 |
Previous Article | Next Article 
Volume 17, Number 13,
Issue of July 1, 1997
pp. 5183-5195
Copyright ©1997 Society for Neuroscience
Memory Representation within the Parahippocampal Region
Brian J. Young1,
Tim Otto2,
Gregory D. Fox3, and
Howard Eichenbaum4
1 Department of Psychology, University of Otago,
Dunedin, New Zealand, 2 Department of Psychology, Rutgers
University, New Brunswick, New Jersey 08901, 3 Department
of Psychology, University of North Carolina, Chapel Hill, North
Carolina 27599, and 4 Department of Psychology, Boston
University, Boston, Massachusetts 02215
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
FOOTNOTES
REFERENCES
ABSTRACT
The activity of 378 single neurons was recorded from areas of
the parahippocampal region (PHR), including the perirhinal and lateral
entorhinal cortex, as well as the subiculum, in rats performing an
odor-guided delayed nonmatching-to-sample task. Nearly every neuron
fired in association with some trial event, and every identifiable trial event or behavior was encoded by neuronal activity in the PHR.
The greatest proportion of cells was active during odor sampling, and
for many cells, activity during this period was odor selective. In
addition, odor memory coding was reflected in two general ways. First,
a substantial proportion of cells showed odor-selective activity
throughout or at the end of the memory delay period. Second,
odor-responsive cells showed odor-selective enhancement or suppression
of activity during stimulus repetition in the recognition phase of the
task. These data, combined with evidence that the PHR is critical for
maintaining odor memories in animals performing the same task, indicate
that this cortical region mediates the encoding of specific memory
cues, maintains stimulus representations, and supports specific
match-nonmatch judgments critical to recognition memory. By contrast,
hippocampal neurons do not demonstrate evoked or maintained
stimulus-specific codings, and hippocampal damage results in little if
any decrement in performance on this task. Thus it becomes increasingly
clear that the parahippocampal cortex can support recognition memory
independent of the distinct memory functions of the hippocampus
itself.
Key words:
entorhinal cortex;
perirhinal cortex;
subiculum;
hippocampus;
recognition memory;
delayed nonmatching;
single
units
INTRODUCTION
The parahippocampal region (PHR) has become a
focus for anatomical, behavioral, and electrophysiological studies of
the medial temporal lobe memory system (Eichenbaum et al., 1994 ; Brown,
1996 ; Murray, 1996 ; Suzuki, 1996 ). This cortical area surrounds the hippocampus and amygdala and is composed of several distinct
subdivisions, including the perirhinal, entorhinal, and parahippocampal
(in monkeys) or postrhinal (in rats) cortices (Witter et al., 1989 ; Burwell et al., 1995 ). The PHR receives inputs from widespread secondary or "association" cortical regions and provides the major conduit for hippocampal outputs to the same cortical association areas.
This anatomical evidence indicates that the PHR occupies a pivotal
position for mediating memory functions of the hippocampal region.
Neuropsychological findings indicate that the PHR indeed plays a
critical role in recognition memory, independent of its role as an
intermediary for cortical-hippocampal interactions (Eichenbaum et al.,
1994 ; Murray, 1996 ). This evidence comes mainly from experiments examining the effects of damage to the hippocampal region on
performance in a simple recognition memory test known as delayed
nonmatching to sample (DNMS) (Eichenbaum et al., 1994 ). In the standard
version of this task, originally devised by Gaffan (1974) , animals are presented with a novel "sample" cue and then after a variable memory delay must show that they recognize the sample by selecting against it (nonmatching) when presented with a choice between the now
familiar stimulus and a new item. Several studies using different
variants of DNMS in both rats and monkeys have shown that damage to the
PHR results in a severe and selective deficit in performance at long
delays (Zola-Morgan et al., 1989b , 1994 ; Gaffan and Murray, 1992 ; Otto
and Eichenbaum, 1992a ; Meunier et al., 1993 ; Suzuki et al., 1993 ;
Eacott et al., 1994 ; Gaffan, 1994 ; Mumby and Pinel, 1994 ), whereas
ablation of the hippocampus or transection of the fornix produce
relatively little deficit (Bachevalier et al., 1985 ; Aggleton et al.,
1986 , 1989 ; Zola-Morgan et al., 1989a , 1994 ; Gaffan, 1974 ; Gaffan et
al., 1984 ; Mumby et al., 1992 ) or no deficit (Rothblat and Kromer,
1991 ; Otto and Eichenbaum, 1992a ; Jackson-Smith et al., 1993 ; Kesner et
al., 1993 ; Gaffan, 1994 ; Murray, 1996 ; Murray and Mishkin, 1996 ).
To mediate performance in DNMS, a specific encoding of the sample
cue must be maintained throughout the memory delay. The stored
representation must then be compared with choice items presented in the
recognition test. In a recent study examining the firing patterns of
hippocampal neurons in rats performing an odor-guided DNMS task, we
found no cells that encoded specific sample cues, maintained stimulus
representations during the memory delay, or fired in association with
match or nonmatch comparisons for particular sample and test odors
(Otto and Eichenbaum, 1992b ). These findings are consistent with the
neuropsychological data indicating that the hippocampus itself is not
essential for odor-guided DNMS performance (Otto and Eichenbaum,
1992a ). In the present study we extended our recordings to determine
whether firing patterns of PHR neurons would reflect these aspects of
stimulus representation. Our studies focused on the perirhinal cortex
and the lateral entorhinal cortex, two parts of the PHR that receive
direct olfactory inputs (Deacon et al., 1983 ), and on the subiculum,
another retrohippocampal cortical area that is reciprocally connected
with the PHR.
MATERIALS AND METHODS
Subjects. Nine male Long-Evans rats, weighing
between 340 and 550 gm at the beginning of the experiment, served as
subjects. The animals were housed individually, maintained on a 12 hr
light/dark cycle, and given ad libitum access to food. Water
access was restricted to that earned during the performance of the
continuous DNMS (cDNMS) task, and to 40 min of free access per day at
the end of each test session.
Electrodes, surgery, and histology. The electrode assemblies
consisted of 10 25-µm-diameter Formvar-coated nichrome wires of equal
length bundled into a 27 gauge cannula (Eichenbaum et al., 1977 ) and
attached to a vertically driveable connector (Kubie, 1984 ). The animals
were anesthetized with sodium pentobarbital (50 mg/kg,
i.p.) supplemented with methoxyflurane when necessary; atropine was
administered (0.5 mg in 1 cc, i.p.) to reduce mucous secretions. With
use of aseptic surgical procedures, the electrode assemblies were
implanted stereotaxically, with the skull level at the following
coordinates: for lateral entorhinal cortex and subiculum, 5.2 mm
posterior to and 5.0 mm lateral to bregma, and 6.5 mm below the pial
surface with the electrode carrier oriented at 16° from vertical in
the coronal plane; for perirhinal cortex, 5.2 mm posterior to and 5.0 mm lateral to bregma, and 4.5 mm below the pial surface with the
electrode carrier oriented at 17.5° from vertical in the coronal
plane. At the conclusion of testing, each subject was administered a
lethal dose of sodium pentobarbital (100 mg/kg), a 15 µA current was passed through three of the recording electrodes, and
the animal was then perfused transcardially with normal saline followed
by 10% buffered formalin. The brains were removed from the skulls and
stored in 10% buffered formalin for 24 hr and then transferred to a
3% potassium ferrocyanide solution for another 24 hr. This second
solution produced a Prussian blue reaction that aided the localization
of the electrode tips. Finally, the brains were transferred to a 30%
sucrose-formalin solution for an additional 24-48 hr, coronal
sections were cut at 30 µm on a sliding microtome, and the sections
were mounted and stained with thionin.
Unit recording and computerized data acquisition. The
subjects were screened once per day for unit activity. If no activity was identified during screening, the electrode was advanced ~40 µm
and allowed to settle for at least 24 hr before subsequent screening.
Up to four channels of neural activity were passed individually through
a high-impedance JFET headstage and then to AC amplifiers (Grass, model
P511K), where the signals were amplified 5000× and bandpass-filtered
at 300-3000 Hz. Each channel of neural activity was recorded
separately on a multi-track digital tape recorder (Vetter, model
PCM400) for subsequent off-line data acquisition. Additionally,
computer-generated digital pulses that coded the behavioral events were
also recorded. During the off-line data analysis sessions, unit
isolation was achieved using a software template-matching algorithm
(Spike2) provided with a computerized data acquisition system
(Cambridge Electronic Design, model 1401+). With this system, up to
eight units could be isolated from each channel of neural activity.
Only units with signal-to-noise ratios of at least 3:1 were included in
the analysis.
Behavioral apparatus. The behavioral apparatus consisted of
a 30-cm-square aluminum chamber with one wall slanted at 5° outward from the floor. Odor stimuli were presented at a conical sniff port
located on the center of the slanted wall, 5 cm above the floor. A
photodetector mounted in the entrance to the sniff port monitored
stimulus sampling responses. A water reward cup with its own
photodetector was located 2.5 cm directly below the sniff port, and two
24 V panel lamps were located 10 cm to each side and 10 cm above the
water cup. Odor cues were generated by a 16-channel flow-dilution
olfactometer. The stimulus set was composed of 16 arbitrarily selected
volatile odors that were easily discriminable to the experimenters.
