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Previous Article | Next Article
The Journal of Neuroscience, December 1, 1999, 19(23):10562-10574
Dynamic Filtering of Recognition Memory Codes in the Hippocampus
Sherman P. Wiebe and Ursula V. Stäubli Center for Neural Science, New York University, New York, New York 10003
ABSTRACT
TOP
ABSTRACT
INTRODUCTION
Principal cells of the dentate gyrus (DG), CA3, and CA1 subfields of the hippocampus were recorded in rat during performance of an odor-guided delayed nonmatch-to-sample task with distinct sample and test phases. The hippocampus was found to possess multiple encoding modes. In the sample phase, odor-selective activity was restricted primarily to CA1 and, to a lesser extent, CA3. Odor representations in half of these cells were predictive of subsequent performance (i.e., correct vs error) in the test phase. Cells in each hippocampal subfield maintained elevated or suppressed activity in the delay interval relative to pre-odor baseline, but were indiscriminate with regard to sample odor identity. In the test phase, the regional distribution of odor-selective activity was inverse to that for the sample: maximal in DG and minimal in CA1. The inverted distribution of odor selectivity was also observed for cells that discriminated match/nonmatch trial types. Most match/nonmatch cells exhibited greater activity on correct nonmatch than error match trials, indicating the presence of a hippocampal recognition memory signal on trials where recognition occurred and its absence on trials where recognition failed. These findings reveal the hippocampus as a highly dynamic encoding device, restricting perceptual stimulus information to different subfields (or none, in the delay phase) depending on memory task contingencies. Moreover, the reduction in cue-specificity of match/nonmatch comparison signals as they pass through the hippocampal trisynaptic circuit may contribute to a generalized recognition signal for use in guiding behavior.
Key words: delayed nonmatch-to-sample; dentate gyrus; CA3; CA1; odors; pyramidal cells; granule cells; spatial; match/nonmatch discrimination; intrahippocampal processing; dynamic filtering; recognition memory; generalization
INTRODUCTION
The delayed nonmatch-to-sample (DNMS) paradigm, commonly used to investigate recognition memory in animals, consists of three phases: sample item presentation followed by a delay interval, and then a recognition phase in which reward follows selection of the nonmatch from among one or more test items. Accurate performance requires the animal to first correctly encode the sample and then discriminate the test stimuli and perform a match/nonmatch (M/N) comparison with the sample held in memory. Although there remains some debate as to the relative contribution of the hippocampus proper versus adjacent cortical structures to DNMS performance (Jarrard, 1993
), there is evidence from lesion studies of both a hippocampal (Wood et al., 1993
Sample cue-specific neuronal activity has been found in associational cortical areas (e.g., piriform and orbitofrontal cortices) and the parahippocampal (perirhinal and entorhinal) cortical region (Schoenbaum and Eichenbaum, 1995
Cells with differential responses to matching versus nonmatching test stimuli have been found both in the parahippocampal cortical region and the hippocampus (Miller et al., 1991
To investigate the role intrahippocampal processing plays in this transformation and to compare hippocampal function during memory encoding and retrieval, DG, CA3, and CA1 principal cells were recorded in rats performing an olfactory DNMS task with distinct sample and test phases. Discriminant analysis and post hoc ANOVAs were used to characterize the functional correlates of cells with event-locked firing in relation to odor, position, and match/nonmatch encoding.
MATERIALS AND METHODS
Subjects
Adult male Long-Evans rats (n = 18; weight at time of surgery, 250-460 gm) were housed individually and given ad libitum food. Water was restricted to that earned during performance of the DNMS task, and to 1-2 hr per day at the end of each recording session. All animals were trained to stable DNMS performance before and after electrode implantation.Apparatus
The odor-cued DNMS task was conducted within a sound-attenuating Y-shaped chamber [sample arm, 36 × 23 × 59 (length × width × height) cm; test arms, 27 × 14 × 59 cm; central area, 33 × 23 × 59 cm] enclosed by an electrically grounded copper mesh grid (Fig. 1A). Nosepoke devices consisting of infrared photodetector and light-emitting diode pairs spanning a cylindrical port at the end of each arm were used to control successive DNMS phase transitions (e.g., sample phasedelay phase
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Figure 1. A, Y-shaped apparatus for 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 odor (either odor A or B). After 10 sec of odor exposure, a sample poke 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 response triggered the discharge of a 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 again turned on, prompting the rat to execute a sample nosepoke to initiate another trial. The identity of the sample odor and the location of the match and nonmatch test odors were randomized across trials. B, Schematic of DNMS Paradigm. C, Delay-dependent performance in the DNMS task. 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: On x-axis, 5 implies 0-5 sec, 10 implies 5-10 sec, etc.
