Fast Spiking and Regular Spiking Neural Correlates of Fear Conditioning in the Medial Prefrontal Cortex of the Rat

Abstract

In order to investigate whether and how medial prefrontal cortex (mPFC) of the rat is involved in processing of information related to fear conditioning, we recorded from single units in the prelimbic and infralimbic cortex of fear-conditioned rats in response to an explicit conditional stimulus (CS; an auditory tone) or contextual cues (conditioning box). The majority of units changed their activities significantly in response to the CS in a delay or trace conditioning paradigm. Both transient and tonic activity changes, including delay cell activity, were observed as in other behavioral tasks. When exposed to the context without CS delivery, most units changed their activities as well. These results show that both tone and contextual information are processed in the rat mPFC in expectation of the delivery of an aversive stimulus (electric foot shock). Interestingly, fast spiking cells (putative inhibitory interneurons) and regular spiking cells (putative projection neurons) showed different patterns of responses. Fast spiking cells tended to show transient responses and increased their firing rates following CS presentation, whereas a complementary pattern was observed in the regular spiking cells. Our results enhance our understanding of the neural mechanisms underlying prediction of an aversive stimulus in the mPFC.

Introduction

Emotion is an important component of the function of prefrontal cortex (PFC). Patients with prefrontal cortical lesions manifest affective and emotional abnormalities such as apathy, depression, panic disorder and obsessive-compulsive disorder (Baxter et al., 1989, 1990; Gorman et al., 1989; Drevets et al., 1992; Godefroy and Rousseaux, 1997). In animals, lesions or stimulation of various divisions of the PFC lead to alterations in emotional functions such as aggression, stress, anxiety and autonomic control (Franzen and Myers, 1973; Siegel et al., 1975; Maskati and Zbrozyna, 1989; Zbrozyna and Westwood, 1991; Diorio et al., 1993; Frysztak and Neafsey, 1994; Jinks and McGregor, 1997). Physiological studies also have shown that neurons in the dorsolateral PFC of the monkey (Ono et al., 1984; Inout et al., 1985) and medial PFC (mPFC) of the rabbit (Maxwell et al., 1994) change their activities in association with emotional aspects of a task. Anatomically, the PFC receives profuse projections from the thalamus, hypothalamus, amygdala, hippocampus and cingulate area (Arikuni and Ban, 1978; Swanson, 1981; Musil and Olson, 1988; McDonald, 1991; Ray and Price, 1993; Gigg et al., 1994; Bacon et al., 1996), which all play important roles in emotion.

Recent investigations of neural mechanisms underlying emotion focused on fear conditioning. Much progress has been made owing to the use of this behaviorally well-defined paradigm (LeDoux, 2000). Concerning the role of the PFC in fear conditioning, however, previous behavioral studies have reported conflicting results. In rats, lesions in the mPFC led to an increase, a decrease or no change in fear reactivity (Mason and Fibiger, 1979; Holson, 1986; Rosen et al., 1992; Morgan et al., 1993; Morgan and LeDoux, 1995; Gewirtz et al., 1997; Joel et al., 1997). The absence of any effect of a PFC lesion on the behavioral reaction to a conditional stimulus (CS) does not necessarily indicate that the PFC has no role in fear conditioning, however. For example, animals with bilateral hippocampal lesions show intact conditioning in a delay-conditioning paradigm, i.e. when there is no interval between a CS and an unconditional stimulus (US). Impairment is observed when the interval between a CS and a US is long or in the context conditioning paradigm, however (Selden et al., 1991; Kim and Fanselow, 1992; Phillips and LeDoux, 1992; McEchron et al., 1998). In addition, some hippocampal neurons show activity changes that correlate with different phases of classical conditioning (Berger et al., 1980; McEchron and Disterhoft, 1997), suggesting that relevant information is processed in the hippocampus and utilized when necessary.

Considering the anatomical organization, it is highly likely that information related to fear conditioning is actively processed in the rat mPFC and influences behavior under appropriate conditions. Sensory information about a stimulus is conveyed to the mPFC via sensory cortical projections to the mPFC (Condé et al., 1995). The amygdala, which plays an essential role in fear conditioning (LeDoux, 1996), sends direct as well as indirect projections via the mediodorsal thalamus to the mPFC. Stimulation and inactivation studies have shown that amygdaloid projections strongly influence neuronal activities in the mPFC (Pérez-Jaranay and Vives, 1991; Garcia et al., 1999). In addition, the mPFC has direct access to contextual information by way of direct hippocampal projections to it (Swanson, 1981; Ferino et al., 1987; Jay and Witter, 1991). Thus, the mPFC of the rat is in a position to receive sensory, hippocampal and amygdaloid inputs, which are major components of fear conditioning. Also, other projections to the mPFC, such as those from the hypothalamus (Arikuni and Ban, 1978), could carry information about visceral changes associated with fear conditioning.

