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.

http://www.jneurosci.org/content/24/6/1288.long#ref-15






http://www.jneurosci.org/content/27/4/840.full#ref-40

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.

5. References

Andersen, P. H., & Jansen, J. A. (1990). Dopamine receptor agonists: selectivity and D1

receptor efficacy. European Journal of Pharmacology, 188, 335–347.

Arnsten, A. F. T. (1998). Catecholamine modulation of prefrontal cortical cognitive function.

Trends in Cognitive Science, 2, 436-447.

Arnsten, A. F. T., Cai, J. X., Murphy, B. L., & Goldman-Rakic, P. S. (1994). Dopamine D1

receptor mechanisms in the cognitive performance of young adult and aged monkeys.

Psychopharmacology, 116, 143-151.

Balleine, B. W., & O‟Doherty, J. P. (2010). Human and rodent homologies in action control:

corticostriatal determinants of goal-directed and habitual action. Neuropsychopharmacology

35, 48–69.

Burgos-Robles, A., Bravo-Rivera, H., & Quirk, G. J. (2013). Prelimbic and Infralimbic

Neurons Signal Distinct Aspects of Appetitive Instrumental Behavior. PLOS ONE, 8,

Cai, J. X., & Arnsten, A. F. T. (1997). Dose-dependent effects of the dopamine D1 receptor

agonists A77636 or SKF81297 on spatial working memory in aged monkeys. Journal of

Pharmacology and Experimental Therapy, 283, 183–189.

Cassaday, H. J., Horsley, R. R., & Norman, C. (2005). Electrolytic lesions to nucleus

accumbens core and shell have dissociable effects on conditioning to discrete and contextual

cues in aversive and appetitive procedures respectively. Behavioural Brain Research, 160,

222–235.

Collins, P., Wilkinson, L. S., Everitt, B. J., Robbins, T. W., & Roberts, A. C. (2000). The

effect of dopamine depletion from the caudate nucleus of the common marmoset (Callithrix

jacchus) on tests of prefrontal cognitive function. Behavioural Neuroscience, 114, 3-17.

Coutureau, E., & Killcross, S. (2003) Inactivation of the infralimbic prefrontal cortex

reinstates goal-directed responding in overtrained rats. Behaviour and Brain Research, 146,

167–174.

Dalley, J. W., Chudasama, Y., Theobald, D. E., Pettifer, C. L., Fletcher, C. M., & Robbins, T.

W. (2002) Nucleus accumbens dopamine and discriminated approach learning: interactive

effects of 6-hydroxydopamine lesions and systemic apomorphine administration.

Psychopharmacology 161, 425–433.

Deutch, A. Y. (1993). Prefrontal cortical dopamine systems and the elaboration of functional

corticostriatal circuits: implications for schizophrenia and Parkinson's disease. Journal of

Neural Transmission, 91, 197–221.

Dias, R., Robbins, T. W., & Roberts, A. C. (1997) Dissociable forms of inhibitory control

within prefrontal cortex with an analog of the Wisconsin card sort test: restriction to novel

situations and independence from “on-line” processing. Journal of Neuroscience, 17, 9285-

9297.

Dolan, R. J., Bench, C. J., Brown, R. G., Scott, L. C., & Frackowiak, R. S. (1994).

Neuropsychological dysfunction in depression: the relationship to regional cerebral blood

flow. Psychological Medicine, 24, 849-857.

Feenstra, M. G. P., Vogel, M., Botterblom, M. H. A., Joosten, R. N. J. M. A., & de Bruin, J.

P. C. (2001). Dopamine and noradrenaline efflux in the rat prefrontal cortex after classical

aversive conditioning to an auditory cue. European Journal of Neuroscience, 13, 1051–1054.

Floresco, S. B., Braaksma, D. N., & Phillips, A. G. (1999). Thalamic-cortical-striatal circuitry

subserves working memory during delayed responding on a radial arm maze. Journal of

Neuroscience, 19, 11061-11071.

Floresco, S. B., & Phillips, A. G. (2001). Delay-dependent modulation of memory retrieval

by infusion of a dopamine D1 agonist into the rat medial prefrontal cortex. Behavioral

Neuroscience, 115, 934–993.

Fibiger, H. C. (1995). Neurobiology of depression: focus on dopamine. Advances in

Biochemical Psychopharmacology, 49, 1–17.

Fuster, J. M., Bodner, M., & Kroger, J. (2000). Cross-modal and cross-temporal association

in neurons of frontal cortex. Nature, 405, 347-351.

Granon, S., Passetti, F., Thomas, K. L., Dalley, J. W., Everitt, B. J., & Robbins, T. W. (2000).

