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The Journal of Neuroscience, October 15, 1998, 18(20):8455-8466
Spatial Firing Properties of Hippocampal CA1 Populations in an
Environment Containing Two Visually Identical Regions
William E.
Skaggs and
Bruce L.
McNaughton
Arizona Research Laboratories, Division of Neural Systems, Memory
and Aging, University of Arizona, Tucson, Arizona 85724
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ABSTRACT |
Populations of 10-39 CA1 pyramidal cells were recorded from four
rats foraging for food reward in an environment consisting of two
nearly identical boxes connected by a corridor. For each rat, a
higher-than-chance fraction of cells had similarly shaped spatial
firing fields in both boxes, but other cells had completely different
fields in the two boxes. The level of correlation of fields in the two
boxes differed greatly across rats and, for three of the four rats,
across recording sessions. Thus, the factors controlling the level of
correlation are likely to be subtle. Two control manipulations were
performed. First, the two boxes were physically interchanged. In no
case did firing fields move along with the boxes. Second, on the final
session of recording, the rat was started in the south box, after
having been started in the north box for every previous session. For at
least two of the four rats, the north fields from the previous session
were instantiated in the south during the first visit of the second session, but thereafter reverted. Thus neither differences between the
physical boxes nor sensory input from outside the apparatus could
account for the differences in firing fields: most likely they were
caused by a combination of learned expectations and a neural mechanism
for remembering movements. These findings could be explained either by
hypothesizing a more sophisticated attractor-map architecture than has
been proposed previously, or by hypothesizing that the hippocampus
conjunctively encodes both map information and some other type of
information.
Key words:
hippocampus; spatial representation; place cell; place
field; cognitive map; ensemble; navigation
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INTRODUCTION |
In many situations, pyramidal cells
in the rat hippocampus display place-dependent activity. A typical cell
will fire robustly whenever the rat enters a particular small portion
of the environment, and be virtually silent at other times. When
multiple cells are examined together, their place fields distribute, in
apparently a random way, across the entire environment. These findings
have provoked the idea that hippocampal population activity constitutes a "cognitive map" of the animal's spatial location (O'Keefe and Nadel, 1978 ). An extensive body of research over the past two decades
has aimed at defining the properties of these maps and the neural
mechanisms that give rise to them. [For pointers to the literature,
see McNaughton et al. (1996) and Wiener (1996).]
The most straightforward hypothesis would be that a cell fires when the
animal is in a given place because it is sensitive to some specific
combination of sensory features for example, the visual angle between
two landmarks (Zipser, 1985; McNaughton et al., 1991). It has gradually
become clear, however, that this type of explanation cannot be correct.
Switching off the lights while an animal is inside an environment does
not disrupt spatial firing, nor does removal of other sensory
modalities such as audition or olfaction. Only complete disorientation,
or strong cue-conflict, is capable of shifting place fields. Moreover,
the effects of cue-conflict are sometimes delayed, indicating that the
mapping system has an intrinsic dynamic stability (Gothard et al.,
1996). Also, bringing an animal twice into the same environment to
perform the same task can sometimes lead to the instantiation of
different, and apparently unrelated, hippocampal maps on the two
occasions (Barnes et al., 1997). To account for these properties, it
has been proposed that cognitive maps are stored as sets of dynamical attractors inside the hippocampal formation, and that the primary mechanism for shifting the internally represented spatial location is
the animal's integration of its own movements (a process generally called "path integration"), with learned sensory relationships coming into play as a secondary calibrating factor (McNaughton et al.,
1996; Samsonovich and McNaughton, 1997). On the basis of the available
evidence from the literature indicating that hippocampal maps may be
uncorrelated even for visually similar environments (Quirk et al.,
1992), Samsonovich and McNaughton (1997) made the assumption that the
hippocampal maps instantiated in any two situations either should be
identical or completely "orthogonal" (i.e., statistically
unrelated). In other words, if the hippocampus encodes pure spatial
coordinates, and the animal is "aware" that two environments,
although visually identical, are in fact different places, then the
hippocampal codes for the two environments should be orthogonal.
The experiment reported here was designed to examine the ability of the
hippocampus to form orthogonal representations of similar situations,
by using an environment containing two interconnected regions that were
made as nearly as possible identical. It was expected that the
hippocampal maps in the two regions would turn out to be completely
orthogonal, or if not, to be essentially identical. As it turned out,
the data did not accord with either prediction. The hippocampal maps
for the two identical regions were neither identical nor orthogonal but
rather partially overlapping. Furthermore, there were large and
reliable differences between individual subjects in the degree of
relatedness of the two maps. This article presents these findings and
discusses their theoretical significance.
