The Journal of Neuroscience, July 23, 2003, 23(16):6475-6479
Previous Article | Next Article 
BRIEF COMMUNICATION
Functional Specialization within Medial Frontal Cortex of the Anterior Cingulate for Evaluating Effort-Related Decisions
Mark E. Walton,
David M. Bannerman,
Karin Alterescu, and
Matthew F. S. Rushworth
Department of Experimental Psychology, Oxford, OX1 3UD, United
Kingdom
 |
Abstract
|
|---|
The rat medial frontal cortex (MFC) has been implicated in allowing animals
to work harder to receive larger rewards. However, it is unknown what role the
individual MFC regions [anterior cingulate cortex (ACC) and
prelimbic-infralimbic cortex (PL-IL)] play in such decision making. To
investigate this, we trained rats on a T-maze cost-benefit task with two
possible courses of action, shown previously to be affected by complete MFC
lesions. One response involved climbing a 30 cm barrier to obtain a large
quantity of reward (high cost-high reward), whereas the other had a lower
energetic demand but also a smaller reward gain (low cost-low reward). Before
surgery, all animals preferred to select the high cost-high reward option.
However, after excitotoxic ACC lesions, there was a complete reversal of
behavior, with the ACC group selecting the low cost-low reward response on
nearly every trial. In contrast, both control animals and rats with PL-IL
lesions continued to choose to climb the barrier for the larger reward. When
the same rats were tested on a delayed match-to-sample paradigm however, it
was the PL-IL group that was significantly impaired at learning the response
rule, with the performance of ACC rats being comparable with controls. This
double dissociation indicates that the ACC is the important region within the
MFC when evaluating how much effort to expend for a specific reward.
Key words: cingulate cortex; decision making; cost-benefit; effort; prelimbic cortex; reward
 |
Introduction
|
|---|
The medial frontal cortex (MFC) forms part of an extended frontostriatal
circuit with direct influence over both the mesolimbic dopamine and motor
systems; as such, it is in a prime position to influence behavioral choice. In
a previous study, we demonstrated that rat MFC, including the anterior
cingulate cortex (ACC) and prelimbic and infralimbic areas (PL-IL), is
important for allowing animals to put in more work to receive greater rewards
(Walton et al., 2002
).
Specifically, whereas animals typically chose to put in work for an increased
quantity of food, after lesions to the MFC, there was a complete reversal in
behavior, the lesioned rats always selecting the response involving less work
and smaller reward. This was not caused by insensitivity to costs and
benefits, however, because reducing the energetic demands or increasing the
reward associated with the high-effort response caused the animals with MFC
lesions to return to the high cost-high reward option.
However, it is not clear what role the individual areas of the MFC play in
overcoming effort constraints to obtain greater reward. All of the MFC
projects to the nucleus accumbens (NAc)
(Berendse et al., 1992
), which
is also known to be involved in evaluating the costs and benefits of actions
(Salamone et al., 1997
;
Cardinal et al., 2001
).
Moreover, although lesions to various parts of the MFC have been shown to
cause impairments in behavioral flexibility and attention
(Muir et al., 1996
;
Bussey et al., 1997
;
Brown and Bowman, 2002
), it has
proved difficult thus far to show functional dissociations on separate tasks
between these areas. In particular, there has been little consistent evidence
of what role the ACC might play.
There is some indication from primate studies suggesting that the ACC might
be a good candidate for influencing effort-based decision making. Cells have
been reported in this region that respond while working toward or receiving
rewards (Akkal et al., 2002
;
Shidara and Richmond, 2002
).
Moreover, ACC lesions cause impairments in the ability to link particular
movements with reinforcers (Hadland et
al., 2003
).
The aim of the present study, therefore, was to investigate the effects of
either ACC (including both Cg1 and Cg2 fields of ACC)
(Zilles, 1985
) or PL-IL
lesions on the ability of rats to choose how much effort to exert to obtain a
particular size of reward. Initially, we tested rats on the T-maze
cost-benefit paradigm used previously
(Salamone et al., 1994
;
Walton et al., 2002
), in which
animals could elect either to a obtain small reward in one arm or to climb a
barrier to receive high reward in the other. Subsequently, the same animals
were run on a delayed match-to-sample (DMTS) task, which has been shown to be
sensitive to MFC lesions (Dias and
Aggleton, 2000
).
 |
Materials and Methods
|
|---|
Animals. Thirty male Lister hooded rats,
2 months of age at
the start of testing, were used for both experiments. All animals were housed
in groups of three under a 12 hr light/dark cycle (lights on at 7:00 A.M.). At
surgery, rats weighed 300-380 gm. The experiments described were conducted in
accordance with the UK Animals Scientific Procedures Act (1986), under project
license number PPL 30/1505.
Surgical procedures. Rats received excitotoxic bilateral ACC
lesions (n = 10), PL-IL lesions (n = 10), or sham surgery
(n = 10) after training on the cost-benefit task. Assignment of
lesion groups was counterbalanced according to preoperative performance and
the right-left orientation of the rewards. Lesions were produced by infusing
quinolinic acid (0.09 M) through a 10 µl syringe with a
specially adapted 34 gauge needle mounted onto the stereotaxic frame. All
