<s>
Bursting	B-Algorithm
,	O
or	O
burst	B-Algorithm
firing	I-Algorithm
,	O
is	O
an	O
extremely	O
diverse	O
general	O
phenomenon	O
of	O
the	O
activation	O
patterns	O
of	O
neurons	O
in	O
the	O
central	O
nervous	O
system	O
and	O
spinal	O
cord	O
where	O
periods	O
of	O
rapid	O
action	B-Algorithm
potential	I-Algorithm
spiking	O
are	O
followed	O
by	O
quiescent	O
periods	O
much	O
longer	O
than	O
typical	O
inter-spike	O
intervals	O
.	O
</s>
<s>
Bursting	B-Algorithm
is	O
thought	O
to	O
be	O
important	O
in	O
the	O
operation	O
of	O
robust	O
central	O
pattern	O
generators	O
,	O
the	O
transmission	O
of	O
neural	O
codes	O
,	O
and	O
some	O
neuropathologies	O
such	O
as	O
epilepsy	O
.	O
</s>
<s>
The	O
study	O
of	O
bursting	B-Algorithm
both	O
directly	O
and	O
in	O
how	O
it	O
takes	O
part	O
in	O
other	O
neural	O
phenomena	O
has	O
been	O
very	O
popular	O
since	O
the	O
beginnings	O
of	O
cellular	O
neuroscience	O
and	O
is	O
closely	O
tied	O
to	O
the	O
fields	O
of	O
neural	B-Algorithm
synchronization	I-Algorithm
,	O
neural	O
coding	O
,	O
plasticity	O
,	O
and	O
attention	O
.	O
</s>
<s>
Observed	O
bursts	O
are	O
named	O
by	O
the	O
number	O
of	O
discrete	O
action	B-Algorithm
potentials	I-Algorithm
they	O
are	O
composed	O
of	O
:	O
a	O
doublet	O
is	O
a	O
two-spike	O
burst	O
,	O
a	O
triplet	O
three	O
and	O
a	O
quadruplet	O
four	O
.	O
</s>
<s>
Neurons	O
that	O
are	O
intrinsically	O
prone	O
to	O
bursting	B-Algorithm
behavior	O
are	O
referred	O
to	O
as	O
bursters	O
and	O
this	O
tendency	O
to	O
burst	O
may	O
be	O
a	O
product	O
of	O
the	O
environment	O
or	O
the	O
phenotype	O
of	O
the	O
cell	O
.	O
</s>
<s>
Neurons	O
typically	O
operate	O
by	O
firing	O
single	O
action	B-Algorithm
potential	I-Algorithm
spikes	B-Algorithm
in	O
relative	O
isolation	O
as	O
discrete	O
input	O
postsynaptic	B-Algorithm
potentials	I-Algorithm
combine	O
and	O
drive	O
the	O
membrane	O
potential	O
across	O
the	O
threshold	B-Algorithm
.	O
</s>
<s>
Bursting	B-Algorithm
can	O
instead	O
occur	O
for	O
many	O
reasons	O
,	O
but	O
neurons	O
can	O
be	O
generally	O
grouped	O
as	O
exhibiting	O
input-driven	O
or	O
intrinsic	O
bursting	B-Algorithm
.	O
</s>
<s>
Most	O
cells	O
will	O
exhibit	O
bursting	B-Algorithm
if	O
they	O
are	O
driven	O
by	O
a	O
constant	O
,	O
subthreshold	O
input	O
and	O
particular	O
cells	O
which	O
are	O
genotypically	O
prone	O
to	O
bursting	B-Algorithm
(	O
called	O
bursters	O
)	O
have	O
complex	O
feedback	O
systems	O
which	O
will	O
produce	O
bursting	B-Algorithm
patterns	O
with	O
less	O
dependence	O
on	O
input	O
and	O
sometimes	O
even	O
in	O
isolation	O
.	O
</s>
<s>
The	O
fast	O
subsystem	O
is	O
responsible	O
for	O
each	O
spike	B-Algorithm
the	O
neuron	O
produces	O
.	O
</s>
<s>
The	O
slow	O
subsystem	O
modulates	O
the	O
shape	O
and	O
intensity	O
of	O
these	O
spikes	B-Algorithm
before	O
eventually	O
triggering	O
quiescence	O
.	O
</s>
<s>
Input-driven	O
bursting	B-Algorithm
often	O
encodes	O
the	O
intensity	O
of	O
input	O
into	O
the	O
bursting	B-Algorithm
frequency	O
where	O
a	O
neuron	O
then	O
acts	O
as	O
