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The Journal of Neuroscience, June 1, 2001, 21(11):3955-3967
Recognition Memory Correlates of Hippocampal Theta Cells
Sherman P.
Wiebe and
Ursula V.
Stäubli
Center for Neural Science, New York University, New York, New York
10003
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ABSTRACT |
Investigations of hippocampal theta cell activity have typically
involved behavioral tasks with modest cognitive demands. Recordings in
rats locomoting through space or engaged in simple stimulus
discrimination or conditioning have revealed some place specificity and
S+/S selectivity in addition to
the hippocampal EEG theta-related behavioral/motor
correlates. However, little data exist regarding theta cell
activity during performance of more cognitively demanding, hippocampal-dependent recognition memory tasks. Here, we examined the
cognitive firing correlates of theta cells in rats that were performing
an olfactory recognition memory task with distinct sample and test
phases. Discriminant analysis revealed odor and match/nonmatch memory
correlates in theta cell activity comparable in relative
magnitude to that of the principal cells. Odor-specific theta cell responses in the sample phase were restricted primarily to
CA1 and linked to task performance. In the test recognition phase,
match/nonmatch theta cells were found primarily in the CA3 and CA1
fields, most of which exhibited greater activity on correct nonmatch
trials in which recognition occurred than on error match trials in
which recognition failed. Odor selectivity of the match/nonmatch
signaling was greatest in the dentate gyrus (DG) and CA3 and least in
CA1. This inverted pattern of stimulus specificity in the sample versus
test phase was similar to that observed in principal cells but with a
greater contrast between the CA1 and DG/CA3 fields. Together, these
findings suggest that theta cells actively participate in hippocampal
recognition memory processing and play a specific role in shaping the
cognitive firing properties of the hippocampal principal cells.
Key words:
interneurons; theta cells; hippocampus; DNMS; odors; spatial; match/nonmatch discrimination; recognition memory; cognition; dynamic filtering; generalization; dentate gyrus; CA3; CA1; principal
cells
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INTRODUCTION |
The gross behavioral
correlates of hippocampal theta interneurons have been known for almost
three decades. Ranck's original description of theta cells (Ranck,
1973 ) focused on activity relating to movement and arousal and the
correlation with hippocampal slow-wave theta rhythm; hence the name
"theta cell." Most recording studies of theta cells since then have
involved tasks with minimal cognitive demands, typically with a rat
searching for randomly positioned food rewards in an open area or
moving through a maze or linear track. In these situations,
behavior/motor correlates (Ranck, 1973; O'Keefe and Nadel, 1978) have
been observed along with some modest place specificity (McNaughton et
al., 1983a; Kubie et al., 1990). A few studies have reported
learning-related theta cell firing correlates during simple perceptual
discrimination (Christian and Deadwyler, 1986; Eichenbaum et al., 1987)
and trace eyeblink conditioning (McEchron and Disterhoft, 1997);
however, little data exist describing theta cell
activity during performance of cognitively demanding,
hippocampal-dependent recognition memory tasks. Principal cells, and
not theta interneurons, have traditionally been the focus of
hippocampal recording studies of recognition memory. Recognition memory
tasks such as delayed-nonmatch-to-sample (DNMS) are represented in
hippocampal principal cell firing (Deadwyler et al., 1996; Wood et al.,
1999) and are sensitive to hippocampal lesions (Wood et al., 1993;
Alvarez et al., 1995; Hampson et al., 1999). Therefore, given the
prominent role that hippocampal interneurons play in modulating
principal cell population activity via feedforward (Buzsaki, 1984) and
feedback (Andersen et al., 1963, 1964) inhibition, the following
question arises: do hippocampal theta cells, like the principal cells,
represent information about nonspatial perceptual variables and higher
cognitive and mnemonic functions? And, if so, how do those
representations compare with that of the principal cells?
Hippocampal principal cells (pyramidal and dentate granule cells)
can be distinguished from theta interneurons in freely moving rats on
the basis of their electrophysiological properties. Hippocampal principal cells are known to encode both odors (Wiebe and
Stäubli, 1999; Wood et al., 1999) and match/nonmatch comparisons
(Otto and Eichenbaum, 1992; Rolls et al., 1993; Deadwyler et al., 1996; Wood et al., 1999) within the DNMS recognition memory task. Some evidence also exists for differential processing of stimulus events within the hippocampal subfields (Hess et al., 1995; Deadwyler and
Hampson, 1998). In a previous report of principal cell activity during
olfactory DNMS performance (Wiebe and Stäubli, 1999), an
inversely graded distribution of stimulus-specific responses was found
across the hippocampal subfields in the sample acquisition phase
(maximal in CA1, minimum in DG) compared with the recall phase (maximal
in DG, minimum in CA1). To investigate the perceptual and cognitive
firing correlates of theta cells and to compare them with that of
principal cells, we recorded hippocampal principal cells (Wiebe and
Stäubli, 1999) and theta interneurons in the DG, CA3, and
CA1 subfields in rats performing an odor-guided DNMS task with distinct
sample and test phases.
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MATERIALS AND METHODS |
A detailed description of the apparatus, behavioral training
protocol, surgery, and recording techniques has been included in a
previous study of hippocampal principal cell activity during DNMS
performance (Wiebe and Stäubli, 1999). Briefly, adult male Long
Evans rats (weight at time of surgery, 250-460 gm; n = 18; the same rats were used in the companion principal cell paper) were
water-deprived for 20-22 hr before DNMS performance but allowed ad libitum food. All animals were trained to stable DNMS
performance (>85% correct on 0-5 sec delays) before and after
electrode implantation. The apparatus was a sound-attenuating wooden
Y-shaped chamber [sample arm, 36 × 23 × 59 (length × width × height) cm; test arms, 27 × 14 × 59 cm;
central area, 33 × 23 × 59 cm] surrounded by an
electrically grounded copper mesh grid. Cylindrical nosepoke ports
(diameter, 20 mm) and water troughs were located at the end of each
arm, and photodetector-LED pairs were located at the entrance to each
arm to record behavioral events. A cue light positioned above the
sample port was illuminated during the sample and delay phases, and a
house light was lit during the test phase. Solenoid valves mounted
outside the chamber were used to deliver the odorized air (either Apple
Oliffac or Carenko; International Flavors and Fragrances, Inc., New
York, NY) at the end of each arm. Odorized airstream
concentration and flow rates at the end of each arm were controlled by
a flow-dilution olfactometer. Lingering odors were extracted from the
chamber by a ceiling fan and vacuum pump. Water rewards (0.05 ml) were
delivered using a gravity-feed system through a solenoid valve to
troughs located directly below the test-arm nosepoke devices. A
high-intensity flashbulb mounted on the ceiling of the chamber signaled
error responses. A computer with custom-designed digital
input-output interfaces controlled the apparatus.
