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Whole brain comparative anatomy using connectivity blueprints
Comparing the brains of related species faces the challenges of establishing homologies whilst accommodating evolutionary specializations. Here we propose a general framework for understanding similarities and differences between the brains of primates. The approach uses white matter blueprints of the whole cortex based on a set of white matter tracts that can be anatomically matched across species. The blueprints provide a common reference space that allows us to navigate between brains of different species, identify homologue cortical areas, or to transform whole cortical maps from one species to the other. Specializations are cast within this framework as deviations between the species’ blueprints. We illustrate how this approach can be used to compare human and macaque brains.
Connectivity profile and function of uniquely human cortical areas.
Determining the brain specializations unique to humans requires directly comparative anatomical information from other primates, especially our closest relatives. Human (Homo sapiens) (m/f), chimpanzee (Pan troglodytes) (f), and rhesus macaque (Macaca mulatta) (m/f) white matter atlases were used to create connectivity blueprints, i.e., descriptions of the cortical grey matter in terms of the connectivity with homologous white matter tracts. This allowed a quantitative comparative of cortical organization across the species. We identified human-unique connectivity profiles concentrated in temporal and parietal cortices, and hominid-unique organization in prefrontal cortex. Functional decoding revealed human-unique hotspots correlated with language processing and social cognition. Overall, our results counter models that assign primacy to prefrontal cortex for human uniqueness.Significance statement Understanding what makes the human brain unique requires direct comparisons with other primates, particularly our closest relatives. Using connectivity blueprints, we compared to cortical organization of the human to that of the macaque and, for the first time, the chimpanzee. This approach revealed human-specific connectivity patterns in the temporal and parietal lobes, regions linked to language and social cognition. These findings challenge traditional views that prioritize the prefrontal cortex in defining human cognitive uniqueness, emphasizing instead the importance of temporal and parietal cortical evolution in shaping our species' abilities.
Predictive Methods and Probabilistic Mapping of Subcortical Brain Components in Fossil Carnivora.
Paleoneurology reconstructs the evolutionary history of nervous systems through direct observations from the fossil record and comparative data from extant species. Although this approach can provide direct evidence of phylogenetic links among species, it is constrained by the availability and quality of data that can be gleaned from the fossil record. Here, we sought to translate brain component relationships in a sample of extant Carnivora to make inferences about brain structure in fossil species. Using high resolution magnetic resonance imaging on extant canids and felids and 3D laser scanning on fossil Carnivora, spanning some 40 million years of evolution, we derived measurements for select brain components. From these primary data, predictive equations of cortical (gray matter mass, cortical thickness, and gyrification index) and subcortical structures (caudate nucleus, putamen, and external globus pallidus mass) were used to derive estimates for select fossil Carnivora. We found that regression equations based on both extant and simulation samples provided moderate to high predictability of subcortical masses for fossil Carnivora. We also found that using exploratory probabilistic mapping of subcortical structures in extant Carnivora, a reasonable prediction could be made of the 3D subcortical morphospace of fossil endocasts. These results identify allometric departures and establish adult species ranges in brain component size for fossil species. The integrative approach taken in this study may serve as a model to promote further dialog between neurobiologists working on extant Carnivora models and paleoneurologists describing the nervous system of fossils from this understudied group of mammals.
Distinct impact modes of polygenic disposition to dyslexia in the adult brain.
Dyslexia is a common and partially heritable condition that affects reading ability. In a study of up to 35,231 adults, we explored the structural brain correlates of genetic disposition to dyslexia. Individual dyslexia-disposing genetic variants showed distinct patterns of association with brain structure. Independent component analysis revealed various brain networks that each had their own genomic profiles related to dyslexia susceptibility. Circuits involved in motor coordination, vision, and language were implicated. Polygenic scores for eight traits genetically correlated with dyslexia, including cognitive, behavioral, and reading-related psychometric measures, showed partial similarities to dyslexia in terms of brain-wide associations. Notably, microstructure of the internal capsule was consistently implicated across all of these genetic dispositions, while lower volume of the motor cortex was more specifically associated with dyslexia genetic disposition alone. These findings reveal genetic and neurobiological features that may contribute to dyslexia and its associations with other traits at the population level.
Generalising XTRACT tractography protocols across common macaque brain templates.
