44 J.R. Wolpaw and C.B. Boulay 72. NE. Crone, A. Sinai, and A. Korzeniewska, High-frequency gamma oscillations and human brain mapping with electrocorticography. Prog Brain Res, 159, 275–295, (2006). 73. SP. Levine J.E. Huggins, S.L. BeMent, et al., Identification <strong>of</strong> electrocorticogram patterns as the basis for a direct brain interface. J Clin Neurophysiol, 16, 439–447, (1999). 74. C. Mehring, MP. Nawrot, S.C. de Oliveira, et al., Comparing information about arm movement direction in single channels <strong>of</strong> local and epicortical field potentials from monkey and human motor cortex. J Physiol, Paris 98, 498–506, (2004). 75. T. Satow, M. Matsuhashi, A. Ikeda, et al., Distinct cortical areas for motor preparation and execution in human identified by Bereitschaftspotential recording and ECoG-EMG coherence analysis. Clin Neurophysiol, 114, 1259–1264, (2003). 76. G. Schalk, J. Kubanek, K.J. Miller, et al., Decoding two-dimensional movement trajectories using electrocorticographic signals in humans. J Neural Eng, 4, 264–275, (2007). 77. G. Schalk, P. Brunner, L.A. Gerhardt, H. Bisch<strong>of</strong>, J.R. Wolpaw, Brain-computer interfaces (BCIs): Detection instead <strong>of</strong> classification. J Neurosci Methods, (2007). 78. N.E. Crone, D.L. Miglioretti, B. Gordon, and R.P. Lesser, Functional mapping <strong>of</strong> human sensorimotor cortex with electrocorticographic spectral analysis. II. Event-related synchronization in the gamma band. Brain, 121(Pt 12), 2301–2315, (1998). 79. E.C. Leuthardt, K. Miller, N.R. Anderson, et al., Electrocorticographic frequency alteration mapping: a clinical technique for mapping the motor cortex. Neurosurgery, 60, 260–270; discussion 270–261, (2007). 80. K.J. Miller, E.C. Leuthardt, G, Schalk, et al., Spectral changes in cortical surface potentials during motor movement. J Neurosci, 27, 2424–2432, (2007). 81. S. Ohara, A. Ikeda, T. Kunieda, et al., Movement-related change <strong>of</strong> electrocorticographic activity in human supplementary motor area proper. Brain, 123(Pt 6), 1203–1215, (2000). 82. G. Pfurtscheller, B. Graimann, J.E. Huggins, S.P. Levine, and L.A. Schuh, Spatiotemporal patterns <strong>of</strong> beta desynchronization and gamma synchronization in corticographic data during self-paced movement. Clin Neurophysiol, 114, 1226–1236, (2003). 83. J. Kubanek, K.J. Miller, J.G. Ojemann, J.R. Wolpaw, and G. Schalk, Decoding flexion <strong>of</strong> individual fingers using electrocorticographic signals in humans. J Neural Eng, 6(6), 66001, (2009). 84. G. Schalk, N. Anderson, K. Wisneski, W. Kim, M.D. Smyth, J.R. Wolpaw, D.L. Barbour, and E.C. Leuthardt, Toward brain-computer interfacing using phonemes decoded from electrocorticography activity (ECoG) in humans. Program No. 414.11. 2007 Abstract Viewer/Itinerary Planner. Society for Neuroscience, Washington, DC, (2007). Online. 85. E.C. Leuthardt, G. Schalk, J.R. Wolpaw, J.G. Ojemann, and D.W. Moran, A brain-computer interface using electrocorticographic signals in humans. J Neural Eng 1, 63–71, (2004). 86. G. Schalk, K.J. Miller, N.R. Anderson, et al., Two-dimensional movement control using electrocorticographic signals in humans. J Neural Eng, 5, 75–84, (2008). 87. U. Mitzdorf, Current source-density method and application in cat cerebral cortex: investigation <strong>of</strong> evoked potentials and EEG phenomena. Physiol Rev, 65, 37–100, (1985). 88. U. Mitzdorf, Properties <strong>of</strong> cortical generators <strong>of</strong> event-related potentials. Pharmacopsychiatry, 27, 49–51, (1994). 89. K.J. Otto, M.D. Johnson, and D.R. Kipke, Voltage pulses change neural interface properties and improve unit recordings with chronically implanted microelectrodes. IEEE Trans Biomed Eng, 53, 333–340, (2006). 90. O. Donchin, A. Gribova, O. Steinberg, H. Bergman, S. Cardoso de Oliveira, and E. Vaadia, Local field potentials related to bimanual movements in the primary and supplementary motor cortices. Exp Brain Res, 140, 46–55, (2001). 91. J. Rickert, S.C. Oliveira, E. Vaadia, A. Aertsen, S. Rotter, and C. Mehring, Encoding <strong>of</strong> movement direction in different frequency ranges <strong>of</strong> motor cortical local field potentials. J Neurosci, 25, 8815–8824, (2005). 92. P.R. Kennedy, M.T. Kirby, M.M. Moore, B. King, and A. Mallory, Computer control using human intracortical local field potentials. IEEE Trans Neural Syst Rehabil Eng, 12, 339–344, (2004).
