Neurophysiological Bases of Auditory Perception (eBook)
XXXI, 644 Seiten
Springer New York (Verlag)
978-1-4419-5686-6 (ISBN)
Enrique A. Lopez-Poveda, Ph.D. is director of the Auditory Computation and Psychoacoustics Unit of the Neuroscience Institute of Castilla y León (University of Salamanca, Spain). His research focuses on understanding and modeling human cochlear nonlinear signal processing and the role of the peripheral auditory system in normal and impaired auditory perception. He has authored over 45 scientific papers and book chapters and is co-editor of the book Computational Models of the Auditory System (Springer Handbook of Auditory Research). He has been principal investigator, participant and consultant on numerous research projects. He is member of the Acoustical Society of America and of the Association of Research in Otolaryngololgy.
Alan R. Palmer, Ph.D. is Deputy Director of the MRC Institute of Hearing Research and holds a Special Professorship in neuroscience at the University of Nottingham UK. He received his first degree in Biological Sciences from the University of Birmingham UK and his PhD in Communication and Neuroscience from the University of Keele UK. After postdoctoral research at Keele, he established his own laboratory at the National Institute for Medical Research in London. This was followed by a Royal Society University Research Fellowship at the University of Sussex before taking a program leader position at the Medical Research Council Institute for Hearing Research in 1986. He heads a research team that uses neurophysiological, computational and neuroanatomical techniques to study the way the brain processes sound.
Ray Meddis, Ph.D. is director of the Hearing Research Laboratory at the University of Essex, England. His research has concentrated on the development of computer models of the physiology of the auditory periphery and how these can be incorporated into models of psychophysical phenomena such as pitch and auditory scene analysis. He has published extensively in this area. He is co-editor of the book Computational Models of the Auditory System (Springer Handbook of Auditory Research). His current research concerns the application of computer models to an understanding of hearing impairment. He is a fellow of the Acoustical Society of America and a member of the Association of Research in Otolaryngololgy.
This volume contains the papers presented at the 15th International Symposium on Hearing (ISH), which was held at the Hotel Regio, Santa Marta de Tormes, Salamanca, Spain, between 1st and 5th June 2009. Since its inception in 1969, this Symposium has been a forum of excellence for debating the neurophysiological basis of auditory perception, with computational models as tools to test and unify physiological and perceptual theories. Every paper in this symposium includes two of the following: auditory physiology, psychoph- ics or modeling. The topics range from cochlear physiology to auditory attention and learning. While the symposium is always hosted by European countries, p- ticipants come from all over the world and are among the leaders in their fields. The result is an outstanding symposium, which has been described by some as a "e;world summit of auditory research. "e; The current volume has a bottom-up structure from "e;simpler"e; physiological to more "e;complex"e; perceptual phenomena and follows the order of presentations at the meeting. Parts I to III are dedicated to information processing in the peripheral au- tory system and its implications for auditory masking, spectral processing, and c- ing. Part IV focuses on the physiological bases of pitch and timbre perception. Part V is dedicated to binaural hearing. Parts VI and VII cover recent advances in und- standing speech processing and perception and auditory scene analysis. Part VIII focuses on the neurophysiological bases of novelty detection, attention, and learning.
Enrique A. Lopez-Poveda, Ph.D. is director of the Auditory Computation and Psychoacoustics Unit of the Neuroscience Institute of Castilla y León (University of Salamanca, Spain). His research focuses on understanding and modeling human cochlear nonlinear signal processing and the role of the peripheral auditory system in normal and impaired auditory perception. He has authored over 45 scientific papers and book chapters and is co-editor of the book Computational Models of the Auditory System (Springer Handbook of Auditory Research). He has been principal investigator, participant and consultant on numerous research projects. He is member of the Acoustical Society of America and of the Association of Research in Otolaryngololgy. Alan R. Palmer, Ph.D. is Deputy Director of the MRC Institute of Hearing Research and holds a Special Professorship in neuroscience at the University of Nottingham UK. He received his first degree in Biological Sciences from the University of Birmingham UK and his PhD in Communication and Neuroscience from the University of Keele UK. After postdoctoral research at Keele, he established his own laboratory at the National Institute for Medical Research in London. This was followed by a Royal Society University Research Fellowship at the University of Sussex before taking a program leader position at the Medical Research Council Institute for Hearing Research in 1986. He heads a research team that uses neurophysiological, computational and neuroanatomical techniques to study the way the brain processes sound. Ray Meddis, Ph.D. is director of the Hearing Research Laboratory at the University of Essex, England. His research has concentrated on the development of computer models of the physiology of the auditory periphery and how these can be incorporated into models of psychophysical phenomena such as pitch and auditory scene analysis. He has published extensively in this area. He is co-editor of the book Computational Models of the Auditory System (Springer Handbook of Auditory Research). His current research concerns the application of computer models to an understanding of hearing impairment. He is a fellow of the Acoustical Society of America and a member of the Association of Research in Otolaryngololgy.
