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A new microfluidic assembly method for semiconductor-based biosensors using 3D-printing technologies was proposed for a rapid and cost-efficient design of new sensor systems. The microfluidic unit is designed and printed by a 3D-printer in just a few hours and assembled on a light-addressable potentiometric sensor (LAPS) chip using a photo resin. The cell growth curves obtained from culturing cells within microfluidics-based LAPS systems were compared with cell growth curves in cell culture flasks to examine biocompatibility of the 3D-printed chips. Furthermore, an optimal cell culturing within microfluidics-based LAPS chips was achieved by adjusting the fetal calf serum concentrations of the cell culture medium, an important factor for the cell proliferation.
A network of brain areas is expected to be involved in supporting the motion aftereffect. The most active components of this network were determined by means of an fMRI study of nine subjects exposed to a visual stimulus of moving bars producing the effect. Across the subjects, common areas were identified during various stages of the effect, as well as networks of areas specific to a single stage. In addition to the well-known motion-sensitive area MT the prefrontal brain areas BA44 and 47 and the cingulate gyrus, as well as posterior sites such as BA37 and BA40, were important components during the period of the motion aftereffect experience. They appear to be involved in control circuitry for selecting which of a number of processing styles is appropriate. The experimental fMRI results of the activation levels and their time courses for the various areas are explored. Correlation analysis shows that there are effectively two separate and weakly coupled networks involved in the total process. Implications of the results for awareness of the effect itself are briefly considered in the final discussion.