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Computational complexity explains neural differences in quantifier verification
Heming Strømholt Bremnes1, Jakub Szymanik2, Giosuè Baggio1
1Language Acquisition and Language Processing Lab, Department of Language and Literature, Norwegian University of Science and Technology, Trondheim, Norway.
Cognition
|January 23, 2022
Summary
This study shows that verifying sentences with complex quantifiers like "most" triggers different brain responses than simpler ones like "all". These differences in electroencephalogram (EEG) signals during verification tasks highlight distinct cognitive processes.
Area of Science:
- Cognitive Science
- Neuroscience
- Linguistics
Background:
- Quantifiers in language have varying computational complexities.
- Proportional quantifiers ('most') are computationally more demanding than nonproportional quantifiers ('all', 'three').
- The cognitive mechanisms underlying sentence verification and comprehension may differ.
Purpose of the Study:
- To investigate if differing quantifier complexities influence electroencephalogram (ERP) responses during sentence verification.
- To determine if these ERP differences persist during sentence comprehension tasks.
- To explore the relationship between algorithmic complexity and neural processing in language.
Main Methods:
- Experiment 1 involved participants verifying the truth of sentences with different quantifiers against visual arrays.
- Experiment 2 used the same stimuli but required participants to answer comprehension questions.
- Event-related potentials (ERPs) were recorded throughout both experiments.
Main Results:
- A truth-value effect was observed, modulated by quantifier class, in sentence-final ERPs during verification.
- Proportional quantifiers elicited unique sentence-internal positive ERPs compared to nonproportional quantifiers.
- These quantifier-specific ERP effects vanished during the comprehension task in Experiment 2.
Conclusions:
- The observed ERP differences are specific to the sentence verification process, not general comprehension.
- Algorithmic complexity in language processing is reflected in distinct neural signatures.
- Human language processing adheres to formal computational constraints similar to abstract machines.
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