Effect of D1 receptor agonist within the mPFC

Effect of D1 receptor agonist within the mPFC during an appetitive trace
conditioning task; the role of the infralimbic and prelimbic cortices
The effect of a D1 receptor agonist,
SKF81297, on learning of temporally
separated stimuli was tested in an
appetitive trace conditioning task.
Wherein, a time interval existed, either two
or 10-seconds, between the conditioned
stimulus (CS) (noise) before the delivery
of the unconditioned stimulus (UCS)
(food). SKF81297 was administered via
intra-fusion into two medial prefrontal
cortex sub-regions, the infralimbic and
prelimbic cortices. The results showed
SKF81297 (10 ul) impaired learning of the
trace conditioning task under the two-
second interval. Whereas responding was
at baseline for both the drug conditions
and a saline condition under the 10-second
interval. The findings did not demonstrate
any functional differentiation between the
infralimbic and prelimbic cortices. In
conjunction with the literature, it is
suggested that the D1 receptor had an
inversed U-function. The baseline
responding under all conditions under the
10-second interval also suggests the D1
receptor is possibly not involved under
certain time intervals.
Keywords
appetitive conditioning, dopamine receptor
1, medial prefrontal cortex, infralimbic,
prelimbic, SKF81297, trace conditioning

1. Introduction
Working memory is documented to decline with increasing age (Moore, Killiany, Herndon,
Rosene, & Moss, 2003; Nieoullon, 2002), reflecting neuronal loss, particularly in subcortical
and prefrontal dopaminergic neurons (Collins, Wilkinson, Everitt, Robbins, & Roberts, 2000;
Harada, Nishiyama, Satoh, Fukumoto, Kakiuchi, & Tsukada, 2002; Henby & Trojanowski,
2003). The prefrontal cortex is involved in learning the temporal context of events and
stimuli (Fuster, Bodner, & Kroger, 2000). Indeed, damage to this area prevents the learning
of stimuli which are temporally separated (Dias, Robbins, & Roberts, 1997). The pivotal role
of dopaminergic neurons in the age driven pathology is demonstrated by the efficacy of
dopamine receptor 1 (D1) agonists in restoring working memory (Arnsten, Cai, Murphy, &
Goldman-Rakic, 1994; Cai & Arnsten, 1997). Whilst the medial prefrontal cortex (mPFC) to
be implicated in working memory, the sub-regions of responsible for associating temporally
distant events and stimuli have yet to be elucidated.
The mPFC may be anatomically differentiated by the prelimbic (PL) and infralimbic (IF)
cortices (Balleine & O‟Doherty, 2010) although how these sub-regions are functionally
distinctive has yet to be fully determined. To explore this role of the PL and IL a trace
conditioning procedure may be utilised. This procedure requires a subject to learn the
association between a conditioned stimulus (CS) which is temporally separate, by a specified
amount of time, from the unconditioned stimulus (UCS) (Pavlov, 1927). Previous studies
have identified the role of mPFC in trace conditioning procedures (Kronforst-Collins &
Disterhoft, 1998; McLaughlin, Skaggs, Churchwell, & Powell, 2002). Of particular note is
the Vidal-Gonzalez, Vidal-Gonzalez, Rauch, & Quirk (2006) study which adopted a trace
conditioning procedure to demonstrate the involvement of the PL in learning fear between
temporally distant events.