Behavior
Animals were trained on the two-odor simultaneous DNMS task,
illustrated schematically in Figure
1A, as described in
Wiebe and Stäubli (1999). Illumination of a cue light above the
sample port marked the start of the trial. The first sample nosepoke commenced a 2 sec minimum pre-odor baseline period, after which a
nosepoke turned on the odor (either odor A or odor B). After a minimum
of 10 sec of odor exposure, a nosepoke terminated the odor and
initiated a variable 1-50 sec delay period. After the delay, a sample
poke extinguished the cue light, illuminated the ceiling house light,
and prompted the delivery of the two odors in the test arms, one odor
per arm. The rat exited the sample arm and then simultaneously
discriminated the two odors in the center region of the Y maze, just
outside the entry point of the test arms. On discrimination of the two
odors, the rat selected one of the odors by entering an arm and
committing a nosepoke. The test odors (one in each arm) emanated
continually from both test arms and could be detected within and just
outside the entry point of the arms, regardless of whether a nosepoke
was made in the arm. The distance between the test-arm entry point and
the infrared beam in the nosepoke device protruding from the end of the
test arm was short (24 cm, approximately the body length of the rat)
and was traversed rapidly by the water-deprived rats. The time between
arm entry and the nosepoke was an accurate measure of locomotion in the
test arms because the time span was short (mean, 0.920 sec, on average
for each rat) and varied little across trials (SEM, 0.009 sec). A
nosepoke in the nonmatch arm resulted in a 0.05 ml water reward. A
match response triggered a high-intensity flash discharge. By
definition, then, all nonmatch trials were correct trials, and all
match trials were error trials. Three seconds after both correct and
error responses, odor delivery to the test ports was terminated, the
house light was extinguished, and an intertrial interval of 20 sec was
imposed. The identity of the sample odor and location of the match and
nonmatch test odors were randomized across trials. Performance
diminished linearly as a function of delay from 86% correct at 0-5
sec delays to 74% correct at 45-50 sec delays. Figure
1B shows the mean performance curve per session
summed over all rats, with 100-250 trials per session.
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Figure 1.
A, Schematic diagram of odor-cued
DNMS task. A nosepoke in the sample arm was required to initiate the
trial with a minimum 2 sec pre-odor period, after which a sample poke
turned on the sample odor (either odor A or B). After 10 sec of odor
exposure, a nosepoke turned off the odor and initiated a variable 0-60
sec delay. The first poke after the delay interval turned off a cue
light above the sample port, turned on a house light, and prompted the
start of the test phase with the delivery of the two odors in the test
arms (one per arm). Infrared beams detected the rat's exit from the
sample arm, entry into the left and right test arms, and subsequent
nosepoke response. A nosepoke in the nonmatch arm resulted in water
reinforcement. A match nosepoke triggered the discharge of a light
flash. The water reward and light flash reinforcement signals were
delayed 1.5 sec on a select number of randomly interspersed trials to
determine whether correct/error-selective firing immediately after the
test nosepoke was associated with the behavioral execution of the
nosepoke or attributable to differential responding to the water
reward-light flash. Three seconds after the reinforcement signal, the
odors were terminated, the house light was extinguished, and an
intertrial interval of 20 sec was imposed. After the intertrial
interval, the cue light above the sample port was turned on again,
prompting the rat to execute a sample nosepoke to initiate another
trial. The identity of the sample odor and location of the match and
nonmatch test odors were randomized across trials. B,
Delay-dependent DNMS performance. Mean ± SEM percentage of
correct trials per recording session (100-250 trials) was averaged
over 435 sessions in 18 rats. Trials were grouped in 5 sec intervals
and plotted across the 1-50 sec delay period. Note that on the
x-axis, 5 implies 0-5 sec, 10 implies 5-10 sec, etc.
C, Histological verification of microwire placement.
Examples of electrode placement in the dentate gyrus
(DG, top), CA3 (center),
and CA1 (bottom) subfields. The
line in each image marks the CA3-CA1 boundary.
D, Discrimination of theta interneurons and principal
cells on the basis of extracellularly recorded physiological
parameters. Up to four neurons, principal cells, and/or interneurons
could be isolated per microwire channel using time-amplitude window
discrimination and template matching. Left, In the
example shown, two distinct units with well defined waveform
characteristics were discriminated from the same microelectrode.
Right, A linear cutoff in firing rate-spike
width space was used in conjunction with firing rhythmicity criteria to
discriminate principal cells from theta interneurons. Cells with mean
firing rates r (in Hertz) and negative-going spike
widths w (in microseconds) such that
r < 0.04 · w  3.5 (shaded region) and a peak at 3-5 msec in the
autocorrelogram followed by a fast exponential decay
(filled arrowhead) were classified as principal
cells and were analyzed previously in Wiebe and Stäubli (1999).
Cells with mean firing rates and negative-going spike widths such that
r > 0.04 · w 3.5 and a
peak in the 80-200 msec (5-12 Hz) range of the autocorrelogram
(open arrowhead) were classified as theta interneurons.
Marginal distributions of principal cell (filled
histogram) and interneuron (open histogram)
spike widths and mean firing rates are shown on top and
to the right of the plot, respectively (bin width, 20 µsec, 2.5 Hz). The interneuron population (firing rate, mean, 17.4 Hz; SEM, 1.13; min, 2.29; max, 91.93; negative-going spike width, mean,
206 µsec; SEM, 6; min, 100; max, 670; n = 139)
was statistically well separated in two-dimensional firing rate-spike
width space (MANOVA; F(2,1237) = 817;
p < 1010) from the principal
cell population (firing rate, mean, 1.1 Hz; SEM, 0.05; min, 0.001; max,
13.27; negative-going spike width, mean, 305 µsec; SEM, 3; min, 120;
max, 825; n = 1101). P-cells,
Principal cells; I-cells, interneurons.
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Although the rat could correct initial odor/arm selections in the test
phase by stopping after entering one arm, backing up, and then entering
the other arm, this postselection corrective behavior was observed on a
relatively small percentage of trials (6 ± 1% of the trials per
session; mean ± SEM averaged across all rats). This implies that
on most trials, the rats made the match/nonmatch decision in the test
phase while sampling the two odors simultaneously at the junction
between the two test arms, as opposed to selecting one particular odor
or arm in the test phase by default and then making a corrective
response if necessary. Therefore, the task was performed as
"delayed-nonmatch-to-sample" and not using alternative
response strategies such as "win-stay/lose-shift" involving
corrective responses after initial default choices.
The delayed-nonmatch-to-sample task by definition (Suzuki, 1996) is
comprised of three phases: (1) sample item presentation, followed by
(2) a delay interval, followed by (3) a recognition phase in which one
or more test items are presented, with reward resulting from selection
of the nonmatch item. Many rat hippocampal recording studies of
recognition memory implementing the DNMS paradigm have used the
continuous protocol (Otto and Eichenbaum, 1992; Wood et al.,
1999) in which only one item is presented in the test phase. Individual
stimuli are presented sequentially, one after another, with the animal
rewarded for recognizing an item as different from its antecedent. In
such a paradigm, stimuli are at once both samples for the following
item and test cues for the preceding item, thereby potentially
obscuring detection of any phase-sensitive coding. In the simultaneous
two-item DNMS task used here and by others (Mumby and Pinel,
1994; Deadwyler et al., 1996; Murray and Mishkin, 1998), two items (the
match cue and the nonmatch cue) are simultaneously presented to the animal in the test phase and continue to be present until the final
behavioral response is executed. In the Deadwyler and Mumby studies,
spatial cues and nonspatial, visual cues were used as discriminative
stimuli, respectively, with the selection response involving lever
presses and displacement of three-dimensional objects. In the present
study, odors were used as discriminative stimuli, and the behavioral
response was a nosepoke. An advantage of the simultaneous DNMS paradigm
that was used here, however, with spatially and temporally distinct
sample and test phases, was that comparisons could be made between the
response properties of cells to stimuli presented in the acquisition
versus recall phase of the task.