Half of the odors were common food scents (e.g., anise, almond,
peppermint, lemon, celery seed, cinnamon, banana, clove) and the others
were pure chemical odorants or extracts (e.g., geraniol, amyl acetate,
phenethyl alcohol, eugenol, terpineol, guiacol, damascone,
jasmopyrane), and each was diluted to 5% in propylene glycol.
Initially a clean airstream was generated from pressurized air that was
dehydrated with calcium chloride, cleaned with activated charcoal, and
then rehydrated with distilled water. This airstream was then split
such that half of it flowed continuously at a rate of 0.5 l/min,
serving to clear the odor channels during the intertrial interval
(ITI). During the last 2 sec of the ITI, the other half of the
airstream (0.5 l/min) was saturated with a selected odor and
then added to the clean airstream, resulting in a final stimulus flow
rate of 1.0 l/min. Odorized and clean airstreams were passed
through a three-way solenoid valve mounted immediately outside of, and
connected to, the sniff port. During the entire ITI the airstream was
diverted by this valve to a vacuum dump at 2 l/min. Because the
vacuum flow rate was greater than that of the input airstream, odors in
the sniff port were effectively eliminated during periods when no odor
was being presented. When a subject initiated an odor presentation by
breaking the sniff port photobeam at an appropriate time, the solenoid
valve was activated, allowing the odorized airstream to reach the sniff port; deactivation of this valve occurred immediately whenever the
subject withdrew its nose from the sniff port. Additionally, a fan
mounted on the top of the chamber was used to continuously exhaust air,
thereby ensuring that odors did not linger in the chamber between odor
presentations. All procedural events were controlled and behavioral
responses were recorded by a PC-compatible computer equipped with a
32-bit digital input/output board.
Behavioral procedures. Training on the cDNMS task proceeded
in a series of three phases. First, rats were given a minimum of two
60-trial sessions of shaping. A nose poke of ~250 msec (in the range
of 220 msec to 280 msec) into the sniff port resulted in the
presentation of an odor chosen on a pseudorandom basis from a set of
either 8 or 16 odors selected at random from a large stock of odorants.
A subsequent water port response terminated the odor presentation and
was reinforced with a 0.05 ml water reward. During this phase, the odor
presented on each trial always differed from that presented on the
immediately preceding trial. A 3 sec delay was imposed between trials;
the house lights were extinguished during the delay and subsequently
reilluminated to signal the availability of the next trial. Nose pokes
into the sniff port during the last 2 sec of the delay extended the
delay by an additional 2 sec.
In the second phase, rats learned the cDNMS task in daily sessions of
60-200 trials, using the full set of 16 odors. On each trial the end
of the ITI (memory delay) was signaled by illumination of the house
light, and the rat could then perform a nose poke of ~250 msec into
the sniff port to initiate stimulus onset. On half of the trials, the
odor was different from that presented on the previous trial (a
nonmatch or S+ trial) and a response to the water port within 5 sec
("go" or R+) was rewarded. On other trials, the odor was the same
as that presented on the previous trial (a match or S trial), and
water port responses on these trials were not reinforced; rats learned
not to make the water port response ("no-go" or R ) on these
trials. Errors of commission resulted in the immediate offset of the
house lights. On any trial when no water port response was made within
5 sec of the odor onset, the odor and house lights were turned off
simultaneously and the delay period began. Correct responses were
followed by a 3 sec delay; incorrect responses were followed by a 7 sec
delay. Incorrect responses on match trials were initially followed by one or two correction trials, that is, repetitions of the same match
trial. Daily training was provided until the rats reached a criterion
of 18 correct responses out of 20 consecutive trials. Once this
criterion was met, correction trials were no longer provided.
In the third stage, daily cDNMS sessions continued while we searched
for and recorded from cells. During these sessions the delay was held
constant at 3 sec for five of the six rats from which perirhinal cells
were recorded. In these rats, odor responses were evaluated for the
full set of 16 odors. The remaining rats were presented with odors from
the reduced set of eight odors and were tested with delays of both 3 and 30 sec. Each delay occurred pseudorandomly on half the trials of a
cDNMS session. The actual delay between the odor offset of one trial
and the odor onset of the next trial could be somewhat longer,
depending on the latency of a rat to initiate a trial after the onset
of the houselight signal. On each day, electrodes were surveyed for
cellular activity while the animals performed the cDNMS task. If no
cells were identified, the animals continued performing the task until
100 trials were completed to maintain performance. When the activity of
at least one cell with a suitable signal-to-noise ratio was observed,
the data recorder was started and a 300-500 trial cDNMS session was presented. After each session, the electrode was advanced 40 µm.
Data analysis. The analysis of neuronal firing
patterns was performed in two stages. First, all cells were assessed
for activity associated with specific trial events and behavioral acts
that occurred in the same sequence on each trial. This event
analysis focused on (1) the onset of the house lights signaling
the beginning of a trial; (2) entry into the sniff port initiating the
trial; (3) onset of the odor presentation; (4) removal of the nose from the sniff port, referred to henceforth as the "unpoke"; and (5) entry into the water port as the discriminative response to retrieve the reward. For each cell a set of graphic analyses was prepared to
display unit activity associated with each of these trial events. Each
analysis included a raster display of approximately 15 representative trials plus a summary histogram for all trials that displayed averaged
peri-event activity accumulated in 100 msec bins for 2 sec before and
after the event, plotted as a continuous line indicating average
spikes/second for each bin. To compare the present results with the CA1
recordings obtained from rats performing the same task (Otto and
Eichenbaum, 1992b ), this analysis was used to identify three general
functionally defined cell types: "cue-sampling cells," whose
activity changed maximally (either increased or decreased) while the
subject was sampling an odor; "reward-approach cells," whose
activity changed during the approach to the water cup and rewar
consumption; and "trial-initiation cells," whose activity changed
maximally just before or during the trial initiation. Because of our
specific interest in neural activity during the delay, an additional
category of cells was identified as "delay cells," and we focused
on firing during the middle of the shorter (3 sec) delay period.
Cue-sampling cells were operationally defined as those neurons whose
average change in activity was maximal during the period between odor
onset and 500 msec after odor onset; "delay" cells were defined as
those whose change in activity was maximal between 2 and 2.5 sec after the unpoke; reward-approach cells were defined as those whose change in
activity was maximal 100 msec before to 400 msec after the water port
entry; and trial-initiation cells were defined as those whose change in
activity was maximal 250 msec before to 250 msec after the sniff port
entry. The statistical significance of these changes was determined
using paired t tests (two-tailed) that compared activity
during the periods defined above with background activity defined as
the average firing rate during the 1 sec period immediately preceding
the onset of the house lights, a period that followed the defined
"delay" period and preceded the "trial initiation" period. Thus
this epoch is included within the overall memory delay, but it occurs
near the end of that period when delay-related activity might be
expected to be minimized, and so provides the best estimate of
background firing rate between trials. For all cue-sampling and
reward-approach units with significant (p < 0.05) changes in firing, an additional series of post hoc
analyses was applied to test whether firing rates changed
preferentially during trials with particular stimulus type (S+ or S )
and response type (R+ or R ) combinations as described below.
The second stage of analysis focused on the odor specificity of neural
activity associated with stimulus coding, including that reflecting
match-nonmatch comparisons, and during the memory delay. We first
designated the stimulus period as the 500 msec interval
immediately after the odor onset during which the rat was actively
sampling the odor and the memory period as the 500 msec
interval just before onset of the succeeding trial, that is, at the end
of the effective memory delay. At this time the rat was reliably
initiating the trial during which the previous odor would be compared
with the subsequent odor. One-way ANOVAs were used to identify
significant differences in the neuronal responses among the odor set
during the sensory and memory periods. Additionally, to examine whether
the activity during the memory period varied according to the length of
delay, cells recorded in sessions in which both the 3 and 30 sec delays
were used were subjected to a two-way factorial analysis with delay
length and odor as the two factors. Newman-Keuls post hoc
comparisons were used to test differences between pairs of means when
necessary.
Additional analyses of differential match-nonmatch responses focused
on cells that showed odor-selective activity during the stimulus
period. Our aims were to determine whether odor-selective cells tended
to show enhanced or suppressed responses to immediate stimulus
repetition and whether the match-nonmatch response was larger for the
odors to which the cell is tuned than for other odors. One analysis was
focused on individual cells and used a two-way ANOVA (2 × 2) to
compare responses on match versus nonmatch trials for the "best"
versus "worst" odor, that is, for those odors associated with the
highest and lowest mean firing during the cue-sampling period. A second
analysis was focused on the entire population of cells that showed
odor-selective activity during odor sampling. We first categorized
activity as "enhanced" if the mean firing rate was higher on match
than nonmatch trials or "suppressed" if the firing rate was lower
on match than nonmatch trials. Then the difference between match and
nonmatch firing rates was computed, and paired t tests were
performed separately on the groups of enhanced and suppressed cells to
compare the difference scores between the best versus the worst odor
stimulus.
