The size of via holes influence the amplitude and selectivity of neural signals in Micro-ECoG arrays
Electrocorticography (ECoG) arrays are commonly used to record the brain activity both in animal and human subjects. There is a lack of guidelines in the literature as to how the array geometry, particularly the via holes in the substrate, affects the recorded signals. A finite element (FE) model wa...
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Veröffentlicht in: | BMC biomedical engineering 2022-03, Vol.4 (1), p.3-3, Article 3 |
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Sprache: | eng |
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Zusammenfassung: | Electrocorticography (ECoG) arrays are commonly used to record the brain activity both in animal and human subjects. There is a lack of guidelines in the literature as to how the array geometry, particularly the via holes in the substrate, affects the recorded signals. A finite element (FE) model was developed to simulate the electric field generated by neurons located at different depths in the rat brain cortex and a micro ECoG array (μECoG) was placed on the pia surface for recording the neural signal. The array design chosen was a typical array of 8 × 8 circular (100 μm in diam.) contacts with 500 μm pitch. The size of the via holes between the recording contacts was varied to see the effect.
The results showed that recorded signal amplitudes were reduced if the substrate was smaller than about four times the depth of the neuron in the gray matter. The signal amplitude profiles had dips around the via holes and the amplitudes were also lower at the contact sites as compared to the design without the holes; an effect that increased with the hole size. Another noteworthy result is that the spatial selectivity of the multi-contact recordings could be improved or reduced by the selection of the via hole sizes, and the effect depended on the distance between the neuron pair targeted for selective recording and its depth.
The results suggest that the via-hole size clearly affects the recorded neural signal amplitudes and it can be leveraged as a parameter to reduce the inter-channel correlation and thus maximize the information content of neural signals with μECoG arrays. |
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ISSN: | 2524-4426 2524-4426 |
DOI: | 10.1186/s42490-022-00060-4 |