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August 25, 2026
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Minimum-Norm Estimation of Motor Representations in Navigated TMS Mappings

Brain Topography. 2017. Vol. 30. No. 6. P. 711–722.
Pitkänen M., Kallioniemi E., Julkunen P., Nazarova M., Nieminen J., Ilmoniemi R.

Navigated transcranial magnetic stimulation (nTMS) can be applied to locate and outline cortical motor representations. This may be important, e.g., when planning neurosurgery or focused nTMS therapy, or when assessing plastic changes during neurorehabilitation. Conventionally, a cortical location is considered to belong to the motor cortex if the maximum electric field (E-field) targeted there evokes a motor-evoked potential in a muscle. However, the cortex is affected by a broad E-field distribution, which tends to broaden estimates of representation areas by stimulating also the neighboring areas in addition to the maximum E-field location. Our aim was to improve the estimation of nTMS-based motor maps by taking into account the E-field distribution of the stimulation pulse. The effect of the E-field distribution was considered by calculating the minimum-norm estimate (MNE) of the motor representation area. We tested the method on simulated data and then applied it to recordings from six healthy volunteers and one stroke patient. We compared the motor representation areas obtained with the MNE method and a previously introduced interpolation method. The MNE hotspots and centers of gravity were close to those obtained with the interpolation method. The areas of the maps, however, depend on the thresholds used for outlining the areas. The MNE method may improve the definition of cortical motor areas, but its accuracy should be validated by comparing the results with maps obtained with direct cortical stimulation of the cortex where the E-field distribution can be better focused.

Research target: Psychology Biology Earth Sciences
Priority areas: humanitarian engineering science
Language: English
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Keywords: Brain Mappingmotor cortexTMS
Publication based on the results of:
Активное и пассивное декодирование нейрональных процессов при выполнении когнитивных и нейроэкономических задач (2017)
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