Authors:

MITCHELL, D., ASSEM, M., WOOLGAR, A.

Reference:

Year of publication:

2025

CBU number:

9207

Abstract:

Throughout his distinguished career, John Duncan has made numerous influential contributions to understanding the behavioural and brain basis of attention and intelligence. Recognition of John’s work has included the 2012 Heineken Prize in Cognitive Science, and Fellowships of both the Royal Society and the British Academy. At his recent festschrift, John was fittingly described, amongst other superlatives, as “the most complete scientist.” To mark John’s retirement, this special issue brings together a collection of reviews, perspectives, and new research, inspired by John’s work and insights, to celebrate his immense and enduring contributions. See https://osf.io/37kzu for data and analysis scripts

URL:

Data for this project is available at: Https://osf.io/37kzu

Authors:

Rahimi, S., Jackson, R.L., HAUK. O.

Reference:

Year of publication:

2025

CBU number:

9205

Abstract:

Introduction: Investigating task- and stimulus-dependent connectivity is key to understanding how the interactions between brain regions underpin complex cognitive processes. Yet, the connections identified depend on the assumptions of the connectivity method. To date, methods designed for time-resolved electroencephalography/magnetoencephalography (EEG/MEG) data typically reduce signals in regions to one time course per region. This may fail to identify critical relationships between activation patterns across regions. Time-Lagged Multidimensional Pattern Connectivity (TL-MDPC) is a promising new EEG/MEG functional connectivity method improving previous approaches by assessing multidimensional relationships between patterns of brain activity. However, TL-MDPC remains linear and may therefore miss nonlinear interactions among brain areas. Methods: Thus, we introduce Nonlinear TL-MDPC (nTL-MDPC), a novel bivariate functional connectivity method for event-related EEG/MEG applications, and compare its performance to the original linear TL-MDPC. nTL-MDPC describes how well patterns in ROI X at a time point tx can predict patterns of ROI Y at a time point ty using artificial neural networks. Results: Applying this method and its linear counterpart to simulated data demonstrates that both can identify nonlinear dependencies, with nTL-MDPC achieving up to ~0.75 explained variance under optimal conditions (e.g., high SNR), compared to ~0.65 with TL-MDPC. However, with a sufficient number of trials- e.g., a trials-to-vertex ratio ≥10:1 – nTL-MDPC achieves up to 15% higher explained variance than the linear method. Nevertheless, application to a real EEG/MEG dataset demonstrated only subtle increases in nonlinear connectivity strength at longer time lags with no significant differences between the two approaches. Discussion: Overall, this suggests that linear multidimensional methods may be a reasonable practical choice to approximate brain connectivity, given the additional computational demands of nonlinear methods.

URL:

Data for this project is available at: https://github.com/setareh10/Method-Development-MDPC

Authors:

LU, R., POLLITT, E., WOOLGAR, A.

Reference:

Year of publication:

2025

CBU number:

9202

Abstract:

Alpha oscillations are thought to play a key role in visuospatial attention, particularly through lateralisation mechanisms. However, whether this function is driven purely by oscillatory activity or also involves aperiodic neural components remains unclear, making it difficult to develop precise theoretical models of alpha function and attention. Using EEG and concurrent TMS-EEG, this study aimed to (1) disentangle the contributions of oscillatory and aperiodic alpha activity to visuospatial attention and (2) examine their causal roles by differentially modulating aperiodic and oscillatory components. First, across four independent EEG datasets, we found that both aperiodic and oscillatory alpha activity contribute to spatial attention encoding and univariate lateralisation effects. The two signals were uncorrelated across electrodes and their combination yielded stronger lateralisation effects than either signal separately, suggesting that they may play complementary roles. Then, we used concurrent TMS-EEG to modulate the two signals. Compared to arrhythmic TMS (ar-TMS), rhythmic TMS (rh-TMS), enhanced oscillatory alpha power, especially at the stimulated area, while decreasing aperiodic alpha power across the scalp. Despite these opposing effects, rh-TMS improved visuospatial attention representation carried by both oscillatory and aperiodic alpha signals, suggesting that both signals may reflect attentional processing. Moreover, TMS-induced changes in oscillatory and aperiodic alpha decoding differentially predicted behavioural performance, with TMS-induced changes in oscillatory alpha decoding correlating with response errors and changes in aperiodic alpha decoding correlating with response speed. Together these findings reveal a functional dissociation between oscillatory and aperiodic activity in the alpha band. We suggest a dual mechanism for alpha band activity in supporting visuospatial attention, where the two components have distinct but complementary roles. Oscillatory components may primarily support attentional filtering and target prioritization, while aperiodic components may reflect overall neural excitability and cognitive efficiency. Both of these mechanisms contribute to successful visuospatial attention.

URL:

Data available, click to request

Authors:

FLEMING, H., STASIAK, M.K., LAU, I., WHINES, A., MEHRHOF, S.Z. & NORD, C.L.

