Journal of Behavioral and Brain Science, 2012, 2, 156-161
http://dx.doi.org/10.4236/jbbs.2012.22018 Published Online May 2012 (http://www.SciRP.org/journal/jbbs)
Dissociation between Performances in Water Maze and
Spontaneous Alternation in BALB/c versus A/J Mice
Julien Celestine1*, Arnaud Tanti2, Arnaud Aubert3
1INSERM U930 E2 Neurogénétique et Neurométabolomique CHRU de Tours, Hôpital Bretonneau, 2 Boulevard Tonnellé, Bât B1A,
1er Etage, 37044 Tours Cedex 9, France
2Faculté des Sciences et Techniques, Université François Rabelais, Tours, France
3EA 2114, Psychologie des Ages de la Vie, Université de Tours, 3 Rue des Tanneurs , 37041 Tours Cedex 1, France
Received March 7, 2011; revised April 15, 2011; accepted May 7, 2011
ABSTRACT
Learning processes are extensively studied in behavioral neuroscience. As experimental models, Morris Water Maze
(MWM) and Spontaneous Alternation (SA) represent two of the most frequently used laboratory tests to respectively
address spatial vs non-spatial tasks. Several factors have been shown to impact on those learning, including strain, gen-
der, apparatus, conditioning, vision, lighting conditions and stress level. In order to focus on the later, we compared the
acquisition of two learning tasks (MWM and SA) in BALB/c and A/J mice, which are known as fearful and
stress-sensitive strains. Here, we report that BALB/c mice exhibited higher performances than A/J mice in the MWM
(i.e. spatial reference memory task), whereas A/J mice performed better in the SA (i.e. spatial working memory task).
These results indicate dissociated processes in the acquisition of spatial vs non-spatial tasks, and emphasize a varying
influence of emotional reactivity on different forms of cognition.
Keywords: Morris Water Maze; Spontaneous Alternation; Behavior; BALB/c; A/J; Learning
1. Introduction
Emotions are co mmonly descr ibed as the processes wh ere-
by brain could evaluate stimuli, basically as pleasant or
unpleasant [1-3], promoting either approach or avoidance
behaviors, thus supporting individual adaptation and sur-
vival. Such a key role in behavioral guidance and deci-
sion making is growingly been emphasized [1,2], and it
emotions are now commonly regarded as adaptive proc-
esses signaling relevant cues about environmental changes.
However, assessment of emotions remains a difficult task
[4], and especially in non-human animals where verbal
information is unavailable. Nevertheless, human and non-
human darwinian emotions share many biobehavioral
features [5]. This evolutionary common ground allows the
investigation of emotional state by using animal models
[4].
It has been argued that emotions represent a warning
system and a way to optimize action [6]. That is the rea-
son why animals could exhibit very different behaviors
under normal or stressful conditions. Throughout the
evolution of species, some behavioral mechanisms were
selected on the basis of their significant survival benefit.
Such behaviors like fear-induced freezing or fleeing are
considered are widespread evolutionary stable strategies
[7,8]. The selection of the final response (i.e. freezing or
fleeing) is largely dependent on actual emotional arousal
triggered by environmental cues. Emotions act as potent
factors for rapid adaptive decision making processes.
Therefore, they represent modulatory tools for cognition
rather than inhibitory factors.
Advances in psychology and neurosciences have also
shown that core cognitive functio ns such as learning and
memory share many complex interactions with emotional
processes. For example, patients suffering from various
mood disorders also express memory impairments, and
corresponding animal models were developed [4,5] to
better understand the mechanisms underlying these rela-
tions. Among the diverse experimental tests designed to
assess learning and memory in animals, two main cate-
gories of tests consist in reference versus working mem-
ory tasks [9,10], especially in rodent studies [11-16].
Morris Water Maze (MWM) [17] and Spontaneous Al-
ternation (SA) [18] for example became standard tasks to
explore such functions. Indeed, they are versatile and
allow many variations to assess specific processes and/or
factors (e.g. pharmacological agents, gen etic background
and neurological preparation).
While those behavioral models were generally design e d
for rats, mice are nowadays the main animal model in
*Corresponding a uthor.
