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Adl Zarrabi A, Jeulin M, Bardet P, Commère P, Naccache L, Aucouturier JJ, Ponsot E, Villain M. A simple psychophysical procedure separates representational and noise components in impairments of speech prosody perception after right-hemisphere stroke. Sci Rep 2024; 14:15194. [PMID: 38956187 PMCID: PMC11219855 DOI: 10.1038/s41598-024-64295-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 06/06/2024] [Indexed: 07/04/2024] Open
Abstract
After a right hemisphere stroke, more than half of the patients are impaired in their capacity to produce or comprehend speech prosody. Yet, and despite its social-cognitive consequences for patients, aprosodia following stroke has received scant attention. In this report, we introduce a novel, simple psychophysical procedure which, by combining systematic digital manipulations of speech stimuli and reverse-correlation analysis, allows estimating the internal sensory representations that subtend how individual patients perceive speech prosody, and the level of internal noise that govern behavioral variability in how patients apply these representations. Tested on a sample of N = 22 right-hemisphere stroke survivors and N = 21 age-matched controls, the representation + noise model provides a promising alternative to the clinical gold standard for evaluating aprosodia (MEC): both parameters strongly associate with receptive, and not expressive, aprosodia measured by MEC within the patient group; they have better sensitivity than MEC for separating high-functioning patients from controls; and have good specificity with respect to non-prosody-related impairments of auditory attention and processing. Taken together, individual differences in either internal representation, internal noise, or both, paint a potent portrait of the variety of sensory/cognitive mechanisms that can explain impairments of prosody processing after stroke.
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Affiliation(s)
- Aynaz Adl Zarrabi
- Université de Franche-Comté, SUPMICROTECH, CNRS, Institut FEMTO-ST, 25000, Besançon, France
| | - Mélissa Jeulin
- Department of Physical Medicine & Rehabilitation, APHP/Hôpital Pitié-Salpêtrière, 75013, Paris, France
| | - Pauline Bardet
- Department of Physical Medicine & Rehabilitation, APHP/Hôpital Pitié-Salpêtrière, 75013, Paris, France
| | - Pauline Commère
- Department of Physical Medicine & Rehabilitation, APHP/Hôpital Pitié-Salpêtrière, 75013, Paris, France
| | - Lionel Naccache
- Department of Physical Medicine & Rehabilitation, APHP/Hôpital Pitié-Salpêtrière, 75013, Paris, France
- Paris Brain Institute (ICM), Inserm, CNRS, PICNIC-Lab, 75013, Paris, France
| | | | - Emmanuel Ponsot
- Science & Technology of Music and Sound, IRCAM/CNRS/Sorbonne Université, 75004, Paris, France
| | - Marie Villain
- Department of Physical Medicine & Rehabilitation, APHP/Hôpital Pitié-Salpêtrière, 75013, Paris, France.
- Paris Brain Institute (ICM), Inserm, CNRS, PICNIC-Lab, 75013, Paris, France.
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Guseva M, Bogler C, Allefeld C, Haynes JD. Instruction effects on randomness in sequence generation. Front Psychol 2023; 14:1113654. [PMID: 37034908 PMCID: PMC10075230 DOI: 10.3389/fpsyg.2023.1113654] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 02/20/2023] [Indexed: 04/11/2023] Open
Abstract
Randomness is a fundamental property of human behavior. It occurs both in the form of intrinsic random variability, say when repetitions of a task yield slightly different behavioral outcomes, or in the form of explicit randomness, say when a person tries to avoid being predicted in a game of rock, paper and scissors. Randomness has frequently been studied using random sequence generation tasks (RSG). A key finding has been that humans are poor at deliberately producing random behavior. At the same time, it has been shown that people might be better randomizers if randomness is only an implicit (rather than an explicit) requirement of the task. We therefore hypothesized that randomization performance might vary with the exact instructions with which randomness is elicited. To test this, we acquired data from a large online sample (n = 388), where every participant made 1,000 binary choices based on one of the following instructions: choose either randomly, freely, irregularly, according to an imaginary coin toss or perform a perceptual guessing task. Our results show significant differences in randomness between the conditions as quantified by conditional entropy and estimated Markov order. The randomization scores were highest in the conditions where people were asked to be irregular or mentally simulate a random event (coin toss) thus yielding recommendations for future studies on randomization behavior.
