How can audiovisual pathways enhance the temporal resolution of time-compressed speech in blind subjects?

In blind people, the visual channel cannot assist face-to-face communication via lipreading or visual prosody. Nevertheless, the visual system may enhance the evaluation of auditory information due to its cross-links to (1) the auditory system, (2) supramodal representations, and (3) frontal action-related areas. Apart from feedback or top-down support of, for example, the processing of spatial or phonological representations, experimental data have shown that the visual system can impact auditory perception at more basic computational stages such as temporal resolution. For example, blind as compared to sighted subjects are more resistant against backward masking, and this ability appears to be associated with activity in visual cortex. Regarding the comprehension of continuous speech, blind subjects can learn to use accelerated text-to-speech systems for "reading" texts at ultra-fast speaking rates (> 16 syllables/s), exceeding by far the normal range of 6 syllables/s. An fMRI study has shown that this ability, among other brain regions, significantly covaries with BOLD responses in bilateral pulvinar, right visual cortex, and left supplementary motor area. Furthermore, magnetoencephalographic (MEG) measurements revealed a particular component in right occipital cortex phase-locked to the syllable onsets of accelerated speech. In sighted people, the "bottleneck" for understanding time-compressed speech seems related to a demand for buffering phonological material and is, presumably, linked to frontal brain structures. On the other hand, the neurophysiological correlates of functions overcoming this bottleneck, seem to depend upon early visual cortex activity. The present Hypothesis and Theory paper outlines a model that aims at binding these data together, based on early cross-modal pathways that are already known from various audiovisual experiments considering cross-modal adjustments in space, time, and object recognition.

Abstract licence: CC BY

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