C
opyright © 2012 SciRes. JBBS

J. CELESTINE ET AL. 157
behavioral neurosciences. Many mice strains are avail-
able, which constitute as many convenient models to
assess the roles and functions of various bio-behavioral
systems. A growing set of literature shows strain differ-
ences of performances in different experimental para-
digms [14-16,19-26]. For instance, it is commonly con-
sidered that BALB/c and A/J mice albino strains have
lower performances in mazes due to impaired visual ca-
pabilities, thus leadin g oth er strains su ch as C57 BL6 [27 ]
to be preferred. Nevertheless, th e poor visual cap abilities
of BALB/c and A/J mice are not necessarily the only
factor that could account for their learning performances.
Many factors and individual characteristics are known to
influence learning, such as strain, gender, apparatus fea-
tures, conditioning set, perceptive capabilities, lighting
and stress [14-16,21,22,28-30]. More specifically, BALB/c
and A/J are known to for displaying high emotional reac-
tivity compared to other mouse strains. Using two stan-
dard forms of reference and working memory tasks (i.e.
MWM and SA respectively), the aim of the present study
was to further understand the differences in learning
performances of two mice strains, respectively BALB/c
and A/J mice, regarded both as highly emotional and
poor learners. We aimed to show in that the relativity of
the “poor learner” label of these strains by demonstrating
that in specifics conditions of testing, they can express
efficient learning. Indeed, whereas these strains are com-
monly used in many stress studies [31], additional infor-
mation about their respective learning performances
would be needed to better differentiate the potentialities
of these animal models, especially in the scope to better
understand the relations between cognition, emotions and
stress. Using two different forms of standardized spatial
tasks (i.e. Morris water maze and spontaneous alternation)
involving partly different cognitive processes (i.e. refer-
ence memory and working memory respectively), we
showed that each strain performed better in a specific
task.
2. Materials and Methods
2.1. Animals
A total of 10 male BALB/c mice (Janvier©, France) and
10 male A/J mice (Harlan©, France) were used in this
study. Ice were 7-week old at their arrival to the labora-
tory and 10-week old at the ti me of testing. Prior to test-
ing, they were housed in groups of 5, in standard cages
containing food pellets and water Ad libitum. They were
housed in a room kept at constant temperature (21˚C ±
1˚C) on a 12/12 controlled light/dark cycle with lights on
at 6 a.m. Animals of the two strains were randomized
and tested each day at 2 p.m. After each day of testing,
mice returns into the rearing room in the conditions de-
scribe above. All experiments were carried out in accor-
dance with the European Community Council directive
86/609/EEC.
2.2. Apparatuses
2.2.1. Morris Water M a ze
The apparatus consisted of a circular pool (diameter: 90
cm; high: 30 cm) filled with opaque water (23˚C ± 1˚C)
in which a platform (7 × 6 cm) is located 20 cm from the
border in order to unable escape possibility. The water
used in each tests was kept at constant temperature (23˚C
± 1˚C) and removed every day aft er the end of the session.
Pool was divided in 4 equal quadrants G, A1, A2, O,
which respectively represent the goal quadrant (in which
the platform is located), the two adjacent quadrants and
the opposite one. The experimental room was lighted with
a halogen lamp (85 lux), and various fixed visual cues
were available 85 cm from the pool, on the walls.
2.2.2. Spontaneous Alternation
To run spontaneous alternation, an X-maze apparatus
was used. An X-maze consisted of four wooden arms (10
cm wide; 60 cm long; 10 cm height), with a 90 angle
between two adjacent arms. The maze surface was cov-
ered with sawdust to make the apparatus less aversive.
The experimental room was lighted with a halogen lamp
(85 lx), and provided various visual cues fixed on sur-
rounding walls.
2.3. Behavioral Recordings
2.3.1. Morris Water M a ze
In this task BALB/c (n = 10) and A/J mice (n = 10) had
to learn the location of the hidden platform. The time to
find the platform was recorded and used as the main
learning parame t er.
During familiarization session, platform was located 1
cm above the water (i.e. in a visible position) in the G
quadrant. Mice were maintained 60 seconds on the plat-
form and were successively placed in the water at the
different starting points (A1, A2, O). During the learning
phase, platform was concealed one centimeter under the
water level. The learning phase consisted in one learning
session per day during 4 consecutive days. One session
consisted in three trials, respectively departing from O,
A1 and A2 quadrants in a random order. If a mouse did
not find the platform after 60 seconds, it was brough t out
the water to the platform. Mice were allowed to rest dur-
ing 60 sec on the platform at the end of each trial, before
the beginning of the next trial.
