SCHWARZKOPF D. Samuel's profile
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SCHWARZKOPF D. SamuelORCID_LOGO

  • SamPenDu Lab, School of Optometry & Vision Science, University of Auckland, Auckland, New Zealand
  • Life Sciences, Social sciences
  • recommender

Recommendations:  4

Reviews:  0

Website sampendu.net
Areas of expertise
Sam's research uses psychophysics, functional MRI (in particular in combination with population receptive field analysis and similar encoding models), and occasional other neuroscience techniques to understand how perceptual processing works. How are sensory brain regions organised? What are the neural mechanisms through which we interpret the chaotic sensory input? How can those processes go awry in health and disease? In the broadest sense, his research seeks to better understand how the brain gives rise to our unique and subjective perception of the world around us. Originally trained as a neurophysiologist at Cardiff University (1999-2007), after completing his PhD Sam moved into the field of human neuroimaging and psychophysics (University of Birmingham, 2007-8; University College London, 2008-2018). Since 2017 he has been at the School of Optometry & Vision Science at the University of Auckland on the path to Kiwification. Website: sampendu.net Keywords: vision science, perception, illusions, population receptive fields, encoding models, psychophysics, fMRI, retinotopic mapping, sensory neuroscience

Recommendations:  4

04 Dec 2023
STAGE 1
toto

Cerebral laterality as assessed by functional transcranial Doppler ultrasound in left-and right-handers: A comparison between handwriting and writing using a smartphone

Does typing on a smartphone involve the same neural mechanisms as writing by hand?

Recommended by based on reviews by Todd Richards and Dorothy Bishop
Language production is associated with a distinct lateralised pattern of brain activation biased toward the left cerebral hemisphere. This also applies to writing. It has also been shown to be modulated by handedness, with less pronounced lateralisation in left-handers. However, in recent decades the use of handwriting has declined significantly while the use of smartphones has exploded. To date, no study has explored whether the same neural correlates of written language production found for handwriting also hold for typing on a smartphone.
 
In the current study, Samsouris et al. (2023) will use functional transcranial Doppler ultrasound (fTCD) to measure blood flow velocity within cerebral hemispheres to investigate this question. This technique is particularly suited for this purpose because it provides better control for the movement confounds associated with a writing task and the technical challenges of using a smart device than other neuroimaging techniques like fMRI or M/EEG. The authors hypothesise that there will be no difference in left cerebral lateralisation for handwriting and typing on a smartphone. They also expect to replicate previous findings of weaker lateralisation in left-handers in written language production when typing on a smartphone. To isolate the effect of written language production, both these conditions will be corrected for their corresponding motor component using control conditions without a linguistic component.
 
The Stage 1 manuscript was evaluated over 6 rounds of in-depth review by the recommender and two expert reviewers, before issuing in-principle acceptance.
 
URL to the preregistered Stage 1 protocol: https://osf.io/j7egz
 
Level of bias control achieved: Level 6. No part of the data or evidence that will be used to answer the research question yet exists and no part will be generated until after IPA.
 
List of eligible PCI RR-friendly journals:
 
References
 
1. Samsouris, C., Badcock, N. A., Vlachos, F., & Papadatou-Pastou, M. (2023). Cerebral laterality as assessed by functional transcranial Doppler ultrasound in left-and right-handers: A comparison between handwriting and writing using a smartphone. In principle acceptance of Version 7 by Peer Community in Registered Reports. https://osf.io/j7egz
27 Nov 2023
STAGE 1
toto

Cortical voice processing in Autism Spectrum Disorder

Is voice processing impacted in Autism Spectrum Disorder?

Recommended by and based on reviews by 2 anonymous reviewers
Vocal sounds, including both speech and non-speech sounds, have been found to activate the Superior Temporal Sulci and Gyri in comparison to non-vocal sounds. These regions, termed Temporal Voice Areas (TVAs), are considered to be involved in early voice processing and therefore critical for social interaction. TVA activation has been examined in Autism Spectrum Disorder (ASD) to determine if the characteristic difficulties in social communication and interaction are linked to an impaired early voice processing. Using functional magnetic resonance imaging (fMRI), one study found typical brain activation in TVAs for 15 out of 16 autistic participants (Schelinski et al., 2016), whereas another found atypical activation in 4 out of 5 autistic participants (Gervais et al., 2004).
 
Here, the inconsistencies in the previous literature propel Gautier et al. (2023) to examine brain activation of TVAs with a larger sample size (26 ASD and 26 non-ASD participants). Gautier et al. (2023) will present vocal sounds and non-vocal sounds to both groups of participants during fMRI and predict that fewer participants in the ASD group will show a preferential response to voices in TVAs compared to the non-ASD group. These results would suggest that symptoms of ASD interfere with early stages of social interaction, at the level of voice processing.
 
This Stage 1 manuscript was evaluated in an initial round by the co-recommenders and another two rounds of in-depth review by two expert reviewers. With these revisions, the recommenders judged that the manuscript met the Stage 1 criteria and awarded in-principle acceptance (IPA).
 
URL to the preregistered Stage 1 protocol: https://osf.io/538m4
 
Level of bias control achieved: Level 6. No part of the data or evidence that will be used to answer the research question yet exists and no part will be generated until after IPA.
 
