Motor cortex mapping using active gaussian processes
Motor cortex mapping using active gaussian processes
复制标题
使用主动高斯过程进行运动皮层映射
DOI:
10.1145/3389189.3389202
复制
发表时间:
2020
期刊:
影响因子:
--
通讯作者:
Erdoğmuş, Deniz
中科院分区:
文献类型:
--
作者:
Faghihpirayesh, Razieh;Imbiriba, Tales;Yarossi, Mathew;Tunik, Eugene;Brooks, Dana;Erdoğmuş, Deniz
One important application of transcranial magnetic stimulation (TMS) is to map cortical motor topography by spatially sampling the motor cortex, and recording motor evoked potentials (MEP) with surface electromyography. Standard approaches to TMS mapping involve repetitive stimulations at different loci spaced on a (typically 1 cm) grid on the scalp. These mappings strategies are time consuming and responsive sites are typically sparse. Furthermore, the long time scale prevents measurement of transient cortical changes, and is poorly tolerated in clinical populations. An alternative approach involves using the TMS mapper expertise to exploit the map's sparsity through the use of feedback of MEPs to decide which loci to stimulate. In this investigation, we propose a novel active learning method to automatically infer optimal future stimulus loci in place of user expertise. Specifically, we propose an active Gaussian Process (GP) strategy with loci selection criteria such as entropy and mutual information (MI). The proposed method twists the usual entropy- and MI-based selection criteria by modeling the estimated MEP field, i.e., the GP mean, as a Gaussian random variable itself. By doing so, we include MEP amplitudes in the loci selection criteria which would be otherwise completely independent of the MEP values. Experimental results using real data shows that the proposed strategy can greatly outperform competing methods when the MEP variations are mostly confined in a sub-region of the space.
登录
查看更多内容
DOI:
10.1016/s0924-980x(98)00006-x
发表时间:
1998
期刊:
Electroencephalography and clinical neurophysiology
影响因子:
--
作者:
G. Thickbroom;R. Sammut;F. Mastaglia
通讯作者:
F. Mastaglia
影响因子:
5.1
作者:
Huber, Marco F.
通讯作者:
Huber, Marco F.
DOI:
10.1109/icassp.2014.6855148
发表时间:
2014
期刊:
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
影响因子:
--
作者:
T. Imbiriba;J. Bermudez;J. Tourneret;C. Richard
通讯作者:
C. Richard
影响因子:
4.4
作者:
WILSON, SA;THICKBROOM, GW;MASTAGLIA, FL
通讯作者:
MASTAGLIA, FL
影响因子:
3.9
作者:
Kocanaogullari, Aziz;Erdogmus, Deniz;Akcakaya, Murat
通讯作者:
Akcakaya, Murat