Neural Signal to Violations of Abstract Rules Using Speech-Like Stimuli

Evidence of a predictive coding hierarchy in the human brain listening to speech

Considerable progress has recently been made in natural language processing: deep learning algorithms are increasingly able to generate, summarize, translate and classify texts. Yet, these language models still fail to match the language abilities of humans. Predictive coding theory offers a tentative explanation to this discrepancy: while language models are optimized to predict nearby words, the human brain would continuously predict a hierarchy of representations that spans multiple timescales. To test this hypothesis, we analysed the functional magnetic resonance imaging brain signals of 304 participants listening to short stories. First, we confirmed that the activations of modern language models linearly map onto the brain responses to speech. Second, we showed that enhancing these algorithms with predictions that span multiple timescales improves this brain mapping. Finally, we showed that these predictions are organized hierarchically: frontoparietal cortices predict higher-level, longer-range and more contextual representations than temporal cortices. Overall, these results strengthen the role of hierarchical predictive coding in language processing and illustrate how the synergy between neuroscience and artificial intelligence can unravel the computational bases of human cognition.

Auditory representations for long lasting sounds: Insights from event-related brain potentials and neural oscillations

The basic features of short sounds, such as frequency and intensity including their temporal dynamics, are integrated in a unitary representation. Knowledge on how our brain processes long lasting sounds is scarce. We review research utilizing the Mismatch Negativity event-related potential and neural oscillatory activity for studying representations for long lasting simple versus complex sounds such as sinusoidal tones versus speech. There is evidence for a temporal constraint in the formation of auditory representations: Auditory edges like sound onsets within long lasting sounds open a temporal window of about 350 ms in which the sounds' dynamics are integrated into a representation, while information beyond that window contributes less to that representation. This integration window segments the auditory input into short chunks. We argue that the representations established in adjacent integration windows can be concatenated into an auditory representation of a long sound, thus, overcoming the temporal constraint.