1Department of Neurobiology and Anatomy, W. M. Keck Center for the Neurobiology of Learning and Memory, University of Texas-Houston Medical School, Houston, Texas 77225; and 2Arizona Research Laboratories Division of Neural Systems, Memory, and Aging, University of Arizona, Tucson, Arizona 85724
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ABSTRACT |
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Knierim, James J. and Bruce L. McNaughton. Hippocampal Place-Cell Firing During Movement in Three-Dimensional Space. J. Neurophysiol. 85: 105-116, 2001. "Place" cells of the rat hippocampus are coupled to "head direction" cells of the thalamus and limbic cortex. Head direction cells are sensitive to head direction in the horizontal plane only, which leads to the question of whether place cells similarly encode locations in the horizontal plane only, ignoring the z axis, or whether they encode locations in three dimensions. This question was addressed by recording from ensembles of CA1 pyramidal cells while rats traversed a rectangular track that could be tilted and rotated to different three-dimensional orientations. Cells were analyzed to determine whether their firing was bound to the external, three-dimensional cues of the environment, to the two-dimensional rectangular surface, or to some combination of these cues. Tilting the track 45° generally provoked a partial remapping of the rectangular surface in that some cells maintained their place fields, whereas other cells either gained new place fields, lost existing fields, or changed their firing locations arbitrarily. When the tilted track was rotated relative to the distal landmarks, most place fields remapped, but a number of cells maintained the same place field relative to the x-y coordinate frame of the laboratory, ignoring the z axis. No more cells were bound to the local reference frame of the recording apparatus than would be predicted by chance. The partial remapping demonstrated that the place cell system was sensitive to the three-dimensional manipulations of the recording apparatus. Nonetheless the results were not consistent with an explicit three-dimensional tuning of individual hippocampal neurons nor were they consistent with a model in which different sets of cells are tightly coupled to different sets of environmental cues. The results are most consistent with the statement that hippocampal neurons can change their "tuning functions" in arbitrary ways when features of the sensory input or behavioral context are altered. Understanding the rules that govern the remapping phenomenon holds promise for deciphering the neural circuitry underlying hippocampal function.
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INTRODUCTION |
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Two types of neurons in the
rodent brain have been implicated in spatial learning and navigation
processes: "place" cells of the hippocampus and "head
direction" (HD) cells of the thalamus and postsubiculum
(O'Keefe and Dostrovsky 1971; Taube et al.
1990a
). These two brain systems are coupled in that
manipulations that cause HD cells to rotate their preferred firing
directions in an environment will cause the ensemble of place cells
that represent that environment to either rotate their place fields by
the same amount or to "remap" the environment (Blair and
Sharp 1996
; Bostock et al. 1991
; Knierim
et al. 1995
; Sharp et al. 1995
; Tanila et al. 1997
). A situation has never been reported in which the
hippocampal ensemble representation maintains its internal coherency
(i.e., does not remap) but changes its orientation relative to that of the HD system, and it has thus been postulated that one role of the HD
cell system is to set the orientation of the hippocampal "cognitive
map" (Muller et al. 1996
; O'Keefe and Nadel
1978
).
Nonetheless there are key differences between the properties of place
and HD cells. The tuning curves of HD cells are inherently one
dimensional. These cells are sensitive to head direction in the yaw
axis only; changes in direction in the pitch and roll axes (±90°)
have no effect on their firing (Stackman et al. 2000; Taube 1998
). Under normal conditions, a HD cell will
have a preferred firing direction in all environments, and the relative
directions between pairs of HD cells will remain constant in all
environments (Taube 1998
).
Place cells have certain properties that are fundamentally different
from these properties of HD cells (Muller et al. 1996). The spatial selectivity of place cells on a flat surface is (at a
minimum) two dimensional. Place cells typically change their firing
properties unpredictably between two distinct environments, and the
spatial relationships between the fields of different place cells do
not remain consistent from environment to environment (Kubie and
Ranck 1983
; O'Keefe and Conway 1978
). Finally,
only a fraction of place cells are typically active in any given
environment; the remaining cells are virtually silent (Guzowski
et al. 1999
; O'Keefe and Conway 1978
;
Thompson and Best 1989
; Wilson and McNaughton 1993
).
Most studies of place cells have been restricted to essentially
two-dimensional environments, leaving unanswered the question of
whether place cells (like HD cells) are insensitive to changes in the
z axis. The answer would have strong implications for models that attempt to define the mechanisms by which place cells acquire their spatial specificity. One class of models postulates that place
cells encode unique configurations of sensory and internal input
("local views") (McNaughton 1989; McNaughton
et al. 1983a
) that are available to an animal at a given
spatial location (e.g., Shapiro and Hetherington 1993
;
Sharp 1991
; Zipser 1985
). According to a
strict interpretation of this view, place fields should be three
dimensional as changes in position along the z axis result in equivalent modifications of the sensory input as changes in the
x or y axes. A recent model has emphasized the
role of the hippocampus in path integration (McNaughton et al.
1996
; Samsonovich and McNaughton 1997
; see also
Whishaw et al. 1997
). In this model, place cells use
primarily self-motion (idiothetic) cues to encode the animal's
distance and bearing relative to some starting location. As the animal
moves forward in a certain direction, inputs from idiothetic cues and
from the HD cell system update the network to represent the new
location. Modifiable inputs from external landmarks allow for the
correction of cumulative error after the animal gains familiarity in an
environment. Because HD cells are sensitive to changes only in the yaw
axis, this model postulates that the path integration mechanisms in the
hippocampus would be unable to distinguish forward motion in the
horizontal plane from forward motion in an oblique plane and that place
cells would thus be insensitive to the animal's location in the
z axis.
The present study was designed to test this prediction. Ideally one
would record from place cells as an animal navigates in a stable,
three-dimensional volume. Rats are constrained to navigate along
surfaces, however. Thus to address this question, ensembles of place
cells were recorded as rats traversed a rectangular track that could be
tilted and rotated to different three-dimensional orientations.
