The Neurally Controlled Animat: Biological Brains Acting with Simulated Bodies

Autonomous Robots. 2001  |  Pubmed ID: 18584059

The brain is perhaps the most advanced and robust computation system known. We are creating a method to study how information is processed and encoded in living cultured neuronal networks by interfacing them to a computer-generated animal, the Neurally-Controlled Animat, within a virtual world. Cortical neurons from rats are dissociated and cultured on a surface containing a grid of electrodes (multi-electrode arrays, or MEAs) capable of both recording and stimulating neural activity. Distributed patterns of neural activity are used to control the behavior of the Animat in a simulated environment. The computer acts as its sensory system providing electrical feedback to the network about the Animat's movement within its environment. Changes in the Animat's behavior due to interaction with its surroundings are studied in concert with the biological processes (e.g., neural plasticity) that produced those changes, to understand how information is processed and encoded within a living neural network. Thus, we have created a hybrid real-time processing engine and control system that consists of living, electronic, and simulated components. Eventually this approach may be applied to controlling robotic devices, or lead to better real-time silicon-based information processing and control algorithms that are fault tolerant and can repair themselves.

Real-time Multi-channel Stimulus Artifact Suppression by Local Curve Fitting

Journal of Neuroscience Methods. Oct, 2002  |  Pubmed ID: 12385761

We describe an algorithm for suppression of stimulation artifacts in extracellular micro-electrode array (MEA) recordings. A model of the artifact based on locally fitted cubic polynomials is subtracted from the recording, yielding a flat baseline amenable to spike detection by voltage thresholding. The algorithm, SALPA, reduces the period after stimulation during which action potentials cannot be detected by an order of magnitude, to less than 2 ms. Our implementation is fast enough to process 60-channel data sampled at 25 kHz in real-time on an inexpensive desktop PC. It performs well on a wide range of artifact shapes without re-tuning any parameters, because it accounts for amplifier saturation explicitly and uses a statistic to verify successful artifact suppression immediately after the amplifiers become operational. We demonstrate the algorithm's effectiveness on recordings from dense monolayer cultures of cortical neurons obtained from rat embryos. SALPA opens up a previously inaccessible window for studying transient neural oscillations and precisely timed dynamics in short-latency responses to electric stimulation.

Effective Parameters for Stimulation of Dissociated Cultures Using Multi-electrode Arrays

Journal of Neuroscience Methods. Sep, 2004  |  Pubmed ID: 15325108

Electrical stimulation through multi-electrode arrays is used to evoke activity in dissociated cultures of cortical neurons. We study the efficacies of a variety of pulse shapes under voltage control as well as current control, and determine useful parameter ranges that optimize efficacy while preventing damage through electrochemistry. For any pulse shape, stimulation is found to be mediated by negative currents. We find that positive-then-negative biphasic voltage-controlled pulses are more effective than any of the other pulse shapes tested, when compared at the same peak voltage. These results suggest that voltage-control, with its inherent control over limiting electrochemistry, may be advantageous in a wide variety of stimulation scenarios, possibly extending to in-vivo experiments.

A Versatile All-channel Stimulator for Electrode Arrays, with Real-time Control

Journal of Neural Engineering. Mar, 2004  |  Pubmed ID: 15876621

Over the last few decades, technology to record through ever increasing numbers of electrodes has become available to electrophysiologists. For the study of distributed neural processing, however, the ability to stimulate through equal numbers of electrodes, and thus to attain bidirectional communication, is of paramount importance. Here, we present a stimulation system for multi-electrode arrays which interfaces with existing commercial recording hardware, and allows stimulation through any electrode in the array, with rapid switching between channels. The system is controlled through real-time Linux, making it extremely flexible: stimulation sequences can be constructed on-the-fly, and arbitrary stimulus waveforms can be used if desired. A key feature of this design is that it can be readily and inexpensively reproduced in other labs, since it interfaces to standard PC parallel ports and uses only off-the-shelf components. Moreover, adaptation for use with in vivo multi-electrode probes would be straightforward. In combination with our freely available data-acquisition software, MeaBench, this system can provide feedback stimulation in response to recorded action potentials within 15 ms.

