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Individual responses of rodents in modelling of affective disorders and in their treatment: prospective review

Published online by Cambridge University Press:  18 June 2018

Haim Einat ,
Itamar Ezer ,
Nirit Z Kara  and
Catherine Belzung
Haim Einat*
Affiliation:
School of Behavioral Sciences, Tel Aviv-Yaffo Academic College, Tel-Aviv, Israel Dept. of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, Beersheba, Israel College of Pharmacy, University of Minnesota, Duluth, MN, USA
Itamar Ezer
Affiliation:
School of Behavioral Sciences, Tel Aviv-Yaffo Academic College, Tel-Aviv, Israel
Nirit Z Kara
Affiliation:
School of Behavioral Sciences, Tel Aviv-Yaffo Academic College, Tel-Aviv, Israel Dept. of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, Beersheba, Israel
Catherine Belzung
Affiliation:
INSERM 930 & Department of Neurosciences, Université François-Rabelais de Tours, France
*
*Author for correspondence: Haim Einat, Professor, School of Behavioral Sciences, Tel Aviv-Yaffo Academic College, 14 Rabenu Yeruham St., Tel-Aviv, Israel. Tel: (972)3 680 2536; Fax: (972)3 6802526; E-mail: [email protected]
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Abstract

Introduction

Lack of good animal models for affective disorders, including major depression and bipolar disorder, is noted as a major bottleneck in attempts to study these disorders and develop better treatments. We suggest that an important approach that can help in the development and use of better models is attention to variability between model animals.

Results

Differences between mice strains were studied for some decades now, and sex differences get more attention than in the past. It is suggested that one factor that is mostly neglected, individual variability within groups, should get much more attention. The importance of individual differences in behavioral biology and ecology was repeatedly mentioned but its application to models of affective illness or to the study of drug response was not heavily studied. The standard approach is to overcome variability by standardization and by increasing the number of animals per group.

Conclusions

Possibly, the individuality of specific animals and their unique responses to a variety of stimuli and drugs, can be helpful in deciphering the underlying biology of affective behaviors as well as offer better prediction of drug responses in patients.

Keywords

affective disorderanimal modelsantidepressantsbipolar disorderdepressionmood stabilisers
Type
Perspective
Information
Acta Neuropsychiatrica , Volume 30 , Issue 6 , December 2018 , pp. 323 - 333
Copyright
© Scandinavian College of Neuropsychopharmacology 2018 

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References

1. Phelps, EA LeDoux, JE (2005) Contributions of the amygdala to emotion processing: from animal models to human behavior. Neuron 48, 175–187.Google Scholar
2. van der Werff, SJ, van den Berg, SM, Pannekoek, JN, Elzinga, BM van der Wee, NJ (2013) Neuroimaging resilience to stress: a review. Front Behav Neurosci 7, 39.Google Scholar
3. Cloninger, CR, Svrakic, DM Przybeck, TR (1993) A psychobiological model of temperament and character. Arch Gen Psychiatry 50, 975–990.Google Scholar
4. Ebstein, RP, Zohar, AH, Benjamin, J Belmaker, RH (2002) An update on molecular genetic studies of human personality traits. Appl Bioinformatics 1, 57–68.Google Scholar