Enhanced and impaired attentional performance after infusion of D1 dopaminergic receptor

agents into rat prefrontal cortex. Journal of Neuroscience, 20, 1208-1215.

Harada, N., Nishiyama, S., Satoh, K., Fukumoto, D., Kakiuchi, T., & Tsukada, H. (2002).

Age-related changes in the striatal dopamine system in the living brain: a multiparametric

study in conscious monkeys. Synapse, 45, 38–45.

Kantini, E., Norman, C., & Cassaday, H. J. (2004). Amphetamine decreases the expression

and acquisition of appetitive conditioning but increases the acquisition of anticipatory

responding over a trace interval. Journal of Psychopharmacology, 18, 516–526.

Killcross, S., & Coutureau, E. (2003). Coordination of actions and habits in the medial

prefrontal cortex of rats. Cerebral Cortex, 13, 400–408.

Kronforst-Collins, M A., & Disterhoft, J. F. (1998). Lesions of the caudal area of rabbit

medial prefrontal cortex impair trace eyeblink conditioning. Neurobiology of Learning and

Memory, 69, 147-162.

Lange, K. W., Robbins, T. W., Marsden, C. D., James, M., Owen, A. M., & Paul, G.

M. (1992) L-dopa withdrawal in Parkinson's disease selectively impairs cognitive

performance in tests sensitive to frontal lobe dysfunction. Psychopharmacology, 107, 394–

404.

McLaughlin, J., Skaggs, H., Churchwell, J., & Powell, D. A. (2002). Medial prefrontal cortex

and Pavlovian conditioning: trace versus delay conditioning. Behavioral Neuroscience,

116, 37-47.

Mizoguchia, K., Yuzurihara, M., Ishige, A., Sasaki, H., Chui, D. H., & Tabira, T. (2000).

Journal of Neuroscience, 20, 1568-1578.

Mizoguchia, K., Yuzurihara, M., Nagata, M., Ishige, A., Sasaki, H., & Tabira, T. (2002).

Dopamine-receptor stimulation in the prefrontal cortex ameliorates stress-induced rotarod

impairment. Pharmacology, Biochemistry, and Behavior, 72, 723-728.

Moore, T. L., Killiany, R. J., Herndon, J. G., Rosene, D. L., & Moss, M. B. (2003).

Impairment in abstraction and set shifting in aged hesus monkeys. Neurobiology of Aging, 24,

125–134.

Murphy, E. R., Fernando, A. B., Urcelay, G. P., Robinson, E. S., Mar, A. C., Theobald, D. E.

H., Dalley, J. W., & Robbins, T. W. (2012). Impulsive behaviour induced by both NMDA

receptor antagonism and GABAA receptor activation in rat ventromedial prefrontal cortex.

Psychopharmacology, 219, 401–410.

Nieoullon, A. (2002). Dopamine and the regulation of cognition and attention. Progressive

Neurobiology, 67, 53–83.

Ostlund, S. B., & Balleine, B. W. (2005). Lesions of medial prefrontal cortex disrupt the

acquisition but not the expression of goal-directed learning. Journal of Neuroscience, 25,

7763–7770.

Packard, M. G. (1999). Dissociation of multiple memory systems by posttraining

intracerebral injections of glutamate. Psychobiology, 127, 40-50.

Pavlov, I. P. (1927). Conditioned reflexes: an investigation of the physiological activity of the

cerebral cortex. London: Oxford UP.

Pavlov, I. P. (1928). Lectures on conditioned reflexes: The higher nervous activity of animals.

London: Lawrence & Wishart.

Schultz, W. (1998). Predictive reward signal of dopamine neurons. Journal of

Neurophysiology, 80, 1–27.

Skinner, B. F. (1938). The behavior of organisms. New York: Appleton-Century-Crofts.

Sorg, B. A., Li, N., & Wu, W. R. (2001). Dopamine D1 receptor activation in the medial

prefrontal cortex prevents the expression of cocaine sensitization. Journal of Pharmacology

and Experimental Therapy, 297, 501-508.

Vidal-Gonzalez, I., Vidal-Gonzalez, B., Rauch, S. L., & Quirk, G. J. (2006) Microstimulation

reveals opposing influences of prelimbic and infralimbic cortex on the expression of

conditioned fear. Learning & Memory, 13, 728–733.

Waelti, P., Dickinson, A., & Schultz, W. (2001). Dopamine responses comply with basic

assumptions of formal learning theory. Nature, 412, 43–48.

Zahrt, J., Taylor, J. R., Mathew, R. G., & Arnsten, A. F. T. (1997). Supranormal stimulation

of D1 dopamine receptors in the rodent prefrontal cortex impairs working memory

performance. Journal of Neuroscience, 17, 8528-8535.

effect of d1 receptor agonist within the mpfc

Documents