Connectivity adaptations in dopaminergic systems define the brain maturity of investors.
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ABSTRACT:
SUBMITTER: Ortiz-Teran E
PROVIDER: S-EPMC8175592 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Neuroimaging-based functional connectivity (FC) analyses have revealed significant developmental trends in specific intrinsic connectivity networks linked to cognitive and behavioral maturation. However, knowledge of how brain functional maturation is associated with FC dynamics at rest is limited. Here, we examined age-related differences in the temporal variability of FC dynamics with data publicly released by the Nathan Kline Institute (NKI; n = 183, ages 7-30) and showed that dynamic inter-region interactions can be used to accurately predict individual brain maturity across development. Furthermore, we identified a significant age-dependent trend underlying dynamic inter-network FC, including increasing variability of the connections between the visual network, default mode network (DMN) and cerebellum as well as within the cerebellum and DMN and decreasing variability within the cerebellum and between the cerebellum and DMN as well as the cingulo-opercular network. Overall, the results suggested significant developmental changes in dynamic inter-network interaction, which may shed new light on the functional organization of typical developmental brains.
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Project description:The ability to make individual-level predictions from neuroanatomy has the potential to be particularly useful in child development. Previously, resting-state functional connectivity (RSFC) MRI has been used to successfully predict maturity and diagnosis of typically and atypically developing individuals. Unfortunately, submillimeter head motion in the scanner produces systematic, distance-dependent differences in RSFC and may contaminate, and potentially facilitate, these predictions. Here, we evaluated individual age prediction with RSFC after stringent motion denoising. Using multivariate machine learning, we found that 57% of the variance in individual RSFC after motion artifact denoising was explained by age, while 4% was explained by residual effects of head motion. When RSFC data were not adequately denoised, 50% of the variance was explained by motion. Reducing motion-related artifact also revealed that prediction did not depend upon characteristics of functional connections previously hypothesized to mediate development (e.g., connection distance). Instead, successful age prediction relied upon sampling functional connections across multiple functional systems with strong, reliable RSFC within an individual. Our results demonstrate that RSFC across the brain is sufficiently robust to make individual-level predictions of maturity in typical development, and hence, may have clinical utility for the diagnosis and prognosis of individuals with atypical developmental trajectories.
| S-EPMC6519700 | biostudies-literature
Project description:The architecture of the human connectome changes with brain maturation. Pivotal to understanding these changes is defining developmental periods when transitions in network topology occur. Here, using 110 resting-state functional connectivity data sets from healthy fetuses between 19 and 40 gestational weeks, we estimated optimal gestational-age (GA) cut points for dichotomizing fetuses into 'young' and 'old' groups based on global network features. We computed the small-world index, normalized clustering and path length, global and local efficiency, and modularity from connectivity matrices comprised 200 regions and their corresponding pairwise connectivity. We modeled the effect of GA at scan on each metric using separate repeated-measures generalized estimating equations. Our modeling strategy involved stratifying fetuses into 'young' and 'old' based on the scan occurring before or after a selected GA (i.e., 28 to 33). We then used the quasi-likelihood independence criterion statistic to compare model fit between 'old' and 'young' cohorts and determine optimal cut points for each graph metric. Trends for all metrics, except for global efficiency, decreased with increasing gestational age. Optimal cut points fell within 30-31 weeks for all metrics coinciding with developmental events that include a shift from endogenous neuronal activity to sensory-driven cortical patterns.
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Project description:Provider health systems as venture capital investors in digital health are uniquely positioned in the industry. Little is known about the volume or characteristics of their investments and how these compare to other investors. From 2011 to 2019, we found that health systems made 184 investments in 105 companies. Compared with other investors, they were more likely to invest in companies focused on workflow, on-demand health services, and data infrastructure/interoperability.
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Project description:PurposeGreulich and Pyle is the most used system to estimate skeletal maturity but has significant drawbacks, prompting the development of newer skeletal maturity systems, such as the modified Fels skeletal maturity systems based on knee radiographs. To create a new skeletal maturity system, an outcome variable, termed a "skeletal maturity standard," must be selected for calibration of the system. Peak height velocity and 90% of final height are both considered reasonable skeletal maturity standards for skeletal maturity system development. We sought to answer two questions: (1) Does a skeletal maturity system developed using 90% of final height estimate skeletal age as well as it would if it was instead developed using peak height velocity? (2) Does a skeletal maturity system developed using 90% of final height perform as well in lower extremity length prediction as it would if it was instead developed using peak height velocity?MethodsThe modified Fels knee skeletal maturity system was recalibrated based on 90% of final height and peak height velocity skeletal maturity standards. These models were applied to 133 serially obtained, peripubertal antero-posterior knee radiographs collected from 38 subjects. Each model was used to estimate the skeletal age of each radiograph. Skeletal age estimates were also used to predict each patient's ultimate femoral and tibial length using the White-Menelaus method.ResultsThe skeletal maturity system calibrated with 90% of final height produced more accurate skeletal age estimates than the same skeletal maturity system calibrated with peak height velocity (p < 0.05). The 90% of final height and peak height velocity models made similar femoral and tibial length predictions (p > 0.05).ConclusionUsing the 90% of final height skeletal maturity standard allows for simpler skeletal maturity system development than peak height velocity with potentially more accuracy.
