Electrocorticography (ECoG) uses electrodes placed directly on the exposed surface of the brain to record electrical activity from the cerebral cortex. Neurosurgeons have long used ECoG during surgery to treat epilepsy to determine where in the brain the seizures are originating. ECoG also has yielded insights into how brain dynamics produce perception, behavior, and cognition in humans. Yet, the origin of the electrical signals recorded at the cortical surface by ECoG has remained a mystery.
“ECoG is an aggregate, mesoscale signal,” explained Kris Bouchard, a staff scientist in the Biological Systems and Engineering (BSE) Division. “The lack of a deeper, more precise understanding of what is generating that signal hinders the ability to use it both for clinical applications and as a basic neuroscience tool.”
Bouchard, who also heads the integrated Computational Biosciences Group based in the Computing Sciences Area, led a seven-year research effort to understand precisely which neurons are generating the recorded signals. The project involved developing new ECoG devices, performing brain surgery on rats to record their neurological signals, developing new machine-learning algorithms to process the data, and running a full-scale biophysically accurate simulation at the National Energy Research Scientific Computing Center (NERSC).
The team found that the majority—about 85% percent—of the electrical signals picked up by ECoG are produced by neurons in the deepest layers of the cortex, rather than by those closer to the surface and therefore nearer to the sensors. Distance, it turns out, is but a minor factor; neurons are more densely packed in the layers deep in the brain and have a greater propensity to fire simultaneously, which contributes to strong signals.
This improved knowledge of the fundamental processes that generate recorded brain signals offers researchers new tools for understanding brain processing, connecting animal studies with human physiology, and coming up with more effective therapeutics.
Details and results of the project were published in the Journal of Neuroscience.
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