Assessing Task-dependent Flexibility and the Temporal Dynamics of Object Categorization
2020
- 310Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage310
- Downloads229
- Abstract Views81
Thesis / Dissertation Description
When we are presented with everyday objects, we inherently and effortlessly sort them into different categories. Nonetheless, the mechanisms by which this process occurs are not fully understood. There are three main tiers of categories into which the taxonomic tree can be separated: superordinate (e.g. mammal), basic (e.g. cat) and subordinate (e.g. Siamese cat). It is widely accepted that we most readily label objects at the basic level (Rosch et al., 1976). However, would this change if we were forced to attend to the features of a subordinate category? This study investigates the flexibility of assigning objects to the basic and subordinate categories as well as the neural time course of object classification. While recording EEG, participants indicated whether two successive images belong to either the same basic or subordinate category. They performed these tasks in two separate sessions alternating the taxonomic level. The EEG data obtained was analyzed through representational dissimilarity matrices (RDMs) creating a method of comparison for the neural responses of the electrodes at each time point to determine which category levels are most similar in terms of brain activity. We also used a multivariate regression approach to assess the magnitude of the relationship between neural data and the taxonomic level. We observed that the earliest neural responses seem optimized for basic-level categorization even when participants performed a different task. Therefore, these results emphasize the primacy of the basic level and provide further evidence for the automatic nature of object processing.
Bibliographic Details
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