Although most studies of place cells demonstrate that distal cues have
precedence over local surface cues in controlling the firing locations
of place cells, recent studies (e.g., Shapiro et al.
1997; Tanila et al. 1997
) have shown that more
salient local cues can exert an influence over these cells and trigger remapping. It was not known whether changes in the three-dimensional orientation of a local surface would be a cue that is salient enough to
exert a similar influence. Thus the place fields were analyzed to
determine whether they were bound to the distal cues of the
environment, whether they were bound to the two-dimensional rectangular
surface, or whether the manipulations caused an unpredictable remapping
of the surface. The results demonstrate that such three-dimensional manipulations of the local surface can cause a partial remapping of the
hippocampal representation as a majority of cells changed their place
fields unpredictably while a minority maintained the same field
relative to the x-y coordinates of the room, ignoring the
z axis. These results contribute to our understanding of the nature of the interaction between distal landmarks and local cues in
the firing of place cells and of the network dynamics of the hippocampal representation of an environment.
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METHODS |
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Subjects
The experiments were performed on two groups of four rats. Group 1 comprised four male retired breeder Fischer-344 rats obtained from the National Institute on Aging colony at Harlan Laboratories at ~9 mo old. They were ~14 mo old at the time of recording. Group 2 comprised four specific-pathogen-free male Fischer-344 rats obtained from Taconic Farms at a~ 4 mo old; they were ~9 mo old at the time of recording. All animals were put on a controlled feeding schedule to maintain their weights at 80-90% of their ad libitum weights. The rats had free access to water. During the experiment, they were handled and weighed daily. The rats were housed individually and maintained on a 12:12 h reversed light:dark cycle (lights off 10 AM to 10 PM). Recording was done during the dark portion of the cycle. Animal care, surgical procedures, and euthanasia were carried out according to National Institutes of Health guidelines.
Training
Group 1 was trained initially to shuttle back and
forth for combinations of food reward (45-mg pellets or a wet mash of
moistened rat chow) or electrical stimulation of the medial forebrain
bundle (MFB; 30-150 µA current, 300-µs pulses at 100 Hz for
0.5 s) at each end of a 91 × 13 cm alley. This training,
which lasted 3-17 days, was used to ascertain the proper levels of MFB
stimulation adequate to promote good behavioral performance for each
rat. The rats were then trained to run clockwise for food and MFB
stimulation on a rectangular track (38 × 62 cm) that could be
tilted up to a 45° angle along its long axis (Fig.
1). The surface of each side of the track
was 8.5 cm wide. Hinges connected the four sides and allowed the long
sides of the track to be tilted while the short sides of the track
remained horizontal. The short side at the north was supported by two
stationary wooden blocks (12.7 cm high) attached to a wooden base
(76 × 51 cm). The short side at the south was supported by a
hinged arm that allowed it to be raised and lowered. The number of
rewards per lap was gradually reduced until the rat was receiving
rewards only at the middle of each short side of the rectangular track.
When the rat was performing this task reliably, the south side of the
track was gradually raised in increments of 5° until the rat was
running reliably at a track angle of 4045°. The final stage of
training was to acclimate the rat to run 10-15 laps on the flat track, followed by 10-15 laps at the 40
45° tilt angle, and then a final set of 10-15 laps on the flat track. Total training on the rectangle for these rats covered 17-23 sessions over 25-43 days; thus by the
time recording commenced, the rats were highly familiar with the tilted
track, having spent the majority of training time with some degree of
tilt to the track (although they never experienced the track rotations
described in the following text before the start of recording).
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The rats of group 2 had a richer set of training experiences
prior to this experiment. The rats received ~40 days of presurgery training to shuttle for food on the alley track (described in the
preceding text) prior to surgery. After surgical implant of recording
electrodes and MFB stimulation electrodes (see following text), they
were also trained to perform two more tasks for MFB stimulation: to run
clockwise around the tilted rectangular track and to run clockwise
around a small plus maze (20 cm per arm). Training sessions occurred
for ~30 min for 14 days. The animals then took part in two unrelated
experiments involving foraging for food pellets in a cylindrical
chamber (Knierim et al. 1998) or along a circular track.
At the end of these experiments, they received 5 days of training on
the rectangular track described in Fig. 1, including 2 days of
acclimation to the interleaved flat/tilted/flat sessions. Three of the
rats ran for MFB stimulation, whereas the fourth ran for food reward.
Surgery
Surgeries for these rats were performed according to NIH
guidelines using techniques described in detail elsewhere
(Gothard et al. 1996). Briefly, rats were anesthetized
with pentobarbital sodium (Nembutal, 40 mg/kg ip), supplemented with
methoxyflurane (Metofane) inhalation as necessary. Intramuscular
penicillin (30,000 U of Bicillin in each hindlimb) was administered as
a prophylactic antibiotic. A recording device ("Neuro-hyperdrive,"
Kopf Instruments, Tujunga, CA) that allowed the independent
manipulation of 14 recording probes was implanted over the right
hemisphere of each rat (3.8 mm P, 2.0 mm L from Bregma). Twelve of the
probes were tetrodes made of four lengths of fine nichrome wire
(13-µm diam; H. P. Reid, Palm Coast, FL) twisted together
(McNaughton et al. 1983b
; Recce and O'Keefe
1989
; Wilson and McNaughton 1993
). The other two
were single-channel probes for recording electroencephalographic (EEG)
and reference signals. In addition, each rat was implanted bilaterally
with a bipolar stimulating electrode in each hemisphere aimed at the
MFB (0.25 mm A, 1.9 mm L from Bregma, 8.5 mm V from brain surface,
angled 19.5° posteriorly in the sagittal plane). The stimulating
electrode was made of two lengths of 0.003-in diameter,
Teflon-insulated, stainless steel wire (Medwire, Mount Vernon, NY)
twisted together with ~1 mm spacing between the two electrode tips.
