Correct a few typos in documentation comments

models/hh_psc_alpha.h

@@ -65,7 +65,7 @@ Name: hh_psc_alpha - Hodgkin Huxley neuron model.
  hh_psc_alpha is an implementation of a spiking neuron using the Hodkin-Huxley
  formalism.
 
- (1) Post-syaptic currents
+ (1) Post-synaptic currents
  Incoming spike events induce a post-synaptic change of current modelled
  by an alpha function. The alpha function is normalised such that an event of
  weight 1.0 results in a peak current of 1 pA.

models/hh_psc_alpha_gap.h

@@ -69,7 +69,7 @@ Name: hh_psc_alpha_gap - Hodgkin Huxley neuron model with gap-junction support.
  additionally supports gap junctions.
 
 
- (1) Post-syaptic currents
+ (1) Post-synaptic currents
  Incoming spike events induce a post-synaptic change of current modelled
  by an alpha function. The alpha function is normalised such that an event of
  weight 1.0 results in a peak current of 1 pA.

models/iaf_psc_alpha.h

@@ -102,7 +102,7 @@ Name: iaf_psc_alpha - Leaky integrate-and-fire neuron model.
   If tau_m is very close to tau_syn_ex or tau_syn_in, the model
   will numerically behave as if tau_m is equal to tau_syn_ex or
   tau_syn_in, respectively, to avoid numerical instabilities.
-  For details, please see IAF_Neruons_Singularity.ipynb in
+  For details, please see IAF_Neurons_Singularity.ipynb in
   the NEST source code (docs/model_details).
 
 References:

models/iaf_psc_exp.h

@@ -93,7 +93,7 @@ namespace nest
    If tau_m is very close to tau_syn_ex or tau_syn_in, the model
    will numerically behave as if tau_m is equal to tau_syn_ex or
    tau_syn_in, respectively, to avoid numerical instabilities.
-   For details, please see IAF_Neruons_Singularity.ipynb in the
+   For details, please see IAF_Neurons_Singularity.ipynb in the
    NEST source code (docs/model_details).
 
    iaf_psc_exp can handle current input in two ways: Current input

models/iaf_tum_2000.h

@@ -104,7 +104,7 @@ namespace nest
    If tau_m is very close to tau_syn_ex or tau_syn_in, the model
    will numerically behave as if tau_m is equal to tau_syn_ex or
    tau_syn_in, respectively, to avoid numerical instabilities.
-   For details, please see IAF_Neruons_Singularity.ipynb in
+   For details, please see IAF_Neurons_Singularity.ipynb in
    the NEST source code (docs/model_details).
 
    References:

nestkernel/nestmodule.cpp

@@ -726,7 +726,7 @@ NestModule::ResetKernelFunction::execute( SLIInterpreter* i ) const
    at T=0. The dynamic state comprises typically the membrane potential,
    synaptic currents, buffers holding input that has been delivered, but not
    yet become effective, and all events pending delivery. Technically, this
-   is achieve by calling init_state() on all nodes and forcing a call to
+   is achieved by calling init_state() on all nodes and forcing a call to
    init_buffers() upon the next call to Simulate. Node parameters, such as
    time constants and threshold potentials, are not affected.