Non-human primates are extensively used in neuroscience research as models of the human brain, with the rhesus macaque being a prominent example. We have previously introduced a set of tractography protocols (XTRACT) for reconstructing 42 corresponding white matter (WM) bundles in the human and the macaque brain and have shown cross-species comparisons using such bundles as WM landmarks. Our original XTRACT protocols were developed using the F99 macaque brain template. However, additional macaque template brains are becoming increasingly common. Here, we generalise the XTRACT tractography protocol definitions across five macaque brain templates, including the F99, D99, INIA, Yerkes and NMT. We demonstrate equivalence of such protocols in two ways: (a) Firstly by comparing the bodies of the tracts derived using protocols defined across the different templates considered, (b) Secondly by comparing the projection patterns of the reconstructed tracts across the different templates in two cross-species (human-macaque) comparison tasks. The results confirm similarity of all predictions regardless of the macaque brain template used, providing direct evidence for the generalisability of these tractography protocols across the five considered templates.
Comparative anatomy of the caudate nucleus in canids and felids: Associations with brain size, curvature, cross-sectional properties, and behavioral ecology.
The evolutionary history of canids and felids is marked by a deep time separation that has uniquely shaped their behavior and phenotype toward refined predatory abilities. The caudate nucleus is a subcortical brain structure associated with both motor control and cognitive, emotional, and executive functions. We used a combination of three-dimensional imaging, allometric scaling, and structural analyses to compare the size and shape characteristics of the caudate nucleus. The sample consisted of MRI scan data obtained from six canid species (Canis lupus lupus, Canis latrans, Chrysocyon brachyurus, Lycaon pictus, Vulpes vulpes, Vulpes zerda), two canid subspecies (Canis lupus familiaris, Canis lupus dingo), as well as three felids (Panthera tigris, Panthera uncia, Felis silvestris catus). Results revealed marked conservation in the scaling and shape attributes of the caudate nucleus across species, with only slight deviations. We hypothesize that observed differences in caudate nucleus size and structure for the domestic canids are reflective of enhanced cognitive and emotional pathways that possibly emerged during domestication.
Comparative neuroimaging of sex differences in human and mouse brain anatomy.
In vivo neuroimaging studies have established several reproducible volumetric sex differences in the human brain, but the causes of such differences are hard to parse. While mouse models are useful for understanding the cellular and mechanistic bases of sex-biased brain development in mammals, there have been no attempts to formally compare mouse and human sex differences across the whole brain to ascertain how well they translate. Addressing this question would shed critical light on use of the mouse as a translational model for sex differences in the human brain and provide insights into the degree to which sex differences in brain volume are conserved across mammals. Here, we use cross-species structural magnetic resonance imaging to carry out the first comparative neuroimaging study of sex-biased neuroanatomical organization of the human and mouse brain. In line with previous findings, we observe that in humans, males have significantly larger and more variable total brain volume; these sex differences are not mirrored in mice. After controlling for total brain volume, we observe modest cross-species congruence in the volumetric effect size of sex across 60 homologous brain regions (r=0.30; e.g.: M>F amygdala, hippocampus, bed nucleus of the stria terminalis, and hypothalamus and F>M anterior cingulate, somatosensory, and primary auditory cortices). This cross-species congruence is greater in the cortex (r=0.33) than non-cortex (r=0.16). By incorporating regional measures of gene expression in both species, we reveal that cortical regions with greater cross-species congruence in volumetric sex differences also show greater cross-species congruence in the expression profile of 2835 homologous genes. This phenomenon differentiates primary sensory regions with high congruence of sex effects and gene expression from limbic cortices where congruence in both these features was weaker between species. These findings help identify aspects of sex-biased brain anatomy present in mice that are retained, lost, or inverted in humans. More broadly, our work provides an empirical basis for targeting mechanistic studies of sex-biased brain development in mice to brain regions that best echo sex-biased brain development in humans.
Manipulation of subcortical and deep cortical activity in the primate brain using transcranial focused ultrasound stimulation
Summary The causal role of an area within a neural network can be determined by interfering with its activity and measuring the impact. Many current reversible manipulation techniques have limitations preventing their focal application particularly in deep areas of the primate brain. Here we demonstrate a transcranial focused ultrasound stimulation (TUS) protocol that manipulates activity even in deep brain areas: a subcortical brain structure, the amygdala (experiment 1), and a deep cortical region, anterior cingulate cortex (ACC, experiment 2), in macaques. TUS neuromodulatory effects were measured by examining relationships between activity in each area and the rest of the brain using functional magnetic resonance imaging (fMRI). In control conditions without sonication, activity in a given area is related to activity in interconnected regions but such relationships are reduced after sonication. Dissociable and focal effects on neural activity could not be explained by auditory artefacts.