Brain Signals for Brain–Computer <strong>Interfaces</strong> 45 93. L.R. Hochberg, M.D. Serruya, G.M. Friehs, et al., Neuronal ensemble control <strong>of</strong> prosthetic devices by a human with tetraplegia. Nature 442, 164–171, (2006). 94. D.A. Heldman, W. Wang, S.S. Chan, and D.W. Moran, Local field potential spectral tuning in motor cortex during reaching. IEEE Trans Neural Syst Rehabil Eng, 14, 180–183, (2006). 95. J.P. Donoghue, J.N. Sanes, N.G. Hatsopoulos, and G. Gaal, Neural discharge and local field potential oscillations in primate motor cortex during voluntary movements. J Neurophysiol, 79, 159–173, (1998). 96. S.N. Baker, J.M. Kilner E.M. Pinches, and R.N. Lemon, The role <strong>of</strong> synchrony and oscillations in the motor output. Exp Brain Res, 128, 109–117, (1999). 97. V.N. Murthy and E.E. Fetz, Coherent 25- to 35-Hz oscillations in the sensorimotor cortex <strong>of</strong> awake behaving monkeys. Proc Natl Acad Sci USA, 89, 5670–5674, (1992). 98. R.A. Andersen, S. Musallam, and B. Pesaran, Selecting the signals for a brain-machine interface. Curr Opin Neurobiol, 14, 720–726, (2004). 99. S. Musallam, B.D. Corneil, B. Greger, H. Scherberger, and R.A. Andersen, Cognitive control signals for neural prosthetics. Science, 305, 258–262, (2004). 100. B. Pesaran, J.S. Pezaris, M. Sahani, P.P. Mitra, and R.A. Andersen, Temporal structure in neuronal activity during working memory in macaque parietal cortex. Nat Neurosci, 5, 805–811, (2002). 101. H. Scherberger, M.R. Jarvis, and R.A. Andersen, Cortical local field potential encodes movement intentions in the posterior parietal cortex. Neuron, 46, 347–354, (2005). 102. E.E. Fetz, Operant conditioning <strong>of</strong> cortical unit activity. Science, 163, 955–958, (1969). 103. E.E., Fetz and D.V. Finocchio, Correlations between activity <strong>of</strong> motor cortex cells and arm muscles during operantly conditioned response patterns. Exp Brain Res, 23, 217–240, (1975). 104. E.M. Schmidt, Single neuron recording from motor cortex as a possible source <strong>of</strong> signals for control <strong>of</strong> external devices. Ann Biomed Eng, 8, 339–349, (1980). 105. A.R. Wyler and K.J. Burchiel, Factors influencing accuracy <strong>of</strong> operant control <strong>of</strong> pyramidal tract neurons in monkey. Brain Res, 152, 418–421, (1978). 106. E. Stark, R. Drori, I. Asher, Y. Ben-Shaul, and M. Abeles, Distinct movement parameters are represented by different neurons in the motor cortex. Eur J Neurosci, 26, 1055–1066, (2007). 107. W.T. Thach, Correlation <strong>of</strong> neural discharge with pattern and force <strong>of</strong> muscular activity, joint position, and direction <strong>of</strong> intended next movement in motor cortex and cerebellum. J Neurophysiol, 41, 654–676, (1978). 108. J. Carmena, M. Lebedev, R. Crist, et al., Learning to control a brain-machine interface for reaching and grasping by primates. PLoS Biol, 1, 193–208, (2003). 