List of eligible PCI RR-friendly journals:
 
 
References
 
1. Gautier, R., Houy-Durand, E., Barantin, L., Briend, F. & Latinus, M. (2023). Cortical voice processing in Autism Spectrum Disorder. In principle acceptance of Version 4 by Peer Community in Registered Reports. https://osf.io/538m4
15 Nov 2023
STAGE 1
toto

Somatosensory Response Changes During Illusory Finger Stretching

Neural responses to a finger-stretching illusion in human somatosensory cortex

Recommended by based on reviews by Harry Farmer, Alexandra Mitchell and Susanne Stoll
Chronic pain is a major cause of disability that can often poorly managed with pharmacological treatments. This has prompted the exploration of other interventions like resizing illusions of body parts in augmented reality. These illusions have shown promise in conditions like osteoarthritis and complex regional pain syndrome, but it remains unclear how they alter the neural representation of body parts in the brain. The study by Hansford and colleagues aims to investigate these mechanisms in healthy participants, using somatosensory steady state evoked potentials (SSEP) and self-report questionnaires.
 
The study will involve finger stretching in an augmented reality setup that allows the researchers to independently manipulate visual and tactical stimulation. Assuming that multisensory stimulation indeed produces a robust illusion, the researchers will quantify the somatosensory evoked potentials in multisensory, unisensory, and two non-illusion control conditions. The study will provide inights into the neural mechanisms of these illusions and lay the ground for future investigations of these processes as a potential treatment for chronic pain.
 
The manuscript was evaluated over seven rounds of in-depth review by the recommender and three expert reviewers. After substantial revisions, the recommender judged that the manuscript met the Stage 1 criteria and awarded in-principle acceptance (IPA).
 
URL to the preregistered Stage 1 protocol: https://osf.io/u6gsb
 
Level of bias control achieved: Level 6. No part of the data or evidence that will be used to answer the research question yet exists and no part will be generated until after IPA.
 
List of eligible PCI RR-friendly journals:
 

References
 
1. Hansford, K. J., Baker, D. H., McKenzie, K. J., & Preston, C. E. J. (2023). Somatosensory Response Changes During Illusory Finger Stretching. In principle acceptance of Version 7 by Peer Community in Registered Reports. https://osf.io/u6gsb
31 May 2023
STAGE 1
toto

Defacing biases in manual and automated quality assessments of structural MRI with MRIQC

The impact of removing facial features on quality measures of structural MRI scans

Recommended by based on reviews by Catherine Morgan and Cassandra Gould van Praag
Data sharing is perhaps the most fundamental step for increasing the transparency and reproducibility of scientific research. However, the goals of open science must be tempered by ethical considerations, protecting the privacy and safety of research participants. Bridging this gap causes challenges for many fields, such as human neuroimaging. Brain images, as measured with magnetic resonance imaging (MRI), are unique to the participant and therefore contain identifying information by definition. One way to mitigate the risk to participants arising from public data sharing has been "defacing" the MRI scans, i.e., literally removing the part of the image that contains the face and surrounding tissue, while preserving the brain structure. This procedure however also removes information that is not (or at least minimally) identifiable. It also remains unclear whether defacing the images affects image quality and thus the information necessary for addressing many research questions.
 
The current study by Provins et al. (2023) seeks to address this question. Leveraging a publicly available "IXI dataset" comprising hundreds of T1-weighted structural MRI scans, they will assess the effect of defacing on manual and automatic estimates of image quality. Specifically, the researchers will compare image quality ratings by experts for a subset of 185 images. They hypothesise that images in which facial features have been removed are typically assigned higher quality ratings. Moreover, using a full data set of 580 images, which have been obtained across three scanning sites, they will also test the impact defacing MRI scans has on automated quality measures obtained with MRIQC software. The results of this study should have important implications for open science policy and for designing the optimal procedures for sharing structural MRI data in an ethical way. For example, if the authors' hypothesis is confirmed, studies relying on MRI quality measures might be better served by a custodianship model where identifiable data is shared under strict conditions, rather than relying on publishing defaced data. More generally, the outcome of this study may have significant legal implications in many jurisdictions.
 
The Stage 1 manuscript was evaluated at the inital triage stage by the Recommender and PCI:RR team, and another round of in-depth review by two experts. After a detailed response and substantial revisions, the recommender judged the manuscript met the Stage 1 criteria and awarded in-principle acceptance (IPA).
 
URL to the preregistered Stage 1 protocol: https://osf.io/qcket (under temporary private embargo)
 
Level of bias control achieved: Level 2. At least some data/evidence that will be used to answer the research question has been accessed and partially observed by the authors, but the authors certify that they have not yet observed the key variables within the data that will be used to answer the research question AND they have taken additional steps to maximise bias control and rigour.
 
List of eligible PCI RR-friendly journals:
 
References
 
1. Provins, C., Savary, E., Alemán-Gómez, Y., Richiardi, J., Poldrack, R. A., Hagmann, P. & Esteban, O. (2023). Defacing biases in manual and automated quality assessments of structural MRI with MRIQC, in principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/qcket
avatar

SCHWARZKOPF D. SamuelORCID_LOGO

  • SamPenDu Lab, School of Optometry & Vision Science, University of Auckland, Auckland, New Zealand
  • Life Sciences, Social sciences
  • recommender

Recommendations:  4

Reviews:  0

Website sampendu.net
Areas of expertise
Sam's research uses psychophysics, functional MRI (in particular in combination with population receptive field analysis and similar encoding models), and occasional other neuroscience techniques to understand how perceptual processing works. How are sensory brain regions organised? What are the neural mechanisms through which we interpret the chaotic sensory input? How can those processes go awry in health and disease? In the broadest sense, his research seeks to better understand how the brain gives rise to our unique and subjective perception of the world around us. Originally trained as a neurophysiologist at Cardiff University (1999-2007), after completing his PhD Sam moved into the field of human neuroimaging and psychophysics (University of Birmingham, 2007-8; University College London, 2008-2018). Since 2017 he has been at the School of Optometry & Vision Science at the University of Auckland on the path to Kiwification. Website: sampendu.net Keywords: vision science, perception, illusions, population receptive fields, encoding models, psychophysics, fMRI, retinotopic mapping, sensory neuroscience