Probe test was undertaken 24 hr after the end of the
conditioning pr ocess. During th e prob e test, there wa s no
platform in the pool. The test begun with the in trodu ction
of mice in the center of the pool. The time spent in each
quadrant was recorded within the 60-sec period of ob-

J. CELESTINE ET AL.
158
servation. Samples for probe test, samples sizes of each
group of mice were decreased to n = 8 due to accidental
mortality.
2.3.2. Spontaneous Alternation
This paradigm uses the spontaneous tendency of mice to
move from one arm of the maze to another. At the begin-
ning of the test, BALB/c (n = 8) and A/J (n = 8) mice
were placed at the center of the maze and the sequence of
entries into the three arms was recorded ov er a period of
10 min, an arm entry being determined as the four paws
within that arm. The total number of arm entries was
recorded and the spontaneous alternation score was cal-
culated as the number of alternations (i.e . entries in three
different arms consecutively) divi ded by the total num ber
of possible alternations (i.e. total number of arm entries-
two) and multiplied by 100.
2.4. Statistical Analyses
To allow a valid use of parametric statistical tests, nor-
mality and homoscedasticity of data was checked before
each test, using Shapiro-Wilk’s and Bartlett’s tests re-
spectively. When parametric assumptions were not satis-
fied, data were submitted to a Log10 transform to reach
the criteria. Learning performances of mice in the MWM
were analyzed with a two-way repeated ANOVA (strain
× training session). When main analysis showed a sig-
nificant effect of one of the main factors, post-hoc pair-
wise analyses were done using the Holm-Sidak proce-
dure. The differences between strains in the probe test
were analyzed with unpaired Student’s t-test. Student’s
t-test was also used to analyze spontaneous alternation
scores, number of arm entries and alternation percentage
in the SA (within and between subjects’ comparisons re-
spectively). Comparisons between strains were done using
unpaired t-tests while comparisons of performances of
each strain with random scores were done using one-sam-
ple t-tests.
3. Results
3.1. Morris Water Maze
Figure 1 shows the mean latency to reach the hidden plat-
form during acquisition sessions in BALB/c (n = 10) and
A/J mice (n = 10). A two-way repeated ANOVA showed
a significant difference in latency to find the hidden
platform between the two strains (F1,54 = 5.365; p =
0.033), revealing a globally shorter latency in BALB/c
mice compared to A/J (mean latencies: 24.97 sec vs
35.15 sec respectively). It also showed a significant dif-
ference for latency to find the hidden platform between
training day (F3,54 = 5.093; p = 0.004). Post-hoc com-
parisons showed that latency to find the platform was
significantly smaller from session 4 relative to session 1
in BALB/c (Holm-Sidak’ s p = 0.004) but not in A /J mice
(Holm-Sidak’s p = 0.178). Moreover, test showed that
latency to find the platform was not significantly differ-
ent between the two strains on session 1 (Holm-Sidak’s p
= 0.382), but was significantly shorter in BALB/c mice
for session 4 compared to A/J mice (Holm-Sidak’s p =
0.034).
Figure 2 illustrates performances of BALB/c (n = 8)
and A/J mice (n = 8) in the probe test. Independent Stu-
dent’s t-test showed that BALB/c express significantly
longer swimming time in the goal quadrant (G) com-
pared to A/J (t = 2.274; df = 14; p = 0.0392).
Figure 1. Mean (±SEM) escape latencies (in seconds) on
successive sessions. Each point represents the average score
over three trials. (a) Indicates significant difference inside
A/J group (n = 10); (b), (c) Indicate significant difference
inside BALB/c group (n = 10); **: p < 0.01: significant dif-
ference between the two strains in session 4.
Figure 2. Mean (±SEM) time spent in each quadrant (sec-
onds) during probe test. G is the goal quadrant, A1 and A2
are the adjacent quadrants, and O is the opposite quadrant.
(a)-(c) Indicate significant difference between quadrant in-
side BALB/c group (n = 8); (d) Indicate significant differ-
ence between quadrants inside A/J group (n = 8); ***: p <
0.001: significant difference between the two strains in
quadrant G and O.

