RESUMO
The thalamus is a central brain structure that serves as a relay station for sensory inputs from the periphery to the cortex and regulates cortical arousal. Traditionally, it has been regarded as a passive relay that transmits information between brain regions. However, recent studies have suggested that the thalamus may also play a role in shaping functional connectivity (FC) in a task-based context. Based on this idea, we hypothesized that due to its centrality in the network and its involvement in cortical activation, the thalamus may also contribute to resting-state FC, a key neurological biomarker widely used to characterize brain function in health and disease. To investigate this hypothesis, we constructed ten in-silico brain network models based on neuroimaging data (MEG, MRI, and dwMRI), and simulated them including and excluding the thalamus, and raising the noise into thalamus to represent the afferences related to the reticular activating system (RAS) and the relay of peripheral sensory inputs. We simulated brain activity and compared the resulting FC to their empirical MEG counterparts to evaluate model's performance. Results showed that a parceled version of the thalamus with higher noise, able to drive damped cortical oscillators, enhanced the match to empirical FC. However, with an already active self-oscillatory cortex, no impact on the dynamics was observed when introducing the thalamus. We also demonstrated that the enhanced performance was not related to the structural connectivity of the thalamus, but to its higher noisy inputs. Additionally, we highlighted the relevance of a balanced signal-to-noise ratio in thalamus to allow it to propagate its own dynamics. In conclusion, our study sheds light on the role of the thalamus in shaping brain dynamics and FC in resting-state and allowed us to discuss the general role of criticality in the brain at the mesoscale level.
Assuntos
Encéfalo , Tálamo , Encéfalo/fisiologia , Tálamo/diagnóstico por imagem , Tálamo/fisiologia , Imageamento por Ressonância Magnética/métodos , Tronco Encefálico , Mapeamento Encefálico/métodos , Vias Neurais/fisiologiaRESUMO
BACKGROUND: Transcutaneous bilirubinometry is a widely used screening method for neonatal hyperbilirubinemia. Deviation of the transcutaneous bilirubin concentration (TcB) from the total serum bilirubin concentration (TSB) is often ascribed to biological variation between patients, but variations between TcB meters may also have a role. This study aims to provide a systematic evaluation of the inter-device reproducibility of TcB meters. MATERIALS AND METHODS: Thirteen commercially available TcB meters (JM-105 and JM-103) were evaluated in vitro on phantoms that optically mimic neonatal skin. The mimicked TcB was varied within the clinical range (0.5-181.3 µmol/L). RESULTS: Absolute differences between TcB meter outcomes increased with the measured TcB, from a difference of 5.0 µmol/L (TcB = 0.5 µmol/L phantom) up to 65.0 µmol/L (TcB = 181.3 µmol/L phantom). CONCLUSION: The inter-device reproducibility of the examined TcB meters is substantial and exceeds the specified accuracy of the device (±25.5 µmol/L), as well as the clinically used TcB safety margins (>50 µmol/L below phototherapy threshold). Healthcare providers should be well aware of this additional uncertainty in the TcB determination, especially when multiple TcB meters are employed in the same clinic. We strongly advise using a single TcB meter per patient to evaluate the TcB over time. IMPACT: Key message: The inter-device reproducibility of TcB meters is substantial and exceeds the clinically used TcB safety margins. What this study adds to existing literature: The inter-device reproducibility of transcutaneous bilirubin (TcB) meters has not been reported in the existing literature. This in vitro study systematically evaluates this inter-device reproducibility. IMPACT: This study aids in a better interpretation of the measured TcB value from a patient and is of particular importance during patient monitoring when using multiple TcB meters within the same clinical department. We strongly advise using a single TcB meter per patient to evaluate the TcB over time.
Assuntos
Bilirrubina/análise , Bilirrubina/sangue , Hiperbilirrubinemia Neonatal/diagnóstico , Testes Diagnósticos de Rotina , Desenho de Equipamento , Humanos , Recém-Nascido , Doenças do Recém-Nascido , Recém-Nascido Prematuro/sangue , Monitorização Fisiológica , Triagem Neonatal/métodos , Imagens de Fantasmas , Reprodutibilidade dos Testes , Fenômenos Fisiológicos da PeleRESUMO
Dravet Syndrome (DS) is a severe developmental epileptic encephalopathy with frequent intractable seizures accompanied by cognitive impairment, often caused by pathogenic variants in SCN1A encoding sodium channel NaV1.1. Recent research utilizing in vitro patient-derived neuronal networks and accompanying in silico models uncovered that not just sodium-but also potassium-and synaptic currents were impaired in DS networks. Here, we explore the implications of these findings for three questions that remain elusive in DS: How do sodium channel impairments result in epilepsy? How can identical variants lead to varying phenotypes? What mechanisms underlie the developmental delay in DS patients? We speculate that impaired potassium currents might be a secondary effect to NaV1.1 mutations and could result in hyperexcitable neurons and epileptic networks. Moreover, we reason that homeostatic plasticity is actively engaged in DS networks, possibly affecting the phenotype and impairing learning and development when driven to extremes.
Assuntos
Epilepsias Mioclônicas , Humanos , Epilepsias Mioclônicas/genética , Epilepsias Mioclônicas/patologia , Canal de Sódio Disparado por Voltagem NAV1.1/genética , Neurônios/patologia , Neurônios/fisiologia , Mutação , Fenótipo , PotássioRESUMO
Human induced pluripotent stem cell (hiPSC)-derived neuronal networks on multi-electrode arrays (MEAs) provide a unique phenotyping tool to study neurological disorders. However, it is difficult to infer cellular mechanisms underlying these phenotypes. Computational modeling can utilize the rich dataset generated by MEAs, and advance understanding of disease mechanisms. However, existing models lack biophysical detail, or validation and calibration to relevant experimental data. We developed a biophysical in silico model that accurately simulates healthy neuronal networks on MEAs. To demonstrate the potential of our model, we studied neuronal networks derived from a Dravet syndrome (DS) patient with a missense mutation in SCN1A, encoding sodium channel NaV1.1. Our in silico model revealed that sodium channel dysfunctions were insufficient to replicate the in vitro DS phenotype, and predicted decreased slow afterhyperpolarization and synaptic strengths. We verified these changes in DS patient-derived neurons, demonstrating the utility of our in silico model to predict disease mechanisms.