Modeling Small Molecule Elution From a Hydrogel using a Microfluidic Technique

Drug release from a fluid-contacting biomaterial is simulated using a microfluidic device with channels defined by solute-loaded hydrogel. In order to mimic a drug delivery device, a solution of poly(ethylene glycol) diacrylate (PEG-DA), solute, and photoinitiator is cured inside a microfluidic device with a channel through the center ofthe hydrogel. As water is pumped through the channel, solute diffuses out of the hydrogel and into the water. Channel sizes within the devices range from 300 µm to 1000 µm to simulate vessels within the body. The properties of the PEG hydrogel were characterizedby the extent of crosslinking, the swelling ratio, and the mesh size of the gel. The structure of the hydrogel was related to the UV exposure dosage and the initial water and solute content in the PEG-DA solution.

Multimodal Integration in Statistical Learning: Evidence from the McGurk Illusion

Recent advances in the field of statistical learning have established that learners are able to track regularities of multimodal stimuli, yet it is unknown whether the statistical computations are performed on integrated representations or on separate, unimodal representations. In the present study, we investigated the ability of adults to integrate audio and visual input during statistical learning. We presented learners with a speech stream synchronized with a video of a speaker's face. In the critical condition, the visual (e.g., /gi/) and auditory (e.g., /mi/) signals were occasionally incongruent, which we predicted would produce the McGurk illusion, resulting in the perception of an audiovisual syllable (e.g., /ni/). In this way, we used the McGurk illusion to manipulate the underlying statistical structure of the speech streams, such that perception of these illusory syllables facilitated participants' ability to segment the speech stream. Our results therefore demonstrate that participants can integrate audio and visual input to perceive the McGurk illusion during statistical learning. We interpret our findings as support for modality-interactive accounts of statistical learning.