RESULTS
Electrode localizations
Reconstructions of the electrode tracks are provided in Figure
1. Because of the angle of electrode penetrations,
recordings in the perirhinal and entorhinal cortices were almost
exclusively in superficial layers. Recordings in the perirhinal cortex
were primarily within the dorsal bank of the rhinal sulcus, with some sites bordering on ectorhinal cortex and a few sites in the ventral bank of the rhinal sulcus. Recordings in the entorhinal area were restricted to the lateral entorhinal cortex. In the subiculum, recordings were within the ventral part of the subiculum near the CA1
border. Analysis of recording sites along the electrode penetrations
did not reveal any systematic localization of any of the functionally
characterized cell types described below; however, there was a distinct
bias for neighboring cells to have similar functional correlates.
Fig. 1.
Reconstructions of the electrode tracts for each
of the subjects. Thick lines indicate the extent of loci
of analyzed cellular activity. Sections are identified from the Swanson
(1992) atlas. ab, Angular bundle; alv,
alveus; ECT, ectorhinal cortex; ENTl, lateral entorhinal cortex; m, molecular layer;
PERI, perirhinal cortex; PIR, piriform
cortex; rf, rhinal fissure; sp, pyramidal layer; sr, stratum radiatum; SUBv,
ventral subiculum; TEv, ventral temporal association
area; TR, postpiriform transition area.
[View Larger Version of this Image (43K GIF file)]
Behavioral performance
Rats acquired the cDNMS task rapidly, with all animals reaching
the performance criterion in <400 trials. Rats tested with the 16 odor
set continued to perform accurately during the recording sessions,
averaging 92.1% correct. Compared with the performance of rats using
the 16 odor set, the performance of rats tested with the 8 odor set was
significantly reduced at both delays, averaging 84.9% correct at the 3 sec delay (t(7) = 3.63; p < 0.01) and 70.3% at the 30 sec delay (t(7)=
8.89; p < 0.001). Furthermore, the performance of
those rats tested with the 8 odor set was significantly higher at the 3 sec delay than at the 30 sec delay (t(6) = 4.26; p < 0.01). This pattern of decreased cDNMS performance
associated with reduced odor set size (higher inter-item interference)
and longer memory delays parallels the earlier findings of Otto and Eichenbaum (1992a) .
Neuronal activity related to behavioral events
A total of 378 units were isolated from perirhinal cortex
(n = 177), lateral entorhinal cortex (n = 128), and subiculum (n = 73). The units were recorded
during the course of 56 recording sessions, averaging 6.2 sessions per
animal. Table 1 summarizes the results from the analysis
of neuronal activity associated with the four specific behavioral
events listed above, segregating the different cell types according to
whether the firing changes occurred primarily during the stimulus onset
period or during the delay period. Consistent with the findings on
hippocampal CA1 cells recorded from rats performing the same cDNMS task
(Otto and Eichenbaum, 1992b ), as well as that from odor discrimination tasks (Eichenbaum et al., 1987 ; Wiener et al., 1989 ), the activity of
single neurons in these areas was correlated with each identifiable event occurring during cDNMS performance. Indeed, a large proportion of
neurons from each of the regions recorded (entorhinal 91.4%, perirhinal 89.8%, subiculum 100%) displayed activity that could be
statistically related to one of the four behavioral events. This
behavior-related activity was in the form of an increase in some units,
a decrease in others, and both an increase and decrease in still other
units. Most perirhinal and entorhinal cells showed increased firing,
whereas most subiculum cells showed decreases in firing. Examples of
responses for each of the four categories of cells identified in the
event analysis are displayed in Figure 2.
Table 1.
Percentage of cells (and n) with changes in
activity associated with trial
events
| Correlate |
Perirhinal
(n = 177) |
Lateral entorhinal (n = 128) |
Subiculum (n = 73) |
|
| Cue-sampling
cells |
43.5 (77) |
43.0 (54) |
47.9 (35) |
| Delay
cells |
2.8 (5) |
14.8 (19) |
1.4 (1) |
| Reward-approach
cells |
11.3 (20) |
4.7 (6) |
5.5 (4) |
| Trial-initiation
cells |
32.2 (57) |
28.9 (37) |
45.2 (33) |
| No
correlate |
10.2 (18) |
9.4 (12) |
0.0 (0) |
|
|
|
Fig. 2.
Examples of parahippocampal neurons with activity
related to different trial events. For the present figure and all
subsequent figures of this format, each panel includes a raster display
of representative trials and a summary histogram of peri-event activity accumulated across all trials in 100 msec bins and displayed in a
continuous line showing average spikes/second for each bin during the 2 sec period before and after the synchronization event. The n shown on each panel refers to the number of cDNMS
trials over which unit activity was averaged. A, A
perirhinal cue-sampling cell that began firing during trial initiation
and fired maximally during odor sampling. Vertical tic
marks to the right of the synchronization point
indicate the unpoke. B, A perirhinal reward-approach
cell that fired maximally just before the water port response.
Vertical tic marks to the left of the
synchronization point indicate the unpoke. C, A
subiculum trial-initiation cell whose firing decreased during trial
initiation (the poke). D, An entorhinal delay cell that
fired maximally during the intertrial (delay) interval.
[View Larger Version of this Image (19K GIF file)]
Cue-sampling cells
Neuronal activity during cDNMS performance strongly reflected the
cue-sampling event (Table 1). Peak changes in firing during the
cue-sampling phase varied among units, with perirhinal units often
showing a striking synchronization to odor onset, offset, or both of
these events. Figure 3 shows a perirhinal unit that exhibited a suppression of activity after the nose poke, a subsequent marked activity increase sharply time-locked to the odor onset, and
finally a return to its basal firing rate synchronized with the
cessation of odor sampling (the unpoke). Much less evidence of this
stimulus synchronization was observed in lateral entorhinal and
subiculum units.
Fig. 3.
Example of a perirhinal cue-sampling cell that
showed a rapid increase in activity after the odor onset
(A) and then a decrease in activity that was less
sharply time-locked to the unpoke (B). Vertical tic marks to the left and
right of the synchronization point indicate the
occurrence of a poke and an unpoke respectively (A); tic marks to the
left of the synchronization point indicate the
occurrence of the odor onset (B).
[View Larger Version of this Image (22K GIF file)]
During the cue-sampling phase of each cDNMS trial, subjects must not
only store information about the current trial but also must determine
whether the current cue is a "match" or a "nonmatch" for the
previous sample. To assess whether the activity of the cue-sampling
units identified in the preliminary event analysis reflected
match-nonmatch processing across all odor comparisons, three
additional statistical analyses were conducted. First, cellular activity was compared for all nonmatch (S+) versus all match trials (S ) using a two-tailed t-test. To the extent that
performance was accurate, however, differences in firing on nonmatch
trials versus match trials could be attributable to the match-nonmatch distinction or the difference in the associated response (R+ vs R ).
To decide between these two alternatives, additional post hoc
t tests were performed comparing unit activity between match and
nonmatch trials that ended in the same behavioral response, that is,
S+R+ versus S R+ trials, and between match and nonmatch trials that
ended in different behavioral responses, that is, S+R+ versus S R
trials. Cells whose activity was statistically different between match
and nonmatch trials and in both post hoc tests were
designated "strong" match-nonmatch cells, and cells who only
differed in S+ versus S and S+R+ versus S R+ comparisons were
designated "weak" match-nonmatch cells, a distinction made in our
previous analysis of hippocampal neurons (Otto and Eichenbaum, 1992b ).
Unfortunately, because of accurate task performance, there were very
few S R+ trials for some cells (<2% of the total trials in the most
extreme case). Correspondingly, these analyses were restricted to
sessions in which performance was poorest, that is, where substantial
numbers of errors of commission were made. Thus, the complete set of
comparisons could not be performed for the 61 cue-sampling units
recorded from the perirhinal cortex of rats tested with the 16 odor
set, or for 11 of the cue-sampling units recorded from the lateral
entorhinal area of rats tested with the 8 odor set. Of the remaining
cue-sampling cells, 7 of the 43 units recorded from lateral entorhinal
cortex and 6 of the 35 units recorded from the subiculum were
designated as "strong" or "weak" match-nonmatch cells (Table
2). An example of a "strong" match-nonmatch cell is shown in Figure 4. This
entorhinal unit showed a marked increase in activity time-locked to the
unpoke on S+R+ (Fig. 4A) trials, but showed no
appreciable increase in activity on S R+ (Fig. 4B)
or S R (Fig. 4C) trials. Match-nonmatch cells were about
equally divided in their preference for either match or nonmatch
trials. Additional analyses aimed to identify neural activity
associated with match-nonmatch comparisons for specific sample odors
are provided below.
Table 2.
