Disrupted limbic-prefrontal effective connectivity in response to fearful faces in lifetime depression

BACKGROUND

Multiple brain imaging studies of negative emotional bias in major depressive disorder (MDD) have used images of fearful facial expressions and focused on the amygdala and the prefrontal cortex. The results have, however, been inconsistent, potentially due to small sample sizes (typically N<50). It remains unclear if any alterations are a characteristic of current depression or of past experience of depression, and whether there are MDD-related changes in effective connectivity between the two brain regions.

METHODS

Activations and effective connectivity between the amygdala and dorsolateral prefrontal cortex (DLPFC) in response to fearful face stimuli were studied in a large population-based sample from Generation Scotland. Participants either had no history of MDD (N=664 in activation analyses, N=474 in connectivity analyses) or had a diagnosis of MDD during their lifetime (LMDD, N=290 in activation analyses, N=214 in connectivity analyses). The within-scanner task involved implicit facial emotion processing of neutral and fearful faces.

RESULTS

Compared to controls, LMDD was associated with increased activations in left amygdala (PFWE=0.031,kE=4) and left DLPFC (PFWE=0.002,kE=33), increased mean bilateral amygdala activation (β=0.0715,P=0.0314), and increased inhibition from left amygdala to left DLPFC, all in response to fearful faces contrasted to baseline. Results did not appear to be attributable to depressive illness severity or antidepressant medication status at scan time.

LIMITATIONS

Most studied participants had past rather than current depression, average severity of ongoing depression symptoms was low, and a substantial proportion of participants were receiving medication. The study was not longitudinal and the participants were only assessed a single time.

CONCLUSIONS

LMDD is associated with hyperactivity of the amygdala and DLPFC, and with stronger amygdala to DLPFC inhibitory connectivity, all in response to fearful faces, unrelated to depression severity at scan time. These results help reduce inconsistency in past literature and suggest disruption of 'bottom-up' limbic-prefrontal effective connectivity in depression.

Characterizing the Neurobiological Mechanisms of Action of Exercise and Cognitive-Behavioral Interventions for Rheumatoid Arthritis Fatigue: A Magnetic Resonance Imaging Brain Study

OBJECTIVE

Chronic fatigue is a major clinical unmet need among patients with rheumatoid arthritis (RA). Current therapies are limited to nonpharmacological interventions, such as personalized exercise programs (PEPs) and cognitive-behavioral approaches (CBAs); however, most patients still continue to report severe fatigue. To inform more effective therapies, we conducted a magnetic resonance imaging (MRI) brain study of PEPs and CBAs, nested within a randomized controlled trial (RCT), to identify their neurobiological mechanisms of fatigue reduction in RA.

METHODS

A subgroup of patients with RA (n = 90), participating in an RCT of PEPs and CBAs for fatigue, undertook a multimodal MRI brain scan following randomization to either usual care (UC) alone or in addition to PEPs and CBAs and again after the intervention (six months). Brain regional volumetric, functional, and structural connectivity indices were curated and then computed employing a causal analysis framework. The primary outcome was fatigue improvement (Chalder fatigue scale).

RESULTS

Several structural and functional connections were identified as mediators of fatigue improvement in both PEPs and CBAs compared to UC. PEPs had a more pronounced effect on functional connectivity than CBAs; however, structural connectivity between the left isthmus cingulate cortex (L-ICC) and left paracentral lobule (L-PCL) was shared, and the size of mediation effect ranked highly for both PEPs and CBAs (ßAverage = -0.46, SD 0.61; ßAverage = -0.32, SD 0.47, respectively).

CONCLUSION

The structural connection between the L-ICC and L-PCL appears to be a dominant mechanism for how both PEPs and CBAs reduce fatigue among patients with RA. This supports its potential as a substrate of fatigue neurobiology and a putative candidate for future targeting.

The cerebellum plays more than one role in the dysregulation of appetite: Review of structural evidence from typical and eating disorder populations

OBJECTIVE

Dysregulated appetite control is characteristic of anorexia nervosa (AN), bulimia nervosa (BN), and obesity (OB). Studies using a broad range of methods suggest the cerebellum plays an important role in aspects of weight and appetite control, and is implicated in both AN and OB by reports of aberrant gray matter volume (GMV) compared to nonclinical populations. As functions of the cerebellum are anatomically segregated, specific localization of aberrant anatomy may indicate the mechanisms of its relationship with weight and appetite in different states. We sought to determine if there were consistencies in regions of cerebellar GMV changes in AN/BN and OB, as well as across normative (NOR) variation.

METHOD

Systematic review and meta-analysis using GingerALE.

RESULTS

Twenty-six publications were identified as either case-control studies (nOB  = 277; nAN/BN  = 510) or regressed weight from NOR data against brain volume (total n = 3830). AN/BN and OB analyses both showed consistently decreased GMV within Crus I and Lobule VI, but volume reduction was bilateral for AN/BN and unilateral for OB. Analysis of the NOR data set identified a cluster in right posterior lobe that overlapped with AN/BN cerebellar reduction. Sensitivity analyses indicated robust repeatability for NOR and AN/BN cohorts, but found OB-specific heterogeneity.

DISCUSSION

Findings suggest that more than one area of the cerebellum is involved in control of eating behavior and may be differentially affected in normal variation and pathological conditions. Specifically, we hypothesize an association with sensorimotor and emotional learning via Lobule VI in AN/BN, and executive function via Crus I in OB.

Associations of negative affective biases and depressive symptoms in a community-based sample

BACKGROUND

Major depressive disorder (MDD) was previously associated with negative affective biases. Evidence from larger population-based studies, however, is lacking, including whether biases normalise with remission. We investigated associations between affective bias measures and depressive symptom severity across a large community-based sample, followed by examining differences between remitted individuals and controls.

METHODS

Participants from Generation Scotland (N = 1109) completed the: (i) Bristol Emotion Recognition Task (BERT), (ii) Face Affective Go/No-go (FAGN), and (iii) Cambridge Gambling Task (CGT). Individuals were classified as MDD-current (n = 43), MDD-remitted (n = 282), or controls (n = 784). Analyses included using affective bias summary measures (primary analyses), followed by detailed emotion/condition analyses of BERT and FAGN (secondary analyses).

RESULTS

For summary measures, the only significant finding was an association between greater symptoms and lower risk adjustment for CGT across the sample (individuals with greater symptoms were less likely to bet more, despite increasingly favourable conditions). This was no longer significant when controlling for non-affective cognition. No differences were found for remitted-MDD v. controls. Detailed analysis of BERT and FAGN indicated subtle negative biases across multiple measures of affective cognition with increasing symptom severity, that were independent of non-effective cognition [e.g. greater tendency to rate faces as angry (BERT), and lower accuracy for happy/neutral conditions (FAGN)]. Results for remitted-MDD were inconsistent.

CONCLUSIONS

This suggests the presence of subtle negative affective biases at the level of emotion/condition in association with depressive symptoms across the sample, over and above those accounted for by non-affective cognition, with no evidence for affective biases in remitted individuals.

Concurrent validity and reliability of suicide risk assessment instruments: A meta-analysis of 20 instruments across 27 international cohorts

OBJECTIVE

A major limitation of current suicide research is the lack of power to identify robust correlates of suicidal thoughts or behavior. Variation in suicide risk assessment instruments used across cohorts may represent a limitation to pooling data in international consortia.

METHOD

Here, we examine this issue through two approaches: (a) an extensive literature search on the reliability and concurrent validity of the most commonly used instruments and (b) by pooling data (N ∼ 6,000 participants) from cohorts from the Enhancing NeuroImaging Genetics Through Meta-Analysis (ENIGMA) Major Depressive Disorder and ENIGMA-Suicidal Thoughts and Behaviour working groups, to assess the concurrent validity of instruments currently used for assessing suicidal thoughts or behavior.

