Comparison of single-word and adjective-noun phrase production using event-related brain potentials

Lange, Violaine Michel; Perret, Cyril; Laganaro, Marina

doi:10.1016/j.cortex.2015.02.017

Cited by 10 publications

(9 citation statements)

References 57 publications

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“…grand chat, "large cat") was primed by a phonologicallyrelated distractor word during picture-word interference; no effect was found when the second word in the phrase was primed. In an ERP study using picture naming, Lange et al (2015) found that response latencies were significantly longer for adjectival phrases than simple nouns. Thus, the evidence for the phonological encoding of noun phrases and compounds is mixed in distractor tasks.…”

Section: Multiword Utterances: Compounds and Phrasesmentioning

confidence: 99%

Compounds, phrases and clitics in connected speech

Wynne

Wheeldon

Lahiri

2018

Journal of Memory and Language

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Four language production experiments examine how English speakers plan compound words during phonological encoding. The experiments tested production latencies in both delayed and online tasks for English noun-noun compounds (e.g., daytime), adjective-noun phrases (e.g., dark time), and monomorphemic words (e.g., denim). In delayed production, speech onset latencies reflect the total number of prosodic units in the target sentence. In online production, speech latencies reflect the size of the first prosodic unit. Compounds are metrically similar to adjectivenoun phrases as they contain two lexical and two prosodic words. However, in Experiments 1 and 2, native English speakers treated the compounds as single prosodic units, indistinguishable from simple words, with RT data statistically different than that of the adjective-noun phrases. Experiments 3 and 4 demonstrate that compounds are also treated as single prosodic units in utterances containing clitics (e.g., dishcloths are clean) as they incorporate the verb into a single phonological word (i.e. dishcloths-are). Taken together, these results suggest that English compounds are planned as single recursive prosodic units. Our data require an adaptation of the classic model of phonological encoding to incorporate a distinction between lexical and postlexical prosodic processes, such that lexical boundaries have consequences for post-lexical phonological encoding.

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Section: Multiword Utterances: Compounds and Phrasesmentioning

confidence: 99%

Compounds, phrases and clitics in connected speech

Wynne

Wheeldon

Lahiri

2018

Journal of Memory and Language

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“…Moreover, a morpho-phonological representation has to be generated and maintained, which includes retrieving the appropriate morphemes and inflecting the adjectives (e.g., grote; morphological encoding), retrieving the phonemes and syllabifying them (phonological encoding), and accessing articulatory programs for the syllables (phonetic encoding), followed by the initiation of articulation (for "het grote blauwe oor"). These conceptual and linguistic processes and their time course have been extensively investigated in previous RT experiments (e.g., Meyer, 1996;Schriefers, 1992) and more recently in electrophysiological experiments (e.g., Bürki and Laganaro, 2014;Bürki et al, 2016;Eulitz et al, 2000;Michel Lange et al, 2015;Pylkkänen et al, 2014). However, none of these earlier studies examined influences of capacity demands on the P3 (i.e., analyses of the P3 were not reported), which was central to the present experiment.…”

Section: Discussionmentioning

confidence: 91%

P3 event-related brain potential reflects allocation and use of central processing capacity in language production

et al. 2017

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Allocation and use of central processing capacity have been associated with the P3 event-related brain potential amplitude in a large variety of non-linguistic tasks. However, little is known about the P3 in spoken language production. Moreover, the few studies that are available report opposing P3 effects when task complexity is manipulated. We investigated allocation and use of central processing capacity in a spoken phrase production task: Participants switched every second trial between describing pictures using noun phrases with one adjective (size only; simple condition, e.g., "the big desk") or two adjectives (size and color; complex condition, e.g., "the big red desk"). Capacity allocation was manipulated by complexity, and capacity use by switching. Response time (RT) was longer for complex than for simple trials. Moreover, complexity and switching interacted: RTs were longer on switch than on repeat trials for simple phrases but shorter on switch than on repeat trials for complex phrases. P3 amplitude increased with complexity. Moreover, complexity and switching interacted: The complexity effect was larger on the switch trials than on the repeat trials. These results provide evidence that the allocation and use of central processing capacity in language production are differentially reflected in the P3 amplitude.

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“…The output of “ tanova()” function is the series of p -values. We corrected the p -values by accepting the consecutive significant data points which are longer than 20 ms (Lange et al, 2015 ) using a command “ correct(method = ' cluster') .” Users can also use the other solutions for multiple comparisons correction such as FDR Benjamini-Hochberg (Benjamini and Hochberg, 1995 ) by replacing the value of parameter “method.”…”

Section: Examples and Resultsmentioning

confidence: 99%

“…Strategy 1 is used by many researchers (Murray et al, 2008 ; Brunet et al, 2011 ; Lange et al, 2015 ). However, it loses subject's information by mixing all subjects' data into one pool.…”

Section: Workflow and Methodsmentioning

confidence: 99%

Group-Level Multivariate Analysis in EasyEEG Toolbox: Examining the Temporal Dynamics Using Topographic Responses

2018

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Electroencephalography (EEG) provides high temporal resolution cognitive information from non-invasive recordings. However, one of the common practices–using a subset of sensors in ERP analysis is hard to provide a holistic and precise dynamic results. Selecting or grouping subsets of sensors may also be subject to selection bias, multiple comparison, and further complicated by individual differences in the group-level analysis. More importantly, changes in neural generators and variations in response magnitude from the same neural sources are difficult to separate, which limit the capacity of testing different aspects of cognitive hypotheses. We introduce EasyEEG, a toolbox that includes several multivariate analysis methods to directly test cognitive hypotheses based on topographic responses that include data from all sensors. These multivariate methods can investigate effects in the dimensions of response magnitude and topographic patterns separately using data in the sensor space, therefore enable assessing neural response dynamics. The concise workflow and the modular design provide user-friendly and programmer-friendly features. Users of all levels can benefit from the open-sourced, free EasyEEG to obtain a straightforward solution for efficient processing of EEG data and a complete pipeline from raw data to final results for publication.

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Comparison of single-word and adjective-noun phrase production using event-related brain potentials

Cited by 10 publications

References 57 publications

Compounds, phrases and clitics in connected speech

Compounds, phrases and clitics in connected speech

P3 event-related brain potential reflects allocation and use of central processing capacity in language production

Group-Level Multivariate Analysis in EasyEEG Toolbox: Examining the Temporal Dynamics Using Topographic Responses

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