5. Cryan, JF Slattery, DA (2007) Animal models of mood disorders: recent developments. Curr Opin Psychiatry 20, 1–7.Google Scholar
6. Einat, H (2007) Different behaviors and different strains: potential new ways to model bipolar disorder. Neurosci Biobehav Rev 31, 850–857.Google Scholar
7. Agid, Y, Buzsaki, G, Diamond, DM, Frackowiak, R, Giedd, J, Girault, JA, Grace, A, Lambert, JJ, Manji, H, Mayberg, H, Popoli, M, Prochiantz, A, Richter-Levin, G, Somogyi, P, Spedding, M, Svenningsson, P Weinberger, D (2007) How can drug discovery for psychiatric disorders be improved? Nat Rev Drug Discov 6, 189–201.Google Scholar
8. Gould, TD Einat, H (2007) Animal models of bipolar disorder and mood stabilizer efficacy: a critical need for improvement. Neurosci Biobehav Rev 31, 825–831.Google Scholar
9. Kafkafi, N, Agassi, J, Chesler, EJ, Crabbe, JC, Crusio, WE, Eilam, D, Gerlai, R, Golani, I, Gomez-Marin, A, Heller, R, Iraqi, F, Jaljuli, I, Karp, NA, Morgan, H, Nicholson, G, Pfaff, DW, Richter, SH, Stark, PB, Stiedl, O, Stodden, V, Tarantino, LM, Tucci, V, Valdar, W, Williams, RW, Wurbel, H Benjamini, Y (2018) Reproducibility and replicability of rodent phenotyping in preclinical studies. Neurosci Biobehav Rev 18, 30651–30657.Google Scholar
10. Nestler, EJ Hyman, SE (2010) Animal models of neuropsychiatric disorders. Nat Neurosci 13, 1161–1169.Google Scholar
11. Insel, TR (2007) From animal models to model animals. Biol Psychiatry 62, 1337–1339.Google Scholar
12. Kronfeld-Schor, N Einat, H (2012) Circadian rhythms and depression: human psychopathology and animal models. Neuropharmacology 62, 101–114.Google Scholar
13. Bilu, C, Einat, H Kronfeld-Schor, N (2016) Utilization of diurnal rodents in the research of depression. Drug Dev Res 77, 336–345.Google Scholar
14. Hendrie, CA Pickles, AR (2009) Depression as an evolutionary adaptation: implications for the development of preclinical models. Med Hypotheses 72, 342–347.Google Scholar
15. Gould, TD Gottesman, II (2006) Psychiatric endophenotypes and the development of valid animal models. Genes, Brain and Behavior 5, 113–119.Google Scholar
16. Cosgrove, VE, Kelsoe, JR Suppes, T (2016) Toward a valid animal model of bipolar disorder: how the research domain criteria help bridge the clinical-basic science divide. Biol Psychiatry 79, 62–70.Google Scholar
17. Malkesman, O, Scattoni, ML, Paredes, D, Tragon, T, Pearson, B, Shaltiel, G, Chen, G, Crawley, JN Manji, HK (2009) The female urine sniffing test: a novel approach for assessing reward-seeking behavior in rodents. Biol Psychiatry 67, 864–871.Google Scholar
18. Perry, W, Minassian, A, Paulus, MP, Young, JW, Kincaid, MJ, Ferguson, EJ, Henry, BL, Zhuang, X, Masten, VL, Sharp, RF Geyer, MA (2009) A reverse-translational study of dysfunctional exploration in psychiatric disorders: from mice to men. Arch Gen Psychiatry 66, 1072–1080.Google Scholar
19. Cryan, JF Holmes, A (2005) The ascent of mouse: advances in modelling human depression and anxiety. Nat Rev Drug Discov 4, 775–790.Google Scholar
20. Stukalin, Y Einat, H (2018) Analyzing test batteries in animal models of psychopathology with multivariate analysis of variance (MANOVA): one possible approach to increase external validity. Pharmacol Biochem Behav 28, 30402–30408.Google Scholar
21. WHO (2008) The global burden of disese: 2004 update. Geneva: World Health Organization Press.Google Scholar
22. Vohringer, PA Perlis, RH (2016) Discriminating between bipolar disorder and major depressive disorder. Psychiatr Clin North Am 39, 1–10.Google Scholar