Previous research illustrates the efficacy of trace conditioning in examining the effects of
aging on memory (Lopez-Ramos et al., 2012; Moyer & Brown, 2006), validating this
procedure as a model of memory. Applying this model in the examination of mPFC
dopaminergic mechanisms may identify the role of the PL and IL in temporally associative
memory. Evidence exists for dopaminergic modulation of trace conditioning, wherein Nelson
et al. (2011b) investigated the functional role of the nucleus accumbens core. Moreover, the
activity within the PL and IL display changes in accordance with time intervals between
stimuli (Gilmartin & McEchron, 2005). In considering trace condition procedures and mPFC
activity it is of importance to ensure a distinction between fear and appetitive trace
conditioning, as these two variants invoke distinctive functional activity.
Whilst dopaminergic mechanisms are implicated in both aversive (Feenstra, Vogel,
Botterblom, Joosten, & de Bruin, 2001) and appetitive (Dalley, Chudasama, Theobald,
Pettifer, Fletcher, & Robbins, 2002) conditioning, the PL and IL may be differentiated in
their functional role during these variants of trace conditioning (Balleine & O‟Doherty, 2010)
In regard to appetitive conditioning, studies (Killcross & Coutureau, 2003; Ostlund &
Balleine, 2005) have demonstrated distinctive functional roles of the PL and IL via lesioning
which caused sub-region specific differentiated appetitive behavioural responses. Of interest,
inactivation of the IL caused a significant delay in reward collection (Burgos-Robles et al.,
2013; Murphy, Fernando, Urcelay, Robinson, Mar, Theobald, Dalley, & Robbins, 2012),
suggesting IL mechanisms are implicated in appetitive behavioural responses (Coutureau E,
Killcross, 2003; Killcross & Coutureau, 2003). On the other hand Burgos-Robles, Bravo-
Rivera, & Quirk (2013) displayed PL inactivation to produce no noticeable effect upon
appetitive behaviour. However, this study incorporated an instrumental design, trace
conditioning procedures being a classical conditioning design. Although the surrounding

literature implicates the mPFC sub-regions in appetitive behaviour the functional role of PL
and IL in trace conditioning learning has yet to be deduced. Furthermore, Waelti, Dickinson,
& Schultz (2001) reported that activation of mPFC associated dopaminergic mechanisms are
not exclusive to presentation of the UCS, but also in the prediction of the UCS. The length of
delay between the CS and UCS may then exert an effect upon learning. As such, the
following study will incorporate two different trace intervals in order to elucidate how
interval length affects D1 activation. The aims of the following study is as follows; Identify
the role of D1 receptors in trace learning, and if there is a functional differentiation between
the prelimbic and infralimbic cortices.

2. Materials and methods
2.1. Subjects
On arrival in the laboratory, rats were caged in pairs on a 12:12 h light/dark cycle and given
free access to food and water. They were handled daily for 2 weeks. The rats‟ weights on
arrival were in the range 150–175 g and they were on free food until they reached 300 g in
body weight. The amount of food provided was subsequently adjusted in order to maintain
weights as close to 300 g as possible so that the rats were all operated at about the same size.
Rats were weighed daily during the first two post-operative weeks, and weekly thereafter. 52
naıve male Wistar rats (Charles Rivers, UK), of mean weight 300 g (range 280–350 g)
underwent surgery.
Of the 52 rats, 11 were lost due to varying causes ranging from meningitis to the implanted
cannula becoming loose during the course of the experiment. The remaining rats were
randomly allocated. Twenty-one were placed in the two-second trace interval group and
twenty in the 10-second trace interval group. Within the Saline and PL conditions there were
a total of 14, with 13 in the IL condition on.
2.2. Surgery
The surgical co-ordinates for implanting the cannula into the mPFC sub-regions are as
follows;
IF = Anterior-Posterior + 3, Lateral-Medial; Left + 0.6 Right - 0.6, Ventral -5.0.
PL = Anterior-Posterior + 3, Lateral-Medial; Left + 0.6 Right - 0.6, Ventral -4.0.
For further details on the surgical procedure see Cassaday, Horsley, & Norman (2005).

2.3. Drugs
There were two treatment conditions to test the effects of the D1 agonist SKF81297 (Sigma,
Poole, UK). Microinfusions were administered (10ul) 10 min before each trace conditioning
session. This variant of SKF was employed as it is found to be highly selective for the D1
subtype of dopamine receptors (Andersen & Jansen, 1990). SKF was infused before the task
as storage and consolidation of delayed working memory is mediated by dorsal hippocampal
DA-dependent mechanisms (Packard, 1999), whereas the PFC is involved in retrieval of
memory (Floresco, Braaksma, & Phillips, 1999).
2.4. Apparatus
For details on apparatus implemented within the study see Kantini, Norman, & Cassaday
(2004).
2.5. Behavioural procedure
2.5.1 Pre-experimental
On the first day, each rat was placed in its allocated conditioning box with access to food
pellets in the magazine and shaped to nose poke. On the second and third day, rats were
placed singly in the boxes and allowed to nose poke for 15 unsignalled rewards, delivered on
a variable interval schedule over a 15-min session over four days.
2.5.2 Conditioning
Rats were conditioned with 30 signalled rewards (UCS) presented on a variable interval over
a 60-min session. Conditioning took place over eight days. The target CS was in each case a
five second auditory stimulus (pure tone set at two kHz and at 70 dB including background).

