High-resolution three-dimensional extracellular recording of neuronal activity with microfabricated electrode arrays

Bioadhesive polymer semiconductors and transistors for intimate biointerfaces

The use of bioelectronic devices relies on direct contact with soft biotissues. For transistor-type bioelectronic devices, the semiconductors that need to have direct interfacing with biotissues for effective signal transduction do not adhere well with wet tissues, thereby limiting the stability and conformability at the interface. We report a bioadhesive polymer semiconductor through a double-network structure formed by a bioadhesive brush polymer and a redox-active semiconducting polymer. The resulting semiconducting film can form rapid and strong adhesion with wet tissue surfaces together with high charge-carrier mobility of ~1 square centimeter per volt per second, high stretchability, and good biocompatibility. Further fabrication of a fully bioadhesive transistor sensor enabled us to produce high-quality and stable electrophysiological recordings on an isolated rat heart and in vivo rat muscles.

Post-explant profiling of subcellular-scale carbon fiber intracortical electrodes and surrounding neurons enables modeling of recorded electrophysiology

Objective.Characterizing the relationship between neuron spiking and the signals that electrodes record is vital to defining the neural circuits driving brain function and informing clinical brain-machine interface design. However, high electrode biocompatibility and precisely localizing neurons around the electrodes are critical to defining this relationship.Approach.Here, we demonstrate consistent localization of the recording site tips of subcellular-scale (6.8µm diameter) carbon fiber electrodes and the positions of surrounding neurons. We implanted male rats with carbon fiber electrode arrays for 6 or 12+ weeks targeting layer V motor cortex. After explanting the arrays, we immunostained the implant site and localized putative recording site tips with subcellular-cellular resolution. We then 3D segmented neuron somata within a 50µm radius from implanted tips to measure neuron positions and health and compare to healthy cortex with symmetric stereotaxic coordinates.Main results.Immunostaining of astrocyte, microglia, and neuron markers confirmed that overall tissue health was indicative of high biocompatibility near the tips. While neurons near implanted carbon fibers were stretched, their number and distribution were similar to hypothetical fibers placed in healthy contralateral brain. Such similar neuron distributions suggest that these minimally invasive electrodes demonstrate the potential to sample naturalistic neural populations. This motivated the prediction of spikes produced by nearby neurons using a simple point source model fit using recorded electrophysiology and the mean positions of the nearest neurons observed in histology. Comparing spike amplitudes suggests that the radius at which single units can be distinguished from others is near the fourth closest neuron (30.7 ± 4.6µm,X-± S) in layer V motor cortex.Significance.Collectively, these data and simulations provide the first direct evidence that neuron placement in the immediate vicinity of the recording site influences how many spike clusters can be reliably identified by spike sorting.

MatriGrid® Based Biological Morphologies: Tools for 3D Cell Culturing

Recent trends in 3D cell culturing has placed organotypic tissue models at another level. Now, not only is the microenvironment at the cynosure of this research, but rather, microscopic geometrical parameters are also decisive for mimicking a tissue model. Over the years, technologies such as micromachining, 3D printing, and hydrogels are making the foundation of this field. However, mimicking the topography of a particular tissue-relevant substrate can be achieved relatively simply with so-called template or morphology transfer techniques. Over the last 15 years, in one such research venture, we have been investigating a micro thermoforming technique as a facile tool for generating bioinspired topographies. We call them MatriGrid^®s. In this research account, we summarize our learning outcome from this technique in terms of the influence of 3D micro morphologies on different cell cultures that we have tested in our laboratory. An integral part of this research is the evolution of unavoidable aspects such as possible label-free sensing and fluidic automatization. The development in the research field is also documented in this account.

3D Electrodes for Bioelectronics

In recent studies related to bioelectronics, significant efforts have been made to form 3D electrodes to increase the effective surface area or to optimize the transfer of signals at tissue-electrode interfaces. Although bioelectronic devices with 2D and flat electrode structures have been used extensively for monitoring biological signals, these 2D planar electrodes have made it difficult to form biocompatible and uniform interfaces with nonplanar and soft biological systems (at the cellular or tissue levels). Especially, recent biomedical applications have been expanding rapidly toward 3D organoids and the deep tissues of living animals, and 3D bioelectrodes are getting significant attention because they can reach the deep regions of various 3D tissues. An overview of recent studies on 3D bioelectronic devices, such as the use of electrical stimulations and the recording of neural signals from biological subjects, is presented. Subsequently, the recent developments in materials and fabrication processing to 3D micro- and nanostructures are introduced, followed by broad applications of these 3D bioelectronic devices at various in vitro and in vivo conditions.

Recording Strategies for High Channel Count, Densely Spaced Microelectrode Arrays

Neuroscience research into how complex brain functions are implemented at an extra-cellular level requires in vivo neural recording interfaces, including microelectrodes and read-out circuitry, with increased observability and spatial resolution. The trend in neural recording interfaces toward employing high-channel-count probes or 2D microelectrodes arrays with densely spaced recording sites for recording large neuronal populations makes it harder to save on resources. The low-noise, low-power requirement specifications of the analog front-end usually requires large silicon occupation, making the problem even more challenging. One common approach to alleviating this consumption area burden relies on time-division multiplexing techniques in which read-out electronics are shared, either partially or totally, between channels while preserving the spatial and temporal resolution of the recordings. In this approach, shared elements have to operate over a shorter time slot per channel and active area is thus traded off against larger operating frequencies and signal bandwidths. As a result, power consumption is only mildly affected, although other performance metrics such as in-band noise or crosstalk may be degraded, particularly if the whole read-out circuit is multiplexed at the analog front-end input. In this article, we review the different implementation alternatives reported for time-division multiplexing neural recording systems, analyze their advantages and drawbacks, and suggest strategies for improving performance.

