Cortical Encoding of Auditory Objects in the Cocktail Party Problem. Jonathan Z. Simon University of Maryland
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1 Cortical Encoding of Auditory Objects in the Cocktail Party Problem Jonathan Z. Simon University of Maryland
2 Introduction Auditory Objects Magnetoencephalography (MEG) Decoding Neural Signals/Encoding Stimuli Cortical Representations of Auditory Objects I Cortical Representations of Auditory Objects II
3 Auditory Objects What is an Auditory Object? Perceptual/Psychophysical Construct Some Commonalities with Visual Objects I know it when I see it vs. Formal Definition
4 Auditory Object Definition E. g., Griffiths & Warren an object corresponds with something in the sensory world information related to the object is separate from information related to the rest of the sensory world abstracted so that object information can be generalized among particular sensory experiences in any one sensory domain
5 Auditory Objects at the Cocktail Party Alex Katz, The Cocktail Party
6 Auditory Objects at the Cocktail Party Alex Katz, The Cocktail Party
7 Auditory Objects at the Cocktail Party Alex Katz, The Cocktail Party
8 Auditory Objects at the Cocktail Party Alex Katz, The Cocktail Party
9 Auditory Objects at the Cocktail Party Alex Katz, The Cocktail Party
10 Auditory Objects at the Cocktail Party Alex Katz, The Cocktail Party
11 Auditory Objects at the Cocktail Party Alex Katz, The Cocktail Party
12 Auditory Objects at the Cocktail Party Alex Katz, The Cocktail Party
13 Auditory Objects at the Cocktail Party Alex Katz, The Cocktail Party
14 Auditory Objects at the Cocktail Party Ding & Simon, PNAS (2012)
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20 Magnetoencephalography (MEG) scalp skull B MEG V EEG recording surface orientation of magnetic field Magnetic Dipolar Field Projection CSF tissue current flow Photo by Fritz Goro Direct electrophysiological measurement not hemodynamic real-time No unique solution for distributed source Measures spatially synchronized cortical activity Fine temporal resolution (~ 1 ms) Moderate spatial resolution (~ 1 cm)
21 MEG Phase Locking to Slow Temporal Modulations AM at 3 Hz 3 Hz phase-locked response MEG activity is precisely phase-locked to temporal modulations of sound response spectrum (subject R0747) 3 Hz 6 Hz 0 10 Ding & Simon, J Neurophysiol (2009) Wang et al., J Neurophysiol (2012) Frequency (Hz)
22 Modeling MEG Response to Speech Modulations Auditory Model
23 Modeling MEG Response using STRF model Ding & Simon, J Neurophysiol (2012) Spectro-Temporal Response Function (STRF) (up to ~ 10 Hz)
24 Neural Reconstruction of Speech Envelope MEG Responses Decoder Speech Envelope. (up to ~ 10 Hz) stimulus speech envelope reconstructed stimulus speech envelope 2 s Ding & Simon, J Neurophysiol (2012) Reconstruction accuracy comparable to single unit recordings & ECoG
25 Speech Stream as an Auditory Object a speech stream corresponds with something in the sensory world information related to a speech stream is separate from information related to the rest of the sensory world, e.g. other speech streams or noise a speech stream is abstracted: it is generalized among different sensory experiences, e.g. different sound mixtures
26 Neural Representation of an Auditory Object neural representation is of auditory object, something in sensory world when auditory object is with other sounds, the neural representation is of the auditory object, not the entire acoustic scene neural representation remains invariant under broad changes in acoustic representation of auditory object
27 Selective Neural Encoding
28 Unselective vs. Selective Neural Encoding
29 Auditory Object- Specific Representation Representative subject Grand average attentding to speaker 2 attending to speaker 1 stimulus reconstructed from MEG envelope of the attended speech
30 Auditory Object- Specific Representation Representative subject Grand average attentding to speaker 2 attending to speaker 1 stimulus reconstructed from MEG envelope of the attended speech
