Cognition and Memory after Covid-19 in a Large Community Sample.

BACKGROUND: Cognitive symptoms after coronavirus disease 2019 (Covid-19), the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are well-recognized. Whether objectively measurable cognitive deficits exist and how long they persist are unclear. METHODS: We invited 800,000 adults in a study in England to complete an online assessment of cognitive function. We estimated a global cognitive score across eight tasks. We hypothesized that participants with persistent symptoms (lasting ≥12 weeks) after infection onset would have objectively measurable global cognitive deficits and that impairments in executive functioning and memory would be observed in such participants, especially in those who reported recent poor memory or difficulty thinking or concentrating ("brain fog"). RESULTS: Of the 141,583 participants who started the online cognitive assessment, 112,964 completed it. In a multiple regression analysis, participants who had recovered from Covid-19 in whom symptoms had resolved in less than 4 weeks or at least 12 weeks had similar small deficits in global cognition as compared with those in the no-Covid-19 group, who had not been infected with SARS-CoV-2 or had unconfirmed infection (-0.23 SD [95% confidence interval {CI}, -0.33 to -0.13] and -0.24 SD [95% CI, -0.36 to -0.12], respectively); larger deficits as compared with the no-Covid-19 group were seen in participants with unresolved persistent symptoms (-0.42 SD; 95% CI, -0.53 to -0.31). Larger deficits were seen in participants who had SARS-CoV-2 infection during periods in which the original virus or the B.1.1.7 variant was predominant than in those infected with later variants (e.g., -0.17 SD for the B.1.1.7 variant vs. the B.1.1.529 variant; 95% CI, -0.20 to -0.13) and in participants who had been hospitalized than in those who had not been hospitalized (e.g., intensive care unit admission, -0.35 SD; 95% CI, -0.49 to -0.20). Results of the analyses were similar to those of propensity-score-matching analyses. In a comparison of the group that had unresolved persistent symptoms with the no-Covid-19 group, memory, reasoning, and executive function tasks were associated with the largest deficits (-0.33 to -0.20 SD); these tasks correlated weakly with recent symptoms, including poor memory and brain fog. No adverse events were reported. CONCLUSIONS: Participants with resolved persistent symptoms after Covid-19 had objectively measured cognitive function similar to that in participants with shorter-duration symptoms, although short-duration Covid-19 was still associated with small cognitive deficits after recovery. Longer-term persistence of cognitive deficits and any clinical implications remain uncertain. (Funded by the National Institute for Health and Care Research and others.).

Changes in affective control covary with changes in mental health difficulties following affective control training (AffeCT) in adolescents.

BACKGROUND: Everyday affective fluctuations are more extreme and more frequent in adolescence compared to any other time in development. Successful regulation of these affective experiences is important for good mental health and has been proposed to depend on affective control. The present study examined whether improving affective control through a computerised affective control training app (AffeCT) would benefit adolescent mental health. METHODS: One-hundred and ninety-nine participants (11-19 years) were assigned to complete 2 weeks of AffeCT or placebo training on an app. Affective control (i.e. affective inhibition, affective updating and affective shifting), mental health and emotion regulation were assessed at pre- and post-training. Mental health and emotion regulation were assessed again one month and one year later. RESULTS: Compared with the placebo group, the AffeCT group showed significantly greater improvements in affective control on the trained measure. AffeCT did not, relative to placebo, lead to better performance on untrained measures of affective control. Pre- to post-training change in affective control covaried with pre- to post-training change in mental health problems in the AffeCT but not the placebo group. These mental health benefits of AffeCT were only observed immediately following training and did not extend to 1 month or year post-training. CONCLUSION: In conclusion, the study provides preliminary evidence that AffeCT may confer short-term preventative benefits for adolescent mental health.

Neuroinflammation is independently associated with brain network dysfunction in Alzheimer's disease.

