bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2023,
Volume and Issue:
unknown
Published: Oct. 23, 2023
Abstract
Clinical
neuroscience
principally
aims
to
delineate
the
neurobiology
underpinning
symptoms
of
various
disorders,
with
ultimate
goal
developing
mechanistically
informed
treatments
for
these
conditions.
This
has
been
hindered
by
complex
hierarchical
organisation
brain
and
extreme
heterogeneity
neuropsychiatric
disorders.
However,
recent
advances
in
multimodal
analytic
techniques
–
such
as
Receptor
Enriched
Analysis
Connectivity
Targets
(REACT)
have
allowed
integrate
functional
dynamics
seen
fMRI
brain’s
receptor
landscape,
providing
novel
trans-hierarchical
insights.
Similarly,
normative
modelling
features
translational
move
beyond
group
average
differences
between
patients
controls
characterise
deviations
from
health
at
an
individual
level.
Here,
we
bring
methods
together
first
time
order
address
two
longstanding
barriers
clinical
neuroscience.
REACT
was
used
create
networks
enriched
main
modulatory
(noradrenaline,
dopamine,
serotonin,
acetylcholine),
inhibitory
(GABA),
excitatory
(glutamate)
neurotransmitter
systems
a
large
healthy
participants
[N=607].
Next,
generated
models
across
spectrum
ageing
demonstrated
that
capture
within
Schizophrenia,
Bipolar-disorder,
ADHD
[N=119].
Our
results
align
prior
accounts
excitatory-inhibitory
imbalance
schizophrenia
bipolar
disorder,
former
also
related
cholinergic
system.
transdiagnostic
analyses
emphasised
substantial
overlap
Altogether,
this
work
provides
impetus
development
biomarkers
both
molecular-
systems-level
dysfunction
level,
helping
facilitate
transition
towards
targeted
treatments.
Significance
statement
Human
beings
show
enormous
variability,
inter-individual
spanning
neurotransmitters
networks.
Understanding
how
mechanisms
interact
scales
produce
heterogenous
symptomatology
psychiatric
disorders
presents
challenge.
provide
framework
overcome
barriers,
combining
molecular-enriched
neuroimaging
examine
neuropathology
converge
on
neurobiological
disorder
well
ADHD.
Moreover,
map
transdiagnostically
By
bridging
gap
dysfunctional
underlying
systems,
can
one-size-fits-all
approaches
personalized
pharmacological
interventions
Journal of Clinical Medicine,
Journal Year:
2025,
Volume and Issue:
14(2), P. 550 - 550
Published: Jan. 16, 2025
The
convergence
of
Artificial
Intelligence
(AI)
and
neuroscience
is
redefining
our
understanding
the
brain,
unlocking
new
possibilities
in
research,
diagnosis,
therapy.
This
review
explores
how
AI’s
cutting-edge
algorithms—ranging
from
deep
learning
to
neuromorphic
computing—are
revolutionizing
by
enabling
analysis
complex
neural
datasets,
neuroimaging
electrophysiology
genomic
profiling.
These
advancements
are
transforming
early
detection
neurological
disorders,
enhancing
brain–computer
interfaces,
driving
personalized
medicine,
paving
way
for
more
precise
adaptive
treatments.
Beyond
applications,
itself
has
inspired
AI
innovations,
with
architectures
brain-like
processes
shaping
advances
algorithms
explainable
models.
bidirectional
exchange
fueled
breakthroughs
such
as
dynamic
connectivity
mapping,
real-time
decoding,
closed-loop
systems
that
adaptively
respond
states.
However,
challenges
persist,
including
issues
data
integration,
ethical
considerations,
“black-box”
nature
many
systems,
underscoring
need
transparent,
equitable,
interdisciplinary
approaches.
By
synthesizing
latest
identifying
future
opportunities,
this
charts
a
path
forward
integration
neuroscience.
From
harnessing
multimodal
cognitive
augmentation,
fusion
these
fields
not
just
brain
science,
it
reimagining
human
potential.
partnership
promises
where
mysteries
unlocked,
offering
unprecedented
healthcare,
technology,
beyond.
PLoS Biology,
Journal Year:
2023,
Volume and Issue:
21(9), P. e3002314 - e3002314
Published: Sept. 25, 2023
The
brain
is
composed
of
disparate
neural
populations
that
communicate
and
interact
with
one
another.
Although
fiber
bundles,
similarities
in
molecular
architecture,
synchronized
activity
all
reflect
how
regions
potentially
another,
a
comprehensive
study
these
interregional
relationships
jointly
structure
function
remains
missing.
Here,
we
systematically
integrate
7
multimodal,
multiscale
types
similarity
("connectivity
modes")
derived
from
gene
expression,
neurotransmitter
receptor
density,
cellular
morphology,
glucose
metabolism,
haemodynamic
activity,
electrophysiology
humans.
We
first
show
for
connectivity
modes,
feature
decreases
distance
increases
when
are
structurally
connected.
