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Data Repository


This page shows all 352 data sets currently available in our Data repository

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Using exploratory graph analysis (EGA) in validating the structure of the Perth alexithymia questionnaire in Iranians with chronic pain
Authors:
Sheykhangafshe, F.B., Farahanui, H., WATSON, P.
Reference:
Frontiers in Psychology: Quantative Psychology and Measurement, 15, 3 July 2024
Year of publication:
2024
CBU number:
8993
Abstract:
Background: Chronic pain’s influence on emotional well-being can be significant. It may evoke feelings of despair, frustration, nervousness, and melancholy in individuals, which often manifest as reactions to enduring pain and disruptions in their daily lives. In this study, we seek to perform Bootstrap Exploratory Graph Analysis (EGA) on the Persian Version of the Perth Alexithymia Questionnaire (PAQ) in a cohort of people with chronic pain. Methods: The research concentrated on the population of individuals encountering chronic pain within Tehran province from 2022 to 2023. Ultimately, the analysis comprised information from 234 male participants (with a mean age of 30.59, SD = 6.84) and 307 female participants (with a mean age of 30.16, SD = 6.65). After data collection, statistical analysis was conducted using the EGAnet2.0.4 package in R.4.3.2 software. Results: The outcome of bootstrapped EGA unveiled a two-dimensional configuration of the PAQ comprising Factor 1 denoted as negative difficulty in describing and identifying feelings (N-DDIF) and Factor 2 characterized as general-externally orientated thinking (GEOT), representing robust structural integrity and item consistency (all items have stabilities > 0.70). Conclusion: These findings endorse the validity of the PAQ, as evidenced by its confirmation in a broader sample using a novel methodology consistent with existing literature on two-factor decentering models.
URL:
Data available, click to request
Unraveling symptom interplay: a network analysis of procrastination in gifted students
Authors:
Bagheri, S., Farahani, H., WATSON, P., Bezdan, T. and Rezaiean, K.
Reference:
BMC Psychology, 12:370
Year of publication:
2024
CBU number:
8992
Abstract:
Background This study explores the intricate web of symptoms experienced by academically gifted high school students, focusing on procrastination, rumination, perfectionism, and cognitive flexibility. The well-being of these gifted adolescents remains a pivotal concern, and understanding the dynamics of these symptoms is vital. Methods A diverse sample of 207 academically gifted high school students from Mashhad, Iran, participated in this study. Using convenience sampling, participants from grades 10, 11, and 12 were included, with detailed assessments conducted through questionnaires measuring the mentioned symptoms. Results Our network analysis uncovers compelling insights into the interplay of these symptoms: Procrastination, though moderately central, exerts significant influence within the network, underscoring its relevance. Cognitive flexibility, while centrally positioned, curiously exhibits a negative influence, potentially serving as a protective factor. Negative perfectionism emerges as the keystone symptom, with both high centrality and a positive influence. Rumination displays substantial centrality and a positive influence, indicating its role in symptom exacerbation. Positive perfectionism, moderately central, lacks direct influence on other symptoms. Conclusion This network analysis provides a nuanced understanding of the relationships among procrastination, rumination, perfectionism, and cognitive flexibility in academically gifted adolescents. Negative perfectionism and cognitive flexibility emerge as critical factors deserving attention in interventions aimed at enhancing the well-being of this unique group. Further research should explore causal relationships to refine targeted interventions.
URL:
Data available, click to request
Neural decoding of the speech envelope: Effects of intelligibility and spectral degradation
Authors:
DEIGHTON MACINTYRE, A., CARLYON, R.P., GOEHRING, T.