Behavior
Illumination of a cue light above the sample port marked the start of the DNMS trial. The first sample nosepoke commenced a minimum 2 sec pre-odor period, after which a sample poke turned on the odor (either odor A or odor B). After a minimum of 10 sec of odor exposure, a sample poke terminated the odor and initiated a variable 1-50 sec delay period. The first poke in the sample arm after the delay interval 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 discriminated the odors around the entry point of the test arms. Occasionally the rat entered one arm and then, realizing it contained the match odor, backed out and entered the other arm, indicating that the match/nonmatch decision-making process extended right up to the final nosepoke at the end of the arms. The test odors (one in each arm) emanated continually from both 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. A nosepoke in the nonmatch arm resulted in a 0.05 ml water reward. A match nosepoke triggered a high-intensity flash discharge. 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 odors were randomized across trials. Figure 1B diagrams the behavioral events in the two-odor DNMS task, and Figure 1C shows the mean performance curve per session summed over all rats, with 100-250 trials per session. Delay-dependent performance ranged from 86% correct at 0-5 sec delays to 74% correct at 45-50 sec delays.Training procedure
Training on the two-odor DNMS task was accomplished in a series of four stages. In the first stage, the rat was trained to execute sequential nosepokes in the sample and test arms by placing 0.05 ml water incentives. After 15-20 sample and test pokes were completed, test-arm water rewards were made contingent on a preceding sample arm poke, which was no longer rewarded (stage two). Both stage one and two of training were conducted with the ceiling house light illuminated throughout. After successful completion of 50 sample poke90% correct had been accomplished over 20 consecutive trials. Once this occurred, the sample odor was switched, and the other odor was used until a percentage of correct responding of
Surgical procedure
When animals reached criterion performance on the DNMS task, they were surgically implanted with a microwire electrode array (NBLabs, Denison, TX; www.nblabslarry.com) consisting of two rows (row separation, 0.8 mm) of eight 50 µm Teflon-coated, stainless steel microwires (pair separation, 200 µm). A diagram of the microwire electrode recording array is shown in Figure 2A. To help eliminate low-frequency movement artifacts caused by active behaving animals, recording signals were subtracted from that of a reference wire located just posterior and at the same depth as the array. The reference wire had a deinsulated tip (200 µm) which, with its low impedance, served as a low-pass filter. The rat was anesthetized with a single intraperitoneal injection of sodium pentobarbital (50 mg/kg). Atropine was administered (0.1 mg/kg, i.p.) to reduce mucous secretions. Supplementary intraperitoneal pentobarbital injections (8 mg/kg) were given when necessary to assure deep anesthesia. Body temperature was maintained throughout surgery at 37°C with a thermal heating pad. After transfer to the stereotaxic apparatus (David Kopf), a midsagittal skin incision was made, soft tissue was retracted, and the periosteum of the skull was removed. Six stainless steel screws (Frederick Haer and Co.) were firmly attached to the skull, both to ensure proper anchoring of the probe array and for grounding purposes. A small oval craniotomy was then performed on the right parietal bone and the electrode assembly implanted vertically with a microdrive. The center pair of array electrodes was positioned at coordinates 4.0 mm posterior to bregma and 3.3 mm (2.8 mm) lateral to midline for CA3 (DG and CA1) placement. 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 ranging from 3.4-4.0 mm for CA3 to 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, and 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.
At the conclusion of recording, each subject was administered a lethal dose of sodium pentobarbital (100 mg/kg), and 40 µA current was passed for 1 sec through each of the 16 recording electrodes. The animal was then perfused transcardially with 0.9% saline/0.1% heparan followed by 10% buffered formalin. The brain was removed from the skull and stored in a 10% buffered formalin/30% sucrose/2% potassium ferrocyanide solution. This produced a Prussian blue reaction that aided the localization of the electrode tips (Fig. 2B). After the brain absorbed the solution (~36 hr), it was placed in 10% buffered formalin for an additional 24-48 hr. Coronal sections of 40 µm thickness were cut on a freezing microtome, mounted, and stained with cresyl violet to aid in 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.