23. Fountoulakis, KN, Kasper, S, Andreassen, O, Blier, P, Okasha, A, Severus, E, Versiani, M, Tandon, R, Moller, HJ Vieta, E (2012) Efficacy of pharmacotherapy in bipolar disorder: a report by the WPA section on pharmacopsychiatry. Eur Arch Psychiatry Clin Neurosci 262(Suppl. 1):1–48.Google Scholar
24. Schumann, G, Binder, EB, Holte, A, de Kloet, ER, Oedegaard, KJ, Robbins, TW, Walker-Tilley, TR, Bitter, I, Brown, VJ, Buitelaar, J, Ciccocioppo, R, Cools, R, Escera, C, Fleischhacker, W, Flor, H, Frith, CD, Heinz, A, Johnsen, E, Kirschbaum, C, Klingberg, T, Lesch, KP, Lewis, S, Maier, W, Mann, K, Martinot, JL, Meyer-Lindenberg, A, Muller, CP, Muller, WE, Nutt, DJ, Persico, A, Perugi, G, Pessiglione, M, Preuss, UW, Roiser, JP, Rossini, PM, Rybakowski, JK, Sandi, C, Stephan, KE, Undurraga, J, Vieta, E, van der Wee, N, Wykes, T, Haro, JM Wittchen, HU (2014) Stratified medicine for mental disorders. Eur Neuropsychopharmacol 24, 5–50.Google Scholar
25. Hasler, G Wolf, A (2015) Toward stratified treatments for bipolar disorders. Eur Neuropsychopharmacol 25, 283–294.Google Scholar
26. Crabbe, JC, Wahlsten, D Dudek, BC (1999) Genetics of mouse behavior: interactions with laboratory environment. Science 284, 1670–1672.Google Scholar
27. Lewejohann, L, Zipser, B Sachser, N (2011) “Personality” in laboratory mice used for biomedical research: a way of understanding variability? Dev Psychobiol 53, 624–630.Google Scholar
28. Kara, N, Stukalin, Y Einat, H (2018) Revisiting the validity of the mouse forced swim test: systematic review and meta-analysis of the effects of prototypic antidepressants. Neurosci Biobehav Rev 84, 1–11.Google Scholar
29. Flaisher-Grinberg, S Einat, H (2010) Strain specific battery of tests for separate behavioral domains of mania. Front Psychiatry 1, 1–10.Google Scholar
30. Gould, TD, O’Donnell, KC, Picchini, AM Manji, HK (2007) Strain differences in lithium attenuation of d-amphetamine-induced hyperlocomotion: a mouse model for the genetics of clinical response to lithium. Neuropsychopharmacology 32, 1321–1333.Google Scholar
31. Pilz, LK, Quiles, CL, Dallegrave, E, Levandovski, R, Hidalgo, MP Elisabetsky, E (2015) Differential susceptibility of BALB/c, C57BL/6N, and CF1 mice to photoperiod changes. Rev Bras Psiquiatr 37, 185–190.Google Scholar
32. Sugimoto, Y, Kajiwara, Y, Hirano, K, Yamada, S, Tagawa, N, Kobayashi, Y, Hotta, Y Yamada, J (2008) Mouse strain differences in immobility and sensitivity to fluvoxamine and desipramine in the forced swimming test: analysis of serotonin and noradrenaline transporter binding. Eur J Pharmacol 592, 116–122.Google Scholar
33. Jacobson, LH Cryan, JF (2007) Feeling strained? Influence of genetic background on depression-related behavior in mice: a review. Behav Genet 37, 171–213.Google Scholar
34. Kara, NZ Einat, H (2013) Rodent models for mania: practical approaches. Cell Tissue Res 354, 191–201.Google Scholar
35. Ene, HM, Kara, NZ Einat, H (2015b) Introducing female black Swiss mice: minimal effects of sex in a strain-specific battery of tests for mania-like behavior and response to lithium. Pharmacology 95, 224–228.Google Scholar
36. Franceschelli, A, Herchick, S, Thelen, C, Papadopoulou-Daifoti, Z Pitychoutis, PM (2014) Sex differences in the chronic mild stress model of depression. Behav Pharmacol 14, 14.Google Scholar
37. Warner, TA, Libman, MK, Wooten, KL Drugan, RC (2013) Sex differences associated with intermittent swim stress. Stress 16, 655–663.Google Scholar
