TY - JOUR
T1 - High spatiotemporal resolution ECoG recording of somatosensory evoked potentials with flexible micro-electrode arrays
AU - Kaiju, Taro
AU - Doi, Keiichi
AU - Yokota, Masashi
AU - Watanabe, Kei
AU - Inoue, Masato
AU - Ando, Hiroshi
AU - Takahashi, Kazutaka
AU - Yoshida, Fumiaki
AU - Hirata, Masayuki
AU - Suzuki, Takafumi
N1 - Funding Information:
This work was partially supported by the Strategic Research Program for Brain Sciences by the Ministry of Education, Culture, Sports, Science and Technology of Japan, the “Research and development of technologies for high speed wireless communication from inside to outside of the body and large scale data analyses of brain information and their application for BMI” by the Commissioned Research of the National Institute of Information and Communications Technology (NICT), JSPS KAKENHI Grant Number 15H03049 and National Institute of Dental and Craniofacial Research Grant (RO1-DE023816).
Publisher Copyright:
© 2017 Kaiju, Doi, Yokota, Watanabe, Inoue, Ando, Takahashi, Yoshida, Hirata and Suzuki.
PY - 2017/4/11
Y1 - 2017/4/11
N2 - Electrocorticogram (ECoG) has great potential as a source signal, especially for clinical BMI. Until recently, ECoG electrodes were commonly used for identifying epileptogenic foci in clinical situations, and such electrodes were low-density and large. Increasing the number and density of recording channels could enable the collection of richer motor/sensory information, and may enhance the precision of decoding and increase opportunities for controlling external devices. Several reports have aimed to increase the number and density of channels. However, few studies have discussed the actual validity of high-density ECoG arrays. In this study, we developed novel high-density flexible ECoG arrays and conducted decoding analyses with monkey somatosensory evoked potentials (SEPs). Using MEMS technology, we made 96-channel Parylene electrode arrays with an inter-electrode distance of 700 µm and recording site area of 350 µm2. The arrays were mainly placed onto the finger representation area in the somatosensory cortex of the macaque, and partially inserted into the central sulcus. With electrical finger stimulation, we successfully recorded and visualized finger SEPs with a high spatiotemporal resolution. We conducted offline analyses in which the stimulated fingers and intensity were predicted from recorded SEPs using a support vector machine. We obtained the following results: (1) Very high accuracy (∼98%) was achieved with just a short segment of data (∼15 ms from stimulus onset). (2) High accuracy (∼96%) was achieved even when only a single channel was used. This result indicated placement optimality for decoding. (3) Higher channel counts generally improved prediction accuracy, but the efficacy was small for predictions with feature vectors that included time-series information. These results suggest that ECoG signals with high spatiotemporal resolution could enable greater decoding precision or external device control.
AB - Electrocorticogram (ECoG) has great potential as a source signal, especially for clinical BMI. Until recently, ECoG electrodes were commonly used for identifying epileptogenic foci in clinical situations, and such electrodes were low-density and large. Increasing the number and density of recording channels could enable the collection of richer motor/sensory information, and may enhance the precision of decoding and increase opportunities for controlling external devices. Several reports have aimed to increase the number and density of channels. However, few studies have discussed the actual validity of high-density ECoG arrays. In this study, we developed novel high-density flexible ECoG arrays and conducted decoding analyses with monkey somatosensory evoked potentials (SEPs). Using MEMS technology, we made 96-channel Parylene electrode arrays with an inter-electrode distance of 700 µm and recording site area of 350 µm2. The arrays were mainly placed onto the finger representation area in the somatosensory cortex of the macaque, and partially inserted into the central sulcus. With electrical finger stimulation, we successfully recorded and visualized finger SEPs with a high spatiotemporal resolution. We conducted offline analyses in which the stimulated fingers and intensity were predicted from recorded SEPs using a support vector machine. We obtained the following results: (1) Very high accuracy (∼98%) was achieved with just a short segment of data (∼15 ms from stimulus onset). (2) High accuracy (∼96%) was achieved even when only a single channel was used. This result indicated placement optimality for decoding. (3) Higher channel counts generally improved prediction accuracy, but the efficacy was small for predictions with feature vectors that included time-series information. These results suggest that ECoG signals with high spatiotemporal resolution could enable greater decoding precision or external device control.
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U2 - 10.3389/fncir.2017.00020
DO - 10.3389/fncir.2017.00020
M3 - Article
C2 - 28442997
AN - SCOPUS:85019227604
SN - 1662-5110
VL - 11
JO - Frontiers in Neural Circuits
JF - Frontiers in Neural Circuits
M1 - 20
ER -