| Title | Closed-Loop Characterization of Neuronal Activation Using Electrical Stimulation and Optical Imaging |
| Author | Michelle L. Kuykendal 1,2,3, Gareth S. Guvanasen 1,3, Steve M. Potter 2,3, Martha A. Grover 4 and Stephen P. DeWeerth 1,2,3,* |
| Affiliation(s) | 1 School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
2 Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
3 Laboratory for Neuroengineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
4 School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA |
| Published | Processes 2017, 5(2), 30; doi:10.3390/pr5020030 |
| Keyword | extracellular electrical stimulation; closed-loop; strength-duration; micro-electrode array (MEA); dissociated culture; activation curve; optical recording |
| Snippet | |
| Abstract | We have developed a closed-loop, high-throughput system that applies electrical stimulation and optical recording to facilitate the rapid characterization of extracellular, stimulus-evoked neuronal activity. In our system, a microelectrode array delivers current pulses to a dissociated neuronal culture treated with a calcium-sensitive fluorescent dye; automated real-time image processing of high-speed digital video identifies the neuronal response; and an optimized search routine alters the applied stimulus to achieve a targeted response. Action potentials are detected by measuring the post-stimulus, calcium-sensitive fluorescence at the neuronal somata. The system controller performs directed searches within the strength–duration (SD) stimulus-parameter space to build probabilistic neuronal activation curves. This closed-loop system reduces the number of stimuli needed to estimate the activation curves when compared to the more commonly used open-loop approach. This reduction allows the closed-loop system to probe the stimulus regions of interest in the multi-parameter waveform space with increased resolution. A sigmoid model was fit to the stimulus-evoked activation data in both current (strength) and pulse width (duration) parameter slices through the waveform space. The two-dimensional analysis results in a set of probability isoclines corresponding to each neuron–electrode pair. An SD threshold model was then fit to the isocline data. We demonstrate that a closed-loop methodology applied to our imaging and micro-stimulation system enables the study of neuronal excitation across a large parameter space. |
