Brainmap Seminars- Michael Beauchamp, PhD: Models and Mechanisms of Multisensory Speech Perception

Abstract:

Humans interacting face-to-face make use of auditory cues from the talker’s voice and visual cues from the talker’s mouth to understand speech. I will discuss computational models that use Bayesian principles to predict human speech perception. These models make specific predictions about the neural mechanisms of speech perception, which we test with electrocorticography (ECoG) and BOLD fMRI. The anatomical focus of these studies is the human posterior superior temporal gyrus and sulcus (pSTS), a brain region known to be important for speech perception. The pSTS has a complex organization, with some regions responding to specific visual stimuli and others to specific auditory stimuli. Using ECoG, we demonstrate a double dissociation in the pSTG. More anterior regions show a greater neural activity to audiovisual speech with a clear auditory component, as predicted for unisensory auditory regions, while more posterior regions showed similar or greater responses to noisy audiovisual speech, as predicted for multisensory cortex. Using BOLD fMRI, we show for the first time that the natural statistics of human speech, in which voices co-occur with mouth movements, are reflected in the neural architecture of the pSTS. Different pSTS regions prefer visually-presented faces containing either a moving mouth or moving eyes, but only mouth-preferring regions respond strongly to voices. 

About the Speaker

Dr. Beauchamp is a Professor in the Department of Neurosurgery and the Department of Neuroscience at Baylor College of Medicine with adjunct appointments at the University of Texas McGovern Medical School and Rice University. His laboratory examines multisensory integration and visual perception using a variety of techniques, including BOLD fMRI, electrocorticography, and computational modeling. Dr.Beauchamp is the Director of Research in the Department of Neurosurgery and the Director of CAMRI, the Core for Advanced MRI. He graduated from Harvard College in 1992, receiving his PhD from the University of California, San Diego in 1997 before pursuing postdoctoral studies in the National Institute of Mental Health Intramural Research Program.