Furthermore, imaging dozens of neurons simultaneously allowed us to unravel temporal interactions between thousands of neuronal pairs as measured by noise correlations.
Most often, your result either with the other result.
This is how the new data you've generated is "situated" in the field -- by your careful placement of what is new against that which is already known.
While the introduction starts generally and narrows down to the specific hypothesis, the discussion starts with the interpretation of the results, then moves outwards to contextualize these findings in the general field.
The Discussion section is sort of an odd beast because it is here where you speculate, but must avoid rambling, guessing, or making logical leaps beyond what is reasonably supported for your data.
As tempting as it may be, avoid over-using the grammatical first person.
"I" is powerful grammatically and can be intrusive if used too often.
These findings are consistent with the random connectivity model provided that there is at least one component of the overall connectivity that is strong, sparse and decreases fast with distance.
Such a model would result in the formation of Notably, a subnetworks model would account for the details of the dependence of signal correlation and noise correlation on distance.
Results can take the form of data, hypotheses, models, definitions, formulas, etc.
(I imagine the Results section like a dance with swords -- sometimes you are engaging your partner with the pointy end and sometimes you are gliding along side them).