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Data Repository


This page shows all 176 data sets currently available in our Data repository

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Reverse-Engineering the Cortical Architecture for Controlled Semantic Cognition
Authors:
JACKSON, R.L., Rogers, T.T., LAMBON RALPH, M.A.
Reference:
Nature Human Behaviour
Year of publication:
In Press
CBU number:
8595
Abstract:
We employ a ‘reverse-engineering’ approach to illuminate the neurocomputational building blocks that combine to support controlled semantic cognition: the storage and context-appropriate use of conceptual knowledge. By systematically varying the structure of a computational model and assessing the functional consequences, we identified the architectural properties that best promote some core functions of the semantic system. Semantic cognition presents a challenging test case as the brain must achieve two seemingly contradictory functions: abstracting context-invariant conceptual representations across time and modalities, whilst producing specific context-sensitive behaviours appropriate for the immediate task. These functions were best achieved in models possessing a single, deep multimodal hub with sparse connections from modality-specific regions, and control systems acting on peripheral rather than deep network layers. The reverse-engineered model provides a unifying account of core findings in the cognitive neuroscience of controlled semantic cognition, including evidence from anatomy, neuropsychology, and functional brain imaging.
Data available, click to request
Roles of the default mode and multiple-demand networks in naturalistic versus symbolic decisions
Authors:
SMITH, V., DUNCAN, J.D., MITCHELL, D.
Reference:
Journal of Neuroscience
Year of publication:
In Press
CBU number:
8593
Abstract:
The default mode network (DMN) is often associated with representing semantic, social and situational content of contexts and episodes. The DMN may therefore be important for contextual decision-making, through representing situational constraints and simulating common courses of events. Most decision-making paradigms, however, use symbolic stimuli and instead implicate cognitive control regions such as the multiple demand (MD) system. This fMRI study aimed to contrast the brain mechanisms underlying decision-making based on rich naturalistic contexts or symbolic cues. Whilst performing an ongoing task, 40 human participants (25 female) responded to different sounds. For one sound, the stimulus-response mapping was fixed; responses for the other sounds depended on the visual context: either lifelike scenes or letter symbols, varying across participants. Despite minimal behavioural differences between the groups, posterior DMN regions showed increased activity during context-dependent decision-making using the naturalistic scenes only, compared to symbolic cues. More anterior temporal and frontal DMN regions showed a different pattern, with sensitivity to the need for contextual control, but not to the type of context. Furthermore, in the scenes group, widespread DMN regions showed stronger representation of not just the context but also the sound whose significance it modulated. In comparison, the MD system showed strong univariate activity for every decision, but, intriguingly, somewhat reduced activity in the case of a scene-based but demanding context-dependent decisions. Depending on context, we suggest, either DMN or MD regions may play a prominent role in selection and control of appropriate behaviour.
Data available, click to request
Subjective SES is associated with children’s neurophysiological response to auditory oddballs
Authors:
ANWYL-IRVINE, A., DALMAIJER, E.S., Quinn, A., Johnson, A. and ASTLE, D.E.
Reference:
Cerebral Cortex Communications
Year of publication:
In Press
CBU number:
8591
Abstract:
Language and reading acquisition are strongly associated with a child’s socioeconomic environment (SES). There are a number of potential explanations for this relationship. We explore one potential explanation – a child’s SES is associated with how children discriminate word-like sounds (i.e. phonological processing), a foundational skill for reading acquisition. Magnetoencephalography data from a sample of 71 children (aged 6 years 11 months – 12 years 3 months), during a passive auditory oddball task containing word and non-word deviants, were used to test where (which sensors) and when (at what time) any association may occur. We also investigated associations between cognition, education, and this neurophysiological response. We report differences in the neural processing of word and non-word deviant tones at an early N200 component (likely representing early sensory processing) and a later P300 component (likely representing attentional and/or semantic processing). More interestingly we found Parental Subjective SES (the parents rating of their own relative affluence) was convincingly associated with later responses, but there were no significant associations with equivalised income. This suggests that the socioeconomic environment as rated by their parents, is associated with underlying phonological detection skills. Furthermore, this correlation likely occurs at a later time-point in information processing, associated with semantic and attentional processes. In contrast, household income is not significantly associated with these skills. One possibility is that the subjective assessment of SES is more impactful on neural mechanisms of phonological processing than the less complex and more objective measure of household income.