Effects of Random External Background Stimulation on Network Synaptic Stability After Tetanization: a Modeling Study

Neuroinformatics. 2005  |  Pubmed ID: 16077162

We constructed a simulated spiking neural network model to investigate the effects of random background stimulation on the dynamics of network activity patterns and tetanus induced network plasticity. The simulated model was a "leaky integrate-and-fire" (LIF) neural model with spike-timing-dependent plasticity (STDP) and frequency-dependent synaptic depression. Spontaneous and evoked activity patterns were compared with those of living neuronal networks cultured on multi-electrode arrays. To help visualize activity patterns and plasticity in our simulated model, we introduced new population measures called Center of Activity (CA) and Center of Weights (CW) to describe the spatio-temporal dynamics of network-wide firing activity and network-wide synaptic strength, respectively. Without random background stimulation, the network synaptic weights were unstable and often drifted after tetanization. In contrast, with random background stimulation, the network synaptic weights remained close to their values immediately after tetanization. The simulation suggests that the effects of tetanization on network synaptic weights were difficult to control because of ongoing synchronized spontaneous bursts of action potentials, or "barrages." Random background stimulation helped maintain network synaptic stability after tetanization by reducing the number and thus the influence of spontaneous barrages. We used our simulated network to model the interaction between ongoing neural activity, external stimulation and plasticity, and to guide our choice of sensory-motor mappings for adaptive behavior in hybrid neural-robotic systems or "hybrots."

Controlling Bursting in Cortical Cultures with Closed-loop Multi-electrode Stimulation

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience. Jan, 2005  |  Pubmed ID: 15659605

One of the major modes of activity of high-density cultures of dissociated neurons is globally synchronized bursting. Unlike in vivo, neuronal ensembles in culture maintain activity patterns dominated by global bursts for the lifetime of the culture (up to 2 years). We hypothesize that persistence of bursting is caused by a lack of input from other brain areas. To study this hypothesis, we grew small but dense monolayer cultures of cortical neurons and glia from rat embryos on multi-electrode arrays and used electrical stimulation to substitute for afferents. We quantified the burstiness of the firing of the cultures in spontaneous activity and during several stimulation protocols. Although slow stimulation through individual electrodes increased burstiness as a result of burst entrainment, rapid stimulation reduced burstiness. Distributing stimuli across several electrodes, as well as continuously fine-tuning stimulus strength with closed-loop feedback, greatly enhanced burst control. We conclude that externally applied electrical stimulation can substitute for natural inputs to cortical neuronal ensembles in transforming burst-dominated activity to dispersed spiking, more reminiscent of the awake cortex in vivo. This nonpharmacological method of controlling bursts will be a critical tool for exploring the information processing capacities of neuronal ensembles in vitro and has potential applications for the treatment of epilepsy.

An Extremely Rich Repertoire of Bursting Patterns During the Development of Cortical Cultures

BMC Neuroscience. 2006  |  Pubmed ID: 16464257

We have collected a comprehensive set of multi-unit data on dissociated cortical cultures. Previous studies of the development of the electrical activity of dissociated cultures of cortical neurons each focused on limited aspects of its dynamics, and were often based on small numbers of observed cultures. We followed 58 cultures of different densities--3000 to 50,000 neurons on areas of 30 to 75 mm2--growing on multi-electrode arrays (MEAs) during the first five weeks of their development.