38. Bale, TL Epperson, CN (2017) Sex as a biological variable: who, what, when, why, and how. Neuropsychopharmacology 42, 386–396.Google Scholar
39. Kokras, N Dalla, C (2014) Sex differences in animal models of psychiatric disorders. Br J Pharmacol 4, 12710.Google Scholar
40. Prendergast, BJ, Onishi, KG Zucker, I (2014) Female mice liberated for inclusion in neuroscience and biomedical research. Neurosci Biobehav Rev 40, 1–5.Google Scholar
41. Simpson, J, Ryan, C, Curley, A, Mulcaire, J Kelly, JP (2012) Sex differences in baseline and drug-induced behavioural responses in classical behavioural tests. Prog Neuropsychopharmacol Biol Psychiatry 37, 227–236.Google Scholar
42. Juetten, J Einat, H (2012) Behavioral differences in black Swiss mice from separate colonies: implications for modeling domains of mania. Behav Pharmacol 23, 211–214.Google Scholar
43. Fitzpatrick, CJ, Gopalakrishnan, S, Cogan, ES, Yager, LM, Meyer, PJ, Lovic, V, Saunders, BT, Parker, CC, Gonzales, NM, Aryee, E, Flagel, SB, Palmer, AA, Robinson, TE Morrow, JD (2013) Variation in the form of Pavlovian conditioned approach behavior among outbred male Sprague-Dawley rats from different vendors and colonies: sign-tracking vs. goal-tracking. PLoS One 8, e75042.Google Scholar
44. Sparks, LM, Sciascia, JM, Ayorech, Z Chaudhri, N (2014) Vendor differences in alcohol consumption and the contribution of dopamine receptors to Pavlovian-conditioned alcohol-seeking in Long-Evans rats. Psychopharmacology (Berl) 231, 753–764.Google Scholar
45. Pena-Oliver, Y, Sanchez-Roige, S, Stephens, DN Ripley, TL (2014) Alpha-synuclein deletion decreases motor impulsivity but does not affect risky decision making in a mouse gambling task. Psychopharmacology (Berl) 231, 2493–2506.Google Scholar
46. Becker, JB Cha, JH (1989) Estrous cycle-dependent variation in amphetamine-induced behaviors and striatal dopamine release assessed with microdialysis. Behav Brain Res 35, 117–125.Google Scholar
47. Milad, MR, Igoe, SA, Lebron-Milad, K Novales, JE (2009) Estrous cycle phase and gonadal hormones influence conditioned fear extinction. Neuroscience 164, 887–895.Google Scholar
48. Verma, P, Hellemans, KG, Choi, FY, Yu, W Weinberg, J (2009) Circadian phase and sex effects on depressive/anxiety-like behaviors and HPA axis responses to acute stress. Physiol Behav 99, 276–285.Google Scholar
49. Overstreet, DH, Friedman, E, Mathe, AA Yadid, G (2005) The Flinders Sensitive Line rat: a selectively bred putative animal model of depression. Neurosci Biobehav Rev 29, 739–759.Google Scholar
50. Kara, NZ, Flaisher-Grinberg, S, Anderson, GW, Agam, G Einat, H (2018) Mood-stabilizing effects of rapamycin and its analog temsirolimus: relevance to autophagy. Behav Pharmacol 29, 379–384.Google Scholar
51. Touma, C, Bunck, M, Glasl, L, Nussbaumer, M, Palme, R, Stein, H, Wolferstatter, M, Zeh, R, Zimbelmann, M, Holsboer, F Landgraf, R (2008) Mice selected for high versus low stress reactivity: a new animal model for affective disorders. Psychoneuroendocrinology 33, 839–862.Google Scholar
52. Bougarel, L, Guitton, J, Zimmer, L, Vaugeois, JM El Yacoubi, M (2011) Behaviour of a genetic mouse model of depression in the learned helplessness paradigm. Psychopharmacology (Berl) 215, 595–605.Google Scholar
53. Wegener, G, Mathe, AA Neumann, ID (2012) Selectively bred rodents as models of depression and anxiety. Curr Top Behav Neurosci 12, 139–187.Google Scholar