RESULTS

We observed moderate-to-high correlations between measures, consistent with the wide range (κ range: 0.15-0.97; r range: 0.21-0.94) reported in the literature. Two common multi-item instruments, the Columbia Suicide Severity Rating Scale and the Beck Scale for Suicidal Ideation were highly correlated with each other (r = 0.83). Sensitivity analyses identified sources of heterogeneity such as the time frame of the instrument and whether it relies on self-report or a clinical interview. Finally, construct-specific analyses suggest that suicide ideation items from common psychiatric questionnaires are most concordant with the suicide ideation construct of multi-item instruments.

CONCLUSIONS

Our findings suggest that multi-item instruments provide valuable information on different aspects of suicidal thoughts or behavior but share a modest core factor with single suicidal ideation items. Retrospective, multisite collaborations including distinct instruments should be feasible provided they harmonize across instruments or focus on specific constructs of suicidality. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Brain mapping inflammatory-arthritis-related fatigue in the pursuit of novel therapeutics

Despite developments in pharmacological treatments, chronic fatigue is an unresolved issue for most people with inflammatory arthritis that severely disrupts their personal and working lives. Fatigue in these patients is not strongly linked with peripheral disease activity but is associated with CNS-derived symptoms such as chronic pain, sleep disturbance, and depression. Therefore, a neurobiological basis should be considered when pursuing novel fatigue-specific therapeutics. In this Review, we focus on clinical imaging biomarkers that map candidate brain regions and are crucial in fatigue pathophysiology. We then evaluate neuromodulation techniques that could affect these candidate brain regions and are potential treatment strategies for fatigue in patients with inflammatory arthritis. We delineate work that is still required for neuroimaging and neuromodulation to eventually become part of a clinical pathway to treat and manage fatigue.

Cognition and brain iron deposition in whole grey matter regions and hippocampal subfields

Regional brain iron accumulation is observed in many neurodegenerative diseases, including Alzheimer's disease and Parkinson's disease, and is associated with cognitive decline. We explored associations between age, cognition and iron content in grey matter regions and hippocampal subfields in 380 participants of the Aberdeen children of the 1950s cohort and their first-generation relatives (aged 26-72 years). Participants underwent cognitive assessment at the time of MRI scanning. Quantitative susceptibility mapping of these MRI data was used to assess iron content in grey matter regions and in hippocampal subfields. Principle component analysis was performed on cognitive test scores to create a general cognition score. Spline analysis was used with the Akaike information criterion to determine if order 1, 2 or 3 natural splines were optimal for assessing non-linear relationships between regional iron and age. Multivariate linear models were used to assess associations between regional iron and cognition. Higher iron correlated with older age in the left putamen across all ages and in the right putamen of only participants over 58. Whereas a decrease in iron with older age was observed in the right thalamus and left pallidum across all ages. Right amygdala iron levels were associated with poorer general cognition scores and poorer immediate recall scores. Iron was not associated with any measures of cognitive performance in other regions of interest. Our results suggest that, whilst iron in some regions was associated with cognitive performance, there is an overall lack of association between regional iron content and cognitive ability in cognitively healthy individuals.

Investigation of the Inter- and Intrascanner Reproducibility and Repeatability of Radiomics Features in T1-Weighted Brain MRI

BACKGROUND

Radiomics is the high throughput analysis of medical images using computer algorithms, which specifically assess textural features. It has increasingly been proposed as a tool for the development of imaging biomarkers. However, an important acknowledged limitation of radiomics is the lack of reproducibility of features produced.

PURPOSE

To assess reproducibility and repeatability of radiomics variables in brain MRI through a multivisit, multicenter study.

STUDY TYPE

Retrospective.

POPULATION

Fourteen individuals visiting three institutions twice, 10 males with the mean age of 36.3 years and age range 25-51.

FIELD STRENGTH

3D T1W inversion recovery on three 1.5-T General Electric scanners.

ASSESSMENT

Radiomics analysis by a consultant radiologist performed on the T1W images of the whole brain on all visits. All possible radiomics features were generated.

STATISTICAL TEST

Concordance correlation coefficient (CCC) and dynamic range (DR) for all variables were calculated to assess the test-retest repeatability. Intraclass correlation coefficients (ICCs) were calculated to investigate the reproducibility of features across centers.

RESULTS

Of 1596 features generated, 57 from center 1, 15 from center 2, and 22 from center 3 had a CCC > 0.9 and DR > 0.9. Eight variables had CCC > 0.9 and DR > 0.9 in all centers. Forty-one variables had an ICC of >0.9. No variables had CCC > 0.9, DR > 0.9, and ICC > 0.9.

DATA CONCLUSION

Repeatability and reproducibility of variables is a significant limitation of radiomics analysis in 3DT1W brain MRI. Careful selection of radiomic features is required.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY STAGE: 2.

Local CpG density affects the trajectory and variance of age-associated DNA methylation changes

BACKGROUND

DNA methylation is an epigenetic mark associated with the repression of gene promoters. Its pattern in the genome is disrupted with age and these changes can be used to statistically predict age with epigenetic clocks. Altered rates of aging inferred from these clocks are observed in human disease. However, the molecular mechanisms underpinning age-associated DNA methylation changes remain unknown. Local DNA sequence can program steady-state DNA methylation levels, but how it influences age-associated methylation changes is unknown.

RESULTS

We analyze longitudinal human DNA methylation trajectories at 345,895 CpGs from 600 individuals aged between 67 and 80 to understand the factors responsible for age-associated epigenetic changes at individual CpGs. We show that changes in methylation with age occur at 182,760 loci largely independently of variation in cell type proportions. These changes are especially apparent at 8322 low CpG density loci. Using SNP data from the same individuals, we demonstrate that methylation trajectories are affected by local sequence polymorphisms at 1487 low CpG density loci. More generally, we find that low CpG density regions are particularly prone to change and do so variably between individuals in people aged over 65. This differs from the behavior of these regions in younger individuals where they predominantly lose methylation.

CONCLUSIONS

Our results, which we reproduce in two independent groups of individuals, demonstrate that local DNA sequence influences age-associated DNA methylation changes in humans in vivo. We suggest that this occurs because interactions between CpGs reinforce maintenance of methylation patterns in CpG dense regions.

Age-associated sex and asymmetry differentiation in hemispheric and lobar cortical ribbon complexity across adulthood: A UK Biobank imaging study

Cortical morphology changes with ageing and age-related neurodegenerative diseases. Previous studies suggest that the age effect is more pronounced in the frontal lobe. However, our knowledge of structural complexity changes in male and female brains is still limited. We measured cortical ribbon complexity through fractal dimension (FD) analysis at the hemisphere and lobe level in 7010 individuals from the UK Biobank imaging cohort to study age-related sex differences (3332 males, age ranged 45-79 years). FD decreases significantly with age and sexual dimorphism exists. With correction for brain size, females showed higher complexity in the left hemisphere and left and right parietal lobes whereas males showed higher complexity in the right temporal and left and right occipital lobes. A nonlinear age effect was observed in the left and right frontal, and right temporal lobes. Differential patterns of age effects were observed in both sexes with relatively more age-affected regions in males. Significantly higher rightward asymmetries at hemisphere, frontal, parietal, and occipital lobe level and higher leftward asymmetry in temporal lobe were observed. There was no age-by-sex-by asymmetry interaction in any region. When controlling for brain size, the leftward hemispheric, and temporal lobe asymmetry decreased with age. Males had significantly lower asymmetry between hemispheres and higher asymmetry in the parietal and occipital lobes than females. This work provides distinct patterns of age-related sex and asymmetry differences that can aid in the future development of sex-specific models of the normal brain to ascribe cognitive functional significance of these patterns in ageing.

Brain predictors of fatigue in rheumatoid arthritis: A machine learning study

Background

Fatigue is a common and burdensome symptom in Rheumatoid Arthritis (RA), yet is poorly understood. Currently, clinicians rely solely on fatigue questionnaires, which are inherently subjective measures. For the effective development of future therapies and stratification, it is of vital importance to identify biomarkers of fatigue. In this study, we identify brain differences between RA patients who improved and did not improve their levels of fatigue based on Chalder Fatigue Scale variation (ΔCFS≥ 2), and we compared the performance of different classifiers to distinguish between these samples at baseline.