After surgery, rats from all groups recovered from anesthesia in an
incubator, and they were administered 26 mg of acetaminophen
(Children's Tylenol) orally for analgesia. They also received 2.7 mg/ml acetaminophen in their drinking water for 1-3 days after surgery.
Recording electronics
After 2-7 days postsurgical recovery, the electrodes were
advanced gradually over the course of many days. Neuronal signals were
passed through a headstage of low-noise, unity gain, CMOS operational
amplifiers (Neuralynx, Tucson, AZ) that could be attached to the
hyperdrive. Also mounted on the front of the headstage was an array of
infrared light-emitting diodes (LEDs), and attached to the back was an
arm with a single LED on the end (16 cm from the front LEDs) to track
the animal's position and head direction during the recording trials.
The LED signals were sampled at 20 Hz (SA-2 Dragon Tracker, Boulder,
CO) and stored on disk. Electrical signals were amplified between 2,500 and 10,000 times and filtered between 600 Hz and 6 kHz, before being
digitized at 32 kHz and stored in a 25-MHz IBM 80486-based workstation.
(See Gothard et al. 1996, for a description of the
multiunit recording system.) Activity also was monitored through an
audio monitor (Grass Instruments, West Warwick, Rhode Island).
Experimental protocol
Three experiments were performed on the rats. All eight rats were tested in experiment 1, whereas only the four rats from group 2 were tested in experiments 2 and 3. For each experiment, the rat was brought into the recording room and was placed in a holding dish near the track. Tetrodes were monitored for units, and adjustments were made as necessary to optimize the signal quality. Because the implants on these rats were relatively old (2-3 mo since surgery), many tetrodes were no longer functional, but each rat had at least two functional tetrodes (range 2-9). Baseline data were recorded from each rat for 15-30 min while it sat quietly in the holding dish before the first experimental session and after the last session of the day. Comparison of the firing patterns in these baseline sessions helped in the determination of recording stability during the sessions.
EXPERIMENT 1.
For group 1, the experiment took place in a corner alcove
(3.2 × 2.25 m) of an open laboratory with many visual
landmarks (e.g., curtains, bench tops, computers, lights, and
electronic equipment). The rectangular track was located approximately
0.5 m from two walls of the alcove and ~2 m from the third wall.
The recording system was located next to the track. For group
2, the experiment took place in a sound-attenuated recording room
illuminated by four dim lights spaced symmetrically around the center
of the room. A circle of black curtains that hung from the ceiling to the floor surrounded the perimeter of the room (3.5 m diam). The rectangle apparatus was centered in this curtained area on top of a
wooden circular table (1.67 m diam). Nine large salient objects of
various dimensions, placed on the floor (a roll of bubble wrap, a
wooden triangular apparatus, a large square piece of plywood, a coat
rack, a white card, and a large gray ring), attached to the curtains (a
white card with black diagonal stripes), or suspended from the ceiling
(a white, inverted cone and a striped post) provided distinct visual
landmarks in all three dimensions. In addition, the door to the
adjacent computer room, which housed the recording electronics, was
left ajar, allowing the sounds of the recording equipment and audio
monitor into the room. Both groups of rats were taken from the holding
dish after the first baseline period and placed in the middle of the
north side of the track, facing clockwise. The track used for recording
was made of four rectangular pieces of plastic (51 × 8.5 cm)
covered with gray foam rubber; it was slightly larger (51 × 68 cm) than that used during training. The rats were run for 10-15 laps
around the track for food or MFB stimulation at the middle of each
short side of the track with occasional extra rewards given at
different locations on the track as necessary to promote good
behavioral performance. The rats were placed back in the holding dish,
and the south side of the track was raised such that the long sides
were tilted at 4045°; the north side of the track remained in the
exact same position in three-dimensional space (see Fig.
2). (For 1 rat, the sides were tilted at
only 30° on 1 day because the rat would not perform at the steeper
angles; only 2 cells from that session contributed to the analysis and
they did not differ from the overall pattern of results.) The rat was
placed back on the track at the usual starting location and was run for
10-15 laps on the tilted track. It was removed from the track, the
track was returned to its original flat configuration, and a final set
of 10-15 laps was run. After a baseline period was recorded in the
dish, the rat was returned to the colony room. This procedure was
performed two to four times for the rats in group 1 and only
once for each rat in group 2.
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EXPERIMENT 2. Only the four rats from group 2 took place in this experiment, which was run in the sound-attenuated room described in the preceding text. After the initial baseline period, the rats ran 12-15 laps on the flat track, after which they were removed and the track was rotated 180° (see Fig. 5). The rats were placed on the north arm of the track (i.e., in the same location relative to the external room but 180° opposite relative to the track) and were run for another 12-15 laps. The track was rotated back to its original position, and the south side was raised to the 40° tilt position for another session. The rat was removed, and the tilted rectangle was rotated 180° such that the high side occupied the same location in x-y coordinates that had been occupied by the low side and vice-versa. The rat was placed on the track on the high side (i.e., in the same x-y coordinates relative to the room as before) and was run for 12-15 laps. Finally, the track was returned to the standard, flat configuration for a final session of 12-15 laps. After this session, a second baseline period ensued.
EXPERIMENT 3. The four rats from group 2 took place in this experiment. The protocol was the same as for experiment 2 except that the track was rotated only 90° in the second and fourth sessions rather than 180° (see Fig. 9). The track was rotated around the vertical line through the center of the rectangle such that none of the arms occupied the exact same location in x-y coordinates in both the normal and 90° rotated conditions. In these sessions, the rat was placed on the track on the same side relative to the track (i.e., 90° rotated relative to the room) so as to avoid placing the rat on the tilted part of the track in the rotated/tilted session. For two of the rats, sessions 1, 2, and 5 were flat and sessions 3 and 4 were tilted, whereas for the other two rats, sessions 1, 2, and 5 were tilted and sessions 3 and 4 were flat.
Data analysis
OFF-LINE UNIT ISOLATION.