an	O
integrator	O
.	O
</s>
<s>
Intrinsic	O
bursting	B-Algorithm
is	O
a	O
more	O
specialized	O
phenomenon	O
and	O
is	O
believed	O
to	O
play	O
a	O
much	O
more	O
diverse	O
role	O
in	O
neural	O
computation	O
.	O
</s>
<s>
Bursts	O
differ	O
from	O
tonic	O
firing	O
,	O
typically	O
associated	O
with	O
Poisson	O
distributed	O
spike	B-Algorithm
times	O
for	O
a	O
given	O
average	O
firing	O
rate	O
,	O
in	O
that	O
bursting	B-Algorithm
involves	O
a	O
physiological	O
"	O
slow	O
subsystem	O
"	O
that	O
eventually	O
depletes	O
as	O
the	O
bursting	B-Algorithm
continues	O
and	O
then	O
must	O
be	O
replenished	O
before	O
the	O
cell	O
can	O
burst	O
again	O
(	O
compare	O
refractory	O
period	O
)	O
.	O
</s>
<s>
During	O
the	O
bursting	B-Algorithm
event	O
,	O
this	O
slow	O
subsystem	O
modulates	O
the	O
timing	O
and	O
intensity	O
of	O
the	O
emitted	O
spikes	B-Algorithm
and	O
is	O
thought	O
to	O
be	O
important	O
in	O
the	O
computational	O
aspects	O
of	O
the	O
resulting	O
burst	O
pattern	O
.	O
</s>
<s>
The	O
slow	O
subsystem	O
also	O
is	O
connected	O
to	O
endogenous	O
bursting	B-Algorithm
patterns	O
in	O
neurons	O
,	O
where	O
the	O
pattern	O
can	O
be	O
maintained	O
completely	O
by	O
internal	O
mechanism	O
without	O
any	O
synaptic	B-Application
input	O
.	O
</s>
<s>
As	O
calcium	O
concentrations	O
decline	O
,	O
the	O
period	O
of	O
rapid	O
bursting	B-Algorithm
ceases	O
,	O
and	O
the	O
phase	O
of	O
quiescence	O
begins	O
.	O
</s>
<s>
When	O
calcium	O
levels	O
are	O
low	O
,	O
the	O
original	O
calcium	O
channels	O
will	O
reopen	O
,	O
restarting	O
the	O
process	O
and	O
creating	O
a	O
bursting	B-Algorithm
pattern	O
.	O
</s>
<s>
In	O
isolation	O
or	O
in	O
mathematical	O
models	O
bursting	B-Algorithm
can	O
be	O
recognized	O
since	O
the	O
environment	O
and	O
state	O
of	O
the	O
neuron	O
can	O
be	O
carefully	O
observed	O
and	O
modulated	O
.	O
</s>
<s>
When	O
observing	O
neurons	O
in	O
the	O
wild	O
,	O
however	O
,	O
bursting	B-Algorithm
may	O
be	O
difficult	O
to	O
distinguish	O
from	O
normal	O
firing	O
patterns	O
.	O
</s>
<s>
In	O
order	O
to	O
recognize	O
bursting	B-Algorithm
patterns	O
in	O
these	O
contexts	O
statistical	O
methods	O
are	O
used	O
to	O
determine	O
threshold	B-Algorithm
parameters	O
.	O
</s>
<s>
Bursting	B-Algorithm
is	O
characterized	O
by	O
a	O
coefficient	O
of	O
variation	O
(	O
CV	O
)	O
of	O
the	O
interspike	O
intervals	O
(	O
ISI	O
)	O
that	O
is	O
larger	O
than	O
one	O
,	O
or	O
a	O
Fano	B-General_Concept
factor	I-General_Concept
of	O
the	O
spike	B-Algorithm
count	O
that	O
is	O
larger	O
than	O
one	O
,	O
because	O
bursting	B-Algorithm
leads	O
to	O
spike	B-Algorithm
patterns	O
that	O
are	O
more	O
irregular	O
than	O
a	O
Poisson	O
process	O
(	O
which	O
has	O
a	O
CV	O
and	O
Fano	B-General_Concept
factor	I-General_Concept
equal	O
to	O
unity	O
)	O
.	O
</s>
<s>
Alternatively	O
,	O
the	O
serial	O
correlation	O
coefficient	O
of	O
the	O
ISI	O
sequence	O
is	O
positive	O
for	O
bursting	B-Algorithm
patterns	O
,	O
because	O
in	O
this	O
case	O
short	O
ISIs	O
tend	O
to	O
be	O
followed	O
by	O
