Consequences of converting graded to action potentials upon neural information coding and energy efficiency

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na+ and K+ channels, with generator potential and graded potential models lacking voltage-gated Na+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na+ channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a ‘footprint’ in the generator potential that obscures incoming signals. These three processes reduce information rates by ~50% in generator potentials, to ~3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation

The severity of pandemic H1N1 influenza in the United States, from April to July 2009: A Bayesian analysis

Background: Accurate measures of the severity of pandemic (H1N1) 2009 influenza (pH1N1) are needed to assess the likely impact of an anticipated resurgence in the autumn in the Northern Hemisphere. Severity has been difficult to measure because jurisdictions with large numbers of deaths and other severe outcomes have had too many cases to assess the total number with confidence. Also, detection of severe cases may be more likely, resulting in overestimation of the severity of an average case. We sought to estimate the probabilities that symptomatic infection would lead to hospitalization, ICU admission, and death by combining data from multiple sources. Methods and Findings: We used complementary data from two US cities: Milwaukee attempted to identify cases of medically attended infection whether or not they required hospitalization, while New York City focused on the identification of hospitalizations, intensive care admission or mechanical ventilation (hereafter, ICU), and deaths. New York data were used to estimate numerators for ICU and death, and two sources of data - medically attended cases in Milwaukee or self-reported influenza-like illness (ILI) in New York - were used to estimate ratios of symptomatic cases to hospitalizations. Combining these data with estimates of the fraction detected for each level of severity, we estimated the proportion of symptomatic patients who died (symptomatic case-fatality ratio, sCFR), required ICU (sCIR), and required hospitalization (sCHR), overall and by age category. Evidence, prior information, and associated uncertainty were analyzed in a Bayesian evidence synthesis framework. Using medically attended cases and estimates of the proportion of symptomatic cases medically attended, we estimated an sCFR of 0.048% (95% credible interval [CI] 0.026%-0.096%), sCIR of 0.239% (0.134%-0.458%), and sCHR of 1.44% (0.83%-2.64%). Using self-reported ILI, we obtained estimates approximately 7-96lower. sCFR and sCIR appear to be highest in persons aged 18 y and older, and lowest in children aged 5-17 y. sCHR appears to be lowest in persons aged 5-17; our data were too sparse to allow us to determine the group in which it was the highest. Conclusions: These estimates suggest that an autumn-winter pandemic wave of pH1N1 with comparable severity per case could lead to a number of deaths in the range from considerably below that associated with seasonal influenza to slightly higher, but with the greatest impact in children aged 0-4 and adults 18-64. These estimates of impact depend on assumptions about total incidence of infection and would be larger if incidence of symptomatic infection were higher or shifted toward adults, if viral virulence increased, or if suboptimal treatment resulted from stress on the health care system; numbers would decrease if the total proportion of the population symptomatically infected were lower than assumed.published_or_final_versio

Multiscale InSAR Time Series (MInTS) analysis of surface deformation

We present a new approach to extracting spatially and temporally continuous ground deformation fields from interferometric synthetic aperture radar (InSAR) data. We focus on unwrapped interferograms from a single viewing geometry, estimating ground deformation along the line-of-sight. Our approach is based on a wavelet decomposition in space and a general parametrization in time. We refer to this approach as MInTS (Multiscale InSAR Time Series). The wavelet decomposition efficiently deals with commonly seen spatial covariances in repeat-pass InSAR measurements, since the coefficients of the wavelets are essentially spatially uncorrelated. Our time-dependent parametrization is capable of capturing both recognized and unrecognized processes, and is not arbitrarily tied to the times of the SAR acquisitions. We estimate deformation in the wavelet-domain, using a cross-validated, regularized least squares inversion. We include a model-resolution-based regularization, in order to more heavily damp the model during periods of sparse SAR acquisitions, compared to during times of dense acquisitions. To illustrate the application of MInTS, we consider a catalog of 92 ERS and Envisat interferograms, spanning 16 years, in the Long Valley caldera, CA, region. MInTS analysis captures the ground deformation with high spatial density over the Long Valley region

Development of an Acute and Highly Pathogenic Nonhuman Primate Model of Nipah Virus Infection

Nipah virus (NiV) is an enigmatic emerging pathogen that causes severe and often fatal neurologic and/or respiratory disease in both animals and humans. Amongst people, case fatality rates range between 40 and 75 percent and there are no vaccines or treatments approved for human use. Guinea pigs, hamsters, cats, ferrets, pigs and most recently squirrel monkeys (New World monkey) have been evaluated as animal models of human NiV infection, and with the exception of the ferret, no model recapitulates all aspects of NiV-mediated disease seen in humans. To identify a more viable nonhuman primate (NHP) model, we examined the pathogenesis of NiV in African green monkeys (AGM). Exposure of eight monkeys to NiV produced a severe systemic infection in all eight animals with seven of the animals succumbing to infection. Viral RNA was detected in the plasma of challenged animals and occurred in two of three subjects as a peak between days 7 and 21, providing the first clear demonstration of plasma-associated viremia in NiV experimentally infected animals and suggested a progressive infection that seeded multiple organs simultaneously from the initial site of virus replication. Unlike the cat, hamster and squirrel monkey models of NiV infection, severe respiratory pathology, neurological disease and generalized vasculitis all manifested in NiV-infected AGMs, providing an accurate reflection of what is observed in NiV-infected humans. Our findings demonstrate the first consistent and highly pathogenic NHP model of NiV infection, providing a new and critical platform in the evaluation and licensure of either passive and active immunization or therapeutic strategies for human use

Effects of Active Conductance Distribution over Dendrites on the Synaptic Integration in an Identified Nonspiking Interneuron