Preface 5
Contents 10
About the Editors 17
Contributors 18
Part I Peripheral/Cochlear Processing 29
Chapter 1 30
Otoacoustic Emissions Theories Can Be Tested with Behavioral Methods 30
1.1 Introduction 31
1.2 Methods 33
1.2.1 Listeners 33
1.2.2 Optimal Rules 34
1.2.3 Behavioral Rules 34
1.2.3.1 Common Procedures 34
1.2.3.2 TMC Stimuli 34
1.2.3.3 GOFM Stimuli 35
1.2.3.4 GOSM Stimuli 35
1.3 Results and Discussion 35
1.4 Conclusions 40
References 40
Chapter 2 42
Basilar Membrane Responses to Simultaneous Presentations of White Noise and a Single Tone 42
2.1 Introduction 42
2.2 Methods 43
2.2.1 Physiological Recordings and Data Analysis 43
2.2.2 Computer Modeling 44
2.3 Results 44
2.4 Discussion 48
References 49
Chapter 3 51
The Influence of the Helicotrema on Low-Frequency Hearing 51
3.1 Introduction 51
3.2 Methods 52
3.2.1 Forward-Middle-Ear-Transfer Function 52
3.2.2 Hearing Thresholds and Equal-Loudness-Contours 54
3.2.3 Subjects 54
3.3 Results 55
3.4 Discussion 58
3.4.1 Comparison Between fMETF and ELC 58
3.4.2 Agreement with Isophons (ISO 389-7 2005) 59
3.4.3 A Possible Cochlear Origin of Low-Frequency Hypersensitivity or Tinnitus 59
3.5 Summary 60
References 61
Chapter 4 62
Mechanisms of Masking by Schroeder-Phase Complexes 62
4.1 Introduction 62
4.2 Experiment: Effects of Masker Duration in Masking by On- and Off-Frequency Schroeder-Phase Complexes 63
4.3 Methods 63
4.4 Results and Discussion 64
4.5 Model Predictions 66
4.5.1 Model Description 66
4.5.2 Model Predictions 66
4.5.3 Simulating the Effect of the MOCR 67
4.6 Conclusions 69
References 69
Chapter 5 71
The Frequency Selectivity of Gain Reduction Masking: Analysis Using Two Equally-Effective Maskers 71
5.1 Introduction 72
5.2 Method 73
5.2.1 Subjects 73
5.2.2 Stimuli 74
5.2.3 Procedures 74
5.2.4 Experiments 74
5.2.4.1 Experiment 1: Off-Frequency GOM 74
5.2.4.2 Experiment 2: PTCs 75
5.2.4.3 Experiment 3: Combined Maskers 75
5.2.4.4 Experiment 4: Control Experiment 75
5.3 Results 76
5.3.1 GOM Data (masking data for M2) 76
5.3.2 PTC Data (Masking Data for M1) 76
5.3.3 Combined Masker Data and Control Experiment 76
5.4 Modeling 78
5.4.1 Additivity Model 78
5.4.2 Gain Reduction Model 79
5.4.3 Modeling Results 80
5.4.3.1 Additivity Model 80
5.4.3.2 Gain Reduction Model 80
5.5 Discussion 81
References 81
Chapter 6 83
Investigating Cortical Descending Control of the Peripheral Auditory System 83
6.1 Introduction 83
6.2 Methods 85
6.2.1 Anaesthesia and Surgical Preparation 85
6.2.2 Stimulus Presentation and Neuronal Recordings 85
6.2.3 Cortical Cooling 85
6.3 Results 86
6.3.1 Effect of Cortical Inactivation on the Contralateral Cochlea 86
6.3.2 Effect of Cortical Inactivation on the Ipsilateral Cochlea 88
6.4 Discussion 90
6.5 Comment by Stefan Strahl 91
6.6 Reply Alan R. Palmer 91
References 91
Chapter 7 93
Exploiting Transgenic Mice to Explore the Role of the Tectorial Membrane in Cochlear Sensory Processing 93
7.1 Introduction 93
7.2 Three Tectorin Mutants 94
7.2.1 Tecta Mice 94
7.2.2 Y1870C Missense Mutation in TECTA 96
7.2.3 Beta Tectorin Mice: Sharpened Cochlear Tuning in a Mouse with a Genetically Modified Tectorial Membrane 98
7.3 Conclusions 100
References 100
Chapter 8 102
Auditory Prepulse Inhibition of Neuronal Activity in the Rat Cochlear Root Nucleus 102
8.1 Introduction 103
8.2 Materials and Methods 103
8.2.1 Animals, Surgery, and Stereotaxic Approach 103
8.2.2 Stimulation, Data Collection, and Analyses 104
8.3 Results 106
8.3.1 Electrophysiological Identification of Cochlear Root Neurons 106
8.3.2 Auditory Prepulse Inhibition of Cochlear Root Neurons Response 106
8.3.3 Does Auditory Prepulse Inhibition Occur in Neurons Types of the Ventral Cochlear Nucleus? 107
8.4 Discussion 109
8.4.1 Auditory Prepulse Inhibition as a Specialized Mechanism of Neuronal Inhibition in the Cochlear Root Nucleus 109
