The Argo: a high channel count recording system for neural recording in vivo.

OBJECTIVE: Decoding neural activity has been limited by the lack of tools available to record from large numbers of neurons across multiple cortical regions simultaneously with high temporal fidelity. To this end, we developed the Argo system to record cortical neural activity at high data rates. APPROACH: Here we demonstrate a massively parallel neural recording system based on platinum-iridium microwire electrode arrays bonded to a CMOS voltage amplifier array. The Argo system is the highest channel count in vivo neural recording system, supporting simultaneous recording from 65 536 channels, sampled at 32 kHz and 12-bit resolution. This system was designed for cortical recordings, compatible with both penetrating and surface microelectrodes. MAIN RESULTS: We validated this system through initial bench testing to determine specific gain and noise characteristics of bonded microwires, followed by in-vivo experiments in both rat and sheep cortex. We recorded spiking activity from 791 neurons in rats and surface local field potential activity from over 30 000 channels in sheep. SIGNIFICANCE: These are the largest channel count microwire-based recordings in both rat and sheep. While currently adapted for head-fixed recording, the microwire-CMOS architecture is well suited for clinical translation. Thus, this demonstration helps pave the way for a future high data rate intracortical implant.

Relationship between jerky and sinusoidal oscillations in cervical dystonia.

INTRODUCTION: Dystonia is often associated with repetitive jerky oscillations (i.e. dystonic tremor), while tremor is characterized by sinusoidal oscillations. We propose two competing predictions for dystonic tremor and sinusoidal tremor relationship. In any given patient, (1) the oscillation could be characterized as either sinusoidal or jerky based on the degree of distortion in the waveforms, (2) the oscillation consists of both sinusoidal and jerky waveforms mixed in a certain proportion that varies among individuals. We objectively test these predictions in patients with cervical dystonia. METHODS: We recorded head oscillations in 14 subjects with cervical dystonia using a high-resolution magnetic field search coil system. Distortion in the signal was used as a measure of jerkiness. A hierarchical clustering classified the oscillations based on distortion characteristics. RESULTS: Signal analysis in the frequency domain allowed identification of the components of the waveforms at frequencies other than the fundamental frequency. The distortion from the component at fundamental frequency was present in both low and high frequency range. Based on varying levels of distortions, i.e. jerkiness, the head oscillations were grouped into 4 clusters: one cluster with lowest distortion (sinusoidal waveforms), one cluster with highest distortion (jerky waveforms), and two intermediate clusters - one with distortion at low frequency and another with distortion at high frequency. The distribution of 4 clusters varied across subjects suggesting co-existence of sinusoidal and jerky waveforms. CONCLUSION: These results support the prediction that jerky and sinusoidal waveforms concur in cervical dystonia. Amount of concurrence varies amongst patients.

The shuttling scaffold model for prevention of yeast pheromone pathway misactivation.

The molecular scaffold in the yeast pheromone pathway, Ste5, shuttles continuously between the nucleus and the cytoplasm. Ste5 undergoes oligomerization reaction in the nucleus. Upon pheromone stimulation, the Ste5 dimer is rapidly exported out of the nucleus and recruited to the plasma membrane for pathway activation. This clever device on part of the yeast cell is thought to prevent pathway misactivation at high enough levels of Ste5 in the absence of pheromone. We have built a spatiotemporal model of signaling in this pathway to describe its regulation. Our present work underscores the importance of spatial modeling of cell signaling networks to understand their control and functioning.

Equilibrium analysis of allosteric interactions shows zero-order effects.

The binding of effector to an allosteric protein exhibits a non-Michaelis-Menten behavior, resulting in either ultrasensitive or subsensitive response. In the present work, a modular approach has been developed to determine the response curve for allosteric systems at higher concentration of allosteric enzyme than that of effector (zero-order sensitivity, as observed in enzyme cascades) by equilibrium analysis. The analysis shows that, in an allosteric system, the zero-order effect can make the response ultrasensitive or subsensitive with respect to the enzyme concentration. The response is dependent on the number of binding sites, cooperativity, and the total effector concentration. The framework was further applied to a well studied allosteric protein, the Escherichia coli aspartate transcarbamoylase. The predictions are found to be consistent with the reported experimental data.

Robust global sensitivity in multiple enzyme cascade system explains how the downstream cascade structure may remain unaffected by cross-talk.

A steady-state framework was applied to the ubiquitous tricyclic enzyme cascade structure, as seen in the mitogen-activated protein (MAP) kinase system, to analyze the effect of upstream kinase concentrations on final output response. The results suggest that signal amplification achieved by the cascade structure ensured that the modifying enzymes at various steps of the cascade were nearly saturated. Thus, there was no change in the response sensitivity with increasing upstream kinase concentration. Analysis was also extended to branching of a signaling pathway as an example of cross-talk. It was observed that the cascade structure confers a larger share of the signal transduction properties to its last kinase. This phenomenon in enzyme cascades may explain how the response of the terminal MAP kinase is unaffected by cross-talk of upstream kinases.