neurons) compared with the random explora-
tion experiment, which may be attributed to
the increased attentional demand and highly
structured behavioral patterns exhibited dur-
ing the task ( 34 ). This high degree of nonlocal
spatiotemporal information was exemplified
by the ability to decode past, present, and fu-
ture positions on individual flight trajectories,
with higher performance for decoders using
the optimal time lag of each neuron (fig. S14;
see the supplementary materials and methods).
Furthermore, neurons appeared directionally
tuned to either the feeders or the stand direc-
tions, suggesting that the task environmenthad a polarizing effect on the neural represen-
tations (Fig. 2C). Indeed, 85% (155/183) of spa-
tially informative neurons and 81% (165/204)
of total neurons were significantly tuned for
headingatoneormoretimelags(seethesup-
plementary materials and methods). The re-
sulting spatiotemporal fields were distributedSCIENCEsciencemag.org 9JULY2021•VOL 373 ISSUE 6551 245
Fig. 3. Flight path intersections are aligned
with nonlocal spatiotemporal fields.
(A) Examples of intersecting flight paths. Each
panel shows the flights for two paths (one
path in gray and one in black). Blue dot
indicates the intersection point. Green (before
intersection) and red (after intersection)
highlights indicate the portion of the flights
used to calculate the intersection angles.
Intersection angles (enter and exit) are
indicated for each panel. (B) Locations of
spatiotemporal fields (black squares; largest
field is shown if multiple fields exist per
neuron) and intersections (red dots). Note the
tight correspondence between the location of
firing fields and intersections. (C) 2D heat
map of the differences inxaxis (stand-feeder
axis) andyaxis positions between spatio-
temporal fields and intersection locations
(normalized to maximum incidence).
The schematic on the right indicates the
xaxis andyaxis reference frame of the room.
(D) Distribution of the intersection phases.
For each intersection, there are two phases,
one for each path. (E) Firing rate tuning
profiles for each pair of paths at lag zero (top)
and the optimal lag (bottom). Rank is ordered
by the peak firing rates in path #1. Red dots
indicate the intersection phase. (F) Scatter
plots for the peak phase of path 1 and path 2 at
lag zero (top;r= 0.69,P< 0.01) and the
optimal lag (bottom;r= 0.81,P< 0.01). Least-
squares fit lines are shown in gray. (G) Histograms
showing the difference between the peak
firing rate phase and the phase of the intersec-
tion at lag zero and the optimal lag. Small
black and red arrows indicate the median
difference for lag zero and the optimal lag,
respectively (lag zero median = 34.03%, optimal
lag median =–2.27%).RESEARCH | REPORTS