8.4.2 Proposed Mediating Circuit for the Auditory Prepulse Inhibition of the ASR Based on Interstimulus Intervals 111
References 112
Part II Masking 114
Chapter 9 115
FM Forward Masking: Implications for FM Processing 115
9.1 Introduction 115
9.2 Procedure and Methods 116
9.3 Results 117
9.4 Discussion 119
References 120
Chapter 10 121
Electrophysiological Correlates of Intensity Resolution Under Forward Masking 121
10.1 Introduction 121
10.2 Method 124
10.3 Results and Discussion 125
10.3.1 Sensitivity 125
10.3.2 Auditory-Evoked Potentials 126
10.3.3 Relation Between the Behavioral and Electrophysiological Consequences of Forward Masking 129
10.4 Summary 130
References 131
Chapter 11 133
Neuronal Measures of Threshold and Magnitude of Forward Masking in Primary Auditory Cortex 133
11.1 Introduction 134
11.2 Methods 135
11.2.1 Physiological Recordings 135
11.2.2 Stimuli 136
11.2.3 Estimation of Probe Thresholds 136
11.3 Results 136
11.4 Discussion 139
References 141
Chapter 12 143
Effect of Presence of Cue Tone on Tuning of Auditory Filter Derived from Simultaneous Masking 143
12.1 Introduction 143
12.2 Simultaneous Masking with Notched-Noise Masker 144
12.2.1 Methods 144
12.2.2 Results 146
12.3 Estimates of Tuning of Auditory Filter Derived from Notched-Noise Masking Data 147
12.4 Simultaneous Masking with Band-Pass Noise Masker 149
12.4.1 Method 149
12.4.2 Results 149
12.5 Estimates of Tuning of Auditory Filter Derived from Band-Pass Noise Masking Data 149
12.6 Summary 150
12.7 Comment by Andrew Oxenham 151
12.8 Reply Shunsuke Kidani 151
References 152
Part III Spectral Processing and Coding 153
Chapter 13 154
Tone-in-Noise Detection: Observed Discrepancies in Spectral Integration 154
13.1 Introduction 154
13.2 Experiment 155
13.2.1 Method and Stimuli 155
13.3 Results 156
13.4 Discussion 159
13.5 Conclusion 161
References 162
Chapter 14 163
Linear and Nonlinear Coding of Sound Spectra by Discharge Rate in Neurons Comprising the Ascending Pathway Through the Latera 163
14.1 Introduction 164
14.2 Methods 164
14.3 Results 165
14.3.1 General Properties of Spectral Weight Functions 166
14.3.2 Testing the Validity of Spectral Weight Functions 167
14.3.3 Spectral Weight Function Properties for the Different Neuron Types 168
14.4 Discussion 171
References 173
Chapter 15 174
Enhancement in the Marmoset Inferior Colliculus: Neural Correlates of Perceptual “Pop-Out” 174
15.1 Introduction 175
15.2 Methods 176
15.3 Results 177
15.3.1 Examples of Conditioner Influence on Target Response 177
15.3.2 Response Dependence on Notch Width and Isolation of Conditioner Components 178
15.3.3 Enhancement is Not Coupled to the Presence of Postinhibitory Rebound Spikes 179
15.4 Discussion 180
15.4.1 Neural Mechanisms Underlying Enhancement 180
15.4.2 Comparison with Perception 181
15.4.3 Additional Considerations 182
15.5 Comment by Skyler Jennings 183
15.6 Reply by Paul Nelson 183
References 183
Chapter 16 185
Auditory Temporal Integration at Threshold: Evidence of a Cortical Origin 185
16.1 Introduction 185
16.2 Theory 186
16.3 Auditory Evoked Field at Threshold Revisited 188
16.3.1 Data 189
16.3.2 Amplitude Analysis 190
16.3.3 Latency Analysis 191
16.3.4 Discussion 192
16.4 Auditory Evoked Response to a Series of Tone Pulses 192
16.4.1 Methods 193
16.4.2 Results 193
16.4.3 Discussion 193
16.5 Conclusions 194
References 194
Part IV Pitch and Timbre 196
Chapter 17 197
Spatiotemporal Characteristics of Cortical Responses to a New Dichotic Pitch Stimulus 197
17.1 Introduction 197
17.2 Methods 198
17.2.1 Stimuli 198
17.2.2 Experiment 1: Pitch Matching 199
17.2.3 Experiment 2: MEG 199
17.3 Results 200
17.3.1 Experiment 1: Pitch Matching 200
17.3.2 Experiment 2: MEG Data 201
