Biomedical subjects

C T Nordhausen

Publications and source records attributed to C T Nordhausen.

3 recordsLinked to original sources

PubMed1997

The Utah intracortical Electrode Array: a recording structure for potential brain-computer interfaces.

We investigated the potential of the Utah Intracortical Electrode Array (UIEA) to provide signals for a brain-computer interface (BCI). The UIEA records from small populations of neurons which have an average signal-to-noise ratio (SNR) of 6:1. We provide specific examples that show the activities of these populations of neurons contain sufficient information to perform control tasks. Results from a simple stimulus detection task using these signals as inputs confirm that the number of neurons present in a recording is significant in determining task performance. Increasing the number of units in a recording decreases the sensitivity of the response to the stimulus; decreasing the number of units in the recording, however, increases the variability of the response to the stimulus. We conclude that recordings from small populations of neurons, not single units, provide a reliable source of sufficiently stimulus selective signals which should be suitable for a BCI. In addition, the potential for simultaneous and proportional control of a large number of external devices may be realized through the ability of an array of microelectrodes such as the UIEA to record both spatial and temporal patterns of neuronal activation.

Action Potentials↗

PubMed1996

Single unit recording capabilities of a 100 microelectrode array.

We have developed a three-dimensional silicon electrode array which provides 100 separate channels for neural recording in cortex. The device is manufactured using silicon micromachining techniques, and we have conducted acute recording experiments in cat striate cortex to evaluate the recording capabilities of the array. In a series of five acute experiments, 58.6% of the electrodes in the array were found to be capable of recording visually evoked responses. In the most recent acute study, the average signal-to-noise ratio for recordings obtained from 56 of the electrodes in the array was calculated to be 5.5:1. Using standard window discrimination techniques, an average of 3.4 separable spikes were identified for each of these electrodes. In order to compare the two-dimensional mapping capabilities of the array with those derived from other technologies, orientation preference and ocular dominance maps were generated for each of the evoked responses. Histological evaluation of the implant site indicates some localized tissue insult, but this is likely due to the perfusion procedure since high signal-to-noise ratio neural responses were recorded. The recording capabilities of the Utah Intracortical Electrode Array in combination with the large number of electrodes available for recording make the array a tool well suited for investigations into the parallel processing mechanisms in cortex.

Animals↗

PubMed1994

Optimizing recording capabilities of the Utah Intracortical Electrode Array.

The Utah Intracortical Electrode Array is a unique silicon-based monolithic structure designed for use as a multichannel interface to the central nervous system. In this paper, we describe a series of acute experiments designed to determine the neural recording capabilities of this electrode array and the dependence of the signal-to-noise ratio (SNR) of the recordings on the electrode surface area (length of metallized tip). We found that both separable unit and multiunit cluster responses could be recorded. Additionally, high SNR recordings could be achieved for some electrodes (with electrode tip lengths of 30-220 microns), while recordings with signals substantially greater than the noise could be made from most of the electrodes provided that the proper electrode surface area was used. The demonstrated recording capabilities of the Utah Intracortical Electrode Array and its unique three-dimensional structure should form the basis for innovative physiological investigations into the functional organization of the cortex as well as for long term neuroprosthesis development.

Algorithms↗