Evidence map›Paper›PMID 27929337›Full record

ArticleJournal of experimental psychology. Learning, memory, and cognition2016

Where to look for American Sign Language (ASL) sublexical structure in the visual world: Reply to Salverda (2016).

Amy M Lieberman, Arielle Borovsky, Marla Hatrak, Rachel I Mayberry

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In one paragraph

Article in Journal of experimental psychology. Learning, memory, and cognition, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Amy M LiebermanSchool of Education, Boston University.
Arielle BorovskyDepartment of Psychology, Florida State University.
Marla HatrakDepartment of Linguistics, University of California, San Diego.
Rachel I MayberryDepartment of Linguistics, University of California, San Diego.

Funding

Age of Acquisition effects on sign language development and brain processingR01DC012797 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MAYBERRY, RACHEL I · 2013 to 2023
$6.3M
Development of Gaze Control for Integration of Language and Visual Information in Deaf ChildrenR01DC015272 · NIDCD · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI Amy M Lieberman · 2016 to 2026
$4.4M
Eye-gaze shift as a measure of sign language processing in young deaf childrenR03DC011615 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LIEBERMAN, AMY MICHELLE · 2011 to 2013
$457k
Online language processing and semantic development in late-talking infantsR03DC013638 · NIDCD · FLORIDA STATE UNIVERSITY · PI BOROVSKY, ARIELLE · 2015 to 2017
$439k
NIDCD NIH HHS R01 DC012797NIDCD NIH HHS R01 DC015272NIDCD NIH HHS R03 DC011615NIDCD NIH HHS R03 DC013638
6 · The paper itself

Abstract

In this reply to Salverda (2016), we address a critique of the claims made in our recent study of real-time processing of American Sign Language (ASL) signs using a novel visual world eye-tracking paradigm (Lieberman, Borovsky, Hatrak, & Mayberry, 2015). Salverda asserts that our data do not support our conclusion that native signers and late-learning signers show variable patterns of activation in the presence of phonological competitors. We provide a logical rationale for our study design and present a reanalysis of our data using a modified time window, providing additional evidence for our claim. We maintain that target fixation patterns provide an important window into real-time processing of sign language. We conclude that the use of eye-tracking methods to study real-time processing in a visually perceived language such as ASL is a promising avenue for further exploration. (PsycINFO Database Record

Indexed as

Sign LanguageTime PerceptionHumansLanguageLearningLinguisticsUnited States

Identifiers

PMID27929337
PMCPMC5152681

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.