The tetrode (McNaughton et al. 1983b; Recce and
O'Keefe 1989
; Wilson and McNaughton 1993
)
allows the isolation of single units based primarily on the relative
amplitudes of signals recorded simultaneously at four slightly
different locations. Additional waveform characteristics, such as spike
width, also are used. Waveform characteristics were plotted as a
scatter plot of one of the electrodes versus another. Individual units
formed clusters of points on such scatter plots, and the boundaries of
these plots were defined with the use of a custom interactive program
(Xclust, M. Wilson) running on a Sun Sparcstation. The spike
times of individual units then were combined with the position and
direction information provided by the tracker to generate firing rate maps.
FIRING-RATE MAPS.
Firing-rate maps were constructed by dividing the behavioral apparatus
into 2.4-cm square bins for group 1 and 1.5-cm square bins
for group 2. The firing rate for each bin was calculated with an "adaptive binning" formula, which optimizes the tradeoff between sampling error and spatial resolution (Skaggs et al.
1996). The results were plotted as a grayscale rate map. The
specificity of spatial tuning for each cell was calculated as the
amount of information about the rat's position conveyed by the firing
of a single spike from the cell (Skaggs et al. 1993
). It
was defined as
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SPATIAL CORRELATION ANALYSIS. To quantify the similarity in place fields between different sessions, a spatial correlation score was measured for each cell. Each side of the track was divided into 10 bins, and a firing rate for each bin was calculated by dividing the number of spikes fired by the cell while the rat occupied that bin by the total amount of time spent by the rat in the bin, thus generating a one-dimensional, topologically circular array of 40 firing-rate bins (Fig. 1B). This analysis was performed on the raw data (rather than the adaptively binned data; see preceding text) and the bins were smoothed by recalculating the firing rate of each bin as the average of itself and its two adjacent bins. For each cell, the similarity in its place fields between two sessions was measured as the Pearson product-moment correlation between its firing-rate arrays in each session. For experiments 2 and 3, these correlations were performed in both a track-based reference frame and a room-based reference frame. Because the 40-bin firing rate arrays were anchored to the track itself (i.e., each bin was always at the same location on the track, regardless of the position or orientation of the track in the room), an analysis in the track-based reference frame entailed simply a correlation between corresponding bins. To analyze the results in a room-based reference frame, the data in one array were shifted (by 20 bins for the 180° rotations of experiment 2 and by 10 bins for the 90° rotations of experiment 3) relative to the other array and the correlation was performed between the original array of the first session and the shifted array of the second session. A comparison of the correlation coefficients between the room- and track-based correlations enabled a determination of whether the place fields were bound more strongly to the external room cues or to the cues local to the track. Correlations between a particular pair of sessions for each cell were calculated only if the cell met the inclusion criteria for at least one session of the pair.
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RESULTS |
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Experiment 1: effects of tilting the track
The effects of tilting the rectangular track were analyzed for 82 cells from the eight rats of groups 1 and 2. The
set of analyzed cells includes only those cells that had a significant place field in at least one of the three sessions and does not include
the many cells that were silent or fired weakly on the track. These
cells were all recorded from the CA1 field of the hippocampus. This
experiment was performed two to four times on each rat of group
1. To avoid possible double-counting, cells were included in the
analysis for only 1 day of recordings for each tetrode, based on the
first day that stable unit isolation was obtained for that tetrode. The
analyzed cells came from no more than two data sets in each rat. The
experiment was performed only once on the rats of group 2. The results from 17 of 18 simultaneously recorded cells from rat
109 are shown in Fig. 2. When the flat track was tilted by
~45°, some cells maintained similar firing fields (e.g., cells 6, 9, and 15), whereas other cells changed their firing fields (e.g.,
cells 3, 4, and 11). A histogram of correlations between the spatial
firing distributions on the flat rectangle versus the tilted rectangle
of all cells for this recording session is shown in Fig.
3B. The correlations were
significantly smaller than the correlations between the first and
second flat sessions (Fig. 3A; Mann-Whitney U
test P 0.024), although ~1/3 of the cells had a
high correlation between the flat and tilted sessions. This
distribution suggests that the representation of the track was
partially remapped as a result of the 45° tilt, as many cells changed
their firing fields on the track, whereas other cells maintained the
same field. It is possible, however, that the tilt manipulation caused
the hippocampus to remap the track completely and that those cells that
maintained a high correlation between the tilted and flat rectangles
did so as a result of chance. That is, two hippocampal representations
that are completely independent and orthogonal will contain purely by
chance a certain proportion of cells with similar place fields in each
representation. The expected distribution of such random place field
duplications is an unknown function of place field size, shape, and the
probability of a cell having a place field in a given environment
and/or behavioral task. To estimate this distribution, the spatial
firing pattern of each place cell on the flat track was correlated with
the place fields of all other cells in the sample on the tilted track.
This simulation gives an estimate of what the distribution of
correlations would be if the two representations were completely
independent. The real distribution of place field correlations was then
compared with this simulated distribution to test for the statistical
significance of any difference.
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Figure 3C shows the expected distribution of correlations if
the firing fields between the two sessions were completely
uncorrelated, and the actual distribution shown in Fig. 3B
is significantly different from this predicted distribution
(Mann-Whitney, P 0.014). These results indicate that
some place cells maintained their firing fields relative to the track
in the tilted and flat tracks, whereas other cells changed their
fields. The results from this rat were representative of the population
as a whole as the same analyses performed on the 82 cells pooled from
all eight rats showed an identical pattern of results (Fig. 3,
D-F). It is not known whether all eight rats demonstrated
partial remapping as there were usually not enough cells recorded in
each data set to generate the statistical power to test this question.
For the two rats with the greatest number of active place cells
recorded in a single session (rat 109 with 18 cells,
described in the preceding text, and rat 117 with 21 cells),
the distributions of correlations between the flat and tilted tracks
were each significantly different from those produced by the simulation
of completely independent remapping (P < 0.02). Thus
the partial remapping effect can be seen at the level of individual
data sets as well as at the population level (see also Skaggs
and McNaughton 1998
).
