The salmon experiment was ages ago, and just showed that the threshold for statistical significance was too liberal. At that time, when neuroimaging was quite new, it was common practice to just pick a threshold, say .001, and not do corrections for multiple tests. That proved to be too liberal. It wasn't a totally stupid guess though. Much of the brain's BOLD activity is correlated, so Bonferroni correction was stupidly conservative (not independent tests). It was only then that newer techniques (cluster-based correction) were adopted, which explicitly made an assumption about the spatial autocorrelation of the data. The one assumption of this technique was that this autocorrelation was the same throughout the brain, which ended up not being a good assumption, though computationally useful. Newer methods today try to model the autocorrelation in the data for cluster based correction, or have moved to other numerical techniques for correction of multiple comparisons re repeated resampling.
So, while the dead salmon experiment was eye opening to some when the neuroimaging field was very new, it is no longer relevant now.
Neuroimaging techniques are constantly improving, both from better analytical techniques and knowledge about the factors that can compromise the veracity of analyses, but they, including the present paper, show that neuroimgaging is bunk science or useless, which is most certainly incorrect.