Top-down influences on the neural processing of speech sounds
In speech perception, extraction of meaning and speaker identity from complex streams of sounds is surprisingly fast and efficient. This efficiency depends on the crucial capability of our speech recognition system to deal with the acoustic variability of the input signal and to form invariant abstract representations. Furthermore top-down cues such as linguistic context and task demands may bias and facilitate this process and can be used to predict incoming information. In this talk, using examples from EEG and MEG studies, I will illustrate the central role of top-down influences during the decoding of meaning, speech sound and speaker identity information.