Persistent Dynamic Attractors in Activity Patterns of Cultured Neuronal Networks

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. May, 2006  |  Pubmed ID: 16802967

Three remarkable features of the nervous system--complex spatiotemporal patterns, oscillations, and persistent activity--are fundamental to such diverse functions as stereotypical motor behavior, working memory, and awareness. Here we report that cultured cortical networks spontaneously generate a hierarchical structure of periodic activity with a strongly stereotyped population-wide spatiotemporal structure demonstrating all three fundamental properties in a recurring pattern. During these "superbursts," the firing sequence of the culture periodically converges to a dynamic attractor orbit. Precursors of oscillations and persistent activity have previously been reported as intrinsic properties of the neurons. However, complex spatiotemporal patterns that are coordinated in a large population of neurons and persist over several hours--and thus are capable of representing and preserving information--cannot be explained by known oscillatory properties of isolated neurons. Instead, the complexity of the observed spatiotemporal patterns implies large-scale self-organization of neurons interacting in a precise temporal order even in vitro, in cultures usually considered to have random connectivity.

Searching for Plasticity in Dissociated Cortical Cultures on Multi-electrode Arrays

Journal of Negative Results in Biomedicine. 2006  |  Pubmed ID: 17067395

We attempted to induce functional plasticity in dense cultures of cortical cells using stimulation through extracellular electrodes embedded in the culture dish substrate (multi-electrode arrays, or MEAs). We looked for plasticity expressed in changes in spontaneous burst patterns, and in array-wide response patterns to electrical stimuli, following several induction protocols related to those used in the literature, as well as some novel ones. Experiments were performed with spontaneous culture-wide bursting suppressed by either distributed electrical stimulation or by elevated extracellular magnesium concentrations as well as with spontaneous bursting untreated. Changes concomitant with induction were no larger in magnitude than changes that occurred spontaneously, except in one novel protocol in which spontaneous bursts were quieted using elevated extracellular magnesium concentrations.

Multi-site Stimulation Quiets Network-wide Spontaneous Bursts and Enhances Functional Plasticity in Cultured Cortical Networks

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference. 2006  |  Pubmed ID: 17946052

We culture high-density cortical cultures on multi-electrode arrays (MEAs), which allow us to stimulate and record from thousands of neurons. One of the modes of activity in these high-density cultures is dish-wide synchronized bursting. Unlike in vivo, these synchronized patterns persist for the lifetime of the culture. Such aberrant patterns of activity might be due to the fact that cortical cultures are sensory-deprived and arrested in development. We have devised methods to control this spontaneous activity by multi-electrode electrical stimulation and to study long-term functional neural plasticity, on a background of such burst-quieting stimulation. Here, we investigate whether burst quieting reveals long-term plasticity induced by tetanic stimulation. Spatio-temporal activity patterns (STAPs) that result from probe pulses were clustered and quantified in quieted and non-quieted cultures. Burst-quieted cultures show more tetanus-induced functional change than cultures which are allowed to express spontaneous bursts. The methods developed for this study will help in the understanding of network dynamics and appreciation of their role in long-term plasticity and information processing in the brain.

Embodying Cultured Networks with a Robotic Drawing Arm

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference. 2007  |  Pubmed ID: 18002625

The advanced and robust computational power of the brain is shown by the complex behaviors it produces. By embodying living cultured neuronal networks with a robotic or simulated animal (animat) and situating them within an environment, we study how the basic principles of neuronal network communication can culminate into adaptive goal-directed behavior. We engineered a closed-loop biological-robotic drawing machine and explored sensory-motor mappings and training. Preliminary results suggest that real-time performance-based feedback allowed an animat to draw in desired directions. This approach may help instruct the future design of artificial neural systems and of the algorithms to interface sensory and motor prostheses with the brain.