Investigating well potential parameters on neural spike enhancement in a stochastic-resonance pre-emphasis algorithm

Objective.Background noise experienced during extracellular neural recording limits the number of spikes that can be reliably detected, which ultimately limits the performance of next-generation neuroscientific work. In this study, we aim to utilize stochastic resonance (SR), a technique that can help identify weak signals in noisy environments, to enhance spike detectability.Approach.Previously, an SR-based pre-emphasis algorithm was proposed, where a particle inside a 1D potential well is exerted by a force defined by the extracellular recording, and the output is obtained as the displacement of the particle. In this study, we investigate how the well shape and damping status impact the output signal-to-noise ratio (SNR). We compare the overdamped and underdamped solutions of shallow- and steep-wall monostable wells and bistable wells in terms of SNR improvement using two synthetic datasets. Then, we assess the spike detection performance when thresholding is applied on the output of the well shape-damping status configuration giving the best SNR enhancement.Main results.The SNR depends on the well-shape and damping-status type as well as the input noise level. The underdamped solution of the shallow-wall monostable well can yield to more than four orders of magnitude greater SNR improvement compared to other configurations for low noise intensities. Using this configuration also results in better spike detection sensitivity and positive predictivity than the state-of-the-art spike detection algorithms for a public synthetic dataset. For larger noise intensities, the overdamped solution of the steep-wall monostable well provides better spike enhancement than the others.Significance.The dependence of SNR improvement on the input signal noise level can be used to design a detector with multiple outputs, each more sensitive to a certain distance from the electrode. Such a detector can potentially enhance the performance of a successive spike sorting stage.

Recording site placement on planar silicon-based probes affects signal quality in acute neuronal recordings

Multisite, silicon-based probes are widely used tools to record the electrical activity of neuronal populations. Several physical features of these devices are designed to improve their recording performance. Here, our goal was to investigate whether the position of recording sites on the silicon shank might affect the quality of the recorded neural signal in acute experiments. Neural recordings obtained with five different types of high-density, single-shank, planar silicon probes from anesthetized rats were analyzed. Wideband data were filtered to extract spiking activity, then the amplitude distribution of samples and quantitative properties of the recorded brain activity (single unit yield, spike amplitude and isolation distance) were compared between sites located at different positions of the silicon shank, focusing particularly on edge and center sites. Edge sites outperformed center sites: for all five probe types there was a significant difference in the signal power computed from the amplitude distributions, and edge sites recorded significantly more large amplitude samples both in the positive and negative range. Although the single unit yield was similar between site positions, the difference in spike amplitudes was noticeable in the range corresponding to high-amplitude spikes. Furthermore, the advantage of edge sites slightly decreased with decreasing shank width. Our results might aid the design of novel neural implants in enhancing their recording performance by identifying more efficient recording site placements.

Recording site placement on planar silicon-based probes affects signal quality in acute neuronal recordings

Multisite, silicon-based probes are widely used tools to record the electrical activity of neuronal populations. Several physical features of these devices are designed to improve their recording performance. Here, our goal was to investigate whether the position of recording sites on the silicon shank might affect the quality of the recorded neural signal in acute experiments. Neural recordings obtained with five different types of high-density, single-shank, planar silicon probes from anesthetized rats were analyzed. Wideband data were filtered to extract spiking activity, then the amplitude distribution of samples and quantitative properties of the recorded brain activity (single unit yield, spike amplitude and isolation distance) were compared between sites located at different positions of the silicon shank, focusing particularly on edge and center sites. Edge sites outperformed center sites: for all five probe types there was a significant difference in the signal power computed from the amplitude distributions, and edge sites recorded significantly more large amplitude samples both in the positive and negative range. Although the single unit yield was similar between site positions, the difference in spike amplitudes was noticeable in the range corresponding to high-amplitude spikes. Furthermore, the advantage of edge sites slightly decreased with decreasing shank width. Our results might aid the design of novel neural implants in enhancing their recording performance by identifying more efficient recording site placements.

Technological Challenges in the Development of Optogenetic Closed-Loop Therapy Approaches in Epilepsy and Related Network Disorders of the Brain

Epilepsy is a chronic, neurological disorder affecting millions of people every year. The current available pharmacological and surgical treatments are lacking in overall efficacy and cause side-effects like cognitive impairment, depression, tremor, abnormal liver and kidney function. In recent years, the application of optogenetic implants have shown promise to target aberrant neuronal circuits in epilepsy with the advantage of both high spatial and temporal resolution and high cell-specificity, a feature that could tackle both the efficacy and side-effect problems in epilepsy treatment. Optrodes consist of electrodes to record local field potentials and an optical component to modulate neurons via activation of opsin expressed by these neurons. The goal of optogenetics in epilepsy is to interrupt seizure activity in its earliest state, providing a so-called closed-loop therapeutic intervention. The chronic implantation in vivo poses specific demands for the engineering of therapeutic optrodes. Enzymatic degradation and glial encapsulation of implants may compromise long-term recording and sufficient illumination of the opsin-expressing neural tissue. Engineering efforts for optimal optrode design have to be directed towards limitation of the foreign body reaction by reducing the implant's elastic modulus and overall size, while still providing stable long-term recording and large-area illumination, and guaranteeing successful intracerebral implantation. This paper presents an overview of the challenges and recent advances in the field of electrode design, neural-tissue illumination, and neural-probe implantation, with the goal of identifying a suitable candidate to be incorporated in a therapeutic approach for long-term treatment of epilepsy patients.

