No abstract

A new, scalable process for microfabrication of a silicone-based, elastic multi-electrode array (MEA) is presented. The device is constructed by spinning poly(dimethylsiloxane) (PDMS) silicone elastomer onto a glass slide, depositing and patterning gold to construct wires and electrodes, spinning on a second PDMS layer, and then micropatterning the second PDMS layer to expose electrode contacts. The micropatterning of PDMS involves a custom reactive ion etch (RIE) process that preserves the underlying gold thin film. Once completed, the device can be removed from the glass slide for conformal interfacing with neural tissue. Prototype MEAs feature electrodes smaller than those known to be reported on silicone substrate (60 μm diameter exposed electrode area) and were capable of selectively stimulating the surface of the in vitro isolated spinal cord of the juvenile rat. Stretchable serpentine traces were also incorporated into the functional PDMS-based MEA, and their implementation and testing is described.

The generation of rhythmic patterns by neuronal networks is a complex phenomenon, relying on the interaction of numerous intrinsic and synaptic currents, as well as modulatory agents. To investigate the functional contribution of an individual ionic current to rhythmic pattern generation in a network, we constructed a hybrid system composed of a silicon model neuron and a heart interneuron from the heartbeat timing network of the medicinal leech. When the model neuron and a heart interneuron are connected by inhibitory synapses, they produce rhythmic activity similar to that observed in the heartbeat network. We focused our studies on investigating the functional role of the hyperpolarization-activated inward current (I h ) on the rhythmic bursts produced by the network. By introducing changes in both the model and the heart interneuron, we showed that I h determines both the period of rhythmic bursts and the balance of activity between the two sides of the network, because the amount and the activation/deactivation time constant of I h determines the length of time that a neuron spends in the inhibited phase of its burst cycle. Moreover, we demonstrated that the model neuron is an effective replacement for a heart interneuron and that changes made in the model can accurately mimic similar changes made in the living system. Finally, we used a previously developed mathematical model (Hill et al. 2001) of two mutually inhibitory interneurons to corroborate these findings. Our results demonstrated that this hybrid system technique is advantageous for investigating neuronal properties that are inaccessible with traditional techniques.

We have designed, fabricated, and tested an analog integrated-circuit architecture to implement the conductance-based dynamics that model the electrical activity of neurons. The dynamics of this architecture are in accordance with the Hodgkin-Huxley formalism, a widely exploited, biophysically plausible model of the dynamics of living neurons. Furthermore the architecture is modular and compact in size so that we can implement networks of silicon neurons, each of desired complexity, on a single integrated circuit. We present in this paper a six-conductance silicon-neuron implementation, and characterize it in relation to the Hodgkin-Huxley formalism. This silicon neuron incorporates both fast and slow ionic conductances, which are required to model complex oscillatory behaviors (spiking, bursting, subthreshold oscillations).