An open resource for nonhuman primate imaging
ABSTRACT Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMate Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 13 independent data collections aggregated across 11 sites (total = 98 macaque monkeys). We also outline the unique pitfalls and challenges that should be considered in the analysis of the non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets.
Improving sleep after stroke: A randomised controlled trial of digital cognitive behavioural therapy for insomnia.
Stroke is frequently accompanied by long-term sleep disruption. We therefore aimed to assess the efficacy of digital cognitive behavioural therapy for insomnia to improve sleep after stroke. A parallel group randomised controlled trial was conducted remotely in participant's homes/online. Randomisation was online with minimisation of between-group differences in age and baseline Sleep Condition Indicator-8 score. In total, 86 community-dwelling stroke survivors consented, of whom 84 completed baseline assessments (39 female, mean 5.5 years post-stroke, mean 59 years old), and were randomised to digital cognitive behavioural therapy or control (sleep hygiene information). Follow-up was at post-intervention (mean 75 days after baseline) and 8 weeks later. The primary outcome was self-reported insomnia symptoms, as per the Sleep Condition Indicator-8 (range 0-32, lower numbers indicate more severe insomnia, reliable change 7 points) at post-intervention. There were significant improvements in Sleep Condition Indicator-8 for digital cognitive behavioural therapy compared with control (intention-to-treat, digital cognitive behavioural therapy n = 48, control n = 36, 5 imputed datasets, effect of group p ≤ 0.02, η p 2 = 0.07-0.12 [medium size effect], pooled mean difference = -3.35). Additionally, secondary outcomes showed shorter self-reported sleep-onset latencies and better mood for the digital cognitive behavioural therapy group, but no significant differences for self-efficacy, quality of life or actigraphy-derived sleep parameters. Cost-effectiveness analysis found that digital cognitive behavioural therapy dominates over control (non-significant cost savings and higher quality-adjusted life years). No related serious adverse events were reported to the researchers. Overall, digital cognitive behavioural therapy for insomnia effectively improves sleep after stroke. Future research is needed to assess earlier stages post-stroke, with a longer follow-up period to determine whether it should be included as part of routine post-stroke care. Clinicaltrials.gov NCT04272892.
Investigating heterogeneity across autism, ADHD, and typical development using measures of cortical thickness, surface area, cortical/subcortical volume, and structural covariance.
INTRODUCTION: Attention-deficit/hyperactivity disorder (ADHD) and autism are multi-faceted neurodevelopmental conditions with limited biological markers. The clinical diagnoses of autism and ADHD are based on behavioural assessments and may not predict long-term outcomes or response to interventions and supports. To address this gap, data-driven methods can be used to discover groups of individuals with shared biological patterns. METHODS: In this study, we investigated measures derived from cortical/subcortical volume, surface area, cortical thickness, and structural covariance investigated of 565 participants with diagnoses of autism [n = 262, median(IQR) age = 12.2(5.9), 22% female], and ADHD [n = 171, median(IQR) age = 11.1(4.0), 21% female] as well neurotypical children [n = 132, median(IQR) age = 12.1(6.7), 43% female]. We integrated cortical thickness, surface area, and cortical/subcortical volume, with a measure of single-participant structural covariance using a graph neural network approach. RESULTS: Our findings suggest two large clusters, which differed in measures of adaptive functioning (χ 2 = 7.8, P = 0.004), inattention (χ 2 = 11.169, P
Nurse-delivered sleep restriction therapy in primary care for adults with insomnia disorder: a mixed-methods process evaluation.
BACKGROUND: Sleep restriction therapy (SRT) is a behavioural therapy for insomnia. AIM: To conduct a process evaluation of a randomised controlled trial comparing SRT delivered by primary care nurses plus a sleep hygiene booklet with the sleep hygiene booklet only for adults with insomnia disorder. DESIGN AND SETTING: A mixed-methods process evaluation in a general practice setting. METHOD: Semi-structured interviews were conducted in a purposive sample of patients receiving SRT, the practice nurses who delivered the therapy, and also GPs or practice managers at the participating practices. Qualitative data were explored using framework analysis, and integrated with nurse comments and quantitative data, including baseline Insomnia Severity Index score and serial sleep efficiency outcomes to investigate the relationships between these. RESULTS: In total, 16 patients, 13 nurses, six practice managers, and one GP were interviewed. Patients had no previous experience of behavioural therapy, needed flexible appointment times, and preferred face-to-face consultations; nurses felt prepared to deliver SRT, accommodating patient concerns, tailoring therapy, and negotiating sleep timings despite treatment complexity and delays between training and intervention delivery. How the intervention produced change was explored, including patient and nurse interactions and patient responses to SRT. Difficulties maintaining SRT, negative attitudes towards treatment, and low self-efficacy were highlighted. Contextual factors, including freeing GP time, time constraints, and conflicting priorities for nurses, with suggestions for alternative delivery options, were raised. Participants who found SRT a positive process showed improvements in sleep efficiency, whereas those who struggled did not. CONCLUSION: SRT was successfully delivered by practice nurses and was generally well received by patients, despite some difficulties delivering and applying the intervention in practice.