Surgery
After criterion behavioral DNMS performance was reached, animals
were surgically implanted with an 8 × 2 microwire (diameter, ~45 µm) electrode array (NB Labs, Denison, TX). To help eliminate low-frequency movement artifacts, the recording signals were subtracted from that of a low-impedance-tip reference microwire positioned just posterior and at the same depth as the array. The rat was anesthetized with sodium pentobarbital (50 mg/kg, i.p.) and given atropine (0.1 mg/kg, i.p.) to reduce mucous secretions. The center pair
of electrodes was positioned at coordinates 4.0 mm posterior to bregma,
3.3 and 2.8 mm lateral to midline for CA3 and DG-CA1 placement,
respectively. The longitudinal axis of the array was rotated to a 30°
angle from midline, with the anterior end more medial and the posterior
end more lateral, to follow the contour of the hippocampus. The array
was driven slowly (~25 µm/min) through the brain to a depth of
3.4-4.0 mm for CA3 and 2.2-3.2 mm for CA1. Neural activity from the
microwire electrodes was monitored throughout surgery to ensure
placement near the hippocampal cell layers. After array placement, the
cranium was sealed with bone wax and dental cement. The animal was
allowed to recover for 6-7 d before DNMS retraining and recording
commenced. The scalp wound was treated periodically with Neosporin
antibiotic to prevent infection.
Histology
At the conclusion of recording, the location of each recording
electrode was histologically verified (Fig. 1C) by passing 40 µA current through each microwire and reacting with potassium ferrocyanide to form a Prussian blue stain. A Nissl stain was used to
aid the visualization of the cell body layers. All animal care and
experimental procedures conformed to National Institutes of Health and
Society for Neuroscience guidelines for care and use of experimental animals.
Unit recording technique
Extracellular action potentials ("spikes") and behavioral
responses were digitized and time-stamped for computer processing in
relation to successive behavioral events within each DNMS trial. Neuronal activity was digitized at 40 kHz and isolated by
time-amplitude window discrimination and template matching using a
Multichannel Acquisition Processor system (Plexon, Dallas, TX).
Up to four single units could be isolated per microwire (Fig.
1D). Identified spikes were tracked from session to
session by waveform and firing characteristics within the task
(perievent histograms). To maximize the likelihood that single units
were recorded, only waveforms with zero spike counts in the first 1 msec time bin of their interspike interval histogram were included in
the analysis. Also, to help ensure that the same neurons were recorded
continuously over time, waveforms were required to have stable
perievent firing rates across sessions. Although it is possible that
the neuronal spikes that were discriminated on a given microwire may
not have isolated single units or consistently identified the same
neuron over time (McNaughton et al., 1983b), selecting only waveforms
with absolute 1 msec refractory periods, and with constant firing
rates and behavioral correlates across recording sessions
greatly reduced the probability that different neurons were mistaken as
single units (Deadwyler et al., 1996).
Identification of hippocampal principal cells and
theta interneurons
Theta interneurons can be distinguished from principal cells in
the hippocampus on the basis of their physiological characteristics. Interneurons in the dentate gyrus (Mizumori et al., 1989; Jung and
McNaughton, 1993) and CA3/1 fields (Ranck, 1973; Fox and Ranck, 1975,
1981) exhibit high (>5 Hz) overall mean firing rates modulated at
theta rhythm (5-12 Hz) and have narrow spike widths (most with <250
µsec negative-going spike widths); in contrast, granule and pyramidal
cells discharge in complex-spike bursts of two to seven spikes at 3-5
msec interspike intervals with low (<2 Hz) overall mean firing rates
and possess large spike widths (>250 µsec negative-going spike
widths). Although mean firing rate alone or spike width alone is
insufficient to clearly distinguish the principal cell and theta
interneuron populations because of partially overlapping distributions,
the two cell groups can be effectively separated if the two parameters
are considered together in firing rate-spike width space (Csicsvari et
al., 1999). In the present study, up to four individual units could be
isolated on each microwire, including at times both principal
cells and interneurons on the same wire. A linear cutoff in firing
rate-spike width space was used in conjunction with the
autocorrelation function to classify the two cell types. Cells with
mean firing rates r (in Hertz) and negative-going spike
widths w (in microseconds) such that r < 0.04 · w 3.5 and a peak at 3-5 msec in the
autocorrelogram followed by a fast exponential decay (i.e.,
complex-spike activity) were classified as principal cells. Cells with
mean firing rates and negative-going spike widths such that
r > 0.04 · w 3.5 and a prominent
peak in the 80-200 msec range (5-12 Hz) of the autocorrelogram were
classified as theta interneurons. The two populations of cells (Fig.
1D) were separated reasonably well in firing
rate-spike width space by the linear cutoff method, as measured by
multivariate ANOVA (F(2,1237) = 817.29; p < 1010). The
firing correlates of the theta interneurons (firing rate, 17.4 ± 1.13 Hz, mean ± SEM; negative-going spike width, 206 ± 6 µsec; n = 139) were compared with that of the
complex-spike principal cells (firing rate, 1.1 ± 0.05 Hz;
negative-going spike width, 305 ± 3 µsec; n = 1101) reported in Wiebe and Stäubli (1999).
Analysis
Event-responsive activity. Perievent histograms were
generated for each cell around each DNMS event. The associated event, bin width, histogram boundary limits, and grouping factors for each
perievent histogram are shown in Table
1. The responsivity of cells to
events in the sample, delay, and test phase was determined by comparing
the firing rate within each perievent histogram with its appropriate
baseline period. For perievent histograms in the test phase, in which
the rat's position was different for each event, the baseline used was
mean firing rate over the entire trial. A neuron was classified as a
"test cell" if there was a significant (ANOVA; p < 0.01) firing rate increase in one or more perievent histogram bins
relative to baseline. Only increases in firing were considered for
events in the test phase, which did not all occur at a common location
to avoid classifying low, out-of-field firing of a spatially selective
cell as a response (e.g., to avoid classifying a place cell with
a receptive field in the sample arm and no activity in the test arms as
"responsive" to events in the test phase). For perievent histograms
in the sample and delay phases in which the location of the
rat was fixed at the sample port, the pre-odor interval at the sample
port was used as the baseline reference period. A cell was classified
as a "sample cell" or "delay cell" if there was a significant
change (either enhancement or suppression) in the firing rate of one or
more perievent histogram bins relative to pre-odor baseline. Further
discriminant analyses were performed then on each event-responsive cell.
Determination of firing selectivity. The test-phase
perievent histograms constructed around the test-arm entry and poke
response consisted of three factors: position [left/right
(L/R)], odor (A/B), and trial type [correct/error (C/E)]. The
sample phase and delay phase perievent histograms constructed around
odor onset and offset consisted of two factors: odor (A/B) and trial
type (correct/error). Note that correct/error in the sample and delay phases refers to trials in which a nonmatch or match response, respectively, was made in the test phase.