animals were anesthetized with avertin (0.29 gm/kg, i.p.) and placed in a
stereotaxic frame with the head level between bregma and lambda. An incision
was made along the mid-line, and a craniotomy was performed before injections
were made at the following coordinates relative to bregma or dura for
dorsoventral (DV) coordinates (volume of 0.2 µl unless specified): for ACC
lesion, antero-posterior (AP), +2.3, mediolateral (ML), ±0.5; DV, -1.5;
AP, +1.6; ML, ±0.5; DV, -2.0; AP, +0.9; ML, ±0.5; DV, -2.0; AP,
+0.2; ML, ±0.5; DV, -2.0; for PL-IL lesion, AP, +3.3; ML, ±0.5;
DV, -3.5; AP, +2.6; ML, ±0.5; DV, -3.5 (0.25 µl). Infusions were
made manually at a rate of 0.1 µl every 30 sec, with a 30 sec interval
between each 0.1 µl infusion. The needle was then left in place for another
3 min to ensure that diffusion occurred away from the injection site. Sham
animals received only a craniotomy. After completion of surgery, all animals
were sutured and a topical antibiotic powder (P.E.P. 2% powder; Intervet
Laboratories, Cambridge, UK) was sprinkled over the wound.
Histology. At the conclusion of behavioral testing, rats were
anesthetized with sodium pentobarbitone (200 mg/kg) and perfused
transcardially with physiological saline and 10% formal saline. The brains
were removed and placed into a formal saline solution before being stored in a
sucrose-formalin solution for 24 hr, frozen, and then sectioned coronally (50
µm). All sections were mounted and stained with cresyl violet. The lesions
are described in terms of the nomenclature and classification of cortical
areas adopted by Paxinos and Watson
(1998
).
Experiment 1: cost-benefit T-maze
Apparatus. Rats were tested on a high-sided wooden T-maze,
consisting of one start arm and two goal arms, each being 60 cm long, 10 cm
wide, and 30 cm high. Food rewards (45 mg food-reinforcement pellets, Formula
A/I; P. J. Noyes, Lancaster, NH) were placed in raised metal wells 2 cm from
the far end of each goal arm. Barriers were constructed from wire mesh in the
shape of a three-dimensional triangle. These were placed at the midpoint of
each goal arm as required, meaning that animals had to scale the vertical side
and descend the slope corresponding to the hypotenuse to obtain rewards. On
"forced" trials, a 30-cm-high, 10-cm-wide wooden block was placed
to prevent access to one goal arm.
Training and testing procedures. For detailed methods on
habituation and training schedule, see the study by Walton et al.
(2002
). In brief, after
habituation, four food pellets were placed in one goal arm [high reward (HR)]
and two pellets in the other [low reward (LR)]. For one-half of the animals,
the HR arm was to the left. Once all animals had been trained to choose the HR
arm on
80% trials, a 15 cm barrier was introduced into the HR arm. When
all animals returned to selecting the HR arm on
80% of trials, the
barrier size was increased by 5 cm, and then by 5 cm every 2 d up to a maximum
of 30 cm. For the first two trials occurring each day, and on all subsequent
testing, the rats were forced in opposite directions. They were then given 10
choice trials, with an intertrial interval of
5 min.
During prelesion and the first postlesion testing block (blocks A and B,
each consisting of3dof10 choice trials), the 30 cm barrier was placed in the
HR arm while the LR arm was vacant. For the second postlesion testing block
(block C), identical 30 cm barriers were present in both arms to measure
whether any deficit was caused by a spatial or motor impairment or by an
inability to remember reward quantity.
Experiment 2: DMTS
Apparatus and testing. Rats were run on an elevated, low-walled
T-maze (2 cm high, with the maze 40 cm above floor level) of otherwise
identical size to that used in experiment 1. Testing began
4 months after
the end of experiment 1 and took place in a different room containing novel
distal cues. Rats were habituated to the maze in the same manner as in
experiment 1. During testing, each trial consisted of a sample run in which
the animal was forced by a wooden block to select a particular goal arm for a
single food pellet reward, followed by a choice run in which both goal arms
were open. A correct trial, rewarded with two food pellets, required making
the same response in the choice as in the sample run (i.e.,
matching-to-position). The direction of the sample response was generated
pseudorandomly for each animal, with equal numbers of left and right turns
across 10 trials and no more than three successive turns in the same
direction. There was a delay of
10 sec between the sample and choice
phases. A trial was considered to be concluded once the animal had visited one
of the two food wells. Testing was divided into sessions of 10 trials and
continued until 24 sessions had been completed.
 |
Results
|
|---|
Histology
Both sets of lesions were highly restricted, and there was little overlap
between the groups. ACC lesions were all consistent and reproducible, with
little overall difference in size between animals (Figs.
1, left column,
2, middle row). Generally, any
variation consisted of a rostrocaudal shift in the lesion, with the small
lesion depicted in Figure 1
representing the furthest posterior starting point of cell damage. The lesion
produced extensive cell loss in the entire ACC, extending back to
0.8-0.2
mm anterior to bregma. This is
0.5-1 mm more anterior than the extent of
ACC damage in our previous study (Walton
et al., 2002
). In all animals, there was some sparing of the
rostral ACC in the most anterior sections (3.7 mm anterior to bregma). At
supracallosal levels, there was also partial damage to secondary motor
cortex.