Sleep regularity index as a novel indicator of sleep disturbance in stroke survivors: a secondary data analysis.
Sleep disturbance is common but often overlooked after stroke. Regular sleep is increasingly recognised as important for overall health, yet little is known about how sleep regularity changes after stroke. This study examined differences in the Sleep Regularity Index (SRI) between stroke survivors and healthy controls using actigraphy data from an existing dataset (~ 1 week per participant). Data were analysed for 162 stroke survivors (mean age 61 ± 14 years, 5 ± 5 years post-stroke, 89 males) and 60 controls (mean age 57 ± 17 years, 32 males). Stroke survivors had significantly lower SRI scores than controls (p = 0.001), indicating less regular sleep. In the stroke group, higher SRI correlated with longer total sleep time (p = 0.003) and better self-reported sleep quality (p = 0.001) but not with other sleep metrics. Lower SRI was associated with worse depressive symptoms (p = 0.006) and lower quality of life (p = 0.001) but not with disability (p = 0.886) or time since stroke (p = 0.646). These findings suggest that sleep regularity is disrupted post-stroke and may influence well-being. Future research should explore interventions to improve sleep regularity and related health outcomes in stroke survivors.
Clinical and cost-effectiveness of nurse-delivered sleep restriction therapy for insomnia in primary care (HABIT): a pragmatic, superiority, open-label, randomised controlled trial.
BACKGROUND: Insomnia is prevalent and distressing but access to the first-line treatment, cognitive behavioural therapy (CBT), is extremely limited. We aimed to assess the clinical and cost-effectiveness of sleep restriction therapy, a key component of CBT, which has the potential to be widely implemented. METHODS: We did a pragmatic, superiority, open-label, randomised controlled trial of sleep restriction therapy versus sleep hygiene. Adults with insomnia disorder were recruited from 35 general practices across England and randomly assigned (1:1) using a web-based randomisation programme to either four sessions of nurse-delivered sleep restriction therapy plus a sleep hygiene booklet or a sleep hygiene booklet only. There was no restriction on usual care for either group. Outcomes were assessed at 3 months, 6 months, and 12 months. The primary endpoint was self-reported insomnia severity at 6 months measured with the insomnia severity index (ISI). The primary analysis included participants according to their allocated group and who contributed at least one outcome measurement. Cost-effectiveness was evaluated from the UK National Health Service and personal social services perspective and expressed in terms of incremental cost per quality-adjusted life year (QALY) gained. The trial was prospectively registered (ISRCTN42499563). FINDINGS: Between Aug 29, 2018, and March 23, 2020 we randomly assigned 642 participants to sleep restriction therapy (n=321) or sleep hygiene (n=321). Mean age was 55·4 years (range 19-88), with 489 (76·2%) participants being female and 153 (23·8%) being male. 580 (90·3%) participants provided data for at least one outcome measurement. At 6 months, mean ISI score was 10·9 (SD 5·5) for sleep restriction therapy and 13·9 (5·2) for sleep hygiene (adjusted mean difference -3·05, 95% CI -3·83 to -2·28; p<0·0001; Cohen's d -0·74), indicating that participants in the sleep restriction therapy group reported lower insomnia severity than the sleep hygiene group. The incremental cost per QALY gained was £2076, giving a 95·3% probability that treatment was cost-effective at a cost-effectiveness threshold of £20 000. Eight participants in each group had serious adverse events, none of which were judged to be related to intervention. INTERPRETATION: Brief nurse-delivered sleep restriction therapy in primary care reduces insomnia symptoms, is likely to be cost-effective, and has the potential to be widely implemented as a first-line treatment for insomnia disorder. FUNDING: The National Institute for Health and Care Research Health Technology Assessment Programme.
Persistence of training-induced visual improvements after occipital stroke.