Methods

Fifty-four fatigued RA patients underwent a magnetic resonance (MR) scan at baseline and 6 months later. At 6 months we identified those whose fatigue levels improved and those for whom it did not. More than 900 brain features across three data sets were assessed as potential predictors of fatigue improvement. These data sets included clinical, structural MRI (sMRI) and diffusion tensor imaging (DTI) data. A genetic algorithm was used for feature selection. Three classifiers were employed in the discrimination of improvers and non-improvers of fatigue: a Least Square Linear Discriminant (LSLD), a linear Support Vector Machine (SVM) and a SVM with Radial Basis Function kernel.

Results

The highest accuracy (67.9%) was achieved with the sMRI set, followed by the DTI set (63.8%), whereas classification performance using clinical features was at the chance level. The mean curvature of the left superior temporal sulcus was most strongly selected during the feature selection step, followed by the surface are of the right frontal pole and the surface area of the left banks of the superior temporal sulcus.

Conclusions

The results presented evidence a superiority of brain metrics over clinical metrics in predicting fatigue changes. Further exploration of these methods may support clinicians to triage patients towards the most appropriate fatigue alleviating therapies.

A meta-analytic investigation of grey matter differences in anorexia nervosa and autism spectrum disorder

Recent research reports Anorexia Nervosa (AN) to be highly dependent upon neurobiological function. Some behaviours, particularly concerning food selectivity are found in populations with both Autism Spectrum Disorder (ASD) and AN, and there is a proportionally elevated number of anorexic patients exhibiting symptoms of ASD. We performed a systematic review of structural MRI literature with the aim of identifying common structural neural correlates common to both AN and ASD. Across 46 ASD publications, a meta‐analysis of volumetric differences between ASD and healthy controls revealed no consistently affected brain regions. Meta‐analysis of 23 AN publications revealed increased volume within the orbitofrontal cortex and medial temporal lobe, and adult‐only AN literature revealed differences within the genu of the anterior cingulate cortex. The changes are consistent with alterations in flexible reward‐related learning and episodic memory reported in neuropsychological studies. There was no structural overlap between ASD and AN. Findings suggest no consistent neuroanatomical abnormality associated with ASD, and evidence is lacking to suggest that reported behavioural similarities between those with AN and ASD are due to neuroanatomical structural similarities.

Findings related to neuroanatomical structure in AN/ASD demonstrate overlap and require revisiting.

Meta‐analytic findings show structural increase/decrease versus healthy controls (LPFC/MTL/OFC) in AN, but no clusters found in ASD.

The neuroanatomy associated with ASD is inconsistent, but findings in AN reflect condition‐related impairment in executive function and sociocognitive behaviours.

Cohort profile for the STratifying Resilience and Depression Longitudinally (STRADL) study: A depression-focused investigation of Generation Scotland, using detailed clinical, cognitive, and neuroimaging assessments

STratifying Resilience and Depression Longitudinally (STRADL) is a population-based study built on the Generation Scotland: Scottish Family Health Study (GS:SFHS) resource. The aim of STRADL is to subtype major depressive disorder (MDD) on the basis of its aetiology, using detailed clinical, cognitive, and brain imaging assessments. The GS:SFHS provides an important opportunity to study complex gene-environment interactions, incorporating linkage to existing datasets and inclusion of early-life variables for two longitudinal birth cohorts. Specifically, data collection in STRADL included: socio-economic and lifestyle variables; physical measures; questionnaire data that assesses resilience, early-life adversity, personality, psychological health, and lifetime history of mood disorder; laboratory samples; cognitive tests; and brain magnetic resonance imaging. Some of the questionnaire and cognitive data were first assessed at the GS:SFHS baseline assessment between 2006-2011, thus providing longitudinal measures relevant to the study of depression, psychological resilience, and cognition. In addition, routinely collected historic NHS data and early-life variables are linked to STRADL data, further providing opportunities for longitudinal analysis. Recruitment has been completed and we consented and tested 1,188 participants.

Amygdala and subregion volumes are associated with photoperiod and seasonal depressive symptoms: A cross-sectional study in the UK Biobank cohort

Although seasonal changes in amygdala volume have been demonstrated in animals, seasonal differences in human amygdala subregion volumes have yet to be investigated. Amygdala volume has also been linked to depressed mood. Therefore, we hypothesised that differences in photoperiod would predict differences in amygdala or subregion volumes and that this association would be linked to depressed mood. 10,033 participants ranging in age from 45 to 79 years were scanned by MRI in a single location. Amygdala subregion volumes were obtained using automated processing and segmentation algorithms. A mediation analysis tested whether amygdala volume mediated the relationship between photoperiod and mood. Photoperiod was positively associated with total amygdala volume (p < .001). Multivariate (GLM) analyses revealed significant effects of photoperiod across all amygdala subregion volumes for both hemispheres (p < .001). Post hoc univariate regression analyses revealed significant associations of photoperiod with each amygdala subregion volume (p < .001). PLS showed the highest loadings of amygdala subregions in lateral nucleus, ABN, basal nucleus, CAT, PLN, AAA, central nucleus, cortical nucleus and medial nucleus for left hemisphere and ABN, lateral nucleus, CAT, PLN, cortical nucleus, AAA, central nucleus and medial nucleus for right hemisphere. There were no significant associations between photoperiod and mood nor between mood scores and amygdala volumes, and due to the lack of these associations, the mediation hypothesis was not supported. This study is the first to demonstrate an association between photoperiod and amygdala volume. These findings add to the evidence supporting the role of photoperiod on brain structural plasticity.

Early life predictors of late life cerebral small vessel disease in four prospective cohort studies

Development of cerebral small vessel disease, a major cause of stroke and dementia, may be influenced by early life factors. It is unclear whether these relationships are independent of each other, of adult socio-economic status or of vascular risk factor exposures. We examined associations between factors from birth (ponderal index, birth weight), childhood (IQ, education, socio-economic status), adult small vessel disease, and brain volumes, using data from four prospective cohort studies: STratifying Resilience And Depression Longitudinally (STRADL) (n = 1080; mean age = 59 years); the Dutch Famine Birth Cohort (n = 118; mean age = 68 years); the Lothian Birth Cohort 1936 (LBC1936; n = 617; mean age = 73 years), and the Simpson's cohort (n = 110; mean age = 78 years). We analysed each small vessel disease feature individually and summed to give a total small vessel disease score (range 1-4) in each cohort separately, then in meta-analysis, adjusted for vascular risk factors and adult socio-economic status. Higher birth weight was associated with fewer lacunes [odds ratio (OR) per 100 g = 0.93, 95% confidence interval (CI) = 0.88 to 0.99], fewer infarcts (OR = 0.94, 95% CI = 0.89 to 0.99), and fewer perivascular spaces (OR = 0.95, 95% CI = 0.91 to 0.99). Higher childhood IQ was associated with lower white matter hyperintensity burden (OR per IQ point = 0.99, 95% CI 0.98 to 0.998), fewer infarcts (OR = 0.98, 95% CI = 0.97 to 0.998), fewer lacunes (OR = 0.98, 95% CI = 0.97 to 0.999), and lower total small vessel disease burden (OR = 0.98, 95% CI = 0.96 to 0.999). Low education was associated with more microbleeds (OR = 1.90, 95% CI = 1.33 to 2.72) and lower total brain volume (mean difference = -178.86 cm3, 95% CI = -325.07 to -32.66). Low childhood socio-economic status was associated with fewer lacunes (OR = 0.62, 95% CI = 0.40 to 0.95). Early life factors are associated with worse small vessel disease in later life, independent of each other, vascular risk factors and adult socio-economic status. Risk for small vessel disease may originate in early life and provide a mechanistic link between early life factors and risk of stroke and dementia. Policies investing in early child development may improve lifelong brain health and contribute to the prevention of dementia and stroke in older age.