Reference:
Trends in Hearing
Year of publication:
In Press
CBU number:
8991
Abstract:
During continuous speech perception, endogenous neural activity becomes time-locked to acoustic stimulus features, such as the speech amplitude envelope. This speech-brain coupling can be decoded using non-invasive brain imaging techniques, including electroencephalography (EEG). Neural decoding may provide clinical use as an objective measure of stimulus encoding by the brain – for example during cochlear implant (CI) listening, wherein the speech signal is severely spectrally degraded. Yet, interplay between acoustic and linguistic factors may lead to top-down modulation of perception, thereby complicating audiological applications. To address this ambiguity, we assess neural decoding of the speech envelope under spectral degradation with EEG in acoustically hearing listeners (n = 38; 18-35 years old) using vocoded speech. We dissociate sensory encoding from higher-order processing by employing intelligible (English) and non-intelligible (Dutch) stimuli, with auditory attention sustained using a repeated-phrase detection task. Subject-specific and group decoders were trained to reconstruct the speech envelope from held-out EEG data, with decoder significance determined via random permutation testing. Whereas speech envelope reconstruction did not vary by spectral resolution, intelligible speech was associated with better decoding accuracy in general. Results were similar across subject-specific and group analyses, with less consistent effects of spectral degradation in group decoding. Permutation tests revealed possible differences in decoder statistical significance by experimental condition. In general, while robust neural decoding was observed at the individual and group level, variability within participants would most likely prevent the clinical use of such a measure to differentiate levels of spectral degradation and intelligibility on an individual basis. The data and acoustic stimuli that support the findings of this study are openly available at DOI 10.17605/OSF.IO/CZWJ9
Data for this project is held by an external institution. Please contact the authors to request a copy.
Mapping the multidimensional geometric landscape of graded phenotypic variation and progression in neurodegenerative syndromes
Authors:
RAMANAN, S., AKARCA, D., HENDERSON, S.K., ROUSE, M.A., Allinson, K., PATTERSON, K., ROWE, J.B., LAMBON RALPH, M.A.
Reference:
Brain
Year of publication:
2023
CBU number:
8990
Abstract:
Clinical variants of Alzheimer’s disease and frontotemporal lobar degeneration display a spectrum of cognitive-behavioural changes varying between individuals and over time. Understanding the landscape of these graded individual-/group-level longitudinal variations is critical for precise phenotyping; however, this remains challenging to model. Addressing this challenge, we leverage the National Alzheimer’s Coordinating Center database to derive a unified geometric framework of graded longitudinal phenotypic variation in Alzheimer’s disease and frontotemporal lobar degeneration. We included three time-point, cognitive-behavioural and clinical data from 390 typical, atypical and intermediate Alzheimer’s disease and frontotemporal lobar degeneration variants (114 typical Alzheimer’s disease; 107 behavioural variant frontotemporal dementia; 42 motor variants of frontotemporal lobar degeneration; and 103 primary progressive aphasia patients). On this data, we applied advanced data-science approaches to derive low-dimensional geometric spaces capturing core features underpinning clinical progression of Alzheimer’s disease and frontotemporal lobar degeneration syndromes. To do so, we first used principal component analysis to derive six axes of graded longitudinal phenotypic variation capturing patient-specific movement along and across these axes. Then, we distilled these axes into a visualisable 2D manifold of longitudinal phenotypic variation using Uniform Manifold Approximation and Projection. Both geometries together enabled the assimilation and inter-relation of paradigmatic and mixed cases, capturing dynamic individual trajectories, and linking syndromic variability to neuropathology and key clinical end-points such as survival. Through these low-dimensional geometries, we show that (i) specific syndromes (Alzheimer’s disease and primary progressive aphasia) converge over time into a de-differentiated pooled phenotype, while others (frontotemporal dementia variants) diverge to look different from this generic phenotype; (ii) phenotypic diversification is predicted by simultaneous progression along multiple axes, varying in a graded manner between individuals and syndromes; and (iii) movement along specific principal axes predicts survival at 36 months in a syndrome-specific manner and in individual pathological groupings. The resultant mapping of dynamics underlying cognitive-behavioural evolution potentially holds paradigm-changing implications to predicting phenotypic diversification and phenotype-neurobiological mapping in Alzheimer’s disease and frontotemporal lobar degeneration. The National Alzheimer’s Coordinating Center dataset are freely available through request on their official website (https://naccdata.org/). Code for all analyses from this study have been made available at: https://github.com/siddharthramanan/NACC_UMAP.
Data for this project is held by an external institution. Please contact the authors to request a copy.
Sensorimotor learning during synchronous speech is modulated by the acoustics of the other voice
Authors:
BRADSHAW, A.R., Wheeler, E.D., McGettigan, C., Lametti, D.R.