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MATERIALS AND METHODS |
The surgical and electrophysiological techniques used in this
experiment have been described in detail in previous publications (Skaggs et al., 1996). Briefly, male Fischer-Brown Norway hybrid rats
(Harlan Sprague Dawley), ~9 months old, were implanted
stereotaxically, under Nembutal anesthesia, with chronic recording
microdrive arrays. Each array contained 14 independently adjustable
microdrives loaded with four-channel "tetrodes." Twelve of the
tetrodes were aimed at the CA1 cell body layer and used for unit
recording; one was positioned in the corpus callosum above the
hippocampus and used as a reference for differential recording, and the
final electrode was positioned near the level of the hippocampal
fissure and used to record EEG. The tetrodes were arranged in a
hexagonal lattice roughly 2 mm in diameter, and the center of the array
was positioned at coordinates 3.7 mm posterior, 2.0 mm lateral from
bregma. After recovery from surgery, the unit-recording tetrodes were
lowered gradually, over the course of several days, to the CA1 cell
body layer, which was recognized by standard electrophysiological
criteria. Under ideal conditions, a tetrode placed in the CA1 cell body layer can pick up distinguishable signals from as many as 20 pyramidal cells, which can be isolated from each other using a "stereo" principle based on the relative spike sizes on different channels of
the tetrode (McNaughton et al., 1983; O'Keefe and Recce, 1993). Thus,
in principle, an array of 12 tetrodes can yield well over 100 distinguishable pyramidal cells, but yields of 40-60 are more commonly
achieved. In this experiment, only cells that showed recognizable
activity inside the experimental apparatus were considered. Previous
studies have shown that in most cases approximately two-thirds of
hippocampal pyramidal cells are silent in a given behavioral paradigm;
these cells can be recognized by recording during slow-wave sleep
(Thompson and Best, 1989). Pyramidal cells were distinguished from
interneurons on the basis of spike waveforms and statistical properties
of the spike train; only units classified as pyramidal cells were used
in the data analysis.
For recording, a headstage was attached to the drive array, which was
connected to a cable leading to a commutator mounted in the ceiling of
the recording area. The headstage contained two sets of light-emitting
diodes, enabling position and head direction to be tracked using a
video camera, which also was mounted in the ceiling of the recording
room. Data acquisition was performed using eight 80486-based
microcomputers, running DataWave Discovery software (Longmont, CO) with
synchronized timestamp clocks. After each day's recording, the data
were transferred to Sun workstations for processing and analysis.
Apparatus and training procedure
The behavioral apparatus was designed to permit a rat to travel
between two regions that were as nearly as possible identical, both
visually and in terms of behavioral demands. It was also considered
important to ensure that the two regions were identically oriented and
to avoid disorienting the rats rotationally, so that the sense of
direction could not be used to distinguish the regions. The behavioral
protocol was designed to motivate the rats to move back and forth
between the two regions and repeatedly visit every part of each
region.
The rats were initially placed on a restricted-feeding regimen, and
after their weights had dropped to ~80% of baseline, they were
pretrained to forage for randomly scattered chocolate sprinkles inside
a 67 × 67 cm plywood box placed on a table at the center of a
room. Other than being square and opaque, this pretraining box had no
visual resemblance to the apparatus used in the actual experiment.
After recovery from surgery, the rats were given several more days of
pretraining, with the recording headstage and cable attached. This was
done to accustom the rats to the recording hardware and maximize the
likelihood that they would perform well the first time they were
introduced into the experimental apparatus.
The experimental apparatus consisted of two 58 × 61 cm wide by 61 cm high plywood boxes, painted flat gray, connected to each other by a
corridor (Fig. 1). The intent was that
the two boxes would be as nearly as possible visually identical. In
each box a trapezoidal doorway 4 cm wide at the bottom, broadening to
46 cm at the top, was cut in the center of one wall. A thin metal strip, used to improve the rigidity of the boxes, ran across the floor
of each doorway. Small battery-powered incandescent lights were mounted
at the center of the walls opposite the doorways, 54 cm above the floor
of the box. The lights were shielded by cut-out film canisters so that
the only illumination came through small rectangular holes, directed
downward toward the floor. Translucent white tape was placed over the
holes to reduce the light and prevent the formation of sharp shadows.
The boxes were open on the bottom, and the floor beneath them was
covered with brown wrapping paper, which was changed between recording
sessions, as described below. The apparatus was placed in a
sound-attenuated room with black walls, and the only light came from
the lights inside the maze. There was enough light in the room for a
human experimenter to see very dimly, but for a rat inside one of the
boxes, with the light shining down into his eyes, it is unlikely that
anything outside was visible.
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Figure 1.
Apparatus for the experiment. A, Floor
plan. The two boxes and corridor wall were all separate pieces, which
could be disassembled to exchange the boxes between sessions of an
experiment. Small downward-facing lights were mounted in the middle of
each wall opposite the doorways. B, Photograph of the
apparatus and the recording area in which it was located.
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The boxes were constructed so that the two of them, and a separate
piece forming the outer wall of the corridor, were held together by a
set of easily removable metal clips. It took 5-10 min to disassemble
the apparatus, move the boxes off to the side, replace the paper on the
floor, move the boxes back into position, and reconnect them. The two
boxes were marked with letters "A" and "B." Some sessions were
run with box A in the north (N) position and B in the south (S); others
were run with the two boxes reversed, as described in more detail
below.
During the first few days of recording, only a single session was
conducted per day, lasting as long as the rat would continue to search
for food. Once the duration approached 30 min (usually after 3-4 d),
the protocol was changed to two 12-15 min sessions per day, with the
floor paper replaced and boxes interchanged between sessions. The rat
was conveyed to and from the apparatus inside a small cardboard box,
nearly closed on top. Before and after the recording sessions, and
while the boxes were being interchanged, the rat was held in a large
cardboard box on a table ~5 feet east of the recording area. At the
beginning of each session the rat was picked up, placed inside the
transfer box, and carried to the two-box apparatus by one of the
experimenters, who in the process made a series of slow north-south
translational movements, to prevent the rat from determining his
starting location by integrating his motion with respect to the holding
box. Because it was considered important not to disrupt the rat's
sense of direction, the experimenter made an effort only to translate
the transfer box, not to rotate it. The transfer box was then placed on
the floor of the recording area, and the rat was released. In every
case but one, the rat was started on the N side of the two-box
apparatus. This was true both when there was one session and when there
were two sessions in a day, with the sole exception of the final day of
recording (described below). The physical box (A or B) that was
initially located on the N side was alternated from day to day. When
two sessions were conducted, the A and B boxes were exchanged between sessions.