J. CELESTINE ET AL. 159
3.2. Spontaneous Alternation
BALB/c mice (n = 8) showed an alternation rate (mean ±
SEM: 54.4% ± 3%) not significantly different from a ran-
dom arm entries sequence (one-sample t-test: t = 1.4667;
df = 7; p = 0.1859). On the contrary, A/J mice (n = 8)
expressed a significantly higher alternation rate (mean ±
SEM: 70.8% ± 4.2%) than BALB/c mice (unpaired t-test:
t = 3.177; df = 14; p = 0.0067), and significantly differ-
ent from a random arm entries sequence (one-sample
t-test: t = 4.9524; df = 7; p = 0.0017). Finally, the total
number of arm-entries was however higher in BALB/c
mice compared to A/J mice (unpaired t-test: t = 5.168; df
= 14; p = 0.0001).
4. Discussion
In this study, we compared lear ning performances of two
strains of mice (BALB/c and A/J) known for their high
emotional reactivity and poor learning skills. Each strain
was submitted to a spatial memory task (MWM) and a
spatial working memory learning task (SA).
Results showed that contrary to A/J mice, BALB/c
learned the location of the MWM hidden platform in 4
days (Figure 1). Probe test has shown that BALB/c ex-
press better abilities to restore the learning information
than A/J strain. Moreover, results of spontaneo us alterna-
tion test were the opposite, and A/Js’ performances in
this test were significantly better than BALB/c.
Stress studies involve a limited choice of mice strains
(including BALB/c and A/J mice), which are selected on
the basis of their sensitivity to stressors [31 ]. In addition,
throughout the literature BALB/c and A/J strains are
commonly considered as unable or very inefficient in spa-
tial task resolution [21]. This work shows that in th e con-
trary, these strains are able to efficiently learn a task, but
with opposite potentialities, BALB/c performing better
than A/J in spatial reference task while A/J mice were
better than BALB/c in spatial working task. Since the
strains tested in this study are commonly used for their
high emotional reactivity, our results can be discussed in
terms of relations between emotion and learning [32].
Indeed, our results point out a relation between strain
(BALB/c vs A/J), and learning type (spatial vs non-spa-
tial). BALB/c and A/J are known to exhibit low lo como-
tor activity and high level of emotional reactivity com-
pared to other mouse strains [21]. Such an emotional
reactivity is generally expressed in mazes as wall hug-
ing, floating [5,14,16,19-21,29,33-38] or anxiety-like be-
haviors [15,27]. However, supporting the differences
showed in our results, few studies reveal that BALB/c
have better learning performances than A/J throughout
spatial learning [36]. Interestingly, it has been shown that
A/J mice exhibit a higher emotional reactivity than
BALB/c. It was indirectly reviewed by several authors
which showed a differentiation between those two strains
for example in the open field test or anxiety like behavior
[19,21,37,39,40]. Hence, the less emotionally reactive
strain tested in our study (i.e. BALB/c) expressed better
performances in the spatial MWM task, thus further sup-
porting the known inv erse relation between sensitivity to
stress and spatial cognition .
As suggested by the germinal works of Donald Hebb
[41], performances in many tasks (hence cognitive proc-
esses), are a function of the degree of emotional arousal.
Indeed, a general rule was described in which emotional
arousal influences performances with an inverted U-shape
relation, where lowest and highest emotional loads are
associated with lowest performances (i.e. poor motiva-
tion to solve the task and inhibitory emotional over-load
respectively). However, our results support previous sug-
gestions that such emotion-cognition relation would not
be uni-dimensional, but woul d be ta sk-dependent.
In conclusion, our study shows that whereas consid-
ered as poor learners, BALB/c and A/J mice can perform
efficiently in different learning tasks. More specifically,
our results revealed that BALB/c mice performed better
than A/J mice in a spatial learning task (MWM) while
A/J mice acquired faster a non-spatial task (SA). Consid-
ering the fact that BALB/c and less emotionally reactive
than A/J mice, this suggests that the influence of emo-
tional arousal on cognition (inhibition or facilitation) de-
pends on th e natur e of th e task (ref er ence vs work ing me m-
ory) and involv ed neural substr ates (e.g. hippocam pus).
