Book contents
- Evolution of Learning and Memory Mechanisms
- Evolution of Learning and Memory Mechanisms
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Preface
- Introduction
- Part I Evolution of Learning Processes
- 1 Learning and Memory in the Nematode Caenorhabditis elegans
- 2 Adaptive Evolution of Learning and Memory in a Model Lineage
- 3 Learning in Insects: Perspectives and Possibilities
- 4 Experimental Evolution and Mechanisms for Prepared Learning
- 5 Evolutionary Processes Shaping Learning Ability in Insects
- 6 Brain and Spatial Cognition in Amphibians
- 7 Pavlovian Conditioning, Survival, and Reproductive Success
- 8 Compensatory Responses to Wildlife Control
- 9 Relational Memory Functions of the Hippocampal Pallium in Teleost Fish
- 10 Mechanisms Underlying Absolute and Relative Reward Value in Vertebrates
- 11 The Optimality of “Suboptimal” Choice
- 12 A Behavior Systems Framework
- 13 Dissociable Learning Processes
- 14 Social Learning Strategies
- 15 How Learning Affects Evolution
- Part II Evolution of Memory Processes
- Index
- References
13 - Dissociable Learning Processes
A Comparative Perspective
from Part I - Evolution of Learning Processes
Published online by Cambridge University Press: 26 May 2022
Book contents
- Evolution of Learning and Memory Mechanisms
- Evolution of Learning and Memory Mechanisms
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Preface
- Introduction
- Part I Evolution of Learning Processes
- 1 Learning and Memory in the Nematode Caenorhabditis elegans
- 2 Adaptive Evolution of Learning and Memory in a Model Lineage
- 3 Learning in Insects: Perspectives and Possibilities
- 4 Experimental Evolution and Mechanisms for Prepared Learning
- 5 Evolutionary Processes Shaping Learning Ability in Insects
- 6 Brain and Spatial Cognition in Amphibians
- 7 Pavlovian Conditioning, Survival, and Reproductive Success
- 8 Compensatory Responses to Wildlife Control
- 9 Relational Memory Functions of the Hippocampal Pallium in Teleost Fish
- 10 Mechanisms Underlying Absolute and Relative Reward Value in Vertebrates
- 11 The Optimality of “Suboptimal” Choice
- 12 A Behavior Systems Framework
- 13 Dissociable Learning Processes
- 14 Social Learning Strategies
- 15 How Learning Affects Evolution
- Part II Evolution of Memory Processes
- Index
- References
Summary
It is a traditional hope of comparative psychology that animal minds might be unitary, parsimonious, associative. In contrast, cognitive researchers acknowledge multiple learning systems, including humans’ capacity for explicit hypothesis testing and rule learning. The authors describe new paradigms that may dissociate the explicit from the associative and demonstrate animals’ explicit capabilities. These paradigms include matched tasks that foster explicit or associative category learning, and paradigms that disable crucial components of associative learning. Given this disabling, animals may adopt instead an alternative, more explicit learning system. The authors review this area, including research on humans, monkeys, rats, and pigeons. They also consider the evolutionary and fitness factors that might favor the development of complementary associative and explicit learning systems.