An assistant was inside the room with the rat while the recording
sessions were conducted, and the experimenter was in an adjoining room
monitoring the computers, occasionally giving instructions over an
intercom. Before the rat was initially released, a small handful of
chocolate sprinkles was scattered diffusely across the N box. The
assistant in the room mentally divided the box into a 3 × 3 grid,
and the rat was required, in the judgement of the assistant, to visit
every sector, at which time she scattered food on the opposite side.
The purpose of this was to ensure that the rat would spend a
substantial amount of time, and sample each part of the box, on each
visit. Except during the initial period in the N box, the rat was free
at all times to pass through the corridor at will, but no additional
food was dropped until he had visited every ninth part of the currently
active box. The sound of chocolate sprinkles dropping on paper was
easily audible and usually caused the rat to run immediately to the
opposite box. During the recording session, the assistant inside the
room supported the recording cable by hand, as nearly as possible
directly above the rat, so that the pull of the cable would not provide a directional cue to distinguish between the N and S boxes. The cable
was always kept slack, so that the motions of the rat would not be
guided by the assistant. The assistant wore dark clothing and shifted
her position north-southward in a quasi-random way along the west side
of the apparatus so that she did not provide a reliable distinguishing
cue. In any case, with the box lights in between shining down into
their eyes, it was unlikely that the rats could see her, and they gave
no obvious sign of being aware of her presence, except at the end of a
session when she moved around to the east side of the apparatus to pick
them up.
The first rat of the group quickly developed a habit of running
immediately through the corridor to the S box. Because this would
interfere with the test planned for the final day of recording, a small
modification was made in the procedure, beginning on the sixth day: a
brick was initially placed in the doorway, to prevent the rat from
passing through it. After the rat had spent ~1 min inside the N box,
the brick was removed; all subsequent sessions for this rat were
conducted this way. Rat 2, however, when treated the same way, climbed
over the brick, so it was replaced on his fifth day with a large white
cylindrical plastic jar, and all subsequent sessions for this rat and
the remaining two rats were conducted this way. The brick or jar were
present only during the first visit to the initial box. For the
remainder of the session, the rat was free to move at will between
boxes. Removing the brick or jar from the doorway caused no apparent
changes in the pattern of hippocampal cell activity.
On the final day of recording, a special probe session was conducted.
The first session of the day was conducted as usual; the boxes were
disassembled and the floor paper was replaced, but then, contrary to
the previous procedure, the boxes were reassembled in the same
locations they had occupied during the first session. During the second
(probe) session, the rat was placed initially on the S side of the
apparatus, rather than being placed initially on the N side as in every
previous session. In every other respect, the procedure for the probe
session was as usual.
Data analysis
Correlation analysis. A major part of the analysis
consisted of interpreting correlations between firing rate maps. For
this purpose, a 64 × 64 pixel firing rate map was first
calculated for the entire environment, and then 14 × 14 pixel
portions were extracted for the regions corresponding to the N and S
boxes. These sub-maps could then be compared using Pearson correlation coefficients. Pixels having zero occupancy in either box (and hence an
undefined firing rate) were omitted from the calculation (these were
rare). Because correlation coefficients become very noisy when firing
rates are very low, for most analyses the cells were required to have
spatial firing rates exceeding 1 Hz at some point in both boxes to be
included.
The 64 × 64 pixel firing rate maps were constructed using an
"adaptive smoothing" method that has been described in previous publications (Skaggs et al., 1996). Briefly, the method is designed to
optimize the tradeoff between blurring error (attributable to averaging
together data from locations with different true firing rates) and
sampling error (the statistical error attributable to the limited
number of samples available). To calculate the firing rate at a given
point, a circle centered on the point is gradually expanded until the
following criterion is met:
|
(1)
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where  is a constant, r is the radius of the
circle in pixels, n is the number of 50-msec-long occupancy
samples lying within the circle, and s is the total number
of spikes contained in those occupancy samples. Once this criterion was
met, the firing rate assigned to the point was equal to s/n.
For this experiment, was set to the value 1000.
In data sets composed of a single session, correlations between the
north and south firing fields (denoted N-S) were calculated for each
pyramidal cell. When there were two sessions, six types of correlation
could be calculated, denoted N1-N2, N1-S1, N1-S2, S1-N2, S1-S2,
and S1-S2, where for example N1-S2 is the correlation between the
north firing rate map during session 1 and the south firing rate map
during session 2. For the probe session (in which the rat was
introduced to the apparatus inside the S box for the first time), two
special firing rate maps were calculated, denoted S2a (representing the
first period of time in the S box in session 2, lasting ~2 min) and
S2b (representing all remaining visits to the S box in session 2).
Comparisons of correlation distributions were performed using either
factorial ANOVAs, the nonparametric Kolmogorov-Smirnov test (Press et
al., 1992), or, for comparison of means, Student's t
test.
