Gytis Baranauskas

Sodium Currents Activate without a Hodgkin and Huxley-Type Delay in Central Mammalian Neurons

Hodgkin and Huxley established that sodium currents in the squid giant axons activate after a delay, which is explained by the model of a channel with three identical independent gates that all have to open before the channel can pass current (the HH model). It is assumed that this model can adequately describe the sodium current activation time course in all mammalian central neurons, although there is no experimental evidence to support such a conjecture. We performed high temporal resolution studies of sodium currents gating in three types of central neurons. The results show that, within the tested voltage range from -55 to -35 mV, in all of these neurons, the activation time course of the current could be fit, after a brief delay, with a monoexponential function. The duration of delay from the start of the voltage command to the start of the extrapolated monoexponential fit was much smaller than predicted by the HH model. For example, in prefrontal cortex pyramidal neurons, at -46 mV and 12°C, the observed average delay was 140 μs versus the 740 μs predicted by the two-gate HH model and the 1180 μs predicted by the three-gate HH model. These results can be explained by a model with two closed states and one open state. In this model, the transition between two closed states is approximately five times faster than the transition between the second closed state and the open state. This model captures all major properties of the sodium current activation. In addition, the proposed model reproduces the observed action potential shape more accurately than the traditional HH model.

Carbon nanotube composite coating of neural microelectrodes preferentially improves the multiunit signal-to-noise ratio

Extracellular metal microelectrodes are widely used to record single neuron activity in vivo. However, their signal-to-noise ratio (SNR) is often far from optimal due to their high impedance value. It has been recently reported that carbon nanotube (CNT) coatings may decrease microelectrode impedance, thus improving their performance. To tease out the different contributions to SNR of CNT-coated microelectrodes we carried out impedance and noise spectroscopy measurements of platinum/tungsten microelectrodes coated with a polypyrrole-CNT composite. Neuronal signals were recorded in vivo from rat cortex by employing tetrodes with two recording sites coated with polypyrrole-CNT and the remaining two left untreated. We found that polypyrrole-CNT coating significantly reduced the microelectrode impedance at all neuronal signal frequencies (from 1 to 10 000 Hz) and induced a significant improvement of the SNR, up to fourfold on average, in the 150-1500 Hz frequency range, largely corresponding to the multiunit frequency band. An equivalent circuit, previously proposed for porous conducting polymer coatings, reproduced the impedance spectra of our coated electrodes but could not explain the frequency dependence of SNR improvement following polypyrrole-CNT coating. This implies that neither the neural signal amplitude, as recorded by a CNT-coated metal microelectrode, nor noise can be fully described by the equivalent circuit model we used here and suggests that a more detailed approach may be needed to better understand the signal propagation at the electrode-solution interface. Finally, the presence of significant noise components that are neither thermal nor electronic makes it difficult to establish a direct relationship between the actual electrode noise and the impedance spectra.

Flufenamic acid decreases neuronal excitability through modulation of voltage-gated sodium channel gating

The electrophysiological phenotype of individual neurons critically depends on the biophysical properties of the voltage‐gated channels they express. Differences in sodium channel gating are instrumental in determining the different firing phenotypes of pyramidal cells and interneurons; moreover, sodium channel modulation represents an important mechanism of action for many widely used CNS drugs. Flufenamic acid (FFA) is a non‐steroidal anti‐inflammatory drug that has been long used as a blocker of calcium‐dependent cationic conductances. Here we show that FFA inhibits voltage‐gated sodium currents in hippocampal pyramidal neurons; this effect is dose‐dependent with IC50= 189 μm. We used whole‐cell and nucleated patch recordings to investigate the mechanisms of FFA modulation of TTX‐sensitive voltage‐gated sodium current. Our data show that flufenamic acid slows down the inactivation process of the sodium current, while shifting the inactivation curve ∼10 mV toward more hyperpolarized potentials. The recovery from inactivation is also affected in a voltage‐dependent way, resulting in slower recovery at hyperpolarized potentials. Recordings from acute slices demonstrate that FFA reduces repetitive‐ and abolishes burst‐firing in CA1 pyramidal neurons. A computational model based on our data was employed to better understand the mechanisms of FFA action. Simulation data support the idea that FFA acts via a novel mechanism by reducing the voltage dependence of the sodium channel fast inactivation rates. These effects of FFA suggest that it may be an effective anti‐epileptic drug.

What limits the performance of current invasive brain machine interfaces

The concept of a brain-machine interface (BMI) or a computer-brain interface is simple: BMI creates a communication pathway for a direct control by brain of an external device. In reality BMIs are very complex devices and only recently the increase in computing power of microprocessors enabled a boom in BMI research that continues almost unabated to this date, the high point being the insertion of electrode arrays into the brains of 5 human patients in a clinical trial run by Cyberkinetics with few other clinical tests still in progress. Meanwhile several EEG-based BMI devices (non-invasive BMIs) were launched commercially. Modern electronics and dry electrode technology made possible to drive the cost of some of these devices below few hundred dollars. However, the initial excitement of the direct control by brain waves of a computer or other equipment is dampened by large efforts required for learning, high error rates and slow response speed. All these problems are directly related to low information transfer rates typical for such EEG-based BMIs. In invasive BMIs employing multiple electrodes inserted into the brain one may expect much higher information transfer rates than in EEG-based BMIs because, in theory, each electrode provides an independent information channel. However, although invasive BMIs require more expensive equipment and have ethical problems related to the need to insert electrodes in the live brain, such financial and ethical costs are often not offset by a dramatic improvement in the information transfer rate. Thus the main topic of this review is why in invasive BMIs an apparently much larger information content obtained with multiple extracellular electrodes does not translate into much higher rates of information transfer? This paper explores possible answers to this question by concluding that more research on what movement parameters are encoded by neurons in motor cortex is needed before we can enjoy the next generation BMIs.