Even a little sleepiness influences neural activation and clinical reasoning in novices

BACKGROUND AND AIMS

Sleepiness influences alertness and cognitive functioning and impacts many aspects of medical care, including clinical reasoning. However, dual processing theory suggests that sleepiness will impact clinical reasoning differently in different individual, depending on their level of experience with the given condition. Our aim, therefore, was to examine the association between clinical reasoning, neuroanatomical activation, and sleepiness in senior medical students.

METHODS

Our methodology replicated an earlier study but with novices rather than board-certified physicians. Eighteen final-year medical students answered validated multiple-choice questions (MCQs) during an fMRI scan. Each MCQ was projected in three phases: reading, answering, and reflection (modified think aloud). Echo-planar imaging (EPI) scans gave a time series that reflected blood oxygenation level dependent (BOLD) signal in each location (voxel) within the brain. Sleep data were collected via self-report (Epworth Sleepiness Scale) and actigraphy. These data were correlated with answer accuracy using Pearson correlation.

RESULTS

Analysis revealed an increased BOLD signal in the right dorsomedial prefrontal cortex (P < .05) during reflection (Phase 3) associated with increased self-reported sleepiness (ESS) immediately before scanning. Covariate analysis also revealed that increased BOLD signal in the right supramarginal gyrus (P < .05) when reflecting (Phase 3) was associated with increased correct answer response time. Both patterns indicate effortful analytic (System 2) reasoning.

CONCLUSION

Our findings that novices use System 2 thinking for clinical reasoning and even a little (perceived) sleepiness influences their clinical reasoning ability to suggest that the parameters for safe working may be different for novices (eg, junior doctors) and experienced physicians.

Hair glucocorticoids are associated with childhood adversity, depressive symptoms and reduced global and lobar grey matter in Generation Scotland

Hypothalamic-pituitary-adrenal (HPA) axis dysregulation has been commonly reported in major depressive disorder (MDD), but with considerable heterogeneity of results; potentially due to the predominant use of acute measures of an inherently variable/phasic system. Chronic longer-term measures of HPA-axis activity have yet to be systematically examined in MDD, particularly in relation to brain phenotypes, and in the context of early-life/contemporaneous stress. Here, we utilise a temporally stable measure of cumulative HPA-axis function (hair glucocorticoids) to investigate associations between cortisol, cortisone and total glucocorticoids with concurrent measures of (i) lifetime-MDD case/control status and current symptom severity, (ii) early/current-life stress and (iii) structural neuroimaging phenotypes, in N = 993 individuals from Generation Scotland (mean age = 59.1 yrs). Increased levels of hair cortisol were significantly associated with reduced global and lobar brain volumes with reductions in the frontal, temporal and cingulate regions (βrange = -0.057 to -0.104, all PFDR < 0.05). Increased levels of hair cortisone were significantly associated with MDD (lifetime-MDD status, current symptoms, and severity; βrange = 0.071 to 0.115, all PFDR = < 0.05), with early-life adversity (β = 0.083, P = 0.017), and with reduced global and regional brain volumes (global: β = -0.059, P = 0.043; nucleus accumbens: β = -0.075, PFDR = 0.044). Associations with total glucocorticoids followed a similar pattern to the cortisol findings. In this large community-based sample, elevated glucocorticoids were significantly associated with MDD, with early, but not later-life stress, and with reduced global and regional brain phenotypes. These findings provide important foundations for future mechanistic studies to formally explore causal relationships between early adversity, chronic rather than acute measures of glucocorticoids, and neurobiological associations relevant to the aetiology of MDD.

Spectral clustering based on structural magnetic resonance imaging and its relationship with major depressive disorder and cognitive ability

There is increasing interest in using data-driven unsupervised methods to identify structural underpinnings of common mental illnesses, including major depressive disorder (MDD) and associated traits such as cognition. However, studies are often limited to severe clinical cases with small sample sizes and most do not include replication. Here, we examine two relatively large samples with structural magnetic resonance imaging (MRI), measures of lifetime MDD and cognitive variables: Generation Scotland (GS subsample, N = 980) and UK Biobank (UKB, N = 8,900), for discovery and replication, using an exploratory approach. Regional measures of FreeSurfer derived cortical thickness (CT), cortical surface area (CSA), cortical volume (CV) and subcortical volume (subCV) were input into a clustering process, controlling for common covariates. The main analysis steps involved constructing participant K-nearest neighbour graphs and graph partitioning with Markov stability to determine optimal clustering of participants. Resultant clusters were (1) checked whether they were replicated in an independent cohort and (2) tested for associations with depression status and cognitive measures. Participants separated into two clusters based on structural brain measurements in GS subsample, with large Cohen's d effect sizes between clusters in higher order cortical regions, commonly associated with executive function and decision making. Clustering was replicated in the UKB sample, with high correlations of cluster effect sizes for CT, CSA, CV and subCV between cohorts across regions. The identified clusters were not significantly different with respect to MDD case-control status in either cohort (GS subsample: p_FDR  = .2239-.6585; UKB: p_FDR  = .2003-.7690). Significant differences in general cognitive ability were, however, found between the clusters for both datasets, for CSA, CV and subCV (GS subsample: d = 0.2529-.3490, p_FDR  < .005; UKB: d = 0.0868-0.1070, p_FDR  < .005). Our results suggest that there are replicable natural groupings of participants based on cortical and subcortical brain measures, which may be related to differences in cognitive performance, but not to the MDD case-control status.

Cohort profile for the STratifying Resilience and Depression Longitudinally (STRADL) study: A depression-focused investigation of Generation Scotland, using detailed clinical, cognitive, and neuroimaging assessments

STratifying Resilience and Depression Longitudinally (STRADL) is a population-based study built on the Generation Scotland: Scottish Family Health Study (GS:SFHS) resource. The aim of STRADL is to subtype major depressive disorder (MDD) on the basis of its aetiology, using detailed clinical, cognitive, and brain imaging assessments. The GS:SFHS provides an important opportunity to study complex gene-environment interactions, incorporating linkage to existing datasets and inclusion of early-life variables for two longitudinal birth cohorts. Specifically, data collection in STRADL included: socio-economic and lifestyle variables; physical measures; questionnaire data that assesses resilience, early-life adversity, personality, psychological health, and lifetime history of mood disorder; laboratory samples; cognitive tests; and brain magnetic resonance imaging. Some of the questionnaire and cognitive data were first assessed at the GS:SFHS baseline assessment between 2006-2011, thus providing longitudinal measures relevant to the study of depression, psychological resilience, and cognition. In addition, routinely collected historic NHS data and early-life variables are linked to STRADL data, further providing opportunities for longitudinal analysis. Recruitment has been completed and we consented and tested 1,188 participants.

Structural brain correlates of serum and epigenetic markers of inflammation in major depressive disorder

Inflammatory processes are implicated in the aetiology of Major Depressive Disorder (MDD); however, the relationship between peripheral inflammation, brain structure and depression remains unclear, partly due to complexities around the use of acute/phasic inflammatory biomarkers. Here, we report the first large-scale study of both serological and methylomic signatures of CRP (considered to represent acute and chronic measures of inflammation respectively) and their associations with depression status/symptoms, and structural neuroimaging phenotypes (T1 and diffusion MRI) in a large community-based sample (Generation Scotland; NMDD cases = 271, Ncontrols = 609). Serum CRP was associated with overall MDD severity, and specifically with current somatic symptoms- general interest (β = 0.145, PFDR = 6 × 10-4) and energy levels (β = 0.101, PFDR = 0.027), along with reduced entorhinal cortex thickness (β = -0.095, PFDR = 0.037). DNAm CRP was significantly associated with reduced global grey matter/cortical volume and widespread reductions in integrity of 16/24 white matter tracts (with greatest regional effects in the external and internal capsules, βFA= -0.12 to -0.14). In general, the methylation-based measures showed stronger associations with imaging metrics than serum-based CRP measures (βaverage = -0.15 versus βaverage = 0.01 respectively). These findings provide evidence for central effects of peripheral inflammation from both serological and epigenetic markers of inflammation, including in brain regions previously implicated in depression. This suggests that these imaging measures may be involved in the relationship between peripheral inflammation and somatic/depressive symptoms. Notably, greater effects on brain morphology were seen for methylation-based rather than serum-based measures of inflammation, indicating the importance of such measures for future studies.

