Polymer-fiber-coupled field-effect sensors for label-free deep brain recordings.

Electrical recording permits direct readout of neural activity but offers limited ability to correlate it to the network topography. On the other hand, optical imaging reveals the architecture of neural circuits, but relies on bulky optics and fluorescent reporters whose signals are attenuated by the brain tissue. Here we introduce implantable devices to record brain activities based on the field effect, which can be further extended with capability of label-free electrophysiological mapping. Such devices reply on light-addressable potentiometric sensors (LAPS) coupled to polymer fibers with integrated electrodes and optical waveguide bundles. The LAPS utilizes the field effect to convert electrophysiological activity into regional carrier redistribution, and the neural activity is read out in a spatially resolved manner as a photocurrent induced by a modulated light beam. Spatially resolved photocurrent recordings were achieved by illuminating different pixels within the fiber bundles. These devices were applied to record local field potentials in the mouse hippocampus. In conjunction with the raster-scanning via the single modulated beam, this technology may enable fast label-free imaging of neural activity in deep brain regions.

Use of information visualization methods eliminating cross talk in multiple sensing units investigated for a light-addressable potentiometric sensor.

The integration of nanostructured films containing biomolecules and silicon-based technologies is a promising direction for reaching miniaturized biosensors that exhibit high sensitivity and selectivity. A challenge, however, is to avoid cross talk among sensing units in an array with multiple sensors located on a small area. In this letter, we describe an array of 16 sensing units of a light-addressable potentiometric sensor (LAPS), which was made with layer-by-layer (LbL) films of a poly(amidomine) dendrimer (PAMAM) and single-walled carbon nanotubes (SWNTs), coated with a layer of the enzyme penicillinase. A visual inspection of the data from constant-current measurements with liquid samples containing distinct concentrations of penicillin, glucose, or a buffer indicated a possible cross talk between units that contained penicillinase and those that did not. With the use of multidimensional data projection techniques, normally employed in information visualization methods, we managed to distinguish the results from the modified LAPS, even in cases where the units were adjacent to each other. Furthermore, the plots generated with the interactive document map (IDMAP) projection technique enabled the distinction of the different concentrations of penicillin, from 5 mmol L(-1) down to 0.5 mmol L(-1). Data visualization also confirmed the enhanced performance of the sensing units containing carbon nanotubes, consistent with the analysis of results for LAPS sensors. The use of visual analytics, as with projection methods, may be essential to handle a large amount of data generated in multiple sensor arrays to achieve high performance in miniaturized systems.