Indeed MWM and SA as spatial and non-spatial tasks
are respectively hippocampus-dependent and non-de-
pendent. Conveniently, influence of emotion and stress
on hippocampus has been extensively studied [13,32-35,
42,43]. Indeed many studies have investigated and dem-
onstrated so far the impairment of hippocampus spatial
learning in response to stress procedure such as learned
helplessness or chronic mild stress [13,44]. Furthermore,
limbic system is largely implicated in emotional response.
Particularly the amygdala and also the hippocampus in
fear context [45-48]. This link is very consistent with th e
behavioral differentiation observed between those two
strains. In fact our results are in line with an inverse rela-
tionship between hippocampus processing efficiency and
HPA axis activity.
If conflicting hippocampal activations between emo-
tional and spatial p rocesses could constitute a subs tantial
hypothesis to understand why a lower emotional arousal
would allow better performances in spatial tasks, further
studies would be then needed to better understand why
high emotional arousal would be beneficial to a dis-
criminant task.
5. Acknowledgements
Authors thank Catherine Belzung for providing logistic
support (i.e. animals and experimental facilities). J. Céles-
tine and A. Tanti designed the experimental protocol and

J. CELESTINE ET AL.
160
collected data. J. Célestine and A. Aubert undertook sta-
tistical analysis. All authors revised draft of the manu-
scripts and have approved the final manuscript. Finally,
authors thank Helen Morrison for language revision.
REFERENCES
[1] J. LeDoux, “The Emotional Brain: The Mysterious Un-
derpinnings of Emotional Life,” Simon & Schuster, New
York, 1996.
[2] J. E. Ledoux, “Emotion Circuits in the Brain,” Annual
Review of Neurosciences, Vol. 23, 2000, pp. 155-184.
doi:10.1146/annurev.neuro.23.1.155
[3] J. Panksepp, “Evolution Constructed the Potential for
Subjective Experience within the Neurodynamics of the
Mammalian Brain,” In: P. Ekman and R. J. David son, E ds . ,
The Nature of Emotion: Fundamental Questions, 1994,
pp. 396-399.
[4] E. S. Paul, E. J. Harding and M. Mendi, “Measuring
Emotional Processes in Animals: The Utility of a Cogni-
tive Approach,” Neuroscience and Biobehavioral Revi ew s,
Vol. 29, No. 3, 2005, pp. 469-491.
doi:10.1016/j.neubiorev.2005.01.002
[5] A. Cabanac and M. Cabanac, “Heart Rate Response to
Gentle Handling of Frog and Lizard,” Behavioural Proc-
esses, Vol. 52, No. 2-3, 2000, pp. 89-95.
doi:10.1016/S0376-6357(00)00108-X
[6] M. Cabanac, “Emotion and Phylogeny,” Japanese Jour-
nal of Physiology, Vol. 49, No. 1, 1999, pp. 1-10.
doi:10.2170/jjphysiol.49.1
[7] A. Fischer, M. Radulovic, C. Schrick, F. Sananbenesi, J.
Godovac-Zimmermann and J. Radulovic, “Hippocampal
Mek/Erk Signaling Mediates Extinction of Contextual
Freezing Behavior,” Neurobiology of Learning and Mem-
ory, Vol. 87, No. 1, 2007, pp. 149-158.
doi:10.1016/j.nlm.2006.08.003
[8] M. R. Holahan and N. M. White, “Amygdala c-Fos In-
ducting Corresponds to Unconditioned and Conditioned
Aversive Stimuli but Not to Freezing,” Behavioural Brain
Research, Vol. 152, 2004, pp. 109-120.
[9] N. Graindorge, C. Alves, A. S. Darmaillacq, R. Chichery,
L. Dickel and C. Bellanger, “Effects of Dorsal and Ven-
tral Vertical Lobe Electrolytic Lesions on Spatial Learn-
ing and Locomotor Activity in Sepia Officinalis,” Be-
havioral Neuroscience, Vol. 120, No. 5, 2006, pp. 1151-
1158. doi:10.1037/0735-7044.120.5.1151
[10] C. Alves, J. G. Boal, R. Chichery and L. Dickel, “Orien-
tation in the Cuttlefish Sepia Officinalis: Response versus
Place Learning,” Animal Cognition, Vol. 10, No. 1, 2007,
pp. 29-36. doi:10.1007/s10071-006-0027-6
[11] E.-T. Ang, G. S. Dawe, P. T. H. Wong, S. Moochhala and
Y.-K. Ng, “Alterations in Spatial Learning and Memory
after Forced Exercise,” Brain Research, Vol. 1113, No. 1,
2006, pp. 186-193. doi:10.1016/j.brainres.2006.07.023
[12] R. A. Countryman, N. L. Kaban and P. J. Colombo,
“Hippocampal c-Fos Is Necessary for Long-Term Mem-
ory of a Socially Transmitted Food Preference,” Neuro-
biology of Learning and Memory, Vol. 84, No. 3, 2005, p.