Experimental Platform for the Study of Region Specific Excitation and Inhibition in Neural Tissue

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference. 2007  |  Pubmed ID: 18003069

Willfully controlling the focus of an extracellular stimulus remains a significant challenge in the development of neural prosthetics and therapeutic devices. In part, this is due to the fact that experimental validation of the evoked response to stimuli is an arduous and time-consuming task. The development of a high-throughput data acquisition and analysis tool would greatly facilitate the design of spatially selective stimulation protocols. We present an automated imaging system that can optically track and identify the action potentials of individual neurons evoked by coordinated stimulus waveforms applied at multiple electrodes. This system can simultaneously provide arbitrary current waveforms to four electrodes, and it is capable of automatically monitoring the cellular responses of every neuron in a cultured network within a 1.6 x 1.6 mm area. The purpose of this platform is to develop stimulus protocols that exploit the benefits of multi-polar field shaping and temporal ion-channel manipulation to localize cellular excitation beyond the vicinity of the electrode. Preliminary single electrode experiments demonstrate that spatially selective stimulus suppression may be achieved with cathodic, depolarizing prepulses that induce a sub-threshold refractory state in neighboring neurons. Coordinated, multi-site stimuli could potentially take advantage of this refractory state to direct the stimulus focus away from the surrounding area of the electrode and into the inter-electrode spaces.

Region-specific Network Plasticity in Simulated and Living Cortical Networks: Comparison of the Center of Activity Trajectory (CAT) with Other Statistics

Journal of Neural Engineering. Sep, 2007  |  Pubmed ID: 17873432

Electrically interfaced cortical networks cultured in vitro can be used as a model for studying the network mechanisms of learning and memory. Lasting changes in functional connectivity have been difficult to detect with extracellular multi-electrode arrays using standard firing rate statistics. We used both simulated and living networks to compare the ability of various statistics to quantify functional plasticity at the network level. Using a simulated integrate-and-fire neural network, we compared five established statistical methods to one of our own design, called center of activity trajectory (CAT). CAT, which depicts dynamics of the location-weighted average of spatiotemporal patterns of action potentials across the physical space of the neuronal circuitry, was the most sensitive statistic for detecting tetanus-induced plasticity in both simulated and living networks. By reducing the dimensionality of multi-unit data while still including spatial information, CAT allows efficient real-time computation of spatiotemporal activity patterns. Thus, CAT will be useful for studies in vivo or in vitro in which the locations of recording sites on multi-electrode probes are important.

Plasticity of Recurring Spatiotemporal Activity Patterns in Cortical Networks

Physical Biology. Sep, 2007  |  Pubmed ID: 17928657

How do neurons encode and store information for long periods of time? Recurring patterns of activity have been reported in various cortical structures and were suggested to play a role in information processing and memory. To study the potential role of bursts of action potentials in memory mechanisms, we investigated patterns of spontaneous multi-single-unit activity in dissociated rat cortical cultures in vitro. Spontaneous spikes were recorded from networks of approximately 50 000 neurons and glia cultured on a grid of 60 extracellular substrate- embedded electrodes (multi-electrode arrays). These networks expressed spontaneous culture- wide bursting from approximately one week in vitro. During bursts, a large portion of the active electrodes showed elevated levels of firing. Spatiotemporal activity patterns within spontaneous bursts were clustered using a correlation-based clustering algorithm, and the occurrences of these burst clusters were tracked over several hours. This analysis revealed spatiotemporally diverse bursts occurring in well-defined patterns, which remained stable for several hours. Activity evoked by strong local tetanic stimulation resulted in significant changes in the occurrences of spontaneous bursts belonging to different clusters, indicating that the dynamical flow of information in the neuronal network had been altered. The diversity of spatiotemporal structure and long-term stability of spontaneous bursts together with their plastic nature strongly suggests that such network patterns could be used as codes for information transfer and the expression of memories stored in cortical networks.

MEART: The Semi-Living Artist

Frontiers in Neurorobotics. 2007  |  Pubmed ID: 18958276

Here, we and others describe an unusual neurorobotic project, a merging of art and science called MEART, the semi-living artist. We built a pneumatically actuated robotic arm to create drawings, as controlled by a living network of neurons from rat cortex grown on a multi-electrode array (MEA). Such embodied cultured networks formed a real-time closed-loop system which could now behave and receive electrical stimulation as feedback on its behavior. We used MEART and simulated embodiments, or animats, to study the network mechanisms that produce adaptive, goal-directed behavior. This approach to neural interfacing will help instruct the design of other hybrid neural-robotic systems we call hybrots. The interfacing technologies and algorithms developed have potential applications in responsive deep brain stimulation systems and for motor prosthetics using sensory components. In a broader context, MEART educates the public about neuroscience, neural interfaces, and robotics. It has paved the way for critical discussions on the future of bio-art and of biotechnology.

