Perhaps her neurons are different, i.e. she could rewire some part of her brain as needed - forgetting past experience to free up the capacity for the new one - and this is why it takes hours of setup (observation) and this is why she can do it over and over again within the confines of 600K neurons.
Synapse "rewiring" is not typically how we think memories are formed in adult animals. Mostly it is done by modulating the strengths of the existing connections (this process involves signaling cascades and protein expression, so it does take some time). So if you want to form a "memory", a particular connection is strengthened. There isn't a concomitant loss of another connection. It's not a zero sum game.
All my statements are based on my understanding of mammalian learning and memory. But I think you hit on the key with "Perhaps her neurons are different".
Indeed, invertebrate neurons are wildly different from those of mammals. In fact, if you are accustomed to looking at mammalian neurons [1], invertebrate neurons can look positively alien. For example, check out the Lobula Giant Movement Detector (LGMD) neuron of the locust [2] and other insects [3].
A) The scale is different: The thickness of some of its branches are about the size of the cell body on a mammalian neuron.
B) The organization is different: The dendritic arbor is divided into nearly independent subfields with very independent functions.
C) The behavior is different: The spike output patterns of an LGMD would be distinguishable to a first-year neuroscience student. And the output connections are extremely strong, pretty much one-to-one.
Add it all together, and this one neuron does the job of at least a few dozen mammalian neurons. How many, exactly, is difficult to tell. Not every insect neuron is as fantastical as the LGMD, but I would say that "600000" value ought to be scaled by some number greater than five. Given that, one could say our spider friend has the equivalent of several million mammalian neurons.
Raw neuron count is merely the crudest of measures of neural processing capability. How sophisticated the processing nodes are (i.e., the neurons) and how they are wired together (i.e., the network topology) are way more critical.
Perhaps her neurons are different, i.e. she could rewire some part of her brain as needed - forgetting past experience to free up the capacity for the new one - and this is why it takes hours of setup (observation) and this is why she can do it over and over again within the confines of 600K neurons.