more	O
short	O
ISIs	O
(	O
at	O
least	O
if	O
the	O
bursts	O
consist	O
of	O
more	O
than	O
two	O
spikes	B-Algorithm
)	O
.	O
</s>
<s>
When	O
the	O
system	O
is	O
sufficiently	O
perturbed	O
by	O
input	O
stimuli	O
it	O
may	O
follow	O
a	O
complex	O
return	O
path	O
back	O
to	O
the	O
stable	O
attractor	O
representing	O
an	O
action	B-Algorithm
potential	I-Algorithm
.	O
</s>
<s>
In	O
bursting	B-Algorithm
neurons	O
,	O
these	O
dynamic	O
spaces	O
bifurcate	O
between	O
quiescent	O
and	O
bursting	B-Algorithm
modes	O
according	O
to	O
the	O
dynamics	O
of	O
the	O
slow	O
system	O
.	O
</s>
<s>
These	O
two	O
bifurcations	O
may	O
take	O
many	O
forms	O
and	O
the	O
choice	O
of	O
bifurcation	O
both	O
from	O
quiescent	O
to	O
bursting	B-Algorithm
and	O
bursting	B-Algorithm
to	O
quiescent	O
can	O
affect	O
the	O
behavioral	O
aspects	O
of	O
the	O
burster	O
.	O
</s>
<s>
The	O
complete	O
classification	O
of	O
quiescent-to-bursting	O
and	O
bursting-to-quiescent	O
bifurcations	O
leads	O
to	O
16	O
common	O
forms	O
and	O
120	O
possible	O
forms	O
if	O
the	O
dimensionality	O
of	O
the	O
fast	O
subsystem	O
is	O
not	O
constrained	O
.	O
</s>
<s>
Bursting	B-Algorithm
is	O
a	O
very	O
general	O
phenomenon	O
and	O
is	O
observed	O
in	O
many	O
contexts	O
in	O
many	O
neural	O
systems	O
.	O
</s>
<s>
For	O
this	O
reason	O
it	O
is	O
difficult	O
to	O
find	O
a	O
specific	O
meaning	O
or	O
purpose	O
for	O
bursting	B-Algorithm
and	O
instead	O
it	O
plays	O
many	O
roles	O
.	O
</s>
<s>
Synaptic	B-Application
strengths	O
between	O
neurons	O
follow	O
changes	O
that	O
depend	O
on	O
spike	B-Algorithm
timing	O
and	O
bursting	B-Algorithm
.	O
</s>
<s>
For	O
excitatory	O
synapses	B-Application
of	O
the	O
cortex	O
,	O
pairing	O
an	O
action	B-Algorithm
potential	I-Algorithm
in	O
the	O
pre-synaptic	O
neuron	O
with	O
a	O
burst	O
in	O
the	O
post-synaptic	O
neuron	O
leads	O
to	O
long-term	O
potentiation	O
of	O
the	O
synaptic	B-Application
strength	O
,	O
while	O
pairing	O
an	O
action	B-Algorithm
potential	I-Algorithm
in	O
the	O
pre-synaptic	O
neuron	O
with	O
a	O
single	O
spike	B-Algorithm
in	O
the	O
post-synaptic	O
neuron	O
leads	O
to	O
long-term	O
depression	O
of	O
the	O
synaptic	B-Application
strength	O
.	O
</s>
<s>
Such	O
dependence	O
of	O
synaptic	B-Application
plasticity	O
on	O
the	O
spike	B-Algorithm
timing	O
patterns	O
is	O
referred	O
to	O
as	O
burst-dependent	O
plasticity	O
.	O
</s>
<s>
Intrinsically	O
bursting	B-Algorithm
neurons	O
can	O
use	O
this	O
band-pass	O
filtering	O
effect	O
in	O
order	O
to	O
encode	O
for	O
specific	O
destination	O
neurons	O
and	O
multiplex	B-Architecture
signals	O
along	O
a	O
single	O
axon	B-Algorithm
.	O
</s>
<s>
More	O
generally	O
,	O
due	O
to	O
short-term	O
synaptic	B-Application
depression	O
and	O
facilitation	O
specific	O
synapses	B-Application
can	O
be	O
resonant	O
for	O
certain	O
frequencies	O
and	O
thus	O
become	O
viable	O
specific	O
targets	O
for	O
bursting	B-Algorithm
cells	O
.	O
</s>
<s>
When	O
combined	O
with	O
burst-dependent	O
long-term	O
plasticity	O
,	O
such	O
multiplexing	B-Architecture
