In this paper, we present a modular Data Acquisition (DAQ) system for simultaneous electrical stimulation and recording of brain activity. The DAQ system is designed to work with custom-designed Application Specific Integrated Circuit (ASIC) called Neurostim-3 and a variety of commercially available Multi-Electrode Arrays (MEAs). The system can control simultaneously up to 512 independent bidirectional i.e., input-output channels. We present in-depth insight into both hardware and software architectures and discuss relationships between cooperating parts of that system. The particular focus of this study was the exploration of efficient software design so that it could perform all its tasks in real-time using a standard Personal Computer (P...
Abstract: Neural interface is man-made information pathway through which biological nerve system cou...
AbstractThe measurement of neural signals is mandatory for an extensive and detailed understanding o...
International audienceIn order to understand the dynamics of large neural networks, where informatio...
In this paper we present a measurement system for in vivo multichannel recordings of the electro-phy...
Large circuits of neurons are employed by the brain to encode and process information. How this enco...
A measurement system for 256-channel in vitro recordings of brain tissue electrophysiological activi...
Since a few decades, micro-fabricated neural probes are being used, together with microelectronic in...
This paper presents a portable, embedded, microcontroller-based system for bidirectional communicati...
Modern multielectrode array (MEA) systems can record the neuronal activity from thousands of electro...
We describe a novel brain slice system ‘SliceMaster’ that allows electrophysiological recordings fro...
In this paper a system for neural recording and stimulation is presented. The device is composed of...
The rapid progress of technology in the semiconductor industry over the last decades allowed the dev...
In this paper we present SpikeOnChip, a custom embedded platform for neuronal activity recording and...
This work presents a high-voltage, high-precision bi-directional multi-channel system capable of sti...
Recent improvements in microelectrodes technology have enabled neuroscientists to record electrophys...
Abstract: Neural interface is man-made information pathway through which biological nerve system cou...
AbstractThe measurement of neural signals is mandatory for an extensive and detailed understanding o...
International audienceIn order to understand the dynamics of large neural networks, where informatio...
In this paper we present a measurement system for in vivo multichannel recordings of the electro-phy...
Large circuits of neurons are employed by the brain to encode and process information. How this enco...
A measurement system for 256-channel in vitro recordings of brain tissue electrophysiological activi...
Since a few decades, micro-fabricated neural probes are being used, together with microelectronic in...
This paper presents a portable, embedded, microcontroller-based system for bidirectional communicati...
Modern multielectrode array (MEA) systems can record the neuronal activity from thousands of electro...
We describe a novel brain slice system ‘SliceMaster’ that allows electrophysiological recordings fro...
In this paper a system for neural recording and stimulation is presented. The device is composed of...
The rapid progress of technology in the semiconductor industry over the last decades allowed the dev...
In this paper we present SpikeOnChip, a custom embedded platform for neuronal activity recording and...
This work presents a high-voltage, high-precision bi-directional multi-channel system capable of sti...
Recent improvements in microelectrodes technology have enabled neuroscientists to record electrophys...
Abstract: Neural interface is man-made information pathway through which biological nerve system cou...
AbstractThe measurement of neural signals is mandatory for an extensive and detailed understanding o...
International audienceIn order to understand the dynamics of large neural networks, where informatio...