Mechanisms of randomness cognition

• Main Author: Yu, Ru Qi
• Language: English
• Published: University of British Columbia 2017
• Online Access: http://hdl.handle.net/2429/62682

The environment is inherently noisy, with regularities and randomness. Therefore, the challenge for the cognitive system is to detect signals from noise. This extraction of regularities forms the basis of many learning processes, such as conditioning and language acquisition. However, people often have erroneous beliefs about randomness. One pervasive bias in people’s conception of randomness is that they expect random sequences to exhibit greater alternations than typically produced by random devices (i.e., the over-alternation bias). To explain the causes of this bias, in the thesis, I examined the cognitive and neural mechanisms of randomness perception. In six experiments, I found that the over-alternation bias was present regardless of the feature dimensions, sensory modalities, and probing methods (Experiment 1); alternations in a binary sequence were harder to encode and are under-represented compared with repetitions (Experiments 2-5); and hippocampal neurogenesis was a critical neural mechanism for the detection of alternating patterns but not for repeating patterns (Experiment 6). These findings provide new insights on the mechanisms of randomness cognition; specifically, we revealed different mechanisms involved in representing alternating patterns versus repeating patterns. === Arts, Faculty of === Psychology, Department of === Graduate