IEEE Transactions on Pattern Analysis and Machine Intelligence,
Год журнала:
2015,
Номер
37(10), С. 2028 - 2040
Опубликована: Янв. 15, 2015
This
paper
introduces
a
spiking
hierarchical
model
for
object
recognition
which
utilizes
the
precise
timing
information
inherently
present
in
output
of
biologically
inspired
asynchronous
Address
Event
Representation
(AER)
vision
sensors.
The
nature
these
systems
frees
computation
and
communication
from
rigid
predetermined
enforced
by
system
clocks
conventional
systems.
Freedom
constraints
opens
possibility
using
true
to
our
advantage
computation.
We
show
not
only
how
can
be
used
recognition,
but
also
it
fact
simplify
Specifically,
we
rely
on
simple
temporal-winner-take-all
rather
than
more
computationally
intensive
synchronous
operations
typically
neural
networks
recognition.
approach
visual
represents
major
paradigm
shift
clocked
find
application
other
sensory
modalities
computational
tasks.
showcase
effectiveness
achieving
highest
reported
accuracy
date
(97.5\%$\pm$3.5\%)
previously
published
four
class
card
pip
task
an
84.9\%$\pm$1.9\%
new
difficult
36
character
task.
Implanted
brain
electrodes
construct
the
only
means
to
electrically
interface
with
individual
neurons
in
vivo,
but
their
recording
efficacy
and
biocompatibility
pose
limitations
on
scientific
clinical
applications.
We
showed
that
nanoelectronic
thread
(NET)
subcellular
dimensions,
ultraflexibility,
cellular
surgical
footprints
form
reliable,
glial
scar-free
neural
integration.
demonstrated
NET
reliably
detected
tracked
units
for
months;
impedance,
noise
level,
single-unit
yield,
signal
amplitude
remained
stable
during
long-term
implantation.
In
vivo
two-photon
imaging
postmortem
histological
analysis
revealed
seamless,
integration
of
probes
local
vasculature
networks,
featuring
fully
recovered
capillaries
an
intact
blood-brain
barrier
complete
absence
chronic
neuronal
degradation
scar.
Abstract
Efforts
to
identify
meaningful
functional
imaging-based
biomarkers
are
limited
by
the
ability
reliably
characterize
inter-individual
differences
in
human
brain
function.
Although
a
growing
number
of
connectomics-based
measures
reported
have
moderate
high
test-retest
reliability,
variability
data
acquisition,
experimental
designs,
and
analytic
methods
precludes
generalize
results.
The
Consortium
for
Reliability
Reproducibility
(CoRR)
is
working
address
this
challenge
establish
reliability
as
minimum
standard
development
connectomics.
Specifically,
CoRR
has
aggregated
1,629
typical
individuals’
resting
state
fMRI
(rfMRI)
(5,093
rfMRI
scans)
from
18
international
sites,
openly
sharing
them
via
International
Data-sharing
Neuroimaging
Initiative
(INDI).
To
allow
researchers
generate
various
estimates
reproducibility,
variety
acquisition
procedures
designs
included.
Similarly,
enable
users
assess
impact
commonly
encountered
artifacts
(for
example,
motion)
on
characterizations
variation,
datasets
varying
quality
ACS Nano,
Год журнала:
2013,
Номер
7(3), С. 1850 - 1866
Опубликована: Март 20, 2013
Neuroscience
is
at
a
crossroads.
Great
effort
being
invested
into
deciphering
specific
neural
interactions
and
circuits.
At
the
same
time,
there
exist
few
general
theories
or
principles
that
explain
brain
function.
We
attribute
this
disparity,
in
part,
to
limitations
current
methodologies.
Traditional
neurophysiological
approaches
record
activities
of
one
neuron
neurons
time.
Neurochemical
focus
on
single
neurotransmitters.
Yet,
an
increasing
realization
circuits
operate
emergent
levels,
where
between
hundreds
thousands
neurons,
utilizing
multiple
chemical
transmitters,
generate
functional
states.
Brains
function
nanoscale,
so
tools
study
brains
must
ultimately
scale,
as
well.
Nanoscience
nanotechnology
are
poised
provide
rich
toolkit
novel
methods
explore
by
enabling
simultaneous
measurement
manipulation
activity
even
millions
neurons.
others
refer
goal
Brain
Activity
Mapping
Project.
In
Nano
Focus,
we
discuss
how
recent
developments
nanoscale
analysis
design
synthesis
nanomaterials
have
generated
optical,
electrical,
can
readily
be
adapted
for
use
neuroscience.
These
represent
exciting
areas
technical
development
research.
Moreover,
unique
opportunities
nanoscientists,
nanotechnologists,
other
physical
scientists
engineers
contribute
tackling
challenging
problems
involved
understanding
fundamentals
Philosophical Transactions of the Royal Society B Biological Sciences,
Год журнала:
2014,
Номер
369(1653), С. 20130521 - 20130521
Опубликована: Сен. 2, 2014
The
brain
can
be
regarded
as
a
network:
connected
system
where
nodes,
or
units,
represent
different
specialized
regions
and
links,
connections,
communication
pathways.
From
functional
perspective
is
coded
by
temporal
dependence
between
the
activities
of
areas.
In
last
decade,
abstract
representation
graph
has
allowed
to
visualize
networks
describe
their
non-trivial
topological
properties
in
compact
objective
way.
Nowadays,
use
analysis
translational
neuroscience
become
essential
quantify
dysfunctions
terms
aberrant
reconfiguration
networks.
Despite
its
evident
impact,
not
simple
toolbox
that
blindly
applied
signals.
On
one
hand,
it
requires
know-how
all
methodological
steps
processing
pipeline
manipulates
input
signals
extract
network
properties.
other
knowledge
neural
phenomenon
under
study
required
perform
physiological-relevant
analysis.
aim
this
review
provide
practical
indications
make
sense
contrast
counterproductive
attitudes.
Journal of Neurophysiology,
Год журнала:
2013,
Номер
111(5), С. 1132 - 1149
Опубликована: Дек. 19, 2013
Monitoring
representative
fractions
of
neurons
from
multiple
brain
circuits
in
behaving
animals
is
necessary
for
understanding
neuronal
computation.
Here,
we
describe
a
system
that
allows
high-channel-count
recordings
small
volume
tissue
using
lightweight
signal
multiplexing
headstage
permits
free
behavior
rodents.
The
integrates
multishank,
high-density
recording
silicon
probes,
ultraflexible
interconnects,
and
miniaturized
microdrive.
These
improvements
allowed
simultaneous
local
field
potentials
unit
activity
hundreds
sites
without
confining
movements
the
animal.
advantages
large-scale
are
illustrated
by
determining
electroanatomic
boundaries
layers
regions
hippocampus
neocortex
constructing
circuit
diagram
functional
connections
among
real
anatomic
space.
methods
will
allow
investigation
operations
behavior-dependent
interregional
interactions
testing
hypotheses
neural
networks
function.