One interpretation of this partial remapping might be that it reflects
a three-dimensional tuning profiles of place cells. If place fields are
three dimensional, one would predict that the cells that were highly
correlated between the tilted and flat rectangles would have fields at
the north side of the track (which did not change location in the
z axis when the flat track was tilted) and that the cells
that were uncorrelated between the two tracks would have fields at the
south side of the track (the raised side). There was no significant
difference, however, between the correlations between the flat and
tilted rectangles for those cells that had place fields on the south
half (Fig. 4A) or the north
half (Fig. 4B) of the flat rectangle (Mann-Whitney,
P 0.26). In general, cells on the south half of the
track were just as likely to maintain the same firing field on the
track as were cells on the north half. Similarly, cells on the north
half were as likely to change their firing properties as were cells on
the south half. For example, cells 3 and 13 of Fig. 2 had place fields on the north section of the track only during the tilted session (although, interestingly, they both maintained weak remnants of the new
field in the flat 2 session), whereas cell 6 had an
identical place field at the south side of the track in all three
sessions. It is thus more likely that the change in place fields
reflects a remapping of the rectangular surface rather than an inherent three-dimensional structure to place fields.
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When the flat track was tilted to the 45° angle, the raised side of the track was no longer in exactly the same x-y coordinates in the frame of reference of the room; rather, the south side was moved closer to the north side (although in the track frame of reference, of course, the 2 sides were as far apart as when the track was flat). Another possible interpretation of the data, therefore, is that the correlations between fields in the flat and tilted tracks were reduced because the place fields were bound to the precise x-y coordinate frame of the room rather than to the local coordinate frame of the track. It was not possible to answer this question quantitatively, however, due to the small number of cells that did not remap on the long sides of the track. Nonetheless, visual inspection of the data suggests that such an interpretation would not adequately describe the results.
Stackman et al. (2000) demonstrated that 11/13 head
direction cells increased their peak firing rates when the animal moved around an elevated annulus compared with when the animal moved around
the floor of an apparatus. To determine if place cells changed firing
similarly in response to the elevation of the track, the peak firing
rates of the nine cells with similar place fields on the south (raised)
side of the track on both the flat 1 and tilt
sessions were analyzed. Of these cells, four increased their peak
firing rate (by a factor of 1.23-6.33) when the south side was raised
and five decreased their peak firing rate (by a factor of 1.26-10.2).
Thus no consistent effect of raising the platform on the peak firing
rates of individual place fields was observed.
Experiment 2: 180° rotations
Many previous studies have indicated that place cells tend to be
more strongly influenced by distal cues than by intramaze cues
(Cressant et al. 1997; O'Keefe and Conway
1978
; O'Keefe and Speakman 1987
; but see
Shapiro et al. 1997
). The four rats of group
2 were tested under conditions in which the flat and tilted rectangles were rotated 180° to test whether the three-dimensional orientation of the track would affect how strongly the fields were
bound to the distal cues.
Figure 5 shows the results from 12 of 23 neurons recorded from rat 109 during this set of
manipulations. When the flat rectangle was rotated 180° between
sessions, most cells had similar fields bound to the room cues,
corresponding to previous reports, even though the track had salient
local cues that broke the symmetry (the most prominent being the
support-arm that raised the track to the tilted positions, which the
rats often investigated during the sessions). When the tilted rectangle
was rotated, the results were very different. A number of cells
maintained their place fields relative to the room cues, ignoring the
z axis (Fig. 5A). For example, cell 1 fired on
the southeast corner of the track regardless of whether this was the
raised corner or the lower corner in the rotated condition. Other cells
appeared to maintain the same fields relative to a track-based
coordinate frame, in that the fields rotated 180° with the track
(Fig. 5B). For most cells, the place fields changed
unpredictably between the two conditions (Fig. 5C). Note
that, similar to experiment 1, some cells maintained
vestiges of the remapped fields from the tilted track when the rat was
returned to the flat track for the final session (see also
Muller and Kubie 1987; Sharp et al.
1990
). This was not due to poor isolation of the units as care
was taken to exclude those cells that were poorly isolated or had
unstable spike waveforms, and such effects were seen in some of the
most well-isolated cells in the sample. Thus the changes in the place fields caused by the partial remapping of the tilted track caused changes to the subsequent representation of the flat track, although the representations of the flat 1 and flat 3 tracks were still highly correlated [mean correlation flat
1-flat 2 = 0.74 ± 0.06 (SE); flat 1-flat
3 = 0.62 ± 0.06; Mann-Whitney U, P
0.051].
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Figure 6 shows the sample distributions
(left) and the simulated distributions (right)
for the correlations between the first and second flat rectangle
sessions in the room-based coordinate frame (Fig. 6, A and
B) and in the track-based coordinate frame (Fig. 6,
C and D). The sample distributions for both flat
rectangles were highly significantly different from the simulated
population distributions (Mann-Whitney, P < 0.000001 for both). Because the great majority of cells maintained the same
field relative to the distal laboratory cues, almost all correlations
were high in the room-based comparison and uniformly low in the
track-based comparison. Figure 7 shows
the same analysis for the tilted rectangle. For the room-based
correlations (Fig. 7, A and B), the sample distribution was significantly different from the simulated population (Mann-Whitney, P 0.026). Although most cells in the
sample had low correlations between the tilted rectangle and the 180°
rotated tilted rectangle, there were more cells with high correlations than expected by chance if the two maps were completely independent. Thus it is likely that there was a partial remapping of the tilted rectangle in the room-based coordinate frame. There was no difference between the sample distribution and the simulated population
distribution for the track-based correlations (Fig. 7, C and
D; Mann-Whitney, P
0.77), indicating that
the number of cells with apparent track-based firing (e.g., Fig.
5B) did not exceed that predicted by completely random
remapping.
