Digital Twin Brain Simulator: Harnessing Primate ECoG Data for Real-Time Consciousness Monitoring and Virtual Intervention
Takahashi, Y.; Idei, H.; Komatsu, M.; Tani, J.; Tomita, H.; Yamashita, Y.
Show abstract
At the forefront of bridging computational brain modeling with personalized medicine, this study introduces a novel, real-time, electrocorticogram (ECoG) simulator based on the digital twin brain concept. Utilizing advanced data assimilation techniques, specifically a Variational Bayesian Recurrent Neural Network model with hierarchical latent units, the simulator dynamically predicts ECoG signals reflecting real-time brain latent states. By assimilating broad ECoG signals from Macaque monkeys across awake and anesthetized conditions, the model successfully updated its latent states in real-time, enhancing the precision of ECoG signal simulations. Behind the successful data assimilation, a self-organization of latent states in the model was observed, reflecting brain states and individuality. This self-organization facilitated simulation of virtual drug administration and uncovered functional networks underlying changes in brain function during anesthesia. These results show that the proposed model is not only capable of simulating brain signals in real-time with high accuracy, but is also useful for revealing underlying information processing dynamics.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Personalized whole-brain models of seizure propagation 95%
- Personalized stimulation therapies for disorders of consciousness: A computational approach to inducing healthy-like brain activity based on neural field theory 95%
- Scalable Surrogate Deconvolution for Identification of Partially-Observable Systems and Brain Modeling 95%
Similar papers in this journal
- Computation of the electroencephalogram (EEG) from network models of point neurons 96%
- Methods and considerations for estimating parameters in biophysically detailed neural models with simulation based inference 96%
- A hidden Markov model reliably characterizes ketamine-induced spectral dynamics in macaque LFP and human EEG 95%
Similar papers in this journal
Similar papers in this journal
- Diffusion model-based image generation from rat brain activity 96%
- Multiscale effective connectivity analysis of brain activity using neural ordinary differential equations 96%
- Personalized models of Disorders of Consciousness revealcomplementary roles of connectivity and local parameters in diagnosis and prognosis 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.