17.3.3 Discussion 203
References 205
Chapter 18 207
A Temporal Code for Huggins Pitch? 207
18.1 Introduction 207
18.2 Methods 209
18.2.1 Listeners 209
18.2.2 Stimuli 209
18.2.3 F0DL Measurement Procedure 211
18.2.4 FFR Recording Procedure 211
18.3 Results 212
18.3.1 F0DLs 212
18.3.2 FFR 212
18.4 Discussion 214
References 215
Chapter 19 216
Understanding Pitch Perception as a Hierarchical Process with Top-Down Modulation 216
19.1 Introduction 216
19.2 Methods 217
19.2.1 Feed-Forward Processing 219
19.2.2 Feed-Back Processing 220
19.3 Results and Discussion 222
References 224
Chapter 20 225
The Harmonic Organization of Auditory Cortex 225
20.1 Harmonic Inputs to Auditory Cortex 226
20.2 Harmonic Pitch Processing 230
20.3 Temporal Periodicity Processing 232
20.4 Harmonic Organizations of Auditory Cortex 233
References 234
Chapter 21 237
Reviewing the Definition of Timbre as it Pertains to the Perception of Speech and Musical Sounds 237
21.1 Timbre, Speech Sounds and Acoustical Scale 237
21.2 Timbre and the Perception of Speech Sounds 239
21.2.1 Timbre in the Perception of “Acoustic Scale Melodies” 240
21.2.2 The Second Dimension of Pitch Hypothesis 244
21.2.3 The Scale of the Filter, Sf, as a Dimension of Timbre 245
21.2.4 The Independence of Spectral Envelope Shape 245
21.3 Conclusions 246
References 246
Chapter 22 248
Size Perception for Acoustically Scaled Sounds of Naturally Pronounced and Whispered Words 248
22.1 Introduction 249
22.2 Experiment 249
22.2.1 Stimuli 250
22.2.2 Discrimination Procedures and Listeners 251
22.2.3 Results on Voiced Words 252
22.2.4 Results on Unvoiced and Whispered Words 254
22.2.5 Summary and Comparison 255
22.3 Conclusions 255
References 256
Part V Binaural Hearing 257
Chapter 23 258
Subcomponent Cues in Binaural Unmasking 258
23.1 Introduction 258
23.2 Experiment 259
23.2.1 Method 260
23.2.2 Results 260
23.2.3 Discussion 261
23.3 Modelling 263
23.3.1 Method 264
23.3.2 Results 264
23.3.3 Discussion 264
23.4 Conclusions 265
References 266
Chapter 24 267
Interaural Correlations Between +1 and 1 on a Thurstone Scale: Psychometric Functions and a Two-Parameter Model 267
24.1 Introduction 268
24.1.1 Reasons Against the Use of the Normalized IAC 268
24.1.2 Alternative Hypothesis: Spatial Percept Represented by the dB Scaled Ratio of N0- and Np-Components 269
24.2 Methods 270
24.2.1 Psychoacoustical Experiments 270
24.2.2 Thurstone Scaling 270
24.3 Results 270
24.4 Discussion 272
References 273
Chapter 25 274
Dynamic ITDs, Not ILDs, Underlie Binaural Detection of a Tone in Wideband Noise 274
25.1 Introduction 274
25.2 Methods 275
25.2.1 Binaural Modulation 275
25.2.2 Stimuli and Data Collection 277
25.3 Results 277
25.4 Modeling the Data 279
25.5 Discussion 280
References 281
Chapter 26 282
Effect of Reverberation on Directional Sensitivity of Auditory Neurons: Central and Peripheral Factors 282
26.1 Introduction 282
26.2 Methods 283
26.3 Results 284
26.3.1 Sensitivity to ITD in the Envelope and Fine Structure of Noise in the Awake Rabbit IC 284
26.3.2 Characterization of Directional Sensitivity Using ITD-Only in the Awake Rabbit IC 285
26.3.3 Peripheral Factors Determining ITD-Only Sensitivity in Reverberation 287
26.3.4 Directional Sensitivity in the IC with ITD and ILD Cues 288
26.4 Discussion 289
References 291
Chapter 27 292
New Experiments Employing Raised-Sine Stimuli Suggest an Unknown Factor Affects Sensitivity to Envelope-Based ITDs for Stimuli 292
27.1 Introduction 293
27.2 Generating Raised-Sine Stimuli 293
27.3 Procedure, Results, and Discussion 295
References 301
Chapter 28 302
Modeling Physiological and Psychophysical Responses to Precedence Effect Stimuli 302
28.1 Introduction 303
28.2 Methods 303
28.2.1 Stimuli 303
28.2.2 Model Structure 304
28.2.3 Data Analysis 305