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Because the preceding analysis was performed with the combined cells from four rats (1 recording sequence per rat), it is possible that no individual rat created a partially independent map between the two tilted rectangles; rather, some rats might have remapped the tilted rectangle completely while other rats maintained the same map in room coordinates. To test for partial remapping in individual rats, the same analysis was performed on the cells from each data set. No rat demonstrated a statistically significant difference from the expected distribution for complete remapping for either the room-based or the track-based correlations for the tilted rectangle (Fig. 8). It is clear from Fig. 8, however, that all of the rats displayed remapping in that the majority of cells from each data set had low correlations. Because the larger, pooled sample was significantly different from an independent remapping, partial remapping must have occurred in at least one of the four rats (most likely rats 109 and 114), and the lack of significance in the individual data sets was most likely due to the small sample size of each individual data set.
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Experiment 3: 90° rotations
Figure 9 shows the firing patterns
of 5 of 16 cells from rat 111 when the flat and tilted
rectangles were rotated 90°. When the flat rectangle was rotated,
most cells changed their firing properties by either becoming silent,
gaining a field, or changing a field (e.g., cells 2-5). Some cells,
however, maintained the same location in the room-based coordinate
frame (e.g., cell 1 and 1 of the fields of cell 4); that is, cells that
fired on the long arm of the track in the standard condition fired in
approximately the same location on the short arm in the rotated
condition (note that, because of the rotation of the anisotropic
rectangular track, these place fields were not in precisely the same
location in the room-based coordinate frame). When the tilted track was
rotated, some cells changed their firing fields unpredictably (e.g.,
cells 1, 2, 4, and 5), whereas other cells maintained the same field either in the track-based reference frame (e.g., cell 3) or in the
room-based reference frame (no examples from this particular data set).
To test for the significance of those cells that maintained their
firing fields, the same analysis of partial remapping that was
performed on the 180° rotation results was performed on these data
(Figs. 10 and
11). Notice that the effects of the
90° rotation of the flat rectangle (Fig. 10) were rather different
from those of the 180° rotation of the flat rectangle (Fig. 6). The
correlations between the standard and the 90° rotated flat rectangles
were on average low in both room- and track-based coordinates. Thus the
90° rotation, which approximately swapped the locations of the short
and long sides of the rectangle, caused a remapping of the rectangle.
Figure 10, A and B, shows that the remapping was
partial in the room-based reference frame as more cells have a high
correlation in this frame than expected by chance for a full remapping.
For the track-based reference frame, the distribution of correlations
was not different from the simulated distribution, suggesting that any
cell that apparently maintained the same field in track-based
coordinates did so by chance. For the tilted rectangle, there was a
trend toward partial remapping in the track-based reference frame (Fig.
11, C and D), although this missed statistical significance (P 0.07). There was no evidence for
partial remapping in the room-based reference frame (Fig. 11,
A and B). Overall it appears that the hippocampus
tended to partially remap the flat rectangle when it was rotated 90°
with a small but significant fraction of the cells maintaining their
fields in approximately room-based coordinates. (Note that in the
90°-rotated sessions, the starting point of the rat was on the same
location in the track reference frame but 90° rotated in the room
reference frame in contrast to the 180° rotation experiment;
see METHODS.) Additionally, there was another partial
remapping of these representations when the normal and 90°-rotated
rectangles were tilted (as in experiment 1), as many cells
maintained these fields on the track, whereas other cells changed their
spatial tuning properties. For example, cell 1 of Fig. 9 had the same
field in both flat 1 and tilt 1, whereas cell 2 had different fields. Similarly, cell 3 had the same field in both
flat 2 and tilt 2, whereas cell 2 had different fields.
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DISCUSSION |
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Place cells are sensitive to the three-dimensional geometry of surfaces
HD cells reflect head direction in the yaw axis and are
insensitive to changes in direction in the pitch and roll axes
(Stackman et al. 2000; Taube et al.
1990b
). The present study was designed to test whether the
spatial tuning of place cells extended into the z axis or
whether place cells (like HD cells) were insensitive to a change in
position in this axis. A recent model (Samsonovich and
McNaughton 1997
; see also Zhang 1996
) proposed
that self-motion information about speed and distance traveled, coupled
with heading direction from HD cells, were the primary inputs that
updated place cells; external landmarks acquired, through learning, a role in correcting for the cumulative error that is inherent in such a
system. Because the HD cells cannot distinguish between forward motion
in the horizontal plane from forward motion in an oblique plane, it was
possible that place cells would remain bound to the surface of the
track when it was tilted 45°. Alternatively, because the
three-dimensional manipulations of the track placed the rat in
different locations in three-dimensional space, it was possible that
the concomitant changes in the sensory input available at each location
on the track would cause the cells to change firing in predictable
ways. Because of the partial remapping phenomenon that occurred,
however, the results do not fit cleanly with either possibility.
Although this study demonstrates for the first time that the
representation of an environment in area CA1 is sensitive to
three-dimensional manipulations of the recording track (unlike HD
cells) (Stackman et al. 2000
), the results provide no
evidence that individual place fields are inherently three dimensional
as the changes in the place fields were not consistent with any of the
predictions based on a three-dimensional model of individual place
fields. Nonetheless the partial remapping makes it unwarranted to
conclude that the place fields on the track were two dimensional.
Rather the environmental manipulation of tilting the track may have
caused changes to the input into the hippocampus (e.g., changes in the
sensory input, in the rat's behavior, or in internal states such as
stress level), and attractor dynamics of the hippocampal network may
have caused the cells to respond to the altered input in a complex,
nonlinear fashion.
It is possible that these cells would have demonstrated the predicted
effects of a two- or three-dimensional model of individual place fields
had the remapping phenomenon not occurred. Although changes in certain
local cues have been demonstrated to cause remapping (Shapiro et
al. 1997; Tanila et al. 1997
), not all
environmental changes do so, and it was not obvious a priori whether
the three-dimensional manipulations of the track would provoke the
remapping phenomenon. A convincing answer to the question may require a
well-explored environment where the animal can move in a
three-dimensional volume without the need for experimental manipulation
(e.g., a jungle-gym apparatus) (Grobety and Schenk
1992
). Logistical concerns, such as the tangling of a recording
cable, would make such an experiment difficult to execute, although the
development of multi-channel telemetry systems would make this feasible
(Hawley et al. 1999
). Other situations, in which an
animal moves along different surfaces in the z axis, might
be subject to ambiguous interpretations similar to the present study.
