Journal: Cell reports

Article Title: Multi-modal characterization and simulation of human epileptic circuitry

doi: 10.1016/j.celrep.2022.111873

Figure Lengend Snippet:

Article Snippet: Single-neuron biophysical all-active models , Allen Institute for Brain Science , https://portal.brain-map.org/explore/models/perisomatic-single-neurons.

Techniques: Software, Extraction

Journal: eNeuro

Article Title: Modeling Brain Dynamics in Brain Tumor Patients Using the Virtual Brain

doi: 10.1523/ENEURO.0083-18.2018

Figure Lengend Snippet: Graphical summary of computational modeling workflow using TVB. Imaging: As input to the model, individual neuroimaging data should be acquired. Diffusion MRI data processed to an SC matrix as input for TVB, and resting-state functional MRI data processed to an empirical functional connectivity (FCemp) matrix to evaluate model fit (red, positive connection weights; blue, negative connection weights). Personalized virtual brain model: Local dynamics in each of the 68 Freesurfer cortical brain regions were simulated using the Reduced Wong–Wang model , implemented as highly optimized C code that allows for efficient parameter exploration . Excitatory neural mass models of all 68 brain regions were subsequently coupled according to the individual subject’s empirical structural connectome and weighted by a global scaling factor ( G ) to simulate large-scale brain dynamics. Resting-state BOLD time series were generated with the same duration and sampling rate as the subject’s empirical resting-state fMRI acquisition, using the Balloon–Windkessel hemodynamic model . From these simulated time series, a simulated functional connectivity (FCsim) matrix was computed. Identify optimal model parameters: To optimize the fit between empirical and simulated FC, subject-specific parameter space explorations were conducted in which G was optimized. For each value of G , a simulated FC matrix was constructed. The value of G that maximized the link-wise Pearson correlation between each individual’s simulated and empirical functional connectivity matrix was then selected for further analyses. Run statistics: Individually optimized model parameters were subsequently tested for group differences and correlated with structural graph theory metrics and cognitive performance.

Article Snippet: ------------- Reviewer 2: The aim of the manuscript was to integrate neuroimaging data with biophysically based The Virtual Brain (TVB) model to determine whether the individually optimized biophysical model parameter values would differ between brain tumor patients with glioma or meningioma and control participants.

Techniques: Imaging, Diffusion-based Assay, Functional Assay, Generated, Sampling, Construct