109. J.K. Chapin, K.A. Moxon, R.S. Markowitz, and M.A. Nicolelis, Real-time control <strong>of</strong> a robot arm using simultaneously recorded neurons in the motor cortex. Nat Neurosci, 2, 664–670, (1999). 110. M. Serruya, N.G. Hastopoulos, L. Paminski, Fel M.R. lows, and J.P. Donoghue, Instant neural control <strong>of</strong> a movement signal. Nature, 416, 141–142, (2002). 111. M. Velliste, S. Perel, M.C. Spalding, A.S. Whitford, and A.B. Schwartz, Cortical control <strong>of</strong> a prosthetic arm for self-feeding. Nature, 453, 1098–1101, (2008). 112. K. Shenoy, D. Meeker, S. Cao, et al., Neural prosthetic control signals from plan activity. Neuroreport, 14, 591–596, (2003). 113. G. Kreiman, C. Koch, and I. Fried, Imagery neurons in the human brain. Nature 408, 357–361, (2000). 114. J.W. Gnadt and R.A. Andersen, Memory related motor planning activity in posterior parietal cortex <strong>of</strong> macaque. Exp Brain Res 128, 70, 216–220, (1988). 115. P.R. Kennedy, The cone electrode: a long-term electrode that records from neurites grown onto its recording surface. J Neurosci Meth, 29, 181–193, (1989). 116. P.R. Kennedy, R.A. Bakay, M.M. Moore, and J. Goldwaithe, Direct control <strong>of</strong> a computer from the human central nervous system. IEEE Trans Rehabil Eng, 8, 198–202, (2000).
- Page 2 and 3:
THE FRONTIERS COLLECTION
- Page 4 and 5:
Bernhard Graimann · Brendan Alliso
- Page 6 and 7:
Preface It’s an exciting time to
- Page 8 and 9: Contents Brain-Computer Interfaces:
- Page 10 and 11: Contributors Brendan Allison Instit
- Page 12 and 13: Contributors xi Femke Nijboer Insti
- Page 14 and 15: List of Abbreviations ADHD Attentio
- Page 16 and 17: Brain-Computer Interfaces: A Gentle
- Page 18 and 19: Brain-Computer Interfaces: A Gentle
- Page 20 and 21: Brain-Computer Interfaces: A Gentle
- Page 22 and 23: Brain-Computer Interfaces: A Gentle
- Page 24 and 25: Brain-Computer Interfaces: A Gentle
- Page 26 and 27: Brain-Computer Interfaces: A Gentle
- Page 28 and 29: Brain-Computer Interfaces: A Gentle
- Page 30 and 31: Brain-Computer Interfaces: A Gentle
- Page 32 and 33: Brain-Computer Interfaces: A Gentle
- Page 34 and 35: Brain-Computer Interfaces: A Gentle
- Page 36 and 37: Brain-Computer Interfaces: A Gentle
- Page 38 and 39: Brain-Computer Interfaces: A Gentle
- Page 40 and 41: Brain-Computer Interfaces: A Gentle
- Page 42 and 43: Brain-Computer Interfaces: A Gentle
- Page 44 and 45: 30 J.R. Wolpaw and C.B. Boulay by b
- Page 46 and 47: 32 J.R. Wolpaw and C.B. Boulay 2 Br
- Page 48 and 49: 34 J.R. Wolpaw and C.B. Boulay Fig.
- Page 50 and 51: 36 J.R. Wolpaw and C.B. Boulay Sens
- Page 52 and 53: 38 J.R. Wolpaw and C.B. Boulay pote
- Page 54 and 55: 40 J.R. Wolpaw and C.B. Boulay EEG-
- Page 56 and 57: 42 J.R. Wolpaw and C.B. Boulay 29.
- Page 60 and 61: 46 J.R. Wolpaw and C.B. Boulay 117.
