bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2022,
Volume and Issue:
unknown
Published: Dec. 2, 2022
Abstract
Spatiotemporal
oscillations
underlie
all
cognitive
brain
functions.
Large-scale
models,
constrained
by
neuroimaging
data,
aim
to
trace
the
principles
underlying
such
macroscopic
neural
activity
from
intricate
and
multi-scale
structure
of
brain.
Despite
substantial
progress
in
field,
many
aspects
about
mechanisms
behind
onset
spatiotemporal
dynamics
are
still
unknown.
In
this
work
we
establish
a
simple
framework
for
emergence
complex
dynamics,
including
high-dimensional
chaos
travelling
waves.
The
model
consists
network
90
regions,
whose
structural
connectivity
is
obtained
tractography
data.
each
area
governed
Jansen
mass
normalize
total
input
received
node
so
it
amounts
same
across
areas.
This
assumption
allows
existence
an
homogeneous
invariant
manifold,
i.e.,
set
different
stationary
oscillatory
states
which
nodes
behave
identically.
Stability
analysis
these
solutions
unveils
transverse
instability
synchronized
state,
gives
rise
types
as
chaotic
alpha
activity.
Additionally,
illustrate
ubiquity
route
towards
next-generation
models.
Altogehter,
our
results
unveil
bifurcation
landscape
that
underlies
function
Author
summary
Monitoring
with
techniques
EEG
fMRI
has
revealed
normal
characterized
dynamics.
behavior
well
captured
large-scale
models
incorporate
data
MRI-based
methods.
Nonetheless,
not
yet
clear
how
emerges
interplay
regions.
paper
show
waves
can
arise
through
destabilization
state.
Such
instabilities
akin
those
observed
chemical
reactions
turbulence,
allow
semi-analytical
treatment
uncovers
overall
dynamical
system.
Overall,
establishes
characterizes
general
Journal of Neural Engineering,
Journal Year:
2024,
Volume and Issue:
21(2), P. 026024 - 026024
Published: March 26, 2024
Abstract
Objective
.
Transcranial
alternating
current
stimulation
(tACS)
can
be
used
to
non-invasively
entrain
neural
activity
and
thereby
cause
changes
in
local
oscillatory
power.
Despite
its
increased
use
cognitive
clinical
neuroscience,
the
fundamental
mechanisms
of
tACS
are
still
not
fully
understood.
Approach
We
developed
a
computational
neuronal
network
model
two-compartment
pyramidal
neurons
(PY)
inhibitory
interneurons,
which
mimic
cortical
circuits.
modeled
with
electric
field
strengths
that
achievable
human
applications.
then
simulated
intrinsic
measured
entrainment
investigate
how
modulates
ongoing
endogenous
oscillations.
Main
results
The
intensity-specific
effects
non-linear.
At
low
intensities
(<0.3
mV
mm
−1
),
desynchronizes
firing
relative
higher
(>0.3
entrained
exogenous
field.
further
explore
parameter
space
find
oscillations
also
depends
on
frequency
by
following
an
Arnold
tongue.
Moreover,
networks
amplify
tACS-induced
via
synaptic
coupling
effects.
Our
shows
PY
directly
drive
neurons.
Significance
presented
this
study
provide
mechanistic
framework
for
understanding
intensity-
frequency-specific
oscillating
fields
networks.
This
is
crucial
rational
selection
studies
NeuroImage,
Journal Year:
2023,
Volume and Issue:
270, P. 119938 - 119938
Published: Feb. 10, 2023
Cortical
function
emerges
from
the
interactions
of
multi-scale
networks
that
may
be
studied
at
a
high
level
using
neural
mass
models
(NMM)
represent
mean
activity
large
numbers
neurons.
Here,
we
provide
first
new
framework
called
laminar
NMM,
or
LaNMM
for
short,
where
combine
conduction
physics
with
NMMs
to
simulate
electrophysiological
measurements.
Then,
employ
this
infer
location
oscillatory
generators
laminar-resolved
data
collected
prefrontal
cortex
in
macaque
monkey.
We
define
minimal
model
capable
generating
coupled
slow
and
fast
oscillations,
optimize
LaNMM-specific
parameters
fit
multi-contact
recordings.
rank
candidate
an
optimization
evaluates
match
between
functional
connectivity
(FC)
data,
FC
is
defined
by
covariance
bipolar
voltage
measurements
different
cortical
depths.
