7 research outputs found
In vivo validation of the electronic depth control probes.
In this article, we evaluated the electrophysiological performance of a novel, high-complexity silicon probe array. This brain-implantable probe implements a dynamically reconfigurable voltage-recording device, coordinating large numbers of electronically switchable recording sites, referred to as electronic depth control (EDC). Our results show the potential of the EDC devices to record good-quality local field potentials, and single- and multiple-unit activities in cortical regions during pharmacologically induced cortical slow wave activity in an animal model
CMOS-Based High-Density Silicon Microprobe Arrays for Electronic Depth Control in Intracortical Neural Recording
P300 Detection Based on Feature Extraction in On-line Brain-Computer Interface
We propose a new EEG-based wireless brain computer interface (BCI) with which subjects can “mind-type” text on a computer screen. The application is based on detecting P300 event-related potentials in EEG signals recorded on the scalp of the subject. The BCI uses a simple classifier which relies on a linear feature extraction approach. The accuracy of the presented system is comparable to the state-of-the-art for on-line P300 detection, but with the additional benefit that its much simpler design supports a power-efficient on-chip implementation.status: publishe
Control and data acquisition software for high-density CMOS-based microprobe arrays implementing electronic depth control
This paper presents the NeuroSelect software for managing
the electronic depth control of cerebral CMOS-based microprobes for extracellular in vivo recordings. These microprobes contain up to 500 electronically switchable electrodes which can be appropriately selected with regard to specific neuron locations in the course of a recording experiment. NeuroSelect makes it possible to scan the electrodes electronically and to (re)select those electrodes of best signal quality resulting in a closed-loop design of a neural acquisition system. The signal quality is calculated by the relative power of the spikes compared with the background noise. The spikes are detected by an adaptive threshold using a robust estimator of the standard deviation. Electrodes can be selected in a manual or semi-automatic mode based on the signal quality. This electronic depth control constitutes a significant improvement for multielectrode probes, given that so far the only alternative has been the fine positioning by mechanical probe translation. In addition to managing communication with the hardware controller of the probe array, the software also controls acquisition, processing, display and storage of the neural signals for further analysis.status: publishe