In a group of 831 participants from the general population in the Human Connectome Project, smokers exhibited low overall functional connectivity, and more specifically of the lateral orbitofrontal ...cortex which is associated with non-reward mechanisms, the adjacent inferior frontal gyrus, and the precuneus. Participants who drank a high amount had overall increases in resting state functional connectivity, and specific increases in reward-related systems including the medial orbitofrontal cortex and the cingulate cortex. Increased impulsivity was found in smokers, associated with decreased functional connectivity of the non-reward-related lateral orbitofrontal cortex; and increased impulsivity was found in high amount drinkers, associated with increased functional connectivity of the reward-related medial orbitofrontal cortex. The main findings were cross-validated in an independent longitudinal dataset with 1176 participants, IMAGEN. Further, the functional connectivities in 14-year-old non-smokers (and also in female low-drinkers) were related to who would smoke or drink at age 19. An implication is that these differences in brain functional connectivities play a role in smoking and drinking, together with other factors.
•Developed a model-based reproducibility index for large-scale high-throughput MRI-based studies.•Provided an analytical tool to evaluate the sample size necessary for achieving a desirable ...model-based reproducibility.•Model-based reproducibility >0.99 was observed for a few large sample size analyses.•Both sample size and study-specific experimental factors play important roles in model-based reproducibility assessment.
Magnetic Resonance Imaging (MRI) technology has been increasingly used in neuroscience studies. Reproducibility of statistically significant findings generated by MRI-based studies, especially association studies (phenotype vs. MRI metric) and task-induced brain activation, has been recently heavily debated. However, most currently available reproducibility measures depend on thresholds for the test statistics and cannot be use to evaluate overall study reproducibility. It is also crucial to elucidate the relationship between overall study reproducibility and sample size in an experimental design. In this study, we proposed a model-based reproducibility index to quantify reproducibility which could be used in large-scale high-throughput MRI-based studies including both association studies and task-induced brain activation. We performed the model-based reproducibility assessments for a few association studies and task-induced brain activation by using several recent large sMRI/fMRI databases. For large sample size association studies between brain structure/function features and some basic physiological phenotypes (i.e. Sex, BMI), we demonstrated that the model-based reproducibility of these studies is more than 0.99. For MID task activation, similar results could be observed. Furthermore, we proposed a model-based analytical tool to evaluate minimal sample size for the purpose of achieving a desirable model-based reproducibility. Additionally, we evaluated the model-based reproducibility of gray matter volume (GMV) changes for UK Biobank (UKB) vs. Parkinson Progression Marker Initiative (PPMI) and UK Biobank (UKB) vs. Human Connectome Project (HCP). We demonstrated that both sample size and study-specific experimental factors play important roles in the model-based reproducibility assessments for different experiments. In summary, a systematic assessment of reproducibility is fundamental and important in the current large-scale high-throughput MRI-based studies.
The objective was a large-scale analysis of the relation between hypertension, memory problems, and brain function.
The study design was to measure the association between a history of hypertension, ...and the functional connectivity between 94 brain regions, and prospective and numeric memory, in 19,507 participants from the UK Biobank, with cross-validation in 1,002 participants in the Human Connectome Project, and 13,441 individuals in the second release of the UK Biobank. A history of hypertension was measured by whether individuals were admitted to hospital for the treatment of hypertension, with the control group admissions for other reasons.
A history of hypertension was associated with reduced functional connectivity of the hippocampus, and with reduced prospective memory score (FDR correction p<0.01). The reduced functional connectivity mediated the association between the hypertension history and the prospective memory score. A graded linear relation between both the hippocampal functional connectivity and memory impairment, was found across a wide range of blood pressure (r=-0.04). In 502,537 participants from the UK Biobank, a history of hypertension was associated with impaired prospective memory (p = 9.1 × 10−41, Cohen's d=-0.08) and numeric memory (p = 4.7 × 10−24, Cohen's d=-0.10). The association between hypertension, functional connectivity, and impaired memory was cross-validated with 1,002 participants from the Human Connectome Project; and for functional connectivity in 13,441 individuals in the second release of the UK Biobank imaging dataset.
The reduced functional connectivity of the hippocampus, and the memory impairments, both related to hypertension across a wide range of blood pressure, are important for clinical practice.
Macroinvertebrates play a vital role in coastal ecosystems and are an important indicator of ecosystem quality. Both anthropogenic activity and environmental changes may lead to significant changes ...in the marine macroinvertebrate community. However, the assembly process of benthic biodiversity and its mechanism driven by environmental factors at large scales remains unclear. Here, using the benthic field survey data of 15 years at large spatial and temporal scales from the Yellow Sea Large Marine Ecosystem, we investigated the relative importance of environmental selection, dispersal processes, random‐deterministic processes of macroinvertebrates community diversity assembly, and the responses of this relative importance driven by temperature and nutrients. Results showed that the macroinvertebrates community diversity is mainly affected by dispersal. Nitrogen and phosphorus are the most important negative factors among environmental variables, while geographical distance is the main limiting factor of β diversity. Within the range of 0.35–0.70 mg/L of nutrients, increasing nutrient concentration can significantly facilitate the contribution of the decay effect to β diversity. Within the temperature range studied (15.0–18.0°C), both warming and cooling can lead to a greater tendency for species diversity assembly processes to be dominated by deterministic processes. The analysis contributes to a better understanding of the assembly process of the diversity of coastal marine macroinvertebrates communities and how they adapt to global biogeochemical processes.
