Abstract
Perceiving linguistic input is vital for human functioning, but the process is complicated by the fact that the incoming signal is often degraded. However, humans can compensate for unimodal noise by relying on simultaneous sensory input from another modality. Here, we investigated noise-compensation for spoken and printed words in two experiments. In the first behavioral experiment, we observed that accuracy was modulated by reaction time, bias and sensitivity, but noise compensation could nevertheless be explained via accuracy differences when controlling for RT, bias and sensitivity. In the second experiment, we also measured Event Related Potentials (ERPs) and observed robust electrophysiological correlates of noise compensation starting at around 350 ms after stimulus onset, indicating that noise compensation is most prominent at lexical/semantic processing levels.
Highlights
Perceiving linguistic input is vital for human functioning, but the process is complicated by the fact that the incoming signal is often degraded
Likewise, when AV noise compensation is assessed by comparing noisy unimodal trials to AV trials where there is one noisy signal and one clear signal, one cannot rule out the possibility that the AV gain relative to unimodal trials is driven by the clear unimodal signal, rather than cross-modal noise compensation per se
We explored how accuracy, bias, sensitivity and accuracy-based noise compensation were modulated by RT, using the noise compensation score described in the introduction (i.e., Acccomp: [Nonoise −AVnoise] −([Nonoise −Anoise] +[Nonoise −Vnoise])
Summary
Perceiving linguistic input is vital for human functioning, but the process is complicated by the fact that the incoming signal is often degraded. We measured Event Related Potentials (ERPs) and observed robust electrophysiological correlates of noise compensation starting at around 350 ms after stimulus onset, indicating that noise compensation is most prominent at lexical/semantic processing levels.
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