View larger version (41K):
[in this window]
[in a new window]
|
Figure 1. Representations of the maximal (gray shading) and minimal (black shading)
examples of both the ACC (left) and PL-IL (right) lesions.
|
|

View larger version (77K):
[in this window]
[in a new window]
|
Figure 2. Photomicrographs of coronal sections showing typical cell loss for a
representative ACC-lesioned (middle) and PL-IL-lesioned (bottom) animal. The
boxed regions in the top panels (brain outlines) are shown at high
magnification in the middle and bottom panels. The extent of the lesion is
indicated by the black arrowheads. Note that both ACC and PL-IL lesions are
complete and separate at sections 2.7 mm anterior to bregma.
|
|
Two of the PL-IL lesions showed extensive sparing of tissue in either one
or both hemispheres and were thus excluded from analysis. However, the eight
remaining lesions were as intended, centered on the PL-IL, and again showed
little variation between animals (Figs.
1, right column,
2, bottom row). The majority of
lesions had some sparing of the PL in the most anterior sections. Otherwise,
the lesion completely removed the PL-IL in all animals, except one for which
there was slight sparing of the dorsal-most portion of the PL throughout. In
anterior sections, cell loss included parts of the medial orbital cortex,
extending in the largest case into the ventral orbital cortex. Damage also
extended ventrally to include the dorsopeduncular cortex.
Experiment 1: cost-benefit T-maze
The rats were divided into three groups on the basis of their prelesion
performance. As can be seen in Figure
3 (block A), all three groups showed a strong preference to climb
the barrier to obtain the high reward. After surgery, there was a marked
change in behavior of the group with ACC lesions, with all animals selecting
the low-reward option on most trials. In contrast, although there was a
tendency for more LR choices than during the prelesion testing, the majority
of rats in both the sham and PL-IL groups continued to prefer the HR arm
(Fig. 3, block B). This was
confirmed by an ANOVA that showed a significant interaction between testing
block (blocks A and B) and lesion group (F(2,25) = 5.81;
p < 0.01). To explore this more closely, an additional ANOVA was
run on postlesion data (block B). This confirmed the significant difference
between the groups (F(2,25) = 3.42; p < 0.05),
and post hoc Fisher's least significant difference (LSD) tests showed
that this was caused by ACC animals making significantly more LR arm choices
than both the sham and PL-IL groups (p < 0.05). However, there
were no differences in choices between the sham and PL-IL animals.

