Merge pull request #3233 from aoot/master

Fixed conductance based neuron model header files

models/hh_cond_beta_gap_traub.h

@@ -94,7 +94,7 @@ Postsynaptic currents
 
 Incoming spike events induce a postsynaptic change of conductance modelled by a
 beta function as outlined in [4]_ [5]_. The beta function is normalized such that an
-event of weight 1.0 results in a peak current of 1 nS at :math:`t = \tau_{rise,xx}`
+event of weight 1.0 results in a peak conductance of 1 nS at :math:`t = \tau_{rise,xx}`
 where xx is `ex` or `in`.
 
 Spike Detection

models/iaf_cond_alpha.h

@@ -69,7 +69,7 @@ Description
 ``iaf_cond_alpha`` is an implementation of a spiking neuron using IAF dynamics with
 conductance-based synapses. Incoming spike events induce a postsynaptic change
 of conductance modelled by an alpha function. The alpha function
-is normalized such that an event of weight 1.0 results in a peak current of 1 nS
+is normalized such that an event of weight 1.0 results in a peak conductance of 1 nS
 at :math:`t = \tau_{syn}`.
 
 See also [1]_, [2]_, [3]_.

models/iaf_cond_exp_sfa_rr.h

@@ -74,7 +74,7 @@ spike-frequency adaptation and relative refractory mechanisms as described in
 
 Incoming spike events induce a postsynaptic change of conductance modelled by
 an exponential function. The exponential function is normalized such that an
-event of weight 1.0 results in a peak current of 1 nS.
+event of weight 1.0 results in a peak conductance of 1 nS.
 
 Outgoing spike events induce a change of the adaptation and relative refractory
 conductances by ``q_sfa`` and ``q_rr``, respectively. Otherwise these conductances