The role of the mPFC in fear conditioning can be conjectured by examining changes in mPFC neural activity during fear conditioning. In addition, insights about the way the mPFC processes fear-related information can be obtained by physiological studies. So far, few single unit studies have examined PFC unit activity in the context of negative emotion. Single unit studies in rabbits (Gibbs and Powell, 1991; Maxwell et al., 1994) have shown that neuronal activities in the mPFC show changes that correlated with heart rate conditioning. In the present study, we examined single unit activities in the prelimbic and infralimbic cortex of the rat during fear conditioning. We examined the effects of both an explicit CS (tone) and context. Our results show that an explicit CS, as well as contextual cues, induces changes in mPFC unit activity, and that putative projection neurons and putative inhibitory neurons play different roles in this process.

Materials and Methods

Subjects

Thirteen adult male Sprague–Dawley rats, ~10–12 weeks old, weighing 280–350 g, were used. All subjects were maintained on a 12 h light:dark cycle and allowed free access to food and water. The experimental protocol was approved by the Ethics Review Committees for Animal Experimentation of Ajou University School of Medicine.

Electrode Implantation

Rats were deeply anesthetized with Nembutal (50 mg/kg) and two microelectrode drivers (McNaughton et al., 1989) were installed on opposite sides of the skull, both directed at the medial wall of the PFC (2.5–3.0 mm A and 0.6–1.3 mm L to bregma) at an angle 0–10° toward the midline. The recording electrodes (tetrode) (Recce and O'Keefe, 1989; Wilson and McNaughton, 1993) consisted of bundles of four polyimide insulated nichrome wires (H.P. Reid Co., Palm Coast, FL) twisted together and heated gently to fuse the insulation without short-circuiting the wires (final overall diameter: 40 μm). The electrode tips were cut and gold-plated to reduce their impedance to 0.2–1.0 MΩ measured at 1 kHz. The reference electrode was a stainless steel wire that was fixed to six skull screws. Another stainless steel wire was soldered onto one screw to serve as an earth lead. The entire implant was encased in dental acrylic.

Unit Recording

Unit signals were recorded via an FET source-follower headstage mounted on the animal's head. Output signals from the headstage were filtered between 0.6 and 6 kHz, digitized at 32 kHz and stored on a SUN 4u workstation for future offline analysis. Data acquisition was performed using the Cheetah system (Neuralynx, Tucson, AZ). Units were isolated by projecting the four-channel relative amplitude data two-dimensionally, and applying boundaries to each subjectively apparent unit cluster (McNaughton et al., 1983). Care was taken to apply the same criteria to all cells in the population.

Apparatus and Behavioral Tasks

Apparatus

The conditioning chamber was 27 × 25 × 40 cm in dimension and had 18 metal grids (4 mm diameter, 1.5 cm spaced) on the floor that were connected to a shock scrambler. The box was washed thoroughly with 70% alcohol and completely dried before conditioning and testing. The chamber was placed on a speaker (diameter = 26 cm) that converted animal movements into electrical signals. The movement signals were digitized at 2.5 kHz and stored on the workstation.

Fear Conditioning

The behavioral task was an aversive classical conditioning task. After ~1 week of recovery from surgery, rats were adapted to transportation and handling for 5 min over three consecutive days. On the initial day of training, animals were placed in the conditioning box and allowed to habituate for 1 min. They were then presented with 20 incidences of an auditory tone (CS; 5 s, 1 kHz) that were paired with electric foot shock (US; 1 mA, 0.5 s) at 50% chance in a quasi-random manner with 50–70 s inter-trial intervals. Animals were removed from the conditioning box 1 min after the last shock and returned to their home cages. The partial punishment schedule was lowered progressively over the next 2 days from a quasi-random 50% level to 15–20% and the number of trials was raised to 40. The punishment rate and number of trials were maintained at 15–20% and 40 trials, respectively, throughout the subsequent recording sessions unless otherwise noted. Recordings began on day 4 whenever well-isolated units were found. A search of units and electrode advancement were made while the animals were sitting on a pedestal outside the conditioning box. Following recording of baseline unit activity on the pedestal, each animal was placed in the conditioning box and recordings were made in 10 out of 40 trials in which the electric foot shock was not delivered. Care was taken not to allow the animal to predict the delivery of the foot shock. The room light was turned off before training and recording. Four and five rats were used for standard (delay) and trace conditioning, respectively. In the standard conditioning task, the US was delivered during the last 0.5 s of the CS so that the CS and US co-terminated. In the trace conditioning task, the US was delivered 2 s after the offset of the CS (Fig. 1A).