The
family
best
solutions
reproduces
observed
electrophysiology
selecting
locations
pyramidal
cells
their
synapses
result
generation
superficial
layers
across
most
depths,
line
recent
literature
proposals.
In
closing,
discuss
how
hybrid
modeling
can
more
generally
used
circuitry.
Physical review. E,
Journal Year:
2024,
Volume and Issue:
109(1)
Published: Jan. 31, 2024
Recently,
low-dimensional
models
of
neuronal
activity
have
been
exactly
derived
for
large
networks
deterministic,
quadratic
integrate-and-fire
(QIF)
neurons.
Such
firing
rate
(FRM)
describe
the
emergence
fast
collective
oscillations
(>30
Hz)
via
frequency
locking
a
subset
neurons
to
global
oscillation
frequency.
However,
suitability
such
realistic
states
is
seriously
challenged
by
fact
that
during
episodes
oscillations,
discharges
are
often
very
irregular
and
low
rates
compared
Here
we
extend
theory
derive
exact
FRM
QIF
include
noise
show
stochastic
displaying
at
governed
same
evolution
equations
as
deterministic
networks.
Our
results
reconcile
two
traditionally
confronted
views
on
synchronization
upgrade
applicability
broad
range
biologically
states.
Neural Computation,
Journal Year:
2024,
Volume and Issue:
36(8), P. 1476 - 1540
Published: July 19, 2024
Abstract
Pulse-coupled
spiking
neural
networks
are
a
powerful
tool
to
gain
mechanistic
insights
into
how
neurons
self-organize
produce
coherent
collective
behavior.
These
use
simple
neuron
models,
such
as
the
θ-neuron
or
quadratic
integrate-and-fire
(QIF)
neuron,
that
replicate
essential
features
of
real
dynamics.
Interactions
between
modeled
with
infinitely
narrow
pulses,
spikes,
rather
than
more
complex
dynamics
synapses.
To
make
these
biologically
plausible,
it
has
been
proposed
they
must
also
account
for
finite
width
which
can
have
significant
impact
on
network
However,
derivation
and
interpretation
pulses
contradictory,
pulse
shape
is
largely
unexplored.
Here,
I
take
comprehensive
approach
coupling
in
QIF
θ-neurons.
argue
activate
voltage-dependent
synaptic
conductances
show
implement
them
their
effect
last
through
phase
after
spike.
Using
an
exact
low-dimensional
description
globally
coupled
neurons,
prove
instantaneous
interactions
oscillations
emerge
due
effective
mean
voltage.
analyze
by
means
family
smooth
functions
arbitrary
symmetric
asymmetric
shapes.
For
resulting
voltage
not
very
synchronizing
but
slightly
skewed
spike
readily
generate
oscillations.
The
results
unveil
synchronization
mechanism
at
heart
emergent
behavior,
facilitated
complementary
traditional
transmission
networks.
Physical review. E,
Journal Year:
2025,
Volume and Issue:
111(1)
Published: Jan. 24, 2025
We
investigate
a
large
ensemble
of
quadratic
integrate-and-fire
neurons
with
heterogeneous
input
currents
and
adaptation
variables.
Our
analysis
reveals
that,
for
specific
class
adaptation,
termed
spike-frequency
the
high-dimensional
system
can
be
exactly
reduced
to
low-dimensional
ordinary
differential
equations,
which
describes
dynamics
three
mean-field
variables:
population's
firing
rate,
mean
membrane
potential,
variable.
The
resulting
rate
equations
(FREs)
uncover
key
generic
feature
networks
adaptation:
Both
center
width
distribution
neurons'
frequencies
are
reduced,
this
largely
promotes
emergence
collective
synchronization
in
network.
findings
further
supported
by
bifurcation
FREs,
accurately
captures
spiking
neuron
network,
including
phenomena
such
as
oscillations,
bursting,
macroscopic
chaos.
Frontiers in Neuroscience,
Journal Year:
2025,
Volume and Issue:
19
Published: March 12, 2025
Gamma
transcranial
alternating
current
stimulation
(gamma-tACS)
represents
a
novel
neuromodulation
technique
with
promising
therapeutic
applications
across
neurodegenerative
diseases.