Reference:

Year of publication:

In Press

CBU number:

9200

Abstract:

Background: Signals from the body profoundly influence cognition. This process is known as interoception, and has been extensively studied in the cardiac, respiratory, and gastric domains; in contrast, metabolic influences remain poorly understood. Here, we focus on the link between glucose control and cognition, motivated by the observation that there is substantial, unexplained comorbidity between type-2 diabetes and depression. In rodents, insulin modulates dopamine signalling in the ventral striatum. We therefore hypothesised that, in humans, differences in glucose control would be associated with altered reward learning. Methods: To test this hypothesis, we recruited 48 participants from the general population, who each completed a glucose tolerance test, a monetary reward learning task known to relate to dopamine function, and mental health questionnaires. We fitted an established reinforcement learning model to the task data in order to obtain computational parameters characterising participants’ learning, and then examined the associations between these parameters and their glucose control. Results: We discovered that poorer glucose control was associated with greater reliance on recent rewards during learning which was, in turn, associated with higher depression symptoms. There was also more modest evidence for the association between glucose control and depression symptoms. Conclusions: Together, our results identify a specific neurocognitive process, reward learning, by which metabolic information may influence cognition, and which may explain the link between metabolic diseases like type-2 diabetes and depression.

URL:

Data for this project is available at: https://doi.org/10.17605/OSF.IO/B9Z5V

Authors:

FLEMING, H., Feng, G.W., Rutledge, R.B., Roiser, J.P., & Robinson, O.J.

Reference:

Year of publication:

In Press

CBU number:

9199

Abstract:

Pavlovian biases are patterns of behaviour that involve approaching stimuli associated with reward and avoiding those associated with punishment (regardless of whether this is actually optimal behaviour). They are an ubiquitous feature of everyday decision-making, and are also believed to play an important role in the symptoms of anxiety and depression. Although Pavlovian biases have classically been described as fixed and automatic, some studies have indicated that their influence on behaviour can actually vary over time and with task demands. While these results hint that people may have some control over their Pavlovian biases, direct behavioural evidence for this control is still lacking. In a preregistered, double- blind, sham-controlled study (N = 800), we tested whether a week-long cognitive training intervention could reduce Pavlovian biases on the Orthogonalised Go/No-Go task, a well- established paradigm for isolating Pavlovian-instrumental conflict. Participants were trained on either high-conflict or no-conflict conditions of the task across five days. Using reinforcement learning models to dissociate components of decision-making, we found that high-conflict training led to a significant reduction in Pavlovian bias—particularly avoidance bias—at follow-up. This result is incompatible with the view that Pavlovian biases are fixed and automatic, and instead implies much greater flexibility in the way that they influence cognition than has previously been understood. The training was kept deliberately simple (i.e. one stimulus per condition, with the correct responses kept constant over sessions) so as to provide a minimal proof of concept of whether Pavlovian biases can be reduced through training, but as a result we did not observe transfer to other tasks or self-reported mood. Nonetheless, these findings demonstrate that targeted cognitive training can modulate Pavlovian biases, which may be beneficial both in everyday life and especially in the context of affective disorders like anxiety and depression.

Data available, click to request

Authors:

Vidal-Piñeiro, D, Sørensen, O., Strømstrad,M., Amlien, I.K., Baaré, W., Bartrés-Faz, D., Brandmaier, A.M., Cattaneo, G., Düze, S., Ghisletta, P., HENSON, R.N., Kühn, S., Lindenberger, U., Mowinckel, A.M., Nyberg1, L., Pascual-Leone, A., Roe, J.M., Solana-Sánchez, J., Solé-Padullés, C., Watne, L.O., Wolfers, T., for the Vietnam Era Twin Study of Aging (VETSA), the Australian Imaging Biomarkers and Lifestyle flagship study of ageing (AIBL), the Alzheimer's Disease Neuroimaging Initiative (ADNI)., Walhovd, K.B., and Fjell1, A.M.

Reference:

Year of publication:

In Press

CBU number:

9196

Abstract:

Brain atrophy is a key factor behind episodic memory loss in aging, but the nature and ubiquity of this relationship remains poorly understood. This study leverages 13 longitudinal datasets, including 3,737 cognitively healthy adults (10,343 MRI scans; 13,460 memory assessments), to determine whether brain change-memory change associations are more pronounced with age and genetic risk for Alzheimer’s Disease. Both factors are associated with accelerated brain decline, yet it remains unclear whether memory loss is exacerbated beyond what atrophy alone would predict. Additionally, we assess whether memory decline aligns with a global pattern of atrophy or stems from distinct regional contributions. Our mega-analysis reveals a nonlinear relationship between memory decline and brain atrophy, primarily affecting individuals with above-average brain structural decline. The associations are stronger in the hippocampus but also spread across diverse cortical and subcortical regions. The associations strengthen with age, reaching moderate associations in participants in their eighties. While APOE ε4 carriers exhibit steeper brain and memory loss, genetic risk has no effect on the change-change associations. These findings support the presence of common biological macrostructural substrates underlying memory function in older age which are vulnerable to multiple age-related factors, even in the absence of overt pathological changes.