Microstructural differences in white matter tracts across middle to late adulthood: a diffusion MRI study on 7167 UK Biobank participants

White matter fiber tracts demonstrate heterogeneous vulnerabilities to aging effects. Here, we estimated age-related differences in tract properties using UK Biobank diffusion magnetic resonance imaging data of 7167 47- to 76-year-old neurologically healthy people (3368 men and 3799 women). Tract properties in terms of generalized fractional anisotropy, axial diffusivity, radial diffusivity, and mean diffusivity were sampled on 76 fiber tracts; for each tract, age-related differences were estimated by fitting these indices against age in a linear model. This cross-sectional study demonstrated 4 age-difference patterns. The dominant pattern was lower generalized fractional anisotropy and higher axial diffusivity, radial diffusivity, and mean diffusivity with age, constituting 45 of 76 tracts, mostly involving the association, projection, and commissure fibers connecting the prefrontal lobe. The other 3 patterns constituted only 14 tracts, with atypical age differences in diffusion indices, and mainly involved parietal, occipital, and temporal cortices. By analyzing the large volume of diffusion magnetic resonance imaging data available from the UK Biobank, the study has provided a detailed description of heterogeneous age-related differences in tract properties over the whole brain which generally supports the myelodegeneration hypothesis.

The impact of brain iron accumulation on cognition: A systematic review

Iron is involved in many processes in the brain including, myelin generation, mitochondrial function, synthesis of ATP and DNA and the cycling of neurotransmitters. Disruption of normal iron homeostasis can result in iron accumulation in the brain, which in turn can partake in interactions which amplify oxidative damage. The development of MRI techniques for quantifying brain iron has allowed for the characterisation of the impact that brain iron has on cognition and neurodegeneration. This review uses a systematic approach to collate and evaluate the current literature which explores the relationship between brain iron and cognition. The following databases were searched in keeping with a predetermined inclusion criterion: Embase Ovid, PubMed and PsychInfo (from inception to 31^st March 2020). The included studies were assessed for study characteristics and quality and their results were extracted and summarised. This review identified 41 human studies of varying design, which statistically assessed the relationship between brain iron and cognition. The most consistently reported interactions were in the Caudate nuclei, where increasing iron correlated poorer memory and general cognitive performance in adulthood. There were also consistent reports of a correlation between increased Hippocampal and Thalamic iron and poorer memory performance, as well as, between iron in the Putamen and Globus Pallidus and general cognition. We conclude that there is consistent evidence that brain iron is detrimental to cognitive health, however, more longitudinal studies will be required to fully understand this relationship and to determine whether iron occurs as a primary cause or secondary effect of cognitive decline.

Sex differences in the association of photoperiod with hippocampal subfield volumes in older adults: A cross-sectional study in the UK Biobank cohort

INTRODUCTION

Even though seasonal and sex-dependent changes in hippocampal and subfield volumes are well known in animals, little is known about changes in humans. We hypothesized that changes in photoperiod would predict changes in hippocampal subfield volumes and that this association would be different between females and males.

METHODS

A total of 10,033 participants ranging in age from 45 to 79 years were scanned by MRI in a single location as part of the UK Biobank project. Hippocampal subfield volumes were obtained using automated processing and segmentation algorithms using the developmental version of the FreeSurfer v 6.0. Photoperiod was defined as the number of hours between sunrise and sunset on the day of scan.

RESULTS

Photoperiod correlated positively with total hippocampal volume and all subfield volumes across participants as well as in each sex individually, with females showing greater seasonal variation in a majority of left subfield volumes compared with males. ANCOVAs revealed significant differences in rate of change in only left subiculum, CA-4, and GC-ML-DG between females and males. PLS showed highest loadings of hippocampal subfields in both females and males in GC-ML-DG, CA1, CA4, subiculum, and CA3 for left hemisphere and CA1, GC-ML-DG, CA4; subiculum and CA3 for right hemisphere in females; GC-ML-DG, CA1, subiculum, CA4 and CA3 for left hemisphere; CA1, GC-ML-DG, subiculum, CA4 and CA3 for right hemisphere in males.

CONCLUSION

The influence of day length on hippocampal volume has implications for modeling age-related decline in memory in older adults, and sex differences suggest an important role for hormones in these effects.

Blunted medial prefrontal cortico-limbic reward-related effective connectivity and depression

Major depressive disorder is a leading cause of disability and significant mortality, yet mechanistic understanding remains limited. Over the past decade evidence has accumulated from case-control studies that depressive illness is associated with blunted reward activation in the basal ganglia and other regions such as the medial prefrontal cortex. However it is unclear whether this finding can be replicated in a large number of subjects. The functional anatomy of the medial prefrontal cortex and basal ganglia has been extensively studied and the former has excitatory glutamatergic projections to the latter. Reduced effect of glutamatergic projections from the prefrontal cortex to the nucleus accumbens has been argued to underlie motivational disorders such as depression, and many prominent theories of major depressive disorder propose a role for abnormal cortico-limbic connectivity. However, it is unclear whether there is abnormal reward-linked effective connectivity between the medial prefrontal cortex and basal ganglia related to depression. While resting state connectivity abnormalities have been frequently reported in depression, it has not been possible to directly link these findings to reward-learning studies. Here, we tested two main hypotheses. First, mood symptoms are associated with blunted striatal reward prediction error signals in a large community-based sample of recovered and currently ill patients, similar to reports from a number of studies. Second, event-related directed medial prefrontal cortex to basal ganglia effective connectivity is abnormally increased or decreased related to the severity of mood symptoms. Using a Research Domain Criteria approach, data were acquired from a large community-based sample of subjects who participated in a probabilistic reward learning task during event-related functional MRI. Computational modelling of behaviour, model-free and model-based functional MRI, and effective connectivity dynamic causal modelling analyses were used to test hypotheses. Increased depressive symptom severity was related to decreased reward signals in areas which included the nucleus accumbens in 475 participants. Decreased reward-related effective connectivity from the medial prefrontal cortex to striatum was associated with increased depressive symptom severity in 165 participants. Decreased striatal activity may have been due to decreased cortical to striatal connectivity consistent with glutamatergic and cortical-limbic related theories of depression and resulted in reduced direct pathway basal ganglia output. Further study of basal ganglia pathophysiology is required to better understand these abnormalities in patients with depressive symptoms and syndromes.

Brainstem volume mediates seasonal variation in depressive symptoms: A cross sectional study in the UK Biobank cohort

Seasonal differences in mood and depressive symptoms affect a large percentage of the general population, with seasonal affective disorder (SAD) representing the most common presentation. SAD affects up to 3% of the world’s population, and it tends to be more predominant in females than males. The brainstem has been shown to be affected by photoperiodic changes, and that longer photoperiods are associated with higher neuronal density and decreased depressive-like behaviours. We predict that longer photoperiod days are associated with larger brainstem volumes and lower depressive scores, and that brainstem volume mediates the seasonality of depressive symptoms. Participants (N = 9289, 51.8% females and 48.1% males) ranging in age from 44 to 79 years were scanned by MRI at a single location. Photoperiod was found to be negatively correlated with low mood and anhedonia in females while photoperiod was found to be positively correlated with brainstem volumes. In females, whole brainstem, pons and medulla volumes individually mediated the relationship between photoperiod and both anhedonia and low mood, while midbrain volume mediated the relationship between photoperiod and anhedonia. No mediation effects were seen in males. Our study extends the understanding of the neurobiological factors that contribute to the pathophysiology of seasonal mood variations.