The assembly mechanism of macroinvertebrates diversity in offshore waters is dominated by the dispersal process and random model, and this trend is maintained on a long‐time scale.
Attention-deficit/hyperactivity disorder (ADHD) comorbid with sleep disturbances can produce profound disruption in daily life and negatively impact quality of life of both the child and the family. ...However, the temporal relationship between ADHD and sleep impairment is unclear, as are underlying common brain mechanisms.
This study used data from the Quebec Longitudinal Study of Child Development (n = 1601, 52% female) and the Adolescent Brain Cognitive Development Study (n = 3515, 48% female). Longitudinal relationships between symptoms were examined using cross-lagged panel models. Gray matter volume neural correlates were identified using linear regression. The transcriptomic signature of the identified brain-ADHD-sleep relationship was characterized by gene enrichment analysis. Confounding factors, such as stimulant drugs for ADHD and socioeconomic status, were controlled for.
ADHD symptoms contributed to sleep disturbances at one or more subsequent time points in both cohorts. Lower gray matter volumes in the middle frontal gyrus and inferior frontal gyrus, amygdala, striatum, and insula were associated with both ADHD symptoms and sleep disturbances. ADHD symptoms significantly mediated the link between these structural brain abnormalities and sleep dysregulation, and genes were differentially expressed in the implicated brain regions, including those involved in neurotransmission and circadian entrainment.
This study indicates that ADHD symptoms and sleep disturbances have common neural correlates, including structural changes of the ventral attention system and frontostriatal circuitry. Leveraging data from large datasets, these results offer new mechanistic insights into this clinically important relationship between ADHD and sleep impairment, with potential implications for neurobiological models and future therapeutic directions.
In this paper, we study the asymptotic and transient dynamics of a predator–prey model with square root functional responses and random perturbation. Firstly, the mean square stability matrix is ...obtained from the stability theory of stochastic systems, and three stability indexes (root-mean-square resilience, root-mean-square reactivity and root-mean-square amplification envelope) of the ecosystem response to stochastic disturbances are calculated. We find that: (1) no matter which population is disturbed, increasing the intensity of disturbance improves the ability of the system leaves steady state and thus decreases the stability. The root-mean-square amplification envelope rises with increasing disturbance intensity, (2) the system is more sensitive to the disturbance of the predator than disturbance to prey, (3) ρmax and tmax are important indicators, which represent the intensity and time of maximum amplification by disturbance. These findings are helpful for managers to take corresponding management measures to reduce the disturbances, especially for predators, thereby avoiding the possible change of the structure and functions of the ecosystem.
Network communities refer to groups of vertices within which their connecting links are dense but between which they are sparse. A network community mining problem (or NCMP for short) is concerned ...with the problem of finding all such communities from a given network. A wide variety of applications can be formulated as NCMPs, ranging from social and/or biological network analysis to web mining and searching. So far, many algorithms addressing NCMPs have been developed and most of them fall into the categories of either optimization based or heuristic methods. Distinct from the existing studies, the work presented in this paper explores the notion of network communities and their properties based on the dynamics of a stochastic model naturally introduced. In the paper, a relationship between the hierarchical community structure of a network and the local mixing properties of such a stochastic model has been established with the large-deviation theory. Topological information regarding to the community structures hidden in networks can be inferred from their spectral signatures. Based on the above-mentioned relationship, this work proposes a general framework for characterizing, analyzing, and mining network communities. Utilizing the two basic properties of metastability, i.e., being locally uniform and temporarily fixed, an efficient implementation of the framework, called the LM algorithm, has been developed that can scalably mine communities hidden in large-scale networks. The effectiveness and efficiency of the LM algorithm have been theoretically analyzed as well as experimentally validated.
Complex neuronal networks are an important tool to help explain paradoxical phenomena observed in biological recordings. Here we present a general approach to mathematically tackle a complex neuronal ...network so that we can fully understand the underlying mechanisms. Using a previously developed network model of the milk-ejection reflex in oxytocin cells, we show how we can reduce a complex model with many variables and complex network topologies to a tractable model with two variables, while retaining all key qualitative features of the original model. The approach enables us to uncover how emergent synchronous bursting can arise from a neuronal network which embodies known biological features. Surprisingly, the bursting mechanisms are similar to those found in other systems reported in the literature, and illustrate a generic way to exhibit emergent and multiple time scale oscillations at the membrane potential level and the firing rate level.
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