Shaping Embodied Neural Networks for Adaptive Goal-directed Behavior

PLoS Computational Biology. Mar, 2008  |  Pubmed ID: 18369432

The acts of learning and memory are thought to emerge from the modifications of synaptic connections between neurons, as guided by sensory feedback during behavior. However, much is unknown about how such synaptic processes can sculpt and are sculpted by neuronal population dynamics and an interaction with the environment. Here, we embodied a simulated network, inspired by dissociated cortical neuronal cultures, with an artificial animal (an animat) through a sensory-motor loop consisting of structured stimuli, detailed activity metrics incorporating spatial information, and an adaptive training algorithm that takes advantage of spike timing dependent plasticity. By using our design, we demonstrated that the network was capable of learning associations between multiple sensory inputs and motor outputs, and the animat was able to adapt to a new sensory mapping to restore its goal behavior: move toward and stay within a user-defined area. We further showed that successful learning required proper selections of stimuli to encode sensory inputs and a variety of training stimuli with adaptive selection contingent on the animat's behavior. We also found that an individual network had the flexibility to achieve different multi-task goals, and the same goal behavior could be exhibited with different sets of network synaptic strengths. While lacking the characteristic layered structure of in vivo cortical tissue, the biologically inspired simulated networks could tune their activity in behaviorally relevant manners, demonstrating that leaky integrate-and-fire neural networks have an innate ability to process information. This closed-loop hybrid system is a useful tool to study the network properties intermediating synaptic plasticity and behavioral adaptation. The training algorithm provides a stepping stone towards designing future control systems, whether with artificial neural networks or biological animats themselves.

Long-term Activity-dependent Plasticity of Action Potential Propagation Delay and Amplitude in Cortical Networks

PloS One. 2008  |  Pubmed ID: 18461127

The precise temporal control of neuronal action potentials is essential for regulating many brain functions. From the viewpoint of a neuron, the specific timings of afferent input from the action potentials of its synaptic partners determines whether or not and when that neuron will fire its own action potential. Tuning such input would provide a powerful mechanism to adjust neuron function and in turn, that of the brain. However, axonal plasticity of action potential timing is counter to conventional notions of stable propagation and to the dominant theories of activity-dependent plasticity focusing on synaptic efficacies.

Spatio-temporal Electrical Stimuli Shape Behavior of an Embodied Cortical Network in a Goal-directed Learning Task

Journal of Neural Engineering. Sep, 2008  |  Pubmed ID: 18714127

We developed an adaptive training algorithm, whereby an in vitro neocortical network learned to modulate its dynamics and achieve pre-determined activity states within tens of minutes through the application of patterned training stimuli using a multi-electrode array. A priori knowledge of functional connectivity was not necessary. Instead, effective training sequences were continuously discovered and refined based on real-time feedback of performance. The short-term neural dynamics in response to training became engraved in the network, requiring progressively fewer training stimuli to achieve successful behavior in a movement task. After 2 h of training, plasticity remained significantly greater than the baseline for 80 min (p-value<0.01). Interestingly, a given sequence of effective training stimuli did not induce significant plasticity (p-value=0.82) or desired behavior, when replayed to the network and no longer contingent on feedback. Our results encourage an in vivo investigation of how targeted multi-site artificial stimulation of the brain, contingent on the activity of the body or even of the brain itself could treat neurological disorders by gradually shaping functional connectivity.