A novel method for quantifying periodicity and time delay in dynamic neural networks using unstable subaction potential threshold depolarizations

Techniques to identify and correlate the propagation of electrical signals (like action potentials) along neural networks are well described, using multisite recordings. In these cases, the waveform of action potentials is usually relatively stable and discriminating relevant electrical signals straightforward. However, problems can arise when attempting to identify and correlate the propagation of signals when their waveforms are unstable (e.g., fluctuations in amplitude or time course). This makes correlation of the degree of synchronization and time lag between propagating electrical events across two or more recording sites problematic. Here, we present novel techniques for the determination of the periodicity of electrical signals at individual sites. When recording from two independent sites, we present novel analytical techniques for joint determination of periodicity and time delay. The techniques presented exploit properties of the cross-correlation function, rather than utilizing the time lag at which the cross-correlation function is maximized. The approach allows determination of directionality of the spread of excitation along a neural network based on measurements of the time delay between recording sites. This new method is particularly applicable to analysis of signals in other biological systems that have unstable characteristics in waveform that show dynamic variability.NEW & NOTEWORTHY The determination of frequency(s) at which two sources are synchronized, and relative time delay between them, is a fundamental problem for a wide a range of signal-processing applications. In this methodology paper, we present novel procedures for periodicity estimation for single time series and joint periodicity and time delay estimation for two time series. The methods use properties of the cross-correlation function rather than the cross-correlation function explicitly.

Ultracompact Multielectrode Array for Neurological Monitoring

Patients with paralysis, spinal cord injury, or amputated limbs could benefit from using brain–machine interface technology for communication and neurorehabilitation. In this study, a 32-channel three-dimensional (3D) multielectrode probe array was developed for the neural interface system of a brain–machine interface to monitor neural activity. A novel microassembly technique involving lead transfer was used to prevent misalignment in the bonding plane during the orthogonal assembly of the 3D multielectrode probe array. Standard microassembly and biopackaging processes were utilized to implement the proposed lead transfer technique. The maximum profile of the integrated 3D neural device was set to 0.50 mm above the pia mater to reduce trauma to brain cells. Benchtop tests characterized the electrical impedance of the neural device. A characterization test revealed that the impedance of the 3D multielectrode probe array was on average approximately 0.55 MΩ at a frequency of 1 KHz. Moreover, in vitro cytotoxicity tests verified the biocompatibility of the device. Subsequently, 3D multielectrode probe arrays were implanted in rats and exhibited the capability to record local field potentials and spike signals.

Scalable, Modular Three-Dimensional Silicon Microelectrode Assembly via Electroless Plating

We devised a scalable, modular strategy for microfabricated 3-D neural probe synthesis. We constructed a 3-D probe out of individual 2-D components (arrays of shanks bearing close-packed electrodes) using mechanical self-locking and self-aligning techniques, followed by electroless nickel plating to establish electrical contact between the individual parts. We detail the fabrication and assembly process and demonstrate different 3-D probe designs bearing thousands of electrode sites. We find typical self-alignment accuracy between shanks of <0.2° and demonstrate orthogonal electrical connections of 40 µm pitch, with thousands of connections formed electrochemically in parallel. The fabrication methods introduced allow the design of scalable, modular electrodes for high-density 3-D neural recording. The combination of scalable 3-D design and close-packed recording sites may support a variety of large-scale neural recording strategies for the mammalian brain.

Network analysis of hippocampal neurons by microelectrode array in the presence of HIV-1 Tat and cocaine

HIV-associated neurocognitive disorders affecting greater than 30% of patients are caused by HIV-1 infection of the CNS, and in part, include neurotoxic effects of the viral transactivator of transcription, Tat protein. In addition to increasing the risk for becoming HIV infected, cocaine abuse enhances the neuropathogenic impacts of HIV-1. To investigate the outcome of Tat and cocaine interference in the hippocampal neuronal network, cross-rank-corrlation was employed to develop a systematic framework to assess hippocampal neurons behavior cultured on multielectrode arrays. Tat and cocaine differentially disturbed neuronal spiking rates, amplitude, synchronous activity, and oscillations within the hippocampal neuronal network via potentiation of inhibitory neurotransmission. The Tat-mediated impairment of neuronal spiking was reversible by removal of Tat, which restored neuronal activity. The presence of astrocytes co-cultured with neuronal networks diminished the effects of Tat and cocaine on neuron function suggesting a role for astrocytes in stabilizing neuronal behavior and increasing neuronal spontaneous activities such as bursting amplitude, frequency, and wave propagation rate. Taken together, our studies indicate that the HIV protein Tat and cocaine impair hippocampal neuronal network functioning and that the presence of astrocytes alleviates network dysfunction pointing to a newly discovered pathway through which ionic homeostasis is maintained by neuron-glial crosstalk in the CNS.

Extrapolating meaning from local field potential recordings

Local field potentials (LFP) reflect the spatially weighted low-frequency activity nearest to a recording electrode. LFP recording is a window to a wide range of cellular activities and has gained increasing attention over recent years. We here review major conceptual issues related to LFP with the goal of creating a resource for non-experts considering implementing LFP into their research. We discuss the cellular activity that constitutes the local field potential; recording techniques, including recommendations and limitations; approaches to analysis of LFP data (with focus on power-banded analyses); and finally we discuss reports of the successful use of LFP in clinical applications.

