Memristors
are
electronic
devices
with
non-volatile,
adjustability,
and
variability,
which
can
enhance
the
learning
adaptability
of
neural
networks.
A
model
a
photosensitive
FitHugh
Nagumo
(FHN)
neuron
that
mimic
discharge
mechanism
neurons
was
recently
proposed.
This
article
presents
controlled
memristive
(CMP-FHN)
based
on
this
concept
by
introducing
memristor
setting
switch
to
regulate
its
access
status.
Firstly,
build
CMP-FHN
examine
how
it
discharges.
To
obtain
four
coupling
loops,
two
models
an
induction
coil
coupled.
Subsequently,
analysis
conducted
circuit
consistent
states,
discovered
stable
synchronization
between
could
be
attained;
additionally,
time
found
influenced
external
current
stimulation
strength
gain
ratio.
Furthermore,
model's
shows
robustness
outside
noise
disturbances.
Ultimately,
inconsistent
states
revealed
system
desynchronizes—that
is,
energy
is
continuously
fed
into
channel
but
unable
attain
balance.
Potential
harm
from
over
avoided
desynchronization.
PLoS Computational Biology,
Journal Year:
2023,
Volume and Issue:
19(2), P. e1010853 - e1010853
Published: Feb. 1, 2023
The
synaptic
organization
of
the
brain
is
constantly
modified
by
activity-dependent
plasticity.
In
several
neurological
disorders,
abnormal
neuronal
activity
and
pathological
connectivity
may
significantly
impair
normal
function.
Reorganization
circuits
therapeutic
stimulation
has
potential
to
restore
dynamics.
Increasing
evidence
suggests
that
temporal
pattern
crucially
determines
long-lasting
effects
stimulation.
Here,
we
tested
whether
a
specific
can
enable
suppression
pathologically
strong
inter-population
through
spike-timing-dependent
plasticity
(STDP).
More
specifically,
how
introducing
time
shift
between
stimuli
delivered
two
interacting
populations
neurons
effectively
decouple
them.
To
end,
first
used
tractable
model,
i.e.,
bidirectionally
coupled
leaky
integrate-and-fire
(LIF)
neurons,
theoretically
analyze
optimal
range
frequency
for
decoupling.
We
then
extended
our
results
reciprocally
connected
(modules)
where
delayed
connections
were
STDP.
As
predicted
theoretical
results,
appropriately
time-shifted
causes
decoupling
two-module
system
STDP,
unlearning
interactions
populations.
Based
on
overall
topology
connections,
modules,
in
turn,
desynchronization
outlasts
cessation
Decoupling
be
realized
burst
as
well
continuous
simulation.
Our
provide
insight
into
further
optimization
variety
multichannel
protocols
aiming
at
reshaping
diseased
networks.
Physical Review Research,
Journal Year:
2025,
Volume and Issue:
7(2)
Published: May 9, 2025
Aberrant
oscillatory
activity
is
a
hallmark
of
several
brain
disorders
including
Parkinson's
disease
(PD).
Specifically,
interactions
between
neurons
the
subthalamic
nucleus
(STN)
and
globus
pallidus
externus
(GPe)
may
contribute
to
emergence
maintenance
overly
synchronized
beta-band
(15–30
Hz)
oscillations
be
associated
with
motor
symptoms
PD.
Excessive
beta
synchrony
can
mitigated
by
pharmacological
intervention
deep
stimulation
(DBS).
Alternatively,
strategies
that
aim
selectively
modulate
interpopulation
connections
have
therapeutic
potential.
Here,
we
tested
computationally
whether
dual
targeting
STN
GPe
time-shifted
pathologically
strong
synapses
through
inhibitory
spike-timing-dependent
plasticity.
More
specifically,
examined
how
paired
stimuli
delivered
lead
synaptic
rewiring.
To
end,
first
theoretically
analyzed
optimal
range
time
shift
frequency
for
effective
Then,
as
minimal
model
generating
in
healthy
PD
conditions,
considered
STN-GPe
loop
biologically
inspired
parameters.
Time-shifted
modified
long-lasting
This
ultimately
caused
desynchronizing
aftereffects,
resulting
reduced
coupling
network
restoration
dynamics.
Our
findings
demonstrate
critical
role
neuroplasticity
shaping
effects
optimization
variety
multisite
paradigms
aimed
at
reshaping
dysfunctional
networks
Published
American
Physical
Society
2025
Journal of Biological Physics,
Journal Year:
2023,
Volume and Issue:
49(4), P. 483 - 507
Published: Sept. 1, 2023
Synchronization
is
a
widespread
phenomenon
in
the
brain.
Despite
numerous
studies,
specific
parameter
configurations
of
synaptic
network
structure
and
learning
rules
needed
to
achieve
robust
enduring
synchronization
neurons
driven
by
spike-timing-dependent
plasticity
(STDP)
temporal
networks
subject
homeostatic
structural
(HSP)
remain
unclear.
Here,
we
bridge
this
gap
determining
required
high
stable
degrees
complete
(CS)
phase
(PS)
time-varying
small-world
random
neural
STDP
HSP.
In
particular,
found
that
decreasing
P
(which
enhances
strengthening
effect
on
average
weight)
increasing
F
speeds
up
swapping
rate
synapses
between
neurons)
always
lead
higher
more
CS
PS
networks,
provided
parameters
such
as
time
delay
[Formula:
see
text],
degree
rewiring
probability
text]
have
some
appropriate
values.
When
are
not
fixed
at
these
values,
stability
may
increase
or
decrease
when
increases,
depending
topology.
It
also
can
induce
intermittent
whose
occurrence
independent
F.
Our
results
could
applications
designing
neuromorphic
circuits
for
optimal
information
processing
transmission
via
phenomena.
Frontiers in Human Neuroscience,
Journal Year:
2023,
Volume and Issue:
16
Published: Jan. 26, 2023
Introduction
Parkinson's
disease
(PD)
is
a
movement
disorder
characterized
by
the
pathological
beta
band
(15–30
Hz)
neural
oscillations
within
basal
ganglia
(BG).
It
shown
that
suppression
of
abnormal
correlated
with
improvement
PD
motor
symptoms,
which
goal
standard
therapies
including
deep
brain
stimulation
(DBS).
To
overcome
stimulation-induced
side
effects
and
inefficiencies
conventional
DBS
(cDBS)
to
reduce
administered
current,
closed-loop
adaptive
(aDBS)
techniques
were
developed.
In
this
method,
frequency
and/or
amplitude
are
modulated
based
on
various
biomarkers.
Methods
Here,
computational
modeling
cortico-BG-thalamic
network
in
normal
conditions,
we
show
aDBS
subthalamic
nucleus
(STN)
modulation
leads
more
effective
parkinsonian
BG.
Results
Our
results
restored
their
range
reliability
response
thalamic
neurons
cortex
commands
retained
due
modulation.
Furthermore,
notably
less
current
during
compared
cDBS
control
STN
local
field
potential
(LFP)
activity.
Discussion
Efficient
models
may
contribute
clinical
development
optimized
designed
patients
while
leading
better
therapeutic
outcome.
Frontiers in Cellular Neuroscience,
Journal Year:
2024,
Volume and Issue:
18
Published: March 14, 2024
Neural
interactions
in
the
brain
are
affected
by
transmission
delays
which
may
critically
alter
signal
propagation
across
different
regions
both
normal
and
pathological
conditions.
The
effect
of
interaction
on
dynamics
generic
neural
networks
has
been
extensively
studied
theoretical
computational
models.
However,
role
development
oscillatory
basal
ganglia
(BG)
Parkinson's
disease
(PD)
is
overlooked.