Culturing Thick Brain Slices: an Interstitial 3D Microperfusion System for Enhanced Viability

Journal of Neuroscience Methods. Jun, 2009  |  Pubmed ID: 19443039

Brain slice preparations are well-established models for a wide spectrum of in vitro investigations in the neuroscience discipline. However, these investigations are limited to acute preparations or thin organotypic culture preparations due to the lack of a successful method that allows culturing of thick organotypic brain slices. Thick brain slice cultures suffer necrosis due to ischemia deep in the tissue resulting from a destroyed circulatory system and subsequent diffusion-limited supply of nutrients and oxygen. Although thin organotypic brain slice cultures can be successfully cultured using a well-established roller-tube method (a monolayer organotypic culture) (Gahwiler B H. Organotypic monolayer cultures of nervous tissue. J Neurosci Methods. 1981; 4: 329-342) or a membrane-insert method (up to 1-4 cell layers, <150 microm) (Stoppini L, Buchs PA, Muller D. A simple method for organotypic cultures of neural tissue. J Neurosci Methods 1991; 37: 173-182), these methods fail to support thick tissue preparations. A few perfusion methods (using submerged or interface/microfluidic chambers) have been reported to enhance the longevity (up to few hours) of acute slice preparations (up to 600 microm thick) (Hass HL, Schaerer B, Vosmansky M. A simple perfusion chamber for study of nervous tissue slices in vitro. J Neurosci Methods 1979; 1: 323-325; Nicoll RA, Alger BE. A simple chamber for recording from submerged brain slices. J Neurosci Methods 1981; 4: 153-156; Passeraub PA, Almeida AC, Thakor NV. Design, microfabrication and characterization of a microfluidic chamber for the perfusion of brain tissue slices. J Biomed Dev 2003; 5: 147-155). Here, we report a unique interstitial microfluidic perfusion technique to culture thick (700 microm) organotypic brain slices. The design of the custom-made microperfusion chamber facilitates laminar, interstitial perfusion of oxygenated nutrient medium throughout the tissue thickness with concomitant removal of depleted medium and catabolites. We examined the utility of this perfusion method to enhance the viability of the thick organotypic brain slice cultures after 2 days and 5 days in vitro (DIV). We investigated the range of amenable flow rates that enhance the viability of 700 microm thick organotypic brain slices compared to the unperfused control cultures. Our perfusion method allows up to 84.6% viability (p<0.01) and up to 700 microm thickness, even after 5 DIV. Our results also confirm that these cultures are functionally active and have their in vivo cyto-architecture preserved. Prolonged viability of thick organotypic brain slice cultures will benefit scientists investigating network properties of intact organotypic neuronal networks in a reliable and repeatable manner.

Statistical Long-term Correlations in Dissociated Cortical Neuron Recordings

IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society. Aug, 2009  |  Pubmed ID: 19482584

The study of nonlinear long-term correlations in neuronal signals is a central topic for advanced neural signal processing. In particular, the existence of long-term correlations in neural signals recorded via multielectrode array (MEA) could provide interesting information about changes in interneuron communications. In this study we propose a new method for long-term correlation analysis of neuronal burst activity based on the periodogram alpha slope estimation of the MEA signal. We applied our method to recordings taken from cultured networks of dissociated rat cortical neurons. We show the effectiveness of the method in analyzing the activity changes as well as the temporal dynamics that take place during the development of such cultures. Results demonstrate that the alpha parameter is able to divide the network development in three well-defined stages, showing pronounced variations in the long-term correlation among bursts.