Brain network dysfunction is increasingly recognised in Alzheimer's disease (AD). However, the causes of brain connectivity disruption are still poorly understood. Recently, neuroinflammation has been identified as an important factor in AD pathogenesis. Microglia participate in the construction and maintenance of healthy neuronal networks, but pro-inflammatory microglia can also damage these circuits. We hypothesised that microglial activation is independently associated with brain connectivity disruption in AD. We performed a cross-sectional multimodal imaging study and interrogated the relationship between imaging biomarkers of neuroinflammation, Aß deposition, brain connectivity and cognition. 42 participants (12 Aß-positive MCI, 14 Aß-positive AD and 16 Aß-negative healthy controls) were recruited. Participants had 11C-PBR28 and 18F-flutemetamol PET to quantify Aß deposition and microglial activation, T1-weighted, diffusion tensor and resting-state functional MRI to assess structural network and functional network. 11C-PBR28 uptake, structural network integrity and functional network orgnisation were compared across diagnostic groups and the relationship between neuroinflammation and brain network was tested in 26 Aß-positive patients. Increased 11C-PBR28 uptake, decreased FA, network small-worldness and local efficiency were observed in AD patients. Cortical 11C-PBR28 uptake correlated negatively with structural integrity (standardised ß = -0.375, p = 0.037) and network local efficiency (standardised ß = -0.468, p < 0.001), independent of cortical thickness and Aß deposition, while Aß was not. Network structural integrity, small-worldness and local efficiency, and cortical thickness were positively associated with cognition. Our findings suggest cortical neuroinflammation coincide with structural and functional network disruption independent of Aß and cortical atrophy. These findings link the brain connectivity change and pathological process in Alzheimer's disease, and suggest a pathway from neuroinflammation to systemic brain dysfunction.

Cognitive domains affected post-COVID-19; a systematic review and meta-analysis.

BACKGROUND AND PURPOSE: This review aims to characterize the pattern of post-COVID-19 cognitive impairment, allowing better prediction of impact on daily function to inform clinical management and rehabilitation. METHODS: A systematic review and meta-analysis of neurocognitive sequelae following COVID-19 was conducted, following PRISMA-S guidelines. Studies were included if they reported domain-specific cognitive assessment in patients with COVID-19 at >4 weeks post-infection. Studies were deemed high-quality if they had >40 participants, utilized healthy controls, had low attrition rates and mitigated for confounders. RESULTS: Five of the seven primary Diagnostic and Statistical Manual of Mental Disorders (DSM-5) cognitive domains were assessed by enough high-quality studies to facilitate meta-analysis. Medium effect sizes indicating impairment in patients post-COVID-19 versus controls were seen across executive function (standardised mean difference (SMD) -0.45), learning and memory (SMD -0.55), complex attention (SMD -0.54) and language (SMD -0.54), with perceptual motor function appearing to be impacted to a greater degree (SMD -0.70). A narrative synthesis of the 56 low-quality studies also suggested no obvious pattern of impairment. CONCLUSIONS: This review found moderate impairments across multiple domains of cognition in patients post-COVID-19, with no specific pattern. The reported literature was significantly heterogeneous, with a wide variety of cognitive tasks, small sample sizes and disparate initial disease severities limiting interpretability. The finding of consistent impairment across a range of cognitive tasks suggests broad, as opposed to domain-specific, brain dysfunction. Future studies should utilize a harmonized test battery to facilitate inter-study comparisons, whilst also accounting for the interactions between COVID-19, neurological sequelae and mental health, the interplay between which might explain cognitive impairment.

The relationship between playing musical instruments and cognitive trajectories: Analysis from a UK ageing cohort.

BACKGROUND: The accumulation of age-associated cognitive deficits can lead to Mild Cognitive Impairment (MCI) and dementia. This is a major public health issue for the modern ageing population, as it impairs health, independence and overall quality of life. Keeping the brain active during life has been associated with an increased cognitive reserve, therefore reducing the risk of cognitive impairment in older age. Previous research has identified a potential relationship between musicality and cognition. OBJECTIVES: Explore the relationship between musicality and cognitive function in a large cohort of older adults. METHODS: This was a nested study within the PROTECT-UK cohort, which collects longitudinal computerised assessments of cognitive function in adults over 40. Participants were invited to complete the validated Edinburgh Lifetime Musical Experience Questionnaire (ELMEQ) to assess their musical experience and lifetime exposure to music. Linear regression analysis was performed using cognitive data from PROTECT-UK. RESULTS: Analysis identified an association between musicality and cognition in this cohort. Playing a musical instrument was associated with significantly better performance in working memory and executive function. Significant associations were also found between singing and executive function, and between overall musical ability and working memory. CONCLUSIONS: Our findings confirm previous literature, highlighting the potential value of education and engagement in musical activities throughout life as a means of harnessing cognitive reserve as part of a protective lifestyle for brain health.

