Dynamic modulation of detection window in conducting polymer based biosensors.

Here we demonstrate a novel application that employs the ion exchange properties of conducting polymers (CP) to modulate the detection window of a CP based biosensor under electrical stimuli. The detection window can be modulated by electrochemically controlling the degree of swelling of the CP associated with ion transport in and out of the polymer. We show that the modulation in the detection window of a caffeine imprinted polypyrrole biosensor, and by extension other CP based biosensors, can be achieved with this mechanism. Such dynamic modulation in the detection window has great potential for the development of smart biosensors, where the sensitivity of the sensor can be dynamically optimized for a specific test solution.

Composition and decomposition in bimanual dynamic learning.

Our ability to skillfully manipulate an object often involves the motor system learning to compensate for the dynamics of the object. When the two arms learn to manipulate a single object they can act cooperatively, whereas when they manipulate separate objects they control each object independently. We examined how learning transfers between these two bimanual contexts by applying force fields to the arms. In a coupled context, a single dynamic is shared between the arms, and in an uncoupled context separate dynamics are experienced independently by each arm. In a composition experiment, we found that when subjects had learned uncoupled force fields they were able to transfer to a coupled field that was the sum of the two fields. However, the contribution of each arm repartitioned over time so that, when they returned to the uncoupled fields, the error initially increased but rapidly reverted to the previous level. In a decomposition experiment, after subjects learned a coupled field, their error increased when exposed to uncoupled fields that were orthogonal components of the coupled field. However, when the coupled field was reintroduced, subjects rapidly readapted. These results suggest that the representations of dynamics for uncoupled and coupled contexts are partially independent. We found additional support for this hypothesis by showing significant learning of opposing curl fields when the context, coupled versus uncoupled, was alternated with the curl field direction. These results suggest that the motor system is able to use partially separate representations for dynamics of the two arms acting on a single object and two arms acting on separate objects.