A Low-cost Multielectrode System for Data Acquisition Enabling Real-time Closed-loop Processing with Rapid Recovery from Stimulation Artifacts

Frontiers in Neuroengineering. 2009  |  Pubmed ID: 19668698

Commercially available data acquisition systems for multielectrode recording from freely moving animals are expensive, often rely on proprietary software, and do not provide detailed, modifiable circuit schematics. When used in conjunction with electrical stimulation, they are prone to prolonged, saturating stimulation artifacts that prevent the recording of short-latency evoked responses. Yet electrical stimulation is integral to many experimental designs, and critical for emerging brain-computer interfacing and neuroprosthetic applications. To address these issues, we developed an easy-to-use, modifiable, and inexpensive system for multielectrode neural recording and stimulation. Setup costs are less than US$10,000 for 64 channels, an order of magnitude lower than comparable commercial systems. Unlike commercial equipment, the system recovers rapidly from stimulation and allows short-latency action potentials (<1 ms post-stimulus) to be detected, facilitating closed-loop applications and exposing neural activity that would otherwise remain hidden. To illustrate this capability, evoked activity from microstimulation of the rodent hippocampus is presented. System noise levels are similar to existing platforms, and extracellular action potentials and local field potentials can be recorded simultaneously. The system is modular, in banks of 16 channels, and flexible in usage: while primarily designed for in vivo use, it can be combined with commercial preamplifiers to record from in vitro multielectrode arrays. The system's open-source control software, NeuroRighter, is implemented in C#, with an easy-to-use graphical interface. As C# functions in a managed code environment, which may impact performance, analysis was conducted to ensure comparable speed to C++ for this application. Hardware schematics, layout files, and software are freely available. Since maintaining wired headstage connections with freely moving animals is difficult, we describe a new method of electrode-headstage coupling using neodymium magnets.

Common Median Referencing for Improved Action Potential Detection with Multielectrode Arrays

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference. 2009  |  Pubmed ID: 19964004

Referencing is frequently used to remove common-mode signals from multielectrode data, in both freely moving animals and in vitro preparations. For action potential (AP) detection, referencing by subtracting the common average signal has been shown to increase AP signal-to-noise ratio (SNR). This method fails, however, when large transients occur on individual electrodes, as occurs during electrical stimulation or with large APs during spontaneous recordings. To deal with these cases, we propose using the common median as a reference. The common median has an improved SNR for AP detection (leading to more isolated single units and more detected APs per unit) and, unlike common average referencing, does not generate spurious APs when processing large single-electrode transients.

NeuroRighter: Closed-loop Multielectrode Stimulation and Recording for Freely Moving Animals and Cell Cultures

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference. 2009  |  Pubmed ID: 19964440

Closed-loop systems, where neural signals are used to control electrical stimulation, show promise as powerful experimental platforms and nuanced clinical therapies. To increase the availability, affordability, and usability of these devices, we have created a flexible open source system capable of simultaneous stimulation and recording from multiple electrodes. The system is versatile, functioning with both freely moving animals and in vitro preparations. Current- and voltage-controlled stimulation waveforms with 1 micros resolution can be delivered to any electrode of an array. Stimulation sequences can be preprogrammed or triggered by ongoing neural activity, such as action potentials (APs) or local field potentials (LFPs). Recovery from artifact is rapid, allowing the detection of APs within 1 ms of stimulus offset. Since the stimulation subsystem provides simultaneous current/voltage monitoring, electrode impedance spectra can be calculated in real time. A sample closed-loop experiment is presented wherein interictal spikes from epileptic animals are used to trigger microstimulation.

MDL Constrained 3-D Grayscale Skeletonization Algorithm for Automated Extraction of Dendrites and Spines from Fluorescence Confocal Images

Neuroinformatics. Dec, 2009  |  Pubmed ID: 20012509

This paper presents a method for improved automatic delineation of dendrites and spines from three-dimensional (3-D) images of neurons acquired by confocal or multi-photon fluorescence microscopy. The core advance presented here is a direct grayscale skeletonization algorithm that is constrained by a structural complexity penalty using the minimum description length (MDL) principle, and additional neuroanatomy-specific constraints. The 3-D skeleton is extracted directly from the grayscale image data, avoiding errors introduced by image binarization. The MDL method achieves a practical tradeoff between the complexity of the skeleton and its coverage of the fluorescence signal. Additional advances include the use of 3-D spline smoothing of dendrites to improve spine detection, and graph-theoretic algorithms to explore and extract the dendritic structure from the grayscale skeleton using an intensity-weighted minimum spanning tree (IW-MST) algorithm. This algorithm was evaluated on 30 datasets organized in 8 groups from multiple laboratories. Spines were detected with false negative rates less than 10% on most datasets (the average is 7.1%), and the average false positive rate was 11.8%. The software is available in open source form.

