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Learning & Behavior

, Volume 46, Issue 4, pp 537–553 | Cite as

Effect of age on discrimination learning, reversal learning, and cognitive bias in family dogs

  • Patrizia Piotti
  • Dóra Szabó
  • Zsófia Bognár
  • Anna Egerer
  • Petrouchka Hulsbosch
  • Rachel Sophia Carson
  • Enikő Kubinyi
Article

Abstract

Several studies on age-related cognitive decline in dogs involve laboratory dogs and prolonged training. We developed two spatial tasks that required a single 1-h session. We tested 107 medium-large sized dogs: “young” (N=41, aged 2.5–6.5 years) and “old” (N=66, aged 8–14.5 years). Our results indicated that, in a discrimination learning task and in a reversal learning task, young dogs learned significantly faster than the old dogs, indicating that these two tasks could successfully be used to investigate differences in spatial learning between young and old dogs. We also provide two novel findings. First, in the reversal learning, the dogs trained based on the location of stimuli learned faster than the dogs trained based on stimulus characteristics. Most old dogs did not learn the task within our cut-off of 50 trials. Training based on an object’s location is therefore more appropriate for reversal learning tasks. Second, the contrast between the response to the positive and negative stimuli was narrower in old dogs, compared to young dogs, during the reversal learning task, as well as the cognitive bias test. This measure favors comparability between tasks and between studies. Following the cognitive bias test, we could not find any indication of differences in the positive and negative expectations between young and old dogs. Taken together, these findings do not support the hypothesis that old dogs have more negative expectations than young dogs and the use of the cognitive bias test in older dogs requires further investigation.

Keywords

Reversal learning Cognitive bias Dog Learning Memory Ageing 

Notes

Acknowledgements

We would like to thank Stiegman B., Deés A., Hemző V., Böröczki R., Marosi S., for their help with data collection and coding, and the dog owners who took part in the study with their dogs. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No. 680040) and was supported by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences for EK and by the Budapest Semester in Cognitive Science program (BSCS-US LLC, Kalamazoo, Michigan) and the Hungarian Academy of Cognitive Science for RSC.

Supplementary material

13420_2018_357_MOESM1_ESM.docx (426 kb)
ESM 1 (DOCX 426 kb)