Match-nonmatch cells
| Correlate |
Perirhinal |
Lateral entorhinal |
Subiculum |
|
| Cue-sampling
cells |
(n
= 16) |
(n = 43) |
(n = 35) |
| Strong
match-nonmatch |
- |
4 |
3 |
| Weak
match-nonmatch |
- |
3 |
3 |
| Response |
2 |
10 |
4 |
| Nonspecific |
14 |
26 |
25 |
| Reward-approach
cells |
(n = 4) |
(n
= 5) |
(n
= 4) |
| Match-nonmatch |
- |
3 |
- |
| Nonspecific |
4 |
2 |
4 |
|
|
|
Fig. 4.
Example of a "strong nonmatch" entorhinal cell
whose firing was closely synchronized to the unpoke on correct nonmatch
trials (A) but showed no clear increase in firing
during this period on correct match trials (B) or
on errors of commission (C).
Vertical tic marks to the left of the
synchronization point indicate the occurrence of a sniff port
poke.
[View Larger Version of this Image (18K GIF file)]
Other units identified in the present analysis reflected the response
(i.e., R+ or R ) that follows the test odor delivery better than the
match-nonmatch comparison between two successive odors. For such cells
the analyses indicated no significant difference in firing rate on S+R+
versus S R+ trials, but differences in firing on S+R+ versus S R
trials. These firing characteristics were identified in 16 units across
all the PHR areas (Table 2). Both of the "response" cells in
perirhinal cortex displayed increased activity on R+ compared with R
trials, whereas three lateral entorhinal cells and two subiculum cells
preferred R+, and seven lateral entorhinal cells and two subiculum
cells preferred R trials.
Reward-approach cells
The increased firing of reward-approach cells immediately before
and during the water response could reflect either the water response
itself or some form of feedback associated with the outcome of the
response (reinforcement or nonreinforcement). Changes in unit activity
that occurred during this period on both S+R+ and S R+ trials, or on
S+R+ trials only, can be accounted for by either alternative. In
contrast, if the change in activity occurred only during S R+ trials,
the firing cannot simply be associated with the water response per se,
but must in some way reflect the outcome of the response. As in the
analysis of the cue-sampling match-nonmatch cells, some units
identified as reward-approach units were excluded from this analysis
because of insufficient S R+ trials. Of the 13 reward-approach cells
that could be analyzed (Table 2), some in lateral entorhinal cortex
fired significantly more on match trials, and the others exhibited no
preference for either trial type. Figure 5 shows an
example of a "match" reward-approach cell recorded from lateral
entorhinal cortex. On both S+R+ (Fig. 5A) and S R+ (Fig.
5B) trials, firing in this cell increased ~300 msec before
the rat made the water port response, but reached a greater peak on the
S R+ trials. Note that in this example the differential increase was
apparent before the water delivery, suggesting that the difference
between the trial types was encoded before information (i.e., the
absence of a water reward), indicating an error of commission.
Fig. 5.
Example of a "match" reward-approach cell
recorded from entorhinal cortex. This cell displayed an increase in
firing that was closely time-locked to the water port response but was
significantly less active on correct nonmatch trials
(A) than during errors of commission
(B).
[View Larger Version of this Image (21K GIF file)]
Trial-initiation cells
Substantial proportions of the units from all three recording
sites were classified as trial initiation in the preliminary analysis
(Table 1). The activity of these units might have reflected the
incipient nose-poke behavior associated with the act of trial initiation or the maintenance or regeneration of an odor memory representation of the preceding sample odor. This issue will be addressed directly below in the analysis of stimulus-specific activity
during the trial initiation period.
Delay cells
Units identified as delay cells in the initial event analysis
(altered activity 2.0-2.5 sec after the unpoke) were most frequently recorded in the lateral entorhinal cortex, with considerably smaller proportions of this cell type in the perirhinal cortex and subiculum (Table 1). The firing pattern of these cells usually took the form of
an increase in firing rate, beginning soon after the trial offset
(house lights turned off), persisting for ~1-2 sec, and then
returning to baseline before the initiation of the subsequent trial.
Closer examination of these cells revealed that responses usually
occurred on S+R+ (i.e., rewarded) trials. Given that the trial offset
occurred almost immediately after the water port response, it may be
that this "delay-related" activity reflects the consummatory
response rather than sensory information about the preceding sample
cue. An example is presented in Figure 6. This cell
displayed a marked increase in activity that occurred around the time
of the trial offset on S+R+ trials, but no such increase occurred on
either S R or S R+ trials.
Fig. 6.
Example of an entorhinal delay cell that displayed
increased firing immediately after the trial offset on correct match
trials (A), but no such increase on correct
nonmatch trials (B) or on errors of commission
(C).
[View Larger Version of this Image (22K GIF file)]
Odor-specific neuronal activity during stimulus and
memory periods
Stimulus period
All units, rather than only those units classified as cue-sampling
cells in event analysis, were included in the assessment of
odor-selective activity during odor sampling. This inclusive approach
was taken because of the possibility that a response that was highly
odor-selective might be greatly diluted by averaging across a large
number of odors, as was done in the event analysis, resulting in an
overall nonsignificant firing rate change.
One-way ANOVAs on mean activity during the first 0.5 sec of the
stimulus sampling period revealed that more than one third (45 of 128 units; 35.2%) of lateral entorhinal neurons had significant odor-selective responses, as did somewhat lesser proportions of perirhinal (20 of 177 units; 11.3%) and subicular (18 of 73 units; 24.7%) units. Most cells showed complex patterns of differential odor
responses involving varying degrees of activation across the odor set;
however, in some cells, activity during the sensory period was
significantly greater for one particular odor. Examples of highly
selective activation in perirhinal, lateral entorhinal, and subiculum
cells are shown in Figure 7. Post hoc
comparisons showed that the perirhinal cell (Fig. 7A) had a
significantly greater response to odor 14 than to any of the other 15 sample odors. Similarly, the lateral entorhinal cell (Fig.
7B) fired more selectively to odor 6, and the subiculum cell
(Fig. 7C) to odor 2. To provide a more detailed
representation of the time course of neural activity in an
odor-selective cell, Figure 8 shows the firing pattern
of the lateral entorhinal unit displayed in the previous figure across
time. This unit showed a clear increase in selective activity during
presentation of odor 6, reaching its peak at ~200 msec after odor
onset, and returning to baseline after termination of the odor
presentation (typically 400-700 msec after odor onset).
Fig. 7.
Examples of the odor-selective activity
during 500 msec periods of stimulus sampling (see time
line at top of figure) in neurons recorded from
(A) perirhinal cortex
(F(15,209) = 3.93; p < 0.01), (B) entorhinal cortex
(F(7,216) = 14.04; p < 0.01), and (C) the subiculum
(F(7,323) = 23.22;
p < 0.01). All three neurons showed activity that
was significantly elevated during the sampling of only one odor of the
8 or 16 odor set.
[View Larger Version of this Image (43K GIF file)]
Fig. 8.
Activity of the lateral entorhinal cell from
Figure 3B during the 2 sec before and after the odor
onset for each of the eight odors with which the subject was tested.
The firing of this cell significantly increased during the cue-sampling
period only for odor 6.
[View Larger Version of this Image (31K GIF file)]
Additional analyses were performed on odor-selective cells to determine
whether responses during immediate stimulus repetition (match trials)
were enhanced or suppressed as compared with activity when a stimulus
was not preceded by itself (nonmatch trials). These analyses included
all cells that showed odor-selective activity but focused on
comparisons of responses to the odor associated with the highest
average firing rate during stimulus sampling (best odor) versus the
odor associated with the lowest average firing rate (worst odor). In
cell-by-cell analyses, 17 of the 83 odor-selective cells (3 of 20 perirhinal, 12 of 45 entorhinal, 2 of 18 subiculum) had significantly
different activity on match versus nonmatch trials either as a main
effect along with a main effect for odor, or in the interaction of
odor × trial type, or both. All three perirhinal cells showed
suppression of activity on match trials, but both subiculum cells
showed match enhancement. In entorhinal cortex, seven of the cells
showed suppression on match trials and five showed match enhancement.
Of these cells, six showed both odor and trial-type effects, or a
significant interaction between these factors, indicating
odor-selective match suppression or enhancement by individual cells
(Fig. 9).
Fig. 9.
Examples of odor-selective match suppression and
match enhancement. Solid lines, Averages for match
trials; dotted lines, averages for nonmatch trials.
A, An entorhinal cell that showed a clear response only
to the best odor on nonmatch trials and suppression of this response on
match trials (selectivity for odor: F(1,92) = 10.55, p < 0.01; selectivity for nonmatch over match trials: F(1,92) = 20.86, p < 0.01). B, An entorhinal cell that showed a clear odor-selective response only on match trials (selectivity for odor: F(1,92) = 19.56, p < 0.01; selectivity for match over nonmatch
trials: F(1,92) = 8.23, p < 0.01).
[View Larger Version of this Image (13K GIF file)]
In yet a further analysis that took into consideration all
odor-selective cells, we first separated those cells that had greater average firing on immediate stimulus repetition, that is, showed match
enhancement, from those that had lower average firing on stimulus
repetition, that is, showed match suppression. Then, in separate paired
t tests, the amount of enhancement or suppression was
compared for the best versus worst odor stimulus for each cell. The
results of this analysis (Fig. 10) indicated that an approximately equal numbers of cells showed match enhancement (n = 44) or suppression (n = 39). The
amount of match-enhancement (t(43) = 3.22;
p < 0.002) and match-suppression
(t(38) = 3.81; p < 0.001) was
substantially greater for the best than the worst odor. Although
relatively few cells individually showed statistically significant
odor-specific match-nonmatch effects, when the analyses on match and
nonmatch responses were combined, the cell population demonstrated
robust odor-selective match enhancement and match suppression.
