Microchip amplifier for in vitro, in vivo, and automated whole cell patch-clamp recording.

Patch clamping is a gold-standard electrophysiology technique that has the temporal resolution and signal-to-noise ratio capable of reporting single ion channel currents, as well as electrical activity of excitable single cells. Despite its usefulness and decades of development, the amplifiers required for patch clamping are expensive and bulky. This has limited the scalability and throughput of patch clamping for single-ion channel and single-cell analyses. In this work, we have developed a custom patch-clamp amplifier microchip that can be fabricated using standard commercial silicon processes capable of performing both voltage- and current-clamp measurements. A key innovation is the use of nonlinear feedback elements in the voltage-clamp amplifier circuit to convert measured currents into logarithmically encoded voltages, thereby eliminating the need for large high-valued resistors, a factor that has limited previous attempts at integration. Benchtop characterization of the chip shows low levels of current noise [1.1 pA root mean square (rms) over 5 kHz] during voltage-clamp measurements and low levels of voltage noise (8.2 µV rms over 10 kHz) during current-clamp measurements. We demonstrate the ability of the chip to perform both current- and voltage-clamp measurement in vitro in HEK293FT cells and cultured neurons. We also demonstrate its ability to perform in vivo recordings as part of a robotic patch-clamping system. The performance of the patch-clamp amplifier microchip compares favorably with much larger commercial instrumentation, enabling benchtop commoditization, miniaturization, and scalable patch-clamp instrumentation.

Statistics of the electrosensory input in the freely swimming weakly electric fish Apteronotus leptorhynchus.

The neural computations underlying sensory-guided behaviors can best be understood in view of the sensory stimuli to be processed under natural conditions. This input is often actively shaped by the movements of the animal and its sensory receptors. Little is known about natural sensory scene statistics taking into account the concomitant movement of sensory receptors in freely moving animals. South American weakly electric fish use a self-generated quasi-sinusoidal electric field for electrolocation and electrocommunication. Thousands of cutaneous electroreceptors detect changes in the transdermal potential (TDP) as the fish interact with conspecifics and the environment. Despite substantial knowledge about the circuitry and physiology of the electrosensory system, the statistical properties of the electrosensory input evoked by natural swimming movements have never been measured directly. Using underwater wireless telemetry, we recorded the TDP of Apteronotus leptorhynchus as they swam freely by themselves and during interaction with a conspecific. Swimming movements caused low-frequency TDP amplitude modulations (AMs). Interacting with a conspecific caused additional AMs around the difference frequency of their electric fields, with the amplitude of the AMs (envelope) varying at low frequencies due to mutual movements. Both AMs and envelopes showed a power-law relationship with frequency, indicating spectral scale invariance. Combining a computational model of the electric field with video tracking of movements, we show that specific swimming patterns cause characteristic spatiotemporal sensory input correlations that contain information that may be used by the brain to guide behavior.

Design and implementation of multipattern generators in analog VLSI.

In recent years, computational biologists have shown through simulation that small neural networks with fixed connectivity are capable of producing multiple output rhythms in response to transient inputs. It is believed that such networks may play a key role in certain biological behaviors such as dynamic gait control. In this paper, we present a novel method for designing continuous-time recurrent neural networks (CTRNNs) that contain multiple embedded limit cycles, and we show that it is possible to switch the networks between these embedded limit cycles with simple transient inputs. We also describe the design and testing of a fully integrated four-neuron CTRNN chip that is used to implement the neural network pattern generators. We provide two example multipattern generators and show that the measured waveforms from the chip agree well with numerical simulations.

Micropower circuits for bidirectional wireless telemetry in neural recording applications.

State-of-the art neural recording systems require electronics allowing for transcutaneous, bidirectional data transfer. As these circuits will be implanted near the brain, they must be small and low power. We have developed micropower integrated circuits for recovering clock and data signals over a transcutaneous power link. The data recovery circuit produces a digital data signal from an ac power waveform that has been amplitude modulated. We have also developed an FM transmitter with the lowest power dissipation reported for biosignal telemetry. The FM transmitter consists of a low-noise biopotential amplifier and a voltage controlled oscillator used to transmit amplified neural signals at a frequency near 433 MHz. All circuits were fabricated in a standard 0.5-microm CMOS VLSI process. The resulting chip is powered through a wireless inductive link. The power consumption of the clock and data recovery circuits is measured to be 129 microW; the power consumption of the transmitter is measured to be 465 microW when using an external surface mount inductor. Using a parasitic antenna less than 2 mm long, a received power level was measured to be -59.73 dBm at a distance of one meter.