Discriminant analysis (Rencher, 1995) is a mathematical technique
to project data in high-dimensional space onto a reduced number of
dimensions (i.e., a set of basis vectors) that maximally separate one
or more groups. For linear discriminant analysis of perievent activity,
this translates to finding weights for each perievent histogram time
bin such that the weighted linear sum maximally separates one or more
of the groups. This process is equivalent to plotting the perievent
firing rate of a cell for each trial in n-dimensional
space, where n is the number of time bins, and computing
directions in n-dimensional space along which the groups are
maximally separated [see Wiebe and Stäubli (1999) for schematic
illustration]. For example, if odor and correct/error are the two
factors and the four groups are correct odor A trials, correct odor B
trials, error odor A trials, and error odor B trials, and if the
perievent firing rate of the cell, X, for trial j
in time bin i is xij, then
the first direction (first discriminant function)
D1 = (d ,
d ,... , d ) is computed such that
the distribution of
across the j trials maximally separates one or more
of the groups. The first discriminant function is chosen therefore such that the data projection onto it accounts for the maximal separation between the groups (maximal variance). Mathematically, this is equivalent to finding the eigenvector with the largest eigenvalue  1 of the matrix B · W1, where B is the
between-group covariance matrix and W is the within-group
covariance matrix for the perievent histogram. The second discriminant
function D2 = (d ,
d ,... , d ) is then selected such
that it maximizes the variance between the groups and is
uncorrelated (linearly independent) with
D1. A total of minimum (number of time
bins, number of groups) discriminant functions is calculated in this
fashion for each perievent histogram such that successive functions
account for maximal variance of the perievent activity of the cell
across groups that are linearly independent from previously calculated
functions. The proportion of perievent firing variance across trials
accounted for by the discriminant function projections
D1 · X, D2
· X, ... is ordered, therefore, from highest to lowest. The
ability of a discriminant function projection to separate one or more of the groups was determined using the
 2 approximation of the Wilks  statistic. Significant discriminant function projections
(p < 0.01; 2)
were analyzed then using two- and three-way ANOVAs to determine which
groups were separated. Cells with discriminant function projections
that had a significant main effect (ANOVA; p < 0.01) were deemed selective for that factor (e.g., odor) and to discriminate the two groups in that factor (e.g., odor A versus odor B) in its
perievent firing rate.
The degree to which the difference in firing rate between separated
groups contributed to the overall perievent firing rate variance across
trials was determined by the ratio of the eigenvalue of the
corresponding discriminant function to the total firing rate variance
in the perievent histogram across trials. Because the discriminant
functions are uncorrelated, the eigenvalues additively partition the
total firing rate variance across trials, and the percentage of firing
rate variance accounted for by the ith discriminant function
is given by:
The percentage of variance in firing rate across trials
accounted for by discriminant functions that separated sample odor A
versus B, test odor A versus B, test position left versus right, and
correct versus error trials in the test phase was calculated (see Fig.
6A) to compare the relative strength of each
correlate. For instance, a discriminant function projection D · X
which separated odor A versus odor B trials and contributed to 80% of
the perievent firing variance of the cell would indicate that 80% of
the variation in perievent activity across trials was attributable to
differential activity on odor A versus odor B trials.
Controls for movement
Because the firing rates of some classes of interneurons
are known to be correlated to walking speed (McNaughton et al., 1983a; Rivas et al., 1996), we compared velocity distributions between groups
separated by the discriminant analysis, as calculated by subtracting
the test-arm entry and nosepoke response times. A significance
level of p > 0.05 (ANOVA) signified that walking speeds on odor A versus odor B, left versus right, or correct versus
error trials were indistinguishable. The distance between the entry
point of the test arm and the nosepoke port infrared beam was 24 cm,
approximately equal to the body length of the rat. In test arms in
which a nosepoke was executed, the rats traversed this length rapidly
(mean time, 0.920 sec on average for each rat) and in a highly
stereotyped fashion (SEM, 0.009). This effectively rules out the
possibility that other variants of overt behavior, such as vigorous
head movements, etc., could have been responsible for generating the
observed position, odor, or correct/error firing selectivity in the
test phase. The 0.920 sec average test-arm traversal time was less than
the 1 sec length of the perievent firing rate histograms analyzed
around the test-arm entry and in the pre-poke period. Hence, the
resolution of the walking speed measurement was of the same order of
magnitude as the time resolution of the perievent firing rate analyses.
In all other perievent histograms analyzed [post-poke in the test
phase; odor-fast, odor-slow, and odor-off in the sample phase; and the
delay histogram (Table 1 and Fig. 2)],
the body and head position of the rat was stationary, with the nose
positioned inside 20-mm-diameter cylindrical nosepoke ports.
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Figure 2.
Examples of hippocampal theta cell activity during
DNMS task performance. Each panel includes a raster display of 30 representative consecutive trials and a summary histogram of perievent
activity in spikes per second summed across all trials in 250 msec
bins, except in the slow sample-odor onset and delay intervals in which
1 sec bins were used. The six cells displayed
(A-F) were selected as illustrative examples
from different recording sessions and were not recorded simultaneously.
Event responsiveness was determined by comparing the perievent firing
rate with baseline activity. For perievent histograms in the sample and
delay phases in which the location of the rat was fixed at the sample
nosepoke port, the pre-odor interval was used as the baseline reference
period (represented as a dotted line extending
throughout the sample and delay phase). A cell was classified as
responsive to a sample-phase or delay-phase event if there was a
significant change (ANOVA; p < 0.01) in firing in
one or more perievent histogram bins. For perievent histograms in the
test phase in which the position of the rat changed as it traversed the
test arm, the baseline used was mean firing rate over the entire trial
(represented as a dotted line extending throughout the
test phase). A cell was classified as responsive to an event in the
test phase if there was a significant (ANOVA; p < 0.01) increase in activity in one or more of the perievent histogram
bins compared with baseline. The extracellularly recorded waveform
(negative deflection-down; calibration, 50 µV, 150 µsec),
hippocampal field, number of DNMS trials recorded
(n), and autocorrelogram for each cell are shown
to the right of each panel. The autocorrelograms
(y-axis, spikes per second;
x-axis, seconds) show a rhythmicity in the theta range for each
cell [peak in 80-200 msec range (5-12 Hz) in autocorrelogram]. The
DNMS phase, perievent histogram limits, and behavior of the rat around
each DNMS event are shown at the top of the figure.