Large-scale recording of thalamocortical circuits: in vivo electrophysiology with the two-dimensional electronic depth control silicon probe

Recording simultaneous activity of a large number of neurons in distributed neuronal networks is crucial to understand higher order brain functions. We demonstrate the in vivo performance of a recently developed electrophysiological recording system comprising a two-dimensional, multi-shank, high-density silicon probe with integrated complementary metal-oxide semiconductor electronics. The system implements the concept of electronic depth control (EDC), which enables the electronic selection of a limited number of recording sites on each of the probe shafts. This innovative feature of the system permits simultaneous recording of local field potentials (LFP) and single- and multiple-unit activity (SUA and MUA, respectively) from multiple brain sites with high quality and without the actual physical movement of the probe. To evaluate the in vivo recording capabilities of the EDC probe, we recorded LFP, MUA, and SUA in acute experiments from cortical and thalamic brain areas of anesthetized rats and mice. The advantages of large-scale recording with the EDC probe are illustrated by investigating the spatiotemporal dynamics of pharmacologically induced thalamocortical slow-wave activity in rats and by the two-dimensional tonotopic mapping of the auditory thalamus. In mice, spatial distribution of thalamic responses to optogenetic stimulation of the neocortex was examined. Utilizing the benefits of the EDC system may result in a higher yield of useful data from a single experiment compared with traditional passive multielectrode arrays, and thus in the reduction of animals needed for a research study.

Depth-specific optogenetic control in vivo with a scalable, high-density μLED neural probe

Controlling neural circuits is a powerful approach to uncover a causal link between neural activity and behaviour. Optogenetics has been widely adopted by the neuroscience community as it offers cell-type-specific perturbation with millisecond precision. However, these studies require light delivery in complex patterns with cellular-scale resolution, while covering a large volume of tissue at depth in vivo. Here we describe a novel high-density silicon-based microscale light-emitting diode (μLED) array, consisting of up to ninety-six 25 μm-diameter μLEDs emitting at a wavelength of 450 nm with a peak irradiance of 400 mW/mm². A width of 100 μm, tapering to a 1 μm point, and a 40 μm thickness help minimise tissue damage during insertion. Thermal properties permit a set of optogenetic operating regimes, with ~0.5 °C average temperature increase. We demonstrate depth-dependent activation of mouse neocortical neurons in vivo, offering an inexpensive novel tool for the precise manipulation of neural activity.

High-density optrodes for multi-scale electrophysiology and optogenetic stimulation

We demonstrate the design and implementation of hybrid optical-electrical probes (`optrodes') for high resolution electrophysiology and optogenetic stimulation of neurons in multiple brain areas. Our 64-channel implantable optrodes are minimally invasive (50 μm × 20 μm) and span 1~2 mm. To minimize tethering forces on the brain tissue a monolithic high-density flexible cable (6 μm thin) connects the probe to a lightweight headstage (1.3 gr, 256 channel configuration) designed for awake, freely-behaving small animals. A polymer-based multi-channel photonic light delivery system is integrated on shank in a separate layer, providing local optogenetic stimulation of the neural population adjacent to the probe. The entire manufacturing process, including the nanofabrication of the optrodes, post-fabrication assembly, and surgical implantation procedures are designed to be scalable, high-yield, and high-throughput.

Development, manufacturing and application of double-sided flexible implantable microelectrodes

Many neuroprosthetic applications require the use of very small, flexible multi-channel microelectrodes (e.g. polyimide-based film-like electrodes) to fit anatomical constraints. By arranging the electrode contacts on both sides of the polyimide film, selectivity can be further increased without increasing size. In this work, two approaches to create such double-sided electrodes are described and compared: sandwich electrodes prepared by precisely gluing two single-sided structures together, and monolithic electrodes created using a new double-sided photolithography process. Both methods were successfully applied to manufacture double-sided electrodes for stimulation of the vestibular system. In a case study, the electrodes were implanted in the semicircular canals of three guinea pigs and proven to provide electrical stimulation of the vestibular nerve. For both the monolithic electrodes and the sandwich electrodes, long-term stability and functionality was observed over a period of more than 12 months. Comparing the two types of electrodes with respect to the manufacturing process, it can be concluded that monolithic electrodes are the preferred solution for very thin electrodes (<20 μm), while sandwich electrode technology is especially suitable for thicker electrodes (40-50 μm).

Tools for probing local circuits: high-density silicon probes combined with optogenetics

To understand how function arises from the interactions between neurons, it is necessary to use methods that allow the monitoring of brain activity at the single-neuron, single-spike level and the targeted manipulation of the diverse neuron types selectively in a closed-loop manner. Large-scale recordings of neuronal spiking combined with optogenetic perturbation of identified individual neurons has emerged as a suitable method for such tasks in behaving animals. To fully exploit the potential power of these methods, multiple steps of technical innovation are needed. We highlight the current state of the art in electrophysiological recording methods, combined with optogenetics, and discuss directions for progress. In addition, we point to areas where rapid development is in progress and discuss topics where near-term improvements are possible and needed.

Cell type- and activity-dependent extracellular correlates of intracellular spiking

Despite decades of extracellular action potential (EAP) recordings monitoring brain activity, the biophysical origin and inherent variability of these signals remain enigmatic. We performed whole cell patch recordings of excitatory and inhibitory neurons in rat somatosensory cortex slice while positioning a silicon probe in their vicinity to concurrently record intra- and extracellular voltages for spike frequencies under 20 Hz. We characterize biophysical events and properties (intracellular spiking, extracellular resistivity, temporal jitter, etc.) related to EAP recordings at the single-neuron level in a layer-specific manner. Notably, EAP amplitude was found to decay as the inverse of distance between the soma and the recording electrode with similar (but not identical) resistivity across layers. Furthermore, we assessed a number of EAP features and their variability with spike activity: amplitude (but not temporal) features varied substantially (∼ 30-50% compared with mean) and nonmonotonically as a function of spike frequency and spike order. Such EAP variation only partly reflects intracellular somatic spike variability and points to the plethora of processes contributing to the EAP. Also, we show that the shape of the EAP waveform is qualitatively similar to the negative of the temporal derivative to the intracellular somatic voltage, as expected from theory. Finally, we tested to what extent EAPs can impact the lowpass-filtered part of extracellular recordings, the local field potential (LFP), typically associated with synaptic activity. We found that spiking of excitatory neurons can significantly impact the LFP at frequencies as low as 20 Hz. Our results question the common assertion that the LFP acts as proxy for synaptic activity.