Testing Effects of Context

To examine the effects of contextual cues on mPFC unit activity, two rats that were trained in the standard conditioning paradigm were used. Once well-isolated and stable units were found, baseline recordings were made for 5 min while the animal was sitting quiet on the pedestal outside the conditioning box. The animal was then placed in the recording chamber and unit activities were recorded for 5 min without delivery of an auditory tone to test whether exposure to contextual cues induces changes in unit activity.

Control Experiment

Recordings were made from four naive (i.e. unconditioned) rats as the control for the effects of the CS (two rats) or contextual cues (two rats) on mPFC unit activity. Unit recordings were made as in the standard conditioning (i.e. the CS was delivered) or contextual cue experiments (the CS was not delivered) except that the rats never received the electric foot shock. The results were compared with those from the conditioned rats.

Extinction Procedure

Two rats from the trace conditioning group were used. When well-isolated units were found, the CS was presented repeatedly without the US delivery until freezing behavior disappeared (40–60 trials), while unit recordings were made. The animals were then retrained with CS–US pairing (20 trials, 30% punishment rate) and unit activity was measured without US delivery until freezing behavior disappeared again (40–80 trials). Thus, the rats went through two episodes of extinction in a given day. Because the animals did not go through CS–US pairing following the second episode of extinction, and therefore exhibited a lower degree of freezing during the first episode of extinction on the next day, only data from the second episodes of extinction were considered in this study. Once the rats experienced extinction, they were not used again for further trace conditioning experiments.

Analysis

Unit Classification

Deep layer units in the rat mPFC were classified into regular spiking (RS) and fast spiking (FS) cells in our previous study (Jung et al., 1998). RS cells fire at relatively low rates and typically have wide spike waveforms with small after-hyperpolarization. On the other hand, FS cells fire at relatively high rates and have narrow spike waveforms with more pronounced after-hyperpolarization. Overall, as shown in Figure 2, the units recorded in this study showed the same characteristics. Units were therefore classified as RS and FS cells, as in our previous study (Jung et al., 1998). Unit classification was based on a non-hierarchical clustering method using mean firing rate. Using the ratio between the peak and valley amplitudes of the spike waveform (peak–valley ratio) as an additional parameter for clustering yielded the same results. Units had only a few different, stepwise values of the spike width (duration between the peak and the valley of a spike waveform) due to a limited resolution of spike waveform sampling (32 kHz); hence spike width was not used as a parameter for clustering.

Determination of Responsive Units to CS

To determine the units that were responsive versus unresponsive to the CS, the task was divided into pre-CS (5 s) and CS (5 s) periods for the standard conditioning and pre-CS, CS, delay (2 s) and US (1 s) periods for the trace conditioning task. CS, delay and US periods were divided into 1 s bins and unit discharge in each bin was compared with that during the pre-CS period over 10 trials using paired t-test (α = 0.05). Those units that contained at least one bin that was significantly different from the pre-CS period were regarded as responsive units.

Classification of Response Patterns to CS

To classify activity patterns of responsive units, peri-stimulus time histograms (PSTH) were first constructed with a bin size of 500 ms by aligning responses to the CS onset. The mean firing rate and standard deviation of each PSTH (no. of bins = 20 and 25 for the standard and trace conditioning, respectively; the first 10 bins correspond to the pre-CS period) were calculated, and then the firing rate in each bin was converted to a Z-score using the mean ± SD. A hierarchical clustering algorithm using the squared Euclidean method was applied to the normalized histograms.

Behavior

To assess the degree of freezing, animal movement was quantified by adding up peak amplitudes of oscillatory movement signals within a given time period and then dividing this value by the total duration. Animal movement was expressed in arbitrary units per second.

Histology

When recordings were completed, an electrolytic current (50 μA cathodal, 30 s) was applied through one of the recording electrodes. The animal was deeply anesthetized and perfused with 0.9% saline followed by buffered 10% formal saline while the electrode remained in situ. The brain was then removed, left in 10% formal saline for 3–5 days and then transferred to a 30% sucrose solution for 2–3 days until it sank to the bottom. Coronal sections (40 μm thick) were cut on a sliding microtome and alternate sections were stained with cresyl violet. Tracks and lesion sites were located under a light microscope.

Results

Recording Locations

Recording was made from 459 well-isolated units in the mPFC of 13 rats. These units were located in the superficial and deep layers of the prelimbic and infralimbic cortex (Fig. 1B). Table 1 summarizes the numbers of animals and recorded units in each task. There was no clear relationship between recording location and response patterns.

