Dense? or TimeDistributedDense? after LSTM layer in Keras Dense and TimeDistributedDense, which one is suitable after LSTM layer in Keras?

For example,

input = Input(shape=(12,N_indepen), dtype='float32', name='inci_input')
lstm = Bidirectional(LSTM(100, activation='elu',return_sequences=False))(input)

# Dense? or TimeDistributedDense?
dense = layers.Dense(30, activation='elu')(lstm)
dense = layers.TimeDistributedDense(30, activation='elu')(lstm)

m_y = layers.Dense(1, activation='linear')(dense)


I read some articles, most of them used Dense, but some used TimeDistributedDense. I hope to know what is proper theoretically.
When using the TimeDistributed, you need to have a sequence through time so that you can apply the same layer (in this case, Dense), to each time slice. In your code, you have return_sequences=False which does not produce a sequence, so you need to apply Dense.
Assuming you meant to put return_sequences=True, then Dense and TimeDistributedDense do the same task in this case.