Damage to the primary visual cortex causes homonymous visual impairments that appear to benefit from visual discrimination training. However, whether improvements persist without continued training remains to be determined and was the focus of the present study. After a baseline assessment visit, 20 participants trained twice daily in their blind-field for a minimum of six months (median=155 sessions), using a motion discrimination and integration task. At the end of training, a return study visit was used to assess recovery. Three months later, 14 of the participants returned for a third study visit to assess persistence of recovery. At each study visit, motion discrimination and integration thresholds, Humphrey visual fields, and structural MRI scans were collected. Immediately after training, all but four participants showed improvements in the trained discrimination task, and shrinkage of the perimetrically-defined visual defect. While these gains were sustained in seven out of eleven participants who improved with training, four participants lost their improvement in motion discrimination thresholds at the follow-up visit. Persistence of recovery was not related to age, time since lesion, number of training sessions performed, proportion of V1 damaged, deficit size, or optic tract degeneration measured from structural MRI scans. The present findings underscore the potential of extended visual training to induce long-term improvements in stroke-induced vision loss. However, they also highlight the need for further investigations to better understand the mechanisms driving recovery, its persistence post-training, and especially heterogeneity among participants.
The value of mental science: we publish what matters.
Recent changes to US research funding are having far-reaching consequences that imperil the integrity of science and the provision of care to vulnerable populations. Resisting these changes, the BJPsych Portfolio reaffirms its commitment to publishing mental science and advancing psychiatric knowledge that improves the mental health of one and all.
Internally consistent and fully unbiased multimodal MRI brain template construction from UK Biobank: Oxford-MM
Anatomical magnetic resonance imaging (MRI) templates of the brain are essential to group-level analyses and image processing pipelines, as they provide a reference space for spatial normalisation. While it has become common for studies to acquire multimodal MRI data, many templates are still limited to one type of modality, usually either scalar or tensor based. Aligning each modality in isolation does not take full advantage of the available complementary information, such as strong contrast between tissue types in structural images, or axonal organisation in the white matter in diffusion tensor images. Most existing strategies for multimodal template construction either do not use all modalities of interest to inform the template construction process, or do not use them in a unified framework. Here, we present multimodal, cross-sectional templates constructed from UK Biobank data: the Oxford-MultiModal-1 (OMM-1) template and age-dependent templates for each year of life between 45 and 81 years. All templates are fully unbiased to represent the average shape of the populations they were constructed from, and internally consistent through jointly informing the template construction process with T1-weighted (T1), T2-weighted fluid-attenuated inversion recovery (T2-FLAIR), and diffusion tensor imaging (DTI) data. The OMM-1 template was constructed with a multiresolution, iterative approach using 240 individuals in the 50–55-year age range. The age-dependent templates were estimated using a Gaussian process, which describes the change in average brain shape with age in 37,330 individuals. All templates show excellent contrast and alignment within and between modalities. The global brain shape and size are not preconditioned on existing templates, although maximal possible compatibility with MNI-152 space was maintained through rigid alignment. We showed benefits in registration accuracy across two datasets (UK Biobank and HCP), when using the OMM-1 as the template compared with FSL’s MNI-152 template, and found that the use of age-dependent templates further improved accuracy to a small but detectable extent. All templates are publicly available and can be used as a new reference space for uni- or multimodal spatial alignment.
Stacking models of brain dynamics to improve prediction of subject traits in fMRI.
Beyond structural and time-averaged functional connectivity brain measures, modelling the way brain activity dynamically unfolds can add important information to our understanding and characterisation of individual cognitive traits. One approach to leveraging this information is to extract features from models of brain network dynamics to predict individual traits. However, these predictions are susceptible to variability due to factors such as variation in model estimation induced by the choice of hyperparameters. We suggest that, rather than merely being statistical noise, this variability may be useful in providing complementary information that can be leveraged to improve prediction accuracy. To leverage this variability, we propose the use of stacking, a prediction-driven approach for model selection. Specifically, we combine predictions developed from multiple hidden Markov models-a probabilistic generative model of network dynamics that identifies recurring patterns of brain activity-to demonstrate that stacking can slightly improve the accuracy and robustness of cognitive trait predictions. By comparing analysis from the Human Connectome Project and UK Biobank datasets, we show that stacking is relatively effective at improving prediction accuracy and robustness when there are enough subjects, and that the effectiveness of combining predictions from static and dynamic functional connectivity approaches depends on the length of scan per subject. We also show that the effectiveness of stacking predictions is driven by the accuracy and diversity in the underlying model estimations.