Baseline Discharge Characteristics and Unit Classification

The mean baseline discharge rates of the recorded units ranged from 0.03 to 51.97 Hz. The distribution of mean firing rates was positively skewed, with an overall mean firing frequency of 5.23 Hz. There was a significant negative correlation (Pearson correlation coefficient = –0.237; P < 0.001) between the mean firing rate and peak–valley ratio of the spike waveform so that high firing rate cells tended to have spike waveforms with relatively large valley amplitudes (i.e. large after-hyperpolarization; Fig. 2B). In addition, the peak–valley ratio correlated positively with the spike width (r = 0.158; P < 0.001) so that wide spikes tended to have small valley amplitudes. However, there was no significant correlation between the mean firing rate and spike width (r = –0.059; P > 0.05). The units were classified into two groups by a non-hierarchical clustering algorithm. The first group (RS cells) fired at low rates (3.44 ± 0.15 Hz) and had wide spike waveforms (352.5 ± 3.32 μs) with large peak–valley ratios (1.44 ± 0.01), whereas the other group (FS cells) fired at high rates (20.17 ± 0.93 Hz) with narrow spike waveforms (327.0 ± 17.75 μs) and small peak–valley ratios (1.26 ± 0.05). The differences between the two cell types in spike width and peak–valley ratio were statistically significant (t-test, P < 0.05 for both parameters).

Freezing Behavior

In the standard and trace conditioning tasks, the animals were exposed to both the explicit CS (auditory tone) and contextual cues (conditioning box). The animals showed significant freezing behavior during the standard and trace conditioning tasks whereas little freezing was observed during control experiments (Fig. 3). The conditioned animals showed freezing responses once they were placed in the conditioning box (context conditioning) regardless of delivery of the CS. The amounts of animal movement during the pre-CS periods (5 s) were 61.3 ± 9.8, 98.9 ± 18.3 and 366.1 ± 3.9 arbitrary units per second in the standard conditioning, trace conditioning and control task, respectively. Animals showed significantly higher degrees of freezing in both conditioning tasks compared with the control task (P < 0.001 for both tasks). The small difference in animal movement between the standard and trace conditioning groups probably reflects different degrees of freezing as well as different weights of the two groups of animals.

Additional CS-induced freezing under the influence of the context was assessed by comparing animal movements before (5 s) and after (5 s) delivery of the CS. The amounts of animal movement are shown in steps of 400 ms in Figure 3. Because CS presentation sometimes induced small startle responses, animal movements during the first three time steps (1200 ms) following CS onset were excluded. The delivery of the CS further enhanced the freezing response. The amounts of animal movement before and after delivery of the CS were 61.3 ± 9.8 and 48.4 ± 8.6, respectively, which were significantly different (P < 0.05, paired t-test) in the standard conditioning task. Those in the trace conditioning task were 98.9 ± 18.3 and 68.0 ± 11.8, respectively, which were also significantly different (P < 0.05, paired t-test). On the other hand, control animals slightly increased their movements when the CS was delivered. They often appeared to direct their attention to the CS.

The rats also showed significant freezing following context conditioning in which the CS was not delivered. The amounts of animal movement were 93.8 ± 24.7 and 406.1 ± 87.3 (measured for 5 min periods) for the context and control animals, respectively, which were significantly different (t-test P < 0.01).

Unit Activity in Standard Conditioning Paradigm

Sixty-nine out of 97 cells (71%) responded to the CS in the standard conditioning task. Thirty-one cells increased and 38 cells decreased their activities compared with the pre-CS period. The responsive cells showed various patterns of responses. Response patterns were classified into three types by a hierarchical clustering method. Figure 4A shows representative examples of unit responses and mean normalized responses for each cluster. The first type (n = 35, 50%) showed sustained decrease in firing rates during the entire 5 s of the CS delivery. These units decreased their firing immediately after CS onset until CS offset. The second type (n = 19, 28%) gradually increased the firing rate, which culminated around the expected US delivery. The third type (n = 15, 22%) showed a transient elevation of discharge rate at the time of CS onset. Unit activities increased within 1 s following CS onset and decreased back to the baseline level within 3 s.

Ninety-five units were recorded from four animals in control experiments. Only 24 out of 95 units (25%) changed their activities significantly in response to CS presentation. A chi-square test indicated that the proportion of responsive units was significantly higher in the standard conditioning task than in the control task (P < 0.001). These results indicate that a stimulus that only slightly influences PFC neural activity when it is neutral evokes significant changes in the PFC neural activity when it predicts an aversive stimulus. An example of unit activity and the mean normalized response in the control task are shown in Figure 4B.