- Page 62 and 63: 48 G. Pfurtscheller and C. Neuper F
- Page 64 and 65: 50 G. Pfurtscheller and C. Neuper F
- Page 66 and 67: 52 G. Pfurtscheller and C. Neuper r
- Page 68 and 69: 54 G. Pfurtscheller and C. Neuper 6
- Page 70 and 71: 56 G. Pfurtscheller and C. Neuper B
- Page 72 and 73: 58 G. Pfurtscheller and C. Neuper F
- Page 74 and 75: 60 G. Pfurtscheller and C. Neuper 4
- Page 76 and 77: 62 G. Pfurtscheller and C. Neuper 4
- Page 78 and 79: 64 G. Pfurtscheller and C. Neuper 9
- Page 80 and 81: 66 C. Neuper and G. Pfurtscheller s
- Page 82 and 83: 68 C. Neuper and G. Pfurtscheller 2
- Page 84 and 85: 70 C. Neuper and G. Pfurtscheller F
- Page 86 and 87: 72 C. Neuper and G. Pfurtscheller b
- Page 88 and 89: 74 C. Neuper and G. Pfurtscheller E
- Page 90 and 91: 76 C. Neuper and G. Pfurtscheller 1
- Page 92 and 93: 78 C. Neuper and G. Pfurtscheller 5
- Page 94 and 95: 80 G. Pfurtscheller et al. mode, th
- Page 96 and 97: 82 G. Pfurtscheller et al. Therefor
- Page 98 and 99: 84 G. Pfurtscheller et al. A B C 1
- Page 100 and 101: 86 G. Pfurtscheller et al. filters
- Page 102 and 103: 88 G. Pfurtscheller et al. differen
- Page 104 and 105: 90 G. Pfurtscheller et al. In this
- Page 106 and 107: 92 G. Pfurtscheller et al. Fig. 8 P
- Page 108 and 109:
94 G. Pfurtscheller et al. 10. D. F
- Page 110 and 111:
96 G. Pfurtscheller et al. 51. G. P
- Page 112 and 113:
98 E.W. Sellers et al. Fig. 1 Three
- Page 114 and 115:
100 E.W. Sellers et al. Fig. 3 Two-
- Page 116 and 117:
102 E.W. Sellers et al. Fig. 5 Comp
- Page 118 and 119:
104 E.W. Sellers et al. Fig. 7 Mont
- Page 120 and 121:
106 E.W. Sellers et al. fixation wa
- Page 122 and 123:
108 E.W. Sellers et al. 5 SMR-Based
- Page 124 and 125:
110 E.W. Sellers et al. 22. D.J Kru
- Page 126 and 127:
Detecting Mental States by Machine
- Page 128 and 129:
Detecting Mental States by Machine
- Page 130 and 131:
Detecting Mental States by Machine
- Page 132 and 133:
Detecting Mental States by Machine
- Page 134 and 135:
Detecting Mental States by Machine
- Page 136 and 137:
Detecting Mental States by Machine
- Page 138 and 139:
Detecting Mental States by Machine
- Page 140 and 141:
Detecting Mental States by Machine
- Page 142 and 143:
Detecting Mental States by Machine
- Page 144 and 145:
Detecting Mental States by Machine
- Page 146 and 147:
Detecting Mental States by Machine
- Page 148 and 149:
Detecting Mental States by Machine
- Page 150 and 151:
138 Y. Wang et al. which has been e
- Page 152 and 153:
140 Y. Wang et al. After many studi
- Page 154 and 155:
142 Y. Wang et al. Left Hand Right
- Page 156 and 157:
144 Y. Wang et al. 0-degree 60-degr
- Page 158 and 159:
146 Y. Wang et al. 3.1.2 Stimulatio
- Page 160 and 161:
148 Y. Wang et al. Foot 1 0.5 Left
- Page 162 and 163:
150 Y. Wang et al. be summarized as
- Page 164 and 165:
152 Y. Wang et al. Fig. 10 A player
- Page 166 and 167:
154 Y. Wang et al. 22. Y. Wang, R.
- Page 168 and 169:
156 N. Birbaumer and P. Sauseng C A
- Page 170 and 171:
158 N. Birbaumer and P. Sauseng 3 B
- Page 172 and 173:
160 N. Birbaumer and P. Sauseng pat
- Page 174 and 175:
162 N. Birbaumer and P. Sauseng Fig
- Page 176 and 177:
164 N. Birbaumer and P. Sauseng of
- Page 178 and 179:
166 N. Birbaumer and P. Sauseng Neu
- Page 180 and 181:
168 N. Birbaumer and P. Sauseng 8.
- Page 182 and 183:
Non Invasive BCIs for Neuroprosthes
- Page 184 and 185:
Non Invasive BCIs for Neuroprosthes
- Page 186 and 187:
Non Invasive BCIs for Neuroprosthes
- Page 188 and 189:
Non Invasive BCIs for Neuroprosthes
- Page 190 and 191:
Non Invasive BCIs for Neuroprosthes
- Page 192 and 193:
Non Invasive BCIs for Neuroprosthes
- Page 194 and 195:
Non Invasive BCIs for Neuroprosthes
- Page 196 and 197:
Brain-Computer Interfaces for Commu
- Page 198 and 199:
Brain-Computer Interfaces for Commu
- Page 200 and 201:
Brain-Computer Interfaces for Commu
- Page 202 and 203:
Brain-Computer Interfaces for Commu
- Page 204 and 205:
Brain-Computer Interfaces for Commu
- Page 206 and 207:
Brain-Computer Interfaces for Commu
- Page 208 and 209:
Brain-Computer Interfaces for Commu
- Page 210 and 211:
Brain-Computer Interfaces for Commu
- Page 212 and 213:
Brain-Computer Interfaces for Commu
- Page 214 and 215:
204 D.M. Taylor and M.E. Stetner mo
- Page 216 and 217:
206 D.M. Taylor and M.E. Stetner el
- Page 218 and 219:
208 D.M. Taylor and M.E. Stetner ac
- Page 220 and 221:
210 D.M. Taylor and M.E. Stetner de
- Page 222 and 223:
212 D.M. Taylor and M.E. Stetner Ma
- Page 224 and 225:
214 D.M. Taylor and M.E. Stetner pe
- Page 226 and 227:
216 D.M. Taylor and M.E. Stetner ev
- Page 228 and 229:
218 D.M. Taylor and M.E. Stetner fo
- Page 230 and 231:
BCIs Based on Signals from Between
- Page 232 and 233:
BCIs Based on Signals from Between
- Page 234 and 235:
BCIs Based on Signals from Between
- Page 236 and 237:
BCIs Based on Signals from Between
- Page 238 and 239:
BCIs Based on Signals from Between
- Page 240 and 241:
BCIs Based on Signals from Between
- Page 242 and 243:
BCIs Based on Signals from Between
- Page 244 and 245:
BCIs Based on Signals from Between
- Page 246 and 247:
BCIs Based on Signals from Between
- Page 248 and 249:
BCIs Based on Signals from Between
- Page 250 and 251:
242 K.J. Miller and J.G. Ojemann 2
- Page 252 and 253:
244 K.J. Miller and J.G. Ojemann ha
- Page 254 and 255:
246 K.J. Miller and J.G. Ojemann Fi
- Page 256 and 257:
248 K.J. Miller and J.G. Ojemann Fi
- Page 258 and 259:
250 K.J. Miller and J.G. Ojemann fo
- Page 260 and 261:
252 K.J. Miller and J.G. Ojemann me
- Page 262 and 263:
254 K.J. Miller and J.G. Ojemann In
- Page 264 and 265:
256 K.J. Miller and J.G. Ojemann ar
- Page 266 and 267:
258 K.J. Miller and J.G. Ojemann 26
- Page 268 and 269:
260 J. Mellinger and G. Schalk mapp
- Page 270 and 271:
262 J. Mellinger and G. Schalk 2 BC
- Page 272 and 273:
264 J. Mellinger and G. Schalk Fig.
- Page 274 and 275:
266 J. Mellinger and G. Schalk Filt
- Page 276 and 277:
268 J. Mellinger and G. Schalk proc
- Page 278 and 279:
270 J. Mellinger and G. Schalk exis
- Page 280 and 281:
272 J. Mellinger and G. Schalk reco
- Page 282 and 283:
274 J. Mellinger and G. Schalk Fig.
- Page 284 and 285:
276 J. Mellinger and G. Schalk numb
- Page 286 and 287:
278 J. Mellinger and G. Schalk 5. A
- Page 288 and 289:
The First Commercial Brain-Computer
- Page 290 and 291:
The First Commercial Brain-Computer
- Page 292 and 293:
The First Commercial Brain-Computer
- Page 294 and 295:
The First Commercial Brain-Computer
- Page 296 and 297:
The First Commercial Brain-Computer
- Page 298 and 299:
The First Commercial Brain-Computer
- Page 300 and 301:
The First Commercial Brain-Computer
- Page 302 and 303:
The First Commercial Brain-Computer
- Page 304 and 305:
The First Commercial Brain-Computer
- Page 306 and 307:
The First Commercial Brain-Computer
- Page 308 and 309:
The First Commercial Brain-Computer
- Page 310 and 311:
The First Commercial Brain-Computer
- Page 312 and 313:
306 Y. Li et al. Fig. 1 Basic desig
- Page 314 and 315:
308 Y. Li et al. Fig. 2 A linear tr
- Page 316 and 317:
310 Y. Li et al. The large Laplacia
- Page 318 and 319:
312 Y. Li et al. components is larg
- Page 320 and 321:
314 Y. Li et al. P300-based, and ER
- Page 322 and 323:
316 Y. Li et al. 3.3.2 Autoregressi
- Page 324 and 325:
318 Y. Li et al. selection as follo
- Page 326 and 327:
320 Y. Li et al. 5.1.2 Support Vect
- Page 328 and 329:
322 Y. Li et al. is small and the n
- Page 330 and 331:
324 Y. Li et al. (ROC) analysis app
- Page 332 and 333:
326 Y. Li et al. Fig. 10 The stimul
- Page 334 and 335:
328 Y. Li et al. 6. M. Cheng, X. Ga
- Page 336 and 337:
330 Y. Li et al. 46. K. Crammer and
- Page 338 and 339:
332 A. Schlögl et al. Fig. 1 Schem
- Page 340 and 341:
334 A. Schlögl et al. For the rect
- Page 342 and 343:
336 A. Schlögl et al. whereby T in
- Page 344 and 345:
338 A. Schlögl et al. Fig. 2 State
- Page 346 and 347:
340 A. Schlögl et al. yk = a1 · y
- Page 348 and 349:
342 A. Schlögl et al. d{i}(x) = ((
- Page 350 and 351:
344 A. Schlögl et al. Accordingly,
- Page 352 and 353:
346 A. Schlögl et al. not exceed a
- Page 354 and 355:
348 A. Schlögl et al. Error [%] RL
- Page 356 and 357:
350 A. Schlögl et al. Table 3 Aver
- Page 358 and 359:
352 A. Schlögl et al. The extended
- Page 360 and 361:
354 A. Schlögl et al. 24. N.G. Pfu
- Page 362 and 363:
Toward Ubiquitous BCIs Brendan Z. A
- Page 364 and 365:
Toward Ubiquitous BCIs 359 BCI Chal
- Page 366 and 367:
Toward Ubiquitous BCIs 361 communic
- Page 368 and 369:
Toward Ubiquitous BCIs 363 facial m
- Page 370 and 371:
Toward Ubiquitous BCIs 365 The best
- Page 372 and 373:
Toward Ubiquitous BCIs 367 Across a
- Page 374 and 375:
Toward Ubiquitous BCIs 369 the ques
- Page 376 and 377:
Toward Ubiquitous BCIs 371 controll
- Page 378 and 379:
Toward Ubiquitous BCIs 373 controls
- Page 380 and 381:
Toward Ubiquitous BCIs 375 hair in
- Page 382 and 383:
Toward Ubiquitous BCIs 377 Table 1
- Page 384 and 385:
Toward Ubiquitous BCIs 379 conversa
- Page 386 and 387:
Toward Ubiquitous BCIs 381 may down
- Page 388 and 389:
Toward Ubiquitous BCIs 383 physicis
- Page 390 and 391:
Toward Ubiquitous BCIs 385 31. F.H.
- Page 392 and 393:
Toward Ubiquitous BCIs 387 67. G. S
- Page 394 and 395:
390 Index 65, 157, 163, 217, 221-23
- Page 396 and 397:
392 Index 208, 236, 243, 245, 260-2