Summary Understanding the detailed dynamics of neuronal networks will require the simultaneous measurement of spike trains from hundreds of neurons (or more). Currently, approaches to extracting spike times and labels from raw data are time consuming, lack standardization and involve manual intervention, making it difficult to maintain data provenance and assess the quality of scientific results. Here, we describe an automated clustering approach and associated software package that addresses these problems and provides novel cluster quality metrics. We show that our approach has accuracy comparable to or exceeding that achieved using manual or semi-manual techniques with desktop CPU runtimes faster than acquisition time for up to hundreds of electrodes. Moreover, a single choice of parameters in the algorithm is effective for a variety of electrode geometries and across multiple brain regions. This algorithm has the potential to enable reproducible and automated spike sorting of larger scale recordings than is currently possible.

Highlights d Firing across hippocampal neurons can regularly ''take turns'' (cycle) every 125 ms d Cycle firing is seen at single-cell, cell-pair, and population levels d Cycle firing encodes hypothetical experience, including multiple possible futures

How does an animal know where it is when it stops moving? Hippocampal place cells fire at discrete locations as subjects traverse space, thereby providing an explicit neural code for current location during locomotion. In contrast, during awake immobility, the hippocampus is thought to be dominated by neural firing representing past and possible future experience. The question of whether and how the hippocampus constructs a representation of current location in the absence of locomotion has stood unresolved. Here we report that a distinct population of hippocampal neurons, located in the CA2 subregion, signals current location during immobility, and furthermore does so in association with a previously unidentified hippocampus-wide network pattern. In addition, signaling of location persists into brief periods of desynchronization prevalent in slow-wave sleep. The hippocampus thus generates a distinct representation of current location during immobility, pointing to mnemonic processing specific to experience occurring in the absence of locomotion.

Summary The brain is a massive neuronal network, organized into anatomically distributed sub-circuits, with functionally relevant activity occurring at timescales ranging from milliseconds to months. Current methods to monitor neural activity, however, lack the necessary conjunction of anatomical spatial coverage, temporal resolution, and long-term stability to measure this distributed activity. Here we introduce a large-scale, multi-site, extracellular recording platform that integrates polymer electrodes with a modular stacking headstage design supporting up to 1024 recording channels in freely behaving rats. This system can support months-long recordings from hundreds of well-isolated units across multiple brain regions. Moreover, these recordings are stable enough to track large numbers of single units for over a week. This platform enables large-scale electrophysiological interrogation of the fast dynamics and long-timescale evolution of anatomically distributed circuits, and thereby provides a new tool for understanding brain activity.

Unplanned extubation is a major complication of translaryngeal intubation, but its impact on mortality, duration of mechanical ventilation (MV), length of intensive care unit (ICU) and hospital stay, and need for ongoing hospital care has not been adequately defined. We performed a case-control study in a tertiary-care medical ICU, comparing 75 patients with unplanned extubation and 150 controls matched for Acute Physiology and Chronic Health Evaluation II score, presence of comorbid conditions, age, indication for MV, and sex. Forty-two (56%) patients required reintubation after unplanned extubation (74% immediately, 86% within 12 h). Thirty-three (44%) unplanned extubations occurred during weaning trials, and 30% of these patients needed reintubation (failed unplanned extubation). In contrast, 76% of patients with unplanned extubation occurring during ventilatory support required reintubation. Although mortality was similar to that of controls (failed unplanned extubation 40%, versus control 31%, p > 0.2), patients with failed unplanned extubation had a significantly longer duration of MV (19 versus 11 d, p < 0.01), longer stay in the ICU (21 versus 14 d, p < 0.05), and longer hospital stay (30 versus 21 d, p < 0.01), and survivors were more likely to require chronic care (64% versus 24%, p < 0.001). Successfully tolerated unplanned extubation was associated with a reduction in time from beginning of weaning to extubation (0.9 versus 2.0 d, p = 0.06), but with no difference in overall duration of MV, mortality, discharge location, ICU, or hospital stay as compared with these measures for controls. We conclude that unplanned extubation is not associated with increased mortality when compared with that of matched controls, although it does result in prolonged MV, longer ICU and hospital stay, and increased need for chronic care. These effects are due exclusively to patients who fail to tolerate unplanned extubation. Although successfully tolerated unplanned extubation decreased the duration of weaning trials, it had no other measurable beneficial impact on outcome.