Unit Activity in Trace Conditioning Paradigm

Of a total of 163 cells that were recorded in the trace conditioning task, 127 were responsive to the CS (78%). Fifty-six cells increased and 71 cells decreased their activities in comparison to the pre-CS period. The proportion of responsive units was significantly higher compared with the control (P < 0.001). These neurons showed a variety of response patterns, as in the standard conditioning task. Hierarchical clustering yielded four basic types of neural response. The first type (n = 37, 29%) showed a sustained decrease in firing rate during the entire 5 s of CS delivery and during the delay period. The second type (n = 38, 30%) gradually increased the firing rate, which reached maximal firing around CS offset and lasted until the expected US delivery. The third type (n = 29, 23%) transiently elevated the discharge rate at the time of CS onset. Unit activities were elevated within 1 s following CS onset and decreased back to the baseline level. Compared with the units that showed transient responses (type 3) in the standard conditioning task, however, responses of these units went back to the baseline in a slower manner. The fourth type (n = 23, 18%) showed biphasic responses, initially decreasing then increasing their firing rates (Fig. 5). Seventy-three out of 163 cells that were recorded in the trace conditioning task significantly elevated their activities during the delay period, and 17 of these changed their firing rates in association with the delay period only. These cells maintained elevated activities 1–2 s past the expected delivery of the US (Fig. 6).

Relationship between Unit Response and Freezing

Monitoring spatiotemporal activity patterns of the mPFC unit population following CS presentation would be necessary to fully understand how information related to fear conditioning is processed by the mPFC neural circuitry. On the other hand, certain units might play particularly important roles in this process so that significant relationships between their activities and freezing behavior can be detected. We tested this possibility by examining the relationship between mPFC unit response and freezing behavior. For this, units in the standard and trace conditioning tasks were combined according to each response type (types 1–3; type 4 of the trace conditioning task was excluded).

The degree of freezing was quantified as the following:

where pre-CSm and CSm respectively indicate animal movements during the pre-CS and the CS period across all trials in each recording session. Then correlation between the magnitude of unit response and the degree of freezing behavior was examined for each response type. No significant relationship was found between any of the three response types and freezing behavior, indicating that there exists no simple relationship between freezing behavior and responses of mPFC units.

Effects of Context

Forty-nine units were tested for their responses to the contextual cues without CS delivery. Unit activity outside the conditioning box on the pedestal was compared with that inside the conditioning box. Twenty-six units increased and 23 decreased their average firing rates in the conditioning box compared with those outside the box. These units were recorded only once inside and outside the box, thus statistical comparison between the two conditions for a given unit was not possible. Instead, firing rate changes recorded from the conditioned rats were compared with those from naive rats (control). Nineteen units were recorded from two naive rats. Because we were interested in whether PFC units change their activities significantly to the contextual cues, regardless of the direction of change, absolute changes in unit activity were calculated and normalized to the baseline activity (firing rate outside the conditioning box) so as to express unit activity change as a percentage of the baseline activity. Whereas the cells recorded from conditioned animals changed their activities by 165 ± 43% relative to the baseline, those from the naive rats changed by only 42 ± 8% (the difference was statistically significant, Mann–Whitney U-test, P < 0.05). Figure 7 shows responses, recorded from a conditioned rat,  of two units to the contextual cues.

Extinction

The effect of behavioral extinction on activities of single units was tested in 36 units from two animals that were previously trained in the trace conditioning task. Extinction was induced by repeatedly presenting the CS without delivering the US until the animals showed minimal freezing. The total number of trials was 40, 60 or 80. A typical example is shown in Figure 8A. For the group data, only those units that showed significantly different activities during the pre-CS versus CS periods were included (n = 20). Because we were interested here in changes in magnitudes of unit responses across extinction trials, statistical significance was determined based on mean firing rates during the entire 5 s of pre-CS and CS periods, instead of dividing the CS period into bins of 1 s duration. The entire extinction trials were divided into 10 blocks so that each block contained 4–8 trials. The magnitudes of unit response and animal movement were quantified for the pre-CS (5 s before the CS onset) and the CS period (5 s) for each block. Because units either reduced or increased their activities following exposure to the context and/or CS presentation, the magnitude of unit response in this analysis was determined by the absolute difference in mean firing rate (during 5 s period) between a given trial and the last trial. As shown in Figure 8A,B, unit responses both before and after CS delivery decreased gradually over the extinction trials. In parallel with the decrease in unit responses, animal movements during the pre-CS and CS period gradually increased (Fig. 8C). The parallel changes in unit response and freezing behavior suggest that PFC unit responses to the CS are linked to the stimulus–punishment contingency.

Response Patterns Depending on Types of Unit

We examined whether RS cells and FS cells show different response patterns during fear conditioning. First, the relationship between the types of unit and the direction of firing rate change was tested. The firing rate in about half of the responsive units (55% in the standard conditioning and 46% in the trace conditioning task) diminished in response to the CS in both tasks. Of all responsive units to the CS, 61% (105/173) of RS cells and 17% (4/23) of FS cells decreased their firing rates, respectively (Fig. 9A). A chi-square test indicated that a significantly (P < 0.001) higher number of RS cells decreased their firing rates compared with FS cells. Conversely, those units that decreased their firing rates in response to the CS had lower baseline firing rates (4.44 ± 0.47 Hz) than those that increased their firing rates (baseline firing rate = 6.86 ± 0.8 Hz; P < 0.01). These results indicate that RS cells and FS cells respond to the CS in different manners.