Trajectory reconstruction. To analyze the moment-to-moment
dynamics of population activity, a Bayesian method of trajectory reconstruction was used, as described by Zhang et al. (1998). This
method makes use of firing rate maps to infer the most likely location
of the rat from a brief sample of population activity and has been
shown to perform better than a number of other reconstruction techniques. For the current experiment, the method was used only where
data from two consecutive sessions were available: firing rate maps
constructed from the first session were used to reconstruct trajectories during the second session. Briefly, a 64 × 64 pixel firing rate map was constructed for each pyramidal cell, as described above, using data from the first session. The second session was split
into 1 sec intervals, and the number of spikes fired by each cell in
the population was counted for each interval. On the basis of these
spike counts, a probability was assigned to each location in the
environment using the Poisson-distribution-based formula:
![P(x)=<LIM><OP>∏</OP><LL>i</LL></LIM><FR><NU>[&lgr;<SUB>i</SUB>(x)]<SUP>n<SUB>i</SUB></SUP>e<SUP><UP>−</UP>&lgr;<SUB>i</SUB>(x)</SUP></NU><DE>n<SUB>i</SUB>!</DE></FR>,](/content/vol18/issue20/fulltext/8455/img002.gif)
|
(2)
|
where i indexes the cells in the population,
ni is the number of spikes emitted by cell
i, and  i(x) is the firing rate of cell i at location x. The reconstructed location
was then the value of x that made P(x) maximal.
To reduce the level of noise, each sample was required to have at least
three active cells, and at least 10 total spikes, to be included.
This technique was called the "Bayesian one-step" method by Zhang
et al. (1998). They also described a "Bayesian two-step" method
that produced more accurate reconstructions, but it relies on a
continuity constraint that would defeat the purpose for which the
analysis was used in the current experiment.
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RESULTS |
Data were obtained from four rats, beginning with the first
experience of each in the two-box environment. Rat 3, however, refused
to leave the starting (N) box during his first session. In his second
session, he went three times into the corridor but refused to enter the
S box. To encourage him to run, the next two sessions were conducted
without the recording headstage and cable attached; thus no data were
taken. Thereafter this rat proved to be comfortable enough for the
standard procedure to be followed. The other three rats moved back and
forth between the N and S boxes during the first session and all
subsequent sessions. The total number of recording days ranged from 9 to 12, and the number of usable cells per session ranged from 10 (worst
session for rat 4) to 39 (best session for rat 1). Because there were
clear individual differences between rats in the firing properties of cells (described below), data from each rat were analyzed separately. Data from four recording sessions were lost because of computer problems.
During the first few sessions, the behavior of the rats was erratic.
They would often leave a box after exploring only a portion of it.
Because no food was scattered on the opposite side until every ninth
part of the current box had been visited, the rats eventually learned
to scour the box in a more or less systematic way before leaving,
although they never became completely reliable about this. During the
first recording session, the number of corridor transits ranged from 7 (rat 1) to 12 (rat 2), with the exception of rat 3, who never left the
N box at all. The initial time spent in the N box before first leaving
it ranged from 2 min 25 sec (rat 2) to 9 min 55 sec (rat 1), again
excluding rat 3.
Figures 2 and
3 illustrate, for rats 1 and 2, the
spatial firing fields of 25 simultaneously recorded CA1 pyramidal
cells, in the first and second recording sessions of a single day.
Between sessions, the two physical boxes were interchanged. For rat 1 (Fig. 2), most firing fields were completely different in the N and S
boxes, but there were a few cases of similar fields. For rat 2 (Fig.
3), in contrast, most fields were similar on both sides, but there were
a few cases of strong difference, and most of these were maintained
across both sessions. Rats 3 and 4, in common with rat 2, showed a
majority of cells with symmetrical N-S fields, although the proportion
was not quite as large as for rat 2. As described quantitatively below,
this pattern of individual differences between rats was maintained
reliably over the entire course of recording.
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Figure 2.
Spatial firing plots for 25 simultaneously
recorded CA1 pyramidal cells from rat 1, during the first and second
sessions. The two boxes were interchanged between sessions. Light
gray represents the rat's trajectory; black points
represent the rat's location at moments when the cell spiked. For this
rat, the majority of cells showed distinct firing patterns in the N and
S boxes, but there were a significantly above-chance number of cases of
similar firing patterns (e.g., cells 2, 4, 12, 15, 19, 24, and 25).
There were occasional instances of fields appearing or disappearing
between sessions (e.g., cell 1), but no cases of fields switching sides
when the boxes were interchanged. This implies that the different
firing fields in N and S were not caused by differences in the physical
features of the two boxes.
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Figure 3.
Spatial firing plots for 25 simultaneously
recorded CA1 pyramidal cells from rat 2, during the first and second
sessions. For this rat, the majority of cells showed similar firing
patterns in the N and S boxes, but there were several instances of
clearly distinct firing patterns on the two sides. In most cases these
differences were maintained across sessions (e.g., cells 4, 7, 10, 20, and 25), although there were a few exceptions (e.g., cell 17). The
reliable maintenance of robust differences indicates that the
differences in this rat were not merely attributable to idiosyncracies
of sampling. The N-S firing patterns for rats 3 and 4 resembled those
for rat 2, albeit with a slightly higher level of differential N-S
activity.
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For each rat, at least 3 d of recording included two sessions of
12-15 min each, with the locations of boxes A and B interchanged between sessions. As illustrated by Figures 2 and 3, in no case did any
field that was confined to one side during the first session switch to
the corresponding location on the opposite side during the second
session; that is, no cell was tied to one of the physical boxes. There
were occasional instances of fields disappearing for the second
session, or appearing anew, but no instances of fields moving to the
opposite side. This was true for all four of the rats, although the
number of meaningful examples was relatively small for rats 2, 3, and
4, because of the overall symmetry of place fields between the two
sides in these rats.
