Long-Term Potentiation: One Kind or Many?

Do neurobiologists aim to discover natural kinds? I address this question in this chapter via a critical analysis of classification practices operative across the 43-year history of research on long-term potentiation (LTP). I argue that this 43-year history supports the idea that the structure of scientific practice surrounding LTP research has remained an obstacle to the discovery of natural kinds

Examination of the role of cGMP in long-term potentiation in the CA1 region of the hippocampus

The mechanisms underlying the generation of NMDA receptor-dependent LTP in the CA1 region of the hippocampus continue to receive a great deal of attention because of the postulated importance of LTP as a synaptic mechanism for learning and memory. It is well accepted that the initial induction of LTP occurs in the postsynaptic cell, but the site of expression remains controversial. One prominent hypothesis is that LTP involves the release of one or more retrograde messengers that act on the presynaptic terminal to enhance transmitter release. Recently, evidence has been presented that retrograde messengers function to activate presynaptic guanylyl cyclase and that the resulting rise in presynaptic cGMP levels, when accompanied by presynaptic activity, is responsible for generating an early component of LTP. We have tested this hypothesis by examining whether synaptic strength is increased by coupling tetanic stimulation with application of a membrane-permeable analog of cGMP. The experiments were done in the presence of an NMDA receptor antagonist to block postsynaptic induction mechanisms. Under a variety of experimental conditions, this manipulation failed to generate LTP, suggesting that an increase in cGMP levels accompanied by presynaptic activity is not sufficient to generate LTP in the CA1 region of the hippocampus

Correlation entropy of synaptic input-output dynamics

The responses of synapses in the neocortex show highly stochastic and nonlinear behavior. The microscopic dynamics underlying this behavior, and its computational consequences during natural patterns of synaptic input, are not explained by conventional macroscopic models of deterministic ensemble mean dynamics. Here, we introduce the correlation entropy of the synaptic input-output map as a measure of synaptic reliability which explicitly includes the microscopic dynamics. Applying this to experimental data, we find that cortical synapses show a low-dimensional chaos driven by the natural input pattern.Comment: 7 pages, 6 Figures (7 figure files

Health System Characteristics and Rates of Readmission After Acute Myocardial Infarction in the United States

Background: Interventions to reduce early readmissions have focused on patient characteristics and the importance of early follow‐up; however, less is known about the characteristics of health systems, including quality, capacity, and intensity, and their influence on readmission rates in the United States. Therefore, we examined the association of hospital patterns of medical care with rates of 30‐day readmission. Methods and Results: Medicare beneficiaries hospitalized for an AMI (n=188 611) between 2008 and 2009 in 1088 hospitals in the United States were included in our cohort. We tested the association between hospital patterns of medical care quality (discharge planning care quality), capacity (hospital size measured as the number of beds, hospital‐level Medicare all medical admission rates, supply of primary care physicians and cardiologists), and intensity (measures of care during the last 6 months of life) on CMS risk‐adjusted rates of 30‐day readmission using Poisson multilevel mixed‐effects models adjusting for patient‐ and hospital‐level covariates. There were 38 350 readmissions at 30‐days (20.3%) AMI discharges. Controlling for patient characteristics, measures of hospital care associated with higher rates of readmission included higher hospital‐level rates for all medical admissions, per capita primary care physicians and cardiologists, and last 6 months of life care intensity measures including increased number of hospital days, number of ICU days, number of physician visits, and 10 or more different physicians seen during the last 6 months of life. Better discharge quality and larger hospitals were associated with lower rates of readmission. Conclusions: In addition to quality of care, high 30‐day readmission rates are associated with hospital‐level measures of capacity and intensity. Efforts to reduce readmission rates may need to address these broader patterns of medical care

Cardiology providers’ recommendations for treatments and use of patient decision aids for multivessel coronary artery disease