175. doi:10.1016/j.nlm.2005.07.005
[13] L. Song, W. Che, W. Min-Wei, Y. Murakami and K. Ma-
tsumoto, “Impairment of the Spatial Learning and Mem-
ory Induced by Learned Helplessness and Chronic Mild
Stress,” Pharmacology, Biochemistry, and Behavior, Vol.
83, No. 2, 2006, pp. 186-193.
doi:10.1016/j.pbb.2006.01.004
[14] J. N. Crawley, J. K. Belknap, A. Collins, J. C. Crabbe, W.
Frankel, N. Henderson, et al., “Behavioral Phenotypes of
Inbred Mouse Strains: Implications and Recommenda-
tions for Molecular Studies,” Psychopharmacology, Vol.
132, No. 2, 1997, pp. 107-124.
doi:10.1007/s002130050327
[15] K. Klapdor and F. J. van der Staay, “The Morris Water-
Escape Task in Mice: Strain Differences and Effects of
Intra-Maze Contrast and Brightness,” Physiology & Be-
havior, Vol. 60, No. 5, 1996, pp. 1247-1254.
doi:10.1016/S0031-9384(96)00224-7
[16] P. Carlier and M. Jamon, “Observational Learning in
C57BL/6j Mice,” Behavioral Brain Research, Vol. 174,
No. 1, 2006, pp. 125-131. doi:10.1016/j.bbr.2006.07.014
[17] R. G. M. Morris, P. Garrud, J. N. P. Rawlins and J.
O’Keefe, “Place Navigation Impaired in Rats with Hip-
pocampal Lesions,” Nature, Vol. 297, 1982, pp. 681-683.
doi:10.1038/297681a0
[18] R. Lalonde, “The Neurobiological Basis of Spontaneous
Alternation,” Neuroscience & Biobehavioral Reviews, Vol.
26, No. 1, 2002, pp. 91-104.
doi:10.1016/S0149-7634(01)00041-0
[19] D. Wahlsten, S. F. Cooper and J. C. Crabbe, “Different
Rankings of Inbred Mouse Strains on the Morris Maze
and a Refined 4-Arm Water Escape Task,” Behavioral
Brain Research, Vol. 165, No. 1, 2005, pp. 36-51.
doi:10.1016/j.bbr.2005.06.047
[20] D. Wahlsten, N. R. Rustay, P. Metten and J. C. Crabbe,
“In Search of a Better Mouse Test,” Trends in Neurosci-
ences, Vol. 26, No. 3, 2003, pp. 132-136.
doi:10.1016/S0166-2236(03)00033-X
[21] V. Carola, F. D’Olimpio, E. Brunamonti, A. Bevilacqua,
P. Renzi and F. Mangia, “Anxiety-Related Behaviour in
C57BL/6-BALB/c Chimeric Mice,” Behavioral Brain Re-
search, Vol. 150, No. 1-2, 2004, pp. 25-32.
[22] V. Kazlauckas, J. Schuh, O. P. Dall’Igna, G. S. Pereira, C.
D. Bonan and D. R. Lara, “Behavioral and Cognitive Pro-
file of Mice with High a nd Low Exploratory Phenoty pe s,”
Behavioural Brain Research, Vol. 162, No. 2, 2005, p.
272. doi:10.1016/j.bbr.2005.03.021
[23] S. J. Clapcote and J. C. Roder, “Survey of Embryonic
Stem Cell Line Source Strains in the Water Maze Reveals
Superior Reversal Learning of 129S6/SvEvTac Mice,”
Behavioural Brain Research, Vol. 152, 2004, pp. 35-48.
[24] E. H. Owen, S. F. Logue, D. L. Rasmussen and J. M.