Previous studies have indicated that place cell firing shows strong
head direction dependence when rats travel along stereotyped trajectories, but weak or nonexistent directionality when they move in
a nonstereotyped way in an open region of space (Markus et al., 1994;
Muller et al., 1994). In the current experiment, the apparatus
consisted of two open regions connected by a linear corridor. No
attempt was made to quantify directionality, but it was generally
observed that place cell activity was largely nondirectional inside the
two boxes, whereas in the corridor there was a mixture of directional
and non-directional fields, with numerous cells firing exclusively when
the rat passed through the place field in one of the two possible
directions.
The relations between N and S firing fields are described more
quantitatively in Figure 4. Figure
4A shows, for one late data set from each rat, the
distribution of correlations between N and S firing fields. Only cells
with spatial firing rates exceeding 1 Hz at some location on both sides
are included (see Materials and Methods). Figure 4A
also shows distributions generated by correlating N and S firing fields
taken from different cells, reflecting the distribution that would be
expected if the N and S fields were completely independent of each
other. For each rat, the observed distribution differed significantly
from the shuffled distribution (p < 0.005 for
each; Kolmogorov-Smirnov test). Thus, even for rat 1, the number of
symmetrical fields, although small, was significantly greater than
chance.
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Figure 4.
Relations between firing fields in the N and S
boxes. A, For each rat, the top plot shows the distribution
of N-S correlations across all cells recorded during a single session
on one of the later days. As a control, the distribution obtained by
taking N and S firing rate maps from different, randomly chosen cells
is shown below, reflecting the distribution that would be expected if
the N and S firing fields of a cell were unrelated. For each rat, the
observed distribution of N-S correlations differed significantly from
the mixed-cell control (p < 0.005;
Kolmogorov-Smirnov test). B, Distribution of N-S
correlations for the first recording session of every day, from each of
the four rats. Each point shows the N-S correlation of one cell, and
each vertical streak shows values from one session. The horizontal
coordinates are randomized slightly to make the points easier to
distinguish. For rat 1, the distributions from different sessions were
statistically indistinguishable. For rats 2, 3, and 4, in contrast,
there was significant variability across sessions, as shown by ANOVAs
(p < 0.01 for each; F test).
C, Mean levels of N-S correlation for the first and last
available recording sessions for each rat. For rats 1, 2, and 4, the
first session came from day 1 in the apparatus; for rat 3, it came from
day 5. The last session for each rat was session 1 of the day of the
probe session. There was no apparent tendency for the level of N-S
correlation to increase or decrease as a function of experience.
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An ANOVA on the distributions shown in Figure 4A
confirms that there were significant individual differences between
rats in the level of N-S correlation (p < 0.001; F test). Not only did the rats differ from each
other, but for three of them, there was significant variability across
days in the level of N-S correlation. Figure 4B
shows the distribution of N-S correlations for all usable recording
sessions (only the first session from any given day, however) from each
rat. The distributions for rats 2, 3, and 4 varied significantly
(p < 0.01 for each; F test), but the
distributions for rat 1 were statistically indistinguishable across
days. Despite this variability, there was no evidence for any gradual
increase or decrease in the levels of N-S correlation as a function of experience in the environment. Figure 4C shows the mean
level of N-S correlation for each rat on the first and last days of recording. There was not even a hint of a trend toward a difference. As
described in previous reports (Hill, 1978; Wilson and McNaughton, 1993), spatially specific firing was observed from the very first entry
of the rat into the environment. It was not possible to track
individual cells from day to day, but in terms of population statistics
there were no apparent changes as a function of experience.
To control for sensitivity to extra-maze cues, each rat on the final
day of recording was given a probe session in which, contrary to the
procedure on every previous session, the two boxes were reassembled for
the second session in the same locations rather than interchanged, and
the rat was started during the second session inside the S box. The
question was whether the rat's "expectation" that he would start
in the N box would be enough to cause the N hippocampal map to be
instantiated during the initial stay inside the S box. If so, this
would be evidence that the differences between the N and S maps were
not caused by sensitivity to extra-maze cues.
The data from the probe session were analyzed in three ways. First,
firing rate maps from the S2a subsession (the first stay inside the S
box during session 2) were correlated with the N and S firing rate maps
from session 1. For comparison, firing rate maps from the S2b
subsession (composed of all remaining visits to the S box during
session 2) were also correlated with the N and S firing rate maps from
session 1. Second, cells that showed clearly distinct spatial firing
patterns in the N and S boxes during session 1 were examined
individually to see whether their spatial firing patterns during the
S2a subsession more closely resembled the N or S patterns. Third, the
technique of Bayesian trajectory reconstruction was used to see whether
the rat's reconstructed position, during the initial stay in the S
box, better matched his actual position or the corresponding position
in the N box.
For rat 1 (with 30 pyramidal cells), the outcome of each analysis was
clear and unambiguous: the N1 map was instantiated during the S2a
subsession, and the session 1 maps were reinstantiated in both the N
and S boxes as soon as the rat first left the S box. As shown in Figure
5, the firing fields of cells during S2a correlated on average much better with their N fields during session 1 than with their S fields (p < 10 5; paired t test). For S2b, on the
other hand, the correlation was better with the S fields
(p < 0.005). Approximately 12 cells showed
clearly distinctive spatial patterns in the N and S boxes during
session 1, and without exception their firing patterns during S2a
matched N better than S, whereas the opposite was true for S2b; two
examples are shown in Figure 5B. As shown in Figure 5C, the reconstructed trajectory fell in the N box during
most of the S2a period, but reverted to match the rat's actual
location as soon as the rat passed through the corridor. During the S2a period, 87 samples of 1 sec each reconstructed to points in the N box,
and only 23 reconstructed to points in the S box.
