Our publication database contains 7791 publications dating back to 1943. You can browse some of the most recently added entries below, or you can:
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Recently Added Publications
Time-Lagged Multidimensional Pattern Connectivity (TL-MDPC): An EEG/MEG pattern transformation based functional connectivity metric.
Authors:
RAHIMI, S., Jackson, R., Farahibozorg, S.G., HAUK, O.
Reference:
Neuroimage, 270:119958
Year of publication:
2023
CBU number:
8904
Abstract:
Functional and effective connectivity methods are essential to study the complex information flow in brain networks underlying human cognition. Only recently have connectivity methods begun to emerge that make use of the full multidimensional information contained in patterns of brain activation, rather than unidimensional summary measures of these patterns. To date, these methods have mostly been applied to fMRI data, and no method allows vertex-to-vertex transformations with the temporal specificity of EEG/MEG data. Here, we introduce time-lagged multidimensional pattern connectivity (TL-MDPC) as a novel bivariate functional connectivity metric for EEG/MEG research. TL-MDPC estimates the vertex-to-vertex transformations among multiple brain regions and across different latency ranges. It determines how well patterns in ROI X at time point tx can linearly predict patterns of ROI Y at time point ty. In the present study, we use simulations to demonstrate TL-MDPC's increased sensitivity to multidimensional effects compared to a unidimensional approach across realistic choices of number of trials and signal-to-noise ratios. We applied TL-MDPC, as well as its unidimensional counterpart, to an existing dataset varying the depth of semantic processing of visually presented words by contrasting a semantic decision and a lexical decision task. TL-MDPC detected significant effects beginning very early on, and showed stronger task modulations than the unidimensional approach, suggesting that it is capable of capturing more information. With TL-MDPC only, we observed rich connectivity between core semantic representation (left and right anterior temporal lobes) and semantic control (inferior frontal gyrus and posterior temporal cortex) areas with greater semantic demands. TL-MDPC is a promising approach to identify multidimensional connectivity patterns, typically missed by unidimensional approaches.
URL:
Syndromes associated with frontotemporal lobar degeneration change response patterns on visual analogue scales
Authors:
WILLIAMS, R., Adams, N., HUGHES, L., ROUSE, M., Murley, A., Naessens, M., Street, D., Holland, N., ROWE, J.
Reference:
Scientific Reports
Year of publication:
In Press
CBU number:
8903
Abstract:
Self-report scales are widely used in cognitive neuroscience and psychology. However, they rest on the central assumption that respondents engage meaningfully. We hypothesise that this assumption does not hold for many patients, especially those with syndromes associated with frontotemporal lobar degeneration. In this study we investigated differences in response patterns on a visual analogue scale between people with frontotemporal degeneration and controls. We found that people with syndromes associated with frontotemporal lobar degeneration respond with more invariance and less internal consistency than controls, with Bayes Factors = 15.2 and 14.5 respectively indicating strong evidence for a group difference. There was also evidence that patient responses feature lower entropy. These results have important implications for the interpretation of self-report data in clinical populations. Meta-response markers related to response patterns, rather than the values reported on individual items, may be an informative addition to future research and clinical practise.
Adaptive coding of stimulus information in human frontoparietal cortex during visual classification
Authors:
Winiewski, D., Gonzalex-Garcia, C., Formica, S., Brass, M., WOOLGAR, A.
Reference:
NeuroImage, 274:120150
Year of publication:
2023
CBU number:
8902
Abstract:
The neural mechanisms of how frontal and parietal brain regions support flexible adaptation of behavior remain poorly understood. Here, we used functional magnetic resonance imaging (fMRI) and representational similarity analysis (RSA) to investigate frontoparietal representations of stimulus information during visual classification under varying task demands. Based on prior research, we predicted that increasing perceptual task difficulty should lead to adaptive changes in stimulus coding: task-relevant category information should be stronger, while task-irrelevant exemplar-level stimulus information should become weaker, reflecting a focus on the behaviorally relevant category information. Counter to our expectations, however, we found no evidence for adaptive changes in category coding. We did find weakened coding at the exemplar-level within categories however, demonstrating that task-irrelevant information is de-emphasized in frontoparietal cortex. These findings reveal adaptive coding of stimulus information at the exemplar-level, highlighting how frontoparietal regions might support behavior even under challenging conditions.
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Experiences of parents of children with rare neurogenetic conditions during the COVID-19 pandemic: an interpretative phenomenological analysis
Authors:
Robertson, K., Richards, C., Scerif, G., BAKER, K., Tye, C., MARTIN, J.
Reference:
BMC Psychology
Year of publication:
In Press
CBU number:
8901
Abstract:
Background
The Coronavirus disease 2019 (COVID-19) pandemic has impacted parental and child mental health and wellbeing in the UK. This study aimed to explore the experiences of parents of children with rare neurological and neurodevelopmental conditions with a known or suspected genetic cause (neurogenetic) across the first year of the pandemic in the UK.