Validation of an abbreviated Big Five personality inventory at large population scale: Psychometric structure and associations with common psychiatric and neurological disorders.

BACKGROUND: The five-factor model of personality, as quantified using instruments such as the Big Five Inventory, consists of broad personality domains including Extraversion, Agreeableness, Conscientiousness, Neuroticism (emotional instability), and Openness. Such instruments typically include >40 items. However, instruments with many items can be unwieldly and a cause of measurement error in clinical and cohort studies where multiple scales are sequenced. Conversely, established 5- and 10-item versions of the Big Five Inventory have poor reliability. Here, we developed and validated an abbreviated 18-item Big Five Inventory that balances efficiency, reliability and sensitivity. METHOD: We analysed three datasets (N = 59,797, N = 21,177, and N = 87,983) from individuals who participated in the online Great British Intelligence Test (GBIT) study, a collaborative citizen science project with BBC2 Horizon. We applied factor analyses (FA), predictive normative modelling, and one-sample t-tests to validate the 18-item version of the Big Five and to investigate its associations with psychiatric and neurological conditions. RESULTS: The 18-item version of the Big Five Inventory had higher validity and retest reliability compared to the other previously shortened versions in the literature, with comparable demographic associations to the full Big Five Inventory. It exhibited strong (i.e. large effect size) associations with psychiatric conditions, and moderate (small-medium) associations with neurological conditions. Neuroticism (emotional instability) was substantially higher in all psychiatric conditions, whereas Conscientiousness, Openness and Extraversion showed differential associations across conditions. CONCLUSION: The newly validated 18-item version of the Big Five provides a convenient means of measuring personality traits that is suitable for deployment in a range of studies. It retains psychometric structure, retest reliability and clinical-group sensitivity, as compared to the full original scale.

Cardiovascular and lifestyle risk factors of mild cognitive impairment in UK veterans and non-veterans.

BACKGROUND: The link between poor cardiovascular health (CVH), lifestyle and mild cognitive impairment (MCI) has been well established in the general population. However, there is limited research exploring these associations in ageing UK veterans. AIMS: This study explored the risk of MCI and its association with nine CVH and lifestyle risk factors (including diabetes, heart disease, high cholesterol, high blood pressure, obesity, stroke, physical inactivity, the frequency of alcohol consumption and smoking) in UK veterans and non-veterans. METHODS: This prospective cohort study comprised data from the PROTECT study between 2014 and 2022. Participants comprised of UK military veterans and non-veterans aged ≥50 years at baseline. Veteran status was defined using the Military Service History Questionnaire. CVH and lifestyle risk factors were defined using a combination of self-report measures, medication history or physical measurements. MCI was defined as the presence of subjective and objective cognitive impairment. RESULTS: Based on a sample of 9378 veterans (n = 488) and non-veterans (n = 8890), the findings showed the risk of MCI significantly reduced in veterans with obesity, those who frequently consumed alcohol and were physically inactive compared to non-veterans. The risk of MCI significantly increased in veterans with diabetes (hazards ratio [HR] = 2.22, 95% confidence interval [CI] 1.04-4.75, P ≤ 0.05) or high cholesterol (HR = 3.11, 95% CI 1.64-5.87, P ≤ 0.05) compared to veterans without. CONCLUSIONS: This study identified CVH and lifestyle factors of MCI in UK veterans and non-veterans. Further work is needed to understand these associations and the underpinning mechanisms which could determine intervention strategies to reduce the risk of MCI.

Planning ahead: Predictable switching recruits task-active and resting-state networks.

