Reliable quantification of white matter hyperintensities of presumed vascular origin (WMHs) is increasingly needed, given the presence of these MRI findings in patients with several neurological and vascular disorders, as well as in elderly healthy subjects. We present BIANCA (Brain Intensity AbNormality Classification Algorithm), a fully automated, supervised method for WMH detection, based on the k-nearest neighbour (k-NN) algorithm. Relative to previous k-NN based segmentation methods, BIANCA offers different options for weighting the spatial information, local spatial intensity averaging, and different options for the choice of the number and location of the training points. BIANCA is multimodal and highly flexible so that the user can adapt the tool to their protocol and specific needs. We optimised and validated BIANCA on two datasets with different MRI protocols and patient populations (a "predominantly neurodegenerative" and a "predominantly vascular" cohort). BIANCA was first optimised on a subset of images for each dataset in terms of overlap and volumetric agreement with a manually segmented WMH mask. The correlation between the volumes extracted with BIANCA (using the optimised set of options), the volumes extracted from the manual masks and visual ratings showed that BIANCA is a valid alternative to manual segmentation. The optimised set of options was then applied to the whole cohorts and the resulting WMH volume estimates showed good correlations with visual ratings and with age. Finally, we performed a reproducibility test, to evaluate the robustness of BIANCA, and compared BIANCA performance against existing methods. Our findings suggest that BIANCA, which will be freely available as part of the FSL package, is a reliable method for automated WMH segmentation in large cross-sectional cohort studies.

Background: Aberrant social behavior is a defining symptom of frontotemporal dementia (FTD) and may eventually occur in all syndromes composing the FTD spectrum. Two main behavioral abnormalities have been described: apathy and disinhibition, but their neuroanatomical correlates remain underspecified. Methods: Sixty-two patients with a clinical diagnosis of FTD participated in the study. Voxel-based morphometry of MRI data was performed to explore the association between gray matter loss and severity of the two behavioral profiles as measured by the Apathy and Disinhibition subscales of the Frontal Systems Behavior Scale. Results: Compared with a group of controls, the FTD group showed extensive bilateral atrophy predominantly involving frontal and temporal lobes. Within the FTD group, the severity of apathy correlated with atrophy in the right dorsolateral prefrontal cortex. The severity of disinhibition correlated with atrophy in the right nucleus accumbens, right superior temporal sulcus, and right mediotemporal limbic structures. Conclusions: Prefrontal and temporal regions are differentially associated with apathy and disinhibition. Our results support the view that successful execution of complex social behaviors relies on the integration of social knowledge and executive functions, represented in the prefrontal cortex, and reward attribution and emotional processing, represented in mesolimbic structures.

We propose an integrative cognitive neuroscience framework for understanding the cognitive and neural foundations of religious belief. Our analysis reveals 3 psychological dimensions of religious belief (God's perceived level of involvement, God's perceived emotion, and doctrinal/experiential religious knowledge), which functional MRI localizes within networks processing Theory of Mind regarding intent and emotion, abstract semantics, and imagery. Our results are unique in demonstrating that specific components of religious belief are mediated by well-known brain networks, and support contemporary psychological theories that ground religious belief within evolutionary adaptive cognitive functions.

Objective: To examine functional connectivity within the basal ganglia network (BGN) in a group of cognitively normal patients with early Parkinson disease (PD) on and off medication compared to age- and sex-matched healthy controls (HC), and to validate the findings in a separate cohort of participants with PD. Methods: Participants were scanned with resting-state fMRI (RS-fMRI) at 3T field strength. Resting-state networks were isolated using independent component analysis. A BGN template was derived from 80 elderly HC participants. BGN maps were compared between 19 patients with PD on and off medication in the discovery group and 19 age- and sex-matched controls to identify a threshold for optimal group separation. The threshold was applied to 13 patients with PD (including 5 drug-naive) in the validation group to establish reproducibility of findings. Results: Participants with PD showed reduced functional connectivity with the BGN in a wide range of areas. Administration of medication significantly improved connectivity. Average BGN connectivity differentiated participants with PD from controls with 100% sensitivity and 89.5% specificity. The connectivity threshold was tested on the validation cohort and achieved 85% accuracy. Conclusions: We demonstrate that resting functional connectivity, measured with MRI using an observer-independent method, is reproducibly reduced in the BGN in cognitively intact patients with PD, and increases upon administration of dopaminergic medication. Our results hold promise for RS-fMRI connectivity as a biomarker in early PD. Classification of evidence: This study provides Class III evidence that average connectivity in the BGN as measured by RS-fMRI distinguishes patients with PD from age- and sex-matched controls.

APOE-ε4 is best known as a risk factor for Alzheimer's disease (AD). Consequently, there is considerable research interest in understanding whether APOE-ε4 influences cognition in healthy adults. Despite a substantial literature reporting effects of APOE genotype on cognition, findings are inconsistent. In particular, it is challenging to separate whether cognitive deficits in APOE-ε4 carriers reflect the influence of prodromal dementia pathology ("prodromal hypothesis"), or a direct contribution of APOE genotype to individual differences ("phenotype hypothesis"). Variable methodology across studies further complicates the issue. These challenges have limited what can be learnt about the processes underlying cognitive ageing and dementia by studying the influence of APOE genotype on cognition. In this review, we focus on the two compatible neurobiological mechanisms by which APOE genotype may influence cognition in healthy adults (prodromal and phenotype). We summarise the behavioural evidence for the influence of APOE on cognition in non-demented adults and explore key methodological challenges for disentangling the cognitive effects of different neurobiological mechanisms of APOE. Evidence suggests that at least some APOE-ε4 cognitive deficits are due to early AD pathology, whilst sensitive measures of cognition are beginning to reveal subtle cognitive differences between APOE genotypes in mid-adulthood, prior to the onset of the AD prodromal period. We conclude with recommendations for future research to investigate the cognitive consequences of neurobiological processes affected by APOE and maximise the translational potential of this research.