The synaptic integration in individual central neuron is critically affected by how active conductances are distributed over dendrites. It has been well known that the dendrites of central neurons are richly endowed with voltage- and ligand-regulated ion conductances. Nonspiking interneurons (NSIs), almost exclusively characteristic to arthropod central nervous systems, do not generate action potentials and hence lack voltage-regulated sodium channels, yet having a variety of voltage-regulated potassium conductances on their dendritic membrane including the one similar to the delayed-rectifier type potassium conductance. It remains unknown, however, how the active conductances are distributed over dendrites and how the synaptic integration is affected by those conductances in NSIs and other invertebrate neurons where the cell body is not included in the signal pathway from input synapses to output sites. In the present study, we quantitatively investigated the functional significance of active conductance distribution pattern in the spatio-temporal spread of synaptic potentials over dendrites of an identified NSI in the crayfish central nervous system by computer simulation. We systematically changed the distribution pattern of active conductances in the neuron's multicompartment model and examined how the synaptic potential waveform was affected by each distribution pattern. It was revealed that specific patterns of nonuniform distribution of potassium conductances were consistent, while other patterns were not, with the waveform of compound synaptic potentials recorded physiologically in the major input-output pathway of the cell, suggesting that the possibility of nonuniform distribution of potassium conductances over the dendrite cannot be excluded as well as the possibility of uniform distribution. Local synaptic circuits involving input and output synapses on the same branch or on the same side were found to be potentially affected under the condition of nonuniform distribution while operation of the major input-output pathway from the soma side to the one on the opposite side remained the same under both conditions of uniform and nonuniform distribution of potassium conductances over the NSI dendrite

Information Transmission in Cercal Giant Interneurons Is Unaffected by Axonal Conduction Noise

What are the fundamental constraints on the precision and accuracy with which nervous systems can process information? One constraint must reflect the intrinsic “noisiness” of the mechanisms that transmit information between nerve cells. Most neurons transmit information through the probabilistic generation and propagation of spikes along axons, and recent modeling studies suggest that noise from spike propagation might pose a significant constraint on the rate at which information could be transmitted between neurons. However, the magnitude and functional significance of this noise source in actual cells remains poorly understood. We measured variability in conduction time along the axons of identified neurons in the cercal sensory system of the cricket Acheta domesticus, and used information theory to calculate the effects of this variability on sensory coding. We found that the variability in spike propagation speed is not large enough to constrain the accuracy of neural encoding in this system

COVID-19 as of January 12, 2021: What Have We Learned? How Can We Use What We Have Learned?

Program OPENING REMARKS: Edward C. Halperin, M.D., M.A.Chancellor and CEO, Professor of Radiation Oncology, Pediatrics and History, New York Medical College | Provost for Biomedical Affairs, Touro College and University System INTRODUCTION AND WELCOME: Alan Kadish, M.D.Cardiologist | President, Touro College and University System | President, New York Medical College TAKING CARE OF THOSE WHO TAKE CARE OF PATIENTS - SELF-CARE OF HEALTH CARE PROVIDERS DURING A PANDEMIC: BEING RESILIENT WHEN YOUR WORLD SEEMS TO BE CRASHING AROUND YOU by Stephen Ferrando, M.D.Har Esh Professor and Chairman, Department of Psychiatry and Behavioral Sciences, New York Medical College WHAT\u27S NEW IN COVID-19 THERAPY? SHALL WE SERVE ANTIBODY COCKTAILS TO COVID-19 PATIENTS? by Marisa A. Montecalvo, M.D.Medical Director, Health Services, Professor of Medicine, New York Medical College | Infectious Disease Specialist THE VACCINES: AN INTRODUCTION TO THE LOGISTICS OF LARGE-SCALE VACCINATION OF A POPULATION: IN VIEW OF THE RELATIVELY POOR COMPLIANCE OF ADULTS WITH RECOMMENDED VACCINATION PROGRAMS, DO WE HAVE ANY REASON TO THINK THAT COVID-19 WILL BE ANY DIFFERENT? by Robert Amler, M.D., MBA Dean, School of Health Sciences and Practice, Vice President for Government Affairs, New York Medical College | Former Regional Health Administrator, U.S. Department of Health and Human Services | Former Medical Epidemiologist, Centers for Disease Control and Prevention (CDC) ETHICAL DECISION-MAKING REGARDING VACCINES #1: THE POWER OF THE STATE TO REQUIRE PEOPLE TO BE VACCINATED - HOW DID THIS CONCEPT DEVELOP AND WHEN CAN IT BE INVOKED? by Lila Kagedan, M.Ed., MTSAssistant Professor of Medicine, Assistant Professor of Dentistry, Director of Biomedical Ethics, School of Medicine, New York Medical College ETHICAL DECISION-MAKING REGARDING VACCINES #2: WHO GOES FIRST? HOW DO WE ALLOCATE SCARCE HEALTH CARE RESOURCES? by Edward C. Halperin, M.D., M.A.Chancellor and CEO, New York Medical College | Provost for Biomedical Affairs, Touro College and University System FREQUENTLY ASKED QUESTIONS AND ANSWERS ABOUT THE COVID-19 VACCINES by Kathleen DiCaprio, Ph.D.Assistant Professor of Medical Microbiology and Immunology, Touro College of Osteopathic Medicine PREGNANCY OR POTENTIAL PREGNANCY AND THE COVID-19 VACCINE by Karen M. Murray, M.D.Associate Dean for Admissions, School of Medicine | Assistant Professor of Obstetrics & Gynecology, New York Medical College MODERATOR: by Edward C. Halperin, M.D., M.A.Chancellor and CEO, New York Medical College | Provost for Biomedical Affairs, Touro College and University System Q&A: Hosted by Alan Kadish, M.D.Cardiologist | President, Touro College and University System | President, New York Medical Colleg