def _neuron_states(self, inputs, t, argv):
xi = inputs[<NUM_LIT:0>];<EOL>index = argv;<EOL>impact = self._weight[index][index] * self._outputs[index];<EOL>for i in range(<NUM_LIT:0>, self._num_osc, <NUM_LIT:1>):<EOL><INDENT>if (self.has_connection(i, index)):<EOL><INDENT>impact += self._weight[index][i] * self._outputs[i];<EOL><DEDENT><DEDENT>x = -xi + impact;<EOL>if (xi > <NUM_LIT:1>): self._outputs_buffer[index] = <NUM_LIT:1>; <EOL>if (xi < -<NUM_LIT:1>): self._outputs_buffer[index] = -<NUM_LIT:1>;<EOL>return x<EOL>
!
        @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.