Switching is a difficult cognitive process characterised by costs in task performance; specifically, slowed responses and reduced accuracy. It is associated with the recruitment of a large coalition of task-positive regions including those referred to as the multiple demand cortex (MDC). The neural correlates of switching not only include the MDC, but occasionally the default mode network (DMN), a characteristically task-negative network. To unpick the role of the DMN during switching we collected fMRI data from 24 participants playing a switching paradigm that perturbed predictability (i.e., cognitive load) across three switch dimensions-sequential, perceptual, and spatial predictability. We computed the activity maps unique to switch vs. stay trials and all switch dimensions, then evaluated functional connectivity under these switch conditions by computing the pairwise mutual information functional connectivity (miFC) between regional timeseries. Switch trials exhibited an expected cost in reaction time while sequential predictability produced a significant benefit to task accuracy. Our results showed that switch trials recruited a broader activity map than stay trials, including regions of the DMN, the MDC, and task-positive networks such as visual, somatomotor, dorsal, salience/ventral attention networks. More sequentially predictable trials recruited increased activity in the somatomotor and salience/ventral attention networks. Notably, changes in sequential and perceptual predictability, but not spatial predictability, had significant effects on miFC. Increases in perceptual predictability related to decreased miFC between control, visual, somatomotor, and DMN regions, whereas increases in sequential predictability increased miFC between regions in the same networks, as well as regions within ventral attention/ salience, dorsal attention, limbic, and temporal parietal networks. These results provide novel clues as to how DMN may contribute to executive task performance. Specifically, the improved task performance, unique activity, and increased miFC associated with increased sequential predictability suggest that the DMN may coordinate more strongly with the MDC to generate a temporal schema of upcoming task events, which may attenuate switching costs.

Microglial activation, tau and amyloid deposition in TREM2 p.R47H carriers and mild cognitive impairment patients: a multi-modal/multi-tracer PET/MRI imaging study with influenza vaccine immune challenge.

BACKGROUND: Microglia are increasingly understood to play an important role in the pathogenesis of Alzheimer's disease. The rs75932628 (p.R47H) TREM2 variant is a well-established risk factor for Alzheimer's disease. TREM2 is a microglial cell surface receptor. In this multi-modal/multi-tracer PET/MRI study we investigated the effect of TREM2 p.R47H carrier status on microglial activation, tau and amyloid deposition, brain structure and cognitive profile. METHODS: We compared TREM2 p.R47H carriers (n = 8; median age = 62.3) and participants with mild cognitive impairment (n = 8; median age = 70.7). Participants underwent two [18F]DPA-714 PET/MRI scans to assess TSPO signal, indicative of microglial activation, before and after receiving the seasonal influenza vaccination, which was used as an immune stimulant. Participants also underwent [18F]florbetapir and [18F]AV1451 PET scans to assess amyloid and tau burden, respectively. Regional tau and TSPO signal were calculated for regions of interest linked to Braak stage. An additional comparison imaging healthy control group (n = 8; median age = 45.5) had a single [18F]DPA-714 PET/MRI. An expanded group of participants underwent neuropsychological testing, to determine if TREM2 status influenced clinical phenotype. RESULTS: Compared to participants with mild cognitive impairment, TREM2 carriers had lower TSPO signal in Braak II (P = 0.04) and Braak III (P = 0.046) regions, despite having a similar burden of tau and amyloid. There were trends to suggest reduced microglial activation following influenza vaccine in TREM2 carriers. Tau deposition in the Braak VI region was higher in TREM2 carriers (P = 0.04). Furthermore, compared to healthy controls TREM2 carriers had smaller caudate (P = 0.02), total brain (P = 0.049) and white matter volumes (P = 0.02); and neuropsychological assessment revealed worse ADAS-Cog13 (P = 0.03) and Delayed Matching to Sample (P = 0.007) scores. CONCLUSIONS: TREM2 p.R47H carriers had reduced levels of microglial activation in brain regions affected early in the Alzheimer's disease course and differences in brain structure and cognition. Changes in microglial response may underlie the increased Alzheimer's disease risk in TREM2 p.R47H carriers. Future therapeutic agents in Alzheimer's disease should aim to enhance protective microglial actions.

Self-reported sleep fragmentation and sleep duration and their association with cognitive function in PROTECT, a large digital community-based cohort of people over 50.