References

  1. Asendorpf, J.B., Conner, M., De Fruyt, F., De Houwer, J., Denissen, J.J., Fiedler, K., Fiedler, S., Funder, D.C., Kliegl, R., Nosek, B.A. and Perugini, M., 2013. Recommendations for increasing replicability in psychology. European Journal of Personality, 27(2), 108-119.CrossRefGoogle Scholar
  2. Becker, J. T., Huff, F. J., Nebes, R. D., Holland, A., & Boller, F. (1988). Neuropsychological function in Alzheimer's disease. Arch Neurol, 45, 263-268.CrossRefPubMedGoogle Scholar
  3. Bognár ZS.*, Piotti P.*, Szabó D., Le Nézet L., Kubinyi E. Behavioural measures of dogs’ responsiveness to visual and auditory stimuli. * these authors contributed equally to the work (in prep)Google Scholar
  4. Burman, O., McGowan, R., Mendl, M., Norling, Y., Paul, E., Rehn, T., & Keeling, L. (2011). Using judgement bias to measure positive affective state in dogs. Applied Animal Behaviour Science, 132(3), 160-168.CrossRefGoogle Scholar
  5. Chan AD, Nippak P, Murphey H, Ikeda-Douglas CJ, Muggenburg B, Head E, Cotman CW, Milgram NW (2002) Visuospatial impairments in aged canines (Canis familiaris): the role of cognitivebehavioral flexibility. Behavioral neuroscience 116(3):443CrossRefPubMedGoogle Scholar
  6. Chapagain, D., Virányi, Z., Wallis, L. J., Huber, L., Serra, J., & Range, F. (2017). Aging of attentiveness in border collies and other pet dog breeds: the protective benefits of lifelong training. Frontiers in aging neuroscience, 9, 100.CrossRefPubMedPubMedCentralGoogle Scholar
  7. Christie, L., Studzinski, C.M., Araujo, J.A., Leung, C.S., Ikeda-douglas, C.J., Head, E., Cotman, C.W., Milgram, N.W., 2005. A comparison of egocentric and allocentric age-dependent spatial learning in the beagle dog. Prog. Neuropsychopharmacol. Biol. Psychiatry 29, 361e369.CrossRefGoogle Scholar
  8. Clegg, I. L., & Delfour, F. (2018). Cognitive judgement bias is associated with frequency of anticipatory behavior in bottlenose dolphins. Zoo Biology.CrossRefPubMedGoogle Scholar
  9. Cockburn, A., Smith, M., Rusbridge, C., Fowler, C., Paul, E.S., Murrell, J.C., Blackwell, E.J., Casey, R.A., Whay, H.R. and Mendl, M., (2017). Evidence of negative affective state in Cavalier King Charles Spaniels with syringomyelia. Applied Animal Behaviour Science.Google Scholar
  10. Cole MG, Dendukuri N (2003) Risk factors for depression among elderly community subjects: a systematic review and meta-analysis. American Journal of Psychiatry 160(6):1147–1156CrossRefPubMedGoogle Scholar
  11. Cotman, C. W., & Head, E. (2008). The canine (dog) model of human aging and disease: dietary, environmental and immunotherapy approaches. Journal of Alzheimer's Disease, 15(4), 685-707.CrossRefPubMedGoogle Scholar
  12. Cummings, B. J., Head, E., Ruehl, W., Milgram, N. W., & Cotman, C. W. (1996). The canine as an animal model of human aging and dementia. Neurobiology of Aging, 17(2), 259–268.CrossRefPubMedGoogle Scholar
  13. Delphin-Combe, F., Bathsavanis, A., Rouch, I., Liles, T., Vannier-Nitenberg, C., Fantino, B., Dauphinot, V. and Krolak-Salmon, P., 2016. Relationship between anxiety and cognitive performance in an elderly population with a cognitive complaint. European journal of neurology, 23(7), 1210-1217.CrossRefPubMedGoogle Scholar
  14. Doyle, R. E., Vidal, S., Hinch, G. N., Fisher, A. D., Boissy, A., and Lee, C. (2010). The effect of repeated testing on judgement biases in sheep. Behav. Processes 83, 349–352.  https://doi.org/10.1016/j.beproc.2010.01.019 CrossRefPubMedGoogle Scholar
  15. Gonzalez-Soriano, J., Garcia, P. M., Contreras-Rodriguez, J., Martinez-Sainz, P., & Rodriguez-Veiga, E. (2001). Age-related changes in the ventricular system of the dog brain. Annals of Anatomy-Anatomischer Anzeiger, 183(3), 283-291.CrossRefGoogle Scholar
  16. González-Martínez, Á., Rosado, B., Pesini, P., García-Belenguer, S., Palacio, J., Villegas, A., Suárez, M.L., Santamarina, G. and Sarasa, M., 2013. Effect of age and severity of cognitive dysfunction on two simple tasks in pet dogs. The Veterinary Journal, 198(1), 176-181.CrossRefPubMedGoogle Scholar
  17. Gotlib, I. H., & Joormann, J. (2010). Cognition and depression: current status and future directions. Annual review of clinical psychology, 6, 285-312.CrossRefPubMedPubMedCentralGoogle Scholar