Methods
Semi-structured interviews were conducted with 11 parents of children with rare neurogenetic conditions. Parents were recruited via opportunity sampling from the CoIN Study, a longitudinal quantitative study exploring the impact of the pandemic on the mental health and wellbeing of families with rare neurogenetic conditions. Interviews were analysed using Interpretative Phenomenological Analysis.
Results
Four main themes were identified: (1) “A varied impact on child wellbeing: from detrimental to ‘no big drama’”; (2) “Parental mental health and wellbeing: impact, changes and coping”; (3) “The world had shut its doors and that was that’: care and social services during the pandemic”; and (4) “Time and luck: abstract concepts central to parents’ perspectives of how they coped during the pandemic”. The majority of parents described experiencing an exacerbation of pre-pandemic challenges due to increased uncertainty and a lack of support, with a minority reporting positive effects of the pandemic on family wellbeing.
Conclusions
These findings offer a unique insight into the experiences parents of children with rare neurogenetic conditions across the first year of the pandemic in the UK. They highlight that the experiences of parents were not pandemic-specific, and will continue to be highly relevant in a non-pandemic context. Future support should to be tailored to the needs of families and implemented across diverse future scenarios to promote coping and positive wellbeing.
Perceptual Analysis of Speaker Embeddings for Voice Discrimination between Machine and Human Listening
Authors:
Thoidis, I., Gaultier, C., GEOHRING, T.
Reference:
IEEE International Conference on Acoustics, Speech and Signal Processing Proceedings, 04-10 June 2023
Year of publication:
2023
CBU number:
8900
Abstract:
This study investigates the information captured by speaker embeddings with relevance to human speech perception. A Convolutional Neural Network was trained to perform one-shot speaker verification under clean and noisy conditions, such that high-level abstractions of speaker-specific features were encoded in a latent embedding vector. We demonstrate that robust and discriminative speaker embed- dings can be obtained by using a training loss function that optimizes the embeddings for similarity scoring during inference. Computational analysis showed that such speaker embeddings predicted various hand-crafted acoustic features, while no single feature explained substantial variance of the embeddings. Moreover, the relative distances in the speaker embedding space moderately coincided with voice similarity, as inferred by human listeners. These findings confirm the overlap between machine and human listening when discriminating voices and motivate further research on the remaining disparities for improving model performance.
URL:
Towards Computational Neuroconstructivism: A Framework for Developmental Systems Neuroscience
Authors:
ASTLE, D., Johnson, M., AKARCA, D.
Reference:
Trends in Cognitive Sciences
Year of publication:
In Press
CBU number:
8899
Abstract:
Brain development is underpinned by complex interactions between neural assemblies, driving structural and functional change. This neuroconstructivism – the notion that neural functions are shaped by these interactions – is core to some developmental theories. However, due to their complexity, understanding underlying developmental mechanisms is challenging. Elsewhere in neurobiology, a computational revolution has shown that mathematical models of hidden biological mechanisms can bridge observations with theory building. Can we build a similar computational framework yielding mechanistic insights for brain development? We outline conceptual and technical challenges of addressing this theory gap, arguing there is great potential in specifying brain development as mathematically-defined processes operating within physical constraints. We provide examples, alongside broader ingredients needed, as the field explores computational explanations of system-wide development.
A core component of psychological therapy causes adaptive changes in computational learning mechanisms
Authors:
NORD, C., MEHHROF, S., SANDHU, T., HITCHCOCK, C., LAWSON, R.P., Pizzagalli, D., DALGLEISH, T., DERCON, Q.
Reference:
Psychological Medicine
Year of publication:
In Press
CBU number:
8898
Abstract:
Background: Cognitive distancing is an emotion regulation strategy commonly used in
psychological treatment of various mental health disorders, but its therapeutic mechanisms are unknown.
Methods: 935 participants completed an online reinforcement learning task involving choices between pairs of symbols with differing reward contingencies. Half (49.1%) of the sample was randomised to a cognitive self-distancing intervention and were trained to regulate or “take a step back” from their emotional response to feedback throughout. Established computational (Q-learning) models were then fit to individuals’ choices to derive reinforcement learning parameters capturing clarity of choice values (inverse temperature) and their sensitivity to positive and negative feedback (learning rates).
Results: Cognitive distancing improved task performance, including when participants were later tested on novel combinations of symbols without feedback. Group differences in computational model-derived parameters revealed that cognitive distancing resulted in clearer representations of option values (estimated 0.17 higher inverse temperatures). Simultaneously, distancing caused increased sensitivity to negative feedback (estimated 19% higher loss learning rates). Exploratory analyses suggested this resulted from an evolving shift in strategy by distanced participants: initially, choices were more determined by expected value differences between symbols, but as the task progressed, they became more sensitive to negative feedback, with evidence for a difference strongest by the end of training.
Conclusions: Adaptive effects on the computations that underlie learning from reward and loss may explain the therapeutic benefits of cognitive distancing. Over time and with practice, cognitive distancing may improve symptoms of mental health disorders by promoting more effective engagement with negative information.