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Figure 2. A, Diagram of microwire electrode recording array. The array consisted of two parallel rows of 50 µm stainless steel microwires (row separation, 800 µm; pair separation, 200 µm) oriented along the septotemporal axis of the hippocampus, positioned to record from the pyramidal cells in the CA3 and CA1 fields and the granule cells in the dentate gyrus. B, Histological verification of microwire placement in the principal cell layers. Examples of electrode placement in the dentate granule cell layer (top) and the CA3 (middle) and CA1 (bottom) pyramidal cell layers. The black line in each image marks the CA3/CA1 boundary. C, Time-amplitude window discrimination of extracellularly recorded action potentials. Up to four neurons could be discriminated per microwire channel. In the example shown, two distinct units with well defined waveform characteristics were discriminated. D, Physiological identification of principal cells by extracellular recording parameters. The mean firing rate of each cell during task performance was plotted against the duration of the negative phase of the extracellular waveform. Cells with low mean firing rates and large negative spike widths were categorized as principal cells. A linear cutoff was used in firing rate-spike width space to separate principal cells [1.1 ± 0.05 Hz; 305 ± 3 µsec (mean ± SEM); n = 1101] from interneurons (17.4 ± 1.13 Hz; 206 ± 6 µsec; n = 139).
Multineuron recording technique
A head stage (NB Labs, Dennison, TX) containing 17 standard field effect transistors (16 for the recording wires and one for the deinsulated reference wire) was used to connect to an 18 channel plastic connector (18th lead connected to the skull screw and used as ground), cemented to the animals head. High-fidelity insulated cables connected the headstage with a preamplifier (gain 50, bandpass 100 Hz to 8 kHz) via a 45 channel commutator (Josef Biela; Idea Development) centrally located on top of the chamber. The preamplifier output was connected through a ribbon cable to a Multichannel Neuronal Acquisition Processor (MNAP) system (Plexon, Dallas, TX; www.plexoninc.com) that performed on-line multichannel neuronal spike sorting. Signals passed through input boards, which provided programmable gain and additional band-pass filtering (set at 400 Hz to 5 kHz), and then to digital signal processing channels for spike discrimination. Neural activity (extracellular action potentials, or "spikes") and behavioral responses (infrared beam interruptions and nosepokes) were digitized and time-stamped for computer processing in relation to successive behavioral events within each DNMS trial. Neuronal action potentials were digitized at 40 kHz and isolated by time-amplitude window discrimination and template matching (Fig. 2C). Up to four single units could be isolated per microwire channel. Control software for the MNAP box ran on a host Pentium PC, allowing digital control of signal gain, filtering, and window discrimination parameters. 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 recording sessions. Although it is possible that the neuronal spikes discriminated on a given microwire may not have isolated single units or consistently identified the same unit over time (McNaughton et al., 19832 Hz) overall mean firing rates and possess large spike widths (most with
Analysis
Event encoding. 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. Event encoding was determined by comparing the firing rate within each 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 the mean firing rate of the cell over the entire trial. A neuron was classified as "test cell" if there was a significant (ANOVA; p < 0.01) increase in firing around one of the test-phase events (i.e., in one or more perievent histogram bins; see Table 1 for bin size used for each event) relative to baseline. Only increases in firing rates were considered for nonstationary test-phase events to avoid counting events within nonfiring regions of place cells as "encoded." For sample and delay phases, in which the rat's location was fixed, 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 in one or more perievent bins relative to pre-odor baseline. Further discriminant analyses were then performed on each event-responsive cell.