Wehner, “Assessment of Learning by the Morris Water
Task and Fear Conditioning in Inbred Mouse Strains and
F1 Hybrids: Implications of Genetic Background for Sin-
gle Genemutations and Quantitative Trai Loci Analyses,”
Neuroscience, Vol. 80, No. 4, 1997, pp. 1087-1099.
doi:10.1016/S0306-4522(97)00165-6

J. CELESTINE ET AL.
161
[25] V. Voikar, S. Koks, E. Vasar and H. Rauvala, “Strain and
Gender Differences in the Behavior of Mouse Lines Com-
monly Used in Transgenic Studies,” Physiology & Be-
havior, Vol. 72, No. 1-2, 2001, pp. 271-281.
doi:10.1016/S0031-9384(00)00405-4
[26] M. Yoshida, K. Goto and S. Watanabe, “Task-Dependent
Strain Difference of Spatial Learning in C57BL/6N and
BALB/c Mice,” Physiology and Behavior, Vol. 73, No.
1-2, 2001, pp. 37-42.
doi:10.1016/S0031-9384(01)00419-X
[27] K. Klapdor and F. J. Van Der Staay, “Repeated Acquisi-
tion of a Spatial Navigation Task in Mice: Effects of
Spacing of Trials and of Unilateral Middle Cerebral Ar-
tery Occlusion,” Physiology & Behavior, Vol. 63, No. 5,
1998, pp. 903-909. doi:10.1016/S0031-9384(98)00003-1
[28] D. Van Dam, G. Lenders and P. P. De Deyn, “Effect of
Morris Water Maze Diameter on Visual-Spatial Learning
in Different Mouse Strains,” Neurobiology of Learning
and Memory, Vol. 85, No. 2, 2006, pp. 164-172.
doi:10.1016/j.nlm.2005.09.006
[29] R. D’Hooge and P. P. De Deyn, “Applications of the
Morris Water Maze in the Study of Learning and Mem-
ory,” Brain Research Reviews, Vol. 36, No. 1, 2001, pp.
60-90. doi:10.1016/S0165-0173(01)00067-4
[30] P. Chapillon and A. Debouzie, “BALB/c Mice Are Not
So Bad in the Morris Water Maze,” Behavioral Brain
Research, Vol. 117, No. 1-2, 2000, pp. 115-118.
doi:10.1016/S0166-4328(00)00292-8
[31] Y. Ibarguen-Vargas, A. Surget, C. Touma, R. Palme and
C. Belzung, “Multifaceted Strain-Specific Effects in a
Mouse Model of Depression and of Antidepressant Re-
versal,” Psychoneuroe ndocrinolo gy, Vol. 33, No . 10, 2008,
pp. 1357-1368. doi:10.1016/j.psyneuen.2008.07.010
[32] K. Yamada, Y. Santo-Yamada and K. Wada, “Stress-
Induced Impairment of Inhibitory Avoidance Learning in
Female Neuromedin B Receptor-Deficient Mice,” Physi-
ology & Behavior, Vol. 78, No. 2, 2003, p. 303.
doi:10.1016/S0031-9384(02)00979-4
[33] D. D. Francis, D. M. Zaharia, N. Shanks and H. Anisman,
“Stress-Induced Disturbances in Morris Water-Maze Per-
formance: Interstain Variability,” Physiology and Beh avior,
Vol. 58, No. 1, 1995, pp. 57-65.
doi:10.1016/0031-9384(95)00009-8
[34] C. Pittenger and R. S. Duman, “Stress, Depression, and
Neuroplasticity: A Convergence of Mechanisms,” Neu-
ropsychopharmacology, Vol. 33, No. 1, 2007, pp. 88-109.
doi:10.1038/sj.npp.1301574
[35] L. Santarelli, M. Saxe, C. Gross, A. Surget, F. Battaglia,
S. Dulawa, et al., “Requirement of Hippocampal Neuro-
genesis for the Behavioral Effects of Antidepressants,”
Science, Vol. 301, No. 5634, 2003, pp. 805-809.
doi:10.1126/science.1083328
[36] R. E. Brown and A. A. Wong, “The Influence of Visual
Ability on Learning and Memory Performance in 13
Strains of Mice,” Learning & Memory, Vol. 14, 2007, pp.
