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Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems, to bidirectional brain-machine interfaces. The specific circuit solutions used to implement silicon neurons depend on the application requirements. In this(More)
The effect of spatial separation on the ability of human listeners to resolve a pair of concurrent broadband sounds was examined. Stimuli were presented in a virtual auditory environment using individualized outer ear filter functions. Subjects were presented with two simultaneous noise bursts that were either spatially coincident or separated (horizontally(More)
We present a new, low-power electrocardiogram (ECG) recording system with an ultra-high input impedance that enables the use of long-lasting, dry electrodes. The system incorporates a low-power Bluetooth module for wireless connectivity and is designed to be suitable for long-term monitoring during daily activities. The new system using dry electrodes was(More)
Cost reduction has become the primary theme of healthcare reforms globally. More providers are moving towards remote patient monitoring, which reduces the length of hospital stays and frees up their physicians and nurses for acute cases and helps them to tackle staff shortages. Physiological sensors are commonly used in many human specialties e.g.(More)
Recent advances in training deep (multi-layer) architectures have inspired a renaissance in neural network use. For example, deep convolutional networks are becoming the default option for difficult tasks on large datasets, such as image and speech recognition. However, here we show that error rates below 1% on the MNIST handwritten digit benchmark can be(More)
OBJECTIVE We present a new, low power EEG recording system with an ultra-high input impedance that enables the use of long-lasting, passive dry electrodes. It incorporates Bluetooth wireless connectivity and is designed to be suitable for long-term monitoring during daily activities. METHODS The new EEG system is compared to a standard and clinically(More)
This study measured the accuracy with which human listeners can localize spoken words. A broadband (300 Hz-16 kHz) corpus of monosyllabic words was created and presented tolisteners using a virtual auditory environment. Localization was examined for 76 locations ona sphere surrounding the listener. Experiment 1 showed that low-pass filtering the speech(More)
A human psychoacoustical experiment is described that investigates the role of the monaural and interaural spectral cues in human sound localization. In particular, it focuses on the relative contribution of the monaural versus the interaural spectral cues towards resolving directions within a cone of confusion (i.e., directions with similar interaural time(More)
We present an FPGA implementation of a re-configurable, polychronous spiking neural network with a large capacity for spatial-temporal patterns. The proposed neural network generates delay paths de novo, so that only connections that actually appear in the training patterns will be created. This allows the proposed network to use all the axons (variables)(More)
Feedback plays an important role when learning to use a brain computer interface (BCI), particularly in the case of synchronous feedback that relies on the interaction subject. In this preliminary study, we investigate the role of combined auditory-visual feedback during synchronous μ rhythm-based BCI sessions to help the subject to remain focused on the(More)