A Compact Multichannel System for Acquisition and Processing of Neural Signals

An increasing popularity of multichannel recordings from freely behaving animals and the need to develop a practical brain-machine interface has fuelled the development of miniature multichannel recording systems. Here we describe our prototype miniature 64-channel acquisition system that could be used for multichannel recordings in freely behaving monkeys or other large animals. The systems features include an high impedance input for neurophysiology electrodes, an integrated battery fed circuitry with a 64 low-noise multiplexed amplifiers array that permits the parallel recording of all channels, a 10-bit resolution ADC, an FPGA digital core for online processing and data transmission, a USB 2.0 link and a custom software for data visualization and whole system control.

A multi-channel low-power system-on-chip for single-unit recording and narrowband wireless transmission of neural signal

This paper reports a multi-channel neural recording system-on-chip (SoC) with digital data compression and wireless telemetry. The circuit consists of a 16 amplifiers, an analog time division multiplexer, an 8-bit SAR AD converter, a digital signal processor (DSP) and a wireless narrowband 400-MHz binary FSK transmitter. Even though only 16 amplifiers are present in our current die version, the whole system is designed to work with 64 channels demonstrating the feasibility of a digital processing and narrowband wireless transmission of 64 neural recording channels. A digital data compression, based on the detection of action potentials and storage of correspondent waveforms, allows the use of a 1.25-Mbit/s binary FSK wireless transmission. This moderate bit-rate and a low frequency deviation, Manchester-coded modulation are crucial for exploiting a narrowband wireless link and an efficient embeddable antenna. The chip is realized in a 0.35- εm CMOS process with a power consumption of 105 εW per channel (269 εW per channel with an extended transmission range of 4 m) and an area of 3.1 × 2.7 mm2. The transmitted signal is captured by a digital TV tuner and demodulated by a wideband phase-locked loop (PLL), and then sent to a PC via an FPGA module. The system has been tested for electrical specifications and its functionality verified in in-vivo neural recording experiments.

The Determinants of the Onset Dynamics of Action Potentials in a Computational Model

Action potentials (APs) in the soma of central neurons exhibit a sharp, step-like onset dynamics, which facilitates the encoding of weak but rapidly changing input signals into trains of action potentials. One possibility to explain the rapid AP onset dynamics is to assume cooperative activation of sodium channels. However, there is no direct evidence for cooperativity of voltage gated sodium channels in central mammalian neurons. The fact that APs in cortical neurons are initiated in the axon and backpropagate into the soma, prompted an alternative explanation of the sharp onset of somatic APs. In the invasion scenario, the AP onset is smooth at the initiation site in the axon initial segment, but the current invading the soma before somatic sodium channels are activated produces a sharp onset of somatic APs. Here we used multicompartment neuron models to identify ranges of active and passive cell properties that are necessary to reproduce the sharp AP onset in the invasion scenario. Results of our simulations show that AP initiation in the axon is a necessary but not a sufficient condition for the sharp onset of somatic AP: for a broad range of parameters, models could reproduce distal AP initiation and backpropagation but failed to quantitatively reproduce the onset dynamics of somatic APs observed in cortical neurons. To reproduce sharp onset of somatic APs, the invasion scenario required specific combinations of active and passive cell properties. The required properties of the axon initial segment differ significantly from the currently accepted and experimentally estimated values. We conclude that factors additional to the invasion contribute to the sharp AP onset and further experiments are needed to explain the AP onset dynamics in cortical neurons.

A low-power integrated circuit for analog spike detection and sorting in neural prosthesis systems

Since the proof of viability of prosthetic devices directly controlled by neurons, there is a huge increase in the interest on integrated multichannel recording systems to register neural signals with implanted chronic electrodes. One of the bottlenecks in such compact systems is the limited rate of data transmission by the wireless link, requiring some sort of data compression/reduction. We propose an analog low power integrated system for action potential (AP) detection and sorting that reduces the output data rate ~100 times. In this system, AP detection is performed by a double threshold method that reduces the probability of false detections while AP sorting is based on the measurement of peak and trough amplitudes and peak width. The circuit has been implemented in 0.35 - mum CMOS technology with power consumption of 70 muW per channel including the pre-amplifier. The system was tested with real recorded traces: compared to standard AP sorting techniques, the proposed simple AP sorter was able to correctly assign to single units over 90% of detected APs.

An integrated low-noise multichannel system for neural signals amplification

We present a 64-channels IC front-end for implantable systems using extracellular neural signals for rehabilitation purposes. Each channel of the ASIC consists of a high-pass filter with subthreshold feedback resistance and a line buffer. Channels are scanned through a time-division multiplexer followed by a variable gain amplifier and an output buffer. Power consumption is 500 muW per channel with plusmn1.65 V dual supply and an excellent noise performance of 2.9 muVrms (100 Hz- 10 kHz).

Can Optogenetic Tools Determine the Importance of Temporal Codes to Sensory Information Processing in the Brain

There is no doubt that optogenetic tools caused a paradigm shift in many fields of neuroscience. These tools enable rapid and reversible intervention with a specific neuronal circuit and then the impact on the remaining circuit and/or behavior can be studied. However, so far the ability of these optogenetic tools to interfere with neuronal signal transmission in the time scale of milliseconds has been used much less frequently although they may help to answer a fundamental question of neuroscience: how important temporal codes are to information processing in the brain. This perspective paper examines why optogenetic tools were used so little to perturb or imitate temporal codes. Although some technical limitations do exist, there is a clear need for a systems approach. More research about action potential pattern formation by interactions between several brain areas is necessary in order to exploit the full potential of optogenetic methods in probing temporal codes.