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In naturally noisy listening conditions, for example at a cocktail party, noise disruptions may completely mask significant parts of a sentence, and yet listeners may still perceive the missing speech as being present. Here we demonstrate that dynamic speech-related auditory cortical activity, as measured by magnetoencephalography (MEG), which can ordinarily be used to directly reconstruct to the physical speech stimulus, can also be used to “reconstruct” acoustically missing speech. The extent to which this occurs depends on the extent that listeners are familiar with the missing speech, which is consistent with this neural activity being a dynamic representation of perceived speech even if acoustically absence. Our findings are two-fold: first, we find that when the speech is entirely acoustically absent, the acoustically absent speech can still be reconstructed with performance up to 25% of that of acoustically present speech without noise; and second, that this same expertise facilitates faster processing of natural speech by approximately 5 ms. Both effects disappear when listeners have no or very little prior experience with a given sentence. Our results suggest adaptive mechanisms of consolidation of detailed representations about speech, and the enabling of strong expectations this entails, as identifiable factors assisting automatic speech restoration over ecologically relevant timescales.

The spectrotemporal response function (STRF) model of neural encoding quantitatively associates dynamic auditory neural (output) responses to a spectrogram-like representation of a dynamic (input) stimulus. STRFs were experimentally obtained via whole-head human cortical responses to dynamic auditory stimuli using magnetoencephalography (MEG). The stimuli employed consisted of unpredictable pure tones presented at a range of rates. The predictive power of the estimated STRFs was found to be comparable to those obtained from the cortical single and multiunit activity literature. The STRFs were also qualitatively consistent with those obtained from electrophysiological studies in animal models; in particular their local-field-potential-generated spectral distributions and multiunit-activity-generated temporal distributions. Comparison of these MEG STRFs with others obtained using natural speech and music stimuli reveal a general structure consistent with common baseline auditory processing, including evidence for a transition in low-level neural representations of natural speech by 100 ms, when an appropriately chosen stimulus representation was used. It is also demonstrated that MEG-based STRFs contain information similar to that obtained using classic auditory evoked potential based approaches, but with extended applications to long-duration, non-repeated stimuli

In the phenomenon of perceptual filling-in, missing sensory information can be reconstructed via interpolation from adjacent contextual cues by what is necessarily an endogenous, not yet well understood, neural process. In this investigation, sound stimuli were chosen to allow observation of fixed cortical oscillations driven by contextual (but missing) sensory input, thus entirely reflecting endogenous neural activity. The stimulus employed was a 5 Hz frequency-modulated tone, with brief masker probes (noise bursts) occasionally added. For half the probes, the rhythmic frequency modulation was moreover removed. Listeners reported whether the tone masked by each probe was perceived as being rhythmic or not. Time-frequency analysis of neural responses obtained by magnetoencephalography (MEG) shows that for maskers without the underlying acoustic rhythm, trials where rhythm was nonetheless perceived show higher evoked sustained rhythmic power than trials for which no rhythm was reported. The results support a model in which perceptual filling-in is aided by differential co-modulations of cortical activity at rates directly relevant to human speech communication. We propose that the presence of rhythmically-modulated neural dynamics predicts the subjective experience of a rhythmically modulated sound in real time, even when the perceptual experience is not supported by corresponding sensory data.