Reference:
Psychonomic Bulletin and Review
Year of publication:
In Press
CBU number:
8989
Abstract:
This study tested the hypothesis that speaking with other voices can influence sensorimotor predictions of one’s own voice. Real-time manipulations of auditory feedback were used to drive sensorimotor adaptation in speech, while participants spoke sentences in synchrony with another voice, a task known to induce implicit imitation (phonetic convergence). The acoustic-phonetic properties of the other voice were manipulated between-groups, such that convergence with it would either oppose (incongruent group, n = 15) or align with speech motor adaptation (congruent group, n = 16). As predicted, significantly greater adaptation was seen in the congruent compared to the incongruent group. This suggests the use of shared sensory targets in speech for predicting the sensory outcomes of both the actions of others (speech perception) and the actions of the self (speech production). This finding has important implications for wider theories of shared predictive mechanisms across perception and action, such as active inference. Data available at: https://osf.io/h26ur/
Data for this project is held by an external institution. Please contact the authors to request a copy.
External task switches activate default mode regions without enhanced processing of the surrounding scene
Authors:
ZHOU, A., DUNCAN, J., MITCHELL, D.
Reference:
Imaging Neuroscience
Year of publication:
In Press
CBU number:
8988
Abstract:
Default mode network (DMN) activity, measured with fMRI, typically increases during internally directed thought, and decreases during tasks that demand externally focused attention. However, Crittenden et al. (2015) and Smith et al. (2018) reported increased DMN activity during demanding external task switches between different cognitive domains, compared to within-domain switches and task repeats. This finding is hard to reconcile with many dominant views of DMN function. Here, we aimed to replicate this DMN task-switch effect in a similar paradigm and test whether it reflects increased representation of broader context, specifically of a scene presented behind the focal task. In the Core DMN, we found significant activity for all task switches, compared to task repeats, and stronger activity for switches between rest and task. Although the content of the background scene was attended, recalled, and neurally decodable, there was no evidence that this differed by switch type. Therefore, external task switches activated DMN without enhanced processing of the surrounding background. Surprisingly, DMN activity at within-domain switches was no less than at between-domain switches. We suggest that modulation of DMN activity by task switches reflects a shift in the current cognitive model and depends on the overall complexity of that model.
Data available, click to request
Auditory change detection and visual selective attention: Association between MMN and N2pc
Authors:
Kong, Y., Zhao, C., Li, D., Li, B., Hu, Y., Liu, H., WOOLGAR, A., Guo, J., Song, Y.
Reference:
Cerebral Cortex
Year of publication:
In Press
CBU number:
8984
Abstract:
While the auditory and visual systems each provide distinct information to our brain, they also work together to process and prioritize input to address ever-changing conditions. Previous studies highlighted the trade-off between auditory change detection and visual selective attention, however, the relationship between them is still unclear. Here, we recorded electroencephalography signals from 106 healthy adults in three experiments. Our findings revealed a positive correlation at the population level between the amplitudes of ERP indices associated with auditory change detection (MMN) and visual selective attention (N2pc) when elicited in separate tasks. This correlation persisted even when participants performed a visual task while disregarding simultaneous auditory stimuli. Interestingly, as visual attention demand increased, participants whose N2pc amplitude increased the most exhibited the largest reduction in MMN, suggesting a within-subject trade-off between the two processes. Taken together, our results suggest an intimate relationship and potential shared mechanism between auditory change detection and visual selective attention. We liken this to a total capacity limit that varies between individuals, which could drive correlated individual differences in auditory change detection and visual selective attention, and also within-subject competition between the two, with task-based modulation of visual attention causing within-participant decrease in auditory change detection sensitivity.
Data available, click to request
Overlapping effects of neuropsychiatric symptoms and circadian rhythm on effort-based decision-making
Authors:
MEHRHOF, S., NORD, C.
