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Biomedical subjects

Kip A Ludwig

Publications and source records attributed to Kip A Ludwig.

2 recordsLinked to original sources

Chronic neural recordings using silicon microelectrode arrays electrochemically deposited with a poly(3,4-ethylenedioxythiophene) (PEDOT) film.

Conductive polymer coatings can be used to modify traditional electrode recording sites with the intent of improving the long-term performance of cortical microelectrodes. Conductive polymers can drastically decrease recording site impedance, which in turn is hypothesized to reduce thermal noise and signal loss through shunt pathways. Moreover, conductive polymers can be seeded with agents aimed at promoting neural growth toward the recording sites or minimizing the inherent immune response. The end goal of these efforts is to generate an ideal long-term interface between the recording electrode and surrounding tissue. The goal of this study was to refine a method to electrochemically deposit surfactant-templated ordered poly(3,4-ethylenedioxythiophene) (PEDOT) films on the recording sites of standard 'Michigan' probes and to evaluate the efficacy of these modified sites in recording chronic neural activity. PEDOT-coated site performance was compared to control sites over a six-week evaluation period in terms of impedance spectroscopy, signal-to-noise ratio, number of viable unit potentials recorded and local field potential recordings. PEDOT sites were found to outperform control sites with respect to signal-to-noise ratio and number of viable unit potentials. The benefit of reduced initial impedance, however, was mitigated by the impedance contribution of typical silicon electrode encapsulation. Coating sites with PEDOT also reduced the amount of low-frequency drift evident in local field potential recordings. These findings indicate that electrode sites electrochemically deposited with PEDOT films are suitable for recording neural activity in vivo for extended periods. This study also provided a unique opportunity to monitor how neural recording characteristics develop over the six weeks following implantation.

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Naive coadaptive cortical control.

The ability to control a prosthetic device directly from the neocortex has been demonstrated in rats, monkeys and humans. Here we investigate whether neural control can be accomplished in situations where (1) subjects have not received prior motor training to control the device (naive user) and (2) the neural encoding of movement parameters in the cortex is unknown to the prosthetic device (naive controller). By adopting a decoding strategy that identifies and focuses on units whose firing rate properties are best suited for control, we show that naive subjects mutually adapt to learn control of a neural prosthetic system. Six untrained Long-Evans rats, implanted with silicon micro-electrodes in the motor cortex, learned cortical control of an auditory device without prior motor characterization of the recorded neural ensemble. Single- and multi-unit activities were decoded using a Kalman filter to represent an audio "cursor" (90 ms tone pips ranging from 250 Hz to 16 kHz) which subjects controlled to match a given target frequency. After each trial, a novel adaptive algorithm trained the decoding filter based on correlations of the firing patterns with expected cursor movement. Each behavioral session consisted of 100 trials and began with randomized decoding weights. Within 7 +/- 1.4 (mean +/- SD) sessions, all subjects were able to significantly score above chance (P < 0.05, randomization method) in a fixed target paradigm. Training lasted 24 sessions in which both the behavioral performance and signal to noise ratio of the peri-event histograms increased significantly (P < 0.01, ANOVA). Two rats continued training on a more complex task using a bilateral, two-target control paradigm. Both subjects were able to significantly discriminate the target tones (P < 0.05, Z-test), while one subject demonstrated control above chance (P < 0.05, Z-test) after 12 sessions and continued improvement with many sessions achieving over 90% correct targets. Dynamic analysis of binary trial responses indicated that early learning for this subject occurred during session 6. This study demonstrates that subjects can learn to generate neural control signals that are well suited for use with external devices without prior experience or training.

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