We then tested the relationship between the types of unit and response patterns. Distribution of RS and FS cells over the three response patterns (type 4 of the trace conditioning task was excluded) is shown in Figure 9B. FS cells tended to show transiently elevated responses (type 3 of Figs 4 and 5; 12/23, or 55%), whereas a complementary pattern was observed in the RS cells. A small proportion of RS cells showed transiently elevated responses (type 3; 36/151, or 24%), whereas a large proportion showed decreasing responses (type 1 of Figs 4 and 5; 68/151, or 45%). A chi-square test indicated that the distributions were significantly different (P < 0.01). When units were grouped into those that showed transiently elevated responses (type 3) and those that did not (the rest), the units with transient responses had a significantly higher firing rate (7.65 ± 1.38 Hz) than those in the other group (4.78 ± 0.6 Hz; P < 0.05). These results indicate that RS and FS cells behave differently during fear conditioning.

Discussion

Although recent investigations of fear conditioning revealed much about underlying neural circuit mechanisms, results of behavioral studies that have examined the PFC role in fear conditioning do not agree well, and single unit recordings in the PFC of fear conditioned animals are scarce. Our study was undertaken to obtain information regarding (i) the role of the rat mPFC in fear conditioning and (ii) neural mechanisms underlying information processing related to fear conditioning. Several conclusions could be drawn from the present study. First, the rat mPFC actively processes information related to fear conditioning. Secondly, unit responses could be classified into several categories, and both transient and tonic response patterns, including delay cell activities, were observed as in previous studies. Thirdly, mPFC neurons respond to both explicit CS and contextual cues that predict an aversive stimulus. Fourthly, putative projection neurons and inhibitory interneurons behave differently during fear conditioning.

Role of mPFC in Fear Conditioning

Previous behavioral studies have reported conflicting results concerning the role of the rat mPFC in fear conditioning. Lesions in the mPFC led to an increase, a decrease or no change in fear reactivity (Mason and Fibiger, 1979; Holson, 1986; Rosen et al., 1992; Morgan et al., 1993; Morgan and LeDoux, 1995; Gewirtz et al., 1997; Joel et al., 1997). Our study showed that the majority of mPFC units respond to the CS in fear-conditioned rats. Of a total of 260 units, 196 (75%) responded to the CS in a significant manner. In control experiments, in which units were recorded from naive rats, only 25% were classified as responsive units and the magnitude of the response was much smaller. These findings indicate that an innocuous auditory stimulus that only slightly influences the activity of mPFC neurons elicits widespread changes in mPFC unit activity after it is temporally paired with an aversive US. Furthermore, the results from the extinction experiments show that unit responses to the CS were correlated to fear reactivity. During extinction, unit responses to the CS diminished gradually as the degree of freezing became smaller. These results suggest strongly that information related to fear conditioning is actively processed in the rat mPFC. Presumably, parallel pathways exist in the brain that mediate a CS to a conditional response during fear conditioning. Expression of some behaviors may not require the intact PFC whereas other behaviors, or the same behaviors but in different context, require the intact PFC to be expressed when a CS is presented. In this regard, Maxwell et al. (Maxwell et al., 1994) reported previously that 68% of units recorded in the rabbit mPFC responded significantly to the CS after being paired with a US, and that 32% changed their activities when an innocuous sound was applied. The proportions agree well with those in the present study. These results suggest strongly that the mPFC of the rat and rabbit participates in processing of external stimuli that predict an aversive stimulus.

Types of Responses

Fuster (Fuster, 1973) initially described several different unit response patterns in the dorsolateral PFC of monkeys. Komatsu (Komatsu, 1982) later classified PFC unit responses into the following three basic types: a brief increase of activity after event onset, tonic activity between different events and gradual activity change preceding event onset. These response patterns have been repeatedly observed across different behavioral tasks. Similar response patterns were also observed in the present study. Responses were classified, by a hierarchical clustering algorithm that does not presume the number of clusters a priori, into transient elevation of activity after CS onset (type 3 of the standard and trace conditioning task), tonic decrease following CS onset (type 1 of the standard and trace conditioning task) and gradual activity change preceding expected delivery of the US (type 2 of the standard and types 2 and 4 of the trace conditioning task). Responses of the units that showed a transient rise in their activities (type 3) returned slowly to the baseline over the course of the CS presentation. Of the units, 13 showed brief responses that were terminated within 1 s following the CS onset (bottom example of Fig. 4A), which would correspond to ‘brief elevation of activity after event onset’ (Komatsu, 1982). These observations suggest that common patterns of activity seem to exist in different divisions of the PFC across different tasks that involve temporal discontiguity between a sensory stimulus and a behavioral response (Fuster, 1997). The transient reaction (brief elevation after event onset) is probably related to directing attention to the CS, and gradual reactivity may participate in some way in the anticipation of the US. It is conceivable that transient responses are induced by an external sensory input (CS) to the PFC. More difficult questions are how gradually changing activity is generated and whether the PFC interacts with other brain structures in this process; these are subjects of future investigations.

