Enes Avcu
Biographic Data
| ID | 9041444 |
|---|---|
| NAME | Enes Avcu |
| GIVEN NAMES | Enes |
| FAMILY NAME | Avcu |
| SIGNATURE | AVCU E |
| AFFILIATIONS | Harvard University |
| ORCID | 0000-0001-5372-1774 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Neural representation of phonological wordform in temporal cortex
While the neural bases of the earliest stages of speech categorization have been widely explored using neural decoding methods, there is still a lack of consensus on questions as basic as how wordforms are represented and in what way this word-level representation influences downstream processing in the brain. Isolating and localizing the neural representations of wordform is challenging because spoken words activate a variety of representations …
Neural evidence suggests phonological acceptability judgments reflect similarity, not constraint evaluation
Experimental linguistics
Unlearnable phonotactics
The Subregular Hypothesis (Heinz 2010) states that only patterns with specific subregular computational properties are phonologically learnable. Lai (2015) provided the initial laboratory support for this hypothesis. The current study aimed to replicate and extend the earlier findings by using a different experimental paradigm (oddball task) and a different measure of learning (sensitivity index, d′). Specifically, we compared the learnability of…
Neural Underpinnings of Phonotactic Rule Learning
This study used behavioral measures and ERP difference waves to measure the underlying brain processes during the categorization of grammatical vs ungrammatical stimuli according to a lab learned phonotactic rule. The results show that participants learned the simple rule at the behavioral level (as measured with d-prime, a sensitivity measure to rule violations). This rule learning is also reflected in the brain response to violations of the rul…
No prominent works on this page.
Neural Underpinnings of Phonotactic Rule Learning
This study used behavioral measures and ERP difference waves to measure the underlying brain processes during the categorization of grammatical vs ungrammatical stimuli according to a lab learned phonotactic rule. The results show that participants learned the simple rule at the behavioral level (as measured with d-prime, a sensitivity measure to rule violations). This rule learning is also reflected in the brain response to violations of the rul…
Unlearnable phonotactics
The Subregular Hypothesis (Heinz 2010) states that only patterns with specific subregular computational properties are phonologically learnable. Lai (2015) provided the initial laboratory support for this hypothesis. The current study aimed to replicate and extend the earlier findings by using a different experimental paradigm (oddball task) and a different measure of learning (sensitivity index, d′). Specifically, we compared the learnability of…
Experimental linguistics
Neural evidence suggests phonological acceptability judgments reflect similarity, not constraint evaluation
Neural representation of phonological wordform in temporal cortex
While the neural bases of the earliest stages of speech categorization have been widely explored using neural decoding methods, there is still a lack of consensus on questions as basic as how wordforms are represented and in what way this word-level representation influences downstream processing in the brain. Isolating and localizing the neural representations of wordform is challenging because spoken words activate a variety of representations …
Computer Science (5 works) · Psychology (5 works) · Artificial Intelligence (4 works) · Linguistics (4 works) · Neuroscience (4 works) · Categorization (3 works) · Neurobiology of Language and Bilingualism (3 works) · Phonology (3 works) · Cognition (2 works) · Cognitive psychology (2 works)