28.2.4 The Readout 305
28.3 Results 307
28.3.1 Simulations of Physiological Data 307
28.3.2 Simulations of Psychophysical Data 309
28.4 Conclusions 309
References 311
Chapter 29 312
Binaurally-Coherent Jitter Improves Neural and Perceptual ITD Sensitivity in Normal and Electric Hearing 312
29.1 Introduction 313
29.2 Perceptual Experiment 313
29.2.1 Method 313
29.2.2 Results 315
29.2.3 Discussion 315
29.3 Neurophysiology 315
29.3.1 Method 315
29.3.2 Jitter Can Restore Ongoing Neural Firing at High Pulse Rates 316
29.3.3 Restoration of Ongoing Firing Reveals ITD Sensitivity 317
29.4 Neural Modeling 319
29.5 General Discussion 320
References 322
Chapter 30 323
Lateralization of Tone Complexes in Noise: The Role of Monaural Envelope Processing in Binaural Hearing 323
30.1 Introduction 323
30.2 Detection Experiment 325
30.3 Results and Discussion 326
30.4 Discrimination Experiment 326
30.5 Results and Discussion 327
30.6 Lateralization Experiment 328
30.7 Results and Discussion 329
30.8 General Discussion 330
References 331
Chapter 31 333
Adjustment of Interaural-Time-Difference Analysis to Sound Level 333
31.1 Introduction 333
31.2 Methods 334
31.2.1 Psychophysics 334
31.2.1.1 Stimuli 334
31.2.1.2 Procedure 336
31.2.1.3 Listeners 336
31.2.2 Electrophysiology 336
31.2.2.1 Animals 336
31.2.2.2 Recording Procedure and General Neural Characterization 337
31.2.2.3 Pip-Train Stimulation 337
31.2.2.4 Analysis 337
31.3 Results 338
31.4 Discussion 342
References 343
Chapter 32 345
The Role of Envelope Waveform, Adaptation, and Attacks in Binaural Perception 345
32.1 Introduction 345
32.2 Experiments 347
32.2.1 Method 347
32.2.1.1 Listeners 347
32.2.1.2 Apparatus and Stimuli 347
32.2.1.3 Procedure 348
32.2.2 Results 348
32.3 Model Predictions 350
32.3.1 Models 350
32.3.2 Model Predictions 351
32.4 Discussion 352
References 353
Chapter 33 355
Short-Term Synaptic Plasticity and Adaptation Contribute to the Coding of Timing and Intensity Information 355
33.1 Introduction 356
33.2 Methods 356
33.2.1 Chick NA Physiology and Simulation 356
33.2.1.1 Recording from Owls’ NM and NL Neurons In Vivo 357
33.2.1.2 Simulation of NL Neuron Responses 358
33.3 Results 358
33.3.1 Short-Term Plasticity Affects Intensity Coding in Nucleus Angularis 358
33.3.2 Timing Pathway and Adaptation 361
33.3.2.1 Firing Rate Adaptation in NM and NL 362
33.3.2.2 Simulation of NL Coding 362
33.4 Conclusions 363
References 364
Chapter 34 365
Adaptive Coding for Auditory Spatial Cues 365
34.1 Introduction 365
34.2 Methods 366
34.2.1 Physiological Recordings 366
34.2.2 Data Analysis 367
34.3 Results 369
34.3.1 Neurons Are Sensitive to Changes in the Mean of ITD Distributions 369
34.3.2 Coding Accuracy Shifts to Accommodate Shifts in HPR Mean 369
34.3.3 Neurons Are Insensitive to the Changes in the Variance of ITD Distributions 370
34.3.4 Neural Mechanisms Underlying Adaptive Coding of ITDs 370
34.4 Discussion 373
References 374
Chapter 35 375
Phase Shifts in Monaural Field Potentials of the Medial Superior Olive 375
35.1 Introduction 376
35.2 Methods 376
35.2.1 Surgical Preparation 376
35.2.2 Stimulus Generation and Signal Sampling 377
35.2.3 Stimuli and Data Collection 377
35.3 Results 378
35.3.1 Current Source Density Analysis 381
35.4 Discussion 383
35.5 Comment by Catherine Carr 384
35.6 Reply Myles Mc Laughlin 385
References 385
Part VI Speech Processing and Perception 387
Chapter 36 388
Representation of Intelligible and Distorted Speech in Human Auditory Cortex 388
36.1 Introduction 389
36.2 Generation of Distorted Speech 389
36.3 Psychophysics of Spectrally Rotated Speech 390
36.3.1 Subjects 391
36.3.2 Stimulus Presentation 391
36.3.3 Results 392
36.4 Brain Activation in Response to Distorted Speech Stimuli 393
36.4.1 Stimulus Presentation 393
