Biology subjects

Beauchamp, M.

Publications and source records attributed to Beauchamp, M..

2 recordsLinked to original sources

bioRxiv2018

Published estimates of group differences in multisensory integration are inflated

A common measure of multisensory integration is the McGurk effect, an illusion in which incongruent auditory and visual speech are integrated to produce an entirely different percept. Published studies report that participants who differ in age, gender, culture, native language, or traits related to neurological or psychiatric disorders also differ in their susceptibility to the McGurk effect. These group-level differences are used as evidence for fundamental alterations in sensory processing between populations. However, there is high variability in the McGurk effect within groups: some participants never report the illusion while others always do. High within-group variability means that sample sizes much larger than those in the published literature are necessary to accurately estimate between-group differences. Using empirical data and simulations, we show that a typical study with a sample size of 15 participants per group and a true group difference of 10% will report a group difference of 31%, an effect inflation of three-fold. Reducing the effect inflation by half requires increasing the sample size ten-fold, to 150 participants per group. The combination of within-group variability and small sizes explains two prominent features of the McGurk literature. First, group differences are inflated and highly variable across studies. Second, follow-up studies fail to replicate published reports of large between-group susceptibility differences because initial effect-size estimates are driven by statistical inflation rather than true group differences. These replication failures are especially problematic in studies of clinical populations because they have real-world consequences. Due to the high within-group variability, caution is essential when using the McGurk effect to assess deficits in clinical groups or propose treatment plans, such as training to improve sensory processing.

neuroscience↗

bioRxiv2018

Converging Evidence from Electrocorticography and BOLD fMRI for a Sharp Functional Boundary in Superior Temporal Gyrus Related to Multisensory Speech Processing

Although humans can understand speech using the auditory modality alone, in noisy environments visual speech information from the talkers mouth can rescue otherwise unintelligible auditory speech. To investigate the neural substrates of multisensory speech perception, we recorded neural activity from the human superior temporal gyrus using two very different techniques: either directly, using surface electrodes implanted in five participants with epilepsy (electrocorticography, ECOG), or indirectly, using blood oxygen level dependent functional magnetic resonance imaging (BOLD fMRI) in six healthy control fMRI participants. Both ECOG and fMRI participants viewed the same clear and noisy audiovisual speech stimuli and performed the same speech recognition task. Both techniques demonstrated a sharp functional boundary in the STG, which corresponded to an anatomical boundary defined by the posterior edge of Heschls gyrus. On the anterior side of the boundary, cortex responded more strongly to clear audiovisual speech than to noisy audiovisual speech, suggesting that anterior STG is primarily involved in processing unisensory auditory speech. On the posterior side of the boundary, cortex preferred noisy audiovisual speech or showed no preference and showed robust responses to auditory-only and visual-only speech, suggesting that posterior STG is specialized for processing multisensory audiovisual speech. For both ECOG and fMRI, the transition between the functionally distinct regions happened within 10 mm of anterior-to-posterior distance along the STG. We relate this boundary to the multisensory neural code underlying speech perception and propose that it represents an important functional division within the human speech perception network.

neuroscience↗