Exploring the Effect of Stimulus Similarity on the Summation Effect in Causal Learning
Abstract
Abstract. Several contemporary models anticipate that the summation effect is modulated by the similarity between the cues forming a compound. Here, we explore this hypothesis in a series of causal learning experiments. Participants were presented with two visual cues that separately predicted a common outcome and later asked for the outcome predicted by the compound of the two cues. Similarity was varied between groups through changes in shape, spatial position, color, configuration, and rotation. In variance with the predictions of these models, we observed similar and strong levels of summation in both groups across all manipulations of similarity. The effect, however, was significantly reduced by manipulations intended to impact assumptions about the causal independence of the cues forming the compound, but this reduction was independent of stimulus similarity. These results are problematic for similarity-based models and can be more readily explained by rational approaches to causal learning.
References
1994). Prototype effects in categorization by pigeons. Journal of Experimental Psychology: Animal Behavior Processes, 20, 264. https://doi.org/10.1037/0097-7403.20.3.264
(1995). Summation in autoshaping with short- and long-duration stimuli. The Quarterly Journal of Experimental Psychology (2006), 48, 215–234.
(1997). Some determinants of response summation. Animal Learning & Behavior, 25, 108–121. https://doi.org/10.3758/bf03199029
(2005). Outcome additivity and outcome maximality influence cue competition in human causal learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31, 238. https://doi.org/10.1037/0278-7393.31.2.238
(2011). Introduction to meta-analysis. Hoboken, NJ: John Wiley & Sons.
(2003). Stimulus representation in SOP: I Theoretical rationalization and some implications. Behavioural Processes, 62, 5–25. https://doi.org/10.1016/S0376-6357(03)00016-0
(2000). A componential view of configural cues in generalization and discrimination in Pavlovian conditioning. Behavioural Brain Research, 110, 67–72. https://doi.org/10.1016/s0166-4328(99)00185-0
(1997). From covariation to causation: A causal power theory. Psychological Review, 104, 367–405. https://doi.org/10.1037/0033-295X.104.2.367
(1992). Covariation in natural causal induction. Psychological Review, 99, 365–382.
(2006). Summation in causal learning: Elemental processing or configural generalization? The Quarterly Journal of Experimental Psychology (2006), 59, 1524–1534. https://doi.org/10.1080/17470210600639389
(2006). Bayesian theories of conditioning in a changing world. Trends in Cognitive Sciences, 10, 294–300. https://doi.org/10.1016/j.tics.2006.05.004
(2008). Evidence for an expectancy-based theory of avoidance behaviour. The Quarterly Journal of Experimental Psychology (2006), 61, 1803–1812. https://doi.org/10.1080/17470210701851214
(1984). Judgement of act-outcome contingency: The role of selective attribution. The Quarterly Journal of Experimental Psychology, 36A, 37–41. https://doi.org/10.1080/14640748408401502
(2002). Spatial separation of target and competitor cues enhances blocking of human causality judgements. The Quarterly Journal of Experimental Psychology. B, Comparative and Physiological Psychology, 55, 121–135. https://doi.org/10.1080/02724990143000207
(2010). Reduced summation with common features in causal judgments. Experimental Psychology, 57, 252–259. https://doi.org/10.1027/1618-3169/a000030
(2006). Elemental representations of stimuli in associative learning. Psychological Review, 113, 584–605. https://doi.org/10.1037/0033-295X.113.3.584
(2010). An attention-modulated associative network. Learning & Behavior, 38, 1–26. https://doi.org/10.3758/lb.38.1.1
(2011). Causal learning and inference as a rational process: The new synthesis. Annual Review of Psychology, 62, 135–163. https://doi.org/10.1146/annurev.psych.121208.131634
(1961). The theory of probability. Oxford, UK: Oxford University Press.
(1994). Summation and configuration between and within sensory modalities in classical conditioning of the rabbit. Animal Learning & Behavior, 22(1), 19–26.
(2003). Similarity and discrimination in human Pavlovian conditioning. Psychophysiology, 40, 226–234. https://doi.org/10.1111/1469-8986.00024
(2004). Outcome additivity, elemental processing and blocking in human causality judgements. The Quarterly Journal of Experimental Psychology. B, Comparative and Physiological Psychology, 57, 361–379. https://doi.org/10.1080/02724990444000005
(2003). Forward and backward blocking of causal judgment is enhanced by additivity of effect magnitude. Memory & Cognition, 31, 133–142.
(2002). The role of awareness in Pavlovian conditioning: Empirical evidence and theoretical implications. Journal of Experimental Psychology: Animal Behavior Processes, 28, 3–26. https://doi.org/10.1037/0097-7403.28.1.3
(2016). A Bayesian theory of sequential causal learning and abstract transfer. Cognitive Science, 40, 404–439. https://doi.org/10.1111/cogs.12236
(2010). Learning the form of causal relationships using hierarchical bayesian models. Cognitive Science, 34, 113–147. https://doi.org/10.1111/j.1551-6709.2009.01058.x
(2002). Associative learning and elemental representation: II. Generalization and discrimination. Animal Learning & Behavior, 30, 177–200. https://doi.org/10.3758/BF03192828
(2008). Stimulus coding in human associative learning: Flexible representations of parts and wholes. Behavioural Processes, 77, 413. https://doi.org/10.1016/j.beproc.2007.09.013
(2009). The propositional nature of human associative learning. The Behavioral and Brain Sciences, 32, 183–246. https://doi.org/10.1017/S0140525X09000855
(2011). Bayes factor approaches for testing interval null hypotheses. Psychological Methods, 16, 406–419.