Fig. 10.
Differences in firing on match minus nonmatch
trials for all odor-selective cells categorized as enhanced or
suppressed during stimulus repetition.
[View Larger Version of this Image (24K GIF file)]
Memory period
Using the same rationale as in the analysis of odor specificity
during cue sampling, all units were included in the analysis of
odor-selective responses during the delay. ANOVAs revealed that 14 of
the 177 perirhinal units (7.9%), 14 of the 128 lateral entorhinal
units (10.9%), and 9 of the 73 subicular units (12.3%) exhibited
odor-selective activity at the end of the memory delay. In the examples
shown in Figure 11, post hoc comparisons
showed that unit activity was significantly greater when one particular odor was presented on the previous trial. The perirhinal cell fired at
a greater rate at the end of the delay after presentation of odor 15 than after any other odor, the entorhinal cell fired selectively at the
end of the delay after odor 7, and the subiculum cell fired selectively
after odor 6.
Fig. 11.
Examples of odor-selective activity during
the final 500 msec of the memory delay (see time line)
in neurons recorded from (A) perirhinal cortex
(F(15,216) = 1.94; p < 0.05), (B) entorhinal cortex
(F(7,317) = 4.57; p < 0.01), and (C) the subiculum
(F(7,281) = 2.79; p < 0.01). All three neurons were maximally responsive during
this period when one particular odor of the 8 or 16 odor set had been
presented on the preceding trial.
[View Larger Version of this Image (52K GIF file)]
To determine the duration over which odor memory representations can be
maintained in the PHR, we evaluated odor specificity at the end of 3 sec delays as compared with that at the end of 30 sec delays. All units
recorded from subjects tested with 3 and 30 sec delays were subjected
to a two-way factorial ANOVA (odor × delay). Substantial
fractions of neurons in each of the three areas displayed
odor-selective responses, regardless of delay. Of the 128 lateral
entorhinal cells analyzed, 10 (7.8%) exhibited odor-selective firing,
as did 3 (10.0%) of the 30 perirhinal units and 8 (11.0%) of the 73 subicular units. Figure 12A shows a
lateral entorhinal cell that maintained similar patterns of firing in
the form of selective activation after presentation of odor 8 at the
end of both 3 and 30 sec delays. Notably, we observed two distinct
forms of neural activity across the delay yielding similar sensory
period and subsequent memory period firing patterns. In some cells,
odor-selective patterns were maintained above baseline throughout short
(Fig. 13A) and in some cases long delays
(not shown). In other cells, odor-selective patterns that appeared
during cue sampling disappeared early in the delay but were reinstated
just before the succeeding stimulus onset (Fig. 13B).
Fig. 12.
Examples of the three different categories of
neurons obtained from the factorial analysis of odor and delay length.
A, An entorhinal cell that displayed odor-selective
activity at the end of the memory delay that was unaffected by the
length of the delay (main effect of odor:
F(7,221) = 9.34; p < 0.01). B, An entorhinal cell that was selectively active
for one particular odor at the end of the 3 sec delay but not at the
end of the 30 sec delay (main effect of odor:
F(7,272) = 4.10, p < 0.01; odor × delay interaction:
F(7,272) = 3.72, p < 0.01). C, A perirhinal cell that fired more at the end
of 3 sec delays, but whose activity did not differ significantly across
the odor set (main effect of delay: F(1,326) = 5.59; p < 0.05).
[View Larger Version of this Image (34K GIF file)]
Fig. 13.
Examples of cells that showed odor-selective
delay activity. A, An entorhinal cell that showed
odor-selective activity above baseline throughout the short but not the
long delay (odor × delay interaction:
F(7,272) = 8.84; p < 0.01). B, An entorhinal cell that "recalled" the
odor-selective sensory-evoked activity pattern at the end of the delay
(main effect of odor: F(7,221) = 7.83; p < 0.01).
[View Larger Version of this Image (45K GIF file)]
Fewer units recorded in lateral entorhinal cortex (6 of 128 units;
4.7%) and subiculum (3 of 73 units; 4.1%), and none of 30 units in
the perirhinal cortex, exhibited an odor-specific change in activity
that was also dependent on the length of the delay. Furthermore,
examination of the magnitude of the odor-specific and delay
length-dependent entorhinal and perirhinal cells revealed no clear
tendency for cells to exhibit better specificity at either of the
delays. Thus only three of the six entorhinal cells and one of the
three subiculum cells that showed odor- and delay-selective activity
displayed greater specificity at the 3 sec delay than at the 30 sec
delay, as might be expected if these cells "forgot" the sample
stimulus. Figure 12B shows an example of an
entorhinal unit that displayed strong odor selectivity for odor 5 at
the end of 3 sec delay but not at the end of the 30 sec delay.
Other cells in each area, however, fired differentially at the short
versus long delays, with or without odor-selective responses. Substantial proportions of lateral entorhinal units (21 of 128 units;
16.4%) and perirhinal units (5 of 30 units; 16.7%) exhibited a
significant delay effect, as did some subiculum units (3 of 73 units;
4.1%). Examination of the magnitude of these responses revealed that
the firing of entorhinal units was not preferentially associated with
either delay, with 11 of the 21 neurons displaying greater activity
during the 3 sec delay. By contrast, all three subiculum units whose
activity varied with the delay showed greater firing at the end of the
3 sec delay, and the activity of four of the five perirhinal units was
greatest at the end of the 30 sec delay. An example of a perirhinal
unit that fired significantly more at the end of 3 sec delays, but did
not show statistically significant odor selectivity, is displayed in
Figure 12C. When the data across these analyses are
combined, the main finding is that firing patterns frequently vary with
the length of the delay, but the pattern of differential odor-selective
activity is largely maintained even across a long delay.
DISCUSSION
Behavioral correlates of neuronal activity in the PHR
Neuronal activity in the PHR reflected all identifiable behavioral
events in the DNMS task. Many of the behavioral correlates likely
reflect specific behaviors, e.g., odor investigation, reward consumption, and movements into or out of the sniff port. Other responses that were closely time-locked to stimulus onset and offset
may reflect sensory-evoked responses. Yet other firing patterns that
closely followed the match or nonmatch stimulus relations seem to
reflect some general cognitive operation associated with all
recognition judgments. More compelling evidence that the PHR is
involved in stimulus-specific memory processing comes from comparisons
of neural responses across the stimulus set described below.
The broad range of responses observed in the PHR is not surprising from
the perspective of the anatomical inputs from widespread cortical
regions, including all unimodal and polymodal sensory association
areas, sensorimotor cortex, and multiple prefrontal and limbic cortical
areas (Deacon et al., 1983 ; Burwell et al., 1995 ). The finding that
nearly all cells reflected sensory, behavioral, and cognitive events
within this task is consistent with the massive convergence of cortical
inputs onto the PHR and the importance of this region to performance on
the DNMS task.
Stimulus-specific "sensory" responses and "memory"
correlates in the PHR of rats and monkeys
Sustained stimulus-selective neuronal activity has been observed
in cells recorded from several cortical association areas, including
the inferotemporal (Fuster and Jervey, 1981 ; Miyashita and Chang, 1988 ;
Fuster, 1990 ) and prefrontal cortices (Goldman-Rakic et al., 1990 ) in
monkeys and the auditory cortex in rats (Sakurai, 1990a ). There have
also been several reports of sensory- and memory-related activity in
the PHR (Sakurai, 1990b ; Miller et al., 1991 , 1993 ; Riches et al.,
1991 ; Quirk et al., 1992 ; Fahy et al., 1993 ; Li et al., 1993 ; Miller
and Desimone, 1994 ; Zhu and Brown, 1995 ; Zhu et al., 1995 ). In
particular, Brown and colleagues (Brown, 1996 ) and Miller and
colleagues (Miller et al., 1991 , 1993 ; Miller and Desimone, 1994 )
observed selective visually driven activity in the perirhinal and
entorhinal areas of monkeys performing visually guided match and
nonmatch to sample tasks. In those studies the predominant memory
correlate was reduced activation on repetition of a sample cue, and
this response was stimulus specific; however, Miller and colleagues
(Miller et al., 1991 , 1993 ; Miller and Desimone, 1994 ) also noted cells
with sustained delay activity, which ended on immediate presentation of
another cue, as well as enhanced activity when a match stimulus was
repeated after intervening stimuli. Recently, Zhu and colleagues (Zhu
and Brown, 1995 ; Zhu et al., 1995 ) also observed lasting
stimulus-specific decremental sensory responses in the rat perirhinal
and entorhinal cortex, and these responses were also sustained through
intervening stimulus presentations.