  18. Harding, E. J., Paul, E. S., & Mendl, M. T. (2004). Cognitive bias and affective state. Nature, 427(January), 312.  https://doi.org/10.1038/427312a CrossRefPubMedGoogle Scholar
  19. Hare, B., Brown, M., Williamson, C., & Tomasello, M. (2002). The domestication of social cognition in dogs. Science, 298(5598), 1634-1636.CrossRefPubMedGoogle Scholar
  20. Head, E. (2013). A canine model of human aging and Alzheimer's disease. Biochimica et Biophysica Acta (BBA)-Molecular Basis of Disease, 1832(9), 1384-1389.CrossRefGoogle Scholar
  21. Head, E., Callahan, H., Muggenburg, B. A., Cotman, C. W., & Milgram, N. W. (1998). Visual-discrimination learning ability and β-amyloid accumulation in the dog. Neurobiology of aging, 19(5), 415-425.CrossRefPubMedGoogle Scholar
  22. Head, E., McCleary, R., Hahn, F. F., Milgram, N. W., & Cotman, C. W. (2000). Region-specific age at onset of β-amyloid in dogs☆. Neurobiology of aging, 21(1), 89-96.CrossRefPubMedGoogle Scholar
  23. Head, E., Mehta, R., Hartley, J., Kameka, M., Cummings, B. J., Cotman, C. W., Ruehl, W. W., & Milgram, N. W. (1995). Spatial learning and memory as a function of age in the dog. Behavioral neuroscience, 109(5), 851.CrossRefPubMedGoogle Scholar
  24. Hoffman, J. M., Creevy, K. E., Franks, A., O'Neill, D. G., & Promislow, D. E. (2018). The companion dog as a model for human aging and mortality. Aging Cell.Google Scholar
  25. Heckler, M. C., Tranquilim, M. V., Svicero, D. J., Barbosa, L., & Amorim, R. M. (2014). Clinical feasibility of cognitive testing in dogs (Canis lupus familiaris). Journal of Veterinary Behavior: Clinical Applications and Research, 9(1), 6-12.CrossRefGoogle Scholar
  26. Kaeberlein, M., Creevy, K. E., & Promislow, D. E. (2016). The dog aging project: translational geroscience in companion animals. Mammalian genome, 27(7-8), 279-288.CrossRefPubMedPubMedCentralGoogle Scholar
  27. Karagiannis, C. I., Burman, O. H., & Mills, D. S. (2015). Dogs with separation-related problems show a “less pessimistic” cognitive bias during treatment with fluoxetine (ReconcileTM) and a behaviour modification plan. BMC Veterinary Research, 11(1), 80.CrossRefPubMedPubMedCentralGoogle Scholar
  28. Kimotsuki, T., Nagaoka, T., Yasuda, M., Tamahara, S., Matsuki, N., & Ono, K. (2005). Changes of magnetic resonance imaging on the brain in beagle dogs with aging. Journal of veterinary medical science, 67(10), 961-967.CrossRefPubMedGoogle Scholar
  29. Kis, A., Hernádi, A., Kanizsár, O., Gácsi, M., & Topál, J. (2015). Oxytocin induces positive expectations about ambivalent stimuli (cognitive bias) in dogs. Hormones and behavior, 69, 1-7.CrossRefPubMedGoogle Scholar
  30. Landsberg, G. M., Nichol, J., & Araujo, J. A. (2012). Cognitive dysfunction syndrome: a disease of canine and feline brain aging. Veterinary Clinics: Small Animal Practice, 42(4), 749-768.Google Scholar
  31. Lazarowski L, Dorman DC (2014) Explosives detection by military working dogs: Olfactory generalization from components to mixtures. Applied Animal Behaviour Science 151:84–93CrossRefGoogle Scholar
  32. Madari, A., Farbakova, J., Katina, S., Smolek, T., Novak, P., Weissova, T., Novak, M. and Zilka, N., 2015. Assessment of severity and progression of canine cognitive dysfunction syndrome using the CAnine DEmentia Scale (CADES). Applied Animal Behaviour Science, 171, 138-145.CrossRefGoogle Scholar
  33. Malenka, R. C., Nestler, E. J., & Hyman, S. E. (2009). Chapter 6: widely projecting systems: monoamines, acetylcholine, and orexin. Sydor A, Brown RY. Molecular Neuropharmacology: A Foundation for Clinical Neuroscience 147–148.Google Scholar
  34. Mendl, M., Burman, O. H. P., Parker, R. M. A., & Paul, E. S. (2009). Cognitive bias as an indicator of animal emotion and welfare: Emerging evidence and underlying mechanisms. Applied Animal Behaviour Science, 118(3–4), 161–181.CrossRefGoogle Scholar
  35. Mendl, M., Brooks, J., Basse, C., Burman, O., Paul, E., Blackwell, E., & Casey, R. (2010). Dogs showing separation-related behaviour exhibit a “pessimistic” cognitive bias. Current Biology, 20(19).CrossRefPubMedGoogle Scholar
