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978-3-8439-4240-9, Reihe Mikrosystemtechnik
Characterization of Brain Activity Recorded by micro-ECoG Electrode Arrays
191 Seiten, Dissertation Albert-Ludwigs-Universität Freiburg im Breisgau (2019), Softcover, B5
Micro-scale electrocorticography (µECoG) provides insight into cortical organization, with the high temporal and spatial resolution conducive to a better understanding of neural information processing.
The present study employed various generations of custom laser-fabricated µECoG electrode arrays composed entirely of well-established implant materials, suitable for long-term implantation in humans. In the experimental part, μECoG electrode arrays were used to characterize neural activity in the somatosensory cortex of large-size animal models (minipig and sheep) in steps by topographic mapping of signals in broad frequency bands, up to 2,400 Hz. The suitability of animal models and surgical procedures was evaluated for the acute and chronic recordings. Significant and multi-focal cortical somatosensory response patterns were repetitively and reliably recorded both in acute and chronic testing (up to 16 weeks after implantation).
We further present results of a simulation study, based on segmented magnetic resonance imaging (MRI) data of the animal model used for the experimental part and using the state-of-the-art finite element method (FEM). Simulation data combining the adjusted background activity from the experimental data revealed further characteristics of the evoked brain activity, e.g. generator size and layer specificity of cortical origins of different frequency activities, giving us a better understanding of brain activity in different frequency ranges.
This work provides a basis for further chronic investigation with large-size animal models. Our findings show that µECoG electrode arrays composed of clinically approved materials can reliably record and measure signals up to the high and very-high gamma frequency range, and are thereby able to serve as a basis for high-resolution brain mapping, advanced epilepsy diagnostics and brain-machine interfacing (BMI) in paralyzed patients.