During this time, a continuous flashing light stimulus was presented in the background. The
two-second trace group was exposed to a delay of two seconds between CS offset and UCS
delivery, whereas the ten-second group experienced a ten second delay.
Assessing effects on conditioning could be confounded by the role of the dopamine system in
motivational (reward-related) or motor (nose poking) responses. However, drug effects on
levels of responding to the CS were compared with responding during the intervals
immediately before CS presentation and the equivalent time period after UCS delivery in
each case. Specifically, we recorded the number of nose pokes in the following five response
bins: (i) Background which is any response outside of the other four response windows; (ii)
„Pre-stimulus in the 5 s before CS presentation; (iii) „Stimulus in the 5 s of CS presentation;
(iv) „Trace‟ during the two or 10 second inter-stimulus-interval (ISI) between CS and UCS;
and (v) „Post-Stimulus in the 5 s immediately following CS delivery. To further examine the
pattern of anticipatory responding within the trace interval, responses were collected in 2-s
bins. One bin for the two-second trace interval group and five for the 10-second trace interval
group.
2.6. Design and analysis
The experiment was run in 3×2 factorial design for later analysis of variance (ANOVA).
Between subjects factors were drug (SKF or saline) and trace (at levels two and 10 seconds).
ANOVA used an alpha level of 0.05. The following statistical analyse were conducted.
Multivariate analysis to compare responding between response windows. Response windows
were the dependent variables with „Trace’ and „Condition’ as the fixed factors. Three
repeated measures were conducted in order to examine responding during across the 30 trials,

the ISI of the 10-trace interval group, and the two response windows „Stimulus’ and „Trace’
across the four days of experimentation. A univariate analysis was also performed,
comparing the first ISI of the trace intervals groups to identify if the length of the interval
affects responding.

3. Results
The results below detail report responding in the trace conditioning task, comparing two and
10-second trace interval groups which each contain three conditions. The conditions being
two drug groups; PL and IL cortices which receive the D1 agonist SKF, and a Saline group.
The results are sub-segregated by the day (total of four days) of experimentation in order to
display increments in responding across days.
3.1. Responding during response windows of trace conditioning task
During a session each rat may respond within five response windows; background noise, pre-
stimulus, during stimulus, within the trace interval, and post the CS. As follows are the
results displaying mean differences for between-condition responding within these five
response windows.
3.1.1. Day 1
No significant effects were found between the conditions and response windows of
responding on Day One.
Table 1 displaying Mean ± SEM nose poke responding across the five response windows
Background
(mean ± SEM)
Pre-stimulus
(mean ±
SEM)
Stimulus
(mean ± SEM)
Trace interval
(mean ±
SEM)
Post
(mean ± SEM)
Day
1
IL 123.798 ±
18.704
4.500 ±
1.394
17.369 ±
3.591
5.917 ±
1.662
31.476 ±
2.490
PL 141.792 ±
18.157
6.271 ±
1.354
18.583 ±
3.486
9.292 ±
1.613
29.313 ±
2.417
Saline 140.357 ±
17.971
7.429 ±
1.340
20.214 ±
3.450
1.597±
1.597
31.857 ±
2.392