Reference:
eLife
Year of publication:
In Press
CBU number:
8982
Abstract:
Motivational deficits are common in several brain disorders and motivational syndromes like apathy and anhedonia predict worse outcomes. Disrupted effort- based decision-making may represent a neurobiological underpinning of motivational deficits, shared across neuropsychiatric disorders. We measured effort-based decision-making in 994 participants using a gamified online task, combined with computational modelling, and validated offline for test-retest reliability. In two pre-registered studies, we first replicated studies linking impaired effort-based decision-making to neuropsychiatric syndromes, taking both a transdiagnostic and a diagnostic-criteria approach. Next, testing participants with early and late circadian rhythms in the morning and evening, we find circadian rhythm interacts with time-of-testing to produce overlapping effects on effort-based decision-making. Circadian rhythm may be an important variable in computational psychiatry, decreasing reliability or distorting results when left unaccounted for. Disentangling effects of neuropsychiatric syndromes and circadian rhythm on effort-based decision-making will be essential to understand motivational pathologies and to develop tailored clinical interventions.
Data available, click to request
Does Theta Synchronicity of Sensory Information Enhance Associative Memory? Replicating the Theta-Induced Memory Effect
Authors:
SERIN, F., Wang, D., DAVIS, M.H., HENSON, R.
Reference:
Brain and Neuroscience Advances,8:23982128241255798
Year of publication:
2024
CBU number:
8981
Abstract:
The binding of information from different sensory or neural sources is critical for associative memory. Previous research in animals suggested that the timing of theta oscillations in the hippocampus is critical for long-term potentiation, which underlies associative and episodic memory. Studies with human participants showed correlations between theta oscillations in medial temporal lobe and episodic memory. Clouter et al. (2017) directly investigated this link by modulating the intensity of the luminance and the sound of the video clips so that they ‘flickered’ at certain frequencies and with varying synchronicity between the visual and auditory streams. Across several experiments, better memory was found for stimuli that flickered synchronously at theta frequency compared with no-flicker, asynchronous theta, or synchronous alpha and delta frequencies. This effect – which they called the Theta Induced Memory Effect (TIME) – is consistent with the importance of theta synchronicity for long-term potentiation. Additionally, electroencephalography (EEG) data showed entrainment of cortical regions to the visual and auditory flicker, and that synchronicity was achieved in neuronal oscillations (with a fixed delay between visual and auditory streams). The theoretical importance, large effect size, and potential application to enhance real-world memory mean that a replication of TIME would be highly valuable. The present study aimed to replicate the key differences among synchronous theta, asynchronous theta, synchronous delta and no-flicker conditions, but within a single experiment. The results do not show evidence of improved memory for theta synchronicity in any of the comparisons. We suggest a reinterpretation of TIME to accommodate this non-replication
URL:
Data available, click to request
Improved tactile speech robustness to background noise with a dual-path recurrent neural network noise-reduction method
Authors:
Fletcher, M.D., Perry, S.W., Thoidis, I., Verschuur, C.A., Goehring, T.
Reference:
Scientific Reports, 14(1):7357
Year of publication:
2024
CBU number:
8975
Abstract:
Many people with hearing loss struggle to understand speech in noisy environments, making noise robustness critical for hearing-assistive devices. Recently developed haptic hearing aids, which convert audio to vibration, can improve speech-in-noise performance for cochlear implant (CI) users and assist those unable to access hearing-assistive devices. They are typically body-worn rather than head-mounted, allowing additional space for batteries and microprocessors, and so can deploy more sophisticated noise-reduction techniques. The current study assessed whether a real-time-feasible dual-path recurrent neural network (DPRNN) can improve tactile speech-in-noise performance. Audio was converted to vibration on the wrist using a vocoder method, either with or without noise reduction. Performance was tested for speech in a multi-talker noise (recorded at a party) with a 2.5-dB signal-to-noise ratio. An objective assessment showed the DPRNN improved the scale-invariant signal-to-distortion ratio by 8.6 dB and substantially outperformed traditional noise-reduction (log-MMSE). A behavioural assessment in 16 participants showed the DPRNN improved tactile-only sentence identification in noise by 8.2%. This suggests that advanced techniques like the DPRNN could substantially improve outcomes with haptic hearing aids. Low-cost haptic devices could soon be an important supplement to hearing-assistive devices such as CIs or offer an alternative for people who cannot access CI technology.
URL:
Data available, click to request


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