In the present study, cells throughout the PHR of rats demonstrated
sustained stimulus-selective activity during the memory delay. In some
cases the odor-specific representation was maintained above baseline
activity throughout the delay, and in other cases the activity pattern
during odor sampling disappeared and then was "recalled" at the end
of the delay. These observations suggest the existence of explicitly
sustained sensory representations and subthreshold encodings that can
be enhanced in anticipation of the matching event. In addition,
equivalent proportions of parahippocampal neurons showed
stimulus-selective match enhancement or match suppression of activity
during a repeated stimulus. One possible explanation for both types of
responses is that these firing patterns reflect the separate outcomes
of equally frequent "match" and "nonmatch" judgments.
Alternatively, the combination of enhancement and suppression could
reflect competitive cellular interactions during reestablishment of a
familiar stimulus representation. Regardless of the basis of these
correlates, the capacity of parahippocampal neurons to identify
specific match and nonmatch comparisons for a preceding cue indicates
that this area contains sufficient information to support the
recognition judgment.
Observations on the memory correlates of neuronal activity in the
hippocampus compared with that in the PHR
The characteristics of PHR cells described above differ in
important ways with observations on hippocampal neurons recorded in
animals performing DNMS tasks. In the most directly comparable study,
Otto and Eichenbaum (1992b) recorded the activity of CA1 neurons from
rats performing the same odor-guided cDNMS task used here. Some aspects
of PHR and hippocampal neuronal activity patterns are similar. In both
the PHR and the hippocampus, cellular activity reflects virtually all
identifiable trial events, including trial initiation, stimulus
sampling, discriminative responses, and appetitive behaviors. This
observation is consistent with the close and bidirectional connections
between these areas and likely reflects their interactions as an
interconnected system; however, the two areas differ strikingly in the
extent to which neural activity reflects some of the critical aspects
of stimulus coding relevant to recognition memory. In particular,
unlike cells in the PHR, CA1 neurons exhibited none of the three
characteristics identified above as important for the recognition
memory demands of the cDNMS task. A subset of the CA1 cells was active
during stimulus sampling, but these cells did not show odor-selective
activity or persistent firing throughout the delay or stimulus-specific
enhancement or suppression on stimulus repetition. Rather, the CA1
cells fired briefly during some part of the delay, perhaps reflecting
ongoing behaviors that occurred at that time, and their activity
reflected the abstract match-nonmatch relations between sample and
choice stimuli. These findings are similar to results from other
studies of hippocampal cellular activity in animals performing DNMS
tasks. Thus, previous experiments that involved recording from
hippocampal neurons in rats (Sakurai, 1990b ) and monkeys (Brown et al.,
1987 ; Riches et al., 1991 ) found no evidence of stimulus-specific
encoding during the performance of DNMS tasks. Instead, similar to the
Otto and Eichenbaum (1992b) findings, each of these studies described
cellular activity related to the match and nonmatch judgments and
related behavioral responses.
Two functional components of the hippocampal system
The present data, combined with the results from other
recording and neuropsychological studies, indicate that the PHR
contains the necessary coding elements for identifying individual
stimuli, for maintaining individual stimulus representations across
long delays, and for mediating specific match-nonmatch comparisons. By
contrast, the hippocampus is not required for recognition of individual
stimuli, and hippocampal neurons do not encode specific cues during
recognition performance, nor do they show delay-related activity for
specific memory cues. Studies using other tasks that require more
elaborate memory processing, however, do indicate a role for the
hippocampus, albeit one that may be qualitatively different from that
of the PHR. Considerable evidence from studies on rats indicates the
importance of the hippocampus in spatial memory processing (O'Keefe
and Nadel, 1978 ; Nadel, 1991 ; Jarrard, 1993 ). These studies distinguish
a critical role for the hippocampus whenever the animal must learn
spatial relations among environmental stimuli and use the spatial
layout of these cues to guide behavior. Correspondingly, hippocampal
neuronal activity reflects the relevant spatial configuration of cues
in animals exploring open fields (O'Keefe, 1976 ). Eichenbaum and
colleagues (Eichenbaum et al., 1992 ; Cohen and Eichenbaum, 1993 ) have
argued that the involvement of the hippocampus in learning stimulus
organizations and using representations of relations among items should
be extended to a broader scope of relational dimensions rather than
only those of physical space. Indeed, recent evidence shows that
selective damage to the hippocampus results in impairments in the
flexible expression of learned odor organizations (Bunsey and
Eichenbaum, 1996 ; Dusek and Eichenbaum, 1997 ). Correspondingly,
hippocampal neuronal activity reflects a broad range of conjunctions or
relations among cues that are relevant to performance in various tasks, even in DNMS tasks in which relational coding is not critical to task
performance (Eichenbaum, 1996 ).
These neuropsychological and neurophysiological findings are consistent
with our proposal (Cohen and Eichenbaum, 1993 ; Eichenbaum et al., 1994 ;
Eichenbaum et al., 1995 ) that the hippocampal system can be divided
into at least two functionally distinct components: a PHR component
that supports persistent representations of individual items and a
hippocampal component that mediates representations of relevant
stimulus relationships. During the course of most memory performances,
these functions of the PHR and hippocampus likely operate cooperatively
and interactively. The PHR may store single items and episodes and
maintain persistent representations that are then accessed by the
hippocampus for interleaving into relational organizations that are
then stored in the cortex (Alvarez and Squire, 1994 ; McClelland et al.,
1995 ).
Finally, the present data speak to the issue of what specific areas
should be included within these functional components of the
hippocampal region. The current observations indicated similar firing
patterns of cells in the perirhinal cortex, lateral entorhinal cortex,
and subiculum, suggesting that all of these areas might be considered
functionally related. Other studies, however, have indicated that the
subiculum should be considered part of the hippocampus, both from an
anatomical view and from evidence for common function (Eichenbaum et
al., 1994 ). When combined with the present data, and consistent with
its intermediate position between the entorhinal cortex and
hippocampus, these findings show that the subiculum may contribute to
both functional mechanisms.
FOOTNOTES
Received Dec. 23, 1996; revised April 9, 1997; accepted April 11, 1997.
This work was supported by Grant MH51570 from the National Institute of
Mental Health. We thank Emma Wood and Pablo Alvarez for their comments
on an earlier version of this manuscript.
Correspondence should be addressed to Dr. Howard Eichenbaum, Laboratory
of Cognitive Neurobiology, Department of Psychology, Boston University,
64 Cummington Street, Boston, MA 02215. recognize the sample by selecting
REFERENCES
-
Aggleton J,
Hunt PR,
Rawlins JNP
(1986)
The effects of hippocampal lesions upon spatial and nonspatial tests of working memory.
Behav Brain Res
19:133-146[Web of Science][Medline].
-
Aggleton J,
Blint HS,
Rawlins JNP
(1989)
Effects of amygdaloid and amygdaloid-hippocampal lesions on object recognition and spatial working memory in rats.
Behav Neurosci
103:962-974[Web of Science][Medline].
-
Alvarez P,
Squire LR
(1994)
Memory consolidation and the medial temporal lobe: a simple network model.
Proc Natl Acad Sci USA
91:7041-7045[Free Full Text].
-
Bachevalier J,
Parkinson JK,
Mishkin M
(1985)
Visual recognition in monkeys: effects of separate vs. combined transection of fornix and amygdalofugal pathways.
Exp Brain Res
57:554-561[Web of Science][Medline].
-
Brown MW
(1996)
Neuronal responses and recognition memory.
Semin Neurosci
8:23-32.
-
Brown MW,
Wilson FA,
Riches IP
(1987)
Neuronal evidence that inferomedial temporal cortex is more important than hippocampus in certain processes underlying recognition memory.
Brain Res
409:158-162[Web of Science][Medline].
-
Bunsey M,
Eichenbaum H
(1996)
Conservation of hippocampal memory function in rats and humans.
Nature
379:255-257[Medline].
-
Burwell RD,
Witter MP,
Amaral DG
(1995)
Perirhinal and postrhinal cortices in the rat: a review of the neuroanatomical literature and comparison with findings from the monkey brain.
Hippocampus
5:390-408[Web of Science][Medline].
-
Cohen NJ,
Eichenbaum H
(1993)
In: Memory, amnesia, and the hippocampal system. Cambridge, MA: MIT.
-
Deacon TW,
Eichenbaum E,
Rosenberg P,
Eckmann K
(1983)
Afferent connections of the perirhinal cortex in the rat.
J Comp Neurol
220:168-190[Web of Science][Medline].
-
Dusek J, Eichenbaum H (1997) The hippocampus and memory for orderly
stimulus relations. Proc Natl Acad Sci USA, in press.
-
Eacott MJ,
Gaffan D,
Murray EA
(1994)
Preserved recognition memory for small sets, and impaired stimulus identification for large sets, following rhinal cortex ablations in monkeys.
Eur J Neurosci
6:1466-1478[Web of Science][Medline].
-
Eichenbaum H
(1996)
Is the rodent hippocampus just for "place"?
Curr Opin Neurobiol
6:187-195[Web of Science][Medline].
-
Eichenbaum H,
Pettijohn D,
Deluca AM,
Chorover SL
(1977)
Compact miniature microelectrode-telemetry system.