A battery-free multichannel digital neural/EMG telemetry system for flying insects.

This paper presents a digital neural/EMG telemetry system small enough and lightweight enough to permit recording from insects in flight. It has a measured flight package mass of only 38 mg. This system includes a single-chip telemetry integrated circuit (IC) employing RF power harvesting for battery-free operation, with communication via modulated backscatter in the UHF (902-928 MHz) band. An on-chip 11-bit ADC digitizes 10 neural channels with a sampling rate of 26.1 kSps and 4 EMG channels at 1.63 kSps, and telemeters this data wirelessly to a base station. The companion base station transceiver includes an RF transmitter of +36 dBm (4 W) output power to wirelessly power the telemetry IC, and a digital receiver with a sensitivity of -70 dBm for 10⁻5 BER at 5.0 Mbps to receive the data stream from the telemetry IC. The telemetry chip was fabricated in a commercial 0.35 µ m 4M1P (4 metal, 1 poly) CMOS process. The die measures 2.36 × 1.88 mm, is 250 µm thick, and is wire bonded into a flex circuit assembly measuring 4.6 × 6.8 mm.

Multiplexing of motor information in the discharge of a collision detecting neuron during escape behaviors.

Locusts possess an identified neuron, the descending contralateral movement detector (DCMD), conveying visual information about impending collision from the brain to thoracic motor centers. We built a telemetry system to simultaneously record, in freely behaving animals, the activity of the DCMD and of motoneurons involved in jump execution. Cocontraction of antagonistic leg muscles, a required preparatory phase, was triggered after the DCMD firing rate crossed a threshold. Thereafter, the number of DCMD spikes predicted precisely motoneuron activity and jump occurrence. Additionally, the time of DCMD peak firing rate predicted that of jump. Ablation experiments suggest that the DCMD, together with a nearly identical ipsilateral descending neuron, is responsible for the timely execution of the escape. Thus, three distinct features that are multiplexed in a single neuron's sensory response to impending collision-firing rate threshold, peak firing time, and spike count-probably control three distinct motor aspects of escape behaviors.

Recording sensory and motor information from peripheral nerves with Utah Slanted Electrode Arrays.

Recording and stimulation via high-count penetrating microelectrode arrays implanted in peripheral nerves may help restore precise motor and sensory function after nervous system damage or disease. Although previous work has demonstrated safety and relatively successful stimulation for long-term implants of 100-electrode Utah Slanted Electrode Arrays (USEAs) in feline sciatic nerve [1], two major remaining challenges were 1) to maintain viable recordings of nerve action potentials long-term, and 2) to overcome contamination of unit recordings by myoelectric (EMG) activity in awake, moving animals. In conjunction with improvements to USEAs themselves, we have redesigned several aspects of our USEA containment and connector systems. Although further increases in unit yield and long-term stability remain desirable, here we report considerable progress toward meeting both of these goals: We have successfully recorded unit activity from USEAs implanted intrafascicularly in sciatic nerve for periods up to 4 months (the terminal experimental time point), and we have developed a containment system that effectively eliminates or substantially reduces EMG contamination of unit recordings in the moving animal. In addition, we used a 100-channel wireless recording integrated circuit attached to implanted USEAs to transmit broadband or spike-threshold data from nerve. Neural data thusly obtained during imposed limb movements were decoded blindly to drive a virtual prosthetic limb in real time. These results support the possibility of using USEAs in peripheral nerves to provide motor control and cutaneous or proprioceptive sensory feedback in individuals after limb loss or spinal cord injury.

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.

Influence of system integration and packaging on its inductive power link for an integrated wireless neural interface.

In an integrated wireless neural interface based on the Utah electrode array, the implanted electronics are supplied with power through inductive coupling between two coils. This inductive link is affected by conductive and dielectric materials and media surrounding the implant coil. In this study, the influences of the integration of an implant coil on a silicon-based IC and electrode array, thin-film Parylene-C encapsulation, and physiological medium surrounding the coil were investigated systematically and quantitatively by empirical measurements. A few embodiments of implant coils with different geometrical parameters were made with a diameter of approximately 5.5 mm by winding fine wire with a diameter of approximately 50 mum. The parasitic influences affecting the inductive link were empirically investigated by measuring the electrical properties of coils in different configurations and in different media. The distance of power transmission between the transmit and receive coils was measured when the receive coil was in air and immersed in phosphate buffered saline solution to simulate an implanted physiological environment. The results from this study quantitatively address the influences of factors such as device integration, encapsulation, and implantation on its inductive power link, and suggest how to maximize the efficiency in power transmission for such neural interface devices powered inductively.

