Conference Presentations by Mark Steadman
Cochlear implants provide a degraded input to the auditory system. Despite this, cochlear implant... more Cochlear implants provide a degraded input to the auditory system. Despite this, cochlear implant users are able to discriminate speech sounds with a degree of accuracy comparable to that of normal hearing listeners in favourable listening conditions. The neural bases of this phenomenon is not well understood.
A set of vowel-consonant-vowel phoneme sequences, each produced by multiple talkers, were parametrically degraded using a noise vocoder. Single- and multi-unit neuronal responses were recorded in the inferior colliculus and auditory cortex of the guinea pig, and auditory nerve responses were generated using a computational model. The discriminability of these responses was quantified using a novel nearest neighbour classifier.
When envelope modulations were severely band-limited, classifier performance was qualitatively similar to that of human listeners for all brain regions. However, in the auditory nerve and the midbrain, the preservation of high rate envelope cues enabled the near perfect discrimination of speech tokens even for heavily spectrally degraded speech. High rate envelope cues do not appear to increase discriminability of cortical representations.
High rate envelope cues, represented up to the midbrain, are useful for discriminating speech tokens. However, qualitatively more consistent with perception, high rate envelope cues do not contribute to the discriminability of cortical neural responses. The optimal timescale of the neural code for discriminability also depends on the brain region and the degree of degradation of the stimuli.
Uploads
Conference Presentations by Mark Steadman
A set of vowel-consonant-vowel phoneme sequences, each produced by multiple talkers, were parametrically degraded using a noise vocoder. Single- and multi-unit neuronal responses were recorded in the inferior colliculus and auditory cortex of the guinea pig, and auditory nerve responses were generated using a computational model. The discriminability of these responses was quantified using a novel nearest neighbour classifier.
When envelope modulations were severely band-limited, classifier performance was qualitatively similar to that of human listeners for all brain regions. However, in the auditory nerve and the midbrain, the preservation of high rate envelope cues enabled the near perfect discrimination of speech tokens even for heavily spectrally degraded speech. High rate envelope cues do not appear to increase discriminability of cortical representations.
High rate envelope cues, represented up to the midbrain, are useful for discriminating speech tokens. However, qualitatively more consistent with perception, high rate envelope cues do not contribute to the discriminability of cortical neural responses. The optimal timescale of the neural code for discriminability also depends on the brain region and the degree of degradation of the stimuli.