Sparse sampling: theory, methods and an application in neuroscience

The current methods used to convert analogue signals into discrete-time sequences have been deeply influenced by the classical Shannon-Whittaker-Kotelnikov sampling theorem. This approach restricts the class of signals that can be sampled and perfectly reconstructed to bandlimited signals. During the last few years, a new framework has emerged that overcomes these limitations and extends sampling theory to a broader class of signals named signals with finite rate of innovation (FRI). Instead of characterising a signal by its frequency content, FRI theory describes it in terms of the innovation parameters per unit of time. Bandlimited signals are thus a subset of this more general definition. In this paper, we provide an overview of this new framework and present the tools required to apply this theory in neuroscience. Specifically, we show how to monitor and infer the spiking activity of individual neurons from two-photon imaging of calcium signals. In this scenario, the problem is reduced to reconstructing a stream of decaying exponentials.

WONOEP appraisal: optogenetic tools to suppress seizures and explore the mechanisms of epileptogenesis

Optogenetics is a novel technology that combines optics and genetics by optical control of microbial opsins, targeted to living cell membranes. The versatility and the electrophysiologic characteristics of the light-sensitive ion-channels channelrhodopsin-2 (ChR2), halorhodopsin (NpHR), and the light-sensitive proton pump archaerhodopsin-3 (Arch) make these optogenetic tools potent candidates in controlling neuronal firing in models of epilepsy and in providing insights into the physiology and pathology of neuronal network organization and synchronization. Opsins allow selective activation of excitatory neurons and inhibitory interneurons, or subclasses of interneurons, to study their activity patterns in distinct brain-states in vivo and to dissect their role in generation of synchrony and seizures. The influence of gliotransmission on epileptic network function is another topic of great interest that can be further explored by using light-activated Gq protein-coupled opsins for selective activation of astrocytes. The ever-growing optogenetic toolbox can also be combined with emerging techniques that have greatly expanded our ability to record specific subtypes of cortical and hippocampal neurons in awake behaving animals such as juxtacellular recording and two-photon guided whole-cell recording, to identify the specific subtypes of neurons that are altered in epileptic networks. Finally, optogenetic tools allow rapid and reversible suppression of epileptic electroencephalography (EEG) activity upon photoactivation. This review outlines the most recent advances achieved with optogenetic techniques in the field of epilepsy by summarizing the presentations contributed to the 13th ILAE WONOEP meeting held in the Laurentian Mountains, Quebec, in June 2013.

Effects of carbon nanotube and conducting polymer coated microelectrodes on single-unit recordings in vitro

Neuronal networks cultured on microelectrode arrays (MEAs) have been utilized as biosensors that can detect all or nothing extracellular action potentials, or spikes. Coating the microelectrodes with carbon nanotubes (CNTs), either pristine or conjugated with a conductive polymer, has been previously reported to improve extracellular recordings presumably via reduction in microelectrode impedance. The goal of this work was to examine the basis of such improvement in vitro. Every other microelectrode of in vitro MEAs was electrochemically modified with either conducting polymer, poly-3,4-ethylenedioxythiophene (PEDOT) or a blend of CNT and PEDOT. Mouse cortical tissue was dissociated and cultured on the MEAs to form functional neuronal networks. The performance of the modified and unmodified microelectrodes was evaluated by activity measures such as spike rate, spike amplitude, burst duration and burst rate. We observed that the yield, defined as percentage of microelectrodes with neuronal activity, was significantly higher by 55% for modified microelectrodes compared to the unmodified sites. However, the spike rate and burst parameters were similar for modified and unmodified microelectrodes suggesting that neuronal networks were not physiologically altered by presence of PEDOT or PEDOT-CNT. Our observations from immunocytochemistry indicated that neuronal cells were more abundant in proximity to modified microelectrodes.

Large-scale, high-density (up to 512 channels) recording of local circuits in behaving animals

Monitoring representative fractions of neurons from multiple brain circuits in behaving animals is necessary for understanding neuronal computation. Here, we describe a system that allows high-channel-count recordings from a small volume of neuronal tissue using a lightweight signal multiplexing headstage that permits free behavior of small rodents. The system integrates multishank, high-density recording silicon probes, ultraflexible interconnects, and a miniaturized microdrive. These improvements allowed for simultaneous recordings of local field potentials and unit activity from hundreds of sites without confining free movements of the animal. The advantages of large-scale recordings are illustrated by determining the electroanatomic boundaries of layers and regions in the hippocampus and neocortex and constructing a circuit diagram of functional connections among neurons in real anatomic space. These methods will allow the investigation of circuit operations and behavior-dependent interregional interactions for testing hypotheses of neural networks and brain function.

A finite rate of innovation algorithm for fast and accurate spike detection from two-photon calcium imaging

OBJECTIVE

Inferring the times of sequences of action potentials (APs) (spike trains) from neurophysiological data is a key problem in computational neuroscience. The detection of APs from two-photon imaging of calcium signals offers certain advantages over traditional electrophysiological approaches, as up to thousands of spatially and immunohistochemically defined neurons can be recorded simultaneously. However, due to noise, dye buffering and the limited sampling rates in common microscopy configurations, accurate detection of APs from calcium time series has proved to be a difficult problem.

