What is the meaning of × in statistics? What is the meaning of the symbol × in an ANOVA context?
More specifically what is the meaning of × in the following table?
Study        Condition MeanSource      SS     df MS    F     p 
Original     .700      Subjects        0.668  39 
Mirror image .621      Item            0.357   2 0.178 12.90 <.001
Unprimed     .567      Item × Subjects 1.078  78 0.014
                       Total           2.103 119

And how can I calculate SS for the third row in the table?
 A: That x is probably representing an interaction term. 
You should really give us more information about the data (and the experiment which produced it), but the SS's here seems to be sequential SS's, as  $0.668+0.357+1.078
=2.103$. Note also that for the df's (degrees of freedom) from the table we have:  $119-78-2-39=0$, so there is no df's left for error. That means that the interaction term Item × Subjects here is confounded with Error. 
The anova table shows that indeed the interaction is used as an estimate of error variance, since $ 0.178/0.014 = 12.71429$ and  pf(12.71429, 2, 78, lower.tail=FALSE) returns  1.662293e-05.  How can it be allowable to use an interaction as error? Again, it would help to know the specifics of this experiment, but:  Assuming this is a randomized experiment, with some Subjects randomized to some treatment group Item.  Then the interest is really in comparing the different treatments.  The Subjects are just some random persons/animals/whatever used to compare the Items. We are not specifically interested in comparing different Subjects. 
The act of randomization means that there should not be systematic differences between the subjects randomized to the different treatments, the subjects are in reality a random factor. The act of randomization is what justifies the use of the interaction as error.
A: The original paper (cited in the link you provided) tells us that the data were collected using a "repeated-measures ANOVA" experimental design (see page 492, last paragraph).  To learn how to calculate the ANOVA table for data from such a study, read a textbook on ANOVA.  Probably a first or second course textbook would tell you how to do that.  (BTW, the column headings in your ANOVA table do not line up perfectly, making the table a bit confusing. See the table in the original article.)  The original paper is here: https://www.researchgate.net/profile/Anna-Lisa_Cohen/publication/24187239_Long-Term_Repetition_Priming_of_Briefly_Identified_Objects/links/00b7d51a505f7c0c8f000000/Long-Term-Repetition-Priming-of-Briefly-Identified-Objects.pdf