Keywords
- Type
- Chapter
- Information
- Evolution of Learning and Memory Mechanisms , pp. 227 - 246Publisher: Cambridge University PressPrint publication year: 2022
References
Arbuthnott, G. W., Ingham, C. A., & Wickens, J. R. (2000). Dopamine and synaptic plasticity in the neostriatum. Journal of Anatomy, 196, 587–596. https://doi.org/10.1046/j.1469-7580.2000.19640587.xGoogle Scholar
Ashby, F. G., Alfonso-Reese, L. A., Turken, A. U., & Waldron, E. M. (1998). A neuropsychological theory of multiple systems in category learning. Psychological Review, 105, 442–481. https://doi.org/10.1037/0033-295X.105.3.442Google Scholar
Ashby, F. G., & Ell, S. W. (2001). The neurobiology of human category learning. Trends in Cognitive Sciences, 5, 204–210. https://doi.org/10.1016/S1364-6613(00)01624-7Google Scholar
Ashby, F. G., & Maddox, W. T. (2011). Human category learning 2.0. Annals of the New York Academy of Sciences, 1224, 147–161. https://doi.org/10.1111/j.1749-6632.2010.05874.xGoogle Scholar
Ashby, F. G., Maddox, W. T., & Bohil, C. J. (2002). Observational versus feedback training in rule-based and information-integration category learning. Memory & Cognition, 30, 666–677. https://doi.org/10.3758/BF03196423Google Scholar
Ashby, F. G., Smith, J. D., & Rosedahl, L. (2020). Dissociations between rule-based and information-integration categorization are not caused by differences in task difficulty. Memory & Cognition, 48, 541–552. https://doi.org/10.3758/s13421-019-00988-4CrossRefGoogle Scholar
Ashby, F. G., & Valentin, V. V. (2017). Multiple systems of perceptual category learning: Theory and cognitive tests. In Cohen, H. & Lefebvre, C. (Eds.), Handbook of Categorization in Cognitive Science (2nd ed., pp. 157–188). Elsevier. https://doi.org/10.1016/B978-0-08-101107-2.00007-5Google Scholar
Basile, B. M., Schroeder, G. R., Brown, E. K., Templer, V. L., & Hampton, R. R. (2015). Evaluation of seven hypotheses for metamemory performance in rhesus monkeys. Journal of Experimental Psychology: General, 144, 85–102. https://doi.org/10.1037/xge0000031Google Scholar
Beran, M. J., Smith, J. D., & Perdue, B. M. (2013). Language-trained chimpanzees name what they have seen but look first at what they have not seen. Psychological Science, 24, 660–666. https://doi.org/10.1177/0956797612458936Google Scholar
Broschard, M. B., Kim, J., Love, B. C., Wasserman, E. A., & Freeman, J. H. (2019). Selective attention in rat visual category learning. Learning & Memory, 26, 84–92. https://doi.org/10.1101/lm.048942.118Google Scholar
Casale, M. B, Roeder, J. L., & Ashby, F. G. (2012). Analogical transfer in perceptual categorization. Memory & Cognition, 40, 434–449. https://doi.org/10.3758/s13421-011-0154-4Google Scholar
Elliott, R., & Dolan, R. J. (1998). Activation of different anterior cingulate foci in association with hypothesis testing and response selection. Neuroimage, 8, 17–29. https://doi.org/10.1006/nimg.1998.0344Google Scholar
Fagot, J., & Thompson, R. K. R. (2011). Generalized relational matching by guinea baboons (Papio papio) in two-by-two-item analogy problems. Psychological Science, 22, 1304–1309. https://doi.org/10.1177/0956797611422916Google Scholar
Hollerman, J. R., & Schultz, W. (1998). Dopamine neurons report an error in the temporal prediction of reward during learning. Nature Neuroscience, 1, 304–309. https://doi.org/10.1038/1124CrossRefGoogle ScholarPubMed
Knowlton, B. J., Mangels, J. A., & Squire, L. R. (1996). A neostriatal habit learning system in humans. Science, 273(5280), 1399–1402. https://doi.org/10.1126/science.273.5280.1399Google Scholar
Maddox, W. T., & Ashby, F. G. (2004). Dissociating explicit and procedural-learning based systems of perceptual category learning. Behavioural Processes, 66, 309–332. https://doi.org/10.1016/j.beproc.2004.03.011Google Scholar
Maddox, W. T., & Ing, A. D. (2005). Delayed feedback disrupts the procedural-learning system but not the hypothesis-testing system in perceptual category learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31, 100–107. https://doi.org/10.1037/0278-7393.31.1.100Google Scholar
Maugard, A., Marzouki, Y., & Fagot, J. (2013). Contribution of working memory processes to relational matching-to-sample performance in baboons (Papio papio). Journal of Comparative Psychology, 127, 370–379. http://doi.org/10.1037/a0032336CrossRefGoogle ScholarPubMed