View larger version (23K):
[in this window]
[in a new window]
|
Figure 3. Mean ± SE number of choices per day (maximum of 10) that the ACC,
PL-IL, and sham groups selected the HR arm when performing the cost-benefit
T-maze task. The left panel represents prelesion performance (block A), and
the middle panel represents postlesion performance with a single 30 cm barrier
in the HR arm (block B). Data in the right panel correspond to postlesion
testing with an identical 30 cm barrier in each goal arm (block C).
|
|
The introduction of a second identical 30 cm barrier in the LR arm caused
all three groups to return to selecting the HR arm on nearly every trial
(Fig. 3, block C). An ANOVA
comparing the postlesion one-barrier condition and two-barrier condition
(blocks B and C) across all groups showed a significant testing block by day
by group interaction (F(2,36) = 4.58; p <
0.05) caused by this change in behavior and the fact that the animals with ACC
lesions shifted further than either of the other groups. By days 2 and 3 of
the two-barrier block, there were no differences between the three groups
(both F(2,27) < 2; NS).
Experiment 2: DMTS
Acquisition of the match-to-sample rule was designated by the achievement
of 85% correct across two sessions of testing (equivalent to a score of
17 of 20). For the purposes of analysis, any animals that did not reach this
criterion were counted as taking the maximum 24 sessions. Because this caused
clear violations of normality assumptions, comparisons between the groups
using the criterion measure were made using nonparametric statistics.
The average number of sessions to reach criterion can be seen in
Figure 4a. It is clear
that the rats in both the sham and ACC groups learned the task in a comparable
amount of time, whereas the PL-IL group took markedly longer. A significant
difference between the groups is borne out by a Kruskal-Wallis test
(H = 8.20; p < 0.05), and subsequent Mann-Whitney tests
demonstrated that PL-IL animals took significantly more sessions to achieve
criterion than either the ACC or sham groups (both p < 0.05;
two-tailed).
Inspection of acquisition indicated that there were several phases involved
in learning the DMTS task (Fig.
4b). Following Dias and Aggleton
(2000
), we divided the data
for each animal into an initial "perseveration" phase, in which
animals tended to respond according to their innate nonmatching preference
(
25%, or
5 of 20 correct across two test sessions), a "response
bias" phase, in which animals adopted a strategy of always turning in
the same direction during the choice run (between 25 and 50% correct), and
finally, a "rule-learning" phase, during which the rats acquired
the matching rule (
50% correct). The number of errors made during each
phase can be seen in Figure
4c. An ANOVA showed a significant group by test phase
interaction (F(4,50) = 3.34; p < 0.05).
Subsequent analyses demonstrated that there were significant group differences
during perseveration (F(2,27) = 4.56; p <
0.05) and rule learning (F(2,27) = 4.46; p <
0.05). Fisher's LSD tests indicated that during the perseveration phase, this
was caused by both lesion groups making more errors than sham animals
(p < 0.05). However, only the PL-IL group was impaired at learning
the rule (p < 0.05, compared with sham and ACC groups); animals
with ACC lesions performed similarly to controls.
 |
Discussion
|
|---|
The results from experiment 1 demonstrate that the ACC is the essential
region of the rat MFC that allows animals to exert effort to obtain a larger
reward. Excitotoxic lesions of the ACC caused rats to switch from climbing a
barrier to obtain a larger reward to selecting the low effort-low reward
option on nearly every trial, replicating our findings with large MFC lesions
(Walton et al., 2002
). In
contrast, rats with lesions to adjacent regions of the MFC (namely, the PL-IL)
performed identically to the control animals. These results cannot be
attributed to a simple spatial or motor deficit, or to an inability to
remember reward quantity, because all ACC animals returned to choosing the
high-reward option when the energetic demands were equated by putting an
