Search results
Found 8121 matches for
Convergent and divergent brain-cognition relationships during development revealed by cross-sectional and longitudinal analyses in the ABCD Study.
How brain networks and cognition co-evolve during development remains poorly understood. Using longitudinal data collected at baseline and Year 2 from 2,949 individuals (ages 8.9-13.5) in the Adolescent Brain Cognitive Development (ABCD) Study, we show that baseline resting-state functional connectivity (FC) more strongly predicts future cognitive ability than concurrent cognitive ability. Models trained on baseline FC to predict baseline cognition generalize better to Year 2 data, suggesting that brain-cognition relationships strengthen over time. Intriguingly, baseline FC outperforms longitudinal FC change in predicting future cognitive ability. Differences in measurement reliability do not fully explain this discrepancy: although FC change is less reliable (intraclass correlation, ICC = 0.24) than baseline FC (ICC = 0.56), matching baseline FC's reliability by shortening scan time only partially narrows the predictive gap. Furthermore, neither baseline FC nor FC change meaningfully predicts longitudinal change in cognitive ability. We also identify converging and diverging predictive network features across cross-sectional and longitudinal models of brain-cognition relationships, revealing a multivariate twist on Simpson's paradox. Together, these findings suggest that during early adolescence, stable individual differences in brain functional network organization exert a stronger influence on future cognitive outcomes than short-term changes.
Active information sampling in health and disease
Active information gathering is a fundamental cognitive process that enables organisms to navigate uncertainty and make adaptive decisions. Here we synthesise current knowledge on the behavioural, neural, and computational mechanisms underlying information sampling in healthy people and across several brain disorders. The role of cortical and subcortical regions spanning limbic, insular, fronto-parietal, and striatal systems is considered, along with the contributions of key neurotransmitters involving norepinephrine, dopamine, and serotonin. We also examine how various clinical conditions, including schizophrenia, obsessive-compulsive disorder, and Parkinson's disease have an impact on information gathering behaviours. To account for the findings, we outline a neuroeconomic perspective on how the brain may evaluate the costs and benefits of acquiring information to resolve uncertainty. This work highlights how active information gathering is a crucial brain process for adaptive behaviour in healthy individuals and how its breakdown is relevant to several psychiatric and neurological conditions. The findings have important implications for developing novel computational assays as well as targeted interventions in brain disorders.
Self- versus caregiver-reported apathy across neurological disorders
Abstract Apathy is a prevalent and persistent neuropsychiatric syndrome across many neurological disorders, significantly impacting both patients and caregivers. We systematically quantified discrepancies between self- and caregiver-reported apathy in 335 patients with a variety of diagnoses, frontotemporal dementia (behavioural variant and semantic dementia subtypes), Parkinson’s disease, Parkinson’s disease dementia, dementia with Lewy bodies, Alzheimer’s disease dementia, mild cognitive impairment, small vessel cerebrovascular disease, subjective cognitive decline and autoimmune encephalitis. Using the Apathy-Motivation Index (AMI) and its analogous caregiver version (AMI-CG), we found that caregiver-reported apathy consistently exceeded self-reported levels across all conditions. Moreover, self-reported apathy accounted for only 14.1% of the variance in caregiver ratings. This apathy reporting discrepancy was most pronounced in conditions associated with impaired insight, such as behavioural variant frontotemporal dementia, and was significantly correlated with cognitive impairment. Deficits in memory and fluency explained an additional 11.2% of the variance in caregiver-reported apathy. Specifically, executive function deficits (e.g., indexed by fluency) and memory impairments may contribute to behavioural inertia or recall of it. These findings highlight the need to integrate patient and caregiver perspectives in apathy assessments, especially for conditions with prominent cognitive impairment. To improve diagnostic accuracy and deepen our understanding of apathy across neurological disorders, we highlight the need of adapted apathy assessment strategies that account for cognitive impairment particularly in individuals with insight or memory deficits. Understanding the cognitive mechanisms underpinning discordant apathy reporting in dementia might help to inform targeted clinical interventions and reduce caregiver burden.
Goal-directedness deficit in Huntington's disease.
