Auditory abstraction from spectro-temporal features to coding auditory entities

Auditory abstraction from spectro-temporal features to coding auditory entities.

The auditory system extracts behaviorally relevant information from acoustic stimuli. The average activity in auditory cortex is known to be sensitive to spectro-temporal patterns in sounds. However, it is not known whether the auditory cortex also processes more abstract features of sounds, which may be more behaviorally relevant than spectro-temporal patterns. Using recordings from three stat...

Robust automatic speech recognition and modeling of auditory discrimination experiments with auditory spectro-temporal features

Spectro-temporal interactions in auditory and auditory-visual speech processing

Speech recognition often involves the face-to-face communication between two or more individuals. The combined influences of auditory and visual speech information leads to a remarkably robust signal that is greatly resistant to noise, reverberation, hearing loss, and other forms of signal distortion. Studies of auditory-visual speech processing have revealed that speechreading interacts with a...

Spectro-Temporal Receptive Fields of Subthreshold Responses in Auditory Cortex

How do cortical neurons represent the acoustic environment? This question is often addressed by probing with simple stimuli such as clicks or tone pips. Such stimuli have the advantage of yielding easily interpreted answers, but have the disadvantage that they may fail to uncover complex or higher-order neuronal response properties. Here we adopt an alternative approach, probing neuronal respon...

Understanding Auditory Spectro-Temporal Receptive Fields and Their Changes with Input Statistics by Efficient Coding Principles

Spectro-temporal receptive fields (STRFs) have been widely used as linear approximations to the signal transform from sound spectrograms to neural responses along the auditory pathway. Their dependence on statistical attributes of the stimuli, such as sound intensity, is usually explained by nonlinear mechanisms and models. Here, we apply an efficient coding principle which has been successfull...