31 Single Trial Speech Reconstruction Attended Speech Reconstruction Speaker Two attentional focus speaker one speaker two Speaker One
32 Single Trial Speech Reconstruction Speaker Two Attended Speech Reconstruction attentional focus speaker one speaker two Speaker Two Background Speech Reconstruction Speaker One Speaker One
33 Overall Speech Reconstruction 0.2 correlation attended speech reconstruction attended speech background reconstruction background
34 Overall Speech Reconstruction correlation Distinct neural representations for different speech streams 0 attended speech reconstruction attended speech background reconstruction background
35 Reconstruction of Same-Sex Speech Correlation Attended Speech Reconstruction Speaker Two Single Trial Decoding Results Attended Speaker One Two attended speech background speech Speaker One
36 Invariance Under Acoustic Changes
37 Invariance Under Acoustic Changes
38 Invariance Under Acoustic Changes
39 Invariance Under Acoustic Changes
40 Invariance Under Acoustic Changes
41 Invariance Under Acoustic Changes
42 Object-Based Gain Gain-Control Models Control? Object-Based correlation.2.1 attended background Speaker Relative Intensity (db) Globally Based correlation.2.1 attended background Speaker Relative Intensity (db)
43 Object-Based Gain Gain-Control Models Control? Object-Based correlation.2.1 attended background Neural Results Speaker Relative Intensity (db) correlation.2.1 attended background Globally Based correlation.2.1 attended background Speaker Relative Intensity (db) Speaker Relative Intensity (db)
44 Object-Based Gain Gain-Control Models Control? Object-Based correlation.2.1 attended background Neural Results Speaker Relative Intensity (db) correlation.2.1 attended background Globally Based correlation.2.1 attended background Speaker Relative Intensity (db) Speaker Relative Intensity (db)
45 Object-Based Gain Gain-Control Models Control? Object-Based correlation.2.1 attended background Neural Results Speaker Relative Intensity (db) correlation.2.1 attended background Globally Based correlation.2.1 attended background Speaker Relative Intensity (db) Speaker Relative Intensity (db) Gain Control is Object-Based Neural representation is invariant to acoustic changes.
46 STRF model Spectro-Temporal Response Function (STRF)
47 STRF Results frequency (khz) Attended time (ms) Background time (ms) STRF separable (time, frequency) 300 Hz - 2 khz dominant carrier M50STRF positive peak M100STRF negative peak M100STRF strongly modulated, but not M50STRF 0 attended background time (ms)
48 Neural Sources M100STRF source near (same as?) M100 source: STG/PT M50STRF source is anterior and medial to M100 (same as M50?): HG anterior posterior Left M50STRF M100STRF M100 medial Right 5 mm
49 Cortical Object- Processing Hierarchy Attentional Modulation Influence of Relative Intensity 0 attended background time (ms) time (ms) 8 db 5 db 0 db -5 db -8 db clean M100STRF strongly modulated by attention, but not M50STRF. M100STRF invariant against acoustic changes (but not M50STRF?). Objects well-neurally represented at 100 ms, but not 50 ms.
50 Summary Cortical representations of speech show properties consistent with being neural representations of auditory objects Meet three formal criteria Object representation well-formed at 100 ms latency (STG, PT), but not at 50 ms (HG)
51 Acknowledgements Collaborators Catherine Carr Alain de Cheveigné Didier Depireux Mounya Elhilali Jonathan Fritz Cindy Moss David Poeppel Shihab Shamma Past Postdocs Dan Hertz Yadong Wang Current Grad Students Francisco Cervantes Marisel Villafane Delgado Kim Drnec Krishna Puvvada Past Grad Students Nayef Ahmar Claudia Bonin Maria Chait Nai Ding Victor Grau-Serrat Ling Ma Raul Rodriguez Juanjuan Xiang Kai Sum Li Jiachen Zhuo Collaborators Students Murat Aytekin Julian Jenkins David Klein Huan Luo Undergraduate Students Abdulaziz Al-Turki Nicholas Asendorf Sonja Bohr Elizabeth Camenga Corinne Cameron Julien Dagenais Katya Dombrowski Kevin Kahn Andrea Shome Ben Walsh Funding NIH R03 DC NIH R01 EB NIH R01 AG NIH R01 DC NIH R01 DC NIH R01 DC NIH R01 DC NIH F31 NS USDA
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