36.4.2 Subjects and Task 394
36.4.3 Scanning Procedure 394
36.4.4 Data Analysis 395
36.4.5 Results 395
36.5 Discussion 396
36.6 Conclusions 397
References 397
Chapter 37 399
Intelligibility of Time-Compressed Speech with Periodic and Aperiodic Insertions of Silence: Evidence for Endogenous Brain R 399
37.1 Introduction 400
37.2 Background 401
37.3 Experiment 402
37.3.1 SUS Corpus 402
37.3.2 Stimulus Preparation 402
37.3.3 Subjects 403
37.3.4 Instructions to Subjects 403
37.3.5 Results 405
37.3.5.1 Overall 405
37.3.5.2 Statistical Analysis 405
37.4 Discussion 406
37.4.1 Does Intelligibility Reflect Short-Term Memory Limitations? 408
37.4.2 Why Is the Intelligibility Curve U-Shaped? 408
37.4.3 Condition x80: Why Does Intelligibility Deteriorate in the Aperiodic Condition? 410
References 411
Chapter 38 412
The Representation of the Pitch of Vowel Sounds in Ferret Auditory Cortex 412
38.1 Introduction 413
38.2 Ferret Behavioral Pitch Sensitivity 414
38.2.1 Psychoacoustic Methods 414
38.2.2 Psychoacoustic Results 414
38.3 Mapping of F0 Sensitivity Across Cortex 415
38.3.1 Electrophysiological Methods 415
38.3.2 Mapping Results (Sensitivity Maps) 416
38.4 Neurometric Analysis: Putative Neural Codes for Pitch 417
38.4.1 Neurometric Methods 417
38.4.2 Neurometric Results 417
38.5 Discussion and Conclusions 419
References 420
Chapter 39 422
Macroscopic and Microscopic Analysis of Speech Recognition in Noise: What Can Be Understood at Which Level? 422
39.1 Introduction 422
39.2 Acoustical Level: SNR-Based Speech Perception Measures (SII Approaches) 424
39.3 Sensory Level/Peripheral Processing: (Example: Binaural Interaction) 425
39.4 Central Level: A Microscopic Model of Speech Recognition 428
39.5 Conclusions 431
References 431
Chapter 40 433
Effects of Peripheral Tuning on the Auditory Nerve’s Representation of Speech Envelope and Temporal Fine Structure Cues 433
40.1 Introduction 434
40.2 Methods 434
40.2.1 The Auditory Periphery Model 434
40.2.2 Speech Intelligibility Metric (STMI) 435
40.2.3 Auditory Chimaeras 437
40.2.4 TFS-Only Signals 437
40.3 Test Speech Material 437
40.4 Results 438
40.5 Conclusions 441
40.6 Comment by Michael Heinz 441
40.7 Reply Rasha Ibrahim 442
References 442
Chapter 41 443
Room Reflections and Constancy in Speech-Like Sounds: Within-Band Effects 443
41.1 Introduction 443
41.2 Method 445
41.2.1 Speech Contexts and the Test-Word Continuum 445
41.2.2 Category Boundaries 446
41.2.3 Room Reflections 446
41.2.4 8-Band Speech 447
41.2.5 Design 447
41.2.6 Procedure 448
41.3 Results 449
41.4 Discussion 450
References 451
Chapter 42 452
Identification of Perceptual Cues for Consonant Sounds and the Influence of Sensorineural Hearing Loss on Speech Perception 452
42.1 Introduction 453
42.2 Identification of Perceptual Cues 454
42.2.1 Modeling Speech Reception 454
42.2.2 Principle of 3D Approach 454
42.2.3 Data Interpretation 455
42.2.4 Perceptual Cues of Stop Consonants 456
42.3 Influence of Hearing Loss on Speech Perception 459
42.3.1 Diagnosis of Hearing Loss 459
42.3.2 Quantification of Consonant Loss 460
42.3.2.1 Speech Stimuli 460
42.3.2.2 Conditions 460
42.3.2.3 Procedure 460
42.4 Results 461
42.4.1 Hearing Loss 461
42.4.2 Consonant Identification 462
42.5 Discussion 463
References 465
Part VII Auditory Scene Analysis 466
Chapter 43 467
A Comparative View on the Perception of Mistuning: Constraints of the Auditory Periphery 467
43.1 Introduction 468
43.2 Detecting Frequency Shifts of Pure Tones 468
43.3 Detecting a Mistuned Component in Harmonic Complexes 472
43.3.1 Mistuning Detection in Sine Phase Harmonic Complexes 472
43.3.2 Mistuning Detection in Random Phase Harmonic Complexes 473
43.3.3 Neural Basis of Mistuning Detection 474
References 476
Chapter 44 478
Stability of Perceptual Organisation in Auditory Streaming 478