A, A theta cell that exhibited movement
(locomotion)-correlated activity similar to that described by Ranck
(1973). The cell had elevated firing while exiting the sample arm
(F(1,97998) = 2249.20;
p < 0.01), entering the test arms
(F(1,97998) = 650.70;
p < 0.01), and in the pre-poke period
(F(1,97998) = 148.30;
p < 0.01). B, A cell with increased
activity around sample odor onset (odor fast;
F(1,8623) = 2536.50;
p < 0.01) and offset (odor off;
F(1,8623) = 476.5;
p < 0.01), suppression during the slow sample odor
onset period (odor slow;
F(1,2782) = 636.85;
p < 0.01), and elevated firing on exit of the
sample arm (F(1,167376) = 1959.00;
p < 0.01), entry into the test arms
(F(1,167376) = 1493.40;
p < 0.01), and in the preresponse period
(F(1,167376) = 968.20;
p < 0.01). C, A cell with increased
activity during sample odor onset (odor fast;
F(1,2035) = 83.06;
p < 0.01) and offset (odor off;
F(1,2035) = 52.27;
p < 0.01), sample arm exit
(F(1,53409) = 45.92;
p < 0.01), test-arm entry
(F(1,53409) = 155.11;
p < 0.01), and the preresponse period
(F(1,53409) = 77.29;
p < 0.01). D, A cell with increased
firing in response to sample odor onset (odor fast;
F(1,3246) = 202.61;
p < 0.01) and offset (odor off;
F(1,3246) = 82.23;
p < 0.01), decreased firing in the slow odor on
(odor slow; F(1,1062) = 144.76; p < 0.01) and delay
(F(1,1062) = 19.85;
p < 0.01) periods, and increased activity on entry
into the test arms (F(1,51872) = 311.18; p < 0.01), and in the preresponse
(F(1,51872) = 941.21;
p < 0.01) and postresponse
(F(1,51872) = 101.83;
p < 0.01) periods. E, A cell that
exhibited suppressed firing during the fast sample odor on
(F(1,1462) = 36.14;
p < 0.01) and off
(F(1,1462) = 53.87;
p < 0.01) periods, increased activity in the slow
odor on period (F(1,436) = 7.12;
p < 0.01), and elevated firing on exiting the
sample arm (F(1,25639) = 107.08;
p < 0.01) and entering the test arms
(F(1,25639) = 25.49;
p < 0.01). F, A cell that exhibited
elevated activity in the fast (odor fast;
F(1,2344) = 239.06;
p < 0.01) and slow (odor slow;
F(1,757) = 230.51;
p < 0.01) sample on periods, on sample odor
termination (odor off;
F(1,2344) = 288.55;
p < 0.01), and in the delay period
(F(1,757) = 103.22;
p < 0.01), on entry into the test arms
(F(1,47923) = 696.67;
p < 0.01), and in the preresponse
(F(1,47923) = 346.54;
p < 0.01) and postresponse
(F(1,47923) = 122.45;
p < 0.01) periods.
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| |
RESULTS |
Theta cell activity correlated to DNMS events
A total of 139 theta cells were isolated from the dentate gyrus
(n = 29), CA3 (n = 72), and CA1
(n = 38) fields in 18 rats during criterion performance
of the DNMS task. The units were recorded during an average of 24 sessions per animal. A subset of the theta cells was responsive
(relative to baseline; ANOVA; p < 0.01) to each DNMS
event, and many cells responded to more than one event. Some cells
exhibited deviations from baseline activity only while the rat moved
toward the nosepoke devices in the test phase (Fig.
2A). Such cells are similar to the theta cells
originally described by Ranck (1973), with firing correlated with
voluntary motor behavior (Type 1 theta behavior) (Bland et al., 1983).
Here, they were classified as test cells (i.e., responsive to events in
the test phase). Other cells demonstrated strong responses to the odor
delivery in the sample phase, in addition to the
locomotion-related activity in the test phase (therefore, both a sample
and test cell) (Fig. 2B,C). Such
theta cell activity in response to sensory (odor) stimuli during alert
immobility, termed Type 2 theta behavior, has been reported previously
(Bland et al., 1983; Eichenbaum et al., 1987). Some theta cells
demonstrated elevated (Fig. 2D) or suppressed (Fig.
2E) firing during odor onset and offset in the sample
phase and around the nosepoke in the test phase (Fig.
2D). Others maintained elevated firing during the
delay interval and were classified as delay cells (Fig.
2F).
Approximately 97% of the theta cells in each subfield (135 of 139 overall) were responsive to events in the sample phase (sample cells),
91 of 139 (65%) in the delay phase (delay cells), and 126 of 139 (90%) in the test phase (test cells) (Table
2). Responsive theta cells were
analyzed further to determine whether their activity was selective for
odor A/B, correct/error trials, or left/right position as determined by
discriminant analysis (2;
p < 0.01 significance criteria) and significant main
effects on post hoc ANOVAs (p < 0.01).
Sample odor-selective activity restricted to CA1 theta
cells and linked to task performance
Theta cells that discriminated odor A versus B in the sample phase
were largely restricted to the CA1 subfield. Examples of two
odor-selective CA1 theta cells are shown in Figure
3, A and B. Other
theta cells exhibited differential activity in response to the sample
odor on correct trials in which recognition of the odor occurred later
in the test phase, versus error trials in which recognition failed
(Fig. 3C). The head and body position remained constant
throughout the sample and delay phases of the task, with the rat's
nose positioned inside the cylindrical nosepoke port. Therefore, the
odor and correct/error correlates of theta cell responses to the sample
stimulus were not the result of or secondary to movement or spatial
correlates. Responsive cells in the sample phase (including the
odor-fast, odor-slow, and odor-off periods) were tallied then for each
subfield (Table 2). Odor selectivity was observed in 26 of 135 (19%)
of the responsive theta cells in the sample phase (compared with 100 of
699 or 14% for principal cells), one-third (8 of 26) of which fired
differentially on correct versus error trials. Ten percent (13 of 135)
of the sample theta cells discriminated correct/error trials, the same proportion as was seen in the principal cells (Fig.
4A). Odor-selective firing in the sample phase (Fig. 4B) occurred
primarily in CA1 theta cells: 15 of 38 (40%) of the responsive CA1
cells discriminated odor compared with 4 of 27 (15%) in DG and 7 of 70 (10%) in CA3 (CA1 vs DG/CA3; 2 test,
2(1) = 13.90;
p < 0.01). This nonhomogeneous pattern of odor
selectivity across the hippocampal subfields was similar to that
observed for the principal cells (7 of 96 or 7%, 67 of 458 or 14%,
and 26 of 145 or 18% of responsive DG, CA3, and CA1 principal cells,
respectively, recorded in the same animals and analyzed in Wiebe and
Stäubli, 1999) but was more steeply graded than the
principal cell pattern (2 test,
2(2) = 6.12;
p = 0.05).
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Figure 3.
Examples of odor, position, and
correct/error-selective firing in theta cells. Panels show a raster
display of 25 representative consecutive trials and a summary histogram
of all trials recorded for each cell. Waveform (negative
deflection-down; calibration, 50 µV, 150 µsec), hippocampal field,
number of trials recorded (n), and significant
(2; p < 0.01) discriminant function
(DF) projection scores (mean + SEM) for odor A/B
(A/B), correct/error
(C/E), or left/right
(L/R) arm position are shown to the
right of each panel. * indicates significant
(p < 0.01) main effect of discriminant
projection scores in the post hoc two-way or three-way
ANOVAs. Sample Phase, A, B, Cells selective for odor but
not correct/error trials in their fast [A,
2(24) = 59.11; p < 0.01; odor, F(1,482) = 24.78;
p < 0.01; C/E,
F(1,482) = 0.19, not significant (NS)]
and slow (B, 2(24) = 65.27; p < 0.01; odor,
F(1,171) = 29.21; p < 0.01; C/E, F(1,171) = 3.44, NS)
sample odor responses. C, A cell selective for
correct/error trials but not odor on termination of the sample odor
(2(18) = 38.91; p < 0.01; odor, F(1,195) = 0.65, NS;
C/E, F(1,195) = 9.16;
p < 0.01). Test Phase, D, Cell with
exclusive position (L/R) selectivity around test-arm entry.