Discriminant analysis. The test-phase perievent histograms constructed around the test arm entry and poke response consisted of three groups or factors: position (L/R), odor (A/B), and trial type (match/nonmatch). The sample- and delay-phase perievent histograms constructed around odor onset and offset consisted of two factors: odor (A/B) and trial type (correct/error). (Note: correct/error in the sample and delay phases refer to trials in which a nonmatch or match response, respectively, was later made in the test phase). Linear discriminant analysis (Rencher, 1995
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Table 1. Perievent histogram parameters c,h of the matrix (Bc,h · Wc,h
1) were then calculated. The number of eigenvectors and eigenvalues extracted was Nfunctions = min{Ngroupsh
1,Nbinsh}, where Ngroupsh was the number of group categories for histogram h. The ability of the ith eigenvector (Eic,h) to separate one or more of the Ngroupsh groups by serving as coefficients for discriminant functions Dic,h = Eic,h· Xc,h was determined using the
2 approximation of the Wilks
statistic, distributed with ((Nbinsh
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Figure 3. Schematic illustration of linear discriminant analysis. A, Perievent histograms of neural activity were composed for each of the groups (for example, group 1= odor A, correct trials; group 2 = odor A, error trials; group 3 = odor B, correct trials; group 4 = odor B, error trials). B, The firing rate within each time bin for each trial was plotted in n-dimensional space, where n = number of time bins. Directions [discriminant functions (DFs)] were then computed that maximally separated groups as follows. The first discriminant function (DF1) was chosen such that the data projection onto it [depicted by Gaussian curves in (B)] accounted for maximal variance between groups. In this example, the first discriminant function separated odor A from odor B trials, but not correct versus error trials. The second discriminant function (DF2) was then selected, which maximized the variance between groups and was uncorrelated (linearly independent) with DF1. In this case, the second discriminant function separated correct from error trials, and not odor A from odor B trials. Subsequent discriminant functions maximized variance of the data uncorrelated with previous DFs. A total of minimum (number of time bins, number of groups
RESULTS
Neuronal activity correlated to DNMS events
A total of 1101 principal cells were isolated from the dentate gyrus (n = 129), field CA3 (n = 767), and field CA1 (n = 205) of 18 rats during criterion performance of the DNMS task. The units were recorded during an average of 24 sessions per rat. All DNMS events were encoded by some subset of principal cells (Fig. 4). Some units responded to just a single event (Fig. 4B,D, E) whereas others were responsive to more than one (Fig. 4A,C,F). The cell shown in Figure 4A exhibited activity time-locked to sample odor onset (odor fast, F(1,2783) = 622.40; p < 0.01) and offset (F(1,2783) = 150.75; p < 0.01), whereas Figure 4B shows a cell with suppressed activity around sample-odor onset (odor fast, F(1,3026) = 11.48; p < 0.01) and offset (F(1,3026) = 9.33; p < 0.01), and elevated slow sample-odor onset firing (odor slow, F(1,943) = 32.96; p < 0.01). Figure 4C depicts a cell with a sample-odor onset (odor fast, F(1,1718) = 26.08; p < 0.01) and offset (odor off, F(1,1718) = 142.54; p < 0.01) response as well as delay firing (F(1,593) = 8.06; p < 0.01). Other cells are shown in Figure 4D, with increased activity during entry into the test arms (F(1,78725) = 9.87; p < 0.01), and Figure 4E, with maximal firing in the postnosepoke period (F(1,94481) = 957.59; p < 0.01). A multiphase cell that exhibited a slow sample odor response (F(1,744) = 152.34; p < 0.01), delay activity (F(1,744) = 12.24; p < 0.01), and firing time-locked to the test-poke response (postresponse, F(1,54209) = 804.20; p < 0.01) is displayed in Figure 4F.
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Figure 4. Examples of hippocampal principal cells encoding different DNMS events. Each panel includes a raster display of 30 representative 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 where 1 sec bins were used. The responsivity of cells was determined by comparing the firing rate within each perievent histogram with baseline activity. For perievent histograms in the sample and delay phases in which the rat's location was fixed, 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 encoding an event in the sample or delay phases if there was a significant (ANOVA; p < 0.01) change in firing in one or more perievent histogram bins. 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 (represented as a dotted line extending throughout the test phase). A cell was classified as encoding an event in the test phase if there was a significant (p < 0.01) increase in firing rate in one or more of the perievent histogram bins compared to baseline. The extracellularly recorded waveform (negative deflection-down; calibration: 100 µV, 200 µsec), hippocampal field, and number of DNMS trials recorded for each cell (n) are shown to the right of each panel. A, A cell with activity time-locked to sample odor onset and offset. B, A cell that exhibited suppressed activity around sample-odor onset and offset and elevated slow sample-odor onset firing. C, A cell with a sample-odor onset and offset response as well as delay firing. D, A cell that encoded entry into the test arms. E, A cell that fired maximally in the postresponse period. F, A multiphase cell that exhibited a slow sample odor response, delay activity, and firing time-locked to the test-poke response.