Delay Cells

Previous studies have shown that a substantial portion of units in the monkey dorsolateral PFC are ‘delay cells’, which increase their activities during the delay period of a delayed response task (Fuster and Alexander, 1971; Kubota and Niki, 1971; Funahashi et al., 1989). In the present study, 73 cells showed a significant rise in their activities during the delay period of the trace conditioning task. Of these cells, 17 changed their firing rates in association with the delay period only. These cells increased their firing rates at the end of the CS until expected delivery of the US (Fig. 6, top). One interesting aspect of our data is that activities of these delay cells returned to the baseline by the ‘expected’ delivery of the US. This indicates that an external sensory cue is not necessary for shaping delay cell activity in the rat mPFC. The rats were trained following a partial reinforcement schedule; thus they learned that the US is either delivered or not delivered 2 s after the offset of the CS. Because delay cell activities terminated at the time of the expected US delivery without an external sensory input, there must be an internal timing mechanism, which is generated by learning. One possibility is that modification of neural circuitry within the mPFC during conditioning, which could be accomplished by synaptic weight changes (Hirsch and Crepel, 1990), is responsible for the observed delay cell activities. On the other hand, no cell showed delay activity that was in perfect register with the delay period. Most delay cells maintained elevated activities 1–2 s past the expected delivery of the US, which may reflect how precisely the mPFC neural circuit can predict the time of US delivery.

Effect of Context

The hippocampus plays an important role in context learning (Hirsh, 1974). Previous studies have shown that, following bilateral hippocampal lesions in the rat, tone-elicited freezing remained intact whereas freezing induced by context (exposure to conditioning box) was severely impaired (Selden et al., 1991; Kim and Fanslow, 1992; Phillips and LeDoux, 1992; Anagnostaras et al., 1999). Considering these results, it is likely that contextual information is conveyed from the hippocampus to the mPFC and induces changes in firing rates of mPFC neurons when the animals are exposed to the conditioning box. There are several different pathways through which the hippocampus can influence mPFC neural activities. First, it sends direct projections to the mPFC. In rats, pyramidal neurons of the ventral CA1 and subiculum send monosynaptic projections to the mPFC including prelimbic and infralimbic cortex, where recordings were made in the present study (Swanson, 1981; Ferino et al., 1987; Jay et al., 1991). The ventral hippocampus also projects to the amygdala, which in turn projects to the mPFC (Musil and Olson, 1988; Ino et al., 1990; Van Groen and Wyss, 1990; McDonald, 1991; Ray and Price, 1993; Gigg et al., 1994; Bacon et al, 1996; McDonald and Mascagni, 1997). Rats with bilateral lesions in the fornix, but not in the entorhinal cortex, were impaired in context-induced freezing (Phillips and LeDoux, 1995). These results suggest that hippocampal projections to subcortical areas convey contextual information that is sufficient to induce freezing behavior. Because amygdala lesion also impairs context-induced fear conditioning (Lee and Kim, 1998; Sacchetti et al., 1999), contextual information must be conveyed to the amygdala. Presumably both direct hippocampal projections and indirect projections via amygdala to the mPFC contribute to context-induced neural activity changes in the mPFC. The amygdala appears to be a ‘quick and dirty’ system that informs that something dangerous is out there or expected without providing detailed information about the source of danger (LeDoux, 1996). It is then likely that the amygdala sends a warning signal to the mPFC when a conditioned animal is exposed to the context that is associated with an aversive stimulus, whereas detailed information about the context is provided by direct hippocampal projections to the mPFC. It is interesting that direct hippocampal projections to the mPFC support NMDA receptor-dependent long-term potentiation (Jay et al., 1995). This will enable association between hippocampal contextual information and the US in the mPFC and enhance hippocampal influences over mPFC neurons. This projection alone may exert a significant influence over the mPFC after fear conditioning. Examination of mPFC unit activities following inactivation of the amygdala of a conditioned animal may provide an answer to this issue.

