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_chs_2007.h

@@ -45,7 +45,7 @@ namespace nest
    potentials (V_syn), waveforms that include a spike and the subsequent
    after-hyperpolarization (V_spike) and Gaussian-distributed white noise.
 
-   The postsynaptic potential is described by alpha function where where
+   The postsynaptic potential is described by alpha function where
    U_epsp is the maximal amplitude of the EPSP and tau_epsp is the time to
    peak of the EPSP.
 

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_delta.cpp

@@ -250,20 +250,20 @@ nest::iaf_psc_delta::calibrate()
   V_.P30_ = 1 / P_.c_m_ * ( 1 - V_.P33_ ) * P_.tau_m_;
 
 
-  // TauR specifies the length of the absolute refractory period as
+  // t_ref_ specifies the length of the absolute refractory period as
   // a double in ms. The grid based iaf_psp_delta can only handle refractory
   // periods that are integer multiples of the computation step size (h).
   // To ensure consistency with the overall simulation scheme such conversion
   // should be carried out via objects of class nest::Time. The conversion
   // requires 2 steps:
-  //     1. A time object r is constructed defining  representation of
-  //        TauR in tics. This representation is then converted to computation
+  //     1. A time object r is constructed, defining representation of
+  //        t_ref_ in tics. This representation is then converted to computation
   //        time steps again by a strategy defined by class nest::Time.
   //     2. The refractory time in units of steps is read out get_steps(), a
   //        member function of class nest::Time.
   //
-  // Choosing a TauR that is not an integer multiple of the computation time
-  // step h will leed to accurate (up to the resolution h) and self-consistent
+  // Choosing a t_ref_ that is not an integer multiple of the computation time
+  // step h will lead to accurate (up to the resolution h) and self-consistent
   // results. However, a neuron model capable of operating with real valued
   // spike time may exhibit a different effective refractory time.
 

models/iaf_psc_exp.cpp

@@ -269,20 +269,20 @@ nest::iaf_psc_exp::calibrate()
   V_.P20_ = P_.Tau_ / P_.C_ * ( 1.0 - V_.P22_ );
   // P20_ = h/C_;
 
-  // TauR specifies the length of the absolute refractory period as
+  // t_ref_ specifies the length of the absolute refractory period as
   // a double in ms. The grid based iaf_psc_exp can only handle refractory
   // periods that are integer multiples of the computation step size (h).
   // To ensure consistency with the overall simulation scheme such conversion
   // should be carried out via objects of class nest::Time. The conversion
   // requires 2 steps:
-  //     1. A time object r is constructed defining  representation of
-  //        TauR in tics. This representation is then converted to computation
+  //     1. A time object r is constructed, defining representation of
+  //        t_ref_ in tics. This representation is then converted to computation
   //        time steps again by a strategy defined by class nest::Time.
   //     2. The refractory time in units of steps is read out get_steps(), a
   //        member function of class nest::Time.
   //
-  // Choosing a TauR that is not an integer multiple of the computation time
-  // step h will leed to accurate (up to the resolution h) and self-consistent
+  // Choosing a t_ref_ that is not an integer multiple of the computation time
+  // step h will lead to accurate (up to the resolution h) and self-consistent
   // results. However, a neuron model capable of operating with real valued
   // spike time may exhibit a different effective refractory time.
 

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.cpp

@@ -271,23 +271,24 @@ nest::iaf_tum_2000::calibrate()
   V_.P20_ = P_.Tau_ / P_.C_ * ( 1.0 - V_.P22_ );
   // P20_ = h/C_;
 
-  // TauR specifies the length of the absolute refractory period as
-  // a double in ms. The grid based iaf_tum_2000 can only handle refractory
-  // periods that are integer multiples of the computation step size (h).
-  // To ensure consistency with the overall simulation scheme such conversion
-  // should be carried out via objects of class nest::Time. The conversion
-  // requires 2 steps:
-  //     1. A time object r is constructed defining  representation of
-  //        TauR in tics. This representation is then converted to computation
-  //        time steps again by a strategy defined by class nest::Time.
+  // tau_ref_abs_ and tau_ref_tot_ specify the length of the corresponding
+  // refractory periods as doubles in ms. The grid based iaf_tum_2000 can
+  // only handle refractory periods that are integer multiples of the
+  // computation step size (h). To ensure consistency with the overall
+  // simulation scheme such conversion should be carried out via objects of
+  // class nest::Time. The conversion requires 2 steps:
+  //     1. A time object r is constructed, defining representation of
+  //        tau_ref_{abs,tot} in tics. This representation is then converted
+  //        to computation time steps again by a strategy defined by class
+  //        nest::Time.
   //     2. The refractory time in units of steps is read out get_steps(), a
   //        member function of class nest::Time.
   //
-  // Choosing a TauR that is not an integer multiple of the computation time
-  // step h will leed to accurate (up to the resolution h) and self-consistent
-  // results. However, a neuron model capable of operating with real valued
-  // spike time may exhibit a different effective refractory time.
-  //
+  // Choosing a tau_ref_{abs,tot} that is not an integer multiple of the
+  // computation time step h will lead to accurate (up to the resolution h)
+  // and self- consistent results. However, a neuron model capable of
+  // operating with real valued spike time may exhibit a different
+  // effective refractory time.
 
   V_.RefractoryCountsAbs_ = Time( Time::ms( P_.tau_ref_abs_ ) ).get_steps();
 

models/iaf_tum_2000.h

@@ -46,13 +46,13 @@ namespace nest
    In particular, this model allows setting an absolute and relative
    refractory time separately, as required by [1].
 
-   The threshold crossing is followed by an absolute refractory period (tau_abs)
-   during which the membrane potential is clamped to the resting potential.
-   During the total refractory period, the membrane potential evolves,
-   but the neuron will not emit a spike, even if the membrane potential
-   reaches threshold. The total refractory time must be larger or equal to
-   the absolute refractory time. If equal, the refractoriness of the model
-   if equivalent to the other models of NEST.
+   The threshold crossing is followed by an absolute refractory period
+   (t_ref_abs) during which the membrane potential is clamped to the resting
+   potential. During the total refractory period (t_ref_tot), the membrane
+   potential evolves, but the neuron will not emit a spike, even if the
+   membrane potential reaches threshold. The total refractory time must be
+   larger or equal to the absolute refractory time. If equal, the
+   refractoriness of the model if equivalent to the other models of NEST.
 
    The linear subthreshold dynamics is integrated by the Exact
    Integration scheme [2]. The neuron dynamics is solved on the time
@@ -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:

models/mat2_psc_exp.cpp

@@ -292,15 +292,15 @@ nest::mat2_psc_exp::calibrate()
   // To ensure consistency with the overall simulation scheme such conversion
   // should be carried out via objects of class nest::Time. The conversion
   // requires 2 steps:
-  //     1. A time object r is constructed defining representation of
+  //     1. A time object r is constructed, defining representation of
   //        tau_ref_ in tics. This representation is then converted to
   //        computation time steps again by a strategy defined by class
   //        nest::Time.
   //     2. The refractory time in units of steps is read out get_steps(), a
   //        member function of class nest::Time.
   //
   // Choosing a tau_ref_ that is not an integer multiple of the computation time
-  // step h will leed to accurate (up to the resolution h) and self-consistent
+  // step h will lead to accurate (up to the resolution h) and self-consistent
   // results. However, a neuron model capable of operating with real valued
   // spike time may exhibit a different effective refractory time.
 

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.