Publications by authors named "J Fousek"
Spontaneously fluctuating brain activity patterns that emerge at rest have been linked to the brain's health and cognition. Despite detailed descriptions of the spatio-temporal brain patterns, our understanding of their generative mechanism is still incomplete. Using a combination of computational modeling and dynamical systems analysis we provide a mechanistic description of the formation of a resting state manifold via the network connectivity.
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- Age-related changes in the brain impact sleep quality, particularly through alterations in slow-wave sleep properties, though the exact reasons for these changes remain unclear.
- The study modifies an existing brain model to simulate slow-wave sleep, starting with a connectome representative of younger brains and progressively reducing inter-hemispheric connections.
- The model successfully replicates key observations, such as shorter and more variable slow waves, and suggests that reduced synchrony between brain regions contributes to the decrease in amplitude of these waves.
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- The study focuses on assessing promoter activity to better understand plant biosynthetic pathways using a method called agroinfiltration-based transient gene expression assay.
- It compares the activity of various known promoters in the plant Nicotiana benthamiana with their activity in Cannabis sativa, which has gained interest for its diverse applications.
- An optimized protocol for transient expression in Cannabis is outlined, utilizing a ratiometric GUS reporter system to enhance accuracy in evaluating promoter activity by minimizing variable infiltration efficiency.
The mechanisms of cognitive decline and its variability during healthy aging are not fully understood, but have been associated with reorganization of white matter tracts and functional brain networks. Here, we built a brain network modeling framework to infer the causal link between structural connectivity and functional architecture and the consequent cognitive decline in aging. By applying in-silico interhemispheric degradation of structural connectivity, we reproduced the process of functional dedifferentiation during aging.
View Article and Find Full Text PDFWhole brain network models are now an established tool in scientific and clinical research, however their use in a larger workflow still adds significant informatics complexity. We propose a tool, RateML, that enables users to generate such models from a succinct declarative description, in which the mathematics of the model are described without specifying how their simulation should be implemented. RateML builds on NeuroML's Low Entropy Model Specification (LEMS), an XML based language for specifying models of dynamical systems, allowing descriptions of neural mass and discretized neural field models, as implemented by the Virtual Brain (TVB) simulator: the end user describes their model's mathematics once and generates and runs code for different languages, targeting both CPUs for fast single simulations and GPUs for parallel ensemble simulations.
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