Recent developments have used light-activated channels or transporters to modulate neuronal activity. One such genetically-encoded modulator of activity, channelrhodopsin-2 (ChR2), depolarizes neurons in response to blue light. In this work, we first conducted electrophysiological studies of the photokinetics of hippocampal cells expressing ChR2, for various light stimulations. These and other experimental results were then used for systematic investigation of the previously proposed three-state and four-state models of the ChR2 photocycle. We show the limitations of the previously suggested three-state models and identify a four-state model that accurately follows the ChR2 photocurrents. We find that ChR2 currents decay biexponentially, a fact that can be explained by the four-state model. The model is composed of two closed (C1 and C2) and two open (O1 and O2) states, and our simulation results suggest that they might represent the dark-adapted (C1-O1) and light-adapted (C2-O2) branches. The crucial insight provided by the analysis of the new model is that it reveals an adaptation mechanism of the ChR2 molecule. Hence very simple organisms expressing ChR2 can use this form of light adaptation.

Studying neuronal processes such as synaptic summation, dendritic physiology and neural network dynamics requires complex spatiotemporal control over neuronal activities. The recent development of neural photosensitization tools, such as channelrhodopsin-2 (ChR2), offers new opportunities for non-invasive, flexible and cell-specific neuronal stimulation. Previously, complex spatiotemporal control of photosensitized neurons has been limited by the lack of appropriate optical devices which can provide 2D stimulation with sufficient irradiance. Here we present a simple and powerful solution that is based on an array of high-power micro light-emitting diodes (micro-LEDs) that can generate arbitrary optical excitation patterns on a neuronal sample with micrometre and millisecond resolution. We first describe the design and fabrication of the system and characterize its capabilities. We then demonstrate its capacity to elicit precise electrophysiological responses in cultured and slice neurons expressing ChR2.

The proposed nanometre-sized electronic devices are generally expected to show an increased probability of errors both in manufacturing and in service. Hence, there is a need to use fault-tolerant techniques in order to make reliable information processing systems out of those devices. Here we examine and compare four fault-tolerant techniques: R-fold multiple redundancy; cascaded triple modular redundancy; von Neumann's multiplexing method; and a reconfigurable computer technique. It is shown that the reconfiguration technique is the most effective technique, able to cope with manufacturing defect rates of the order of 0.01-0.1, but the technique requires enormous amounts of redundancy, of the order of 103-105. However, in the case of transient errors, multiple modular redundancy and multiplexing are the only feasible options.