identical barrier in both goal arms. Moreover, the behavioral change in the
ACC group relative to the PL-IL group was not caused by a larger lesion size,
because when the same rats were tested on a spatial matching-to-sample task,
the ACC group learned the rule in a similar amount of time to the controls; in
contrast, the PL-IL animals were impaired at this task.
The bias toward low-effort responses in rats with ACC lesions but not those
with PL-IL lesions on the cost-benefit task is interesting for several
reasons. First, a similar set of studies by Salamone et al.
(1994
) and Cousins et al.
(1996
) showed that dopamine
depletions of the NAc also reduced the preference of animals to work for
higher reward. However, not only the ACC but also the PL-IL projects to the
NAc (Berendse et al., 1992
;
Brog et al., 1993
), and both
have direct influence on the origin of the mesolimbic dopamine system (the
ventral tegmental area) through reciprocal connections
(Uylings and van Eden, 1990
).
One possibility is that both top-down and bottom-up interactions between the
ACC and subcortical centers with influence over the production of
monoaminergic neurotransmitters are crucial for allowing an animal to overcome
effort constraints to achieve a larger reward.
Furthermore, it seems that the ACC is not needed in all situations
requiring an assessment of costs and benefits. A recent study by Cardinal et
al. (2001
) examining impulsive
choice in rats found that only lesions to the NAc core, but not to either the
ACC or the PL-IL, induced a shift toward choosing the immediate low-reward
option when faced with a choice between this and a delayed but larger reward.
This raises the intriguing possibility that the ACC might be important only
when assessing how much effort to expend for a specific reward and not when
evaluating delay-based costs (or more generally, only when ascribing value to
courses of action).
Such a description of ACC function is bolstered by findings that there are
cells in this region of primate cortex that appear to be concerned with
selecting responses on the basis of their reinforcing outcome
(Shima and Tanji, 1998
;
Procyk et al., 2000
), and one
of the few lesion studies of the primate ACC found a selective impairment in
using rewards to guide action (Hadland et
al., 2003
). Similarly, several human neuroimaging experiments have
reported ACC activity when choosing between and monitoring the consequences of
actions with different potential sizes of reward
(Bush et al., 2002
;
Gehring and Willoughby, 2002
).
Finally, and of particular relevance to the present study, Shidara and
Richmond (2002
) found that
nearly one-third of neurons in the rostral ACC progressively increased their
firing as animals advanced through a fixed schedule of trials for reward.
However, these responses disappeared if the length of the schedule was
randomized, suggesting that they were concerned with the amount of work
required to obtain an expected outcome.
Such a conclusion is based on the assumption of homology between the rodent
and primate MFC. Although there is contention over whether the PL-IL should be
compared with the ventromedial or dorsolateral prefrontal cortex in primates
(Preuss, 1995
;
Brown and Bowman, 2002
), there
is good anatomical correspondence between ACC regions in the two species, with
both projecting to analogous regions of the mediodorsal nucleus of the
thalamus, and both sharing similar subcortical connections
(Uylings and van Eden, 1990
;
Bachevalier et al., 1997
).
Moreover, in addition to the functional similarities in terms of reward
processing described above, both the rat and primate ACC, unlike any other
frontal regions, contain neurons that respond to noxious stimulation and play
a role in processing pain-related unpleasantness
(Devinsky et al., 1995
;
Johansen et al., 2001
).
Although lesions to the PL-IL had no discernable effect on rats' ability to
make effort-based decisions, they did cause a notable impairment in learning
the DMTS task, a finding that concurs with the previous study of the effects
of MFC lesions using this paradigm (Dias
and Aggleton, 2000
). As reported by Dias and Aggleton
(2000
), there appeared to be