Improving Impedance of Implantable Microwire Multi-electrode Arrays by Ultrasonic Electroplating of Durable Platinum Black

Frontiers in Neuroengineering. 2010  |  Pubmed ID: 20485478

Implantable microelectrode arrays (MEAs) have been a boon for neural stimulation and recording experiments. Commercially available MEAs have high impedances, due to their low surface area and small tip diameters, which are suitable for recording single unit activity. Lowering the electrode impedance, but preserving the small diameter, would provide a number of advantages, including reduced stimulation voltages, reduced stimulation artifacts and improved signal-to-noise ratio. Impedance reductions can be achieved by electroplating the MEAs with platinum (Pt) black, which increases the surface area but has little effect on the physical extent of the electrodes. However, because of the low durability of Pt black plating, this method has not been popular for chronic use. Sonicoplating (i.e. electroplating under ultrasonic agitation) has been shown to improve the durability of Pt black on the base metals of macro-electrodes used for cyclic voltammetry. This method has not previously been characterized for MEAs used in chronic neural implants. We show here that sonicoplating can lower the impedances of microwire multi-electrode arrays (MMEA) by an order of magnitude or more (depending on the time and voltage of electroplating), with better durability compared to pulsed plating or traditional DC methods. We also show the improved stimulation and recording performance that can be achieved in an in vivo implantation study with the sonicoplated low-impedance MMEAs, compared to high-impedance unplated electrodes.

Closed-loop, Open-source Electrophysiology

Frontiers in Neuroscience. 2010  |  Pubmed ID: 20859448

Multiple extracellular microelectrodes (multi-electrode arrays, or MEAs) effectively record rapidly varying neural signals, and can also be used for electrical stimulation. Multi-electrode recording can serve as artificial output (efferents) from a neural system, while complex spatially and temporally targeted stimulation can serve as artificial input (afferents) to the neuronal network. Multi-unit or local field potential (LFP) recordings can not only be used to control real world artifacts, such as prostheses, computers or robots, but can also trigger or alter subsequent stimulation. Real-time feedback stimulation may serve to modulate or normalize aberrant neural activity, to induce plasticity, or to serve as artificial sensory input. Despite promising closed-loop applications, commercial electrophysiology systems do not yet take advantage of the bidirectional capabilities of multi-electrodes, especially for use in freely moving animals. We addressed this lack of tools for closing the loop with NeuroRighter, an open-source system including recording hardware, stimulation hardware, and control software with a graphical user interface. The integrated system is capable of multi-electrode recording and simultaneous patterned microstimulation (triggered by recordings) with minimal stimulation artifact. The potential applications of closed-loop systems as research tools and clinical treatments are broad; we provide one example where epileptic activity recorded by a multi-electrode probe is used to trigger targeted stimulation, via that probe, to freely moving rodents.

Closing the Loop Between Neurons and Neurotechnology

Frontiers in Neuroscience. 2010  |  Pubmed ID: 20859449

Spontaneous and Evoked High-frequency Oscillations in the Tetanus Toxin Model of Epilepsy

Epilepsia. Nov, 2010  |  Pubmed ID: 20946126

High-frequency oscillations (HFOs) are an emerging biomarker for epileptic tissue. Yet the mechanism by which HFOs are produced is unknown, and their rarity makes them difficult to study. Our objective was to examine the occurrence of HFOs in relation to action potentials (APs) and the effect of microstimulation in the tetanus toxin (TT) model of epilepsy, a nonlesional model with a short latency to spontaneous seizures.