Wireless neural recording with single low-power integrated circuit.

We present benchtop and in vivo experimental results from an integrated circuit designed for wireless implantable neural recording applications. The chip, which was fabricated in a commercially available 0.6- mum 2P3M BiCMOS process, contains 100 amplifiers, a 10-bit analog-to-digital converter (ADC), 100 threshold-based spike detectors, and a 902-928 MHz frequency-shift-keying (FSK) transmitter. Neural signals from a selected amplifier are sampled by the ADC at 15.7 kSps and telemetered over the FSK wireless data link. Power, clock, and command signals are sent to the chip wirelessly over a 2.765-MHz inductive (coil-to-coil) link. The chip is capable of operating with only two off-chip components: a power/command receiving coil and a 100-nF capacitor.

HermesC: low-power wireless neural recording system for freely moving primates.

Neural prosthetic systems have the potential to restore lost functionality to amputees or patients suffering from neurological injury or disease. Current systems have primarily been designed for immobile patients, such as tetraplegics functioning in a rather static, carefully tailored environment. However, an active patient such as amputee in a normal dynamic, everyday environment may be quite different in terms of the neural control of movement. In order to study motor control in a more unconstrained natural setting, we seek to develop an animal model of freely moving humans. Therefore, we have developed and tested HermesC-INI3, a system for recording and wirelessly transmitting neural data from electrode arrays implanted in rhesus macaques who are freely moving. This system is based on the integrated neural interface (INI3) microchip which amplifies, digitizes, and transmits neural data across a approximately 900 MHz wireless channel. The wireless transmission has a range of approximately 4 m in free space. All together this device consumes 15.8 mA and 63.2 mW. On a single 2 A-hr battery pack, this device runs contiguously for approximately six days. The smaller size and power consumption of the custom IC allows for a smaller package (51 x 38 x 38 mm (3)) than previous primate systems. The HermesC-INI3 system was used to record and telemeter one channel of broadband neural data at 15.7 kSps from a monkey performing routine daily activities in the home cage.

Local field potential measurement with low-power analog integrated circuit.

Local field potentials (LFPs) in the brain are an important source of information for basic research and clinical (i.e., neuroprosthetic) applications. The energy contained in certain bands of LFPs in the 10-100 Hz range has been shown to correlate with specific arm movement parameters in nonhuman primates. In the near future, implantable devices will need to transmit neural information from hundreds of microelectrodes, and transcutaneous data transfer will become a significant bottleneck. Here we present a low-power, fully-integrated circuit that performs on-site data reduction by isolating LFPs and measuring their signal energy. The resulting analog VLSI circuit consumes 586 microm x 79 microm of silicon area and dissipates only 5 nanowatts of power. We show that the chip performs similarly to state-of-the-art signal processing algorithms.

Sensorimotor control of navigation in arthropod and artificial systems.

Arthropods exhibit highly efficient solutions to sensorimotor navigation problems. They thus provide a source of inspiration and ideas to robotics researchers. At the same time, attempting to re-engineer these mechanisms in robot hardware and software provides useful insights into how the natural systems might work. This paper reviews three examples of arthropod sensorimotor control systems that have been implemented and tested on robots. First we discuss visual control mechanisms of flies, such as the optomotor reflex and collision avoidance, that have been replicated in analog VLSI (very large scale integration) hardware and used to produce corrective behavior in robot vehicles. Then, we present a robot model of auditory localization in the cricket; and discuss integration of this behavior with the optomotor behavior previously described. Finally we present a model of olfactory search in the moth, which makes use of several sensory cues, and has also been tested using robot hardware. We discuss some of the similarities and differences of the solutions obtained.

Validation of adaptive threshold spike detector for neural recording.

We compare the performance of algorithms for automatic spike detection in neural recording applications. Each algorithm sets a threshold based on an estimate of the background noise level. The adaptive spike detection algorithm is suitable for implementation in analog VLSI; results from a proof-of-concept chip using neural data are presented. We also present simulation results of algorithm performance on neural data and compare it to other methods of threshold level adjustment based on the root-mean-square (rms) voltage measured over a finite window. We show that the adaptive spike detection algorithm measures the background noise level accurately despite the presence of large-amplitude action potentials and multi-unit hash. Simulation results enable us to optimize the algorithm parameters, leading to an improved spike detector circuit that is currently being developed.