The cell had two significant discriminant functions, both of which
discriminated only position: DF1 (top),
2(28) = 536.82; p < 0.01; position, F(1,386) = 66.09;
p < 0.01; odor,
F(1,386) = 1.41, NS; C/E,
F(1,386) = 0.82, NS; and
DF2 (bottom),
2(18) = 246.48; p < 0.01; position, F(1,386) = 26.88;
p < 0.01; odor,
F(1,386) = 0.81, NS; C/E,
F(1,386) = 2.50, NS. The rat's walking
speed in the left and right arms was indistinguishable (ANOVA;
p > 0.05). E, Cell with selective
correct/error activity in the preresponse period
(2(24) = 59.53; p < 0.01; position, F(1,197) = 2.36, NS;
odor, F(1,197) = 6.28, NS; C/E,
F(1,197) = 19.41; p < 0.01). The rat's walking speed for correct versus error trials was
indistinguishable (ANOVA; p > 0.05).
F, Cell with position, odor, and correct/error
correlates in the post-poke period. The first significant discriminant
function (top) distinguished position and correct/error
(2(84) = 202.42; p < 0.01; position, F(1,322) = 7.95;
p < 0.01; odor,
F(1,322) = 0.22, NS; C/E,
F(1,322) = 11.88; p < 0.01). The second significant discriminant function
(bottom) separated odor A/B and correct/error trials
(2(66) = 104.25; p < 0.01; position, F(1,322) = 1.03, NS;
odor, F(1,322) = 14.46;
p < 0.01; C/E,
F(1,322) = 18.71; p < 0.01).
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Figure 4.
Summary of position, odor, and correct/error
recognition correlates of hippocampal theta cells in the DNMS task.
A, Correlates of event-responsive theta interneurons
(T-Cells, left bars) compared with that
of principal cells (P-Cells, right bars;
taken from Wiebe and Stäubli, 1999). Ten percent of the
responsive theta cells in the sample phase fired differentially on
correct versus error trials. Sample odor selectivity was observed in
20% of the theta cells (compared with 14% for the principal cells),
roughly one-third of which fired differentially on correct versus error
trials ( ). No cells were selective for odor or correct/error trials
in the delay period. In the test phase, a greater proportion of
responsive theta cells were selective for position, correct/error, and
odor than were the responsive principal cells (position, theta cells,
91%; principal cells, 70%; C/E, theta cells, 38%; principal cells,
21%; odor, theta cells, 34%; principal cells, 27%). Spatial
selectivity was more than twice as predominant as odor and C/E
selectivity for responsive theta cells, and almost all odor and C/E
cells had conjunctive spatial correlates ( ). B,
Sample odor selectivity in hippocampal theta cells was restricted
primarily to the CA1 subfield, with odor selectivity in 40% of
responsive cells in CA1, compared with 10 and 15% in CA3 and DG,
respectively (CA1 vs DG/CA3; 2 test,
2(1) = 13.90; p < 0.01). C, Correct nonmatch/error match-selective theta
cells in the test phase were more than twice as predominant in the
CA3/1 regions (~43%) than the dentate gyrus (20%) (2
test, 2(1) = 4.33;
p < 0.05). D, Odor selectivity of
the correct/error cells in the dentate and CA3 fields was near 60%,
but only 12% in CA1. The distribution of odor selectivity in the
test-phase C/E cells was inverse and statistically distinct
(2(2) = 58.2; p < 0.01) from that of the responsive theta cells in the sample phase in
B.
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Sample-nonspecific delay activity
Sixty-five percent (91 of 139) of the theta cells in the
hippocampus exhibited significantly elevated or suppressed activity at
the sample port location in the delay relative to the pre-odor period
but, like the principal cells, none (0 of 91) differentiated odor
A versus odor B or correct versus error (C/E) trials (Table 2, Fig.
4A).
Recognition phase activity
Central to the DNMS task is the ability to discriminate the
test odors and then make a match/nonmatch comparison with the sample
odor held in memory. Individual theta cells were found to discriminate
various combinations of correct nonmatch/error match (C/E), odor A/B,
and left/right position in the test phase. Some exhibited activity that
discriminated only left/right position (Fig. 3D) or
correct/error trials (Fig. 3E), whereas others demonstrated conjunctive position, odor, and C/E correlates (Fig.
3F).
Theta cell odor A/B, correct/error, and left/right position
selectivity in the test phase not attributable to differential walking
speeds between groups
The test phase differed from the sample and
delay phases in that the rat was walking while smelling and
discriminating the odor stimuli. The majority of the test cells with
selective odor, correct/error, or position firing while the rat was
moving from the test-arm entrance to the poke port (i.e., in the
test-entry and pre-poke periods) did not have significant differences
(ANOVA; p > 0.05) in walking speed for odor A versus
odor B trials (20 of 23 cells; 87%), correct versus error trials (20 of 25; 80%), and left versus right position (79 of 104; 76%),
respectively. The walking speed was calculated using the time between
test-arm entry and the end-of-arm nosepoke [0.920 ± 0.009 sec
(mean ± SEM) on average for each rat]. This indicates that the
selectivity of the theta cell firing observed before the nosepoke in
the test phase cannot be attributed to differential rates of locomotion within the different analysis groups.
Correct/error-selective cells with reinforcement-correlated
activity after the test nosepoke excluded from subsequent analyses
To determine whether correct/error-selective
firing immediately after the test nosepoke was associated with the
behavioral execution of the nosepoke or was attributable to
differential responding to the water reward and light flash, the
reinforcement signal was delayed 1.5 sec on a select number of randomly
interspersed trials. Correct/error-selective cells in the post-poke
period were classified as either reinforcement-correlated or
poke-correlated on the basis of whether their poke-aligned or
reinforcement-aligned perievent histogram contained the larger peak
firing rate. An example of a reinforcement-correlated correct/error
cell is shown in Figure 5A.
The elevated activity of the cell after error match, but not correct
nonmatch, responses was better correlated with the flash reinforcement
than the nosepoke response (i.e., more temporally locked in the
flash-centered versus the poke-centered histogram), indicating that
the activity could be interpreted as a response to the light flash. An
example of a poke-correlated cell is shown in Figure 5B. The
increased activity after correct nonmatch responses compared with error
match responses was correlated better with the time of the poke than
the water reinforcement delivery (i.e., more temporally locked in the
poke-centered versus the reinforcement-centered histogram),
indicating that the activity of the cell represented the execution of a
correct nosepoke and not simply a response to the water delivery.
Reinforcement-correlated C/E cells were discarded, and only
C/E-selective cells with poke-correlated activity were included from
the post-poke period in subsequent analyses (Table 2, Figs. 4,
6).
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Figure 5.
Determination of poke-correlated versus
reinforcement-correlated correct/error-selective firing in the
post-poke period. Panels show a perievent histogram of all trials
recorded for each cell and a raster display of 15 representative
consecutive trials. Waveform (negative deflection-down; calibration, 50 µV, 150 µsec), hippocampal field, and number of trials recorded
(n) are shown to the right.
