A systematic review of resting-state functional connectivity in obesity: Refining current neurobiological frameworks and methodological considerations moving forward.

Obesity is the second most common cause of preventable morbidity worldwide. Resting-state functional magnetic resonance imaging (fMRI) has been used extensively to characterise altered communication between brain regions in individuals with obesity, though findings from this research have not yet been systematically evaluated within the context of prominent neurobiological frameworks. This systematic review aggregated resting-state fMRI findings in individuals with obesity and evaluated the contribution of these findings to current neurobiological models. Findings were considered in relation to a triadic model of problematic eating, outlining disrupted communication between reward, inhibitory, and homeostatic systems. We identified a pattern of consistently increased orbitofrontal and decreased insula cortex resting-state functional connectivity in individuals with obesity in comparison to healthy weight controls. BOLD signal amplitude was also increased in people with obesity across studies, predominantly confined to subcortical regions, including the hippocampus, amygdala, and putamen. We posit that altered orbitofrontal cortex connectivity may be indicative of a shift in the valuation of food-based rewards and that dysfunctional insula connectivity likely contributes to altered homeostatic signal processing. Homeostatic violation signals in obesity may be maintained despite satiety, thereby 'hijacking' the executive system and promoting further food intake. Moving forward, we provide a roadmap for more reliable resting-state and task-based functional connectivity experiments, which must be reconciled within a common framework if we are to uncover the interplay between psychological and biological factors within current theoretical frameworks.

Modelling the Anatomical Distribution of Neurological Events in COVID-19 Patients: A Systematic Review.

BACKGROUND: Neuropathology caused by the coronavirus disease 2019 (COVID-19) has been reported across several studies. The characterisation of the spatial distribution of these pathology remains critical to assess long and short-term neurological sequelae of COVID-19. To this end, Mathematical models can be used to characterise the location and aetiologies underlying COVID-19-related neuropathology. METHOD: We performed a systematic review of the literature to quantify the locations of small neurological events identified with magnetic resonance imaging (MRI) among COVID-19 patients. Neurological events were localised into the Desikan-Killiany grey and white matter atlases. A mathematical network diffusion model was then used to test whether the spatial distribution of neurological events could be explained via a linear spread through the structural connectome of the brain. FINDINGS: We identified 35 articles consisting of 123 patients that assessed the spatial distribution of small neurological events among COVID-19 patients. Of these, 91 patients had grey matter changes, 95 patients had white matter changes and 72 patients had confirmed cerebral microbleeds. White matter events were observed within 14 of 42 white matter bundles from the IIT atlas. The highest proportions (26%) of events were observed within the bilateral corticospinal tracts. The splenium and middle of the corpus callosum were affected in 14% and 9% of the cases respectively. Grey matter events were spatially distributed in the 41 brain regions within the Desikan-Killiany atlas. The highest proportions (∼10%) of the events were observed in areas including the bilateral superior temporal, precentral, and lateral occipital cortices. Sub-cortical events were most frequently identified in the Pallidum. The application of a mathematical network diffusion model suggested that the spatial pattern of the small neurological events in COVID-19 can be modelled with a linear diffusion of spread from epicentres in the bilateral cerebellum and basal ganglia (Pearson's r =0.41, p <0.001, corrected). INTERPRETATION: To our knowledge, this is the first study to systematically characterise the spatial distribution of small neurological events in COVID-19 patients and test whether the spatial distribution of these events can be explained by a linear diffusion spread model. The location of neurological events is consistent with commonly identified neurological symptoms including alterations in conscious state among COVID-19 patients that require brain imaging. Given the prevalence and severity of these manifestations, clinicians should carefully monitor neurological symptoms within COVID-19 patients and their potential long-term sequelae .