This
mini-review
consolidates
recent
preclinical
and
clinical
findings,
examining
the
mechanisms
by
which
gamma-tACS
influences
neural
oscillations,
enhances
synaptic
plasticity,
modulates
neuroimmune
responses.
Preclinical
studies
have
demonstrated
capacity
of
to
synchronize
neuronal
firing,
support
long-term
neuroplasticity,
reduce
markers
neuroinflammation,
suggesting
its
potential
counteract
processes.
Early
indicate
that
may
improve
cognitive
functions
network
connectivity,
underscoring
ability
restore
disrupted
oscillatory
patterns
central
performance.
Given
intricate
multifactorial
nature
gamma
development
tailored,
optimized
tACS
protocols
informed
extensive
animal
research
is
crucial.
Overall,
presents
avenue
for
advancing
treatments
resilience
in
range
conditions.
PLoS Computational Biology,
Journal Year:
2023,
Volume and Issue:
19(4), P. e1010781 - e1010781
Published: April 12, 2023
Spatiotemporal
oscillations
underlie
all
cognitive
brain
functions.
Large-scale
models,
constrained
by
neuroimaging
data,
aim
to
trace
the
principles
underlying
such
macroscopic
neural
activity
from
intricate
and
multi-scale
structure
of
brain.
Despite
substantial
progress
in
field,
many
aspects
about
mechanisms
behind
onset
spatiotemporal
dynamics
are
still
unknown.
In
this
work
we
establish
a
simple
framework
for
emergence
complex
dynamics,
including
high-dimensional
chaos
travelling
waves.
The
model
consists
network
90
regions,
whose
structural
connectivity
is
obtained
tractography
data.
each
area
governed
Jansen
mass
normalize
total
input
received
node
so
it
amounts
same
across
areas.
This
assumption
allows
existence
an
homogeneous
invariant
manifold,
i.e.,
set
different
stationary
oscillatory
states
which
nodes
behave
identically.
Stability
analysis
these
solutions
unveils
transverse
instability
synchronized
state,
gives
rise
types
as
chaotic
alpha
activity.
Additionally,
illustrate
ubiquity
route
towards
next
generation
models.
Altogehter,
our
results
unveil
bifurcation
landscape
that
underlies
function
arXiv (Cornell University),
Journal Year:
2022,
Volume and Issue:
unknown
Published: Jan. 1, 2022
Recently,
low-dimensional
models
of
neuronal
activity
have
been
exactly
derived
for
large
networks
deterministic,
Quadratic
Integrate-and-Fire
(QIF)
neurons.
Such
firing
rate
(FRM)
describe
the
emergence
fast
collective
oscillations
(>30~Hz)
via
frequency-locking
a
subset
neurons
to
global
oscillation
frequency.
However,
suitability
such
realistic
states
is
seriously
challenged
by
fact
that
during
episodes
oscillations,
discharges
are
often
very
irregular
and
low
rates
compared
Here
we
extend
theory
derive
exact
FRM
QIF
include
noise,
show
stochastic
displaying
at
governed
same
evolution
equations
as
deterministic
networks.
Our
results
reconcile
two
traditionally
confronted
views
on
synchronization,
upgrade
applicability
broad
range
biologically
states.
Entropy,
Journal Year:
2024,
Volume and Issue:
26(11), P. 953 - 953
Published: Nov. 6, 2024
Major
Depressive
Disorder
(MDD)
is
a
complex,
heterogeneous
condition
affecting
millions
worldwide.
Computational
neuropsychiatry
offers
potential
breakthroughs
through
the
mechanistic
modeling
of
this
disorder.
Using
Kolmogorov
theory
(KT)
consciousness,
we
developed
foundational
model
where
algorithmic
agents
interact
with
world
to
maximize
an
Objective
Function
evaluating
affective
valence.
Depression,
defined
in
context
by
state
persistently
low
valence,
may
arise
from
various
factors-including
inaccurate
models
(cognitive
biases),
dysfunctional
(anhedonia,
anxiety),
deficient
planning
(executive
deficits),
or
unfavorable
environments.
Integrating
algorithmic,
dynamical
systems,
and
neurobiological
concepts,
map
agent
brain
circuits
functional
networks,
framing
etiological
routes
linking
depression
biotypes.
Finally,
explore
how
stimulation,
psychotherapy,
plasticity-enhancing
compounds
such
as
psychedelics
can
synergistically
repair
neural
optimize
therapies
using
personalized
computational
models.