Modular Data Acquisition System for Recording Activity and Electrical Stimulation of Brain Tissue Using Dedicated Electronics

Abstract

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 (PC) without the need for data precomputation even for the most demanding experiment scenarios. Not only do we show bare performance metrics, but we also used this software to characterise signal processing capabilities of Neurostim-3 (e.g., gain linearity, transmission band) so that to obtain information on how well it can handle neural signals in real-world applications. The results indicate that each Neurostim-3 channel exhibits signal gain linearity in a wide range of input signal amplitudes. Moreover, their high-pass cut-off frequency gets close to 0.6Hz making it suitable for recording both Local Field Potential (LFP) and spiking brain activity signals. Additionally, the current stimulation circuitry was checked in terms of the ability to reproduce complex patterns. Finally, we present data acquired using our system from the experiments on a living rat’s brain, which proved we obtained physiological data from non-stimulated and stimulated tissue. The presented results lead us to conclude that our hardware and software can work efficiently and effectively in tandem giving valuable insights into how information is being processed by the brain.

Quality Data Collection and Quality Monitoring of Smart Electric Energy Meter Based on Acceleration Sensor

“…Wang and others designed an intelligent meter reader circuit based on infrared communication to increase the communication distance of infrared data acquisition [9]. Jurgielewicz and others introduced laser aiming and infrared aggregation technology into the infrared communication of electric meter, which improved the efficiency of data acquisition [10]. The above methods are improved on the basis of the existing communication methods and do not fundamentally solve the problems of low data acquisition efficiency and unable to communicate in case of power failure.…”

“…), and complete the quality data collection, calculation, and statistics of intelligent electric energy meters. Considering the special nature of industrial operation of intelligent watt hour meter, the main quality characteristics can be set as functionality and reliability [10]. The former includes the conventional function items of intelligent electric energy meter specified in Q/GDM 1354-2013, such as time period, electric energy measurement, clock, deposit transfer on settlement day, zero clearing, and demand measurement.…”

Local contribution to the somatosensory evoked potentials in rat’s thalamus

“…For recordings with two NeuroNexus A8x8 probes we used 128-channel data acquisition (DAQ) system developed at the AGH University of Science and Technology in Cracow (Szypulska et al, 2016; Jurgielewicz et al, 2021). LFP signal was amplified ( × 500), filtered (0.6 Hz – 9 kHz) and sampled, along with stimuli triggers, at 40 kHz into HDF5 format files (The HDF Group, 2010).…”

Local contribution to the somatosensory evoked potentials in rat’s thalamus

“…For recordings with two NeuroNexus A8x8 probes we used a 128-channel data acquisition (DAQ) system developed at the AGH University of Science and Technology in Cracow [24,25]. LFP signal was amplified (×500), filtered (0.6 Hz-9 kHz) and sampled, along with stimuli triggers, at 40 kHz into HDF5 format files [26].…”