Large-Scale, High-Resolution Microelectrode Arrays for Interrogation of Neurons and Networks

Liquid crystal electro-optical transducers for electrophysiology sensing applications

Objective. Biomedical instrumentation and clinical systems for electrophysiology rely on electrodes and wires for sensing and transmission of bioelectric signals. However, this electronic approach constrains bandwidth, signal conditioning circuit designs, and the number of channels in invasive or miniature devices. This paper demonstrates an alternative approach using light to sense and transmit the electrophysiological signals. Approach. We develop a sensing, passive, fluorophore-free optrode based on the birefringence property of liquid crystals (LCs) operating at the microscale. Main results. We show that these optrodes can have the appropriate linearity (µ ± s.d.: 99.4 ± 0.5%, n = 11 devices), relative responsivity (µ ± s.d.: 57 ± 12%V−1, n = 5 devices), and bandwidth (µ ± s.d.: 11.1 ± 0.7 kHz, n = 7 devices) for transducing electrophysiology signals into the optical domain. We report capture of rabbit cardiac sinoatrial electrograms and stimulus-evoked compound action potentials from the rabbit sciatic nerve. We also demonstrate miniaturisation potential by fabricating multi-optrode arrays, by developing a process that automatically matches each transducer element area with that of its corresponding biological interface. Significance. Our method of employing LCs to convert bioelectric signals into the optical domain will pave the way for the deployment of high-bandwidth optical telecommunications techniques in ultra-miniature clinical diagnostic and research laboratory neural and cardiac interfaces.

Simultaneous Two-Photon Voltage or Calcium Imaging and Multi-Channel Local Field Potential Recordings in Barrel Cortex of Awake and Anesthetized Mice

Neuronal population activity, both spontaneous and sensory-evoked, generates propagating waves in cortex. However, high spatiotemporal-resolution mapping of these waves is difficult as calcium imaging, the work horse of current imaging, does not reveal subthreshold activity. Here, we present a platform combining voltage or calcium two-photon imaging with multi-channel local field potential (LFP) recordings in different layers of the barrel cortex from anesthetized and awake head-restrained mice. A chronic cranial window with access port allows injecting a viral vector expressing GCaMP6f or the voltage-sensitive dye (VSD) ANNINE-6plus, as well as entering the brain with a multi-channel neural probe. We present both average spontaneous activity and average evoked signals in response to multi-whisker air-puff stimulations. Time domain analysis shows the dependence of the evoked responses on the cortical layer and on the state of the animal, here separated into anesthetized, awake but resting, and running. The simultaneous data acquisition allows to compare the average membrane depolarization measured with ANNINE-6plus with the amplitude and shape of the LFP recordings. The calcium imaging data connects these data sets to the large existing database of this important second messenger. Interestingly, in the calcium imaging data, we found a few cells which showed a decrease in calcium concentration in response to vibrissa stimulation in awake mice. This system offers a multimodal technique to study the spatiotemporal dynamics of neuronal signals through a 3D architecture in vivo. It will provide novel insights on sensory coding, closing the gap between electrical and optical recordings.

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

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.