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True on-lap computing?
To quantify the location shift between any two laps, for each sequence in one lap we computed the distance between its center location and the center location of the nearest sequence in the other lap.
The COM change of a firing field at each lap was computed relative to its stabilized value, which was the average of those values at laps #21 25.
For a pair of cells with overlapping firing fields, we identified each cell's spikes within its firing field for each individual lap, and computed two quantities of these spikes: the (within-field) firing rate and the center of mass (COM) of their firing locations.
For non-responsive pairs, the lap-by-lap fluctuations were computed within the dominant firing field for the location-responsive cell, and for the non-responsive cell within a randomly generated spatial interval that was overlapped with the field by a random percentage between 50%and 100%.
In addition, for each trajectory of a track, we measured the animal's performance by the number of laps on the trajectory and quantified the quality of the running by computing the cumulative travel distance per lap, the number of stops (defined as speed <4 cm/s lasting ≥2 s) per lap, and the stopping duration per lap.
This work was driven by the need to significantly reduce computing hardware resources and run times for whole body analyses, and to achieve this goal the lap-joint needs to be modelled by a 'small' number of shell elements.
If multiple sequences existed in any of the two laps, the distance was computed for every sequence and then averaged as the location shift between the two laps.
Computing this week.
Computing frustrations?
Computing blade.
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