Data available, click to request
Gene functional networks and autism spectrum characteristics in young people with intellectual disability: a dimensional phenotyping study
Authors:
BAKER, K., BRKIC, D, Ng-Cordell, E., O’BRIEN, S., Scerif, G., ASTLE, D.
Reference:
Molecular Autism
Year of publication:
In Press
CBU number:
8589
Abstract:
Background The relationships between specific genetic aetiology and phenotype in neurodevelopmental disorders are complex and hotly contested. Genes associated with Intellectual disability (ID) can be grouped into networks according to gene function. This study explored whether individuals with ID show differences in autism spectrum characteristics (ASC), depending on the functional network membership of their rare, pathogenic de novo genetic variants. Methods Children and young people with ID of known genetic origin were allocated to two broad functional network groups: synaptic physiology (n=29) or chromatin regulation (n=23). We applied principle components analysis to the Social Responsiveness Scale to map the structure of ASC in this population, and identified three components – Inflexibility, Social Understanding and Social Motivation. We then used Akaike Information Criterion (AIC) to test the best fitting models for predicting ASC components, including demographic factors (age, gender), non-ASC behavioural factors (global adaptive function, anxiety, hyperactivity, inattention) and gene functional networks. Results We found that, when other factors are accounted for, the chromatin regulation group showed higher levels of Inflexibility. We also observed contrasting predictors of ASC within each network group. Within the chromatin regulation group, Social Understanding was associated with inattention, and Social Motivation was predicted by hyperactivity. Within the synaptic group, Social Understanding was associated with hyperactivity, and Social Motivation was linked to anxiety. Limitations Functional network definitions were manually curated based on multiple sources of evidence, but a data-driven approach to classification may be more robust. Sample sizes for rare genetic diagnoses remain small, mitigated by our network-based approach to group comparisons. This is a cross-sectional study across a wide age range, and longitudinal data within focused age groups will be informative of developmental trajectories across network groups. Conclusion We report that gene functional networks can predict Inflexibility, but not other ASC dimensions. Contrasting behavioural associations within each group suggests network-specific developmental pathways from genomic variation to autism. Simple classification of neurodevelopmental disorder genes as high risk or low risk for autism is unlikely to be valid or useful.
Data available, click to request
Relationship between sensitivity to temporal fine structure and spoken language abilities in children with mild-to-moderate sensorineural hearing loss
Authors:
HALLIDAY, L., Cabrera
Reference:
Journal of the Acoustical Society of America
Year of publication:
2020
CBU number:
8588
Abstract:
Children with sensorineural hearing loss show considerable variability in spoken language outcomes. We tested whether specific deficits in supra-threshold auditory perception might contribute to this variability. In a previous study [Halliday, Rosen, Tuomainen, & Calcus, (2019), J. Acoust. Soc. Am, 146, 4299], children with mild-to-moderate sensorineural hearing loss (MMHL) were shown to perform more poorly than normally hearing (NH) controls on measures designed to assess sensitivity to the temporal fine structure (TFS, the rapid oscillations in the amplitude of narrowband signals over short time intervals). However, they performed within normal limits on measures assessing sensitivity to the envelope (E; the slow fluctuations in the overall amplitude). Here, individual differences in unaided sensitivity to TFS accounted for significant variance in the spoken language abilities of children with MMHL, after controlling for nonverbal IQ, family history of language difficulties, and hearing loss severity. Aided sensitivity to TFS and E cues was equally important for children with MMHL, whereas for children with NH, E cues were more important. These findings suggest that deficits in TFS perception may contribute to the variability in spoken language outcomes in children with sensorineural hearing loss.
URL:
Data available, click to request
Pitch perception at very high frequencies: On psychometric functions and integration of frequency information
Authors:
Gockel, H., Moore, B.J., CARLYON, R.P.
Reference:
The Journal of the Acoustical Society of America, 148, 3322
Year of publication:
2020
CBU number:
8586
Abstract:
Lau et al. [Lau, Mehta, and Oxenham (2017), J. Neuroscience, 37, 9013-9021] showed that discrimination of the fundamental frequency (F0) of complex tones with components in a high frequency region was better than predicted from the optimal combination of information from the individual harmonics. The predictions depend on the assumption that psychometric functions for frequency discrimination have a slope of 1 at high frequencies. This was tested by measuring psychometric functions for F0 discrimination and frequency discrimination. Difference limens for F0 (F0DLs) and difference limens for frequency (FDLs) for each frequency component were also measured. Complex tones contained harmonics 6-10 and had F0s of 280 or 1400 Hz. Thresholds were measured using 210-ms tones presented diotically in diotic threshold-equalizing noise (TEN) and 1000-ms tones presented diotically in dichotic TEN. The slopes of the psychometric functions were close to 1 for all frequencies and F0s. The ratio of predicted to observed F0DLs was around 1 or smaller for both F0s, i.e. not super-optimal, and was significantly smaller for the low than for the high F0. The results are consistent with the idea that place information alone can convey pitch, but pitch is more salient when phase-locking information is available.