(2015). BayesFactor: Computation of Bayes factors for common designs. Retrieved from https://cran.r-project.org/package=BayesFactor
(2001). A comparison of the Rescorla-Wagner and Pearce models in a negative patterning and a summation problem. Animal Learning & Behavior, 29, 36–45. https://doi.org/10.3758/BF03192814
(1987). A model for stimulus generalization in Pavlovian conditioning. Psychological Review, 94, 61–73. https://doi.org/10.1037/0033-295x.94.1.61
(1994). Similarity and discrimination: A selective review and a connectionist model. Psychological Review, 101, 587–607. https://doi.org/10.1037/0033-295x.101.4.587
(2007). PsychoPy – psychophysics software in Python. Journal of Neuroscience Methods, 162, 8–13. https://doi.org/10.1016/j.jneumeth.2006.11.017
(2016). {nlme}: Linear and nonlinear mixed effects models. Retrieved from http://cran.r-project.org/package=nlme
. (2007). Multimodal discrimination learning in humans: Evidence for configural theory. The Quarterly Journal of Experimental Psychology, 60, 1477–1495. https://doi.org/10.1080/17470210601154560
(1976). Stimulus generalization: Some predictions from a model of Pavlovian conditioning. Journal of Experimental Psychology. Animal Behavior Processes, 2, 88–96.
(1997). Summation: Assessment of a configural theory. Animal Learning & Behavior, 25, 200–209. https://doi.org/10.3758/BF03199059
(1995). Summation in autoshaping. Animal Learning & Behavior, 23, 314–326. https://doi.org/10.3758/BF03198928
(1972). A theory of Pavlovian conditioning: Variations in the effectiveness of reinforcement and nonreinforcement. Classical Conditioning II: Current Research and Theory, 2, 64–99.
(2007). Meta: An R package for meta-analysis. R news, 7(3), 40–45.
(2010). Learning: From association to cognition. Annual Review of Psychology, 61, 273–301. https://doi.org/10.1146/annurev.psych.093008.100519
(1998). Feature- and rule-based generalization in human associative learning. Journal of Experimental Psychology: Animal Behavior Processes, 24, 405. https://doi.org/10.1037/0097-7403.24.4.405
(1987). Toward a universal law of generalization for psychological science. Science, 237(4820), 1317–1323.
(2014). Explaining compound generalization in associative and causal learning through rational principles of dimensional generalization. Psychological Review, 121(3), 526–558. https://doi.org/10.1037/a0037018
(2015). Why are some dimensions integral? Testing two hypotheses through causal learning experiments. Cognition, 143, 163–177. https://doi.org/10.1016/j.cognition.2015.07.001
(2009). Generality of the summation effect in human causal learning. The Quarterly Journal of Experimental Psychology (2006), 62, 877–889. https://doi.org/10.1080/17470210802373688
(2010). Error-driven learning in visual categorization and object recognition: a common-elements model. Psychological Review, 117, 349–381. https://doi.org/10.1037/a0018695
(2008). How the associative strengths of stimuli combine in compound: Summation and overshadowing. Journal of Experimental Psychology: Animal Behavior Processes, 34(1), 155.
(2015). RStudio: Integrated development for R. Boston, MA: RStudio, Inc. Retrieved from http://www.rstudio.com
(2012). Normalization between stimulus elements in a model of Pavlovian conditioning: Showjumping on an elemental horse. Learning & Behavior, 40, 334–346. https://doi.org/10.3758/s13420-012-0073-7
(2014). Two heads are better than one, but how much? Evidence that people’s use of causal integration rules does not always conform to normative standards. Experimental Psychology, 61(5), 356–367. https://doi.org/10.1027/1618-3169/a000255
(1994). Cue competition in causality judgments: The role of nonpresentation of compound stimulus elements. Learning and Motivation, 25(2), 127–151.
(2003). Context-sensitive elemental theory. The Quarterly Journal of Experimental Psychology. B, Comparative and Physiological Psychology, 56, 7–29. https://doi.org/10.1080/02724990244000133
(2008). Evolution of an elemental theory of Pavlovian conditioning. Learning & Behavior, 36, 253–265. https://doi.org/10.3758/LB.36.3.253
(2016). I think, therefore eyeblink: The importance of contingency awareness in conditioning. Psychological Science, 27(4), 467–475. https://doi.org/10.1177/0956797615625973
(1972). Negative patterning in classical conditioning: Summation of response tendencies to isolable and configurai components. Psychonomic Science, 27, 299–301. https://doi.org/10.3758/bf03328970
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