We cannot rule out potential involvement of other indirect pathways, such as those via the entorhinal cortex (EC), in context-induced changes in mPFC unit activities. Although EC lesion had no effect on context-induced freezing behavior (Phillips and LeDoux, 1995), this does not exclude the possibility that hippocampal information is conveyed to the mPFC via the EC. Also possible is that part of the contextual information reaches the mPFC through a pathway that does not include the hippocampus. For example, information about certain visual features of the conditioning box can be transmitted to the mPFC through projections from secondary visual cortices (Condé et al., 1995). This information may have contributed to the observed changes in mPFC unit firing when exposed to the conditioning box. Perhaps sensory information through sensory cortical projections, contextual information through hippocampal projections, warning signals through amygdaloid projections and other indirect projections all contribute, albeit to different degrees, to context-induced alterations in mPFC unit activities.

Inhibitory versus Projection Neurons

Units recorded in the present study were classified into RS and FS cells, as in our previous study (Jung et al., 1998). RS and FS cells most likely represent pyramidal cells and inhibitory interneurons, respectively (McCormick et al., 1985). RS and FS cells showed complementary activity patterns. Whereas the majority (19/23) of FS cells increased their firing rates from the baseline after CS onset, RS cells decreased their firing rates following CS onset in most cases (105/173). In addition, FS cells tended to show transiently elevated responses (type 3; Figs 4 and 5), while a different pattern was observed for the RS cells. This is consistent with known physiological characteristics of the cortex. Inhibitory interneurons have a lower activation threshold than pyramidal neurons, and stimulation of afferent fibers induces powerful feedfoward and feedback inhibition (Fox and Ranck, 1981; Buzsaki and Eidelberg, 1982; Douglas et al., 1989). A significant afferent input, such as a CS-induced volley of sensory input, to the mPFC would initially activate inhibitory interneurons (FS cells), leading to initial elevation responses. In contrast, pyramidal neurons (RS cells) would initially be suppressed. Following termination of inhibitory postsynaptic potentials, the mPFC neural circuit would go through a sequence of changes, during which pyramidal cells and inhibitory neurons would show several types of responses such as those observed in the present study, for estimation of the time of US delivery and behavioral preparation. In the dorsolateral PFC of the monkey, responses of putative interneurons and pyramidal neurons were similar (Rao et al., 1999) or inverted (Wilson et al., 1994), depending on the distance between two neurons (Rao et al., 1999). In these studies, comparisons were focused on tuning profiles of RS and FS cells in different phases of delayed response tasks. In the present study, relative proportions of different response patterns across time were compared for RS and FS cells, thus a direct comparison of the present results with the previous studies is not possible.

Relationship with Amygdala

It is well known that the amygdala plays a key role in fear conditioning. The amygdala sends direct as well as indirect projections, through the mediodorsal nucleus of the thalamus, to the PFC. The amygdala can also influence PFC neural activity by way of indirect projections to various modulatory centers, such as the basal forebrain cholinergic system (Pare and Smith, 1994). Stimulation of the basolateral nucleus of the amygdala inhibited the majority of units in the rat mPFC (Pérez-Jaranay and Vives, 1991). A recent inactivation study (Garcia et al., 1999) also has shown that amygdaloid projections reduce mPFC neural activity of the rat during fear conditioning. In the present study, the majority of FS cells (putative inhibitory interneurons) increased their firing rates whereas most RS cells (putative pyramidal cells) decreased their firing rates following CS onset. Interestingly, the proportion of inhibited and unresponsive mPFC units to amygdala stimulation is similar to the proportion of responsive and unresponsive mPFC units in this and a previous study (Maxwell et al., 1994). These similarities raise the possibility that the CS effects on mPFC unit activity are in large part mediated by amygdaloid projections to the mPFC. On the other hand, auditory CS information can reach the mPFC directly from the auditory cortex (Condé et al., 1995). Because mPFC neural circuits are plastic (Hirsch and Crepel, 1990), it is quite possible that CS information through this pathway, after conditioning, contributes to the observed changes in mPFC neuronal activities. Our recent results also indicate that sensory cortical projections to the mPFC support long-term potentiation that is dependent upon activation of NMDA receptors (Kim and Jung, 1999), suggesting the possibility of CS–US association in the mPFC. It is likely, as in the case of context-induced conditioning, that both amgdaloid and auditory cortical projections to the mPFC contribute to tone-induced changes in mPFC neuronal activities. It is difficult to conjecture relative contributions from the two pathways. Again, inactivation studies after conditioning probably help resolve this issue.

Notes

This research was supported by the Korea Ministry of Science and Technology under the Brain Science Research Program, the Korea Science and Engineering Foundation grant through the Brain Disease Research Center at Ajou University, and the Korea Ministry of Science and Technology grant 97-N3-01–01-A-04 to M.W.J.

Address correspondence to Dr Min Whan Jung, Neuroscience Laboratory, Institute for Medical Sciences, Ajou University, Suwon 442-721, Korea. Email: min@madang.ajou.ac.kr.

References