Completeness out of incompleteness: Inferences from regularities in imperfect information ensembles.

Handling imperfect information problems is fundamental to perception, learning, and decision-making. Ensemble perception may partially overcome imperfect information by providing global clues. However, if not all cluster elements are readily accessible, the observations required for computing statistics are incomplete. In this case, these elements' internal correlations (i.e., regularity) could serve as clues to elucidate the missing pieces. We thus investigated spatial regularity's role in ensemble perception under imperfect information situations created using partially occluded stimuli. In two experiments, we manipulated circle size (Experiment 1) and line orientation (Experiment 2) to linearly vary with its location; spatial regularity thus supplied clues for inferring information of the invisible parts. Participants estimated the mean of the targeted feature of the entire cluster, including visible and invisible parts. We observed robust biases toward the overall cluster in the estimations, implying the invisible parts were considered during ensemble perception. We proposed this effect could be understood as assessing evidence from visible parts to construct the missing parts. Experiment 3 employed a periodicity regularity to deter participants from using specific strategies, and consistent results were found. We then developed a generative model, the Regularity-Based Model, to simulate the inference process, which better captured the pattern of human outcomes than the comparative model. These findings indicate the visual system could use high-level structural information to infer scenes with incomplete information, thus producing more accurate ensemble representations. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Two discoveries, one principle: Using a two-stage Bayesian model to explain a dissociated working memory distraction effect.

How working memory (WM) resists perceptual distraction with its limited capacity is a fundamental question to understand its mechanism. To address this question, we used a continuous recall paradigm to directly compare the distraction effect during encoding and the delay periods. Across Experiments 1-3, we observed a substantial distraction-related cost on mnemonic fidelity when distractors presented during the delay (delay-distraction condition), but not if they were introduced at encoding (encoding-distraction condition) or across both periods (full-distraction condition). However, the distraction cost revived when we increased the difficulty to distinguish distractors from targets (Experiments 4 and 4S) and when we changed distractors' relevant features during the delay (Experiment 5). We also found that the robust distraction cost in the delay-distraction condition did not occupy extra spatial resources (Experiments 6a and 6b). These results suggested a dissociated distraction effect, which could be related to the dynamic resource allocation across two WM periods. Here, we proposed a Bayesian model and considered the task relevance and visual uncertainty as two main factors that determine the resource allocation principle at two different stages. This model successfully captured the main findings across all behavioral experiments and performed better than other alternative models. Taken together, the current work advanced our understanding of the distraction resistance of WM under the framework of limited resource allocation. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Abdomen anatomic characteristics on CT scans as predictive markers for short-term complications following radical resection of colorectal cancer.

Background: Prediction and management of short-term postoperative complications in patients with colorectal cancer are essential in postoperative rehabilitation. Through CT scan images, we can easily measure some parameters of abdomen anatomic characteristics. This study aimed to assess whether there is a relationship between the abdomen anatomic characteristics and short-term postoperative complications. Materials and methods: We conducted a retrospective study. Eighty patients in each complication group and non-complication group were recruited with propensity score match. Demographics, perioperative laboratory results and surgical information were collected and compared between groups with univariate analysis. Significant elements were brought into subsequent logistic regression analysis and ROC analysis for further identification. Results: Univariate analysis showed that preoperative white blood cells, preoperative neutrophil counts, rectus abdominis thickness (RAT), subcutaneous fat thickness (SFT), and abdomen depth (AD) were significantly different between the complication group and non-complication group. Logistic regression analysis demonstrated that higher RAT (p = 0.002), SFT (p < 0.001) and AD (p < 0.001) independently predicted the incidence of short-term postoperative complications. Conclusions: In this study on patients undergoing radical resection of colorectal cancer, abdomen anatomic characteristics including higher RAT, SFT and AD are associated with an increased risk of short-term postoperative complications.

The ROCK Tool: A Novel Method for the Structural Exploration of Schemata.

Information stored in the human memory is organized in the form of mental schemata. In this paper we report on the Reproduction of Categorical Knowledge (ROCK) tool, a novel method for uncovering the structure of mental schemata of memorized information. The tool applies serial reproduction and hierarchical clustering to magnify memory bias and uncover inner configurations of fragmented information, using strength of association. We conducted behavioral experiments to test the validity of the tool. Experiment 1a demonstrated that the schematic structure of personality traits uncovered by the ROCK tool highly matched those described by the Big Five theory. This finding was replicated in Experiment 1b, focusing on a lower-level personality dimension extroversion with results aligned with personality theories. Experiment 2 assessed the ROCK tool using artificial stimuli with a pre-defined structure, created using a Markov chain model. Participants acquired the structure of the stimuli through an implicit learning procedure, and the ROCK tool was used to assess their level of recall. The results showed that the learned structure was identical to the designed structure of the stimuli. The results from both studies suggest that the ROCK tool could effectively reveal the structure of mental schemata.