APPROACH

Here we introduce a novel approach to the problem making use of finite rate of innovation (FRI) theory (Vetterli et al 2002 IEEE Trans. SIGNAL PROCESS: 50 1417-28). For calcium transients well fit by a single exponential, the problem is reduced to reconstructing a stream of decaying exponentials. Signals made of a combination of exponentially decaying functions with different onset times are a subclass of FRI signals, for which much theory has recently been developed by the signal processing community. Main results. We demonstrate for the first time the use of FRI theory to retrieve the timing of APs from calcium transient time series. The final algorithm is fast, non-iterative and parallelizable. Spike inference can be performed in real-time for a population of neurons and does not require any training phase or learning to initialize parameters.

SIGNIFICANCE

The algorithm has been tested with both real data (obtained by simultaneous electrophysiology and multiphoton imaging of calcium signals in cerebellar Purkinje cell dendrites), and surrogate data, and outperforms several recently proposed methods for spike train inference from calcium imaging data.

Activation of specific interneurons improves V1 feature selectivity and visual perception

Inhibitory interneurons are essential components of the neural circuits underlying various brain functions. In the neocortex, a large diversity of GABAergic interneurons have been identified based on their morphology, molecular markers, biophysical properties, and innervation pattern^1,2,3. However, how the activity of each subtype of interneurons contributes to sensory processing remains unclear. Here we show that optogenetic activation of parvalbumin-positive (PV+) interneurons in mouse V1 sharpens neuronal feature selectivity and improves perceptual discrimination. Using multichannel recording with silicon probes^4,5 and channelrhodopsin 2 (ChR2)-mediated optical activation⁶, we found that elevated spiking of PV+ interneurons markedly sharpened orientation tuning and enhanced direction selectivity of nearby neurons. These effects were caused by the activation of inhibitory neurons rather than decreased spiking of excitatory neurons, since archaerhodopsin-3 (Arch)-mediated optical silencing⁷ of calcium/calmodulin-dependent protein kinase IIα-positive (CaMKIIα+) excitatory neurons caused no significant change in V1 stimulus selectivity. Moreover, the improved selectivity specifically required PV+ neuron activation, since activating somatostatin (SOM+) or vasointestinal peptide (VIP+) interneurons had no significant effect. Notably, PV+ neuron activation in awake mice caused a significant improvement in their orientation discrimination, mirroring the sharpened V1 orientation tuning. Together, these results provide the first demonstration that visual coding and perception can be improved by elevated spiking of a specific subtype of cortical inhibitory interneurons.

The brain activity map project and the challenge of functional connectomics

The function of neural circuits is an emergent property that arises from the coordinated activity of large numbers of neurons. To capture this, we propose launching a large-scale, international public effort, the Brain Activity Map Project, aimed at reconstructing the full record of neural activity across complete neural circuits. This technological challenge could prove to be an invaluable step toward understanding fundamental and pathological brain processes.

Influence fields: a quantitative framework for representation and analysis of active dendrites

Neuronal dendrites express numerous voltage-gated ion channels (VGICs), typically with spatial gradients in their densities and properties. Dendritic VGICs, their gradients, and their plasticity endow neurons with information processing capabilities that are higher than those of neurons with passive dendrites. Despite this, frameworks that incorporate dendritic VGICs and their plasticity into neurophysiological and learning theory models have been far and few. Here, we develop a generalized quantitative framework to analyze the extent of influence of a spatially localized VGIC conductance on different physiological properties along the entire stretch of a neuron. Employing this framework, we show that the extent of influence of a VGIC conductance is largely independent of the conductance magnitude but is heavily dependent on the specific physiological property and background conductances. Morphologically, our analyses demonstrate that the influences of different VGIC conductances located on an oblique dendrite are confined within that oblique dendrite, thus providing further credence to the postulate that dendritic branches act as independent computational units. Furthermore, distinguishing between active and passive propagation of signals within a neuron, we demonstrate that the influence of a VGIC conductance is spatially confined only when propagation is active. Finally, we reconstruct functional gradients from VGIC conductance gradients using influence fields and demonstrate that the cumulative contribution of VGIC conductances in adjacent compartments plays a critical role in determining physiological properties at a given location. We suggest that our framework provides a quantitative basis for unraveling the roles of dendritic VGICs and their plasticity in neural coding, learning, and homeostasis.

Applicability of independent component analysis on high-density microelectrode array recordings

Emerging complementary metal oxide semiconductor (CMOS)-based, high-density microelectrode array (HD-MEA) devices provide high spatial resolution at subcellular level and a large number of readout channels. These devices allow for simultaneous recording of extracellular activity of a large number of neurons with every neuron being detected by multiple electrodes. To analyze the recorded signals, spiking events have to be assigned to individual neurons, a process referred to as "spike sorting." For a set of observed signals, which constitute a linear mixture of a set of source signals, independent component (IC) analysis (ICA) can be used to demix blindly the data and extract the individual source signals. This technique offers great potential to alleviate the problem of spike sorting in HD-MEA recordings, as it represents an unsupervised method to separate the neuronal sources. The separated sources or ICs then constitute estimates of single-neuron signals, and threshold detection on the ICs yields the sorted spike times. However, it is unknown to what extent extracellular neuronal recordings meet the requirements of ICA. In this paper, we evaluate the applicability of ICA to spike sorting of HD-MEA recordings. The analysis of extracellular neuronal signals, recorded at high spatiotemporal resolution, reveals that the recorded data cannot be modeled as a purely linear mixture. As a consequence, ICA fails to separate completely the neuronal signals and cannot be used as a stand-alone method for spike sorting in HD-MEA recordings. We assessed the demixing performance of ICA using simulated data sets and found that the performance strongly depends on neuronal density and spike amplitude. Furthermore, we show how postprocessing techniques can be used to overcome the most severe limitations of ICA. In combination with these postprocessing techniques, ICA represents a viable method to facilitate rapid spike sorting of multidimensional neuronal recordings.