two different phases of impairment. Initially, both lesion groups persisted in
responding using their innate nonmatching preference compared with control
animals. However, it was only the PL-IL group, and not ACC animals, who made
significantly more errors in switching from a subsequent side-bias strategy to
learning the matching rule. This pattern of results for ACC animals was
similar to that observed by Dias and Aggleton
(2000
), although their ACC
lesion only encompassed the pregenual ACC dorsal and rostral to the corpus
callosum, whereas cell loss in the present study also included supracallosal
ACC regions. It is unlikely that either impairment in the PL-IL group reflects
spatial working memory problems, because all animals were initially able to
perform with a non-matching bias. Moreover, the rapid change in behavior
observed in all groups on the cost-benefit task when energetic requirements
were equated (experiment 1, block C) argues against a simple deficit in
response reversal. Rather, our findings are consistent with those of several
other groups indicating that the PL-IL, rather than other areas of the MFC, is
involved in using recently acquired information to guide actions and switch
strategies (Delatour and Gisquet-Verrier,
1999
; Ragozzino et al.,
1999
; Birrell and Brown,
2000
; Dias and Aggleton,
2000
).
The combination of results from experiments 1 and 2 provides the first
direct demonstration of a double dissociation between two regions of the MFC
using the same rats being tested on different tasks. The selective nature of
the deficit on both tasks reinforces the notion that despite their similar
anatomy and large number of interconnections, ACC and PL-IL are functionally
independent (Passetti et al.,
2002
). Furthermore, the discovery of a particular role for the ACC
in evaluating the costs and benefits of working for a larger reward opens up
several avenues for research into how this region participates in choosing
between multiple courses of action.
 |
Footnotes
|
|---|
Received Mar. 4, 2003;
revised May. 27, 2003;
accepted May. 27, 2003.
This work was supported by the Medical Research Council and a Wellcome
Prize Studentship to M.E.W. D.B. was funded from a Wellcome Project Grant
awarded to J. N. P. Rawlins. We thank Greg Daubney for his assistance with
histology.
Correspondence should be addressed to Mark Walton, Department of
Experimental Psychology, South Parks Road, Oxford, OX1 3UD, UK. E-mail:
mark.walton{at}psy.ox.ac.uk.
Copyright © 2003 Society for Neuroscience
0270-6474/03/236475-05$15.00/0
 |
References
|
|---|
Akkal D, Bioulac B, Audin J, Burbaud P (2002)
Comparison of neuronal activity in the rostral supplementary and cingulate
motor areas during a task with cognitive and motor demands. Eur J
Neurosci 15:
887-904.[Web of Science][Medline]
Bachevalier J, Meunier M, Lu MX, Ungerleider LG (1997)
Thalamic and temporal cortex input to medial prefrontal cortex in rhesus
monkeys. Exp Brain Res 115:
430-444.[Web of Science][Medline]
Berendse HW, Galis-de Graaf Y, Groenewegen HJ (1992)
Topographical organization and relationship with ventral striatal compartments
of pre-frontal corticostriatal projections in the rat. J Comp
Neurol 316:
314-347.[Web of Science][Medline]
Birrell JM, Brown VJ (2000) Medial frontal cortex
mediates perceptual attentional set shifting in the rat. J
Neurosci 20:
4320-4324.[Abstract/Free Full Text]
Brog JS, Salyapongse A, Deutch AY, Zahm DS (1993) The
patterns of afferent innervation of the core and shell in the
"accumbens" part of the rat ventral striatum: immunohistochemical
detection of retrogradely transported fluoro-gold. J Comp
Neurol 338:
255-278.[Web of Science][Medline]
Brown VJ, Bowman EM (2002) Rodent models of prefrontal
cortical function. Trends Neurosci 25:
340-343.[Web of Science][Medline]
Bush G, Vogt BA, Holmes J, Dale AM, Greve D, Jenike MA, Rosen BR
(2002) Dorsal anterior cingulate cortex: a role in reward-based
decision making. Proc Natl Acad Sci USA
99: 523-528.[Abstract/Free Full Text]
Bussey TJ, Muir JL, Everitt BJ, Robbins TW (1997)
Triple dissociation of anterior cingulate, posterior cingulate, and medial