Association of Inflammation With Pronociceptive Brain Connections in Rheumatoid Arthritis Patients With Concomitant Fibromyalgia

OBJECTIVE

Rheumatoid arthritis (RA) patients with concomitant fibromyalgia (FM) exhibit alterations in brain connectivity synonymous with central sensitization. This study was undertaken to investigate how peripheral inflammation, the principal nociceptive stimulus in RA, interacts with brain connectivity in RA patients with FM.

METHODS

RA patients with concomitant FM and those without FM (FM+ and FM-, respectively; n = 27 per group) underwent functional connectivity magnetic resonance imaging. Seed-to-whole-brain functional connectivity analyses were conducted using seeds from the left mid/posterior insula and left inferior parietal lobule (IPL), which are regions that have been previously linked to FM symptoms and inflammation, respectively. The association between functional connectivity and erythrocyte sedimentation rate (ESR) was assessed in each group separately, followed by post hoc analyses to test for interaction effects. Cluster-level, family-wise error (FWE) rates were considered significant if the P value was less than 0.05.

RESULTS

The group of RA patients with FM and those without FM did not differ by age, sex, or ESR (P > 0.2). In FM+ RA patients, increased functional connectivity of the insula-left IPL, left IPL-dorsal anterior cingulate, and left IPL-medial prefrontal cortex regions correlated with higher levels of ESR (all FWE-corrected P < 0.05). Post hoc interaction analyses largely confirmed the relationship between ESR and connectivity changes as FM scores increased.

CONCLUSION

We report the first neurobiologic evidence that FM in RA may be linked to peripheral inflammation via pronociceptive patterns of brain connectivity. In patients with such "bottom-up" pain centralization, concomitant symptoms may partially respond to antiinflammatory treatments.

Validation and comparison of two automated methods for quantifying brain white matter hyperintensities of presumed vascular origin

Objectives

White matter hyperintensities (WMH) are a common imaging finding indicative of cerebral small vessel disease. Lesion segmentation algorithms have been developed to overcome issues arising from visual rating scales. In this study, we evaluated two automated methods and compared them to visual and manual segmentation to determine the most robust algorithm provided by the open-source Lesion Segmentation Toolbox (LST).

Methods

We compared WMH data from visual ratings (Scheltens’ scale) with those derived from algorithms provided within LST. We then compared spatial and volumetric WMH data derived from manually-delineated lesion maps with WMH data and lesion maps provided by the LST algorithms.

Results

We identified optimal initial thresholds for algorithms provided by LST compared with visual ratings (Lesion Growth Algorithm (LGA): initial κ and lesion probability thresholds, 0.5; Lesion Probability Algorithm (LPA) lesion probability threshold, 0.65). LGA was found to perform better then LPA compared with manual segmentation.

Conclusion

LGA appeared to be the most suitable algorithm for quantifying WMH in relation to cerebral small vessel disease, compared with Scheltens’ score and manual segmentation. LGA offers a user-friendly, effective WMH segmentation method in the research environment.

Functional and structural magnetic resonance imaging correlates of fatigue in patients with rheumatoid arthritis

Objectives

Fatigue is a major burden among patients with RA, yet is poorly understood. We sought to conduct the first imaging study to investigate the neurobiological correlates of fatigue in RA and to improve upon the methodological limitations of previous neuroimaging studies that have investigated this symptom in other populations.

Methods

Chronically fatigued RA patients were clinically characterized before undertaking a combined functional and structural mode MRI brain scan. The functional sequences were acquired during a fatigue-evoking task, then network-to-whole-brain analyses were undertaken. The structural analyses employed voxel-based morphometry in order to quantify regional grey matter volume. The scan was repeated 6 months later to test reproducibility.

Results

Fifty-four participants attended both scans [n = 41 female; baseline mean (s.d.) age 54.94 (11.41) years]. A number of significant functional and structural neural imaging correlates of fatigue were identified. Notably, patients who reported higher levels of fatigue demonstrated higher levels of functional connectivity between the Dorsal Attention Network and medial prefrontal gyri, a finding that was reproduced in the repeat scans. Structurally, greater putamen grey matter volumes significantly correlated with greater levels of fatigue.

Conclusion

Fatigue in RA is associated with functional and structural MRI changes in the brain. The newly identified and reproduced neural imaging correlates provide a basis for future targeting and stratification of this key patient priority.

Motion During Acquisition is Associated With fMRI Brain Entropy

Measures of fMRI brain entropy have been used to investigate age and disease related neural changes. However, it is unclear if movement in the scanner is associated with brain entropy after geometric correction for movement. As age and disease can affect motor control, quantifying and correcting for the influence of movement will avoid false findings. This paper examines the influence of head motion on fMRI brain entropy. Resting-state and task-based fMRI data from 281 individuals born in Aberdeen between 1950 and 1956 were analyzed. The images were realigned, followed by nuisance regression of the head motion parameters. The images were either high-pass filtered (0.008 Hz) or band-pass (0.008-0.1 Hz) filtered in order to compare the two methods; fuzzy approximate entropy and fuzzy sample entropy were calculated for every voxel. Motion was quantified as the mean displacement and mean rotation in three dimensions. Greater mean motion was correlated with decreased entropy for all four methods of calculating entropy. Different movement characteristics produce different patterns of associations, which appear to be artefact. However, across all motion metrics, entropy calculation methods, and scan conditions, a number of regions consistently show a significant negative association: the right cerebellar crus, left precentral gyrus (primary motor cortex), the left postcentral gyrus (primary somatosensory cortex), and the opercular part of the left inferior frontal gyrus. The robustness of our findings at these locations suggests that decreased entropy in specific brain regions may be a marker for decreased motor control.

The Neurobiology of Personal Control During Reward Learning and Its Relationship to Mood

BACKGROUND

The majority of reward learning neuroimaging studies have not focused on the motivational aspects of behavior, such as the inherent value placed on choice itself. The experience and affective value of personal control may have particular relevance for psychiatric disorders, including depression.

METHODS

We adapted a functional magnetic resonance imaging reward task that probed the value placed on exerting control over one's decisions, termed choice value, in 122 healthy participants. We examined activation associated with choice value; personally chosen versus passively received rewards; and reinforcement learning metrics, such as prediction error. Relationships were tested between measures of motivational orientation (categorized as autonomy, control, and impersonal) and subclinical depressive symptoms.

RESULTS

Anticipating personal choice activated left insula, cingulate, right inferior frontal cortex, and ventral striatum (p_{familywise error-corrected} < .05). Ventral striatal activations to choice were diminished in participants with subclinical depressive symptoms. Personally chosen rewards were associated with greater activation of the insula and inferior frontal gyrus, cingulate cortex, hippocampus, thalamus, and substantia nigra compared with rewards that were passively received. In participants who felt they had little control over their own behavior (impersonal orientation), prediction error signals in nucleus accumbens were stronger during passive trials.

CONCLUSIONS

Previous findings regarding personal choice have been verified and advanced through the use of both reinforcement learning models and correlations with psychopathology. Personal choice has an impact on the extended reward network, potentially allowing these clinically important areas to be addressed in ways more relevant to personality styles, self-esteem, and symptoms such as motivational anhedonia.

Neural Indicators of Fatigue in Chronic Diseases: A Systematic Review of MRI Studies

While fatigue is prevalent in chronic diseases, the neural mechanisms underlying this symptom remain unknown. Magnetic resonance imaging (MRI) has the potential to enable us to characterize this symptom. The aim of this review was to gather and appraise the current literature on MRI studies of fatigue in chronic diseases. We systematically searched the following databases: MedLine, PsycInfo, Embase and Scopus (inception to April 2016). We selected studies according to a predefined inclusion and exclusion criteria. We assessed the quality of the studies and conducted descriptive statistical analyses. We identified 26 studies of varying design and quality. Structural and functional MRI, alongside diffusion tensor imaging (DTI) and functional connectivity (FC) studies, identified significant brain indicators of fatigue. The most common regions were the frontal lobe, parietal lobe, limbic system and basal ganglia. Longitudinal studies offered more precise and reliable analysis. Brain structures found to be related to fatigue were highly heterogeneous, not only between diseases, but also for different studies of the same disease. Given the different designs, methodologies and variable results, we conclude that there are currently no well-defined brain indicators of fatigue in chronic diseases.