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Project description:Major depressive disorder (MDD), a common psychiatric condition, adversely affects patients' moods and quality of life. Despite the development of various treatments, many patients with MDD remain vulnerable and inadequately controlled. Since anhedonia is a feature of depression and there is evidence of leading to metabolic disorder, deep brain stimulation (DBS) to the nucleus accumbens (NAc) might be promising in modulating the dopaminergic pathway. To determine whether NAc-DBS alters glucose metabolism via mitochondrial alteration and neurogenesis and whether these changes increase neural plasticity that improves behavioral functions in a chronic social defeat stress (CSDS) mouse model. The Lab-designed MR-compatible neural probes were implanted in the bilateral NAc of C57BL/6 mice with and without CSDS, followed by DBS or sham stimulation. All animals underwent open-field and sucrose preference testing, and brain resting-state functional MRI analysis. Meanwhile, we checked the placement of neural probes in each mouse by T2 images. By confirming the placement location, mice with incorrect probe placement (the negative control group) showed no significant therapeutic effects in behavioral performance and functional connectivity (FC) after receiving electrical stimulation and were excluded from further analysis. Western blotting, seahorse metabolic analysis, and electron microscopy were further applied for the investigation of NAc-DBS. We found NAc-DBS restored emotional deficits in CSDS-subjected mice. Concurrent with behavioral amelioration, the CSDS DBS-on group exhibited enhanced FC in the dopaminergic pathway with increased expression of BDNF- and NeuN-positive cells increased dopamine D1 receptor, dopamine D2 receptors, and TH in the medial prefrontal cortex, NAc, ventral hippocampus, ventral tegmental area, and amygdala. Increased pAMPK/total AMPK and PGC-1α levels, functions of oxidative phosphorylation, and mitochondrial biogenesis were also observed after NAc-DBS treatment. Our findings demonstrate that NAc-DBS can promote BDNF expression, which alters FC and metabolic profile in the dopaminergic pathway, suggesting a potential strategy for ameliorating emotional processes in individuals with MDD.
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Project description:Our recent single-cell sequencing of most adult Drosophila circadian neurons indicated notable and unexpected heterogeneity. To address whether other populations are similar, we sequenced a large subset of adult brain dopaminergic neurons. Their gene expression heterogeneity is similar to that of clock neurons, i.e., both populations have two to three cells per neuron group. There was also unexpected cell-specific expression of neuron communication molecule messenger RNAs: G protein–coupled receptor or cell surface molecule (CSM) transcripts alone can define adult brain dopaminergic and circadian neuron cell type. Moreover, the adult expression of the CSM DIP-beta in a small group of clock neurons is important for sleep. We suggest that the common features of circadian and dopaminergic neurons are general, essential for neuronal identity and connectivity of the adult brain, and that these features underlie the complex behavioral repertoire of Drosophila.
2023-02-25 | GSE198948 | GEO
Project description:BackgroundCortical deep brain stimulation (DBS) is a promising therapeutic option for treatment-refractory depression, but its mode of action remains enigmatic. Serotonin (5-HT) systems are engaged indirectly by ventromedial prefrontal cortex (vmPFC) DBS. Resulting neuroplastic changes in 5-HT systems could thus coincide with the long-term therapeutic activity of vmPFC DBS.MethodsWe tested this hypothesis by evaluating the antidepressant-like activity of vmPFC DBS in the chronic social defeat stress (CSDS) model of depression (n = 8-13 mice/group). Circuit-wide activation induced by vmPFC DBS was mapped with c-Fos immunolabeling. The effects of chronic vmPFC DBS on the physiology and morphology of genetically identified 5-HT cells from the dorsal raphe nucleus (DRN) were examined with whole-cell recording, somatodendritic three-dimensional reconstructions and morphometric analyses of presynaptic boutons along 5-HT axons.ResultsAcute DBS drove c-Fos expression locally in the vmPFC and in several distal monosynaptically connected regions, including the DRN. Chronic DBS reversed CSDS-induced social avoidance, restored the disrupted balance of excitatory/inhibitory inputs onto 5-HT neurons, and reversed 5-HT hypoexcitability observed after CSDS. Furthermore, vmPFC DBS reversed CSDS-induced arborization of 5-HT dendrites in the DRN and increased the size and density of 5-HT presynaptic terminals in the dentate gyrus and vmPFC.ConclusionsWe validate a new preclinical paradigm to examine cellular mechanisms underlying the antidepressant-like activity of vmPFC DBS and identify dramatic circuit-mediated cellular adaptations that coincide with this treatment. These neuroplastic changes of 5-HT neurons might contribute to the progressive mood improvements reported in patients treated with chronic courses of cortical DBS.
| S-EPMC4072754 | biostudies-literature
Project description:Patterns of synaptic connectivity are remarkably precise and complex. Single-cell RNA sequencing has revealed a vast transcriptional diversity of neurons. Nevertheless, a clear logic underlying the transcriptional control of neuronal connectivity has yet to emerge. Here, we focused on Drosophila T4/T5 neurons, a class of closely related neuronal subtypes with different wiring patterns. Eight subtypes of T4/T5 neurons are defined by combinations of two patterns of dendritic inputs and four patterns of axonal outputs. Single-cell profiling during development revealed distinct transcriptional programs defining each dendrite and axon wiring pattern. These programs were defined by the expression of a few transcription factors and different combinations of cell surface proteins. Gain and loss of function studies provide evidence for independent control of different wiring features. We propose that modular transcriptional programs for distinct wiring features are assembled in different combinations to generate diverse patterns of neuronal connectivity.
2019-11-05 | GSE126139 | GEO
Project description:BackgroundLearning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning.Methodology/principal findingsWe performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN.Conclusions/significanceThese results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning.
| S-EPMC3894973 | biostudies-literature