134-144. doi:10.1101/lm.473907
[37] S. S. Moy, J. J. Nadler, N. B. Young, A. Perez, L. P. Hol-
loway, R. P. Barbaro, et al., “Mouse Behavioral Tasks
Relevant to Autism: Phenotypes of 10 Inbred Strains,”
Behavioural Brain Research, Vol. 176, No. 1, 2007, pp.
4-20. doi:10.1016/j.bbr.2006.07.030
[38] M. Upchurch and J. M. Wehner, “Differences between
Inbred Strains of Mice in Morris Water Maze Perform-
ance,” Behavior Genetics, Vol. 18, No. 1, 1988, pp. 55-
68. doi:10.1007/BF01067075
[39] J. C. Crabbe, D. Wahlsten and B. C. Dudek, “Genetics of
Mouse Behavior: Interactions with Laboratory Environ-
ment,” Science, Vol. 284, No. 5420, 1999, pp. 1670-1672.
doi:10.1126/science.284.54 20.1670
[40] V. Carola, F. D’Olimpio, E. Brunamonti, F. Mangia and
P. Renzi, “Evaluation of the Elevated Plus-Maze and
Open-Field Tests for the Assessment of Anxiety-Related
Behaviour in Inbred Mice,” Behavioral Brain Research,
Vol. 134, No. 1-2, 2002, pp. 49-57.
doi:10.1016/S0166-4328(01)00452-1
[41] D. O. Hebb, “Drives and the C.N.S. (Conceptual Nervous
System),” Psychological Review, Vol. 62, 1955, pp. 243-
254. doi:10.1037/h0041823
[42] A. Briones-Aranda, L. Rocha and O. Picazo, “Influence
of Forced Swimming Stress on 5-HT1A Receptors and
Serotonin Levels in Mouse Brain,” Progress in Neuro-
Psychopharmacology & Biological Psychiatry, Vol. 29,
No. 2, 2005, pp. 275-281.
doi:10.1016/j.pnpbp.2004.11.011
[43] Y. Xu, B. Ku, L. Tie, H. Yao, W. Jiang, X. Ma, et al.,
“Curcumin Reverses the Effects of Chronic Stress on
Behavior, the HPA Axis, BDNF Expression and Phos-
phorylation of CREB,” Brain Research, Vol. 1122, No. 1,
2006, pp. 56-64. doi:10.1016/j.brainres.2006.09.009
[44] A. Olariu, M. H. Tran, K. Yamada, M. Mizuno, V. Hefco
and T. Nabeshima, “Memory Deficits and Increased
Emotionality Induced by Beta-Amyloid (25-35) Are Cor-
related with the Reduced Acetylcholine Release and Al-
tered Phorbol Dibutyrate Binding in the Hippocampus,”
Journal of Neural Transmission, Vol. 108, No. 8-9, 2001,
pp. 1065-1079. doi:10.1007/s007020170025
[45] N. M. Conejo, M. Lopez, R. Cantora, H. Gonzalez-Pardo,
L. Lopez, A. Begega, et al., “Effects of Pavlovian Fear
Conditioning on Septohippocampal Metabolism in Rats,”
Neuroscience Letters, Vol. 373, No. 2, 2005, pp. 94-98.
doi:10.1016/j.neulet.2004.09.066
[46] M. Fujisaki, K. Hashimoto, M. Iyo and T. Chiba, “Role
of the Amygdalo-Hippocampal Transition Area in the
Fear Expression: Evaluation by Behavior and Immediate
Early Gene Expression,” Neuroscience, Vol. 124, No. 1,
2004, pp. 247-260.
doi:10.1016/j.neuroscience.2003.11.022
[47] C.-H. Lin, S.-H. Yeh, C.-H. Lin, K.-T. Lu, T.-H. Leu,
W.-C. Chang, et al., “A role of PI-3 Kinase Signaling
Pathway in Fear Conditioning and Synaptic Plasticity in
the Amygdala,” Neuron, Vol. 31, No. 5, 2001, pp. 841-
851. doi:10.1016/S0896-6273(01)00433-0
[48] P. Barnes and M. Good, “Impaired Pavlovian Cued Fear
Conditioning in Tg2576 Mice Expressing a Human Mu-
tant Amyloid Precursor Protein Gene,” Behavioral Brain
Research, Vol. 157, No. 1, 2005, pp. 107-117.
doi:10.1016/j.bbr.2004.06.014