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Figure 5.
Evidence for map shifting during the probe
session. A, Two examples of the behavior of individual cells
from rat 1. For each cell, spatial firing plots are shown for sessions
1, 2a, and 2b. In both cases (and this was typical), the plot for
session 2a resembles the N portion of the plot for session 1 much
better than the S portion, whereas the plot for session 2b closely
matches the plot for session 1. B, Trajectory
reconstructions for the first 5 min of the probe session, for rats 1, 2, and 3. In each plot, the horizontal coordinate represents time, and
the vertical coordinate represents the Y coordinate of the rat's
position, with the light gray line at the level of the wall
between the two boxes. The solid line represents the rat's
actual position, and the small rectangles represent positions
reconstructed from 1 sec samples of population activity, using firing
rate maps from the previous session as the basis for reconstruction.
For rats 1 and 3, the reconstructed locations during the initial stay
in the S box fell mostly into the N box, but as soon as the rat passed
through the corridor, the reconstructions reverted to mostly match the
rat's actual position. For rat 2, the reconstructions were at all
times distributed almost evenly between the N and S boxes, regardless
of the rat's actual position. Trajectory reconstruction was not
performed for rat 4 because of the small number of cells available.
C, Correlation plots of firing rate maps derived from the
S2a and S2b subsessions with maps for the same cells from the N and S
boxes in session 1. Each point represents one cell. The horizontal
coordinate is the correlation of the cell's N1 firing rate map with
the S2a map (top panel) or S2b map (bottom
panel). The vertical coordinate is the correlation of the
S1 map with the S2a map or S2b map. Thus, points lying below the
diagonal indicate greater resemblance to N1 than to S1. For all four
rats, the majority of points in the top plots lie below the diagonal,
indicating that the population representation during S2a aligned better
with N1 than with S1; however, the difference was statistically
significant only for rat 1 (p < 0.00001;
t test). Again for all four rats, the majority of points in
the bottom plots lie above the diagonal, indicating that the population
representation during S2b aligned better with S1 than with N1
(p < 0.01 for each; t test).
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For the other three rats the analysis was more problematic, because the
maps in the N and S boxes were so similar that it was difficult to tell
which one the pattern during S2a more closely resembled. For rat 3 (30 pyramidal cells), the evidence indicates that the outcome was the same
as for rat 1. First, the correlation of S2a with N1 was stronger than
the correlation of S2a with S1, although the difference was not
statistically significant in a t test. Second, only three
cells showed clearly distinct fields between N1 and S1, but each of
them showed an S2a field closely resembling the N1 field. Third, the
reconstructed trajectory during the S2a period fell mostly into the N
box, with 53 samples reconstructing to points in N and 30 to points in
S. For this rat, as for rat 1, the firing patterns during S2b reverted
to match the firing patterns during session 1.
For rat 2 (33 pyramidal cells), which had the most similar fields in N
and S, none of the three analyses led to any sort of strong conclusion.
The firing rate map correlations of S2a with N1 were on the whole
stronger than the correlations of S2a with S1, but the difference was
not statistically significant. There were four cells with distinctive
fields during session 1, and their behavior in S2a was ambiguous, with
one showing a firing pattern resembling its N1 field and the other
three more closely resembling their S1 fields. The trajectory analysis
was completely ambiguous, with 45 samples from S2a reconstructing to
points in the N box, and 48 to points in the S box. For rat 4, also, no strong conclusion could be drawn, mainly because of the small number of
cells in the data set (15 pyramidal cells).
In summary, then, the evidence indicates that two of the four rats
showed the N1 place field maps in the S box during the first visit of
session 2 and reverted back to the S1 maps as soon as they passed
through the doorway and, on looking down the corridor, presumably
learned that they had been started on the other side. The other two
rats may have done the same thing, but the data were not strong enough
to support this.
In light of recent theoretical ideas, an important question is whether
the observed partial symmetry of place fields across the two boxes
might be a result of confusion between what were actually orthogonal
maps. If there were actually two or more orthogonal place-field maps,
only one of which could be active at a time, but the visual similarity
of the two sides occasionally caused the system to instantiate the
"wrong" map, this would lead to the appearance of cells firing at
the same location in both boxes, as was observed. The data speak
against this explanation, but they do not definitively refute it.
First, the map-confusion hypothesis predicts that there should be
examples of cells whose activity overlapped spatially but not
temporally, that is, pairs of cells whose place fields overlapped spatially but did not fire spikes simultaneously. No examples of this
type were found. Figure
6A shows an
illustration of the general finding: when symmetric and asymmetric
cells had spatially overlapping fields, they always showed at least
some degree of temporally correlated activity, on a time scale of 10 msec or less.
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Figure 6.
Data relating to the question of multiple
interfering maps. A, Left, Spatial firing plots
for three simultaneously recorded cells from rat 1, two having
asymmetric firing fields (cells 1 and 3) and one having a symmetric
field (cell 2). Right, Temporal cross-correlation plots for
each pair of these three cells. Horizontal axis: seconds. Vertical
axis: counts. This example illustrates the general observation that
when symmetric and asymmetric fields overlapped spatially, the spike
trains of the cells also overlapped temporally, indicating that the
cells were unlikely to belong to separate, mutually exclusive maps.
