@article {3146,
	title = {Quantifying signal-to-noise ratio of mismatch negativity in humans.},
	journal = {Neuroscience letters},
	volume = {341},
	year = {2003},
	month = {05/2003},
	pages = {251{\textendash}255},
	abstract = {Mismatch negativity (MMN) is thought to represent a neurophysiological index of auditory information processing that is independent of attention. Because this measure does not require an overt behavioral response, MMN has potential to evaluate higher order perceptual abilities in infants, young children and difficult-to-test populations, thereby extending results obtained from more basic physiologic and electroacoustic measures (auditory brainstem responses, ABRs; otoacoustic emissions, OAEs). Whereas the basic tenet of MMN is appealing, several issues-of-contention remain to be solved before this event related potential (ERP) can be applicable for routine clinical use. These issues include the consistent identification of MMN within individuals (vs. groups), its stability over time, and its reportedly poor signal-to-noise ratio (SNR). Herein, we focus on the issue of SNR, by comparing and contrasting SNR of MMN with other long latency auditory ERPs.},
	keywords = {auditory brainstem responses, event related potential, mismatch negativity, otoacoustic emissions, signal-to-noise ratio},
	issn = {0304-3940},
	doi = {10.1016/S0304-3940(03)00196-4},
	url = {http://www.ncbi.nlm.nih.gov/pubmed/12697295},
	author = {Anthony T. Cacace and Dennis J. McFarland}
}
@article {3234,
	title = {EEG-based communication: presence of an error potential.},
	journal = {Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology},
	volume = {111},
	year = {2000},
	month = {12/2000},
	pages = {2138{\textendash}2144},
	abstract = {EEG-based communication could be a valuable new augmentative communication technology for those with severe motor disabilities. Like all communication methods, it faces the problem of errors in transmission. In the Wadsworth EEG-based brain-computer interface (BCI) system, subjects learn to use mu or beta rhythm amplitude to move a cursor to targets on a computer screen. While cursor movement is highly accurate in trained subjects, it is not perfect.},
	keywords = {augmentative communication, brain-computer interface, Electroencephalography, error potential, error related negativity, event related potential, mu rhythm, Rehabilitation, sensorimotor cortex},
	issn = {1388-2457},
	doi = {10.1016/S1388-2457(00)00457-0},
	url = {http://www.ncbi.nlm.nih.gov/pubmed/11090763},
	author = {Gerwin Schalk and Jonathan Wolpaw and Dennis J. McFarland and Pfurtscheller, G.}
}