54. Cervantes, MC Delville, Y (2007) Individual differences in offensive aggression in golden hamsters: a model of reactive and impulsive aggression? Neuroscience 150, 511–521.Google Scholar
55. Cohen, H, Zohar, J Matar, M (2003) The relevance of differential response to trauma in an animal model of posttraumatic stress disorder. Biol Psychiatry 53, 463–473.Google Scholar
56. Matar, MA, Zohar, J Cohen, H (2013) Translationally relevant modeling of PTSD in rodents. Cell Tissue Res 354, 127–139.Google Scholar
57. Cohen, R Kronfeld-Schor, N (2006) Individual variability and photic entrainment of circadian rhythms in golden spiny mice. Physiol Behav 87, 563–574.Google Scholar
58. Freund, J, Brandmaier, AM, Lewejohann, L, Kirste, I, Kritzler, M, Kruger, A, Sachser, N, Lindenberger, U Kempermann, G (2013) Emergence of individuality in genetically identical mice. Science 340, 756–759.Google Scholar
59. Jakovcevski, M, Schachner, M Morellini, F (2008) Individual variability in the stress response of C57BL/6J male mice correlates with trait anxiety. Genes Brain Behav 7, 235–243.Google Scholar
60. Jama, A, Cecchi, M, Calvo, N, Watson, SJ Akil, H (2008) Inter-individual differences in novelty-seeking behavior in rats predict differential responses to desipramine in the forced swim test. Psychopharmacology (Berl) 198, 333–340.Google Scholar
61. Khemissi, W, Farooq, RK, Le Guisquet, AM, Sakly, M Belzung, C (2014) Dysregulation of the hypothalamus-pituitary-adrenal axis predicts some aspects of the behavioral response to chronic fluoxetine: association with hippocampal cell proliferation. Front Behav Neurosci 8, 340.Google Scholar
62. Krishnan, V, Han, MH, Graham, DL, Berton, O, Renthal, W, Russo, SJ, Laplant, Q, Graham, A, Lutter, M, Lagace, DC, Ghose, S, Reister, R, Tannous, P, Green, TA, Neve, RL, Chakravarty, S, Kumar, A, Eisch, AJ, Self, DW, Lee, FS, Tamminga, CA, Cooper, DC, Gershenfeld, HK Nestler, EJ (2007) Molecular adaptations underlying susceptibility and resistance to social defeat in brain reward regions. Cell 131, 391–404.Google Scholar
63. Larrieu, T, Cherix, A, Duque, A, Rodrigues, J, Lei, H, Gruetter, R Sandi, C (2017) Hierarchical status predicts behavioral vulnerability and nucleus accumbens metabolic profile following chronic social defeat stress. Curr Biol 27, 2202–2210.Google Scholar
64. Malatynska, E Knapp, RJ (2005) Dominant-submissive behavior as models of mania and depression. Neurosci Biobehav Rev 29, 715–737.Google Scholar
65. Nesher, E, Koman, I, Gross, M, Tikhonov, T, Bairachnaya, M, Salmon-Divon, M, Levin, Y, Gerlitz, G, Michaelevski, I, Yadid, G Pinhasov, A (2015) Synapsin IIb as a functional marker of submissive behavior. Sci Rep 5, 10287.Google Scholar
66. Palencia, M, Diaz-Moran, S, Mont-Cardona, C, Canete, T, Blazquez, G, Martinez-Membrives, E, Lopez-Aumatell, R, Tobena, A Fernandez-Teruel, A (2013) Helplessness-like escape deficits of NIH-HS rats predict passive behavior in the forced swimming test: relevance for the concurrent validity of rat models of depression. World Journal of Neuroscience 3, 83–92.Google Scholar
67. Pitychoutis, PM, Pallis, EG, Mikail, HG Papadopoulou-Daifoti, Z (2011) Individual differences in novelty-seeking predict differential responses to chronic antidepressant treatment through sex- and phenotype-dependent neurochemical signatures. Behav Brain Res 223, 154–168.Google Scholar