An interdisciplinary learning experience in neuro-optics

How can a Ph.D. student initially trained as a biologist take part in the development of a multineuronal recording method that requires cross interaction between physics, neurobiology and mathematics? Beyond student training in the laboratory, interdisciplinary research calls for a new style of academic training of young researchers. Here we present an innovative approach to graduate student academic training that fills the need for multidisciplinary knowledge and provides students, in addition, with a deeper understanding of the interdisciplinary approach to scientific research.

Dipole characterization of single neurons from their extracellular action potentials

The spatial variation of the extracellular action potentials (EAP) of a single neuron contains information about the size and location of the dominant current source of its action potential generator, which is typically in the vicinity of the soma. Using this dependence in reverse in a three-component realistic probe + brain + source model, we solved the inverse problem of characterizing the equivalent current source of an isolated neuron from the EAP data sampled by an extracellular probe at multiple independent recording locations. We used a dipole for the model source because there is extensive evidence it accurately captures the spatial roll-off of the EAP amplitude, and because, as we show, dipole localization, beyond a minimum cell-probe distance, is a more accurate alternative to approaches based on monopole source models. Dipole characterization is separable into a linear dipole moment optimization where the dipole location is fixed, and a second, nonlinear, global optimization of the source location. We solved the linear optimization on a discrete grid via the lead fields of the probe, which can be calculated for any realistic probe + brain model by the finite element method. The global source location was optimized by means of Tikhonov regularization that jointly minimizes model error and dipole size. The particular strategy chosen reflects the fact that the dipole model is used in the near field, in contrast to the typical prior applications of dipole models to EKG and EEG source analysis. We applied dipole localization to data collected with stepped tetrodes whose detailed geometry was measured via scanning electron microscopy. The optimal dipole could account for 96% of the power in the spatial variation of the EAP amplitude. Among various model error contributions to the residual, we address especially the error in probe geometry, and the extent to which it biases estimates of dipole parameters. This dipole characterization method can be applied to any recording technique that has the capabilities of taking multiple independent measurements of the same single units.

Inverse current source density method in two dimensions: inferring neural activation from multielectrode recordings

The recent development of large multielectrode recording arrays has made it affordable for an increasing number of laboratories to record from multiple brain regions simultaneously. The development of analytical tools for array data, however, lags behind these technological advances in hardware. In this paper, we present a method based on forward modeling for estimating current source density from electrophysiological signals recorded on a two-dimensional grid using multi-electrode rectangular arrays. This new method, which we call two-dimensional inverse Current Source Density (iCSD 2D), is based upon and extends our previous one- and three-dimensional techniques. We test several variants of our method, both on surrogate data generated from a collection of Gaussian sources, and on model data from a population of layer 5 neocortical pyramidal neurons. We also apply the method to experimental data from the rat subiculum. The main advantages of the proposed method are the explicit specification of its assumptions, the possibility to include system-specific information as it becomes available, the ability to estimate CSD at the grid boundaries, and lower reconstruction errors when compared to the traditional approach. These features make iCSD 2D a substantial improvement over the approaches used so far and a powerful new tool for the analysis of multielectrode array data. We also provide a free GUI-based MATLAB toolbox to analyze and visualize our test data as well as user datasets.

Multiplexed, high density electrophysiology with nanofabricated neural probes

Extracellular electrode arrays can reveal the neuronal network correlates of behavior with single-cell, single-spike, and sub-millisecond resolution. However, implantable electrodes are inherently invasive, and efforts to scale up the number and density of recording sites must compromise on device size in order to connect the electrodes. Here, we report on silicon-based neural probes employing nanofabricated, high-density electrical leads. Furthermore, we address the challenge of reading out multichannel data with an application-specific integrated circuit (ASIC) performing signal amplification, band-pass filtering, and multiplexing functions. We demonstrate high spatial resolution extracellular measurements with a fully integrated, low noise 64-channel system weighing just 330 mg. The on-chip multiplexers make possible recordings with substantially fewer external wires than the number of input channels. By combining nanofabricated probes with ASICs we have implemented a system for performing large-scale, high-density electrophysiology in small, freely behaving animals that is both minimally invasive and highly scalable.

Integration of silicon-via electrodes with different recording characteristics on a glass microprobe using a glass reflowing process

Electrodes on planar type microelectromechanical system (MEMS) microprobes mainly record neurons on the top-side of probe shaft (called a top-side electrode). However, it is often necessary to record neurons other than those on the top-side of the probe shaft. This study uses the glass reflowing technique to embed silicon-vias in a glass probe to implement a microprobe capable of recording neurons around the shaft. The proposed technology makes it possible to fabricate, distribute, and integrate four types of electrodes on the shaft: top-side, back-side, double-side, and sidewall electrodes. These electrodes have different recording characteristics. The in vitro and in vivo (using crayfish and rat brain) experiments in this study shows that the top-side and back-side electrodes are respectively more sensitive to neurons on the top-side and back-side of the probe shaft. In contrast, signals recorded by double-side electrode and sidewall electrode are equally sensitive to neurons around the probe shaft. This study enables the implementation and integration of these four types of electrodes, meeting the requirements of various neural applications.

Theoretical analysis of intracortical microelectrode recordings

Advanced fabrication techniques have now made it possible to produce microelectrode arrays for recording the electrical activity of a large number of neurons in the intact brain for both clinical and basic science applications. However, the long-term recording performance desired for these applications is hindered by a number of factors that lead to device failure or a poor signal-to-noise ratio (SNR). The goal of this study was to identify factors that can affect recording quality using theoretical analysis of intracortical microelectrode recordings of single-unit activity. Extracellular microelectrode recordings were simulated with a detailed multi-compartment cable model of a pyramidal neuron coupled to a finite-element volume conductor head model containing an implanted recording microelectrode. Recording noise sources were also incorporated into the overall modeling infrastructure. The analyses of this study would be very difficult to perform experimentally; however, our model-based approach enabled a systematic investigation of the effects of a large number of variables on recording quality. Our results demonstrate that recording amplitude and noise are relatively independent of microelectrode size, but instead are primarily affected by the selected recording bandwidth, impedance of the electrode-tissue interface and the density and firing rates of neurons surrounding the recording electrode. This study provides the theoretical groundwork that allows for the design of the microelectrode and recording electronics such that the SNR is maximized. Such advances could help enable the long-term functionality required for chronic neural recording applications.