For example, the hippocampus may encode each plane of a
three-dimensional "stacked" maze as independent two-dimensional
surfaces; thus a cell that fires on a single plane would not
necessarily demonstrate that the individual place fields are three
dimensional. It appears that a number of experiments producing
converging evidence will be required to answer this question
satisfactorily. Nevertheless although our initial attempt to address
this question is incomplete, the results demonstrate a sensitivity to
three-dimensional manipulations at the level of population
representations, and they reveal a number of important observations on
the nature of hippocampal representations in terms of the relative
influences of local versus distal cues and the remapping phenomenon.
Local cues versus distal landmarks
Just as the Morris water maze task demonstrated that animals can
solve spatial tasks without the use of local markers (Morris et
al. 1982), most early experiments on place cells reinforced the
notion of the predominance of distal landmarks over local surface cues.
In these experiments, if the set of distal landmarks and the recording
apparatus were rotated relative to each other, the place fields of
hippocampal neurons would usually remain bound to the distal landmarks
(Kubie and Ranck 1983
; O'Keefe 1976
;
O'Keefe and Speakman 1987
). Similarly, rotation of a
salient cue card on the wall of a recording apparatus controlled place
field location preferentially over local cues on the floor
(Muller and Kubie 1987
). Although the cue card can be
considered a local apparatus cue, its salience in the otherwise
sensory-poor environment and its location at the edge of the apparatus
may have endowed it with strong control over the place cells. Support
for the influence of both of these factors comes from a number of
studies. In the absence of visual input, subtle surface cues (such as
olfactory markings) are the most salient cues available, and rotation
of the apparatus will often cause the fields to rotate (Hill and Best 1981
; see also Young et al. 1994
). It is
likely that these local cues play a role in the ability of place cells
(Markus et al. 1994
; Quirk et al. 1990
)
and HD cells (Knierim et al. 1998
; Taube et al.
1990b
) to maintain stable place fields/direction preferences
for many minutes in complete darkness. The importance of the
controlling cue being at the edge of the apparatus was demonstrated by
Cressant et al. (1997)
, who showed that rotation of a
set of objects located near the middle of a recording apparatus had
little effect on the firing locations of place cells, whereas rotation
of the same objects located at the walls of the apparatus caused the
place fields to rotate by the same amount.
An important set of studies by Shapiro, Tanila, and Eichenbaum
(Shapiro et al. 1997; Tanila et al. 1997
)
demonstrated recently that local surface cues can have a much greater
influence over place cells than previously appreciated even in the
presence of salient distal landmarks. Distinctive textures and odors
were placed on each arm of a four-arm maze in an attempt to match the salience of the local cues to that of the distal cues. Under these conditions, when the local cues were rotated relative to the distal cues, some cells followed the local cues, some followed the distal cues, and some completely changed their firing properties (remapped). The present results are very similar, showing that the
three-dimensional orientation of a behavioral apparatus is a salient
local cue that is strong enough to have a profound influence over place
cells in the presence of salient distal cues. Regardless of whether the
difference between rotations of the flat and tilted rectangles (Figs. 6
and 7) is due to changes in the visual input caused by the
three-dimensional reorientation of the track, changes in behavior (e.g., different locomotor patterns), or other factors, these results
demonstrate clearly how a change in the local cue environment can
affect place cells.
One difference between the present study and that of Tanila et
al. (1997) relates to the question of whether the intramaze cues can actually control the firing of one subset of place cells at
the same time that another subset is controlled by the distal cues.
Although a casual visual inspection of the place fields in the present
study suggested that this dual control occurred, statistical analyses
could not rule out the possibility that the apparent examples of
track-based control of the fields were the results of random chance. In
addition, in the one experiment in which the binding of the place
fields to track-based cues approached significance (the 90° rotation
of the tilted track), the number of cells bound to the room cues was
not significant (Fig. 11). Two data sets from young adult rats of the
Tanila et al. (1997)
study had fields that rotated with
the local cues while simultaneously recorded fields rotated with the
distal cues. Because of this low number, it is not known whether the
difference between the two studies is due to chance duplication of
apparently local-cue-bound fields in the Tanila et al. study or to a
lack of statistical power to reveal small but significant binding to
local cues in the present study. This issue has important implications
as to whether hippocampus circuitry displays attractor dynamics that would tend to suppress such split-control of the place cells. In
support of the conclusions of Tanila et al. (1997)
, a
greater number of their data sets (7) contained place fields that did not change their spatial locations after the double rotation of the
local and distal cues (i.e., they were bound either to uncontrolled background cues or to idiothetic cues) while simultaneously recorded fields were controlled by local or distal cues. This increased number
supports the possibility that this dual control can occur at a level
greater than expected by chance, but it is important for future studies
to test statistically whether this dual control occurs.
It is also interesting that a number of the cells that appeared bound
to the room-based reference frame in the present study (e.g., Fig. 5,
cell 1) fired in slightly different locations in x-y room
coordinates because of the varying two- and three-dimensional orientations of the track. This result, similar to the hysteresis of
place fields demonstrated by Rettenmaier et al. (1999)
on a three-arm maze, suggests that the distal cues may be involved in
setting the global orientation of the hippocampal representation of an
environment, but that salient local cues, idiothetic cues, or
behavioral variables may be equally or more important for determining the precise location of individual place fields (O'Keefe and
Nadel 1978
).
Local cues, distal cues, and partial remapping
Early studies of the hippocampal remapping phenomenon were based
on recording sessions in which typically one neuron was recorded at a
time, thus making it impossible to determine whether remapping was an
"all-or-none" phenomenon or whether it could be partial (e.g.,
Muller and Kubie 1987; see also following text). Based on recordings over multiple sessions, Bostock et al.