Apathy and impulsive behaviour co-occur in Huntington's disease (HD), but these debilitating behavioural syndromes are multidimensional constructs, raising the question of which specific dimensions drive this relationship and the stability of the co-occurring dimensions across time. People with HD and controls completed multidimensional apathy and impulsive behaviour scales at baseline and 1-year follow-up. A principal component analysis was performed on pooled data (n = 109) to identify components and factor loadings of subscales. Linear mixed models were used to examine differences in components between groups and timepoints. Three meaningful components emerged. Component 1 comprised positive loading for dimensions of apathy and impulsive behaviour pertaining to goal-directedness, namely attention, planning, initiation, and perseverance. In contrast, other dimensions of apathy and impulsive behaviour loaded onto components two and three in opposite directions. People with HD only scored worse than controls on the goal-directedness component. All components remained stable over time and closely resembled factors from the five-factor personality model. Component 1 mapped onto the factor conscientiousness, component 2 to extraversion, and component 3 to neuroticism. The clinical overlap between apathy and impulsive behaviour in HD relates to goal-directedness, whilst other dimensions of these constructs did not overlap.
Apnoea suppresses brain activity in infants
Apnoea—the cessation of breathing—is commonly observed in premature infants. These events can reduce cerebral oxygenation and are associated with poorer neurodevelopmental outcomes. However, relatively little is known about how apnoea and shorter pauses in breathing impact brain function in infants, which will provide greater mechanistic understanding of how apnoea affects brain development. We analysed simultaneous recordings of respiration, electroencephalography (EEG), heart rate, and peripheral oxygen saturation in 124 recordings from 118 infants (post-menstrual age: 38.6 ± 2.7 weeks [mean ± standard deviation]) during apnoeas (pauses in breathing greater than 15 seconds) and shorter breathing pauses between 5 and 15 seconds. EEG amplitude significantly decreased during both apnoeas and short breathing pauses compared with normal breathing periods. Change in EEG amplitude was significantly associated with change in heart rate during apnoea and short breathing pauses and, during apnoeas only, with oxygen saturation change. No associations were found between EEG amplitude changes and apnoea/pause duration, post-menstrual age, or sleep state. As apnoeas often occur in premature infants, frequent disruption to brain activity may impact neural development and result in long-term neurodevelopmental consequences.
The effect of D-cycloserine on brain connectivity over a course of pulmonary rehabilitation - A randomised control trial with neuroimaging endpoints.
Combining traditional therapies such as pulmonary rehabilitation with brain-targeted drugs may offer new therapeutic opportunities for the treatment of chronic breathlessness. Recently, we asked whether D-cycloserine, a partial NMDA-receptor agonist which may enhance behavioural therapies, modifies the relationship between breathlessness related brain activity and breathlessness anxiety over pulmonary rehabilitation. However, whether any changes are supported by alterations to underlying brain structure remains unknown. Here we examine the effect of D-cycloserine over a course of pulmonary rehabilitation on the connectivity between key brain regions associated with the processing of breathlessness anxiety. 72 participants with mild-to-moderate COPD took part in a longitudinal study in parallel to their pulmonary rehabilitation course. Diffusion tensor brain imaging and clinical measures of respiratory function were collected at three time points (before, during and after pulmonary rehabilitation). Participants were assigned to 250mg of D-cycloserine or placebo, which they were administered with on four occasions in a randomised, double-blind procedure. Following the first four sessions of pulmonary rehabilitation (visit 2), during which D-cycloserine was administered, improvements in breathlessness anxiety were linked with increased insula-hippocampal structural connectivity in the D-cycloserine group when compared to the placebo group. No differences were found between the two groups following the completion of the full pulmonary rehabilitation course 4-6 weeks later (visit 3). The action of D-cycloserine on brain connectivity appears to be restricted to within a short time-window of its administration. This temporary boost of the brain connectivity of two key regions associated with the evaluation of how unpleasant an experience is may support the re-evaluation of breathlessness cues, illustrated improvements in breathlessness anxiety. Trial registration ClinicalTrials.gov (NCT01985750).