frontal cortices on visual discrimination tasks using a touchscreen testing
procedure for the rat. Behav Neurosci
111: 920-936.[Web of Science][Medline]
Cardinal RN, Pennicott DR, Sugathapala CL, Robbins TW, Everitt BJ
(2001) Impulsive choice induced in rats by lesions of the nucleus
accumbens core. Science 292:
2499-2501.[Abstract/Free Full Text]
Cousins MS, Atherton A, Turner L, Salamone JD (1996)
Nucleus accumbens dopamine depletions alter relative response allocation in a
T-maze cost/benefit task. Behav Brain Res
74: 189-197.[Medline]
Delatour B, Gisquet-Verrier P (1999) Lesions of the
prelimbic-infralimbic cortices in rats do not disrupt response selection
processes but induce delay-dependent deficits: evidence for a role in working
memory? Behav Neurosci 113:
941-955.[Web of Science][Medline]
Devinsky O, Morrell MJ, Vogt BA (1995) Contributions
of anterior cingulate cortex to behaviour. Brain
118: 279-306.[Abstract/Free Full Text]
Dias R, Aggleton JP (2000) Effects of selective
excitotoxic prefrontal lesions on acquisition of nonmatching- and
matching-to-place in the T-maze in the rat: differential involvement of the
prelimbic-infralimbic and anterior cingulate cortices in providing behavioural
flexibility. Eur J Neurosci 12:
4457-4466.[Web of Science][Medline]
Gehring WJ, Willoughby AR (2002) The medial frontal
cortex and the rapid processing of monetary gains and losses.
Science 295:
2279-2282.[Abstract/Free Full Text]
Hadland KA, Rushworth MF, Gaffan D, Passingham RE
(2003) The anterior cingulate and reward-guided selection of
actions. J Neurophysiol 89:
1161-1164.[Abstract/Free Full Text]
Johansen JP, Fields HL, Manning BH (2001) The
affective component of pain in rodents: direct evidence for a contribution of
the anterior cingulate cortex. Proc Natl Acad Sci USA
98: 8077-8082.[Abstract/Free Full Text]
Muir JL, Everitt BJ, Robbins TW (1996) The cerebral
cortex of the rat and visual attentional function: dissociable effects of
mediofrontal, cingulate, anterior dorsolateral, and parietal cortex lesions on
a five-choice serial reaction time task. Cereb Cortex
6: 470-481.[Abstract/Free Full Text]
Passetti F, Chudasama Y, Robbins TW (2002) The frontal
cortex of the rat and visual attentional performance: dissociable functions of
distinct medial prefrontal subregions. Cereb Cortex
12: 1254-1268.[Abstract/Free Full Text]
Paxinos G, Watson C (1998) The rat brain in
stereotaxic coordinates, Ed 4. San Diego: Academic.
Preuss TM (1995) Do rats have prefrontal cortex? The
Rose-Woolsey-Akert program reconsidered. J Cogn Neurosci
7: 1-24.
Procyk E, Tanaka YL, Joseph JP (2000) Anterior
cingulate activity during routine and non-routine sequential behaviors in
macaques. Nat Neurosci 3:
502-508.[Web of Science][Medline]
Ragozzino ME, Detrick S, Kesner RP (1999) Involvement
of the prelimbicinfralimbic areas of the rodent prefrontal cortex in
behavioral flexibility for place and response learning. J
Neurosci 19:
4585-4594.[Abstract/Free Full Text]
Salamone JD, Cousins MS, Bucher S (1994) Anhedonia or
anergia? Effects of haloperidol and nucleus accumbens dopamine depletion on
instrumental response selection in a T-maze cost/benefit procedure.
Behav Brain Res 65:
221-229.[Web of Science][Medline]
Salamone JD, Cousins MS, Snyder BJ (1997) Behavioral
functions of nucleus accumbens dopamine: empirical and conceptual problems
with the anhedonia hypothesis. Neurosci Biobehav Rev
21: 341-359.[Web of Science][Medline]
Shidara M, Richmond BJ (2002) Anterior cingulate:
single neuronal signals related to degree of reward expectancy.
Science 296:
1709-1711.[Abstract/Free Full Text]
Shima K, Tanji J (1998) Role for cingulate motor area
cells in voluntary movement selection based on reward. Science
282: 1335-1338.[Abstract/Free Full Text]
Uylings HB, van Eden CG (1990) Qualitative and
quantitative comparison of the prefrontal cortex in rat and in primates,
including humans. Prog Brain Res 85:
31-62.[Medline]
Walton ME, Bannerman DM, Rushworth MF (2002) The role
of rat medial frontal cortex in effort-based decision making. J
Neurosci 22:
10996-11003.[Abstract/Free Full Text]
Zilles K (1985) The cortex of the rat.
Berlin: Springer.
This article has been cited by other articles:

