<s>
The	O
Galves	B-General_Concept
–	I-General_Concept
Löcherbach	I-General_Concept
model	I-General_Concept
(	O
or	O
GL	O
model	O
)	O
is	O
a	O
mathematical	O
model	O
for	O
a	O
network	B-General_Concept
of	I-General_Concept
neurons	I-General_Concept
with	O
intrinsic	O
stochasticity	O
.	O
</s>
<s>
In	O
specific	O
versions	O
of	O
the	O
GL	O
model	O
,	O
the	O
past	O
network	O
spike	O
history	O
since	O
the	O
last	O
firing	O
of	O
a	O
neuron	O
N	O
may	O
be	O
summarized	O
by	O
an	O
internal	O
variable	O
,	O
the	O
potential	O
of	O
that	O
neuron	O
,	O
that	O
is	O
a	O
weighted	B-Algorithm
sum	I-Algorithm
of	O
those	O
spikes	O
.	O
</s>
<s>
In	O
a	O
common	O
special	O
case	O
of	O
the	O
GL	O
model	O
,	O
the	O
part	O
of	O
the	O
past	O
firing	O
history	O
that	O
is	O
relevant	O
to	O
each	O
neuron	O
at	O
each	O
sampling	O
time	O
is	O
summarized	O
by	O
a	O
real-valued	O
internal	O
state	O
variable	O
or	O
potential	O
(	O
that	O
corresponds	O
to	O
the	O
membrane	O
potential	O
of	O
a	O
biological	O
neuron	O
)	O
,	O
and	O
is	O
basically	O
a	O
weighted	B-Algorithm
sum	I-Algorithm
of	O
the	O
past	O
spike	O
indicators	O
,	O
since	O
the	O
last	O
firing	O
of	O
neuron	O
.	O
</s>
<s>
In	O
this	O
formula	O
,	O
is	O
a	O
numeric	O
weight	B-Algorithm
,	O
that	O
corresponds	O
to	O
the	O
total	O
weight	B-Algorithm
or	O
strength	O
of	O
the	O
synapses	O
from	O
the	O
axon	B-Algorithm
of	O
neuron	O
to	O
the	O
dentrites	O
of	O
neuron	O
.	O
</s>
<s>
The	O
factor	O
is	O
a	O
history	O
weight	B-Algorithm
function	I-Algorithm
that	O
modulates	O
the	O
contributions	O
of	O
firings	O
that	O
happened	O
whole	O
steps	O
after	O
the	O
last	O
firing	O
of	O
neuron	O
and	O
whole	O
steps	O
before	O
the	O
current	O
time	O
.	O
</s>
<s>
If	O
the	O
synaptic	B-Algorithm
weight	I-Algorithm
is	O
negative	O
,	O
each	O
firing	O
of	O
neuron	O
causes	O
the	O
potential	O
to	O
decrease	O
.	O
</s>
<s>
In	O
an	O
even	O
more	O
specific	O
case	O
of	O
the	O
GL	O
model	O
,	O
the	O
potential	O
is	O
defined	O
to	O
be	O
a	O
decaying	O
weighted	B-Algorithm
sum	I-Algorithm
of	O
the	O
firings	O
of	O
other	O
neurons	O
.	O
</s>
<s>
This	O
special	O
case	O
results	O
from	O
taking	O
the	O
history	O
weight	B-Algorithm
factor	O
of	O
the	O
general	O
potential-based	O
variant	O
to	O
be	O
.	O
</s>
<s>
This	O
self-weight	O
therefore	O
represents	O
the	O
reset	O
potential	O
that	O
the	O
neuron	O
assumes	O
just	O
after	O
firing	O
,	O
apart	O
from	O
other	O
contributions	O
.	O
</s>
<s>
In	O
other	O
words	O
,	O
the	O
state	O
of	O
a	O
network	O
with	O
neurons	O
is	O
a	O
list	O
of	O
bits	O
,	O
namely	O
the	O
value	O
of	O
for	O
each	O
neuron	O
,	O
which	O
can	O
be	O
assumed	O
to	O
be	O
stored	O
in	O
its	O
axon	B-Algorithm
in	O
the	O
form	O
of	O
a	O
traveling	O
depolarization	O
zone	O
.	O
</s>
<s>
The	O
Galves	B-General_Concept
–	I-General_Concept
Löcherbach	I-General_Concept
model	I-General_Concept
distinguishes	O
itself	O
because	O
it	O
is	O
inherently	O
stochastic	O
,	O
incorporating	O
probabilistic	O
measures	O
directly	O
in	O
the	O
calculation	O
of	O
spikes	O
.	O
</s>
<s>
The	O
Galves	B-General_Concept
–	I-General_Concept
Löcherbach	I-General_Concept
model	I-General_Concept
was	O
a	O
cornerstone	O
to	O
the	O
NeuroMat	O
project	O
.	O
</s>