B, Trajectory reconstructions for 10 min periods from rats
1, 2, and 3. See legend of Figure 5 for explanation. In this plot, the
times when the rat was inside the corridor are not shown. The
reconstructions are based on populations of 38, 32, and 31 cells,
respectively.
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|
Second, the map-confusion hypothesis predicts that when the Bayesian
technique is used to reconstruct the rat's location on the basis of
population activity samples, there should occasionally be periods of
time when the reconstructed location lies mostly in the opposite box
from the actual location, as occurred for rats 1 and 3 during the probe
session, described above. As illustrated in Figure 6B
for nonprobe sessions from three of the rats, there were of course
errors in reconstruction for all of the rats, particularly rat 2 (rat 4 was not even attempted). For rat 1 these consisted for the most part of
isolated samples, not concentrated in any particular part of the
environment. For rats 2 and 3, there were a number of clusters of
10-20 samples in which the position repeatedly reconstructed to the
"wrong" side. It is possible that these represented true failures
of the system to accurately represent the rat's location.
Alternatively, it is also possible that they were merely reconstruction
errors attributable to limited sampling and would go away if a larger
number of cells were available. Thus, the data do not rule out the
occurrence of genuine map-confusions for rats 2, 3, and 4, in which the
N and S maps were very similar, but such an explanation is unlikely to
hold for rat 1.
| |
DISCUSSION |
The line of thought that led to the current experiment originated
from a provocative study by Quirk et al. (1992), which examined the
spatial firing properties of neurons from the medial entorhinal cortex.
In that study, two types of apparatus were used: first, a gray cylinder
with a white cue card on the wall, and second, a similar-sized gray box
with one white wall. It was found that entorhinal cells showed similar
firing fields in the two environments, in contrast to an earlier study
using a similar procedure (Kubie and Ranck, 1983) in which hippocampal
place cells showed completely different firing patterns in the two
environments. The general interpretation of these findings was that the
hippocampal system transforms similar input representations into very
different internal representations, a so-called "orthogonalization"
process. The original aim of the current study was to gain a better
understanding of this orthogonalization process, by comparing
hippocampal and entorhinal representations of a pair of visually
identical but spatially separated regions, the expectation being that
the hippocampal representations would be orthogonal and the entorhinal
ones at least partially overlapping. As it turned out, the main result of the study was to demonstrate that hippocampal
"orthogonalization" is considerably less thorough and systematic
than has hitherto been supposed.
The current data show that when rats moved back and forth between two
environments that were similar both visually and in terms of behavioral
demands, the spatial representations activated in the CA1 region of the
hippocampus were neither identical nor completely distinct. Moreover,
there were large variations between different individual rats, and even
between different recording sessions from the same rat, in the degree
of similarity. Thus the factors controlling the similarity of spatial
firing patterns in the hippocampus are likely to be subtle and
ephemeral. These findings raise important questions about earlier
observations of nonorthogonality in entorhinal cortex (Quirk et al.,
1992) and subiculum (Sharp, 1997). In neither of these studies were hippocampal recordings included as part of the same experiment; rather,
comparisons were made with previous studies using similar types of
apparatus. Might it not be the case that entorhinal and subicular
correlations between environments are as variable as hippocampal
correlations? It would clarify the issue to replicate these experiments
while recording hippocampal units in exactly the same
paradigmideally, while recording simultaneously from both areas in
the same animals.
In the current study, two control manipulations were performed to test
the possibility that the differences between representations were
caused by physical differences between the two box areas. First, the
apparatus was dismantled between recording sessions and reassembled
with the two physical boxes interchanged. In every unambiguous case,
place fields stayed on the same side of the apparatus and failed to
follow the physical box in which they were first seen. Second, on the
final day of recording, each rat was placed, during the second
recording session, initially in the south box, after having been
started in the north box on all previous sessions. For two of the four
rats, it was clear that the north hippocampal map was instantiated
during the initial period in the south box, whereas the south map was
present during subsequent visits (after the rat had the chance to go
through the corridor and discover which box he had actually been
started in). For the other two rats, the north and south maps were too similar to make it possible to say for certain what happened. Taken
together, these results make it unlikely that the firing patterns were
controlled either by internal features that distinguished the two boxes
from each other or by external room cues that distinguished the north
region from the south region.
It is likely, then, that the differences between the north and south
maps resulted from a combination of the rat's expectations and a
mechanism for remembering the rat's movements through the corridor.
The word "expectations" means, concretely, a learned association of
the transfer box, or the act of being transferred, with the part of the
environment in which the rat was initially placed in every session
except the last. The mechanism for remembering movements could be a
full-scale path integration system, as has been shown by earlier
studies to exist in the rat (for review, see McNaughton et al., 1996),
but a less precise sort of memory would also be sufficient to account
for the present findings (e.g., "I just left the N box and turned
south so the one I'm entering must be the S box").
The data from this experiment provide compelling evidence that two
distinct hippocampal maps can overlap without being identical. This is
consistent with the findings of several previous studies. Markus et al.
(1995) found that, when rats were required to shift from random
foraging to directed running between specified points, even though no
physical feature of the apparatus changed, some place cells developed
new fields, but others, simultaneously recorded, kept the same fields.
