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Characterising ongoing brain aging and baseline effects from cross-sectional data
“Brain age delta” is the difference between age estimated from brain imaging data and actual age. Positive delta in adults is normally interpreted as implying that an individual is aging (or has aged) faster than the population norm, an indicator of unhealthy aging. Unfortunately, from cross-sectional (single timepoint) imaging data, it is impossible to know whether a single individual’s positive delta reflects a state of faster ongoing aging, or an unvarying trait (in other words, a “historical baseline effect” in the context of the population being studied). However, for a cross-sectional dataset comprising many individuals, one could attempt to disambiguate varying aging rates from fixed baseline effects. We present a method for doing this, and show that for the common approach of estimating a single delta per subject, baseline effects are likely to dominate. If instead one estimates multiple biologically distinct modes of brain aging, we find that some modes do reflect aging rates varying strongly across subjects. We demonstrate this, and verify our modelling, using longitudinal (two timepoint) data from 4,400 participants in UK Biobank. In addition, whereas previous work found incompatibility between cross-sectional and longitudinal brain aging, we show that careful data processing does show consistency between cross-sectional and longitudinal results.
The effects of lacosamide, pregabalin, and tapentadol on peripheral nerve excitability: A randomized, double-blind, placebo-controlled, crossover, multi-center trial in healthy subjects.
BACKGROUND: Chronic pain is a leading cause of disability globally, with limited treatment options and frequent adverse effects. The IMI-PainCare-BioPain project aimed to enhance analgesic drug development by standardizing biomarkers. This study, IMI2-PainCare-BioPain-RCT1, evaluated the effects of lacosamide, pregabalin, and tapentadol on peripheral nerve excitability in healthy subjects through a randomized, double-blind, placebo-controlled crossover trial. METHODS: The study included 43 healthy participants aged 18-45 years. Participants underwent four treatment periods where they received single doses of lacosamide (200 mg), pregabalin (150 mg), tapentadol (100 mg), or placebo. High-frequency stimulation was applied to induce hyperalgesia. The two primary endpoints were changes in Strength Duration Time Constant (SDTC) in large sensory and motor fibers between lacosamide and placebo periods at the first post-dose timepoint compared to baseline (60 min). Other predefined endpoints included recovery cycle, threshold electrotonus (TEd), and S2 accommodation as well as effects of pregabalin and tapentadol. RESULTS: Lacosamide statistically significantly reduced SDTC in large sensory fibers (mean reduction 0.04 (95% CI 0.01-0.08), p = 0.012) and in motor fibers (mean reduction 0.04 (95% CI 0.00-0.07), p = 0.039) but had no effect on small sensory fibers at the first timepoint compared to placebo. There were no effects of pregabalin and tapentadol on SDTC. Of other predefined endpoints, lacosamide produced statistically significant changes in subexcitability, S2 accommodation TEd(peak), and TEd40(Accom) in large sensory fibers. No statistically significant changes were observed in refractoriness, relative refractory period, or accommodation half-time at the first timepoint compared to placebo. CONCLUSIONS: This study demonstrates that nerve excitability testing can detect pharmacodynamic effects on large myelinated fibers in healthy subjects. Lacosamide statistically significantly reduced peripheral nerve excitability, particularly in large sensory fibers.
The lifetime accumulation of multimorbidity and its influence on dementia risk: a UK Biobank study.
The number of people living with dementia worldwide is projected to reach 150 million by 2050, making prevention a crucial priority for health services. The co-occurrence of two or more chronic health conditions, termed multimorbidity, occurs in up to 80% of dementia patients, making multimorbidity an important risk factor for dementia. However, we lack an understanding of the specific health conditions, and their age of onset, that drive the link between multimorbidity and dementia. Using data from 282 712 participants of the UK Biobank, we defined the sequential patterns of accumulation of 46 chronic conditions over the life course. By grouping individuals based on their life history of chronic illness, we show here that the risk of incident dementia can be stratified by both the type and timing of their accumulated chronic conditions. We identified several distinct clusters of multimorbidity throughout the lifespan (cardiometabolic, mental health, neurovascular, peripheral vascular, eye diseases and low/no multimorbidity). We observed that the odds of developing dementia varied based on when these comorbidities were diagnosed. Until midlife (age 55), the accumulation of cardiometabolic conditions, such as coronary heart disease, atrial fibrillation, and diabetes, was most strongly associated with dementia risk. However, from 55 to 70 years, the accumulation of mental health conditions, such as anxiety and depression, as well as neurovascular conditions, such as stroke and transient ischaemic attack, was associated with an over 2-fold increase in dementia risk compared with low multimorbidity. Importantly, individuals who continuously and sequentially accumulate cardiometabolic, mental health, and neurovascular conditions were at greatest risk. The age-dependent role of multimorbidity in predicting dementia risk could be used for early stratification of individuals into high- and low-risk groups and could inform targeted prevention strategies based on a person's prior history of chronic disease.
