code: def _neuron_states(self, inputs, t, argv):
          
          
          xi = inputs[0];
          index = argv;
          
          # own impact
          impact = self._weight[index][index] * self._outputs[index];
          
          for i in range(0, self._num_osc, 1):
              if (self.has_connection(i, index)):
                  impact += self._weight[index][i] * self._outputs[i];
  
          x = -xi + impact;
                  
          if (xi > 1): self._outputs_buffer[index] = 1; 
          if (xi < -1): self._outputs_buffer[index] = -1;
         
          return x;
docs: !
          @brief Returns new value of the neuron (oscillator).
          
          @param[in] inputs (list): Initial values (current) of the neuron - excitatory.
          @param[in] t (double): Current time of simulation.
          @param[in] argv (tuple): Extra arguments that are not used for integration - index of the neuron.
          
          @return (double) New value of the neuron.