OBJECTIVE: Many brain-computer interfaces (BCIs) use band power (BP) changes in the electroencephalogram to distinguish between different motor imagery (MI) patterns. Most current approaches do not take connectivity of separated brain areas into account. Our objective is to introduce single-trial connectivity features and apply these features to BCI data. APPROACH: We introduce a procedure for extracting single-trial connectivity estimates from vector autoregressive (VAR) models of independent components in a BCI setting. MAIN RESULTS: In a simulated BCI, we demonstrate that the directed transfer function (DTF) with full-frequency normalization and the direct DTF give classification results similar to BP, while other measures such as the partial directed coherence perform significantly worse. SIGNIFICANCE: We show that single-trial MI classification is possible with connectivity measures extracted from VAR models, and that a BCI could potentially utilize such measures.
OBJECTIVE: Many brain-computer interfaces (BCIs) use band power (BP) changes in the electroencephalogram to distinguish between different motor imagery (MI) patterns. Most current approaches do not take connectivity of separated brain areas into account. Our objective is to introduce single-trial connectivity features and apply these features to BCI data. APPROACH: We introduce a procedure for extracting single-trial connectivity estimates from vector autoregressive (VAR) models of independent components in a BCI setting. MAIN RESULTS: In a simulated BCI, we demonstrate that the directed transfer function (DTF) with full-frequency normalization and the direct DTF give classification results similar to BP, while other measures such as the partial directed coherence perform significantly worse. SIGNIFICANCE: We show that single-trial MI classification is possible with connectivity measures extracted from VAR models, and that a BCI could potentially utilize such measures.
Authors: Kaitlyn Casimo; Kurt E Weaver; Jeremiah Wander; Jeffrey G Ojemann Journal: IEEE Trans Neural Syst Rehabil Eng Date: 2017-03-13 Impact factor: 3.802
Authors: Tim R Mullen; Christian A E Kothe; Yu Mike Chi; Alejandro Ojeda; Trevor Kerth; Scott Makeig; Tzyy-Ping Jung; Gert Cauwenberghs Journal: IEEE Trans Biomed Eng Date: 2015-09-23 Impact factor: 4.538
Authors: Yvonne Höller; Aljoscha Thomschewski; Andreas Uhl; Arne C Bathke; Raffaele Nardone; Stefan Leis; Eugen Trinka; Peter Höller Journal: Front Neurol Date: 2018-11-19 Impact factor: 4.086
Authors: Vivek P Buch; Andrew G Richardson; Cameron Brandon; Jennifer Stiso; Monica N Khattak; Danielle S Bassett; Timothy H Lucas Journal: Front Neurosci Date: 2018-11-01 Impact factor: 4.677