Distance-dependent distribution thresholding in probabilistic tractography
Authors:
HALAI, A., CHANG, Y., LAMBON RALPH, M.
Reference:
Human Brain Mapping
Year of publication:
In Press
CBU number:
8897
Abstract:
Tractography is widely used in human studies of connectivity with respect to every brain region, function, and is explored developmentally, in adulthood, aging, and in disease. However, the core issue of how to systematically threshold, taking into account the inherent differences in connectivity values for different track lengths, and to do this in a comparable way across studies has not been solved. By utilising 54 healthy individuals’ diffusion-weighted image data taken from HCP, this study adopted Monte Carlo derived distance-dependent distributions (DDDs) to generate distance- dependent thresholds with various levels of alpha for connections of varying lengths. As a test case, we applied the DDD approach to generate a language connectome. The resulting connectome showed both short- and long-distance structural connectivity in the close and distant regions as expected for the dorsal and ventral language pathways, consistent with the literature. The finding demonstrates that the DDD approach is feasible to generate data-driven DDDs for common thresholding and can be used for both individual and group thresholding. Critically, it offers a standard method that can be applied to various probabilistic tracking datasets.
URL:
Dimensions of internalising symptoms are stable across early adolescence and predicted by executive functions: Longitudinal findings from the adolescent brain and cognitive development (ABCD) study
Authors:
VEDECHKINA, M., BENNETT, M., HOLMES, J.
Reference:
Development and Psychopathology
Year of publication:
In Press
CBU number:
8896
Abstract:
Early adolescence is characterised by rapid changes in executive function and increased vulnerability to internalising difficulties. The aim of this study was to explore whether internalising symptoms are stable across early adolescence and to identify possible links with executive function. Using data from the Adolescent Brain and Cognitive Development Study (ABCD), we identified four dimensions of internalising symptoms from item-level ratings on the Child Behavior Checklist (CBCL) at ages 10 (n=10,841) and 12 (n=5,846), with an invariant factor structure across time. These dimensions corresponded to anxiety, depression, withdrawal, and somatic problems. We then examined associations between these dimensions and three aspects of executive function at age 10 measured by the NIH Toolbox: inhibition, shifting and working memory. Worse shifting and inhibition at age 10 was associated with elevated symptoms of anxiety and withdrawal cross-sectionally, while poor inhibition was also uniquely associated with symptoms of depression. Longitudinal associations were more limited: Worse inhibition at age 10 predicted greater symptoms of withdrawal at age 12, while worse shifting predicted fewer symptoms of anxiety two years later. These findings suggest that poor executive function in early adolescence is associated with greater internalising difficulties and poor inhibition may contribute to later social withdrawal.
Developing and validating the Sexual Health Literacy Scale in an Iranian adult sample
Authors:
Rashidi, K., Farahani, H., Chesli, R.R., Abiri, F.A., WATSON, P.
Reference:
Humanities and Social Science Communication, 10(1):180
Year of publication:
2023
CBU number:
8895
Abstract:
Introduction: The literature has shown that sexual health literacy has limited applicability in many developing countries. The present study, therefore, aimed to develop and examine the validity and reliability of the Sexual Health Literacy Scale (SHLS) among a sample of 595 Iranian university students. Methods: The first analysis yielded themes obtained from a qualitative content analysis of the 118-item SHLS scale. Concepts were extracted using the method of latent content analysis (Bengtsson (2016)). 327 initial codes were extracted and main categories (Elo & Kyngäs, 2007) or themes (Graneheim & Lundman, 2004) obtained consisting of the information source, individual barriers, understanding and application, capacity and motivation, damage, skills, sexual rights and socio-cultural barriers. In the second analysis, the 595 students were randomly split into two groups. An exploratory factor analysis was conducted on the themes derived and quantified in Phase 1. 6 Factors were obtained and found to be consistent in both groups. Criterion-related validity of sexual health literacy was determined by stepwise multiple regression to predict marital satisfaction. The reliability of SHLS was also investigated. The third analysis examined the fit of the 6 factors obtained from the 595 students in the original sample to a new sample of 221 university students using cross-validation via confirmatory factor analysis. Results: We developed and validated a six-factor structure of the Sexual Health Literacy Scale 106 (SHLS-106): factor 1, Sexual Skills; factor 2, Individual Socio-cultural Barriers; factor 3, Sexual Vulnerability; factor 4, Resources to Access Sexual Information; factor 5, Understanding and Application; factor 6, Capacity and Motivation. SHLS-106 shows good test-retest reliability and criterion, incremental and convergent validities. Conclusions: This is the first study to examine the validity and reliability of the Sexual Health Literacy Scale in an Iranian sample. Considering the acceptable validity and reliability of this instrument, the psychometric properties of SHLS-106 need to be further investigated in diverse, more extended samples to clarify the extent of application of this scale in different settings. Policy Implications: SHLS-106 can effectively examine sexual health literacy, a dynamic scale in nature influenced by the individual, healthcare system, contextual and social factors in different cultures.
URL: