Solved by Adamits in post #2 
              
              
                More neurons in the hidden layer means that you are learning more parameters for more ‘connections’. The LSTM has, for a single state, a structure just like an MLP except that there is a second parameter matrix for the ‘previous state’. So just like with an MLP, more neurons means you are projecting…