OBJECTIVE: Sleep is vital for normal cognitive function in daily life, but is commonly disrupted in older adults. Poor sleep can be detrimental to mental and physical health, including cognitive function. This study assessed the association between self-reported short (<6 h) and long (>9 h) sleep duration and sleep fragmentation (3≥ nightly awakenings) in cognitive function. METHODS: Cross-sectional data from 8508 individuals enroled in the PROTECT study aged 50 and above formed the basis of the univariate linear regression analysis conducted on four cognitive outcomes assessing visuospatial episodic memory (VSEM), spatial working memory, verbal working memory (VWM), and verbal reasoning (VR). RESULTS: Short (ß = -0.153, 95% CI [-0.258, -0.048], p = 0.004) and long sleep duration (ß = -0.459, 95% CI [-0.826, -0.091], p = 0.014) were significantly associated with poorer cognitive performance in VWM. Long sleep duration (ß = -2.986, 95% CI [-5.453, -0.518], p = 0.018) was associated with impaired VR. Short sleep (ß = -0.133, 95% CI [-0.196, -0.069], p = <0.001) and sleep fragmentation (ß = -0.043, 95% CI [-0.085, -0.001], p = 0.043) were associated with reduced VSEM. These associations remained significant when including other established risk factors for dementia and cognitive decline (e.g., depression, hypertension). CONCLUSIONS: Our findings suggest that short and long sleep durations and fragmented sleep, may be risk factors for a decline in cognitive processes such as working memory, VR and episodic memory thus might be potential targets for interventions to maintain cognitive health in ageing.

Conceptualising compulsivity through network analysis: A two-sample study.

Compulsivity is a transdiagnostic construct crucial to understanding multiple psychiatric conditions and problematic repetitive behaviours. Despite being identified as a clinical- and research-relevant construct, there are limited insights into the internal conceptual structure of compulsivity. To provide a more nuanced understanding of compulsivity, the current study estimated the structure of compulsivity (indexed using the previously validated Cambridge-Chicago Compulsivity Trait Scale, CHI-T) among two large-scale and geographically distinct samples using the network estimation method. The samples consisted of a United Kingdom cohort (n = 122,346, 51.4% female, Mean age = 43.7, SD = 16.5, range = 9-86 years) and a South Africa cohort (n = 2674, 65.6% female, Mean age = 24.6, SD = 8.6, range = 18-65 years). Network community analysis demonstrated that compulsivity was constituted of three interrelated dimensions, namely: perfectionism, cognitive rigidity and reward drive. Further, 'Completion leads to soothing' and 'Difficulty moving from task to task' were identified as core (central nodes) to compulsivity. The dimensional structure and central nodes of compulsivity networks were consistent across the two samples. These findings facilitate the conceptualisation and measurement of compulsivity and may contribute to the early detection and treatment of compulsivity-related disorders.

Remote evaluation of sleep to enhance understanding of early dementia due to Alzheimer's Disease (RESTED-AD): an observational cohort study protocol.

BACKGROUND: Sleep and circadian rhythm disorders are well recognised in both AD (Alzheimer's Disease) dementia and MCI-AD (Mild Cognitive Impairment due to Alzheimer's Disease). Such abnormalities include insomnia, excessive daytime sleepiness, decreased sleep efficiency, increased sleep fragmentation and sundowning. Enhancing understanding of sleep abnormalities may unveil targets for intervention in sleep, a promising approach given hypotheses that sleep disorders may exacerbate AD pathological progression and represent a contributory factor toward impaired cognitive performance and worse quality of life. This may also permit early diagnosis of AD pathology, widely acknowledged as a pre-requisite for future disease-modifying therapies. This study aims to bridge the divide between in-laboratory polysomnographic studies which allow for rich characterisation of sleep but in an unnatural setting, and naturalistic studies typically approximating sleep through use of non-EEG wearable devices. It is also designed to record sleep patterns over a 2 month duration sufficient to capture both infradian rhythm and compensatory responses following suboptimal sleep. Finally, it harnesses an extensively phenotyped population including with AD blood biomarkers. Its principal aims are to improve characterisation of sleep and biological rhythms in individuals with AD, particularly focusing on micro-architectural measures of sleep, compensatory responses to suboptimal sleep and the relationship between sleep parameters, biological rhythms and cognitive performance. METHODS/DESIGN: This observational cohort study has two arms (AD-MCI / mild AD dementia and aged-matched healthy adults). Each participant undergoes a baseline visit for collection of demographic, physiological and neuropsychological information utilising validated questionnaires. The main study period involves 7 nights of home-based multi-channel EEG sleep recording nested within an 8-week study period involving continuous wrist-worn actigraphy, sleep diaries and regular brief cognitive tests. Measurement of sleep parameters will be at home thereby obtaining a real-world, naturalistic dataset. Cognitive testing will be repeated at 6 months to stratify participants by longitudinal disease progression. DISCUSSION: This study will generate new insights particularly in micro-architectural measures of sleep, circadian patterns and compensatory sleep responses in a population with and without AD neurodegenerative change. It aims to enhance standards of remotely based sleep research through use of a well-phenotyped population and advanced sleep measurement technology.