Physiol Behav
18:1175-1178[Medline].
-
Eichenbaum H,
Kuperstein M,
Fagan A,
Nagode J
(1987)
Cue-sampling and goal-approach correlates of hippocampal unit activity in rats performing an odor discrimination task.
J Neurosci
7:716-732[Abstract].
-
Eichenbaum H,
Otto T,
Cohen NJ
(1992)
The hippocampus: what does it do?
Behav Neural Biol
57:2-36[Web of Science][Medline].
-
Eichenbaum H,
Otto T,
Cohen NJ
(1994)
Two functional components of the hippocampal memory system.
Behav Brain Sci
17:449-472.[Web of Science]
-
Eichenbaum H,
Young BJ,
Bunsey MD
(1995)
Persisting questions about hippocampal function in memory.
In: Plasticity in the central nervous system: learning and memory (McGaugh JL,
Bermudez-Rattoni F,
Prado-Alcala R,
eds), pp 129-148. New York: Gilford.
-
Fahy FL,
Riches IP,
Brown MW
(1993)
Neuronal activity related to visual recognition memory: long term memory and the encoding of recency and familiarity information in the primate anterior and medial inferior temporal and rhinal cortex.
Exp Brain Res
96:457-472[Web of Science][Medline].
-
Fuster JM
(1990)
Inferotemporal units in selective visual attention and short-term memory.
J Neurophysiol
64:681-697[Abstract/Free Full Text].
-
Fuster JM,
Jervey JP
(1981)
Inferotemporal neurons distinguish and retain behaviourally relevant features of visual stimuli.
Science
219:952-955.
-
Gaffan D
(1974)
Recognition impaired and association intact in the memory of monkeys after transection of the fornix.
J Comp Physiol Psychol
86:1100-1109[Web of Science][Medline].
-
Gaffan D
(1994)
Dissociated effects of perirhinal cortex ablation, fornix transection, and amygdalectomy: evidence for multiple memory systems in the primate temporal lobe.
Exp Brain Res
99:411-422[Web of Science][Medline].
-
Gaffan D,
Murray EA
(1992)
Monkeys (Macaca fascicularis) with rhinal cortex ablations succeed in object discrimination learning despite 24-hr intervals and fail at matching to sample despite double sample presentations.
Behav Neurosci
106:30-38[Web of Science][Medline].
-
Gaffan D,
Gaffan EA,
Harrison S
(1984)
Effects of fornix transection on spontaneous and trained non-matching by monkeys.
Q J Exp Psychol
36:285-303.
-
Goldman-Rakic PS,
Funahashi S,
Bruce CJ
(1990)
Neocortical memory circuits.
In: Cold Spring Harbor symposia on quantitative biology, Vol LV, pp 1025-1038 Cold Spring Harbor, NY: Cold Spring Harbor Laboratory.
-
Jackson-Smith P,
Kesner RP,
Chiba AA
(1993)
Continuous recognition of spatial and nonspatial stimuli in hippocampal-lesioned rats.
Behav Neural Biol
59:107-119[Web of Science][Medline].
-
Jarrard LE
(1993)
Review: on the role of the hippocampus in learning and memory in the rat.
Behav Neural Biol
60:9-26[Web of Science][Medline].
-
Kesner RP,
Boland BL,
Davis M
(1993)
Memory for spatial locations, motor responses, and objects: a triple dissociation among the hippocampus caudate nucleus, and extrastriate visual cortex.
Exp Brain Res
93:462-470[Web of Science][Medline].
-
Kubie JL
(1984)
A driveable bundle of microwires for collecting single-unit data from freely moving rats.
Physiol Behav
32:115-118[Medline].
-
Li L,
Miller EK,
Desimone R
(1993)
The representation of stimulus familiarity in anterior inferior temporal cortex.
J Neurophysiol
69:1918-1929[Abstract/Free Full Text].
-
McClelland JL,
McNaughton BL,
O'Reilly RC
(1995)
Why there are complementary learning systems in the hippocampus and neocortex: insights from successes and failures of connectionist models of learning and memory.
Psychol Rev
102:419-457[Web of Science][Medline].
-
Meunier M,
Bachevalier J,
Mishkin M,
Murray EA
(1993)
Effects on visual recognition of combined and separate ablations of the entorhinal and perirhinal cortex in rhesus monkeys.
J Neurosci
13:5418-5432[Abstract].
-
Miller EK,
Desimone R
(1994)
Parallel neuronal mechanisms for short-term memory.
Science
263:520-522[Abstract/Free Full Text].
-
Miller EK,
Li L,
Desimone R
(1991)
A neural mechanism for working and recognition memory in inferior temporal cortex.
Science
254:1377-1379[Abstract/Free Full Text].
-
Miller EK,
Li L,
Desimone R
(1993)
Activity of neurons in anterior inferior temporal cortex during a short-term memory task.
J Neurosci
13:1460-1478[Abstract].
-
Miyashita Y,
Chang HS
(1988)
Neuronal correlate of pictorial short-term memory in the primate temporal cortex.
Nature
331:68-70[Medline].
-
Mumby DG,
Pinel JPJ
(1994)
Rhinal cortex lesions and object recognition in rats.
Behav Neurosci
108:11-18[Web of Science][Medline].
-
Mumby DG,
Wood ER,
Pinel JPJ
(1992)
Object-recognition memory is only mildly impaired in rats with lesions of the hippocampus and amygdala.
Psychobiology
20:18-27.
-
Murray EA
(1996)
What have ablation studies told us about the neural substrates of stimulus memory?
Semin Neurosci
8:13-22.
-
Murray EA,
Mishkin M
(1996)
40-minute visual recognition memory in rhesus monkeys with hippocampal lesions.
Soc Neurosci Abstr
22:281.
-
Nadel L
(1991)
The hippocampus and space revisited.
Hippocampus
1:221-229[Medline].
-
O'Keefe JA
(1976)
Place units in the hippocampus of the freely moving rat.
Exp Neurol
51:78-109[Web of Science][Medline].
-
O'Keefe JA,
Nadel L
(1978)
In: The hippocampus as a cognitive map. Oxford: Oxford UP.
-
Otto T,
Eichenbaum H
(1992a)
Complementary roles of orbital prefrontal cortex and the perirhinal-entorhinal cortices in an odor-guided delayed non-matching to sample task.
Behav Neurosci
106:763-776.
-
Otto T,
Eichenbaum H
(1992b)
Neuronal activity in the hippocampus during delayed non-match to sample performance in rats: evidence for hippocampal processing in recognition memory.
Hippocampus
2:323-334[Web of Science][Medline].
-
Quirk GJ,
Muller RU,
Kubie JL,
Ranck JB
(1992)
The positional firing properties of medial entorhinal neurons: description and comparison with hippocampal place cells.
J Neurosci
12:1945-1963[Abstract].
-
Riches IP,
Wilson FAW,
Brown MW
(1991)
The effects of visual stimulation and memory on neurons of the hippocampal formation and the neighboring parahippocampal gyrus and inferior temporal cortex of the primate.
J Neurosci
11:1763-1779[Abstract].
-
Rothblat LA,
Kromer LF
(1991)
Object recognition memory in the rat: the role of the hippocampus.
Behav Brain Res
42:25-32[Web of Science][Medline].
-
Sakurai Y
(1990a)
Cells in the rat auditory system have sensory-delay correlates during the performance of an auditory working memory task.
Behav Neurosci
104:856-868[Web of Science][Medline].
-
Sakurai Y
(1990b)
Hippocampal cells have behavioral correlates during the performance of an auditory working memory task in the rat.
Behav Neurosci
104:253-263[Web of Science][Medline].
-
Suzuki WA
(1996)
The anatomy, physiology and functions of the perirhinal cortex.
Curr Opin Neurobiol
6:179-186[Web of Science][Medline].
-
Suzuki WA,
Zola-Morgan S,
Squire LA,
Amaral DG
(1993)
Lesions of the perirhinal and parahippocampal cortices in the monkey produce long-lasting memory impairment in the visual and tactual modalities.
J Neurosci
13:2430-2451[Abstract].
-
Swanson LW
(1992)
In: Brain maps: Structure of the rat brain. Amsterdam: Elsevier.
-
Wiener SI,
Paul CA,
Eichenbaum H
(1989)
Spatial and behavioral correlates of hippocampal neuronal activity.
J Neurosci
9:2737-2763[Abstract].
-
Witter MP,
Groenewegen HJ,
Lopes da Silva Lohman AHM
(1989)
Functional organization of the extrinsic and intrinsic circuitry of the parahippocampal region.
Prog Neurobiol
33:161-254[Web of Science][Medline].
-
Zhu XO,
Brown MW
(1995)
Changes in neuronal activity related to the repetition and relative familiarity of visual stimuli in rhinal and adjacent cortex of the anaesthetised rats.
Brain Res
689:101-110[Web of Science][Medline].
-
Zhu XO,
Brown MW,
Aggleton JP
(1995)
Neuronal signaling of information important to visual recognition memory in rat rhinal and neighbouring cortices.
Eur J Neurosci
7:753-765[Web of Science][Medline].