  36. Miklósi, Á., Polgárdi, R., Topál, J., & Csányi, V. (1998). Use of experimenter-given cues in dogs. Animal cognition, 1(2), 113-121.CrossRefPubMedGoogle Scholar
  37. Miklósi, Á., & Topál, J. (2011). On the hunt for the gene of perspective taking: pitfalls in methodology. Learning & Behavior, 39(4), 310-313.CrossRefGoogle Scholar
  38. Milgram, N.W., E. Head, E. Weiner, E. Thomas, Cognitive functions and aging in the dog: acquisition of nonspatial visual tasks, Behav. Neurosci. 108 (1994) 57–68.CrossRefPubMedGoogle Scholar
  39. Milgram NW, Head E, Muggenburg B, Holowachuk D, Murphey H, Estrada J, Ikeda-Douglas CJ, Zicker SC, Cotman CW (2002) Landmark discrimination learning in the dog: effects of age, an antioxidant fortified food, and cognitive strategy. Neuroscience & Biobehavioral Reviews 26(6):679–695CrossRefGoogle Scholar
  40. Mongillo, P., Araujo, J. A., Pitteri, E., Carnier, P., Adamelli, S., Regolin, L., & Marinelli, L. (2013). Spatial reversal learning is impaired by age in pet dogs. Age, 35(6), 2273–2282.CrossRefPubMedPubMedCentralGoogle Scholar
  41. Neilson, J. C., Hart, B. L., Cliff, K. D., & Ruehl, W. W. (2001). Prevalence of behavioral changes associated with age-related cognitive impairment in dogs. Journal of the American Veterinary Medical Association, 218(11), 1787-1791.CrossRefPubMedGoogle Scholar
  42. Neus Bosch, M., Pugliese, M., Gimeno-Bayón, J., Jose Rodriguez, M., & Mahy, N. (2012). Dogs with cognitive dysfunction syndrome: a natural model of Alzheimer’s disease. Current Alzheimer Research, 9(3), 298-314.CrossRefGoogle Scholar
  43. Ownby RL, Crocco E, Acevedo A, John V, Loewenstein D (2006) Depression and risk for Alzheimer disease: systematic review, meta-analysis, and metaregression analysis. Archives of general psychiatry 63(5):530–538CrossRefPubMedPubMedCentralGoogle Scholar
  44. Paul, E. S., & Mendl, M. T. (2018). Animal emotion: Descriptive and prescriptive definitions and their implications for a comparative perspective. Applied Animal Behaviour Science.Google Scholar
  45. Piotti, P. (2017). Positive emotions and quality of life in dogs. Animal Sentience: An Interdisciplinary Journal on Animal Feeling, 2(14), 17.Google Scholar
  46. Piotti, P., Szabó, D., Wallis, L., Bognár, Z., Stiegmann, B.S., Egerer, A., Marty, P. and Kubinyi, E., 2017. The effect of age on visuo-spatial short-term memory in family dogs. Pet Behaviour Science, (4), 17-19.CrossRefGoogle Scholar
  47. Pongrácz, P., Ujvári, V., Faragó, T., Miklósi, Á., & Péter, A. (2017). Do you see what I see? The difference between dog and human visual perception may affect the outcome of experiments. Behavioural processes, 140, 53-60.CrossRefPubMedGoogle Scholar
  48. R Core Team (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
  49. Roelofs, S., Boleij, H., Nordquist, R. E., & van der Staay, F. J. (2016). Making decisions under ambiguity: judgment bias tasks for assessing emotional state in animals. Frontiers in behavioral neuroscience, 10, 119.CrossRefPubMedPubMedCentralGoogle Scholar
  50. Salvin HE, McGreevy PD, Sachdev PS, Valenzuela MJ (2011) The canine sand maze: an appetitive spatial memory paradigm sensitive to age‐related change in dogs. Journal of the experimental analysis of behavior 95(1):109–118CrossRefPubMedPubMedCentralGoogle Scholar
  51. Schütt, T., Helboe, L., Pedersen, L. Ø., Waldemar, G., Berendt, M., & Pedersen, J. T. (2016). Dogs with cognitive dysfunction as a spontaneous model for early Alzheimer’s disease: a translational study of neuropathological and inflammatory markers. Journal of Alzheimer's Disease, 52(2), 433-449.CrossRefPubMedGoogle Scholar
  52. Szabó D, Gee NR, Miklósi Á (2016) Natural or pathologic? Discrepancies in the study of behavioral and cognitive signs in aging family dogs. Journal of Veterinary Behavior: Clinical Applications and Research 11:86–98CrossRefGoogle Scholar
  53. Szetei, V., Miklósi, Á., Topál, J., & Csányi, V. (2003). When dogs seem to lose their nose: an investigation on the use of visual and olfactory cues in communicative context between dog and owner. Applied Animal Behaviour Science, 83(2), 141-152.CrossRefGoogle Scholar
