scholarly journals Differential relational encoding of categorical information in memory for action events

2005 ◽  
Vol 33 (3) ◽  
pp. 371-379 ◽  
Author(s):  
Johannes Engelkamp ◽  
Kerstin H. Seiler ◽  
Hubert D. Zimmer
Keyword(s):  
Relational Encoding ◽  
Categorical Information

scholarly journals Age-related changes in prefrontal and hippocampal contributions to relational encoding

NeuroImage ◽  
2014 ◽  
Vol 84 ◽  
pp. 19-26 ◽  
Author(s):  
Donna Rose Addis ◽  
Kelly S. Giovanello ◽  
Mai-Anh Vu ◽  
Daniel L. Schacter
Keyword(s):  
Age Related ◽  
Relational Encoding ◽  
Age Related Changes

scholarly journals Positional priming of pop-out: A relational-encoding account

2010 ◽  
Vol 10 (2) ◽  
pp. 1-17 ◽  
Author(s):  
Thomas Geyer
Keyword(s):  
Relational Encoding

scholarly journals Similarity Search and Correlation-Based Exploratory Analysis in EHRs: A Case Study with COVID-19 Databases

2021 ◽  
Author(s):  
Mirela T. Cazzolato ◽  
Lucas S. Rodrigues ◽  
Marcela X. Ribeiro ◽  
Marco A. Gutierrez ◽  
Caetano Traina Jr. ◽  
...  
Keyword(s):  
Data Analysis ◽  
Similarity Search ◽  
Search Task ◽  
Exploratory Analysis ◽  
Strong Correlations ◽  
Health Records ◽  
Categorical Information ◽  
Exploratory Data ◽  
The Relationship

With the COVID-19 pandemic, many hospitals have collected Electronic Health Records (EHRs) from patients and shared them publicly. EHRs include heterogeneous attribute types, such as image exams, numerical, textual, and categorical information. Simply posing similarity queries over EHRs can underestimate the semantics and potential information of particular attributes and thus would be best supported by exploratory data analysis methods. Thus, we propose the Sketch method for comparing EHRs by similarity to provide a tool for a correlation-based exploratory analysis over different attributes. Sketch computes the overall data correlation considering the distance space of every attribute. Further, it employs both ANOVA and association rules with lift correlations to study the relationship between variables, allowing a deep data analysis. As a case study, we employed two open databases of COVID-19 cases, showing that specialists can benefit from the inference modules of Sketch to analyze EHRs. Sketch found strong correlations among tuples and attributes, with statistically significant results. The exploratory analysis has shown to complement the similarity search task, identifying and evaluating patterns discovered from heterogeneous attributes.

scholarly journals Conceptual distinctiveness does not improve visual working memory for objects but aids object-location binding

2021 ◽  
Author(s):  
Yuri Markov ◽  
Igor Utochkin
Keyword(s):  
Working Memory ◽  
Visual Working Memory ◽  
Competitive Interactions ◽  
Object Location ◽  
Location Information ◽  
Limited Capacity ◽  
Common Features ◽  
Categorical Information ◽  
Location Binding ◽  
Different Sources

Visual working memory (VWM) is prone to interference from stored items competing for its limited capacity. These competitive interactions can arise from different sources. For example, one such source is poor item distinctiveness causing a failure to discriminate between items sharing common features. Another source of interference is imperfect binding, a problem of determining which of the remembered features belonged to which object or which item was in which location. In two experiments, we studied how the conceptual distinctiveness of real-world objects (i.e., whether the objects belong to the same or different basic categories) affects VWM for objects and object-location binding. In Experiment 1, we found that distinctiveness did not affect memory for object identities or for locations, but low-distinctive objects were more frequently reported at “swapped” locations that originally went with different objects. In Experiment 2 we found evidence that the effect of distinctiveness on the object-location swaps was due to the use of categorical information for binding. In particular, we found that observers swapped the location of a tested object with another object from the same category more frequently than with any of the objects from another category. This suggests that observers can use some coarse category-location information when objects are conceptually distinct. Taken together, our findings suggest that object distinction and object-location binding act upon different components of VWM.

Item-specific and relational processing both improve recall accuracy in the DRM paradigm

2018 ◽  
Vol 72 (6) ◽  
pp. 1493-1506 ◽  
Author(s):  
Mark J Huff ◽  
Glen E Bodner
Keyword(s):  
Free Recall ◽  
False Recognition ◽  
Correct Recognition ◽  
Relational Processing ◽  
Drm Paradigm ◽  
Recall Accuracy ◽  
Relational Encoding ◽  
Task Difference

Using the Deese–Roediger–McDermott (DRM) paradigm, Huff and Bodner found that both item-specific and relational variants of a task improved correct recognition, but only the item-specific variants reduced false recognition, relative to a read-control condition. Here, we examined the outcome pattern when memory was tested using free recall, using the same item-specific versus relational task variants across three experiments as our previous study (processing instructions, pleasantness ratings, anagram generation). The outcome pattern in recall was similar to recognition, except relational processing at study actually reduced the DRM illusion, though not as much as item-specific processing. To reconcile this task difference, we suggest that the memory information laid down during relational encoding enhances the familiarity of the critical items at test. To the extent that familiarity is used less as a basis for responding in free recall than in recognition, relational processing ironically reduces rather than increases the DRM illusion in recall.

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