|
 |

|
 |
 
J. R. St. Onge and S. B. Floresco
Prefrontal Cortical Contribution to Risk-Based Decision Making
Cereb Cortex,
November 5, 2009;
(2009)
bhp250v1.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
K. E. Shannon, C. Sauder, T. P. Beauchaine, and L. M. Gatzke-Kopp
Disrupted Effective Connectivity Between the Medial Frontal Cortex and the Caudate in Adolescent Boys With Externalizing Behavior Disorders
Criminal Justice and Behavior,
November 1, 2009;
36(11):
1141 - 1157.
[Abstract]
[PDF]
|
 |
|

|
 |

|
 |
 
V. Venkatraman, A. G. Rosati, A. A. Taren, and S. A. Huettel
Resolving Response, Decision, and Strategic Control: Evidence for a Functional Topography in Dorsomedial Prefrontal Cortex
J. Neurosci.,
October 21, 2009;
29(42):
13158 - 13164.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
W. Hauber and S. Sommer
Prefrontostriatal Circuitry Regulates Effort-Related Decision Making
Cereb Cortex,
October 1, 2009;
19(10):
2240 - 2247.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
M. J. Buckley, F. A. Mansouri, H. Hoda, M. Mahboubi, P. G. F. Browning, S. C. Kwok, A. Phillips, and K. Tanaka
Dissociable Components of Rule-Guided Behavior Depend on Distinct Medial and Prefrontal Regions
Science,
July 3, 2009;
325(5936):
52 - 58.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
S. Ghods-Sharifi, J. R. St. Onge, and S. B. Floresco
Fundamental Contribution by the Basolateral Amygdala to Different Forms of Decision Making
J. Neurosci.,
April 22, 2009;
29(16):
5251 - 5259.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
P. L. Croxson, M. E. Walton, J. X. O'Reilly, T. E. J. Behrens, and M. F. S. Rushworth
Effort-Based Cost-Benefit Valuation and the Human Brain
J. Neurosci.,
April 8, 2009;
29(14):
4531 - 4541.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
T. J. Vickery and Y. V. Jiang
Inferior Parietal Lobule Supports Decision Making under Uncertainty in Humans
Cereb Cortex,
April 1, 2009;
19(4):
916 - 925.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
M. M. Botvinick, S. Huffstetler, and J. T. McGuire
Effort discounting in human nucleus accumbens
Cogn Affect Behav Neurosci,
March 1, 2009;
9(1):
16 - 27.
[Abstract]
[PDF]
|
 |
|

|
 |

|
 |
 
S. M. Marcora, W. Staiano, and V. Manning
Mental fatigue impairs physical performance in humans
J Appl Physiol,
March 1, 2009;
106(3):
857 - 864.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
P. H. Rudebeck, T. E. Behrens, S. W. Kennerley, M. G. Baxter, M. J. Buckley, M. E. Walton, and M. F. S. Rushworth
Frontal Cortex Subregions Play Distinct Roles in Choices between Actions and Stimuli
J. Neurosci.,
December 17, 2008;
28(51):
13775 - 13785.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
S. B. Floresco, J. R. St. Onge, S. Ghods-Sharifi, and C. A. Winstanley
Cortico-limbic-striatal circuits subserving different forms of cost-benefit decision making
Cogn Affect Behav Neurosci,
December 1, 2008;
8(4):
375 - 389.
[Abstract]
[PDF]
|
 |
|

|
 |

|
 |
 
S. Mingote, L. Font, A. M. Farrar, R. Vontell, L. T. Worden, C. M. Stopper, R. G. Port, K. S. Sink, J. G. Bunce, J. J. Chrobak, et al.
Nucleus Accumbens Adenosine A2A Receptors Regulate Exertion of Effort by Acting on the Ventral Striatopallidal Pathway
J. Neurosci.,
September 3, 2008;
28(36):
9037 - 9046.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
E. Aarts, A. Roelofs, and M. van Turennout
Anticipatory Activity in Anterior Cingulate Cortex Can Be Independent of Conflict and Error Likelihood
J. Neurosci.,
April 30, 2008;
28(18):
4671 - 4678.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
H. Yamada, N. Matsumoto, and M. Kimura
History- and Current Instruction-Based Coding of Forthcoming Behavioral Outcomes in the Striatum
J Neurophysiol,
December 1, 2007;
98(6):
3557 - 3567.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
S. B. Floresco and S. Ghods-Sharifi
Amygdala-Prefrontal Cortical Circuitry Regulates Effort-Based Decision Making
Cereb Cortex,
February 1, 2007;
17(2):
251 - 260.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
J. Schweimer and W. Hauber
Dopamine D1 receptors in the anterior cingulate cortex regulate effort-based decision making
Learn. Mem.,
November 1, 2006;
13(6):
777 - 782.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
S. F. Taylor, B. Martis, K. D. Fitzgerald, R. C. Welsh, J. L. Abelson, I. Liberzon, J. A. Himle, and W. J. Gehring
Medial Frontal Cortex Activity and Loss-Related Responses to Errors
J. Neurosci.,
April 12, 2006;
26(15):
4063 - 4070.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
E. Hoshi, H. Sawamura, and J. Tanji
Neurons in the Rostral Cingulate Motor Area Monitor Multiple Phases of Visuomotor Behavior With Modest Parametric Selectivity
J Neurophysiol,
July 1, 2005;
94(1):
640 - 656.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
J. Schweimer and W. Hauber
Involvement of the rat anterior cingulate cortex in control of instrumental responses guided by reward expectancy
Learn. Mem.,
May 1, 2005;
12(3):
334 - 342.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
L. K. Fellows
The Cognitive Neuroscience of Human Decision Making: A Review and Conceptual Framework
Behav Cogn Neurosci Rev,
September 1, 2004;
3(3):
159 - 172.
[Abstract]
[PDF]
|
 |
|