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Affiliation(s)
- Maja Guseva
- Bernstein Center for Computational Neuroscience, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Psychology, Humboldt Universität zu Berlin, Berlin, Germany
- *Correspondence: Maja Guseva,
| | - Carsten Bogler
- Bernstein Center for Computational Neuroscience, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Carsten Allefeld
- Department of Psychology, City University of London, London, United Kingdom
| | - John-Dylan Haynes
- Bernstein Center for Computational Neuroscience, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Psychology, City University of London, London, United Kingdom
- Berlin Center for Advanced Neuroimaging, Charité - Universitätsmedizin Berlin, Berlin, Germany
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Steinley D, Vilidaite G, Lygo FA, Smith AK, Flack TR, Gouws AD, Andrews TJ. Power contours: Optimising sample size and precision in experimental psychology and human neuroscience. Psychol Methods 2021; 26:295-314. [PMID: 32673043 PMCID: PMC8329985 DOI: 10.1037/met0000337] [Citation(s) in RCA: 100] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
When designing experimental studies with human participants, experimenters must decide how many trials each participant will complete, as well as how many participants to test. Most discussion of statistical power (the ability of a study design to detect an effect) has focused on sample size, and assumed sufficient trials. Here we explore the influence of both factors on statistical power, represented as a 2-dimensional plot on which iso-power contours can be visualized. We demonstrate the conditions under which the number of trials is particularly important, that is, when the within-participant variance is large relative to the between-participants variance. We then derive power contour plots using existing data sets for 8 experimental paradigms and methodologies (including reaction times, sensory thresholds, fMRI, MEG, and EEG), and provide example code to calculate estimates of the within- and between-participants variance for each method. In all cases, the within-participant variance was larger than the between-participants variance, meaning that the number of trials has a meaningful influence on statistical power in commonly used paradigms. An online tool is provided (https://shiny.york.ac.uk/powercontours/) for generating power contours, from which the optimal combination of trials and participants can be calculated when designing future studies. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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Baker DH, Richard B. Dynamic properties of internal noise probed by modulating binocular rivalry. PLoS Comput Biol 2019; 15:e1007071. [PMID: 31170150 PMCID: PMC6553697 DOI: 10.1371/journal.pcbi.1007071] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Accepted: 05/07/2019] [Indexed: 11/29/2022] Open
Abstract
Neural systems are inherently noisy, and this noise can affect our perception from moment to moment. This is particularly apparent in binocular rivalry, where perception of competing stimuli shown to the left and right eyes alternates over time. We modulated rivalling stimuli using dynamic sequences of external noise of various rates and amplitudes. We repeated each external noise sequence twice, and assessed the consistency of percepts across repetitions. External noise modulations of sufficiently high contrast increased consistency scores above baseline, and were most effective at 1/8Hz. A computational model of rivalry in which internal noise has a 1/f (pink) temporal amplitude spectrum, and a standard deviation of 16% contrast, provided the best account of our data. Our novel technique provides detailed estimates of the dynamic properties of internal noise during binocular rivalry, and by extension the stochastic processes that drive our perception and other types of spontaneous brain activity. Although our perception of the world appears constant, sensory representations are variable because of the ‘noisy’ nature of biological neurons. Here we used a binocular rivalry paradigm, in which conflicting images are shown to the two eyes, to probe the properties of this internal variability. Using a novel paradigm in which the contrasts of rivalling stimuli are modulated by two independent external noise streams, we infer the amplitude and character of this internal noise. The temporal amplitude spectrum of the noise has a 1/f spectrum, similar to that of natural visual input, and consistent with the idea that the visual system evolved to match its environment.
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Affiliation(s)
- Daniel H. Baker
- Department of Psychology, University of York, Heslington, York, United Kingdom
- York Biomedical Research Institute, University of York, Heslington, York, United Kingdom
- * E-mail:
| | - Bruno Richard
- Department of Psychology, University of York, Heslington, York, United Kingdom
- Department of Mathematics and Computer Science, Rutgers University–Newark, Newark, New Jersey, United States of America
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