Artificial Intelligence

The impact of external electromagnetic fields (power line or cell phone exposure, transcranial magnetic stimulation, or deep brain stimulation) on the activity of various brain networks is today an intense area of research. One of the main challenges is that the transduction mechanisms, allowing the electromagnetic field to interact with living brain tissue at different spatial scales (cellular organelle, cell membrane, organ), are still unclear. Computational modeling offers an alternative for investigating the plausibility of putative transduction mechanisms.

R.Z. Stodilka
Hybrid imaging
A. Legros
F.S. Prato
nuclear medicine



Future Directions

Ultimately, this class of models should have a predictive value for therapeutic applications especially designed to reshape, using non-invasive magnetic stimulation, brain rhythms altered by diseases.

Key Accomplishments

As a first step towards the modeling of electromagnetic exposure impact on the dynamical response of brain structures, we present a computational model of a local cortical network that receives both internal and external stimuli; in essence a highly-simplified ‘brain model’. Capacitive and inductive coupling between electromagnetic fields and nerve tissue are tested with the model as two possible transduction mechanisms.

Using frequency analysis, we study how simple and complex stimuli modulate the dynamics of this cortical network model depending on exposure duration, stimuli properties and transduction mechanisms. Our early results indicate that simple and complex stimuli induce different responses in the frequency domains, providing design guidelines for testing predictions in future experiments.

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