The mouse motor system contains multiple premotor areas and partially follows human organizational principles.
While humans are known to have several premotor cortical areas, secondary motor cortex (M2) is often considered to be the only higher-order motor area of the mouse brain and is thought to combine properties of various human premotor cortices. Here, we show that axonal tracer, functional connectivity, myelin mapping, gene expression, and optogenetics data contradict this notion. Our analyses reveal three premotor areas in the mouse, anterior-lateral motor cortex (ALM), anterior-lateral M2 (aM2), and posterior-medial M2 (pM2), with distinct structural, functional, and behavioral properties. By using the same techniques across mice and humans, we show that ALM has strikingly similar functional and microstructural properties to human anterior ventral premotor areas and that aM2 and pM2 amalgamate properties of human pre-SMA and cingulate cortex. These results provide evidence for the existence of multiple premotor areas in the mouse and chart a comparative map between the motor systems of humans and mice.
Incidental Encoding of Objects during Search Is Stronger Than Intentional Memorization due to Increased Recollection Rather Than Familiarity
Abstract Most memory is not formed deliberately but as a by-product of natural behavior. These incidental representations, when generated during visual search, can be stronger than intentionally memorized content (search superiority effect). However, it is unknown if the search superiority effect is purely quantitative (stronger memory) or also driven by differences in the degree of recollection and familiarity, two hallmark processes supporting recognition memory. Here, we use signal detection modeling, introspective judgments, event-related EEG potentials, and eye tracking measures to answer this question. In a preregistered study, 30 participants searched for objects in scenes and intentionally memorized others before completing a surprise recognition memory test. Behavioral data from remember–know judgments and receiver operating characteristics indicate that search targets were more often recollected compared with intentionally memorized objects, whereas the two tasks did not lead to differences in familiarity. Surprisingly, the neural signatures did not fully align with the behavioral findings regarding recollection and familiarity. That is, both search targets and intentionally memorized objects elicited a more positive-going mid-frontal negativity peaking at around 400 msec post stimulus onset (FN400), which is associated with familiarity, as well as a more positive-going parietal late component (LPC), indicative of recollection. Both components showed no differences between tasks, indicating equal contributions of recollection and familiarity to remembering searched and memorized objects. Furthermore, the LPC was, as expected, sensitive to differences between recollected and familiar objects when these were intentionally memorized, but it was not affected by these differences for searched objects. Overall, our findings indicate that search superiority relies predominantly on increased recollection. The fact that established neural markers of recollection (LPC) behaved as anticipated for intentionally memorized objects but carried no predictive power for incidentally memorized objects implies that memories established in more ecologically valid tasks might involve neural processes different from those activated in commonly used settings that are more reductionist.
Genotypic, functional, and phenotypic characterization in CTNNB1 neurodevelopmental syndrome.
CTNNB1 neurodevelopmental syndrome is a rare disorder caused by de novo heterozygous variants in the CTNNB1 gene encoding β-catenin. This study aims to characterize genetic variants in individuals with CTNNB1 neurodevelopmental syndrome, systematically assess the spectrum of clinical phenotypes using standardized measures and explore potential genotype-phenotype correlations. In this cross-sectional cohort study, individuals diagnosed with CTNNB1 neurodevelopmental syndrome underwent structured interviews using standardized scales to evaluate motor skills, speech, communication, feeding abilities, visual function, neurodevelopment, and psychopathology. Genetic variants were analyzed, and in a subset of cases, the impact of β-catenin variants on the Wnt/β-catenin signaling pathway was assessed. Across the 127 included participants (mean age: 70 months; range: 7-242 months) from 20 countries, we identified 88 different variants of the CTNNB1 gene, 87 of which were predicted to lead to loss of CTNNB1 function. Functional assays demonstrated reduced Wnt signaling activity, including 11 variants that also exhibited a dominant-negative effect. One missense variant demonstrated a gain-of-function effect. Dominant-negative variants were not clearly associated with a distinct phenotype, however, those with missense variants presented a milder phenotype, including earlier achievement of independent walking, fewer motor impairments, better conceptual and social skills, improved communication, and fewer feeding difficulties. This study describes genetic, functional, and phenotypic characteristics in individuals with CTNNB1 neurodevelopmental syndrome. Further investigation into the genotypic and phenotypic characteristics of this syndrome and their interrelationships is essential to deepen our understanding of the disorder and inform the development of targeted therapies.