-
Zola-Morgan S,
Squire LR,
Amaral DG
(1989a)
Lesions of the hippocampal formation but not lesions of the fornix or mamillary nuclei produce long-lasting memory impairment in the monkey.
J Neurosci
9:898-913[Abstract].
-
Zola-Morgan S,
Squire LR,
Amaral DG,
Suzuki WA
(1989b)
Lesions of perirhinal and parahippocampal cortex that spare the amygdala and hippocampal formation produce severe memory impairment.
J Neurosci
9:4355-4370[Abstract].
-
Zola-Morgan S,
Squire LR,
Ramus SJ
(1994)
Severity of memory impairment in monkeys as a function of locus and extent of damage within the medial temporal lobe memory system.
Hippocampus
4:483-495[Web of Science][Medline].
This article has been cited by other articles:

|
 |

|
 |
 
J. R. Manns and H. Eichenbaum
A cognitive map for object memory in the hippocampus
Learn. Mem.,
September 30, 2009;
16(10):
616 - 624.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
R. K. Olsen, E. A. Nichols, J. Chen, J. F. Hunt, G. H. Glover, J. D. E. Gabrieli, and A. D. Wagner
Performance-Related Sustained and Anticipatory Activity in Human Medial Temporal Lobe during Delayed Match-to-Sample
J. Neurosci.,
September 23, 2009;
29(38):
11880 - 11890.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
R. W. Komorowski, J. R. Manns, and H. Eichenbaum
Robust Conjunctive Item-Place Coding by Hippocampal Neurons Parallels Learning What Happens Where
J. Neurosci.,
August 5, 2009;
29(31):
9918 - 9929.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
N. Axmacher, C. E. Elger, and J. Fell
Working Memory-Related Hippocampal Deactivation Interferes with Long-Term Memory Formation
J. Neurosci.,
January 28, 2009;
29(4):
1052 - 1060.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
M. Tsanov and D. Manahan-Vaughan
Synaptic Plasticity from Visual Cortex to Hippocampus: Systems Integration in Spatial Information Processing
Neuroscientist,
December 1, 2008;
14(6):
584 - 597.
[Abstract]
[PDF]
|
 |
|

|
 |

|
 |
 
N. Axmacher, D. P. Schmitz, I. Weinreich, C. E. Elger, and J. Fell
Interaction of Working Memory and Long-Term Memory in the Medial Temporal Lobe
Cereb Cortex,
December 1, 2008;
18(12):
2868 - 2878.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
B. Tahvildari, A. A. Alonso, and C. W. Bourque
Ionic Basis of ON and OFF Persistent Activity in Layer III Lateral Entorhinal Cortical Principal Neurons
J Neurophysiol,
April 1, 2008;
99(4):
2006 - 2011.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
D. E. Hannula and C. Ranganath
Medial Temporal Lobe Activity Predicts Successful Relational Memory Binding
J. Neurosci.,
January 2, 2008;
28(1):
116 - 124.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
R. A. Koene and M. E. Hasselmo
First-In-First-Out Item Replacement in a Model of Short-Term Memory Based on Persistent Spiking
Cereb Cortex,
August 1, 2007;
17(8):
1766 - 1781.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
L. Castelli, G. Biella, M. Toselli, and J. Magistretti
Resurgent Na+ current in pyramidal neurones of rat perirhinal cortex: axonal location of channels and contribution to depolarizing drive during repetitive firing
J. Physiol.,
August 1, 2007;
582(3):
1179 - 1193.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
N. Axmacher, F. Mormann, G. Fernandez, M. X Cohen, C. E. Elger, and J. Fell
Sustained Neural Activity Patterns during Working Memory in the Human Medial Temporal Lobe
J. Neurosci.,
July 18, 2007;
27(29):
7807 - 7816.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
T. R. Stoub, L. deToledo-Morrell, G. T. Stebbins, S. Leurgans, D. A. Bennett, and R. C. Shah
Hippocampal disconnection contributes to memory dysfunction in individuals at risk for Alzheimer's disease
PNAS,
June 27, 2006;
103(26):
10041 - 10045.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
J. McGaughy, R. A. Koene, H. Eichenbaum, and M. E. Hasselmo
Cholinergic Deafferentation of the Entorhinal Cortex in Rats Impairs Encoding of Novel But Not Familiar Stimuli in a Delayed Nonmatch-to-Sample Task
J. Neurosci.,
November 2, 2005;
25(44):
10273 - 10281.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
K. Schon, A. Atri, M. E. Hasselmo, M. D. Tricarico, M. L. LoPresti, and C. E. Stern
Scopolamine Reduces Persistent Activity Related to Long-Term Encoding in the Parahippocampal Gyrus during Delayed Matching in Humans
J. Neurosci.,
October 5, 2005;
25(40):
9112 - 9123.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
K. Schon, M. E. Hasselmo, M. L. LoPresti, M. D. Tricarico, and C. E. Stern
Persistence of Parahippocampal Representation in the Absence of Stimulus Input Enhances Long-Term Encoding: A Functional Magnetic Resonance Imaging Study of Subsequent Memory after a Delayed Match-to-Sample Task
J. Neurosci.,
December 8, 2004;
24(49):
11088 - 11097.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
J. Magistretti, L. Ma, M. H. Shalinsky, W. Lin, R. Klink, and A. Alonso
Spike Patterning by Ca2+-Dependent Regulation of a Muscarinic Cation Current in Entorhinal Cortex Layer II Neurons
J Neurophysiol,
September 1, 2004;
92(3):
1644 - 1657.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
D. H. Lindquist, L. E. Jarrard, and T. H. Brown
Perirhinal Cortex Supports Delay Fear Conditioning to Rat Ultrasonic Social Signals
J. Neurosci.,
April 7, 2004;
24(14):
3610 - 3617.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
S. Datta, V. Mavanji, J. Ulloor, and E. H. Patterson
Activation of Phasic Pontine-Wave Generator Prevents Rapid Eye Movement Sleep Deprivation-Induced Learning Impairment in the Rat: A Mechanism for Sleep-Dependent Plasticity
J. Neurosci.,
February 11, 2004;
24(6):
1416 - 1427.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
R. Kajiwara, I. Takashima, Y. Mimura, M. P. Witter, and T. Iijima
Amygdala Input Promotes Spread of Excitatory Neural Activity From Perirhinal Cortex to the Entorhinal-Hippocampal Circuit
J Neurophysiol,
April 1, 2003;
89(4):
2176 - 2184.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
L. M. Frank, U. T. Eden, V. Solo, M. A. Wilson, and E. N. Brown
Contrasting Patterns of Receptive Field Plasticity in the Hippocampus and the Entorhinal Cortex: An Adaptive Filtering Approach
J. Neurosci.,
May 1, 2002;
22(9):
3817 - 3830.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
E. Fransen, A. A. Alonso, and M. E. Hasselmo
Simulations of the Role of the Muscarinic-Activated Calcium-Sensitive Nonspecific Cation Current INCM in Entorhinal Neuronal Activity during Delayed Matching Tasks
J. Neurosci.,
February 1, 2002;
22(3):
1081 - 1097.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
I. Zironi, P. Iacovelli, G. Aicardi, P. Liu, and D.K. Bilkey
Prefrontal Cortex Lesions Augment the Location-related Firing Properties of Area TE/Perirhinal Cortex Neurons in a Working Memory Task
Cereb Cortex,
November 1, 2001;
11(11):
1093 - 1100.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
G. Biella, L. Uva, and M. de Curtis
Network Activity Evoked by Neocortical Stimulation in Area 36 of the Guinea Pig Perirhinal Cortex
J Neurophysiol,
July 1, 2001;
86(1):
164 - 172.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
S. P. Wiebe and U. V. Staubli
Recognition Memory Correlates of Hippocampal Theta Cells
J. Neurosci.,
June 1, 2001;
21(11):
3955 - 3967.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
G. M. Muir and D. K. Bilkey
Instability in the Place Field Location of Hippocampal Place Cells after Lesions Centered on the Perirhinal Cortex
J. Neurosci.,
June 1, 2001;
21(11):
4016 - 4025.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
S. Datta
Avoidance Task Training Potentiates Phasic Pontine-Wave Density in the Rat: A Mechanism for Sleep-Dependent Plasticity
J. Neurosci.,
November 15, 2000;
20(22):
8607 - 8613.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
S. J. Ramus and H. Eichenbaum
Neural Correlates of Olfactory Recognition Memory in the Rat Orbitofrontal Cortex
J. Neurosci.,
November 1, 2000;
20(21):
8199 - 8208.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
J. M. Beggs, J. R. Moyer Jr., J. P. McGann, and T. H. Brown
Prolonged Synaptic Integration in Perirhinal Cortical Neurons
J Neurophysiol,
June 1, 2000;
83(6):
3294 - 3298.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
S. P. Wiebe and U. V. Staubli
Dynamic Filtering of Recognition Memory Codes in the Hippocampus
J. Neurosci.,
December 1, 1999;
19(23):
10562 - 10574.
[Abstract]
[Full Text]
[PDF]
|
 |
|
|

|