A, Top panels, Cell with elevated
activity after error (right) relative to correct
(left) poke responses
(2(84) = 337.94; p < 0.01; C/E, F(1,230) = 197.41;
p < 0.01). The histograms contain both trials in
which the reinforcement signal was immediate and trials in which it was
delayed 1.5 sec. Bottom panels, Perievent histogram of
activity around the error poke response (left) and the
flash reinforcement signal (right). The activity was
better time-locked (i.e., larger maximal firing rate, signified by
open arrowheads) to the flash reinforcement than to the
poke response and therefore was classified as reinforcement
correlated. B, Top panels, Cell with more
robust activity after correct poke responses (left) than
after error poke responses (right) (second DF,
2(66) = 227.75; p < 0.01; C/E, F(1,428) = 58.33;
p < 0.01). Bottom panels, Perievent
histogram of activity around the correct poke response
(left) and the water reinforcement
(right). The activity was better time-locked (i.e.,
larger maximal firing rate) to the poke response than to the water
reinforcement and therefore was classified as poke-correlated. Cells
with reinforcement-correlated correct/error selectivity were discarded.
Only cells with correct/error-selective activity associated with the
nosepoke (poke-correlated) were included in the summary tallies (Table
2, Figs. 4, 6).
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Figure 6.
Comparison of the magnitude of theta cell and
principal cell firing correlates. A, Percentage of the
total perievent firing rate variance accounted for by discriminant
function projections that distinguished odor (A/B) in the sample phase
and position (L/R), odor (A/B), and correct/error
(C/E) trials in the test phase in
hippocampal theta cells and principal cells. There was no significant
difference in the proportion of the total perievent firing rate
variance contained in the theta cell correlates versus principal cell
correlates for the sample odor [ANOVA;
F(1,141) = 0.080; not significant
(NS)] or test left/right position
(F(1,947) = 0.002; NS), odor
(F(1,238) = 0.003; NS), or
correct/error (F(1,193) = 0.002; NS).
The magnitude of the theta cell perievent firing variance accounted for
by the sample odor and test position, odor, and correct/error
correlates did not differ significantly across the four groups
(F(3,382) = 0.011; NS).
B, Ratio of the mean perievent activity (averaging
across all time bins in each perievent histogram) of
correct/error-selective cells on correct (C)
versus error (E) trials [(C E)/(C + E)]. Although, like
principal cells, the majority (79%) of the C/E theta cells in the test
phase exhibited greater activity in correct nonmatch trials than in
error match trials (i.e., ratio >0), the ratio of activity was smaller
(most  20%) than for principal cells (many with  40%).
Inset: Interneuron distribution around the
x-axis origin. Most interneurons had moderately greater
activity on correct trials than error trials. (Note: +0.2 implies
0-20% increase in activity on correct versus error trials, +0.4
implies 20-40% increase, etc., 0.2 implies 0-20% decrease,
etc.)
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Correct/error recognition signaling most prominent in CA3/1
subfields, odor-selective in DG/CA3, and integrated with spatial
representations
Responsive theta cells with odor, correct/error (including 15 C/E
cells in the test-entry period, 15 C/E cells in the pre-poke period,
and 28 poke-correlated C/E cells from the post-poke period), and
position selectivity were tallied over all three test-phase perievent
histograms, as shown in Table 2 and Figure 4A.
Position (115 of 126; 91%), odor (43 of 126; 34%), and correct/error
selectivity (48 of 126; 38%) in the test phase occurred in a greater
proportion of responsive theta cells than principal cells [400 of 571 (70%), 155 of 571 (27%), and 121 of 571 (21%), respectively).
Roughly one-third (37 of 115) of the spatial theta cells were selective for position exclusively with no significant (ANOVA; p < 0.01) main or interaction effects with regard to odor or C/E,
whereas ~95% of the C/E (45 of 48) and odor (41 of 43) cells had
spatial correlates (Table 2, Fig. 4A).
Correct/error trial-selective activity was seen in twice as many theta
cells in CA3/1 (43 of 101 or 43% of responsive neurons) as in DG (5 of
25; 20%) (2 test;
2(1) = 4.33;
p < 0.05) (Fig. 4C). The majority of
correct/error cells in DG and CA3 were odor selective (18 of 32; 56%),
whereas only 2 of 16 (12%) C/E cells in CA1 had conjunctive odor
correlates (Fig. 4D). This distribution of odor
selectivity of C/E cells in the test phase was more steeply graded
(2 test;
2(2) = 12.78;
p < 0.01) than that observed for the C/E-selective
principal cells [10 of 17 (59%) in DG, 32 of 76 (42%) in CA3, and 10 of 28 (36%) in CA1] and was inverse and distinct
(2 test;
2(2) = 58.2;
p < 0.01) from the theta cell odor-selectivity distribution in sample phase in Figure 4B. The
distribution of odor selectivity of responsive theta cells in the test
phase [7 of 25 (28%) in DG, 27 of 65 (42%) in CA3, and 9 of 36 (25%) in CA1], although not inversely distributed across subfields
relative to the sample phase, was statistically different
(2 test;
2(2) = 21.6;
p < 0.01) from the sample-phase distribution.
Equivalent relative strength of odor, position, and correct/error
recognition correlates in interneurons and principal cells
For each odor-selective cell in the sample phase or position-,
C/E-, or odor-selective cell in the test phase, we calculated the
percentage of the total variance in perievent firing across trials
accounted for by the associated discriminant functions. A
summary of the pooled results over all DNMS events for both interneurons and principal cells is shown in Figure
6A. The percentage of total perievent firing rate
variance accounted for by differential sample odor A versus B, test
odor A versus B, test left versus right position, and test correct
versus error trial activity for interneurons did not differ from
that of the principal cells for each of the four variables (ANOVA;
p > 0.1; pairwise comparisons). Nor was there any
significant difference in percentage of total perievent firing variance
among the four variables for the interneurons (ANOVA; p > 0.1).
Majority of C/E theta cells exhibited greater activity on correct
trials than error trials, but with smaller difference in firing rate
compared with principal cells
To compare the magnitude of interneuron correct/error recognition
correlates in absolute terms with that of principal cells, we
calculated the ratio of the mean perievent activity (averaging across all time bins in each perievent histogram) for correct (C) and
error (E) trials, [(C E)/(C + E)], for all C/E-selective cells. The majority of both C/E-selective principal cells (84 of 121;
70%) and interneurons (38 of 48; 79%) exhibited higher firing rates
on correct nonmatch trials than error match trials. The ratio of
correct to error activity, however, was considerably smaller in
interneurons [45 of 48 (94%) of the theta cells with <20%
difference] compared with the principal cell population [55 of 124 (44%) of the cells with >20% difference] (Fig.
6B). The inset portion of Figure
6B illustrates that the majority of C/E theta cells
did exhibit moderately (>0%, <25%) higher firing rates on correct
nonmatch trials than error match trials.
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DISCUSSION |
Since 1973 when Ranck first described the correlation between
theta cell activity and the movement/arousal-related hippocampal EEG
theta rhythm (Ranck, 1973), most theta cell recording studies have
involved tasks with modest cognitive demands, such as searching for
randomly distributed food pellets, traversing linear tracks or mazes,
simple sensory discrimination, or eyeblink conditioning. In addition to
the behavioral (motor) correlates (O'Keefe, 1976), some place
(McNaughton et al., 1983a; Kubie et al., 1990) and S+/S
specificity (Christian and Deadwyler, 1986; Foster et al., 1987) has
been observed as well as activity associated with learned conditioned
responses (McEchron and Disterhoft, 1997). In the present study, we
analyzed theta cell responses to stimuli representing cues in a
cognitively demanding, hippocampally dependent (Wood et al., 1993;
Alvarez et al., 1995; Hampson et al., 1999) recognition memory task.