68. Shishkina, GT, Kalinina, TS, Berezova, IV, Bulygina, VV Dygalo, NN (2010) Resistance to the development of stress-induced behavioral despair in the forced swim test associated with elevated hippocampal Bcl-xl expression. Behav Brain Res 213, 218–224.Google Scholar
69. Vaugeois, JM, Passera, G, Zuccaro, F Costentin, J (1997) Individual differences in response to imipramine in the mouse tail suspension test. Psychopharmacology (Berl) 134, 387–391.Google Scholar
70. Feder, A, Nestler, EJ Charney, DS (2009) Psychobiology and molecular genetics of resilience. Nat Rev Neurosci 10, 446–457.Google Scholar
71. Pinhasov, A, Ilyin, SE, Crooke, J, Amato, FA, Vaidya, AH, Rosenthal, D, Brenneman, DE Malatynska, E (2005) Different levels of gamma-synuclein mRNA in the cerebral cortex of dominant, neutral and submissive rats selected in the competition test. Genes Brain Behav 4, 60–64.Google Scholar
72. Nesher, E, Gross, M, Lisson, S, Tikhonov, T, Yadid, G Pinhasov, A (2013) Differential responses to distinct psychotropic agents of selectively bred dominant and submissive animals. Behav Brain Res 236, 225–235.Google Scholar
73. Cohen, H Zohar, J (2004) An animal model of posttraumatic stress disorder: the use of cut-off behavioral criteria. Ann N Y Acad Sci 1032, 167–178.Google Scholar
74. Cohen, H, Kozlovsky, N, Alona, C, Matar, MA Joseph, Z (2012) Animal model for PTSD: from clinical concept to translational research. Neuropharmacology 62, 715–724.Google Scholar
75. Daskalakis, NP, Cohen, H, Cai, G, Buxbaum, JD Yehuda, R (2014) Expression profiling associates blood and brain glucocorticoid receptor signaling with trauma-related individual differences in both sexes. Proc Natl Acad Sci U S A 111, 13529–13534.Google Scholar
76. Abel, EL Hannigan, JH (1992) Effects of chronic forced swimming and exposure to alarm substance: physiological and behavioral consequences. Physiol Behav 52, 781–785.Google Scholar
77. Ene, HM, Kara, NZ, Barak, N, Reshef Ben-Mordechai, T Einat, H (2015a) Effects of repeated asenapine in a battery of tests for anxiety-like behaviours in mice. Acta Neuropsychiatr 11, 1–7.Google Scholar
78. Geyer, MA (2008) Developing translational animal models for symptoms of schizophrenia or bipolar mania. Neurotox Res 14, 71–78.Google Scholar
79. Blanchard, RJ, Kaawaloa, JN, Hebert, MA Blanchard, DC (1999) Cocaine produces panic-like flight responses in mice in the mouse defense test battery. Pharmacol Biochem Behav 64, 523–528.Google Scholar
80. Crawley, JN (1999) Behavioral phenotyping of transgenic and knockout mice: experimental design and evaluation of general health, sensory functions, motor abilities, and specific behavioral tests. Brain Res 835, 18–26.Google Scholar
81. Bailey, KR, Rustay, NR Crawley, JN (2006) Behavioral phenotyping of transgenic and knockout mice: practical concerns and potential pitfalls. Ilar J 47, 124–131.Google Scholar
82. Lucki, I, Dalvi, A Mayorga, AJ (2001) Sensitivity to the effects of pharmacologically selective antidepressants in different strains of mice. Psychopharmacology (Berl) 155, 315–322.Google Scholar
83. Can, A, Blackwell, RA, Piantadosi, SC, Dao, DT, O’Donnell, KC Gould, TD (2011) Antidepressant-like responses to lithium in genetically diverse mouse strains. Genes Brain Behav 10, 434–443.Google Scholar
84. Sade, Y, Kara, NZ, Toker, L, Bersudsky, Y, Einat, H Agam, G (2014) Beware of your mouse strain; differential effects of lithium on behavioral and neurochemical phenotypes in Harlan ICR mice bred in Israel or the USA. Pharmacol Biochem Behav 124C, 36–39.Google Scholar