44.1 Introduction 479
44.2 Experiment 1 479
44.2.1 Participants 479
44.2.2 Stimulus Paradigm 480
44.2.3 Procedure 480
44.2.4 Results 481
44.3 Experiment 2 482
44.3.1 Participants 482
44.3.2 Stimulus Paradigm 482
44.3.3 Results 483
44.4 Experiment 3 484
44.4.1 Participants 484
44.4.2 Stimulus Paradigm 484
44.4.3 Results 485
44.5 Discussion 486
References 488
Chapter 45 489
Sequential and Simultaneous Auditory Grouping Measured with Synchrony Detection 489
45.1 Introduction 489
45.2 Experiment 1: Sequential Capture Overrides Synchrony Detection 490
45.3 Methods 490
45.4 Results and Discussion 492
45.5 Experiment 2: Synchrony Overrides Sequential Grouping 492
45.6 Methods 492
45.7 Results and Discussion 494
45.8 Conclusions 495
References 496
Chapter 46 497
Rate Versus Temporal Code? A Spatio-Temporal Coherence Model of the Cortical Basis of Streaming 497
46.1 Introduction 498
46.2 Neurophysiological Basis of Stream Organization in AI 498
46.3 Spatio-Temporal Coherence Model 500
46.3.1 Auditory Processing from Periphery to Cortex 500
46.3.2 Coherence Analysis 501
46.3.3 Decomposing the Coherence Matrix 502
46.3.4 Model Validation 502
46.3.4.1 Varying Degrees of Synchrony 502
46.3.4.2 Experiment I: Synchrony Overrides Sequential Grouping 503
46.3.4.3 Experiment II: Sequential Capture Overrides Synchrony Detection 504
46.4 Conclusions 505
References 505
Chapter 47 507
Objective Measures of Auditory Scene Analysis 507
47.1 Introduction 507
47.2 Auditory Streaming 508
47.2.1 Experiment 1: Objective Measures of the Build-Up of Streaming 509
47.2.1.1 Methods 509
47.2.1.2 Results 510
47.2.2 Experiment 2: Effect of Attention on Streaming 510
47.2.2.1 Rationale and Method 510
47.2.2.2 Results 512
47.2.3 Experiment 3: Electrophysiological Measure of Streaming Build-Up 512
47.2.3.1 Rationale and Method 512
47.2.3.2 Results 513
47.3 The Continuity Illusion 514
47.3.1 A Correlate of the Continuity Illusion Obtained Using fMRI 514
47.3.2 Experiment 4: Effect of Attention on the Continuity Illusion 516
47.3.2.1 Rationale and Method 516
47.3.2.2 Results 516
47.4 Summary 517
47.5 Comment by Daniel Oberfeld-Twistel 519
References 519
Chapter 48 520
Perception of Concurrent Sentences with Harmonic or Frequency-Shifted Voiced Excitation: Performance of Human Listeners and 520
48.1 Introduction 521
48.2 Experiment 522
48.3 Computational Models 524
48.4 Modelling Studies: Results 525
48.5 Modelling Studies: Limitations and Future Directions 528
48.6 Summary and Conclusions 529
References 530
Part VIII Novelty Detection, Attention and Learning 531
Chapter 49 532
Is There Stimulus-Specific Adaptation in the Medial Geniculate Body of the Rat? 532
49.1 Introduction 532
49.2 Materials and Methods 534
49.2.1 Surgical Procedures, Acoustic Stimuli, and Electrophysiological Recording 534
49.2.2 Stimulus Presentation Paradigms 535
49.3 Results 535
49.4 Discussion 538
References 540
Chapter 50 542
Auditory Streaming at the Cocktail Party: 542
50.1 Introduction 542
50.2 Methods 544
50.3 Results 545
50.4 Discussion 547
References 549
Chapter 51 551
Correlates of Auditory Attention and Task Performance in Primary Auditory and Prefrontal Cortex 551
51.1 Introduction 551
51.2 Rapid Plasticity in A1 Receptive Fields 553
51.2.1 STRF Plasticity in A1 During Aversive Tone Detection and Discrimination Tasks 554
51.2.2 Contrasting Effects of Aversive and Appetitive Tasks 555
51.3 Encoding of Task Rules and Stimuli in Prefrontal Cortex 556
51.3.1 PFC Responses During Aversive (or Conditioned Avoidance) Tasks 556
51.3.2 PFC Responses During Appetitive Tasks 560
51.3.3 PFC Responses in Tasks with Visual Stimuli 560
51.4 Relationship Between A1 and PFC Responses 560
51.4.1 Analysis and Coherence of Local Field Potentials 561
