Streamlining experiment design in cognitive hearing science using OpenSesame

Sulas, Eleonora; Hasan, Pierre-Yves; Zhang, Yue; Patou, François

doi:10.3758/s13428-022-01886-5

Cited by 6 publications

(8 citation statements)

References 49 publications

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“…The study protocol was implemented via computer on the OpenSesame platform (Mathôt et al, 2012), using the features developed by Sulas et al (2022).…”

Section: Methodsmentioning

confidence: 99%

Phonological discrimination and contrast detection in pupillometry

Chiossi,

Patou,

et al. 2023

Front. Psychol.

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IntroductionThe perception of phonemes is guided by both low-level acoustic cues and high-level linguistic context. However, differentiating between these two types of processing can be challenging. In this study, we explore the utility of pupillometry as a tool to investigate both low- and high-level processing of phonological stimuli, with a particular focus on its ability to capture novelty detection and cognitive processing during speech perception.MethodsPupillometric traces were recorded from a sample of 22 Danish-speaking adults, with self-reported normal hearing, while performing two phonological-contrast perception tasks: a nonword discrimination task, which included minimal-pair combinations specific to the Danish language, and a nonword detection task involving the detection of phonologically modified words within sentences. The study explored the perception of contrasts in both unprocessed speech and degraded speech input, processed with a vocoder.ResultsNo difference in peak pupil dilation was observed when the contrast occurred between two isolated nonwords in the nonword discrimination task. For unprocessed speech, higher peak pupil dilations were measured when phonologically modified words were detected within a sentence compared to sentences without the nonwords. For vocoded speech, higher peak pupil dilation was observed for sentence stimuli, but not for the isolated nonwords, although performance decreased similarly for both tasks.ConclusionOur findings demonstrate the complexity of pupil dynamics in the presence of acoustic and phonological manipulation. Pupil responses seemed to reflect higher-level cognitive and lexical processing related to phonological perception rather than low-level perception of acoustic cues. However, the incorporation of multiple talkers in the stimuli, coupled with the relatively low task complexity, may have affected the pupil dilation.

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“…The study protocol was implemented via computer on the OpenSesame platform (Mathôt et al, 2012), using the features developed by Sulas et al (2022).…”

Section: Methodsmentioning

confidence: 99%

Phonological discrimination and contrast detection in pupillometry

Chiossi,

Patou,

et al. 2023

Front. Psychol.

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“…The luminance level was then kept stable throughout the recording to ensure no impact on pupil traces from non-task-evoked pupillary response (Zhang et al, 2022). The eye-tracker device was connected to a laptop and the pupil data was collected through customized Python scripts developed within the OMEXP research platform (Sulas et al, 2022).…”

Section: Concurrent Pupillometrymentioning

confidence: 99%

“…The spectro-temporal and neurocognitive tests were also performed using the OMEXP computer platform based on custommade and validated Python scripts (Sulas et al, 2022).…”

Section: Neurocognitive Functioningmentioning

confidence: 99%

Impact of SNR, peripheral auditory sensitivity, and central cognitive profile on the psychometric relation between pupillary response and speech performance in CI users

Zhang,

Callejón-Leblic,

Picazo-Reina

et al. 2023

Front. Neurosci.

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Despite substantial technical advances and wider clinical use, cochlear implant (CI) users continue to report high and elevated listening effort especially under challenging noisy conditions. Among all the objective measures to quantify listening effort, pupillometry is one of the most widely used and robust physiological measures. Previous studies with normally hearing (NH) and hearing-impaired (HI) listeners have shown that the relation between speech performance in noise and listening effort (as measured by peak pupil dilation) is not linear and exhibits an inverted-U shape. However, it is unclear whether the same psychometric relation exists in CI users, and whether individual differences in auditory sensitivity and central cognitive capacity affect this relation. Therefore, we recruited 17 post-lingually deaf CI adults to perform speech-in-noise tasks from 0 to 20 dB SNR with a 4 dB step size. Simultaneously, their pupillary responses and self-reported subjective effort were recorded. To characterize top-down and bottom-up individual variabilities, a spectro-temporal modulation task and a set of cognitive abilities were measured. Clinical word recognition in quiet and Quality of Life (QoL) were also collected. Results showed that at a group level, an inverted-U shape psychometric curve between task difficulty (SNR) and peak pupil dilation (PPD) was not observed. Individual shape of the psychometric curve was significantly associated with some individual factors: CI users with higher clinical word and speech-in-noise recognition showed a quadratic decrease of PPD over increasing SNRs; CI users with better non-verbal intelligence and lower QoL showed smaller average PPD. To summarize, individual differences in CI users had a significant impact on the psychometric relation between pupillary response and task difficulty, hence affecting the interpretation of pupillary response as listening effort (or engagement) at different task difficulty levels. Future research and clinical applications should further characterize the possible effects of individual factors (such as motivation or engagement) in modulating CI users’ occurrence of ‘tipping point’ on their psychometric functions, and develop an individualized method for reliably quantifying listening effort using pupillometry.

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“…However, once again, the tool requires substantial programming skills (i.e., JavaScript). More recently, Sulas et al (2022) developed a set of features for the opensource python-based OpenSesame platform that allows the creation of custom behavioral and cognitive hearing science tests. These features exploit the graphical interface of OpenSesame (Mathôt, Schreij & Theeuwes, 2012) and do not require programming skills (but mastering OpenSesame is of course necessary).…”

Section: Digital Tools For Auditory Testingmentioning

confidence: 99%

PSYCHOACOUSTICS-WEB: a free online tool for the estimation of basic auditory sensitivity thresholds

Grassi,

Felline,

Orlandi

et al. 2023

Preprint

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This paper presents PSYCHOACOUSTICS-WEB, an online tool written in javascript that enables the estimation of auditory sensory thresholds for a set of classic psychoacoustical tasks: frequency, intensity, and duration discrimination of pure tones; duration discrimination and gap detection of noises; amplitude modulation detection with noise carriers. The toolbox can be used through a common web browser (it works with fixed and mobile devices) and requires no programming skills. The toolbox was designed for two main types of users: an occasional user and, above all, an experimenter using the toolbox for his/her own research. This latter user can create a personal account, customise existing experiments and send them in the form of direct links to further users (e.g., the participants of a hypothetical experiment). Finally, because data storage is centralised, the toolbox offers the possibility to set the basis of a database of auditory skills.

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Streamlining experiment design in cognitive hearing science using OpenSesame

Cited by 6 publications

References 49 publications

Phonological discrimination and contrast detection in pupillometry

Phonological discrimination and contrast detection in pupillometry

Impact of SNR, peripheral auditory sensitivity, and central cognitive profile on the psychometric relation between pupillary response and speech performance in CI users

PSYCHOACOUSTICS-WEB: a free online tool for the estimation of basic auditory sensitivity thresholds

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