Network dynamics with BrainX3: a large-scale simulation of the human brain network with real-time interaction

Abstract

BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX3 can thus be used as a novel immersive platform for exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas.

Synthetic consciousness: the distributed adaptive control perspective

“…For this reason, we have embarked on a series of DAC control architectures for humanoid robots that in particular advance human-level embodied social interaction [226]. In order to realize its convergent validation, we have also integrated this humanoid platform with state-of-the-art human connectome models using brainx3 [181,182] that are augmented with fully simulated subcortical structures. DACtoc thus predicts that human-level quale parsing will result from the convergence of humanoid robotics and whole brain modelling following the convergent validation methodology.…”

“…(c) An fMRI analysis of the validation gate displacement task showed that the explicit detection of displacements were correlated with activation of fronto-parietal networks involving middle and right superior frontal gyrus (Brodmann area 10, 11, yellow), right anterior cingulate cortex (ACC, BA32, yellow) and left precuneus (BA7, orange) (data from Malekshahi et al [180]). These areas are projected onto a three-dimensional reconstruction of the human connectome using brainx3, visualizing the structural and functional connectivity between the nodes (green) of the conscious detection network [181,182].…”

Modeling Brain Dynamics in Brain Tumor Patients Using the Virtual Brain

“…A future application of this framework could then entail the presurgical virtual exploration of the effects of different neurosurgical approaches based on individual patient data, to identify an optimal surgical strategy (Arsiwalla et al, 2015; Proix et al, 2017). …”

TempoCave: Visualizing Dynamic Connectome Datasets to Support Cognitive Behavioral Therapy

“…For example, Xing et al's Thought Chart [36] presents distinct 3D trajectories for different task conditions and provides a comparative analysis that generates a summary view of how much one dynamic connectome differs in comparison to others. Similar to our implementation, Arsiwalla et al introduce BrainX 3 [3], an interactive and immersive 3D visualization of dynamic connectomes, but which does not support comparison tasks, a main feature of TempoCave.…”