Seminar paper from the year 2019 in the subject Psychology - Cognition,
grade: 1,3, University of Wuppertal, language: English, abstract: In
order to retrieve information more efficiently and quickly, our central
nervous system makes use of implicit preactivation of associative neural
networks. In this study, 78 participants were instructed to identify a
sequence of word pairs consisting of either German words, nonwords or
pseudowords within a lexical decision task. The procedure was carried
out under three different conditions: a) no associations within a word
pair, b) connection through general second-level cooccurrences, and c)
connection through lemmatized second-level cooccurrences. The analysis
of variance revealed highly significant differences in reaction time and
error rate between lemmatized second-level cooccurrence compared to
general second-level cooccurrences. Both, error rate and reaction time,
were lower for lemmatized second-level cooccurrences. Stimuli consisting
of words with second-level association had a positive effect on the
reaction time and error rate. This could be proven due to a stimulus
onset asynchrony of 50ms, avoiding semantical competition that could
cause inhibitory effects on the reaction time. Linear regression also
revealed that lemmatized second-level cooccurrences had a greater
influence on the reaction time up to the target and the error rate
compared to general second-level cooccurrences. This information could
be used to improve models that explain the process of word recognition
by adding the influence of the lemmatized second-level cooccurrence.