Pavlov, I. P. (1927). Conditioned reflexes: An investigation of the physiological activity of the cerebral cortex. Oxford University Press. https://doi.org/10.5214/ans.0972-7531.1017309Google Scholar
Pearce, J. M., Esber, G. R., George, D. N., & Haselgrove, M. (2008). The nature of discrimination learning in pigeons. Learning & Behavior, 36, 188–199. https://doi.org/10.3758/LB.36.3.188Google Scholar
Posner, M. I., & Petersen, S. E. (1990). The attention system of the human brain. Annual Review of Neuroscience, 13, 25–42. https://doi.org/10.1146/annurev.ne.13.030190.000325Google Scholar
Qadri, M. A.-J., Ashby, F. G., Smith, J. D., & Cook, R. G. (2019). Testing analogical rule transfer in pigeons (Columba livia). Cognition, 183, 256–268. https://doi.org/10.1016/j.cognition.2018.11.011Google Scholar
Rao, S. M., Bobholz, J. A., Hammeke, T. A., Rosen, A. C., Woodley, S. J., Cunningham, J. M., & Binder, J. R. (1997). Functional MRI evidence for subcortical participation in conceptual reasoning skills. Neuroreport, 8, 1987–1993. https://doi.org/10.1097/00001756-199705260-00038Google Scholar
Roberts, A. C. (1996). Comparison of cognitive function in human and non-human primates. Cognitive Brain Research, 3, 319–327. https://doi.org/10.1016/0926-6410(96)00017-1Google Scholar
Robinson, A. L., Heaton, R. K., Lehman, R. A., & Stilson, D. W. (1980). The utility of the Wisconsin Card Sorting Test in detecting and localizing frontal lobe lesions. Journal of Consulting and Clinical Psychology, 48, 605–614. https://doi.org/10.1037/0022-006X.48.5.605Google Scholar
Schultz, W. (1992). Activity of dopamine neurons in the behaving primate. Seminars in Neuroscience, 4, 129–138. https://doi.org/10.1016/1044-5765(92)90011-PGoogle Scholar
Semendeferi, K., Lu, A., Schenker, N., & Damásio, H. (2002). Humans and great apes share a large frontal cortex. Nature Neuroscience, 5, 272–276. https://doi.org/10.1038/nn814Google Scholar
Smith, J. D., Ashby, F. G., Berg, M. E., Murphy, M. S., Spiering, B., Cook, R. G., & Grace, R. C. (2011). Pigeons’ categorization may be exclusively nonanalytic. Psychonomic Bulletin & Review, 18, 414–421. http://doi.org/10.3758/s13423-010-0047-8Google Scholar
Smith, J. D., Beran, M. J., Crossley, M. J., Boomer, J., & Ashby, F. G. (2010). Implicit and explicit category learning by macaques (Macaca mulatta) and humans (Homo sapiens). Journal of Experimental Psychology: Animal Behavior Processes, 36, 54–65. https://doi.org/10.1037/a0015892Google ScholarPubMed
Smith, J. D., Berg, M. E., Cook, R. G., Boomer, J., Crossley, M. J., Murphy, M. S., Spiering, B., Beran, M. J., Church, B. A., Ashby, F. G., & Grace, R. C. (2012). Implicit and explicit categorization: A tale of four species. Neuroscience and Biobehavioral Reviews, 36, 2355–2369. https://doi.org/10.1016/j.neubiorev.2012.09.003Google Scholar
Smith, J. D., Boomer, J., Zakrzewski, A. C., Roeder, J. L., Church, B. A., & Ashby, F. G. (2014). Deferred feedback sharply dissociates implicit and explicit category learning. Psychological Science, 25, 447–457. https://doi.org/10.1177/0956797613509112Google Scholar
Smith, J. D. & Church, B. A. (2018). Dissociable learning processes in comparative psychology. Psychonomic Bulletin & Review, 25, 1565–1584. http://doi.org/10.3758/s13423-017-1353-1CrossRefGoogle ScholarPubMed
Smith, J. D., Couchman, J. J., & Beran, M. J. (2012). The highs and lows of theoretical interpretation in animal metacognition research. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 367, 1297–1309. https://doi.org/10.1098/rstb.2011.0366CrossRefGoogle ScholarPubMed
Smith, J. D., Coutinho, M. V. C., Church, B. A., & Beran, M. J. (2013). Executive-attentional uncertainty responses by rhesus macaques (Macaca mulatta). Journal of Experimental Psychology: General, 142, 458–475. https://doi.org/10.1037/a0029601CrossRefGoogle ScholarPubMed
Smith, J. D., Crossley, M. J., Boomer, J., Church, B. A., Beran, M. J., & Ashby, F. G. (2012). Implicit and explicit category learning by capuchin monkeys (Cebus apella). Journal of Comparative Psychology, 126, 294–304. https://doi.org/10.1037/a0026031Google Scholar
Smith, J. D., & Ell, S. W. (2015). One giant leap for categorizers: One small step for categorization theory. PLoS ONE, 10(9), e0137334. https://doi.org/10.1371/journal.pone.0137334Google Scholar
Smith, J. D., Flemming, T. M., Boomer, J., Beran, M. J., & Church, B. A. (2013). Fading perceptual resemblance: A path for rhesus macaques (Macaca mulatta) to conceptual matching? Cognition, 129, 1598–1614. https://doi.org/10.1016/j.cognition.2013.08.001Google Scholar
Smith, J. D., Jackson, B. N., & Church, B. A. (2019). Breaking the perceptual-conceptual barrier: Relational matching and working memory. Memory & Cognition, 47, 544–560. https://doi.org/10.3758/s13421-018-0890-9Google Scholar
Smith, J. D., Jackson, B. N., & Church, B. A. (2020). Monkeys (Macaca mulatta) learn two-choice discriminations under displaced reinforcement. Journal of Comparative Psychology, 134, 423–434. https://doi.org/10.1037/com0000227Google Scholar
Smith, J. D., Jamani, S., Boomer, J., & Church, B. A. (2018). One-back reinforcement dissociates implicit-procedural and explicit-declarative category learning. Memory & Cognition, 46, 261–273. https://doi.org/10.3758/s13421-017-0762-8CrossRefGoogle ScholarPubMed
Smith, J. D., Zakrzewski, A. C., Johnston, J. J. R., Roeder, J. L., Boomer, J., Ashby, F. G., & Church, B. A. (2015). Generalization of category knowledge and dimensional categorization in humans (Homo sapiens) and nonhuman primates (Macaca mulatta). Journal of Experimental Psychology: Animal Learning and Cognition, 41, 322–335. https://doi.org/10.1037/xan0000071Google Scholar
Smith, J. D., Zakrzewski, A. C., Johnson, J. M., Valleau, J. C., & Church, B. A. (2016). Categorization: The view from animal cognition. Behavioural Science, 6, 12. https://doi.org/10.3390/bs6020012Google Scholar
Sutton, J. E., & Shettleworth, S. J. (2008). Memory without awareness: Pigeons do not show metamemory in delayed matching to sample. Journal of Experimental Psychology: Animal Behavior Processes, 34, 266–282. https://doi.org/10.1037/0097-7403.34.2.266Google Scholar
Waldron, E. M., & Ashby, F. G. (2001). The effects of concurrent task interference on category learning: Evidence for multiple category learning systems. Psychonomic Bulletin & Review, 8, 168–176. https://doi.org/10.3758/BF03196154Google Scholar
Waldschmidt, J. G., & Ashby, F. G. (2011). Cortical and striatal contributions to automaticity in information-integration categorization. NeuroImage, 56, 1791–1802. https://doi.org/10.1016/j.neuroimage.2011.02.011Google Scholar
Washburn, D. A. (1994). Stroop-like effects for monkeys and humans: Processing speed or strength of association? Psychological Science, 5, 375–379. https://doi.org/10.1111/j.1467-9280.1994.tb00288.xGoogle Scholar
Yagishita, S., Hayashi-Takagi, A., Ellis-Davies, G. C. R., Urakubo, H., Ishii, S., & Kasai, H. (2014). A critical time window for dopamine actions on the structural plasticity of dendritic spines. Science, 345(6204), 1616–1620. https://doi.org/10.1126/science.1255514Google Scholar
Yin, H. H., Ostlund, S. B., Knowlton, B. J., & Balleine, B. W. (2005). The role of the dorsomedial striatum in instrumental conditioning. European Journal of Neuroscience, 22(2), 513–523. https://doi.org/10.1111/j.1460-9568.2005.04218.xGoogle Scholar
Yonelinas, A. P. (2002). The nature of recollection and familiarity: A review of 30 years of research. Journal of Memory and Language, 46, 441–517. https://doi.org/10.1006/jmla.2002.2864Google Scholar
Young, M. E., Wasserman, E. A., & Garner, K. L. (1997). Effects of number of items on the pigeon’s discrimination of same from different visual displays. Journal of Experimental Psychology: Behavior Processes, 23, 491–501. https://doi.org/10.1037/0097-7403.23.4.491Google Scholar
Zakrzewski, A. C., Church, B. A., & Smith, J. D. (2018). The transfer of category knowledge by macaques (Macaca mulatta) and humans (Homo sapiens). Journal of Comparative Psychology, 132, 58–74. https://doi.org/10.1037/com0000095Google Scholar
Zakrzewski, A. C., Johnson, J. M., & Smith, J. D. (2017). The comparative psychology of metacognition. In Call, J., Burghardt, G. M., Pepperberg, I. M., Snowdon, C. T., & Zentall, T. (Eds.), APA handbook of comparative psychology: Perception, learning, and cognition (pp. 703–721). American Psychological Association. https://doi.org/10.1037/0000012-031Google Scholar