Jiaying Zhao

No abstract available.

No abstract available.

No abstract available.

No abstract available.

A remarkable ability of the cognitive system is to make novel inferences based on prior experiences. What mechanism supports such inference? We propose that statistical learning is a process where transitive inferences of new associations are made between objects that have never been directly associated. After viewing a continuous sequence containing two base pairs (e.g., A-B, B-C), participants automatically inferred a transitive pair (e.g., A-C) where the two objects had never co-occurred before (Experiment 1). This transitive inference occurred in the absence of explicit awareness of the base pairs. However, participants failed to infer the transitive pair from three base pairs (Experiment 2), showing the limits of the transitive inference (Experiment 3). We further demonstrated that this transitive inference can operate across the categorical hierarchy (Experiments 4-7). The findings revealed a novel consequence of statistical learning where new transitive associations between objects are implicitly inferred.

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Resource scarcity poses challenging demands on the cognitive system. Budgeting with limited resources induces an attentional focus on the problem at hand, but it also comes with a cost. Specifically, scarcity causes a failure to notice beneficial information in the environment, or remember to execute actions in the future, that help alleviate the condition of scarcity. This neglect may arise as a result of attentional narrowing. Attentional trade-offs under scarcity can further determine memory encoding. In seven experiments, we demonstrated that participants under scarcity prioritized price information but neglected a useful discount when ordering food from a menu (Experiment 1); they showed better recall for information relevant to the focal task at a subsequent surprise memory test (Experiments 2 and 3); they performed more efficiently on the focal task but neglect a useful cue in the environment that could save them resources (Experiments 4-6); and they failed to remember the previous instructions to execute future actions that could save them resources (Experiment 7). These results collectively demonstrate that scarcity fundamentally shapes the way people process information in the environment, by directing attention to the most urgent task, while inducing a neglect of other information that can be beneficial. The attentional neglect and memory failures may lead to suboptimal behaviors that further aggravate the condition of scarcity. The results provide new insights on the behaviors of the poor, and also important implications for public policy and the design of welfare services and programs for low-income individuals.

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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.

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The visual system is remarkably efficient at extracting summary statistics from the environment. Yet at any given time, the environment consists of many groups of objects distributed over space. Thus, the challenge for the visual system is to summarize over multiple sets distributed across space. My thesis work investigates the capacity constraints and computational efficiency of ensemble perception, in the context of perceiving multiple spatially intermixed groups of objects. First, in three experiments, participants viewed an array of 1 to 8 intermixed sets of circles. Each set contained four circles in the same colors but with different sizes. Participants estimated the mean size of a probed set. Which set would be probed was either known before onset of the array (pre-cue), or after that (post-cue). Fitting a uniform-normal mixture model to the error distribution, I found participants could reliably estimate mean sizes for maximally four sets (Experiment 1). Importantly, their performance was unlikely to be driven by a subsampling strategy (Experiment 2). Allowing longer exposure to the stimulus array did not increase the capacity, suggesting ensemble perception was limited by an internal resource constraint, rather than an information encoding rate (Experiment 3). Second, in two experiments, I showed that the visual system could hold up to four ensemble representations, or up to four individual items (Experiment 4), and an ensemble representation had an information uncertainty (entropy) level similar to that of an individual representation (Experiment 5). Taken together, ensemble perception provides a compact and efficient way of information processing.

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There are 199 species at risk in British Columbia (B.C.). To elicit public support to conserve biodiversity, it is important to understand people’s attitudes and preferences toward species at risk. Here we examine how people perceive endangered species in B.C., how message framing shapes the attitudes toward the species, and whether implicit or explicit preferences determine willingness to pay for conservation. In Study 1 reported in Chapter 2, we presented three messages about sea otters to 623 residents in B.C., and measured the change in their attitudes toward sea otters using Kellert’s typology of basic attitudes toward wildlife. The messages were framed as either positive (as a keystone species), negative (resource conflict with First Nations’ fishermen in the West Coast of Vancouver Island), or neutral (biological facts). We found that the negative message promoted acceptance for managing sea otters and their habitats for use values (utilitarian-consumption, utilitarian-habitat), and for exerting control over sea otters (dominionistic). This shift in attitudes occurred even though the negative message was perceived as less convincing and believable than the positive or neutral messages. The positive message, on the other hand, decreased utilitarian-consumption attitudes. In Study 2 reported in Chapter 3, we evaluated people’s implicit and explicit preferences for four species at risk in B.C. (sea otter, American badger, caribou, and yellow-breasted chat). We found that explicit rather than implicit preference predicts willingness to pay for conservation of each species, and findings suggest that people apply the affect heuristic when judging species—species that are less liked may be perceived as riskier, and vice versa—. This finding holds for both residents in B.C. (n=55) and outside of B.C. (n=463). The results from the two studies highlight the importance of attitudes, messaging, and preference when designing conservation campaigns and efforts.

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