Approximately 70% of the cells in each field (699 of 1101 overall) were responsive to events in the sample phase (sample cells), ~30% (294 of 1101) in the delay phase (delay cells), and ~55% (571 of 1101) in the test phase (test cells) (Table 2). Responsive cells were further analyzed to determine whether their activity differentiated odor, match/nonmatch trial type (referred to as correct/error for the sample and delay phases), or position as determined by discriminant analysis (
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Table 2. Number of cells encoding events in the sample, delay, and test phases Sample odor selectivity
Odor-selective activity most prominent in CA1, least in DG, and linked to task performance
If hippocampal representations of the sample odor mediate later recognition in the test phase, then sample odor codes in the hippocampus should be different in trials where correct recognition of the sample occurred later in the test phase compared to error trials where recognition failed. Activity in some cells discriminated the sample odor but did not fire differentially on correct versus error (C/E) trials (Fig. 5A,
The number of cells in each field responsive to the sample odor onset (fast and slow responses) and offset is shown in Table 3. Although both dentate and CA3/1 cells discriminated odor on its immediate onset (up to 1.5 sec after its onset) in the odor-fast period (5/56 = 9% of the responsive DG cells; 38/381 = 10% in CA3/1), only cells in the CA fields exhibited longer-latency, odor-specific responses in the subsequent odor-slow period (>1.5 sec after odor onset) (odor discrimination, 0/70 = 0% of DG cells compared to 49/433 = 11% in CA3/1).
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Figure 5. Examples of odor, position, and match/nonmatch discriminative firing. Panels show a raster display of 25 representative trials and a summary histogram of all trials recorded for each cell. Waveform (negative deflection-down; calibration: 100 µV, 200 µsec), hippocampal field, number of trials recorded (n), and significant (
Responsive cells in the sample phase (including the odor-fast, odor-slow, and odor-off intervals) were then tallied for each subfield (Table 2). Summing over the hippocampal subfields, odor-selective activity was observed in 100/699 = 14% of the sample-responsive cells, half of which (47/100) were correlated with trial performance (differential correct/error firing), whereas 10% (70/699) of the sample-responsive cells discriminated correct/error trials (Fig. 6A). Odor-selective firing was unevenly distributed across the subfields, least prevalent in the dentate gyrus (7/96 = 7% of the sample cells), more in CA3 (67/458 = 14%), and most prevalent in CA1 (26/145 = 18%) (Fig. 6B).
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Table 3. Number of cells encoding sample-phase events
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Figure 6. Summary of odor, match/nonmatch (correct/error), and position encoding in the DNMS task. A, Encoding properties of event-responsive cells. Ten percent of the responsive cells in the sample phase exhibited differential activity in correct versus error trials. Sample odor-selective activity was observed in 14% of the cells, half of which also fired differentially on correct versus error trials (hatched bars). No cells discriminated odor or correct/error trials in the delay period. In the test phase, spatial encoding was more than twice as predominant (70%) as odor (27%) and M/N (21%). Almost all of the odor and match/nonmatch cells also discriminated position (filled bars). B, Cells with odor selectivity in the sample phase were distributed across the hippocampal fields in a graded fashion, with CA1 cells demonstrating the greatest odor selectivity (18%), then CA3 (14%), and DG the least (7%). In the test phase, the inverse distribution of odor selectivity was observed. C, Match/nonmatch discriminating cells were most odor-selective in DG (59%), followed by CA3 (42%), and least in CA1 (36%). The distribution of odor selectivity of match/nonmatch cells was inverse and statistically distinct (