Estimation of electrode location in a rat motor cortex by laminar analysis of electrophysiology and intracortical electrical stimulation

While the development of microelectrode arrays has enabled access to disparate regions of a cortex for neurorehabilitation, neuroprosthetic and basic neuroscience research, accurate interpretation of the signals and manipulation of the cortical neurons depend upon the anatomical placement of the electrode arrays in a layered cortex. Toward this end, this report compares two in vivo methods for identifying the placement of electrodes in a linear array spaced 100 µm apart based on in situ laminar analysis of (1) ketamine-xylazine-induced field potential oscillations in a rat motor cortex and (2) an intracortical electrical stimulation-induced movement threshold. The first method is based on finding the polarity reversal in laminar oscillations which is reported to appear at the transition between layers IV and V in laminar 'high voltage spindles' of the rat cortical column. Analysis of histological images in our dataset indicates that polarity reversal is detected 150.1 ± 104.2 µm below the start of layer V. The second method compares the intracortical microstimulation currents that elicit a physical movement for anodic versus cathodic stimulation. It is based on the hypothesis that neural elements perpendicular to the electrode surface are preferentially excited by anodic stimulation while cathodic stimulation excites those with a direction component parallel to its surface. With this method, we expect to see a change in the stimulation currents that elicits a movement at the beginning of layer V when comparing anodic versus cathodic stimulation as the upper cortical layers contain neuronal structures that are primarily parallel to the cortical surface and lower layers contain structures that are primarily perpendicular. Using this method, there was a 78.7 ± 68 µm offset in the estimate of the depth of the start of layer V. The polarity reversal method estimates the beginning of layer V within ±90 µm with 95% confidence and the intracortical stimulation method estimates it within ±69.3 µm. We propose that these methods can be used to estimate the in situ location of laminar electrodes implanted in the rat motor cortex.

Wiring nanoscale biosensors with piezoelectric nanomechanical resonators

Nanoscale integrated circuits and sensors will require methods for unobtrusive interconnection with the macroscopic world to fully realize their potential. We report on a nanoelectromechanical system that may present a solution to the wiring problem by enabling information from multisite sensors to be multiplexed onto a single output line. The basis for this method is a mechanical Fourier transform mediated by piezoelectrically coupled nanoscale resonators. Our technique allows sensitive, linear, and real-time measurement of electrical potentials from conceivably any voltage-sensitive device. With this method, we demonstrate the direct transduction of neuronal action potentials from an extracellular microelectrode. This approach to wiring nanoscale devices could lead to minimally invasive implantable sensors with thousands of channels for in vivo neuronal recording, medical diagnostics, and electrochemical sensing.

Validation of a novel three-dimensional electrode array within auditory cortex

Three-dimensional electrode arrays have a variety of potential applications in the fields of both intracortical mapping as well as basic research studies designed to characterize and understand the physiology of the brain. While higher channels counts are desired in brain-machine interface applications, the ability to analyze synchronous data from multiple cortical locations, including various depths is pivotal to fully mapping the underlying neurophysiology of sensory cortices. Within this study, we present a proof of concept validation of a 3D probe technology consisting of 16 silicon shanks in a 4x4 grid arrangement with four electrode sites per shank. This 3D array has been implanted in a rat primary auditory cortex and electrophysiological data are presented showing the utility of electrode sites spanning multilateral cortical space as well as cortical depth.

Insertion of a three dimensional silicon microelectrode assembly through a thick meningeal membrane

There are many different needs for intraoperative mapping in both rodent as well as human brain. Whether the goal of the procedure is for epileptic mapping, removal of cancerous tissue, mapping the motor and sensory cortices, or understanding the underlying neural networks within the brain, dense three-dimensional electrode arrays are necessary. In this study, we outlined and validated thicker silicon probe designs for use in intracortical mapping applications. Multiple shank and electrode site configurations were implanted successfully through rat dura as a model for human pia, and all devices maintained the electrical functionality necessary for electrophysiological mapping applications.

Three-dimensional micro-electrode array for recording dissociated neuronal cultures

This work demonstrates the design, fabrication, packaging, characterization, and functionality of an electrically and fluidically active three-dimensional micro-electrode array (3D MEA) for use with neuronal cell cultures. The successful function of the device implies that this basic concept-construction of a 3D array with a layered approach-can be utilized as the basis for a new family of neural electrode arrays. The 3D MEA prototype consists of a stack of individually patterned thin films that form a cell chamber conducive to maintaining and recording the electrical activity of a long-term three-dimensional network of rat cortical neurons. Silicon electrode layers contain a polymer grid for neural branching, growth, and network formation. Along the walls of these electrode layers lie exposed gold electrodes which permit recording and stimulation of the neuronal electrical activity. Silicone elastomer micro-fluidic layers provide a means for loading dissociated neurons into the structure and serve as the artificial vasculature for nutrient supply and aeration. The fluidic layers also serve as insulation for the micro-electrodes. Cells have been shown to survive in the 3D MEA for up to 28 days, with spontaneous and evoked electrical recordings performed in that time. The micro-fluidic capability was demonstrated by flowing in the drug tetrotodoxin to influence the activity of the culture.