responses
to
therapy,
as
well
assessing
novel
treatments
epilepsy.
Current
methods
grading
rely
on
qualitative
interpretations
from
patients
clinicians.
Quantitative
measures
of
would
complement
existing
approaches
electroencephalographic
(EEG)
monitoring,
outcome
prediction.
Therefore,
we
developed
a
library
quantitative
EEG
markers
that
assess
the
spread
intensity
abnormal
electrical
activity
during
after
seizures.
Methods
We
analyzed
intracranial
(iEEG)
recordings
1009
seizures
63
patients.
For
each
seizure,
computed
16
capture
signal
magnitude,
spread,
duration,
postictal
suppression
Results
distinguished
focal
versus
subclinical
across
In
individual
patients,
53%
had
moderate
large
difference
(rank
sum
,
)
between
three
or
more
markers.
Circadian
longer
term
changes
were
found
majority
Significance
demonstrate
feasibility
using
iEEG
measure
severity.
Our
distinguish
types
are
therefore
sensitive
established
differences
results
also
suggest
modulated
over
different
timescales.
envisage
our
proposed
will
be
expanded
updated
collaboration
with
epilepsy
research
community
include
modalities.
Proceedings of the National Academy of Sciences,
Год журнала:
2023,
Номер
120(28)
Опубликована: Июль 3, 2023
Heterogeneity
is
the
norm
in
biology.
The
brain
no
different:
Neuronal
cell
types
are
myriad,
reflected
through
their
cellular
morphology,
type,
excitability,
connectivity
motifs,
and
ion
channel
distributions.
While
this
biophysical
diversity
enriches
neural
systems'
dynamical
repertoire,
it
remains
challenging
to
reconcile
with
robustness
persistence
of
function
over
time
(resilience).
To
better
understand
relationship
between
excitability
heterogeneity
(variability
within
a
population
neurons)
resilience,
we
analyzed
both
analytically
numerically
nonlinear
sparse
network
balanced
excitatory
inhibitory
connections
evolving
long
scales.
Homogeneous
networks
demonstrated
increases
strong
firing
rate
correlations-signs
instability-in
response
slowly
varying
modulatory
fluctuation.
Excitability
tuned
stability
context-dependent
way
by
restraining
responses
challenges
limiting
correlations,
while
enriching
dynamics
during
states
low
drive.
was
found
implement
homeostatic
control
mechanism
enhancing
resilience
changes
size,
connection
probability,
strength
variability
synaptic
weights,
quenching
volatility
(i.e.,
its
susceptibility
critical
transitions)
dynamics.
Together,
these
results
highlight
fundamental
role
played
cell-to-cell
face
change.
Neurobiology of Disease,
Год журнала:
2023,
Номер
182, С. 106131 - 106131
Опубликована: Апрель 21, 2023
Epilepsy
is
a
complex
disease
that
requires
various
approaches
for
its
study.
This
short
review
discusses
the
contribution
of
theoretical
and
computational
models.
The
presents
frameworks
underlie
understanding
certain
seizure
properties
their
classification
based
on
dynamical
at
onset
offset
seizures.
Dynamical
system
tools
are
valuable
resources
in
study
These
can
provide
insights
into
mechanisms
offer
framework
classification,
by
analyzing
complex,
dynamic
behavior
Additionally,
models
have
high
potential
clinical
applications,
as
they
be
used
to
develop
more
accurate
diagnostic
personalized
medicine
tools.
We
discuss
modeling
span
different
scales
levels,
while
also
questioning
neurocentric
view,
emphasizing
importance
considering
glial
cells.
Finally,
we
explore
epistemic
value
provided
this
type
approach.
Dynamical
system
tools
offer
a
complementary
approach
to
detailed
biophysical
seizure
modeling,
with
high
potential
for
clinical
applications.
This
review
describes
the
theoretical
framework
that
provides
basis
theorizing
certain
properties
of
seizures
and
their
classification
according
dynamical
at
onset
offset.
We
describe
various
modeling
approaches
spanning
different
scales,
from
single
neurons
large-scale
networks.
narrative
an
accessible
overview
this
field,
including
non-exhaustive
examples
key
recent
works.
Epilepsia,
Год журнала:
2023,
Номер
64(4), С. 1074 - 1086
Опубликована: Фев. 2, 2023
Abstract
Objective
Understanding
fluctuations
in
seizure
severity
within
individuals
is
important
for
determining
treatment
outcomes
and
responses
to
therapy,
as
well
assessing
novel
treatments
epilepsy.
Current
methods
grading
rely
on
qualitative
interpretations
from
patients
clinicians.
Quantitative
measures
of
would
complement
existing
approaches
electroencephalographic
(EEG)
monitoring,
outcome
prediction.
Therefore,
we
developed
a
library
quantitative
EEG
markers
that
assess
the
spread
intensity
abnormal
electrical
activity
during
after
seizures.
Methods
We
analyzed
intracranial
(iEEG)
recordings
1009
seizures
63
patients.
For
each
seizure,
computed
16
capture
signal
magnitude,
spread,
duration,
postictal
suppression
Results
distinguished
focal
versus
subclinical
across
In
individual
patients,
53%
had
moderate
large
difference
(rank
sum
,
)
between
three
or
more
markers.
Circadian
longer
term
changes
were
found
majority
Significance
demonstrate
feasibility
using
iEEG
measure
severity.
Our
distinguish
types
are
therefore
sensitive
established
differences
results
also
suggest
modulated
over
different
timescales.
envisage
our
proposed
will
be
expanded
updated
collaboration
with
epilepsy
research
community
include
modalities.