A multi-modal MRI study of the central response to inflammation in rheumatoid arthritis

It is unknown how chronic inflammation impacts the brain. Here, we examined whether higher levels of peripheral inflammation were associated with brain connectivity and structure in 54 rheumatoid arthritis patients using functional and structural MRI. We show that higher levels of inflammation are associated with more positive connections between the inferior parietal lobule (IPL), medial prefrontal cortex, and multiple brain networks, as well as reduced IPL grey matter, and that these patterns of connectivity predicted fatigue, pain and cognitive dysfunction. At a second scan 6 months later, some of the same patterns of connectivity were again associated with higher peripheral inflammation. A graph theoretical analysis of whole-brain functional connectivity revealed a pattern of connections spanning 49 regions, including the IPL and medial frontal cortex, that are associated with peripheral inflammation. These regions may play a critical role in transducing peripheral inflammatory signals to the central changes seen in rheumatoid arthritis.

Many diseases, such as rheumatoid arthritis, are characterized by a chronic inflammatory state, but it is not clear whether or how this affects the brain. Here, the authors show that the severity of on-going inflammation predicts altered functional brain connectivity in people with rheumatoid arthritis.

Increased neural response to social rejection in major depression

BACKGROUND

Being a part of community is critical for survival and individuals with major depressive disorder (MDD) have a greater sensitivity to interpersonal stress that makes them vulnerable to future episodes. Social rejection is a critical risk factor for depression and it is said to increase interpersonal stress and thereby impairing social functioning. It is therefore critical to understand the neural correlates of social rejection in MDD.

METHODS

To this end, we scanned 15 medicated MDD and 17 healthy individuals during a modified cyberball passing game, where participants were exposed to increasing levels of social exclusion. Neural responses to increasing social exclusion were investigated and compared between groups.

RESULTS

We showed that compared to controls, MDD individuals exhibited greater amygdala, insula, and ventrolateral prefrontal cortex activation to increasing social exclusion and this correlated negatively with hedonic tone and self-esteem scores across all participants.

CONCLUSIONS

These preliminary results support the hypothesis that depression is associated with hyperactive response to social rejection. These findings highlight the importance of studying social interactions in depression, as they often lead to social withdrawal and isolation.

Neural changes related to motion processing in healthy aging

Behavioral studies have found a striking decline in the processing of low-level motion in healthy aging whereas the processing of more relevant and familiar biological motion is relatively preserved. This functional magnetic resonance imaging (fMRI) study investigated the neural correlates of low-level radial motion processing and biological motion processing in 19 healthy older adults (age range 62–78 years) and in 19 younger adults (age range 20–30 years). Brain regions related to both types of motion stimuli were evaluated and the magnitude and time courses of activation in those regions of interest were calculated. Whole-brain comparisons showed increased temporal and frontal activation in the older group for low-level motion but no differences for biological motion. Time-course analyses in regions of interest known to be involved in both types of motion processing likewise did not reveal any age differences for biological motion. Our results show that low-level motion processing in healthy aging requires the recruitment of additional resources, whereas areas related to the processing of biological motion processing seem to be relatively preserved.

A brain imaging repository of normal structural MRI across the life course: Brain Images of Normal Subjects (BRAINS)

The Brain Images of Normal Subjects (BRAINS) Imagebank (http://www.brainsimagebank.ac.uk) is an integrated repository project hosted by the University of Edinburgh and sponsored by the Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) collaborators. BRAINS provide sharing and archiving of detailed normal human brain imaging and relevant phenotypic data already collected in studies of healthy volunteers across the life-course. It particularly focusses on the extremes of age (currently older age, and in future perinatal) where variability is largest, and which are under-represented in existing databanks. BRAINS is a living imagebank where new data will be added when available. Currently BRAINS contains data from 808 healthy volunteers, from 15 to 81years of age, from 7 projects in 3 centres. Additional completed and ongoing studies of normal individuals from 1st to 10th decades are in preparation and will be included as they become available. BRAINS holds several MRI structural sequences, including T1, T2, T2* and fluid attenuated inversion recovery (FLAIR), available in DICOM (http://dicom.nema.org/); in future Diffusion Tensor Imaging (DTI) will be added where available. Images are linked to a wide range of 'textual data', such as age, medical history, physiological measures (e.g. blood pressure), medication use, cognitive ability, and perinatal information for pre/post-natal subjects. The imagebank can be searched to include or exclude ranges of these variables to create better estimates of 'what is normal' at different ages.

Nonlinear complexity analysis of brain FMRI signals in schizophrenia

We investigated the differences in brain fMRI signal complexity in patients with schizophrenia while performing the Cyberball social exclusion task, using measures of Sample entropy and Hurst exponent (H). 13 patients meeting diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM IV) criteria for schizophrenia and 16 healthy controls underwent fMRI scanning at 1.5 T. The fMRI data of both groups of participants were pre-processed, the entropy characterized and the Hurst exponent extracted. Whole brain entropy and H maps of the groups were generated and analysed. The results after adjusting for age and sex differences together show that patients with schizophrenia exhibited higher complexity than healthy controls, at mean whole brain and regional levels. Also, both Sample entropy and Hurst exponent agree that patients with schizophrenia have more complex fMRI signals than healthy controls. These results suggest that schizophrenia is associated with more complex signal patterns when compared to healthy controls, supporting the increase in complexity hypothesis, where system complexity increases with age or disease, and also consistent with the notion that schizophrenia is characterised by a dysregulation of the nonlinear dynamics of underlying neuronal systems.

The shared neural basis of empathy and facial imitation accuracy

Empathy involves experiencing emotion vicariously, and understanding the reasons for those emotions. It may be served partly by a motor simulation function, and therefore share a neural basis with imitation (as opposed to mimicry), as both involve sensorimotor representations of intentions based on perceptions of others' actions. We recently showed a correlation between imitation accuracy and Empathy Quotient (EQ) using a facial imitation task and hypothesised that this relationship would be mediated by the human mirror neuron system. During functional Magnetic Resonance Imaging (fMRI), 20 adults observed novel 'blends' of facial emotional expressions. According to instruction, they either imitated (i.e. matched) the expressions or executed alternative, pre-prescribed mismatched actions as control. Outside the scanner we replicated the association between imitation accuracy and EQ. During fMRI, activity was greater during mismatch compared to imitation, particularly in the bilateral insula. Activity during imitation correlated with EQ in somatosensory cortex, intraparietal sulcus and premotor cortex. Imitation accuracy correlated with activity in insula and areas serving motor control. Overlapping voxels for the accuracy and EQ correlations occurred in premotor cortex. We suggest that both empathy and facial imitation rely on formation of action plans (or a simulation of others' intentions) in the premotor cortex, in connection with representations of emotional expressions based in the somatosensory cortex. In addition, the insula may play a key role in the social regulation of facial expression.

Do mirror neuron areas mediate mu rhythm suppression during imitation and action observation?

Mu rhythm is an EEG measure of resting motor neurons, which is normally suppressed by input because of action observation or movement execution. This characteristic has caused mu suppression to be used as proxy marker for mirror neuron activation. However, there is little direct evidence that fluctuations in mu rhythm suppression reflect concurrent fluctuations in mirror neuron activity. A manual imitation paradigm was used to look at correlations between mu rhythm and BOLD response, by recording sequential EEG and fMRI measures to allow within-subject correlation analyses. Participants were instructed to imitate or observe actions involving the movement of a handle with their right hand. Mu power modulation, defined as mu power changes between conditions, correlated negatively with BOLD response in right inferior parietal lobe, premotor cortex and inferior frontal gyrus; putative mirror neuron areas. Clusters were also identified in bilateral cerebellum, left medial frontal gyrus, right temporal lobe and thalamus. This suggests that mu suppression involves a range of structures that modulate motor preparation activities and are sensitive to visual input, including but not restricted to the human analogue of the mirror neuron system.