can	O
allow	O
neurons	O
to	O
coordinate	O
synaptic	B-Application
plasticity	O
across	O
hierarchical	O
networks	O
.	O
</s>
<s>
Burst	O
synchronization	O
refers	O
to	O
the	O
alignment	O
of	O
bursting	B-Algorithm
and	O
quiescent	O
periods	O
in	O
interconnected	O
neurons	O
.	O
</s>
<s>
In	O
general	O
,	O
if	O
a	O
network	O
of	O
bursting	B-Algorithm
neurons	O
is	O
linked	O
it	O
will	O
eventually	O
synchronize	O
for	O
most	O
types	O
of	O
bursting	B-Algorithm
.	O
</s>
<s>
Synchronization	O
can	O
also	O
appear	O
in	O
circuits	O
containing	O
no	O
intrinsically	O
bursting	B-Algorithm
neurons	O
,	O
however	O
its	O
appearance	O
and	O
stability	O
can	O
often	O
be	O
improved	O
by	O
including	O
intrinsically	O
bursting	B-Algorithm
cells	O
in	O
the	O
network	O
.	O
</s>
<s>
Since	O
synchronization	O
is	O
related	O
to	O
plasticity	O
and	O
memory	O
via	O
Hebbian	O
plasticity	O
and	O
long-term	O
potentiation	O
the	O
interplay	O
with	O
plasticity	O
and	O
intrinsic	O
bursting	B-Algorithm
is	O
very	O
important	O
.	O
</s>
<s>
Due	O
to	O
the	O
all-or-nothing	O
nature	O
of	O
action	B-Algorithm
potentials	I-Algorithm
,	O
single	O
spikes	B-Algorithm
can	O
only	O
encode	O
information	O
in	O
their	O
interspike	O
intervals	O
(	O
ISI	O
)	O
.	O
</s>
<s>
This	O
is	O
an	O
inherently	O
low	O
fidelity	O
method	O
of	O
transferring	O
information	O
as	O
it	O
depends	O
on	O
very	O
accurate	O
timing	O
and	O
is	O
sensitive	O
to	O
noisy	O
loss	O
of	O
signal	O
:	O
if	O
just	O
a	O
single	O
spike	B-Algorithm
is	O
mistimed	O
or	O
not	O
properly	O
received	O
at	O
the	O
synapse	B-Application
it	O
leads	O
to	O
a	O
possibly	O
unrecoverable	O
loss	O
in	O
coding	O
.	O
</s>
<s>
In	O
order	O
to	O
perform	O
this	O
function	O
,	O
it	O
uses	O
intrinsically	O
bursting	B-Algorithm
neurons	O
to	O
convert	O
promising	O
single	O
stimuli	O
into	O
longer	O
lasting	O
burst	O
patterns	O
as	O
a	O
way	O
to	O
better	O
focus	O
attention	O
on	O
new	O
stimuli	O
and	O
activate	O
important	O
processing	O
circuits	O
.	O
</s>
<s>
While	O
pacemaker	O
neurons	O
do	O
not	O
necessarily	O
require	O
intrinsically	O
bursting	B-Algorithm
neurons	O
the	O
preBötC	O
contains	O
a	O
heterogeneous	O
population	O
of	O
both	O
regular	O
spiking	O
and	O
intrinsically	O
bursting	B-Algorithm
neurons	O
.	O
</s>
<s>
Intrinsically	O
bursting	B-Algorithm
neurons	O
are	O
thought	O
to	O
make	O
the	O
preBötC	O
oscillations	O
more	O
robust	O
to	O
changing	O
frequencies	O
and	O
the	O
regularity	O
of	O
inspiratory	O
efforts	O
.	O
</s>
<s>
Cerebellar	O
Purkinje	O
neurons	O
have	O
been	O
proposed	O
to	O
have	O
two	O
distinct	O
bursting	B-Algorithm
modes	O
:	O
dendritically	O
driven	O
,	O
by	O
dendritic	O
spikes	B-Algorithm
,	O
and	O
somatically	O
driven	O
,	O
wherein	O
the	O
persistent	O
current	O
is	O
the	O
burst	O
initiator	O
and	O
the	O
SK	O
current	O
is	O
the	O
burst	O
terminator	O
.	O
</s>
<s>
Purkinje	O
neurons	O
may	O
utilise	O
these	O
bursting	B-Algorithm
forms	O
in	O
information	O
coding	O
to	O
the	O
deep	O
cerebellar	O
nuclei	O
.	O
</s>