3.1.2. Day 2
On Day Two of responding only nose poking within the „Pre-stimulus’ response window
displayed significance between conditions, [F(2,33) = 3.606, p < 0.05], with the Saline
condition responding at the highest rate followed by PL (Table 2).
3.1.3. Day 3
Similarly there was no significance observed on Day Three of responding between
conditions, Table 3 illustrates mean differences between the conditions.
Background
(mean ± SEM)
Pre-stimulus
(mean ±
SEM)
Stimulus
(mean ± SEM)
Trace interval
(mean ± SEM)
Post
(mean ± SEM)
Day
3
IL 97.750 ±
22.040
4.083 ±
0.959
29.417 ±
3.386
12.667 ±
2.273
36.083 ±
2.410
PL 118.050 ±
21.763
4.950 ±
0.947
29.125 ±
3.343
14.975 ±
2.273
36.250 ±
2.380
Saline 151.310 ±
21.238
5.917 ±
0.924
36.750 ±
3.263
18.357±
2.218
35.821 ±
2.323
Background
(mean ± SEM)
Pre-stimulus
(mean ±
SEM)
Stimulus
(mean ± SEM)
Trace interval
(mean ± SEM)
Post
(mean ± SEM)
Day
2
IL 117.833 ±
24.868
3.417 ±
1.096
27.333 ±
3.902
10.667 ±
2.026
33.833 ±
2.164
PL 134.950 ±
24.555
5.600 ±
1.082
26.050 ±
3.853
9.225 ±
2.001
35.700 ±
2.137
Saline 160.214 ±
23.023
7.429 ±
1.015
28.714 ±
3.613
11.643 ±
1.876
37.286 ±
2.004

3.1.4. Day 4
Responding within the „Pre-stimulus’ response window was identified as significant between
conditions, [F(2,32) = 3.383, p < 0.05]. Similar to Day 2 the Saline condition responded at
the highest rate followed by PL (Table 4).
Background
(mean ± SEM)
Pre-stimulus
(mean ±
SEM)
Stimulus
(mean ± SEM)
Trace interval
(mean ± SEM)
Post
(mean ± SEM)
Day
4
IL 87.083 ±
17.489
2.917 ±
0.869
28.250 ±
3.960
13.833 ±
2.723
34.417 ±
2.828
PL 103.150 ±
17.269
5.325 ±
0.858
34.213 ±
3.910
17.450 ±
2.689
37.588 ±
2.792
Saline 117.238 ±
16.852
5.893 ±
0.837
41.524 ±
3.816
18.167±
2.624
34.214 ±
2.725
3.2. Rate of responding over 30 trials
Examining responding in greater detail is possible via analysis the 30 trials (segregated into
six response windows of five trials) which composed each session of the trace conditioning
task.
3.2.1. Day 1
Figure 1 illustrates the rate of responding over six response windows for both two and 10
(respectively) trace intervals. A significant difference, [F(1,35) = 4.425, p < 0.05], in
responding between rats within the two-second trace interval group to those in the 10-second
trace interval group is present. Between conditions within the two-second trace interval group
there is no significant difference of responding, [F(2,18) = 0.162, p = 0.851], nor for the 10-
second trace interval group, [F(2,17) = 0.122, p = 0.886].

Figure 1 displaying nose pokes over six response windows of five trials for the two and 10-second (respectively)
trace interval groups
3.2.2. Day 2
The data shown in Figure 2 suggests a difference of responding overall between the two and
10-second groups. Indeed, a significant difference, [F(1,33) = 26.655, p < 0.001], is reported.
Whereas responding between conditions did not illustrate a significant difference within the
two-second trace interval group, [F(2,18) = 0.609, p = 0.555], nor the 10-second trace
interval group, [F(2,14) = 0.748, p = 0.491].

3.2.3. Day 3
Rats within the two-second trace interval group display significantly higher levels of
responding, [F(1,32) = 43.289, p < 0.001]. Responding between the conditions demonstrated
a significant difference for the two-second trace interval group, [F(2,18) = 6.431, p < 0.05].
Figure 3 displays the higher rate of responding of the Saline condition within the two second
trace interval group. The 10-second trace interval group conditions were not significant
different, [F(2,14) = 0.748, p = 0.491].
3.2.4. Day 4
A significant difference in responding was identified between the trace interval groups.
[F(1,32) = 67.300, p < 0.001], with Saline responses being highest (Figure 4) A significant
difference was reported between the conditions within the two-second trace interval group,
[F(2,18) = 3.680, p < 0.05], however, no difference was reported for the 10-second trace
interval group [F(2,14) = 1.278, p = 0.309].