Data for this project is available at: https://github.com/daidak/memory-brain-change

Authors:

FASSI, L., FERGUSON, A.M., Przybylski, A.K., Ford, T.J. & ORBEN, A.

Reference:

Year of publication:

2025

CBU number:

9195

Abstract:

Concerns about the relationship between social media use and adolescent mental health are growing, yet few studies focus on adolescents with clinical-level mental health symptoms. This limits our understanding of how social media use varies across mental health profiles. In this Registered Report, we analyse nationally representative UK data (N = 3,340, aged 11–19 years) including diagnostic assessments by clinical raters alongside quantitative and qualitative social media measures. As hypothesized, adolescents with mental health conditions reported spending more time on social media and were less happy about the number of online friends than adolescents without conditions. We also found hypothesized differences in social media use by condition type: adolescents with internalizing conditions reported spending more time on social media, engaging in more social comparison and experiencing greater impact of feedback on mood, alongside lower happiness about the number of online friends and lower honest self-disclosure. In contrast, those with externalizing conditions only reported higher time spent. These findings emphasize the need to consider diverse adolescent mental health profiles in policy and clinical practice.

URL:

Data for this project is available at: https://osf.io/s2dwu/overview?view_only=5acced2ddb884f9481d439a7746f4dd1

Authors:

Ravndal, A., Fjell1, A.M., Vidal-Piñeiro, D., Sørensen, O., Sogn Falch, E., Kropiunig, J., Garrido, P.F., Roe, J.M., Alatorre-Warren, J-L, Sneve, M.H., Bartrés-Faz, D., Pascual-Leone, A., Brandmaier, A.M., Düzel, S., Kühn, S., Lindenberger, U., Nyberg, L., Watne, L.O., Henson, R.N., for the Australian Imaging Biomarkers and Lifestyle flagship study of ageing (AIBL), the Alzheimer's Disease Neuroimaging Initiative (ADNI), Walhovd, K.B., and Grydeland, H.

Reference:

Year of publication:

2025

CBU number:

9194

Abstract:

As Alzheimer’s disease (AD) is diagnosed more frequently in women, understanding the role of sex has become a key priority in AD research. However, despite aging being the primary risk factor for AD, it remains unclear whether men and women differ in the extent of brain decline with age. Using 12,638 longitudinal brain MRIs from 4,726 participants aged 17 to 95 years across 14 cohorts, we examined sex differences in structural brain changes over time, controlling for differences in head size. Men showed greater cortical thickness decline in the cuneus, lingual, parahippocampal, and pericalcarine regions; surface area decline in the fusiform and postcentral regions; and in older adults, greater subcortical decline in the caudate, nucleus accumbens, putamen and pallidum. In contrast, women only showed greater surface area decline in the banks of the superior temporal sulcus and greater ventricular expansion in older adults. These results suggest that sex differences in age-related brain decline are unlikely to contribute to the higher AD diagnosis prevalence in women, necessitating research into alternative explanations.

URL:

Data for this project is available at: https://osf.io/mgtqr/overview

Authors:

Dercon, Q., Huys, WQ.J.M., Rutledge, R.B., and NORD, C.L.

Reference:

Year of publication:

In Press

CBU number:

9193

Data for this project is available at: All files, scripts, etc. can be found at: https://github.com/qdercon/pstpipeline

Authors:

ROUNIS, E., RAMANAN, S., Bickerton, Demeyere, N., LAMBON RALPH, M.

Reference:

Year of publication:

2025

CBU number:

9191

Abstract:

Background Limb apraxia is common after stroke and may affect long-term activities of daily living (ADL). This study investigates whether early subacute limb praxis scores predict long-term ADL outcomes over and above other cognitive deficits. Methods This longitudinal observational study analysed data from the Birmingham Cognitive Screen (BCoS) cohort, conducted between 2010 and 2015 across multiple stroke centres in the UK. Two-hundred-fifty-six first-ever CT-confirmed stroke survivors (56.3 % men; mean ± SD age = 68.3 ± 11.4 y) were assessed 9 months (chronic). BCoS comprises 34 cognitive tasks; four assess limb praxis. Scores were rescaled to 0–100. Functional outcome was the 20-point Barthel Index (BI). Stepwise multiple linear regression with 4-fold internal cross-validation tested whether sub-acute cognitive and praxis performance predicted chronic BI, adjusting for baseline BI and other cognitive domains. Results Mean BI improved from 13.3 ± 5.5 to 17.3 ± 3.9. Higher sub-acute limb praxis scores predicted better chronic ADL: gesture production β = –0.0555 (p = 0.0008), gesture recognition β = –0.0349 (p = 0.017), meaningless gesture imitation β = 0.0338 (p = 0.0047). The full model explained 60 % of BI variance and outperformed a model without praxis measures (ΔR² = 0.04; ANOVA p < 0.001). Conclusions Detailed early limb praxis testing adds independent prognostic value for long-term ADL and should be incorporated into routine post-stroke assessments to target rehabilitation

URL:

Data for this project is held by an external institution. Please contact the authors to request a copy.