Delay activity
Sample nonspecific delay firing
Whereas ~25% (294/1101) of the hippocampal cells exhibited elevated or suppressed activity in the delay relative to the pre-odor period, none (0/294) differentiated the sample odor or C/E trials (Table 2, Fig. 6A). Most delay firing was restricted to the sample arm location and terminated before entry into the test arms (Fig. 4C).Recognition-phase encoding
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 cells were found to discriminate various combinations of M/N, odor, and position in the test phase. Some exhibited activity, which was that of a "pure" place cell, discriminating the left/right position but not odor or match/nonmatch (Fig. 5C;
Match/nonmatch activity most temporally coupled to reinforcement stimulus in DG, least in CA1
To determine whether match/nonmatch discriminative firing around the test nosepoke response was associated with the behavioral execution of the nosepoke or was caused by differential responding to the water reward and light flash reinforcement, the reinforcement signal was delayed 1.5 sec on a random number of trials. This was done for 16 of the 18 rats recorded. Postresponse match/nonmatch cells with a sufficient number (>10) of reinforcement-delayed trials were classified as either reinforcement-correlated or poke-correlated, based on whether their poke-aligned or reinforcement-aligned perievent histogram contained the larger peak firing rate. An example of a match/nonmatch, reinforcement-correlated cell is shown in Figure 7A. The selective activity of the cell after match, but not nonmatch, responses (
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Figure 7. Determination of poke- versus reinforcement-correlated match/nonmatch discriminative firing. Panels show a perievent histogram of all trials recorded for each cell and a raster display of 15 representative trials. Waveform (negative deflection-down; calibration: 100 µV, 200 µsec), hippocampal field, and number of trials recorded (n) are shown to the right. A, Top panels, Cell with elevated activity after match poke responses (right) but not nonmatch poke responses (left). Middle panels, Postpoke match activity on trials when the reinforcement signal (light flash) was delivered immediately (left) or was delayed by 1.5 sec (right). Note the shifting of activity with the reinforcement signal. Bottom panels, Perievent histogram of activity around the match poke response (left) and the flash reinforcement signal (right). The activity is better time-locked (i.e., larger maximal firing rate) to the flash reinforcement than to the poke response (plotted in C). B, Top panels, Cell with more robust activity after nonmatch poke responses in the test arms (left) than after match poke responses (right). Middle panels, Postpoke nonmatch activity on trials when the reinforcement signal (water reward) was delivered immediately (left) or was delayed by 1.5 sec (right). The majority of activity did not shift with the reinforcement signal. Bottom panels, Perievent histogram of activity around the nonmatch poke response (left) and the water reinforcement signal (right). The activity was better time-locked (i.e., larger maximal firing rate) to the poke response than to the water reinforcement (plotted in C). C, Comparison of peak firing rate in perievent histogram centered around the reinforcement signal relative to that centered around the poke response for cells shown in A and B. The cell shown in A, with greater maximal firing in the reinforcement-centered perievent histogram relative to the poke-centered perievent histogram, had reinforcement-correlated M/N firing. The cell shown in B, with the converse, had poke-correlated M/N firing. D, Summary of match/nonmatch discrimination in postpoke period. The total percentage of cells that differentiated match versus nonmatch trials was ~43% in each subfield. Of these cells, however, DG had the smallest percentage of poke-correlated cells (25%), followed by CA3 (37%), and CA1 with the greatest (47%), as determined using the criteria outlined in A-C.