BNPower: a power calculation tool for data-driven network analysis for whole-brain connectome data
Network analysis of whole-brain connectome data is widely employed to examine systematic changes in connections among brain areas caused by clinical and experimental conditions. In these analyses, the connectome data, represented as a matrix, are treated as outcomes, while the subject conditions serve as predictors. The objective of network analysis is to identify connectome subnetworks whose edges are associated with the predictors. Data-driven network analysis is a powerful approach that automatically organizes individual predictor-related connections (edges) into subnetworks, rather than relying on pre-specified subnetworks, thereby enabling network-level inference. However, power calculation for data-driven network analysis presents a challenge due to the data-driven nature of subnetwork identification, where nodes, edges, and model parameters cannot be pre-specified before the analysis. Additionally, data-driven network analysis involves multivariate edge variables and may entail multiple subnetworks, necessitating the correction for multiple testing (e.g., family-wise error rate (FWER) control). To address this issue, we developed BNPower, a user-friendly power calculation tool for data-driven network analysis. BNPower utilizes simulation analysis, taking into account the complexity of the data-driven network analysis model. We have implemented efficient computational strategies to facilitate data-driven network analysis, including subnetwork extraction and permutation tests for controlling FWER, while maintaining low computational costs. The toolkit, which includes a graphical user interface and source codes, is publicly available at the following GitHub repository: https://github.com/bichuan0419/brain_connectome_power_tool
The spatial layout of antagonistic brain regions is explicable based on geometric principles
Abstract Brain activity emerges in a dynamic landscape of regional increases and decreases that span the cortex. Increases in activity during a cognitive task are often assumed to reflect the processing of task-relevant information, while reductions can be interpreted as suppression of irrelevant activity to facilitate task goals. Here, we explore the relationship between task-induced increases and decreases in activity from a geometric perspective. Using a technique known as kriging, developed in earth sciences, we examined whether the spatial organisation of brain regions showing positive activity could be predicted based on the spatial layout of regions showing activity decreases (and vice versa). Consistent with this hypothesis we established the spatial distribution of regions showing reductions in activity could predict (i) regions showing task-relevant increases in activity in both groups of humans and single individuals; (ii) patterns of neural activity captured by calcium imaging in mice; and, (iii) showed a high degree of generalisability across task contexts. Our analysis, therefore, establishes that antagonistic relationships between brain regions are topographically determined, a spatial analog for the well documented anti-correlation between brain systems over time.
Simulated kangaroo care in very preterm infants does not reduce physiological instability: the COSYBABY randomised controlled cross-over trial.
INTRODUCTION: Infants who are born very preterm experience frequent episodes of physiological instability including apnoea, oxygen desaturation and bradycardia due to immaturity of the pulmonary and nervous systems. Parental contact, such as kangaroo care, may reduce physiological instability. However, there may be long periods when parents cannot be with their baby. The BABYBE SYSTEM® is a medical device designed to simulate kangaroo care. METHODS: We conducted a randomised cross-over trial to determine whether episodes of apnoea and other episodes of physiological instability were reduced when infants were on an active BABYBE mattress. Each infant was included in the study for five consecutive days, with successive 12-h periods of the BABYBE® mattress being switched on or off. Episodes of physiological instability were identified from recordings of the vital signs monitors and compared with clinical notes. Generalised estimating equations models were used to compare physiological instability when the BABYBE mattress was switched on vs. off. RESULTS: A total of 23 infants born before 32 weeks' gestation were included in the main analysis. There was no significant difference between the number of apnoeic episodes infants experienced in the 12-h period when the BABYBE mattress was on compared with when the mattress was switched off (difference between conditions = 1.5 apnoeas, 95% CI: -0.2-3.2, p = 0.09). The number of episodes of apnoea identified from vital signs recordings were much higher than those documented in the clinical records (a total of 1,157 apnoeic episodes were identified across all infants from vital signs recordings compared with a total of 27 documented in clinical/nursing notes of the same infants). DISCUSSION: This trial does not provide evidence of a benefit of the BABYBE mattress for improving physiological stability in preterm infants. This study provides confirmation of the under-recognition of apnoeic episodes in clinical notes and the benefit of assessing electronic recordings of vital signs to gain a more complete picture of physiological stability.
Subgrouping autism and ADHD based on structural MRI population modelling centiles.