Tanila et al. (1997), studying small ensembles of place cells on a plus
maze, found that when a rotational mismatch was created between local
and distal cues, the majority of fields rotated as a consistent
ensemble, but on average about 20% of fields either remapped randomly
or else rotated their fields in discordance from the majority. Numerous
other studies (e.g., Muller and Kubie, 1987; Shapiro et al., 1998) have
described different hippocampal cells responding differently to some
manipulation, but most do not impact on the issue in question, because
they did not record from multiple cells simultaneously. Without
simultaneous recordings, it is difficult to say whether a shift in
firing is caused by all cells shifting together or by individual cells
shifting differently from others.
There have been previous studies of place cells in symmetric
environments, but the symmetry was rotational [for example, a gray
cylinder with two diametrically opposing white cue cards (Sharp et al.,
1990)] rather than translational as in the current experiment. It may
well make a difference. The brain of the rat contains a "head
direction" system that is intimately connected, both anatomically and
functionally, with the hippocampus (Taube et al., 1990; Knierim et al.,
1995; Taube, 1995). The head direction representation is dynamically
stable, and only partially controlled by visual input, so it may be
able to disambiguate views that are visually identical but rotated with
respect to each other. With this in mind, it was considered important
in the current experiment to ensure that the two boxes were identically
oriented as well as visually identical, and to avoid disorienting the
rats rotationally.
The observation of partially overlapping maps is a challenge to the
theory that hippocampal maps are preconfigured in relation to the
path-integrator mechanism and bound to exteroceptive sensory cues only
as a product of learning (McNaughton et al., 1996; Samsonovich and
McNaughton, 1997). If this theory were correct, and different maps were
allocated for the N and S boxes, then there is no obvious reason why
they would have any more in common than any other two preconfigured
maps. If on the other hand the same map were allocated for both, there
is no obvious reason why some cells would show different fields in N
and S.
There are at least two possible ways of accounting for partial overlap.
First, it may be possible to alter the original "multichart" model
of Samsonovich and McNaughton (1997) into a model in which the charts
are nonorthogonal and selected in a nonrandom way, such that
similar-appearing environments predispose the system to allocate
similar charts. One specific possibility is a "hierarchical multichart" model in which the hippocampus contains a hierarchy of
maps, whose overlap depends on their relative locations in the
hierarchy. A hierarchical structuring of attractors has been shown to
exist in some simple neural network structures, including the Hopfield
model (Amit, 1989), and can be produced in the model of Samsonovich and
McNaughton (1997) by making modest changes in the structure of the
model (A. Samsonovich, personal communication).
Second, the primary "cognitive map" may lie outside the hippocampus
proper [perhaps in the subiculum (Sharp, 1997; Redish and Touretzky,
1997)], and hippocampal activity may be determined by a conjunction of
map information and other information. Figure 7 illustrates schematically how this
could work. Suppose the hippocampal network H receives input
from a map network M and a network C representing
other information (C stands for "context"). Each hippocampal unit receives input from one map unit and one context unit,
and fires only when both inputs are active. If the set of active
C units is fixed and unchanging, there is a one-to-one relationship between patterns in the M layer and patterns in
the H layer, so that the H units appear to form a
map. A change in the set of active C units would cause a
corresponding change in the set of active H units, even if
the set of active M units remained identical, resulting in
the appearance of a different hippocampal "map." If only a few
C units changed their activity, only a few H
units would change their relationship to the M units,
resulting in the appearance of partially overlapping hippocampal
maps.
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|
Figure 7.
Schematic illustration of the concept of
conjunctive coding. The idea is that each unit in the hippocampal layer
H is linked to one unit in the map layer M and
one unit in the context layer C. The hippocampal unit fires
if and only if both inputs are active. So long as the same set of units
remains active in the C layer, there is a fixed relationship
between patterns in M and patterns in H. A change
in the set of active C units will induce a correspondingly
large change in the relationship between M patterns and
H patterns. Thus, a small change in C will lead
to the appearance of "partial remapping" in H.
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|
In reality the hippocampal network is much more complicated than the
simplification portrayed in Figure 7, but the general notion of
orthogonalization by conjunctive coding is valid for a broad
range of architectures. In a more realistic scenario, in which each
hippocampal unit receives input indirectly from large groups of
M units and C units, a small change in the
C pattern would cause a perturbation of the observed
hippocampal map, whose size depends on the parameters of the network.
As the C pattern is changed more and more, at some level the
hippocampal map would become completely orthogonal to what it was
originally. The factors that influence this orthogonization process
have been studied computationally by O'Reilly and McClelland (1994)
and others (Marr, 1971; McNaughton, 1989).
Whatever the explanation is of partial remapping, the results of the
current experiment demonstrate that hippocampal activity is influenced
by subtle and changeable factors. Situations that are virtually
identical in all sensory and behavioral respects can be associated with
different hippocampal activity patterns, and it appears that the
pattern present at a given time may be determined at least in part by
an animal's expectations.
| |
FOOTNOTES |
Received April 16, 1998; revised July 23, 1998; accepted July 27, 1998.
This research was supported by National Institutes of Health Grant
NS20331 and the McDonnell and Pew Foundations. We thank Karen Reinke
for assistance in running experiments, Kathy Dillon, Keith Stengel, and
Vince Pawlowski for technical assistance, and Alexei Samsonovich for
helpful discussions.
Correspondence should be addressed to Dr. William Skaggs at his present
address: 446 Crawford Hall, Department of Neuroscience and Center for
the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA
15260.
| |
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Top
Abstract
Introduction