Spatial representations dominate test-phase hippocampal encoding
Odor, match/nonmatch (including 66 cells in the test entry period, 41 cells in the prepoke period, and 38 poke-correlated cells from the postpoke period), and position cells (i.e., cells with main effects on post hoc ANOVAs) were tallied over all test-phase events, as shown in Table 2 and Figure 6A. Spatial encoding was observed in all three hippocampal fields (~70% of responsive cells in each subfield; 400/571 over all subfields) and was more than twice as prevalent as odor (155/571 = 27%) and match/nonmatch (121/571 = 21%) encoding. Approximately one-third (149/400) of the spatial cells encoded position exclusively, with no significant (ANOVA, p < 0.01) main or interaction effects with regard to odor and match/nonmatch, whereas almost all of M/N (112/121) and odor cells (143/155) had spatial correlates (Table 2, Fig. 6A).Increased hippocampal activity for test stimuli which nonmatch the sample stimulus
To investigate whether a recognition signal was present in the hippocampus on correctly performed trials and absent on error trials, the magnitude of perievent activity in nonmatch versus match trials was compared for all M/N-discriminating cells (including only poke-correlated cells from the postnosepoke period). The ratio of the mean perievent activity (averaging across all perievent time bins) for nonmatch (N) versus match (M) trials, [(N
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Figure 8. Increased hippocampal activity on correct nonmatch trials. Ratio of mean activity of match/nonmatch discriminating cells on nonmatch versus match trials ((N
Inverted distribution of odor specificity in test phase compared to sample phase; odor specificity of match/nonmatch comparison signals greatest in DG, least in CA1
Odor representations in the test phase were distributed across the hippocampal fields in a graded fashion, inverse and statistically distinct (
DISCUSSION
The DNMS experimental design of the present study, in contrast to those used by others (Otto and Eichenbaum, 1992b
Hippocampal encoding of sample, delay, and test-phase events
Neuronal activity in the three hippocampal subfields reflected all identifiable DNMS events. This agrees with previous findings from the CA3 and CA1 fields (Otto and Eichenbaum, 1992b
Although a significant number of cells in each subfield (~25%) exhibited delay firing, the activity did not represent a memory of the sample odor or predict performance on the task (Table 2), in agreement with other reports (Cahusac et al., 1989
Sample cue-selective activity most prominent in CA1, least in DG, and linked to task performance
Some studies have suggested that the encoding of specific perceptual variables within the DNMS task (e.g., odor identity within an odor-guided task) is reserved to the parahippocampal cortical regions and does not occur in the hippocampus (Brown et al., 1987
Integration of spatial representations with odor and M/N recognition encoding
There has been debate as to whether the hippocampus is primarily dedicated to spatial processing (O'Keefe and Nadel, 1978
Notwithstanding, our data suggest that spatial codes are integrated into nonspatial representations, with hippocampal activity encoding stimulus properties and M/N comparisons when they occur at a particular location. The delay activity also appeared to be tied in with spatial representations, always restricted to the sample arm location and extinguishing when the rat moved toward the test arms. It is uncertain, however, whether the location dependence of the delay activity was attributable to the integration of spatial representations with the mnemonic delay signaling or whether cessation of activity was caused by the impingement of intervening visual stimuli as the rat turned to leave the sample arm. The presence of interposing stimuli may be sufficient to disrupt the bridging activity between the sample and test cues, as has been observed in the monkey perirhinal cortex (Miller et al., 1993
Test cue-specificity distribution (DG > CA3 > CA1) inverse of that for the sample cue
Differential encoding of stimuli presented in the sample versus test phase of recognition memory tasks has been observed in the hippocampal formation of monkeys (Riches et al., 1991
Evidence for generalization of behaviorally used recognition memory codes in the hippocampus
Differential unit responses to test stimuli that match versus nonmatch the sample have been reported in both the hippocampus (Otto and Eichenbaum, 1992b
The finding of progressively diminished odor specificity of match/nonmatch cells along the DG
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Figure 9. Schematic diagram of odor encoding in the temporal lobe during olfactory recognition memory performance. Odor selectivity is denoted by large bold text, thick lines, and filled symbols. A, Sample phase. Odor cue-specific activity occurs in the neocortical structures, parahippocampal cortex (PHC), and CA1 (perhaps because of the direct, perforant path projection from the entorhinal cortex to CA1). B, Delay phase. PHC maintains sustained, cue-specific activation traces (filled, curved arrows). Hippocampal fields maintain sustained, cue-nonspecific activation traces (open, curved arrows). C, Test recognition phase. Match/nonmatch (M/N) comparisons between the sample (held in memory) and test cues occur in the PHC and in each hippocampal subfield, but with a graded odor cue-specificity: Cortex/PHC > DG > CA3 > CA1. Odor representations enter the hippocampus via the perforant path projection from entorhinal cortex to DG, and the mossy fiber DG
FOOTNOTES Received June 25, 1999; revised Aug. 19, 1999; accepted Sept. 22, 1999.
We thank Wendy Suzuki and J. Christopher Repa for critical comments during preparation of this manuscript.
Correspondence should be addressed to Dr. Sherman P. Wiebe, Plexon, Inc., 6500 Greenville Avenue, Suite 730, Dallas, TX 75206. E-mail: sherman{at}plexoninc.com.
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