3.3. Responding over 10-second trace interval
For the 10-second trace interval between the stimulus and presentation of the US five bins
were collected, each being composed of two seconds from the trace interval. Each two second
bin holds data on the number of nose poke responses within the trace response window.
Responding within the trace response window was not found to be significant across any of
the four days (see section 3.1.) However, analysing the responding within each bin of the
trace response window illustrates how responding was spread throughout the interval, and if
the condition affected this distribution of responding.
3.3.1. Day 1
Although no significance was observed between conditions of rats within the 10-second trace
interval responding within the trace response window [F(2,17) = 1.830, p = 0.191]. The fifth
bin displays twice the amount of responding in the PL condition (see Table 5).

Table 5 displaying Mean ± SEM nose poke responding across the five bins of the 10-second trace interval group
Bin 1 (mean ±
SEM)
Bin 2 (mean ±
SEM)
Bin 3 (mean ±
SEM)
Bin 4 (mean ±
SEM)
Bin 5 (mean ±
SEM)
Day
1
IL 0.048 ± 0.020 0.043 ± 0.013 0.028 ± 0.026 0.024 ± 0.022 0.057 ± 0.027
PL 0.072 ± 0.021 0.056 ± 0.014 0.083 ± 0.028 0.095 ± 0.023 0.106 ± 0.030
Saline 0.047 ± 0.020 0.019 ± 0.013 0.048 ± 0.026 0.048 ± 0.022 0.052 ± 0.027
3.3.2. Day 2
No significance was reported between conditions during the bins [F(2,15) = 0.129, p =
0.880], mean differences are shown in Table 6.
Bin 1 (mean ±
SEM)
Bin 2 (mean ±
SEM)
Bin 3 (mean ±
SEM)
Bin 4 (mean ±
SEM)
Bin 5 (mean ±
SEM)
Day
2
IL 0.053 ± 0.015 0.047 ± 0.023 0.039 ± 0.023 0.045 ± 0.024 0.059 ± 0.020
PL 0.073 ± 0.016 0.027 ± 0.025 0.027 ± 0.025 0.067 ± 0.026 0.047 ± 0.022
Saline 0.038 ± 0.014 0.067 ± 0.021 0.076 ± 0.021 0.048 ± 0.022 0.062 ± 0.018
3.3.3. Day 3
Responding was not found to significantly differ across conditions, [F(2,14) = 0.529, p =
0.601], however, responding within the fifth bin is noticeably higher in the PL condition (see
Table 7).

Bin 1 (mean ±
SEM)
Bin 2 (mean ±
SEM)
Bin 3 (mean ±
SEM)
Bin 4 (mean ±
SEM)
Bin 5 (mean ±
SEM)
Day
3
IL 0.072 ± 0.042 0.039 ± 0.017 0.034 ± 0.025 0.055 ± 0.036 0.028 ± 0.029
PL 0.133 ± 0.046 0.040 ± 0.019 0.040 ± 0.028 0.080 ± 0.039 0.113 ± 0.032
Saline 0.095 ± 0.042 0.033 ± 0.017 0.089 ± 0.025 0.061 ± 0.036 0.056 ± 0.029
3.3.4. Day 4
A significant difference between the conditions was not observed, [F(2,14) = 0.272, p =
0.766], mean differences are displayed in Table 8.
Bin 1 (mean ±
SEM)
Bin 2 (mean ±
SEM)
Bin 3 (mean ±
SEM)
Bin 4 (mean ±
SEM)
Bin 5 (mean ±
SEM)
Day
4
IL 0.056 ± 0.038 0.039 ± 0.028 0.039 ± 0.037 0.022 ± 0.018 0.022 ± 0.031
PL 0.067 ± 0.042 0.060 ± 0.031 0.080 ± 0.041 0.060 ± 0.020 0.047 ± 0.034
Saline 0.067 ± 0.038 0.045 ± 0.028 0.050 ± 0.037 0.039 ± 0.018 0.078 ± 0.031
3.4. Responding within first bin between two and 10-second trace interval groups
Whereas the 10-second trace interval contains five two-second bins, the two-second trace
interval constitutes only a single bin. Comparison of this single bin with the first of the 10-
second trace interval group may identify if rate of responding is affected by trace
conditioning of different intervals.