BACKGROUND: Autism and attention deficit hyperactivity disorder (ADHD) are two highly heterogeneous neurodevelopmental conditions with variable underlying neurobiology. Imaging studies have yielded varied results, and it is now clear that there is unlikely to be one characteristic neuroanatomical profile of either condition. Parsing this heterogeneity could allow us to identify more homogeneous subgroups, either within or across conditions, which may be more clinically informative. This has been a pivotal goal for neurodevelopmental research using both clinical and neuroanatomical features, though results thus far have again been inconsistent with regards to the number and characteristics of subgroups. METHODS: Here, we use population modelling to cluster a multi-site dataset based on global and regional centile scores of cortical thickness, surface area and grey matter volume. We use HYDRA, a novel semi-supervised machine learning algorithm which clusters based on differences to controls and compare its performance to a traditional clustering approach. RESULTS: We identified distinct subgroups within autism and ADHD, as well as across diagnosis, often with opposite neuroanatomical alterations relatively to controls. These subgroups were characterised by different combinations of increased or decreased patterns of morphometrics. We did not find significant clinical differences across subgroups. LIMITATIONS: Crucially, however, the number of subgroups and their membership differed vastly depending on chosen features and the algorithm used, highlighting the impact and importance of careful method selection. CONCLUSIONS: We highlight the importance of examining heterogeneity in autism and ADHD and demonstrate that population modelling is a useful tool to study subgrouping in autism and ADHD. We identified subgroups with distinct patterns of alterations relative to controls but note that these results rely heavily on the algorithm used and encourage detailed reporting of methods and features used in future studies.
Microstructural Properties of the Cerebellar Peduncles in Children With Developmental Language Disorder.
Children with developmental language disorder (DLD) struggle to learn their native language for no apparent reason. While research on the neurobiological underpinnings of the disorder has focused on the role of corticostriatal systems, little is known about the role of the cerebellum in DLD. Corticocerebellar circuits might be involved in the disorder as they contribute to complex sensorimotor skill learning, including the acquisition of spoken language. Here, we used diffusion-weighted imaging data from 77 typically developing and 54 children with DLD and performed probabilistic tractography to identify the cerebellum's white matter tracts: the inferior, middle, and superior cerebellar peduncles. Children with DLD showed lower fractional anisotropy (FA) in the inferior cerebellar peduncles (ICP), fiber tracts that carry motor and sensory input via the inferior olive to the cerebellum. Lower FA in DLD was driven by lower axial diffusivity. Probing this further with more sophisticated modeling of diffusion data, we found higher orientation dispersion but no difference in neurite density in the ICP of children with DLD. Reduced FA is therefore unlikely to be reflecting microstructural differences in myelination, rather the organization of axons in these pathways is disrupted. ICP microstructure was not associated with language or motor coordination performance in our sample. We also found no differences in the middle and superior peduncles, the main pathways connecting the cerebellum with the cortex. To conclude, it is not corticocerebellar but atypical olivocerebellar white matter connections that characterize DLD and suggest the involvement of the olivocerebellar system in speech and language acquisition and development.
Differential beta and gamma activity modulation during unimanual and bimanual motor learning.
Movement-related dynamics in the beta and gamma bands have been studied in relation to motor execution and learning during unimanual movements, but their roles in complex bimanual tasks remain largely unexplored. This study aimed to investigate how beta and gamma activity differs between unimanual and bimanual movements, and how these neural signatures evolve during the learning process. Our motor task incorporated varying levels of bimanual interaction: unimanual, bimanual-equal, and bimanual-unequal. Magnetoencephalography data were recorded in healthy participants (N = 43, 27 females) during task performance, and beta and gamma activity was quantified. As expected, increasing task complexity from unimanual to bimanual-equal, and then to bimanual-unequal movements resulted in slower and less accurate performance. Across all conditions, significant beta event-related desynchronization (ERD) and gamma event-related synchronization (ERS) were observed during movement, as well as beta ERS after movement. Bimanual movements exhibited greater beta ERD, beta ERS, and gamma ERS compared to unimanual movements. With practice, participants demonstrated faster and more accurate movements, accompanied by enhanced beta ERS responses. Furthermore, learning-related reductions in errors correlated with increases in beta ERS. These findings suggest the distinct behavioural and neural demands of unimanual versus bimanual movements and highlight the important role of beta activity in motor performance and learning.Significance statement Bimanual movements, which dominate daily motor behaviours, require finely tuned coordination between the two hands yet remain poorly understood at the neurophysiological level. Using magnetoencephalography, we tested neural responses to a novel movement task incorporating varying levels of bimanual interaction. We demonstrate that greater task complexity elicits enhanced movement-related brain activity in the beta and gamma frequency bands. Motor learning is associated with an increase in beta movement-related synchronization that correlates with improved movement accuracy. This study provides novel insights into how beta and gamma brain activity adapt to increasing movement complexity and motor learning.