51.4.1.1 Within PFC and A1 Correlations 561
51.4.1.2 Coherence Between PFC and A1 562
51.4.2 Microstimulation in PFC Modulates Receptive Fields in A1 562
51.5 Summary and Discussion 564
References 565
Chapter 52 567
The Implicit Learning of Noise: Behavioral Data and Computational Models 567
52.1 Introduction 567
52.2 Experiment 1 568
52.2.1 Method 568
52.2.2 Results 569
52.3 Experiment 2 570
52.3.1 Method 571
52.3.2 Results 571
52.4 Computational Models 572
52.5 Discussion 572
52.5.1 Repeated Exposure Produced Learning of Noise Samples 572
52.5.2 Forming Noise Templates or Memorizing Single Features 574
52.5.3 Constraints for Neural Mechanisms 574
References 575
Chapter 53 576
Role of Primary Auditory Cortex in Acoustic Orientation and Approach-to-Target Responses 576
53.1 Introduction 577
53.2 Methods 577
53.2.1 Sound Localization Testing 578
53.2.2 Inactivation of the Auditory Cortex 578
53.2.3 Histology 579
53.2.4 Data Analysis 579
53.3 Results 580
53.3.1 Anatomy 580
53.3.2 Approach-to-Target Sound Localization 580
53.3.3 Head Orienting Responses 585
53.4 Discussion and Conclusions 585
53.5 Comment by Catherine Carr 586
53.6 Reply Fernando Nodal 587
References 587
Part IX Hearing Impairment 589
Chapter 54 590
Objective and Behavioral Estimates of Cochlear Response Times in Normal-Hearing and Hearing-Impaired Human Listeners 590
54.1 Introduction 590
54.2 Lateralization of Mismatched Tones 592
54.2.1 Methods 592
54.2.2 Results and Discussion 592
54.3 Auditory Brainstem Responses 595
54.3.1 Methods 595
54.3.2 Results and Discussion 595
54.4 Auditory-Filter Bandwidth 596
54.4.1 Method 596
54.4.2 Results and Discussion 597
54.5 Summary and Conclusion 598
References 599
Chapter 55 601
Why Do Hearing-Impaired Listeners Fail to Benefit from Masker Fluctuations? 601
55.1 Introduction 601
55.2 Procedure 603
55.2.1 Experimental Data 603
55.2.2 Model Description 604
55.2.3 Model Parameterization 605
55.2.4 Application to Earlier Results 605
55.3 Results 606
55.4 Discussion 608
55.5 Conclusions 609
References 610
Chapter 56 612
Across-Fiber Coding of Temporal Fine-Structure: Effects of Noise-Induced Hearing Loss on Auditory-Nerve Responses 612
56.1 Introduction 613
56.2 Methods 613
56.2.1 Experimental Procedures 613
56.2.2 Predicting Spatiotemporal Patterns from Individual AN Fibers 614
56.2.3 Within-CF and Across-CF Temporal Analyses 614
56.3 Results 616
56.4 Discussion 620
References 620
Chapter 57 622
Beyond the Audiogram: Identifying and Modeling Patterns of Hearing Deficits 622
57.1 Introduction 622
57.2 Methods 623
57.2.1 Psychoacoustic Profiles of Normal and Impaired Listeners 623
57.2.1.1 Psychoacoustic Measures 623
57.2.1.2 Threshold Estimation Procedure 624
57.2.1.3 Listeners 624
57.2.2 Computer Modeling 625
57.3 Results 625
57.3.1 Normal Data and Model 625
57.3.2 Impaired Data and Models 626
57.3.2.1 Profile 1 (Participant ECr) 626
57.3.2.2 Profile 2 (Participant JEV) 627
57.3.2.3 Profile 3 (Participant JJo) 629
57.4 Discussion 630
References 631
Index 632
| Erscheint lt. Verlag | 23.3.2010 |
|---|---|
| Zusatzinfo | XXXI, 644 p. |
| Verlagsort | New York |
| Sprache | englisch |
| Themenwelt | Geisteswissenschaften |
| Medizin / Pharmazie ► Medizinische Fachgebiete ► HNO-Heilkunde | |
| Medizin / Pharmazie ► Medizinische Fachgebiete ► Neurologie | |
| Medizin / Pharmazie ► Studium | |
| Naturwissenschaften ► Biologie ► Humanbiologie | |
| Naturwissenschaften ► Biologie ► Zoologie | |
| Technik | |
| Schlagworte | Animal Communication • Cells • Cortex • Eliza • Imaging • neurons • Neuroscience • perception • Physiology • Ultrasound |
| ISBN-10 | 1-4419-5686-7 / 1441956867 |
| ISBN-13 | 978-1-4419-5686-6 / 9781441956866 |
| Haben Sie eine Frage zum Produkt? |
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