The document summarizes a study examining how the brain fragments environments into distinct subspaces based on cognitive processes rather than sensory stimuli. Rats were trained on a task where the correct action (left or right turn) at the top of a T-maze depended on the maze's location in the room, effectively fragmenting the environment. Neuronal ensembles in the parietal cortex and hippocampus were recorded. Results showed the rats were capable of environment fragmentation. Hippocampal place cells tended to code for locations on the track rather than in the room. Parietal and hippocampal ensemble activity patterns diverged earlier when comparing between versus within fragments, suggesting these areas map fragmented spaces.

1. Crea%ng spaces: A possible func%on of the hippocampal and parietal networks
Laura E. Shelley, Desi Chu, Shuying Yu, Stacy Kim, ScoC Ragland, Kiana Miyamoto, Jonghwi Park, and Douglas A. Nitz
University of California, San Diego - Department of Cogni%ve Science
abstract
Our research focus addresses how brain systems produce abstract, high-level spa:al concepts. We examined how the brain
‘fragments’ environments into dis:nct sub-spaces based on cogni:ve processes such as rule learning, rather than concrete
sensory s:muli. People do this in their everyday environments. A studio apartment, for instance, can be mentally fragmented
into dis:nct subspaces according to different ac:ons taken in different areas. There’s an area for ea:ng, an area for desk-
work, and an area for sleeping, all without walls physically separa:ng those spaces. Similarly, different neighborhoods in a
city can feel and seem like dis:nct subspaces depending on what the different spaces afford you. A neighborhood full of of
restaurants, bars, and clubs will seem dis:nct from a neighborhood with a lot of parks and suburban homes, even if the
neighborhoods adjoin to make one con:nuous space. We studied this fragmenta:on phenomenon in rats on a rule-based,
decision-making naviga:onal paradigm. The paradigm allowed us to examine the interface between an animal’s awareness of
environmental posi:on and how they apply rules for ac:on. Rats were trained to run up the stem of a T-shaped track, and
either turn leH or right at the top of the T. The correct ac:on depended on where the track was placed in a room, effec:vely
fragmen:ng the environment into two subspaces (see figure below). Behavioral results indicated that rats are capable of
learning such logical fragmenta:on. Studying this phenomenon in rats also afforded us the opportunity to see how subspaces
are mapped out at the neuron level. To this end, we recorded ensembles of single neurons in the parietal cortex and
hippocampus to determine what adapta:ons of their place-specific firing paMerns yielded a capability for logical
fragmenta:on. Neurons mapped out different features of the task (see results sec:on). Surprisingly, place-specific
hippocampal firing tended to adhere to loca:ons on the track rather than loca:ons in the room. It is possible room loca:on
mapping took a different form as evidenced by changes in in-field firing rates at different track posi:ons. Further recordings
in other brain areas may reveal more about how fragmenta:on is handled by the brain.
materials and methods
training, tracking, and recording
• Animals were trained to run up the stem of a T-shaped track and either turn leH or right at the top of the T to receive a food reward.
• The correct leH or right turn response depended on where the track was placed in the room (6 possible loca:ons, see figure below).
• Rats performed 28 blocks consis:ng of five trials each. During a block, the track was leH in one posi:on for five trials before the track was
moved to a new posi:on for the next block. Posi:on order was randomized.
• Custom-built, movable microdrives were surgically implanted over the right and leH hemispheres targe:ng the posterior parietal cortex
(anterior-posterior: -3.5mm; medial-lateral 2.3mm; .5mm deep). Wires could be moved ventrally into the hippocampus.
• Neurons were recorded while rats performed the task.
• LED lights fixed to the rat’s head were tracked via an overhead camera to determine animal’s posi:on at any :me during the task. Neural
ac:vity could then be matched to the rat’s posi:on.
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pos 1
pos 2
pos 3
pos 5
pos 4
pos 6 *
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results
animals are capable of fragmen:ng an environment
DN10
Pos 5:
Pos 6:
DN9
Pos 5:
Pos 6:
AL2
Pos 5:
Pos 6:
within- vs. between-fragments ensemble correla:ons
parietal cortex
ac.on execu.on: straight run
run start end turn
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*
firing
rate
0-40hz
parietal cortex
ac.on planning
run start end turn
*
*
firing
rate
0-40hz
hippocampus
first trial cells
firing
rate
trial 1
trials 2-4
0-40hz
run start end turn
*
*
hippocampus
place cells follow track space
firing
rate
0-50hz
run start end turn
*
*
hippocampus
place cells change in-field firing rates
firing
rate
0-20hz
run start end turn
*
*
parietal cortex
pos1 vs pos2 pos1 vs pos3 pos1 vs pos4
pos2 vs pos3 pos2 vs pos4
pos3 vs pos4
run
start
end
run start end
turn
turn
ensemble
firing rate
correla:ons
run start end turn
point of paMern divergence
(within fragments vs between fragments)
pos 1vs2, 3vs4 (within fragment)
pos 1vs3, 1vs4, 2vs3, 2vs4
(between fragment)
hippocampus
pos1 vs pos2 pos1 vs pos3 pos1 vs pos4
pos2 vs pos3 pos2 vs pos4
pos3 vs pos4
run
start
end
run start end
turn
turn
ensemble
firing rate
correla:ons
run start end turn
point of paMern divergence
(within fragments vs between fragments)
pos 1vs2, 3vs4 (within fragment)
pos 1vs3, 1vs4, 2vs3, 2vs4
(between fragment)
ensemble
firing rate
correla:ons
run start end turn
parietal cortex and hippocampus
parietal cortex
ac.on execu.on: turns
firing
rate
0-40hz
run start end turn
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