02154nas a2200217   4500008004100000022001400041245008300055210006900138260000800207300001000215490000600225520150300231100002301734700001901757700002101776700002701797700001901824700002301843700002201866856004801888       2016                        eng d  a2045-232200aWord pair classification during imagined speech using direct brain recordings.0 aWord pair classification during imagined speech using direct bra  cMay  a258030 v63 aPeople that cannot communicate due to neurological disorders would benefit from an internal speech decoder. Here, we showed the ability to classify individual words during imagined speech from electrocorticographic signals. In a word imagery task, we used high gamma (70-150þinspaceHz) time features with a support vector machine model to classify individual words from a pair of words. To account for temporal irregularities during speech production, we introduced a non-linear time alignment into the SVM kernel. Classification accuracy reached 88% in a two-class classification framework (50% chance level), and average classification accuracy across fifteen word-pairs was significant across five subjects (meanþinspace=þinspace58%; pþinspace<þinspace0.05). We also compared classification accuracy between imagined speech, overt speech and listening. As predicted, higher classification accuracy was obtained in the listening and overt speech conditions (meanþinspace=þinspace89% and 86%, respectively; pþinspace<þinspace0.0001), where speech stimuli were directly presented. The results provide evidence for a neural representation for imagined words in the temporal lobe, frontal lobe and sensorimotor cortex, consistent with previous findings in speech perception and production. These data represent a proof of concept study for basic decoding of speech imagery, and delineate a number of key challenges to usage of speech imagery neural representations for clinical applications.1 aMartin, Stéphanie1 aBrunner, Peter1 aIturrate, Iñaki1 aMillán, José, Del R.1 aSchalk, Gerwin1 aKnight, Robert, T.1 aPasley, Brian, N.  uhttp://www.ncbi.nlm.nih.gov/pubmed/27165452