Neural correlates of individual differences in manual imitation fidelity

Imitation is crucial for social learning, and so it is important to identify what determines between-subject variability in imitation fidelity. This might help explain what makes some people, like those with social difficulties such as in autism spectrum disorder (ASD), significantly worse at performance on these tasks than others. A novel paradigm was developed to provide objective measures of imitation fidelity in which participants used a touchscreen to imitate videos of a model drawing different shapes. Comparisons between model and participants' kinematic data provided three measures of imitative fidelity. We hypothesized that imitative ability would predict variation in BOLD signal whilst performing a simple imitation task in the MRI-scanner. In particular, an overall measure of accuracy (correlation between model and imitator) would predict activity in the overarching imitation system, whereas bias would be subject to more general aspects of motor control. Participants lying in the MRI-scanner were instructed to imitate different grips on a handle, or to watch someone or a circle moving the handle. Our hypothesis was partly confirmed as correlation between model and imitator was mediated by somatosensory cortex but also ventromedial prefrontal cortex, and bias was mediated mainly by cerebellum but also by the medial frontal and parietal cortices and insula. We suggest that this variance differentially reflects cognitive functions such as feedback-sensitivity and reward-dependent learning, contributing significantly to variability in individuals' imitative abilities as characterized by objective kinematic measures.

Changes in the sulcal size associated with autism spectrum disorder revealed by sulcal morphometry

Autism spectrum disorder (ASD) is a complex, neurodevelopmental disorder with various structural abnormalities for different patient groups. Because of the heterogeneity of the disorder, several biomarkers have been suggested so far. Here, we explore the potential of sulcal surface and length as biomarkers. Three-dimensional T1-weighted images of 15 adolescents of normal intelligence with ASD and 15 age-, sex-, and intelligence quotient-matched control adolescents were analysed using Brainvisa 4.0 (http://www.brainvisa.info), which automatically extracts the cortical folds and labels them as 59 sulcal pieces. For each sulcus, the surface, length, and mean geodesic depth were computed using morphometry analysis within this software package. General linear model was conducted to compare the estimated values for the two groups, ASD and control. In the ASD group, the left insula and the right intraparietal sulcus (IPS) had significantly higher values for surface and length, respectively. Nonetheless for all sulcal pieces, the mean geodesic depth was not significantly different between the two groups. Our results suggest that sulcal surface and length can have correlation with morphological changes of cortex in ASD. Greater surface area and length in insula and IPS, respectively, may reflect greater folding. This could result in greater separation of functions with an impact upon the integrative functions of these regions.

Inter-individual differences in fMRI entropy measurements in old age

We investigated the association between individual differences in cognitive performance in old age and the approximate entropy (ApEn) measured from functional magnetic resonance imaging (fMRI) data acquired from 40 participants of the Aberdeen Birth Cohort 1936 (ABC1936), while undergoing a visual information processing task: inspection time (IT). Participants took a version of the Moray House Test (MHT) No. 12 at age 11, a valid measure of childhood intelligence. The same individuals completed a test of non-verbal reasoning (Raven's Standard Progressive Matrices [RPM]) aged about 68 years. The IT, MHT and RPM scores were used as indicators of cognitive performance. Our results show that higher regional signal entropy is associated with better cognitive performance. This finding was independent of ability in childhood but not independent of current cognitive ability. ApEn is used for the first time to identify a potential source of individual differences in cognitive ability using fMRI data.

Mine and me: exploring the neural basis of object ownership

Previous research has shown that encoding information in the context of self-evaluation leads to memory enhancement, supported by activation in ventromedial pFC. Recent evidence suggests that similar self-memory advantages can be obtained under nonevaluative encoding conditions, such as when object ownership is used to evoke self-reference. Using fMRI, the current study explored the neural correlates of object ownership. During scanning, participants sorted everyday objects into self-owned or other-owned categories. Replicating previous research, a significant self-memory advantage for the objects was observed (i.e., self-owned > other-owned). In addition, encoding self-owned items was associated with unique activation in posterior dorsomedial pFC (dMPFC), left insula, and bilateral supramarginal gyri (SMG). Subsequent analysis showed that activation in a subset of these regions (dMPFC and left SMG) correlated with the magnitude of the self-memory advantage. Analysis of the time-to-peak data suggested a temporal model for processing ownership in which initial activation of dMPFC spreads to SMG and insula. These results indicate that a self-memory advantage can be elicited by object ownership and that this effect is underpinned by activity in a neural network that supports attentional, reward, and motor processing.

Stereotype-based modulation of person perception

A core social-psychological question is how cultural stereotypes shape our encounters with other people. While there is considerable evidence to suggest that unexpected targets-such as female airline pilots and male nurses-impact the inferential and memorial aspects of person construal, it has yet to be established if early perceptual operations are similarly sensitive to the stereotype-related status of individuals. To explore this issue, the current investigation measured neural activity while participants made social (i.e., sex categorization) and non-social (i.e., dot detection) judgments about men and women portrayed in expected and unexpected occupations. When participants categorized the stimuli according to sex, stereotype-inconsistent targets elicited increased activity in cortical areas associated with person perception and conflict resolution. Comparable effects did not emerge during a non-social judgment task. These findings begin to elucidate how and when stereotypic beliefs modulate the formation of person percepts in the brain.

Established donepezil treatment modulates task relevant regional brain activation in early Alzheimer's disease

Neuroimaging studies of cholinesterase inhibitor (ChEI) treatment in Alzheimer's disease (AD) have shown the different short and long term actions of ChEIs. fMRI studies of the ChEI donepezil have focused on its short to medium term action without exploring the effects of established treatment. In this exploratory study the effect of 20 weeks donepezil treatment on regional brain activity was measured with fMRI in patients with mild AD. Twelve patients with probable AD and nine age-matched controls were assessed with a Pyramids and Palm Trees semantic association fMRI paradigm and an n-back working memory fMRI paradigm. In the patient group only, the assessment was repeated after 20 weeks of treatment. After treatment, differences from normal healthy elderly became more pronounced. There was also a spread of deactivation which at retest was detectable in task relevant areas. Behaviourally, however, there were no significant differences between group baseline and retest scores, with a range of performance probably reflecting variation in drug efficacy across patients. Parametric analyses established that increased behavioural scores at retest correlated significantly with higher activation levels in non task relevant areas. Behavioural stability with donepezil treatment was not paralleled by the pattern of improved task specific brain activation reported in similar studies of other ChEIs. This is arguably related to the different mechanisms of action of the ChEIs and might be a clinical correlate of the reported synaptic upregulation following long term donepezil treatment.

Puddles, parties, and professors: linking word categorization to neural patterns of visuospatial coding

Behavioral evidence suggests that during word processing people spontaneously map object, valence, and power information to locations in vertical space. Specifically, whereas "overhead" (e.g., attic), positive (e.g., party), and powerful nouns (e.g., professor) are associated with "up," "underfoot" (e.g., carpet), negative (e.g., accident), and powerless nouns (e.g., assistant) are associated with "down." What has yet to be elucidated, however, is the precise nature of these effects. To explore this issue, an fMRI experiment was undertaken, during which participants were required to categorize the position in which geometrical shapes appeared on a computer screen (i.e., upper or lower part of the display). In addition, they also judged a series of words with regard to location (i.e., up vs. down), valence (i.e., good vs. bad), and power (i.e., powerful vs. powerless). Using multivoxel pattern analysis, it was found that classifiers that successfully distinguished between the positions of shapes in subregions of the inferior parietal lobe also provided discriminatory information to separate location and valence, but not power word judgments. Correlational analyses further revealed that, for location words, pattern transfer was more successful the stronger was participants' propensity to use visual imagery. These findings indicate that visual coding and conceptual processing can elicit common representations of verticality but that divergent mechanisms may support the reported effects.