Next,
modes
exhibit
unique
diverse
connection
patterns,
hub
profiles,
spatial
gradients,
modular
organization.
Throughout,
observe
consistent
primacy
modes-namely
correlated
expression
similarity-that
map
onto
multiple
phenomena,
including
the
rich
club
patterns
abnormal
cortical
thickness
across
13
neurological,
psychiatric,
neurodevelopmental
disorders.
Finally,
to
construct
single
multimodal
wiring
human
cortex,
fuse
fused
network
maps
major
organizational
features
cortex
structural
connectivity,
intrinsic
functional
networks,
cytoarchitectonic
classes.
Altogether,
this
work
contributes
integrative
cerebral
cortex.
Human Brain Mapping,
Journal Year:
2024,
Volume and Issue:
45(2)
Published: Jan. 30, 2024
Abstract
Functional
signals
emerge
from
the
structural
network,
supporting
multiple
cognitive
processes
through
underlying
molecular
mechanism.
The
link
between
human
brain
structure
and
function
is
region‐specific
hierarchical
across
neocortex.
However,
relationship
structure–function
decoupling
manifestation
of
individual
behavior
cognition,
along
with
significance
functional
systems
involved,
specific
mechanism
remain
incompletely
characterized.
Here,
we
used
structural‐decoupling
index
(SDI)
to
quantify
dependency
on
connectome
using
a
significantly
larger
cohort
healthy
subjects.
Canonical
correlation
analysis
(CCA)
was
utilized
assess
general
multivariate
pattern
SDIs
whole
traits.
Then,
predicted
five
composite
scores
resulting
in
primary
networks,
association
all
respectively.
Finally,
explored
related
SDI
by
investigating
its
genetic
factors
neurotransmitter
receptors/transporters.
We
demonstrated
that
neocortex,
spanning
networks
networks.
revealed
better
performance
cognition
prediction
achieved
high‐level
SDIs,
varying
different
regions
predicting
processes.
found
were
associated
gene
expression
level
several
receptor‐related
terms,
also
spatial
distributions
four
receptors/transporters
correlated
namely
D2,
NET,
MOR,
mGluR5,
which
play
an
important
role
flexibility
neuronal
function.
Collectively,
our
findings
corroborate
macroscale
provide
implications
for
comprehending
decoupling.
Practitioner
Points
Structure–function
High‐level
contributes
much
more
than
low‐level
cognition.
could
be
regulated
genes
pivotal
receptors
are
crucial
flexibility.
Communications Biology,
Journal Year:
2024,
Volume and Issue:
7(1)
Published: June 5, 2024
Abstract
Advanced
methods
such
as
REACT
have
allowed
the
integration
of
fMRI
with
brain’s
receptor
landscape,
providing
novel
insights
transcending
multiscale
organisation
brain.
Similarly,
normative
modelling
has
translational
neuroscience
to
move
beyond
group-average
differences
and
characterise
deviations
from
health
at
an
individual
level.
Here,
we
bring
these
together
for
first
time.
We
used
create
functional
networks
enriched
main
modulatory,
inhibitory,
excitatory
neurotransmitter
systems
generated
models
capture
connectivity
in
patients
schizophrenia,
bipolar
disorder
(BPD),
ADHD.
Substantial
overlap
was
seen
symptomatology
normality
across
groups,
but
could
be
mapped
into
a
common
space
linking
constellations
symptoms
through
underlying
neurobiology
transdiagnostically.
This
work
provides
impetus
developing
biomarkers
that
molecular-
systems-level
dysfunction
level,
facilitating
transition
towards
mechanistically
targeted
treatments.
PLoS Computational Biology,
Journal Year:
2025,
Volume and Issue:
21(1), P. e1012683 - e1012683
Published: Jan. 13, 2025
Astrocytes
critically
shape
whole-brain
structure
and
function
by
forming
extensive
gap
junctional
networks
that
intimately
actively
interact
with
neurons.
Despite
their
importance,
existing
computational
models
of
activity
ignore
the
roles
astrocytes
while
primarily
focusing
on
Addressing
this
oversight,
we
introduce
a
biophysical
neural
mass
network
model,
designed
to
capture
dynamic
interplay
between
neurons
via
glutamatergic
GABAergic
transmission
pathways.
This
model
proposes
dynamics
are
constrained
two-layered
structural
interconnecting
both
astrocytic
neuronal
populations,
allowing
us
investigate
astrocytes’
modulatory
influences
emerging
functional
connectivity
patterns.
By
developing
simulation
methodology,
informed
bifurcation
multilayer
theories,
demonstrate
dialogue
manifests
over
fast–slow
fluctuation
mechanisms
as
well
through
phase–amplitude
processes.
The
findings
from
our
research
represent
significant
leap
forward
in
modeling
glial-neuronal
collaboration,
promising
deeper
insights
into
collaborative
across
health
disease
states.
