Dataset Information

A Difference of Past Self-Evaluation Between College Students With Low and High Socioeconomic Status: Evidence From Event-Related Potentials.

ABSTRACT: Socioeconomic status (SES) refers to the social position or class according to their material and non-material social resources. We conducted a study with 60 college students to explore whether SES affects past self-evaluation and used event-related potentials (ERPs) in a self-reference task that required participants to judge whether the trait adjectives (positive or negative) describing themselves 5 years ago were appropriate for them. Behavioral data showed that individuals' positive past self-evaluations were significantly higher than individuals' negative past self-evaluations, regardless of high or low SES. Individuals with high SES had significantly higher positive past self-evaluations than those with low SES. ERP data showed that in the low SES group, negative adjectives elicited a marginally greater N400 amplitude than positive adjectives; in the high SES group, negative adjectives elicited a greater late positive potential (LPP) amplitude than positive adjectives. N400 is an index of the accessibility of semantic processing, and a larger N400 amplitude reflects less fluent semantic processing. LPP is an index of continuous attention during late processing; the larger LPP amplitude is elicited, the more attention resources are invested. Our results indicated that compared with college students with low SES, the past self-evaluations of college students with high SES were more positive; college students with high SES paid more attention to negative adjectives. However, college students with low SES were marginally less fluent in processing negative adjectives.

SUBMITTER: Zang X

PROVIDER: S-EPMC8155721 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The goal of the present study was to investigate the interaction between different senses of polysemous nouns (metonymies and metaphors) and different meanings of homonyms using the method of event-related potentials (ERPs) and a priming paradigm. Participants read two-word phrases containing ambiguous words and made a sensicality judgment. Phrases with polysemes highlighted their literal sense and were preceded by primes with either the same or different - metonymic or metaphorical - sense. Similarly, phrases with homonyms were primed by phrases with a consistent or inconsistent meaning of the noun. The results demonstrated that polysemous phrases with literal senses preceded by metonymic primes did not differ in ERP responses from the control condition with the same literal primes. In contrast, processing phrases with the literal sense preceded by metaphorical primes resulted in N400 and P600 effects that might reflect a very limited priming effect. The priming effect observed between metonymic and literal senses supports the idea that these senses share a single representation in the mental lexicon. In contrast, the effects observed for polysemes with metaphorical primes characterize lexical access to the word's target sense and competition between the two word senses. The processing of homonyms preceded by the prime with an inconsistent meaning, although it did not elicit an N400 effect, was accompanied by a P600 effect as compared to the control condition with a consistent meaning of the prime. We suppose that the absence of the N400 effect may result from inhibition of the target meaning by the inconsistent prime, whereas the P600 response might reflect processes of reanalysis, activation, and integration of the target meaning. Our results provide additional evidence for the difference in processing mechanisms between metonymies and metaphors that might have separate representations in the mental lexicon, although they are more related as compared to homonyms.

Dataset Information

A Difference of Past Self-Evaluation Between College Students With Low and High Socioeconomic Status: Evidence From Event-Related Potentials.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets