Heuristic Spike Sorting Tuner (HSST), a framework to determine optimal parameter selection for a generic spike sorting algorithm

Extracellular microelectrodes frequently record neural activity from more than one neuron in the vicinity of the electrode. The process of labeling each recorded spike waveform with the identity of its source neuron is called spike sorting and is often approached from an abstracted statistical perspective. However, these approaches do not consider neurophysiological realities and may ignore important features that could improve the accuracy of these methods. Further, standard algorithms typically require selection of at least one free parameter, which can have significant effects on the quality of the output. We describe a Heuristic Spike Sorting Tuner (HSST) that determines the optimal choice of the free parameters for a given spike sorting algorithm based on the neurophysiological qualification of unit isolation and signal discrimination. A set of heuristic metrics are used to score the output of a spike sorting algorithm over a range of free parameters resulting in optimal sorting quality. We demonstrate that these metrics can be used to tune parameters in several spike sorting algorithms. The HSST algorithm shows robustness to variations in signal to noise ratio, number and relative size of units per channel. Moreover, the HSST algorithm is computationally efficient, operates unsupervised, and is parallelizable for batch processing

Heuristic Spike Sorting Tuner (HSST), a framework to determine optimal parameter selection for a generic spike sorting algorithm

Extracellular microelectrodes frequently record neural activity from more than one neuron in the vicinity of the electrode. The process of labeling each recorded spike waveform with the identity of its source neuron is called spike sorting and is often approached from an abstracted statistical perspective. However, these approaches do not consider neurophysiological realities and may ignore important features that could improve the accuracy of these methods. Further, standard algorithms typically require selection of at least one free parameter, which can have significant effects on the quality of the output. We describe a Heuristic Spike Sorting Tuner (HSST) that determines the optimal choice of the free parameters for a given spike sorting algorithm based on the neurophysiological qualification of unit isolation and signal discrimination. A set of heuristic metrics are used to score the output of a spike sorting algorithm over a range of free parameters resulting in optimal sorting quality. We demonstrate that these metrics can be used to tune parameters in several spike sorting algorithms. The HSST algorithm shows robustness to variations in signal to noise ratio, number and relative size of units per channel. Moreover, the HSST algorithm is computationally efficient, operates unsupervised, and is parallelizable for batch processing

rtMEG: A Real-Time Software Interface for Magnetoencephalography

To date, the majority of studies using magnetoencephalography (MEG) rely on off-line analysis of the spatiotemporal properties of brain activity. Real-time MEG feedback could potentially benefit multiple areas of basic and clinical research: brain-machine interfaces, neurofeedback rehabilitation of stroke and spinal cord injury, and new adaptive paradigm designs, among others. We have developed a software interface to stream MEG signals in real time from the 306-channel Elekta Neuromag MEG system to an external workstation. The signals can be accessed with a minimal delay (≤45 ms) when data are sampled at 1000 Hz, which is sufficient for most real-time studies. We also show here that real-time source imaging is possible by demonstrating real-time monitoring and feedback of alpha-band power fluctuations over parieto-occipital and frontal areas. The interface is made available to the academic community as an open-source resource

A study of the social and physical environment in catering kitchens and the role of the chef in promoting positive health and safety behaviour

This is the account of a mixed method study of chefs and their kitchens in order to identify the nature of their workplace and how this affects their ability to manage health and safety in the kitchen. It included extended periods of observation, monitoring of physical parameters, analysis of records of reported accidents, and a series of reflexive interviews. The findings were integrated and then fed back in a smaller number of second interviews in order to test whether the findings fitted in with the chefs' understanding of their world. Major factors identified included survival in a market environment, the status of the chef (and the kitchen) within organisations, marked autocracy of chefs, and an increasing tempo building up to service time with commensurate heat, noise, and activity. In particular during the crescendo, a threshold shift in risk tolerance was identified. The factors, their interplay, and their implications for health and safety in the catering kitchen are discussed

Quasiparticle-like peaks, kinks, and electron-phonon coupling at the (π\pi,0) regions in the CMR oxide La2−2x_{2-2x}Sr1+2x_{1+2x}Mn2_{2}O7_{7}

Using Angle-Resolved Photoemission (ARPES), we present the first observation of sharp quasiparticle-like peaks in a CMR manganite. We focus on the ($\pi$,0) regions of k-space and study their electronic scattering rates and dispersion kinks, uncovering the critical energy scales, momentum scales, and strengths of the interactions that renormalize the electrons. To identify these bosons we measured phonon dispersions in the energy range of the kink by inelastic neutron scattering (INS), finding a good match in both energy and momentum to the oxygen bond-stretching phonons

Evolution of brown carbon in wildfire plumes

Particulate brown carbon (BrC) in the atmosphere absorbs light at subvisible wavelengths and has poorly constrained but potentially large climate forcing impacts. BrC from biomass burning has virtually unknown lifecycle and atmospheric stability. Here, BrC emitted from intense wildfires was measured in plumes transported over 2 days from two main fires, during the 2013 NASA SEAC4RS mission. Concurrent measurements of organic aerosol (OA) and black carbon (BC) mass concentration, BC coating thickness, absorption Ångström exponent, and OA oxidation state reveal that the initial BrC emitted from the fires was largely unstable. Using back trajectories to estimate the transport time indicates that BrC aerosol light absorption decayed in the plumes with a half-life of 9 to 15 h, measured over day and night. Although most BrC was lost within a day, possibly through chemical loss and/or evaporation, the remaining persistent fraction likely determines the background BrC levels most relevant for climate forcing

Anarcho-Environmentalists: Ascetics of Late Modernity

This article explores experiences of environmental activism from the viewpoint of members of a radical environment group. It is based on data collected during eight months of participant observation and through semistructured interviews with ten core members and two ex-members. Working on personal feelings, attitudes, beliefs, and behaviors (self-work) was central to the strategy for social change employed by this group. Drawing on Weber's sociology of religion, this article explores the way the high expectation the activists had of themselves matched Weber's typification of the rationally active ascetic. It is argued that asceticism is an enduring element of Western culture that takes different forms in response to historical conditions. In this case, we see a form of secular asceticism that responds to the conditions of late modernity

Nitrogen sources and net growth efficiency of zooplankton in three Amazon River plume food webs

The plasticity of nitrogen specific net growth efficiency (NGE) in marine mesozooplankton is currently unresolved, with discordant lines of evidence suggesting that NGE is constant, or that it varies with nitrogen source, food availability, and food quality in marine ecosystems. Specifically, the fate of nitrogen from nitrogen fixation is poorly known. We use 15N : 14N ratios in plankton in combination with hydrological data, nutrient profiles, and nitrogen fixation rate measurements to investigate the relationship between new nitrogen sources and the nitrogen specific NGE in three plankton communities along the outer Amazon River plume. The NGE of small (200–500 μm) mesozooplankton was estimated from the δ 15N differences between particulate nitrogen and zooplankton using an open system Rayleigh fractionation model. The transfer efficiency of nitrogen among larger (\u3e 500 μm) mesozooplankton was estimated from the change in δ 15N as a function of zooplankton size. The Amazon River was not a significant source of bioavailable nitrogen anywhere in our study region, and subsurface nitrate was the primary new nitrogen source for the outer shelf community, which was dominated by diatoms. N2 fixation was the principal new nitrogen source at sites of high diatom diazotroph association abundance and at oceanic sites dominated by Trichodesmium spp. and Synechococcus spp. Although we found clear spatial differences in food quantity, food quality, and diazotroph inputs into mesozooplankton, our data show no significant differences in mesozooplankton nitrogen transfer efficiency and NGE (for latter, mean ± SD: 59 ± 10%) among sites

Craniux: A LabVIEW-Based Modular Software Framework for Brain-Machine Interface Research

This paper presents “Craniux,” an open-access, open-source software framework for brain-machine interface (BMI) research. Developed in LabVIEW, a high-level graphical programming environment, Craniux offers both out-of-the-box functionality and a modular BMI software framework that is easily extendable. Specifically, it allows researchers to take advantage of multiple features inherent to the LabVIEW environment for on-the-fly data visualization, parallel processing, multithreading, and data saving. This paper introduces the basic features and system architecture of Craniux and describes the validation of the system under real-time BMI operation using simulated and real electrocorticographic (ECoG) signals. Our results indicate that Craniux is able to operate consistently in real time, enabling a seamless work flow to achieve brain control of cursor movement. The Craniux software framework is made available to the scientific research community to provide a LabVIEW-based BMI software platform for future BMI research and development