Dear @MitchG_HunterCollege, the issue here is not disk space but memory in the sense of RAM. This is a serious limitation at the moment: all recorded values are stored in RAM before being written out to the disk in the end. The required memory can be quite big, for example, recording 2000 neurons with a timestep of 0.015msf for 10s, means 2000 × 666666 values of 8 bytes (double precision) each ≈ 10GB for each recorded variable… Until we support directly recording to disk, there are some rather complex workarounds like the one mentioned here: Saving data to disk in the middle of a simulation in standalone mode
I think the best approach for now is to choose a bigger time step for the recordings with the dt parameter (e.g. StateMonitor(..., dt=1*ms) and/or record fewer neurons. Changing from double to single precision (using StateMonitor(..., dtype=np.float32) will also half the required memory. Hope that gives some leads!