  54. Siwak-Tapp, C. T., Head, E., Muggenburg, B. A., Milgram, N. W., & Cotman, C. W. (2007). Neurogenesis decreases with age in the canine hippocampus and correlates with cognitive function. Neurobiology of learning and memory, 88(2), 249-259.CrossRefPubMedPubMedCentralGoogle Scholar
  55. Siwak-Tapp, C. T., Head, E., Muggenburg, B. A., Milgram, N. W., & Cotman, C. W. (2008). Region specific neuron loss in the aged canine hippocampus is reduced by enrichment. Neurobiology of aging, 29(1), 39-50.CrossRefPubMedGoogle Scholar
  56. Starling, M. J., Branson, N., Cody, D., Starling, T. R., & McGreevy, P. D. (2014). Canine sense and sensibility: tipping points and response latency variability as an optimism index in a canine judgement bias assessment. PLoS One, 9 (9), e107794.CrossRefPubMedPubMedCentralGoogle Scholar
  57. Studzinski, C. M., Christie, L. A., Araujo, J. A., Burnham, W. M., Head, E., Cotman, C. W., & Milgram, N. W. (2006). Visuospatial function in the beagle dog: an early marker of cognitive decline in a model of human aging and dementia. Neurobiology of learning and memory, 86(2), 197-204.CrossRefPubMedGoogle Scholar
  58. Su, M.Y., Head, E., Brooks, W.M., Wang, Z., Muggenburg, B.A., Adam, G.E., Sutherland, R., Cotman, C.W. and Nalcioglu, O., 1998. Magnetic resonance imaging of anatomic and vascular characteristics in a canine model of human aging. Neurobiology of aging, 19(5), 479-485.CrossRefPubMedGoogle Scholar
  59. Tapp, P. D., Siwak, C. T., Estrada, J., Holowachuk, D., & Milgram, N. W. (2003a). Effects of age on measures of complex working memory span in the beagle dog (Canis familiaris) using two versions of a spatial list learning paradigm. Learning & Memory, 10(2), 148-160.CrossRefGoogle Scholar
  60. Tapp, P. D., Siwak, C. T., Estrada, J., Head, E., Muggenburg, B. A., Cotman, C. W., & Milgram, N. W. (2003b). Size and reversal learning in the beagle dog as a measure of executive function and inhibitory control in aging. Learning & Memory, 10(1), 64-73.CrossRefGoogle Scholar
  61. Tapp, P.D., Siwak, C.T., Gao, F.Q., Chiou, J.Y., Black, S.E., Head, E., Muggenburg, B.A., Cotman, C.W., Milgram, N.W. and Su, M.Y., 2004. Frontal lobe volume, function, and β-amyloid pathology in a canine model of aging. Journal of Neuroscience, 24(38), 8205-8213.CrossRefPubMedGoogle Scholar
  62. Wallis, L. J., Virányi, Z., Müller, C. A., Serisier, S., Huber, L., & Range, F. (2016). Aging effects on discrimination learning, logical reasoning and memory in pet dogs. Age, 38(1), 6.CrossRefPubMedPubMedCentralGoogle Scholar
  63. Wallis, L. J., Range, F., Kubinyi, E., Chapagain, D., Serra, J., & Huber, L. (2017). Utilising dog-computer interactions to provide mental stimulation in dogs especially during ageing. In Proceedings of the Fourth International Conference on Animal-Computer Interaction (p. 1). ACM.Google Scholar
  64. Waters, D. J. (2011). Aging research 2011: exploring the pet dog paradigm. ILAR journal, 52(1), 97-105.CrossRefPubMedGoogle Scholar
  65. Westfall, J., Judd, C. M., & Kenny, D. A. (2015). Replicating studies in which samples of participants respond to samples of stimuli. Perspectives on Psychological Science, 10(3), 390-399.CrossRefPubMedGoogle Scholar
  66. William, W., Kahloon, M., Fakhry, H., Ishak, W.W., 2011. Oxytocin role in enhancing well- being: a literature review. J. Affect. Disord. 130, 1–9.CrossRefGoogle Scholar
  67. Wood, L. S., Desjardins, J. K., & Fernald, R. D. (2011). Effects of stress and motivation on performing a spatial task. Neurobiology of learning and memory, 95(3), 277-285.CrossRefPubMedGoogle Scholar
  68. Yeates J, Main D (2009) Assessment of companion animal quality of life in veterinary practice and research. Journal of Small Animal Practice 50(6):274–281CrossRefPubMedGoogle Scholar

Copyright information

© Psychonomic Society, Inc. 2018

Authors and Affiliations

  • Patrizia Piotti
    • 1
  • Dóra Szabó
    • 1
  • Zsófia Bognár
    • 1
  • Anna Egerer
    • 1
  • Petrouchka Hulsbosch
    • 1
    • 2
  • Rachel Sophia Carson
    • 1
    • 3
  • Enikő Kubinyi
    • 1
  1. 1.Department of EthologyEötvös Loránd UniversityBudapestHungary
  2. 2.Bioengineering TechnologyKatholieke Universiteit LeuvenGeelBelgium
  3. 3.Kalamazoo CollegeKalamazooUSA

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