(1991)
suggested that the process was always all or none.
Subsequent studies suggested that remapping may be partial
(Knierim et al. 1995
; Markus et al. 1995
;
Tanila et al. 1997
; see also O'Keefe and
Speakman 1987
), but the limited number of simultaneously
recorded cells made this suggestion difficult to test statistically.
The simultaneous recording in one study of head direction cells that
remained bound to the stable place fields, while other place cells
remapped, suggested strongly that remapping could be partial
(Knierim et al. 1995
), but this was not verified
statistically. By recording many place cells simultaneously and
comparing the results of individual recording sessions with a simulated
distribution of complete remapping, Skaggs and McNaughton
(1998)
proved that remapping can be partial. The results of the
present experiment provide another strong demonstration of partial remapping.
Muller and Kubie (1987) described a phenomenon in which
placing a barrier in the middle of a place field caused the field to be
altered, whereas placing the barrier in another part of the environment
had no effect on the field. Muller et al. (1996)
later
referred to this effect as partial remapping. This result, in which a
local perturbation of the environment apparently affected only place
fields in that local area, is similar in flavor to the description of
"misplace" cells by O'Keefe (1976)
. The partial remapping described in the present and previous studies (Knierim et al. 1995
; Skaggs and McNaughton 1998
;
Tanila et al. 1997
) is more global in nature as the
remapping occurs in all parts of the environment. It may be useful to
distinguish these types of remapping by the use of the term local
remapping to refer to effects similar to that seen by Muller and
Kubie and the term partial remapping to refer to the graded
nature of incomplete global remapping demonstrated here.
The causes and functional significance of hippocampal remapping are not
known. Remapping may be the result of an orthogonalization operation on
the input into the hippocampus, such that the subsequent representations stored in the CA3 and CA1 fields are less subject to
errors in storage or retrieval (Marr 1971;
McNaughton 1989
; Rolls 1989
). The
hypothesized pattern completion functions of the CA3 network cause this
orthogonalization function to be sigmoidal (McClelland and
Goddard 1996
). That is, when two input patterns differ only
slightly, the CA3 network will tend to generalize the inputs and make
the output patterns more similar than the inputs. As the input patterns
become more dissimilar, however, the outputs are made even more
independent (orthogonal) than the inputs. Partial remapping may reflect
the rising portion of the sigmoidal curve between input pattern overlap
and output pattern overlap (McClelland and Goddard 1996
)
where a moderate amount of input pattern similarity causes the output
patterns to be only partially orthogonal.
Another view of partial remapping, not necessarily inconsistent with
the preceding view, is that partial remapping reflects the differential
sensitivity of place cells to different subsets of cues in the
environment. In this view, cells that do not remap but instead are
bound to one set of cues (e.g., distal cues) are interpreted as
encoding those cues, whereas cells that remap are interpreted as having
encoded a unique combination of cues that has been disrupted by the
manipulation that provoked the remapping. Shapiro et al.
(1997) have suggested further that a change in control from
distal to local cues may reflect a dynamic switching of the inputs into
the hippocampus as one set of inputs actively inhibits the other set in
a winner-take-all type of mechanism.
Because the strongest input onto individual place cells most likely
comes from many other place cells, rather than from any cell that
directly represents sensory input, another possibility is that place
cells are always influenced by some combination of multiple cues,
distal, local, or internal, to the animal. These inputs are presumably
modifiable and differ in their relative strengths, but changes in the
control of place cells by one type of cue over another may reflect the
nonlinear dynamics of an attractor circuitry within the hippocampus
itself rather than a modulation of the inputs. When different sets of
inputs are manipulated, the strong connections among the place cells in
an assembly can cause them to be controlled as a whole by whichever set
of cues is strongest at the moment without any change to the strength of the inputs themselves. Thus in a stable environment, both distal and
local cues may converge on a given place cell, but the distal cues may
have a stronger overall input to the network. When the distal and local
cues are then put in conflict with each other in a probe test, the
attractor circuitry may cause the cells to follow the stronger distal
cues; this does not indicate, however, that the cells were not encoding
the local cues as well in the initial stable configuration. Such a
probe test can change the synaptic weights of the network, however,
which may cause the system to behave differently when the probe test is
repeated at a later time. For example, the probe test may cause changes
in the synaptic matrix such that on the next probe test, the attractor circuitry causes the cell to follow the local cues, even though in the
standard configuration the cell "encoded" both local and distal
cues. Remapping may occur when the synaptic changes induced by probe
tests become prevalent enough to alter the attractor basins in the
network, which may explain the observations that remapping often
becomes more likely after many repetitions of a given probe test
(Shapiro et al. 1997; Sharp et al. 1995
).
Because it is easier to manipulate experimentally the representations of the inputs (by manipulating the cues themselves) than the internal dynamics of the network, it will require a combination of increasingly accurate models of hippocampal function and network architecture, together with a major increase in our currently scant understanding of
the properties of the inputs into the hippocampus, to resolve these
important issues underlying the nature of information processing and
representations in the hippocampus.
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ACKNOWLEDGMENTS |
---|
We thank K. Dillon, S. Roberts, and R. D'Monte for technical assistance; C. Stengel, V. Pawlowski, and D. Wellington for engineering and computer support; and Drs. Matt Wilson and Bill Skaggs for some of the data analysis software.
This work was supported by National Institute of Neurological Disorders and Stroke Grants NS-33471 and NS-20331, National Aeronautics and Space Administration Grant NAG 2-949, and Office of Naval Research Grant N00014-98-1-0180.
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FOOTNOTES |
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Address for reprint requests: J. J. Knierim, Dept. of Neurobiology and Anatomy, University of Texas-Houston Medical School, PO Box 20708, Houston, TX 77225 (E-mail: james.j.knierim{at}uth.tmc.edu).
Received 16 June 2000; accepted in final form 21 September 2000.
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REFERENCES |
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