85. Kara, NZ, Karpel, O, Toker, L, Agam, G, Belmaker, RH Einat, H (2014) Chronic oral carbamazepine treatment elicits mood-stabilising effects in mice. Acta Neuropsychiatr 26, 29–34.Google Scholar
86. Adams, B, Fitch, T, Chaney, S Gerlai, R (2002) Altered performance characteristics in cognitive tasks: comparison of the albino ICR and CD1 mouse strains. Behav Brain Res 133, 351–361.Google Scholar
87. Willner, P (1995) Animal models of depression: validity and applications. In Gessa GL, Fratta W, Pani L and Serra G editors Depression and mania: from neurobiology to treatment, vol 49. Advances in Biochemical Psychopharmacology. New York: Raven Press pp. 19–42.Google Scholar
88. Belzung, C (2001) The genetic basis of the pharmacological effects of anxiolytics: a review based on rodent models. Behav Pharmacol 12, 451–460.Google Scholar
89. Crawley, JN Paylor, R (1997) A proposed test battery and constellations of specific behavioral paradigms to investigate the behavioral phenotypes of transgenic and knockout mice. Horm Behav 31, 197–211.Google Scholar
90. Ducottet, C Belzung, C (2004) Behaviour in the elevated plus-maze predicts coping after subchronic mild stress in mice. Physiol Behav 81, 417–426.Google Scholar
91. Kalueff, AV, Keisala, T, Minasyan, A, Kuuslahti, M Tuohimaa, P (2006) Temporal stability of novelty exploration in mice exposed to different open field tests. Behav Processes 72, 104–112.Google Scholar
92. Kabbaj, M, Devine, DP, Savage, VR Akil, H (2000) Neurobiological correlates of individual differences in novelty-seeking behavior in the rat: differential expression of stress-related molecules. J Neurosci 20, 6983–6988.Google Scholar
93. Shankman, SA, Klein, DN, Torpey, DC, Olino, TM, Dyson, MW, Kim, J, Durbin, CE, Nelson, BD Tenke, CE (2011) Do positive and negative temperament traits interact in predicting risk for depression? A resting EEG study of 329 preschoolers. Dev Psychopathol 23, 551–562.Google Scholar
94. Forbes, EE Dahl, RE (2012) Research review: altered reward function in adolescent depression: what, when and how? J Child Psychol Psychiatry 53, 3–15.Google Scholar
95. Dietz, DM, Tapocik, J, Gaval-Cruz, M Kabbaj, M (2005) Dopamine transporter, but not tyrosine hydroxylase, may be implicated in determining individual differences in behavioral sensitization to amphetamine. Physiol Behav 86, 347–355.Google Scholar
96. Clapcote, SJ, Lazar, NL, Bechard, AR, Wood, GA Roder, JC (2005) NIH Swiss and black Swiss mice have retinal degeneration and performance deficits in cognitive tests. Comp Med 55, 310–316.Google Scholar
97. Serfilippi, LM, Pallman, DR, Gruebbel, MM, Kern, TJ Spainhour, CB (2004) Assessment of retinal degeneration in outbred albino mice. Comp Med 54, 69–76.Google Scholar
98. Ising, M, Horstmann, S, Kloiber, S, Lucae, S, Binder, EB, Kern, N, Kunzel, HE, Pfennig, A, Uhr, M Holsboer, F (2007) Combined dexamethasone/corticotropin releasing hormone test predicts treatment response in major depression – a potential biomarker? Biol Psychiatry 62, 47–54.Google Scholar
99. Kempermann, G, Kuhn, HG Gage, FH (1997) More hippocampal neurons in adult mice living in an enriched environment. Nature 386, 493–495.Google Scholar
100. Shamir, A, Shaltiel, G, Greenberg, ML, Belmaker, RH Agam, G (2003) The effect of lithium on expression of genes for inositol biosynthetic enzymes in mouse hippocampus; a comparison with the yeast model. Brain Res Mol Brain Res 115, 104–110.Google Scholar