3.4.1. Day One
On Day One rats within the two-second trace interval group responded (mean = 0.195 ±
0.028) at a significant higher rate, [F(1,39) = 11.014, p = 0.001], than those within the 10-
second trace interval group (mean = 0.055 ± 0.028) during the first bin.
3.4.2. Day Two
Responding within the two-second trace interval group (mean = 0.436 ± 0.041) was observed
to be significant higher rate, [F(1,37) = 41.177, p < 0.001], than the 10-second trace interval
group (mean = 0.053 ± 0.044).
3.4.3. Day Three
A significance difference was illustrated, rats within the two-second trace interval group
responding (mean = 0.698 ± 0.046) at a higher rate, [F(1,36) = 75.197, p < 0.001], the 10-
second trace interval group (mean = 0.098 ± 0.051).
3.4.4. Day Four
Data from Day Four displayed similar findings as the two-second trace interval group
responded (mean = 0.848 ± 0.051) at a significant higher rate, [F(1,36) = 105.577, p < 0.001],
compared to the 10-second trace interval group (mean = 0.063 ± 0.057).
3.5. Rate of responding across Days within response windows
How the rate of responding changed across days between the trace interval groups and
conditions allows examination of how each variable affected incremental learning.

3.5.1. Responding within the ‘Stimulus’ response windows over four days
Evident in Figure 5 the two-second trace interval group responding significantly increased
across days, [F(1,32) = 42.097, p < 0.001], whilst the 10-second trace interval group
remained at base levels of responding, [F(2,37) = 1.378, p = 0.267].
Figure 5 displaying nose pokes over four days in the ‘Stimulus’ response windows for the two and 10-second
(respectively) trace interval groups
3.5.2. Responding within the ‘Trace’ response windows over four days
As illustrated in Figure 6 the two-second trace interval group responding significantly
increased inclemently across days, [F(1,32) = 16.126, p < 0.001], whereas the 10-second
trace interval group remained at base levels of responding, [F(2,37) = 0.592, p = 0.559].
Figure 6 displaying nose pokes over four days in the ‘Trace response windows for the two and 10-second
(respectively) trace interval groups

4. Discussion
A role of D1 activity within the mPFC for working memory is supported by the literature
(Cai & Arnsten, 1997; Henby & Trojanowski, 2003). Moreover the degeneration of D1
receptors is linked to deficits in working memory, including the temporal association of
events (McLaughlin et al., 2002) which may be ameliorated with D1 agonists such as SKF
(for a review see Mizoguchia, Yuzurihara, Nagata, Ishige, Sasaki, & Tabira, 2002). Such a
role is not suggested from the findings of the present study, they do not convey that SKF
augmented learning but instead inhibited learning. Two trace intervals were utilised in this
study, a two and 10-second interval group. The saline condition within the former group
displayed a similar pattern of responding as the IL and PL conditions (whom received SKF).
However, over the course of the study the saline condition noticeably superseded the
responding of these two drug conditions. From these findings it is clear SKF inhibited
learning the US-CS contingency under the time interval of two seconds. These findings on
the inhibiting effects of SKF may appear to contradict the literature on the ameliorative
effects of mPFC-D1 agonism in aging, and other forms of pathological neurodegeneration
and dysfunction (Deutch, 1993; Dolan et al., 1994; Fibiger, 1995).
However, D1 activity have been reported be constitute an inverse U-function, wherein hypo
or hyper-activation of these receptors causing a dysfunction, thereby impairing associated D1
mechanisms (Arnsten, 1998; Zahrt, Taylor, Mathew, & Arnsten, 1997). In accord, mPFC
dysfunction, such as in the case of Parkinson‟s disease, is treated via D1 agonism (Zahrt et
al., 1997). Futhermore, chronic stress causes hyper-activation of D1 which impairs working
memory, with administration of D1 antagonists reversing the effect (Zahrt et al., 1997).
Taken together, mPFC-D1 activity may be responsible for the modulation of working