The Role of Awareness of Age-Related Change in the Longitudinal Association between Pain and Physical Activity.

We examined how physical pain impacts the developmental construct of Awareness of Age-Related Change (AARC-gains and AARC-losses) and, in turn, how AARC mediates and moderates the association between pain and subsequent physical activity. We used longitudinal data from 434 participants of the UK PROTECT Study (mean age = 65.5 years; SD = 6.94 years). We found that pain in 2019 predicted higher AARC-losses (ß = .07; p = .036) and less physical activity (ß = -.13; p-value = .001) in 2020. Additionally, we found that AARC-losses partially mediated, but did not moderate, the association of pain in 2019 and physical activity in 2020. AARC-losses may explain physical inactivity in middle-aged and older adults experiencing pain. Incorporating developmental constructs such as AARC into theories and empirical studies on pain and pain management may be necessary to more fully capture people's responses to pain.

A Bayesian optimization approach for rapidly mapping residual network function in stroke.

Post-stroke cognitive and linguistic impairments are debilitating conditions, with limited therapeutic options. Domain-general brain networks play an important role in stroke recovery and characterizing their residual function with functional MRI has the potential to yield biomarkers capable of guiding patient-specific rehabilitation. However, this is challenging as such detailed characterization requires testing patients on multitudes of cognitive tasks in the scanner, rendering experimental sessions unfeasibly lengthy. Thus, the current status quo in clinical neuroimaging research involves testing patients on a very limited number of tasks, in the hope that it will reveal a useful neuroimaging biomarker for the whole cohort. Given the great heterogeneity among stroke patients and the volume of possible tasks this approach is unsustainable. Advancing task-based functional MRI biomarker discovery requires a paradigm shift in order to be able to swiftly characterize residual network activity in individual patients using a diverse range of cognitive tasks. Here, we overcome this problem by leveraging neuroadaptive Bayesian optimization, an approach combining real-time functional MRI with machine-learning, by intelligently searching across many tasks, this approach rapidly maps out patient-specific profiles of residual domain-general network function. We used this technique in a cross-sectional study with 11 left-hemispheric stroke patients with chronic aphasia (four female, age ± standard deviation: 59 ± 10.9 years) and 14 healthy, age-matched control subjects (eight female, age ± standard deviation: 55.6 ± 6.8 years). To assess intra-subject reliability of the functional profiles obtained, we conducted two independent runs per subject, for which the algorithm was entirely reinitialized. Our results demonstrate that this technique is both feasible and robust, yielding reliable patient-specific functional profiles. Moreover, we show that group-level results are not representative of patient-specific results. Whereas controls have highly similar profiles, patients show idiosyncratic profiles of network abnormalities that are associated with behavioural performance. In summary, our study highlights the importance of moving beyond traditional 'one-size-fits-all' approaches where patients are treated as one group and single tasks are used. Our approach can be extended to diverse brain networks and combined with brain stimulation or other therapeutics, thereby opening new avenues for precision medicine targeting a diverse range of neurological and psychiatric conditions.

Abnormal dorsal attention network activation in memory impairment after traumatic brain injury.

