A Network Inversion Technique for Estimating Equivalent Dipole Description of Visual Evoked Potential
07 February 2018 (online)
For the activation study of the brain, dipole localization from the scalp potential is one of the most promising techniques to realize a reasonable temporal resolution which cannot be realized in functional MR and PET. The goal of our study is to estimate inversely the electrical brain activity in the form of several dipoles from the scalp potential, using a network inversion technique. As a basic approach, we have inversely estimated several dipoles from the potential distribution on a spherical surface, in the homogeneous sphere model.
In the training phase, by expanding the neural network input dimensions being redundant, the network can easily learn the forward mapping. In the inversion phase, the space of the expanded-network-input-vector can be narrowed by introducing a penalty term. Additionally, a consensus term was used to force several dipoles to have a similar orientation. We estimate that this is applicable to the localization of several dipoles that reflect the actual brain activity, especially in the visual evoked potentials.
- 1 Linden A, Kindermann J. Inversion of multilayer nets. Proc. IJCNN. pp. 425-30 1989
- 2 Kavanagh RN, Darcey TM, Lehmann D. et al. Evaluation of methods for three-dimensional localization of electrical sources in the human brain. IEEE Trans. on BME, Vol. BME-25, No. 5, pp. 421-429 1978
- 3 Uemoto N, Kosugi Y. Dynamic regularization for the restoration of PET images. The Trans. IEICE, Jap D-II, Vol. J81-D-II No.6 pp. 1421-8 1998
- 4 He B, Musha T. et al. Electric dipole tracing in the brain by means of the boundary element method and its accuracy. IEEE Trans. on BME, Vol. BME-34, No. 6, pp. 406-14 1987