You may be asking 3.7 questions in an XY problem setup.
To start with, a path integral is just a (powerful) gimmick to propagate an oscillator, and as you see from the diffusion kernel, it sums over an infinity of paths (unphysical, if you will). This is all in NR one particle QM. So, given the initial conditions, a wavefunction is just these, properly propagated thusly.
Now, a one-particle oscillator wavefunction connects to the superior matrix/operator mechanics like this. You could redo the path integral propagation of the $a, a^\dagger$ operators to all times in path integral language, if you so desire.
To go to QFT, you repackage an infinity of such oscillators $a_k, a_k^\dagger$ by decoupling them in momentum space: the famous normal mode reduction. You enforce Lorentz-invariance, much more easily than in any other way, and upload all to the path integral, if so desired.
It is a bad idea, for problem solving, to squeeze NR one particle wavefunctions out of this, but it could be done.... but why? This defocuses you from the wonderful reverse transition to QFT.
Your "cross section of paths" imagery is present in the first paragraph, (1), where the propagator is actually an integral transform giving preference to paths that maximize the contributions of the kernel $K(x',x;t)$ propagating the wavefunction from the initial state to all places and times. The outstanding book by Feynman and Hibbs on the subject is still a go-to classic.
Response to last comment/question
- By and large, yes. Quantum fields are that mattress, pervading space. Its infinite coupled springs decouple to oscillator normal modes which represent free particles. This is the essence of QFT. Your text should detail it better than my refs. So, in my link to propagators, the propagator for the oscillator represents these notional springs when detached, and that of the free particle, integrating over decoupled amplitudes if you wish, amount to the free particle modes, for each and every E and p... "Real"? Notional? It's a philosopher's dream to tell the difference.