Memory impairment is a common, disabling effect of traumatic brain injury. In healthy individuals, successful memory encoding is associated with activation of the dorsal attention network as well as suppression of the default mode network. Here, in traumatic brain injury patients we examined whether: (i) impairments in memory encoding are associated with abnormal brain activation in these networks; (ii) whether changes in this brain activity predict subsequent memory retrieval; and (iii) whether abnormal white matter integrity underpinning functional networks is associated with impaired subsequent memory. Thirty-five patients with moderate-severe traumatic brain injury aged 23-65 years (74% males) in the post-acute/chronic phase after injury and 16 healthy control subjects underwent functional MRI during performance of an abstract image memory encoding task. Diffusion tensor imaging was used to assess structural abnormalities across patient groups compared to 28 age-matched healthy controls. Successful memory encoding across all participants was associated with activation of the dorsal attention network, the ventral visual stream and medial temporal lobes. Decreased activation was seen in the default mode network. Patients with preserved episodic memory demonstrated increased activation in areas of the dorsal attention network. Patients with impaired memory showed increased left anterior prefrontal activity. White matter microstructure underpinning connectivity between core nodes of the encoding networks was significantly reduced in patients with memory impairment. Our results show for the first time that patients with impaired episodic memory show abnormal activation of key nodes within the dorsal attention network and regions regulating default mode network activity during encoding. Successful encoding was associated with an opposite direction of signal change between patients with and without memory impairment, suggesting that memory encoding mechanisms could be fundamentally altered in this population. We demonstrate a clear relationship between functional networks activated during encoding and underlying abnormalities within the structural connectome in patients with memory impairment. We suggest that encoding failures in this group are likely due to failed control of goal-directed attentional resources.

Traumatic life experiences and post-traumatic stress symptoms in middle-aged and older adults with and without autistic traits.

OBJECTIVES: Research with younger adults has begun to explore associations between autism/autistic traits and vulnerability to Post Traumatic Stress Disorder (PTSD). Large scale studies and/or examination of age-effects have not been conducted. METHODS: Adults aged 50 years+ from the PROTECT study (n = 20,220) completed items about current and childhood socio-communicative difficulties characteristic of autism. Approximately 1% (n = 251) endorsed high autistic traits, henceforth the Autism Spectrum Traits (AST) group. Differences between the AST and an age-and sex-matched "Comparison Older Adults" (COA; n = 9179) group were explored for lifetime traumatic experiences and current symptoms of PTSD, depression, and anxiety. RESULTS: Almost 30% of the AST group, compared to less than 8% of the COA, reported severe trauma in childhood/adulthood, including emotional, physical or sexual abuse. Elevated current PTSD symptoms were reported by AST compared to COA. An interaction was observed between autistic traits and trauma severity; the effect of level of trauma on PTSD symptoms was significantly greater for AST versus COA participants. This interaction remained significant when controlling for current depression and anxiety symptoms. CONCLUSIONS: The findings suggest that high autistic traits may increase the likelihood of experiencing trauma across the lifespan, and the impact of severe trauma on PTSD symptoms. Older adults with high (vs. low) autistic traits may be at greater risk of experiencing PTSD symptoms in latter life. Future research should test whether the pattern of results is similar for diagnosed autistic adults.

Item-level analysis of mental health symptom trajectories during the COVID-19 pandemic in the UK: Associations with age, sex and pre-existing psychiatric conditions.

BACKGROUND: There is widespread concern regarding how the COVID-19 pandemic has affected mental health. Emerging meta-analyses suggest that the impact on anxiety/depression may have been transient, but much of the included literature has major methodological limitations. Addressing this topic rigorously requires longitudinal data of sufficient scope and scale, controlling for contextual variables, with baseline data immediately pre-pandemic. AIMS: To analyse self-report of symptom frequency from two largely UK-based longitudinal cohorts: Cohort 1 (N = 10,475, two time-points: winter pre-pandemic to UK first winter resurgence), and Cohort 2 (N = 10,391, two time-points, peak first wave to UK first winter resurgence). METHOD: Multinomial logistic regression applied at the item level identified sub-populations with greater probability of change in mental health symptoms. Permutation analyses characterised changes in symptom frequency distributions. Cross group differences in symptom stability were evaluated via entropy of response transitions. RESULTS: Anxiety was the most affected aspect of mental health. The profiles of change in mood symptoms was less favourable for females and older adults. Those with pre-existing psychiatric diagnoses showed substantially higher probability of very frequent symptoms pre-pandemic and elevated risk of transitioning to the highest levels of symptoms during the pandemic. Elevated mental health symptoms were evident across intra-COVID timepoints in Cohort 2. CONCLUSIONS: These findings suggest that mental health has been negatively affected by the pandemic, including in a sustained fashion beyond the first UK lockdown into the first winter resurgence. Women, and older adults, were more affected relative to their own baselines. Those with diagnoses of psychiatric conditions were more likely to experience transition to the highest levels of symptom frequency.

A randomized control trial of the effects of home-based online attention training and working memory training on cognition and everyday function in a community stroke sample.

Cognitive difficulties are common following stroke and can have widespread impacts on everyday functioning. Technological advances offer the possibility of individualized cognitive training for patients at home, potentially providing a low-cost, low-intensity adjunct to rehabilitation services. Using this approach, we have previously demonstrated post-training improvements in attention and everyday functioning in fronto-parietal stroke patients. Here we examine whether these benefits are observed more broadly in a community stroke sample. Eighty patients were randomized to either 4 weeks of online adaptive attention training (SAT), working memory training (WMT) or waitlist (WL). Cognitive and everyday function measures were collected before and after the intervention, and after 3 months. During training, weekly measures of patients' subjective functioning were collected. The training was well received and compliance good. No differences in our primary end-point, spatial bias, or other cognitive functions were observed. However, on patient-reported outcomes, SAT participants showed greater levels of improvement in everyday functioning than WMT or WL participants. In line with our previous work, everyday functioning improvements were greatest for patients with spatial impairments and those who received SAT training. Whether attention training can be recommended for stroke survivors depends on whether cognitive test performance or everyday functioning is considered more relevant.

Distinct patterns of structural damage underlie working memory and reasoning deficits after traumatic brain injury.

It is well established that chronic cognitive problems after traumatic brain injury relate to diffuse axonal injury and the consequent widespread disruption of brain connectivity. However, the pattern of diffuse axonal injury varies between patients and they have a correspondingly heterogeneous profile of cognitive deficits. This heterogeneity is poorly understood, presenting a non-trivial challenge for prognostication and treatment. Prominent amongst cognitive problems are deficits in working memory and reasoning. Previous functional MRI in controls has associated these aspects of cognition with distinct, but partially overlapping, networks of brain regions. Based on this, a logical prediction is that differences in the integrity of the white matter tracts that connect these networks should predict variability in the type and severity of cognitive deficits after traumatic brain injury. We use diffusion-weighted imaging, cognitive testing and network analyses to test this prediction. We define functionally distinct subnetworks of the structural connectome by intersecting previously published functional MRI maps of the brain regions that are activated during our working memory and reasoning tasks, with a library of the white matter tracts that connect them. We examine how graph theoretic measures within these subnetworks relate to the performance of the same tasks in a cohort of 92 moderate-severe traumatic brain injury patients. Finally, we use machine learning to determine whether cognitive performance in patients can be predicted using graph theoretic measures from each subnetwork. Principal component analysis of behavioural scores confirm that reasoning and working memory form distinct components of cognitive ability, both of which are vulnerable to traumatic brain injury. Critically, impairments in these abilities after traumatic brain injury correlate in a dissociable manner with the information-processing architecture of the subnetworks that they are associated with. This dissociation is confirmed when examining degree centrality measures of the subnetworks using a canonical correlation analysis. Notably, the dissociation is prevalent across a number of node-centric measures and is asymmetrical: disruption to the working memory subnetwork relates to both working memory and reasoning performance whereas disruption to the reasoning subnetwork relates to reasoning performance selectively. Machine learning analysis further supports this finding by demonstrating that network measures predict cognitive performance in patients in the same asymmetrical manner. These results accord with hierarchical models of working memory, where reasoning is dependent on the ability to first hold task-relevant information in working memory. We propose that this finer grained information may be useful for future applications that attempt to predict long-term outcomes or develop tailored therapies.