Data available, click to request
A causal role for gastric rhythm in human disgust avoidance
Authors:
NORD, C.L., DALMAIJER, E., Armstrong, T., BAKER, K., DALGLEISH, T.
Reference:
Current Biology
Year of publication:
In Press
CBU number:
8579
Data available, click to request
Human Cognitive Neuroscience As It Is Taught
Authors:
HAUK, O.
Reference:
Frontiers in Psychology, section Educational Psychology
Year of publication:
In Press
CBU number:
8578
Abstract:
Cognitive neuroscience increasingly relies on complex data analysis methods. Researchers in this field come from highly diverse scientific backgrounds, such as psychology, engineering and medicine. This poses challenges with respect to acquisition of appropriate scientific computing and data analysis skills, as well as communication among researchers with different knowledge and skills sets. Are researchers in cognitive neuroscience adequately equipped to address these challenges? Here, we present evidence from an online survey of methods skills. Respondents (n=307) mainly comprised students and post-doctoral researchers working in the cognitive neurosciences. Multiple choice questions addressed a variety of basic and fundamental aspects of neuroimaging data analysis, such as signal analysis, linear algebra, and statistics. We analysed performance with respect to the following factors: undergraduate degree (grouped into Psychology, Methods, Biology), current researcher status (undergraduate student, PhD student, post-doctoral researcher), gender, and self-rated expertise levels. Overall accuracy was 72%. Not surprisingly, the Methods group performed best (87%), followed by Biology (73%) and Psychology (66%). Accuracy increased from undergraduate (59%) to PhD (74%) level, but not from PhD to post-doctoral (74%) level. The difference in performance for the Methods versus non-methods (Psychology/Biology) groups was especially striking for questions related to signal analysis and linear algebra, two areas particularly relevant to neuroimaging research. Self-rated methods expertise was not strongly predictive of performance. The majority of respondents (93%) indicated they would like to receive at least some additional training on the topics covered in this survey. In conclusion, methods skills among junior researchers in cognitive neuroscience can be improved, researchers are aware of this, and there is strong demand for more skills-oriented training opportunities. We hope that this survey will provide an empirical basis for the development of bespoke skills-oriented training programmes in cognitive neuroscience institutions. We will provide practical suggestions on how to achieve this.
Data available, click to request
Proof-of-concept for the autobiographical Memory Flexibility (MemFlex) intervention for Posttraumatic Stress Disorder
Authors:
Moradi, A.R., Piltan, M., Choobin, M.H., Azadfallah, P., WATSON, P., DALGLEISH, T., HITCHCOCK, C.
Reference:
Clinical Psychological Science
Year of publication:
In Press
CBU number:
8577
Data available, click to request
Characterising group-level brain connectivity: a framework using Bayesian exponential random graph models
Authors:
Lehmann, B.C.L., HENSON, R.N., Geerligs, L., Cam-CAN, and White, S.R.
Reference:
NeuroImage
Year of publication:
In Press
CBU number:
8576
Abstract:
The brain can be modelled as a network with nodes and edges derived from a range of imaging modalities: the nodes correspond to spatially distinct regions and the edges to the interactions between them. Whole-brain connectivity studies typically seek to determine how network properties change with a given categorical phenotype such as age-group, disease condition or mental state. To do so reliably, it is necessary to determine the features of the connectivity structure that are common across a group of brain scans. Given the complex interdependencies inherent in network data, this is not a straightforward task. Some studies construct a group-representative network (GRN), ignoring individual differences, while other studies analyse networks for each individual independently, ignoring information that is shared across individuals. We propose a Bayesian framework based on exponential random graph models (ERGM) extended to multiple networks to characterise the distribution of an entire population of networks. Using resting-state fMRI data from the Cam-CAN project, a study on healthy ageing, we demonstrate how our method can be used to characterise and compare the brain’s functional connectivity structure across a group of young individuals and a group of old individuals.
URL:
Data available, click to request


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