TY - GEN
T1 - A case study on the relation between electroencephalographic and electrocorticographic event-related potentials
AU - Krusienski, Dean J.
AU - Shih, Jerry J.
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - This study presents a preliminary analysis of the relationship between electroencephalographic (EEG) and electrocorticographic (ECoG) event-related potentials (ERPs) recorded from from a single patient using a brain-computer interface (BCI) speller. The patient had medically intractable epilepsy and underwent temporary placement of an intracranial ECoG grid electrode array to localize seizure foci. The patient performed one experimental session using the BCI spelling paradigm controlled by scalp-recorded EEG prior to the ECoG grid implantation, and one identical session controlled by ECoG after the grid implantation. The patient was able to achieve near perfect spelling accuracy using EEG and ECoG. An offline analysis of the average ERPs was performed to assess how accurately the average EEG ERPs could be predicted from the ECoG data. The preliminary results indicate that EEG ERPs can be accurately estimated from proximal asynchronous ECoG data using simple linear spatial models.
AB - This study presents a preliminary analysis of the relationship between electroencephalographic (EEG) and electrocorticographic (ECoG) event-related potentials (ERPs) recorded from from a single patient using a brain-computer interface (BCI) speller. The patient had medically intractable epilepsy and underwent temporary placement of an intracranial ECoG grid electrode array to localize seizure foci. The patient performed one experimental session using the BCI spelling paradigm controlled by scalp-recorded EEG prior to the ECoG grid implantation, and one identical session controlled by ECoG after the grid implantation. The patient was able to achieve near perfect spelling accuracy using EEG and ECoG. An offline analysis of the average ERPs was performed to assess how accurately the average EEG ERPs could be predicted from the ECoG data. The preliminary results indicate that EEG ERPs can be accurately estimated from proximal asynchronous ECoG data using simple linear spatial models.
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U2 - 10.1109/IEMBS.2010.5627603
DO - 10.1109/IEMBS.2010.5627603
M3 - Conference contribution
AN - SCOPUS:78650852338
SN - 9781424441235
T3 - 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
SP - 6019
EP - 6022
BT - 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
T2 - 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Y2 - 31 August 2010 through 4 September 2010
ER -