memory. The present study also focused on the functional differentiation of the IL and PL
cortices of the mPFC. These two sub-regions appear to be functionally distinct from the
literature (Balleine & O‟Doherty, 2010). However, due to the theorised hyper-activation
produced by SKF any functional distinction is indistinguishable. A theory supported by the
lack of any significant difference between the two drug conditions in both trace interval
groups. It is of importance to emphasize that SKF has shown to have a beneficial effect on
working memory, administered via either systemically or intra-mPFC infusion (Granon,
Passetti, Thomas, Dalley, Everitt, & Robbins, 2000), in subjects which have an underlying
degenerative pathology, such as in aging (Cai & Arnsten, 1997) or Parkinson‟s disease
(Lange, Robbins, Marsden, James, Owen, & Paul, 1992).
Interestingly the saline and both drug conditions did not display a difference of responding
under the 10-second trace interval group. Across 30 trials within each day and across the four
days the rate of responding remained at base levels entirely for all three conditions. It is then
reasonable to conclude that D1 activity, at normal or hyper-activated levels in healthy
subjects, bears no effect upon trace learning over certain time intervals. Examining the five
two-second bins of the 10-second trace interval supports this conclusion. If trace learning of a
10 second interval between the US and CS were successful, responding within the five bins
would be expected to polarise at the last two bins. The literature on the learning of fixed time
intervals, known as a fixed interval schedule, reports a „scallop‟ pattern of responding
(Pavlov, 1928; Skinner, 1938). The temporal expectation of a US delivery from the CS onset
is driven by dopaminergic mechanisms (Schultz, 1998). The pattern of responding is a result
of successfully learning that a CS/reward will only be delivered after a fixed amount of time
and as such responding will is only reinforced near this point of time. However, within the
present study responding was evenly distributed throughout the five bins. Particularly

illustrative of this is the PL group which on Day 3 responding most within the first and fifth
bin.
Noteworthy is how responding was measured as the behaviour of nose poking, detected by a
rat pushing open a flap to access the food dispenser. It is possible that a rat may remain
stationed at the food dispenser, keeping the flap open indefinitely and as such preventing
measurement of behaviour. The number of nose poking responses signifies learning of the
US-CS contingency. Although if a rat has learnt this contingency but remains at the food
dispenser resulting in less nose pokes, the data will suggest a lower rate of responding. As
such it is possible that rats within a particular condition exhibited a higher rate of responding
but, due to the limitation of the apparatus, this difference is not represented. Another possible
confounding element of the study is the duration of SKF effects. Surrounding research which
implemented SKF has documented the D1 agonistic effect to last up to 30 minutes
(Mizoguchi, Yuzurihara, Ishige, Sasaki, Chui, & Tabira, 2000; Sorg et al., 2001; Zahrt et al.,
1997). Within this study rats were within the task for up to 65 minutes, it is unknown if the
effects of SKF lasted the entire duration of the task.
In conclusion, the functional role of PL and IL in learning and memory of a temporally
distant US-CS were not distinguished. However, as both the PL and IL conditions appeared
to be inhibited by SKF. It may then be inferred that the two sub-regions are involved to in the
temporal learning aspect of working memory, albeit to an extent as all three conditions
responded at baseline levels under the 10-second interval group. The lack of learning within
the 10-second trace interval group may signify that the length of this trace interval is too
great. In a similar study, Floresco & Phillips (2001) focused on significantly longer time

intervals, they reported SKF to augment learning between learning a task and repeating the
task after a 12 hour delay. Moreover, the Floresco & Phillips (2001) study found that at
delays of 30 minutes SKF inhibited repetition of the task. In converging the discussed
findings and surrounding literature it would appear the mechanisms of D1 activity are
sensitive to either hypo or hyper-activation and also the length of the time interval.

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