The main findings were: (1) theta cell responses to events in an
olfactory DNMS task represent odor, position, and match/nonmatch
recognition comparisons with the same percentage of perievent firing
variance across trials as hippocampal principal cells; (2) conjunctive
spatial with odor and correct/error recognition correlates; (3)
inverted sample-phase versus recognition-phase distributions of theta
cell odor specificity across the hippocampal subfields, similar to that
of the principal cells but with greater contrast between the CA1 and
DG/CA3 fields; and (4) greater discriminative match/nonmatch activity
on correct versus error trials. A discussion of each finding and its
relevance to hippocampal processing during recognition memory follows.
Theta cell and principal cell cognitive firing correlates
equivalent in magnitude
The olfactory, spatial, and correct/error recognition correlates
of theta cells represented equivalent proportions of variance in
perievent firing rate across trials and were indistinguishable from
that of principal cells. Previous investigations of theta cells, like
the present study, have reported activity correlated with active
stimulus (odor) cue sampling (type 2 theta behavior; alert immobility
with presentation of sensory stimuli) and locomotion (type 1 theta
behavior; voluntary motor patterns) (Ranck, 1973; Bland et al., 1983;
Eichenbaum et al., 1987). Their failure to report perceptual and
cognitive firing correlates may be attributable to the relative
insensitivity of univariate statistics (ANOVAs) typically used to
analyze perievent activity, compared with multivariate discriminant
analysis that incorporates the temporal structure of the firing
patterns. In the past, however, most studies of hippocampal recognition
memory have focused on complex-spike principal cells and not theta
interneurons (Otto and Eichenbaum, 1992; Sakurai, 1994; Deadwyler et
al., 1996; Wood et al., 1999).
The odor, correct/error, and position selectivity could not be
attributed to movement-related activity. In the sample and delay
phases, the head and body position of the rat was constant. In the test
phase, the majority of theta cells with odor, C/E, or position
correlates had statistically indistinguishable walking speeds across
the group categories. The strength of theta cell firing could have
correlated with the magnitude of hippocampal EEG theta, however. EEG
theta was likely robust during odor sampling in the sample phase (type
2 theta) and during odor sampling and locomotion (type 1 theta) in the
test phase (Bland et al., 1983; Eichenbaum et al., 1987), but
diminished in the delay when no odors were present and the rat's
position remained fixed. This may explain the reduced number of
responsive cells in the delay (~65%) relative to the sample and test
(>90%) phases (Table 2). It is possible that the
correct/error-selective theta cell activity was paralleled by
corresponding changes in hippocampal EEG theta; correlations between
EEG theta and hippocampal-dependent memory performance have been
observed previously (Winson, 1978; Givens and Olton, 1994;
Stäubli and Xu, 1995; Burgess and Gruzelier, 1997). It is
unlikely, however, that the EEG theta differed significantly with
left/right position or odor identity. No studies to date have reported
stimulus cue selectivity, either spatial or nonspatial, in the
hippocampal EEG theta. Moreover, the EEG theta would have to have been
nonuniformly present in the different hippocampal subfields to underlie
the regional differences in theta cell firing correlates. Nevertheless,
additional experiments are required to determine the exact relationship
between the cognitive interneuron firing correlates and the EEG theta
in each hippocampal subfield.
Integration of odor and recognition memory correlates with
spatial representations
Odor and correct/error recognition correlates were present both in
the sample phase, in which the spatial position was fixed, and the test
phase in which position varied (left/right arm). In the test phase, the
majority of odor and correct/error-selective cells had conjunctive
spatial correlates, whereas a substantial number of responsive cells
(38%) had pure position correlates. This indicates that when position
was allowed to vary in the test phase, perceptual odor and cognitive
memory representations became incorporated into the spatial map of the
interneurons. The spatially dependent odor and correct/error memory
correlates were not smaller in magnitude or secondary to the spatial
correlates, however. The proportion of perievent firing variance
accounted for by the odor and correct/error memory correlates in the
test phase was equivalent to that of both the spatial correlates in the
test phase and the odor correlates in the sample phase, in which
position was constant (Fig. 6A). The large percentage
of responsive theta cells in the test phase with L/R place specificity
(91%, compared with 70% of principal cells, shown in Fig.
4A) may be attributable to their relatively large
place fields (McNaughton et al., 1983a; Kubie et al., 1990).
Sample cue-selective activity restricted to CA1 and linked to
task performance
An advantage of the simultaneous DNMS experimental design used in
this study was that the sample and test phases were spatially and
temporally distinct, allowing comparisons to be made between theta cell
responses to stimuli presented in the acquisition versus recall phase
of the task. In the sample phase, odor-selective theta cell activity
was largely restricted to the CA1 field (Figs. 4B,
7A), perhaps because of the
direct entorhinal cortex CA1 perforant path projection (Amaral and
Witter, 1989). The fact that activity in one-third of the
odor-selective theta cells also predicted performance in the test phase
(differential activity in the sample phase on correct versus error
trials) suggests that this sample odor representation may be important
for mediating its memory across the delay. The correct/error correlate
in the sample phase (as well as the test phase) could represent a
miscoding of the odor cue (Hampson and Deadwyler, 1996) or a more
general cognitive (e.g., attention) signal required for accurate recall
in the task.
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Figure 7.
Schematic diagram of hippocampal
theta cell firing correlates during memory acquisition and recall.
A, Odor cue-specific activity (filled
circles) in the sample phase is restricted to the CA1
field, perhaps transferred from the parahippocampal cortex
(PHC) via the direct perforant path projection.
B, Test-phase correct nonmatch/error match
(C/E) comparisons with the sample held in
memory occur predominantly in CA3 and CA1 and not in the dentate gyrus
(DG). The match/nonmatch comparison signal is stronger
on correct trials, in which accurate memory of the sample is
demonstrated, and weaker on error trials, in which memory for the
sample fails. The correct/error recognition signaling is odor-specific
in DG and CA3 and odor-general in CA1. During recall, therefore, theta
cell activity contributes to the transformation of
cue-dependent cortical memory signals into abstracted, cue-general
memory signals as the match/nonmatch recognition signals pass through
the DGCA3CA1 circuit.
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Behaviorally relevant recognition memory signal
concentrated in CA fields, but transitions from cue-specific to
cue-general at the CA3-CA1 boundary
Differential unit responses to test stimuli that match versus
nonmatch the sample have been reported in the hippocampus of both
monkeys (Rolls et al., 1993) and rats (Otto and Eichenbaum, 1992; Wiebe
and Stäubli, 1999; Wood et al., 1999). The match/nonmatch signals
have been interpreted as the neuronal substrate for recognition memory,
contributing to the animal's decision about whether stimuli have been
encountered in the recent past. Most of these studies however, because
of the use of the continuous DNMS paradigm with short delays, had few
error trials and subsequently were unable to evaluate the behavioral
relevance of these recognition signals. The more robust theta cell
activity on nonmatch versus match trials that was observed here (Fig.
6B) provides evidence for the presence of a
match/nonmatch comparison signal on correct trials in which recognition
occurred and its absence on error trials in which recognition failed.
The fact that the correct/error correlates were present during and
immediately after odor selection in the test phase but before delivery
of the confirmator |
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ABSTRACT
INTRODUCTION