Imaging Neuroscience opening editorial
In this editorial we introduce a new non-profit open access journal, Imaging Neuroscience. In April 2023, editors of the journals NeuroImage and NeuroImage:Reports resigned, and a month later launched Imaging Neuroscience. NeuroImage had long been the leading journal in the field of neuroimaging. While the move to fully open access in 2020 represented a positive step toward modern academic practices, the publication fee was set to a level that the editors found unethical and unsustainable. The publisher of NeuroImage, Elsevier, was unwilling to reduce the fee after much discussion. This led us to launch Imaging Neuroscience with MIT Press, intended to replace NeuroImage as our field’s leading journal, but with greater control by the neuroimaging academic community over publication fees and adoption of modern and ethical publishing practices.
Tensor image registration library: Deformable registration of stand-alone histology images to whole-brain post-mortem MRI data.
BACKGROUND: Accurate registration between microscopy and MRI data is necessary for validating imaging biomarkers against neuropathology, and to disentangle complex signal dependencies in microstructural MRI. Existing registration methods often rely on serial histological sampling or significant manual input, providing limited scope to work with a large number of stand-alone histology sections. Here we present a customisable pipeline to assist the registration of stand-alone histology sections to whole-brain MRI data. METHODS: Our pipeline registers stained histology sections to whole-brain post-mortem MRI in 4 stages, with the help of two photographic intermediaries: a block face image (to undistort histology sections) and coronal brain slab photographs (to insert them into MRI space). Each registration stage is implemented as a configurable stand-alone Python script using our novel platform, Tensor Image Registration Library (TIRL), which provides flexibility for wider adaptation. We report our experience of registering 87 PLP-stained histology sections from 14 subjects and perform various experiments to assess the accuracy and robustness of each stage of the pipeline. RESULTS: All 87 histology sections were successfully registered to MRI. Histology-to-block registration (Stage 1) achieved 0.2-0.4 mm accuracy, better than commonly used existing methods. Block-to-slice matching (Stage 2) showed great robustness in automatically identifying and inserting small tissue blocks into whole brain slices with 0.2 mm accuracy. Simulations demonstrated sub-voxel level accuracy (0.13 mm) of the slice-to-volume registration (Stage 3) algorithm, which was observed in over 200 actual brain slice registrations, compensating 3D slice deformations up to 6.5 mm. Stage 4 combined the previous stages and generated refined pixelwise aligned multi-modal histology-MRI stacks. CONCLUSIONS: Our open-source pipeline provides robust automation tools for registering stand-alone histology sections to MRI data with sub-voxel level precision, and the underlying framework makes it readily adaptable to a diverse range of microscopy-MRI studies.
Loneliness, social isolation, and effects on cognitive decline in patients with dementia: A retrospective cohort study using natural language processing
INTRODUCTION: The study aimed to compare cognitive trajectories between patients with reports of social isolation and loneliness and those without. METHODS: Reports of social isolation, loneliness, and Montreal Cognitive Assessment (MoCA) scores were extracted from dementia patients' medical records using natural language processing models and analyed using mixed-effects models. RESULTS: Lonely patients (n = 382), compared to controls (n = 3912), showed an average MoCA score that was 0.83 points lower at diagnosis (P = 0.008) and throughout the disease. Socially isolated patients (n = 523) experienced a 0.21 MoCA point per year faster rate of cognitive decline in the 6 months before diagnosis (P = 0.029), but were comparable to controls before this period. This led to average MoCA scores that were 0.69 MoCA points lower at diagnosis (P = 0.011). DISCUSSION: Lower cognitive levels in lonely and socially isolated patients suggest that these factors may contribute to dementia progression. Highlights: Developed Natural Language Processing model to detect social isolation and loneliness in electronic health records. Patients with loneliness reports have lower Montreal Cognitive Assessment (MoCA) scores than other patients. Social isolation was related to the faster decline in MoCA scores before diagnosis. Social isolation and loneliness are promising targets for slowing cognitive decline.