Optimal positioning and size of high-density electrocorticography grids for speech brain-computer interfaces

OBJECTIVE: Speech-based brain-computer interfaces (BCIs) can offer an intuitive communication method for those who have lost the ability to speak due to paralysis. Significant progress has been made in classifying individual words from high numbers of electrocorticographic (ECoG) electrodes on the sensorimotor cortex (SMC). As implantations of larger grids with more ECoG electrodes are associated with higher surgical risk, we investigated whether confined electrode configurations can match the classification accuracy of larger grids.

METHODS: We analyzed data from eight able-bodied participants with high-density ECoG grids (64 to 128 electrodes) performing a 12-word repetition task in Dutch.

RESULTS: Word pronunciation elicited high frequency band activity in two SMC foci: one ventral, one dorsal. Smaller, rectangular configurations with surface areas of 325 mm2 to 561 mm2 (32 electrodes) could achieve similar word classification accuracies as larger grids: 76 ± 16% versus 75 ± 17% across participants, respectively (practical chance level 16.7%). The best configurations were oriented vertically and centered on the central sulcus.

CONCLUSION: These findings indicate that a 32-electrode ECoG grid placed optimally can be sufficient for achieving high word classification accuracy on a closed set of words.

SIGNIFICANCE: These findings support the targeted placement of small ECoG grids, reducing surgical demands on end users and justifying energy- and complexity-efficient designs of fully implantable BCI devices for individuals with severe paralysis.