Background: Rates of recommending percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG) vary across clinicians. Whether clinicians agree on preferred treatment options for multivessel coronary artery disease patients has not been well studied. Methods and results: We distributed a survey to 104 clinicians from the Northern New England Cardiovascular Study Group through email and at a regional meeting with 88 (84.6%) responses. The survey described three clinical vignettes of multivessel coronary artery disease patients. For each patient vignette participants selected appropriate treatment options and whether they would use a patient decision aid. The likelihood of choosing PCI only or PCI/CABG over CABG only was modeled using a multinomial regression. Across all vignettes, participants selected CABG only as an appropriate treatment option 24.2% of the time, PCI only 25.4% of the time, and both CABG or PCI as appropriate treatment options 50.4% of the time. Surgeons were less likely to choose PCI over CABG (RR 0.14, 95% CI 0.03, 0.59) or both treatments over CABG only (RR 0.10, 95% CI 0.03, 0.34) relative to cardiologists. Overall, 65% of participants responded they would use a patient decision aid with each vignette. Conclusions: There is a lack of consensus on the appropriate treatment options across cardiologists and surgeons for patients with multivessel coronary artery disease. Treatment choice is influenced by both patient characteristics and clinician specialty

How Gibbs distributions may naturally arise from synaptic adaptation mechanisms. A model-based argumentation

This paper addresses two questions in the context of neuronal networks dynamics, using methods from dynamical systems theory and statistical physics: (i) How to characterize the statistical properties of sequences of action potentials ("spike trains") produced by neuronal networks ? and; (ii) what are the effects of synaptic plasticity on these statistics ? We introduce a framework in which spike trains are associated to a coding of membrane potential trajectories, and actually, constitute a symbolic coding in important explicit examples (the so-called gIF models). On this basis, we use the thermodynamic formalism from ergodic theory to show how Gibbs distributions are natural probability measures to describe the statistics of spike trains, given the empirical averages of prescribed quantities. As a second result, we show that Gibbs distributions naturally arise when considering "slow" synaptic plasticity rules where the characteristic time for synapse adaptation is quite longer than the characteristic time for neurons dynamics.Comment: 39 pages, 3 figure

Flies put the buzz back into long-term-potentiation

Two new papers show that an atypical protein kinase C may mediate the maintenance of long-term potentiation in the mouse hippocampus and of associative memory in Drosophila

Spatial representation of temporal information through spike timing dependent plasticity

We suggest a mechanism based on spike time dependent plasticity (STDP) of synapses to store, retrieve and predict temporal sequences. The mechanism is demonstrated in a model system of simplified integrate-and-fire type neurons densely connected by STDP synapses. All synapses are modified according to the so-called normal STDP rule observed in various real biological synapses. After conditioning through repeated input of a limited number of of temporal sequences the system is able to complete the temporal sequence upon receiving the input of a fraction of them. This is an example of effective unsupervised learning in an biologically realistic system. We investigate the dependence of learning success on entrainment time, system size and presence of noise. Possible applications include learning of motor sequences, recognition and prediction of temporal sensory information in the visual as well as the auditory system and late processing in the olfactory system of insects.Comment: 13 pages, 14 figures, completely revised and augmented versio

A Dynamic Model of Interactions of Ca^(2+), Calmodulin, and Catalytic Subunits of Ca^(2+)/Calmodulin-Dependent Protein Kinase II

During the acquisition of memories, influx of Ca^(2+) into the postsynaptic spine through the pores of activated N-methyl-D-aspartate-type glutamate receptors triggers processes that change the strength of excitatory synapses. The pattern of Ca^(2+) influx during the first few seconds of activity is interpreted within the Ca^(2+)-dependent signaling network such that synaptic strength is eventually either potentiated or depressed. Many of the critical signaling enzymes that control synaptic plasticity, including Ca^(2+)/calmodulin-dependent protein kinase II (CaMKII), are regulated by calmodulin, a small protein that can bind up to 4 Ca^(2+) ions. As a first step toward clarifying how the Ca^(2+)-signaling network decides between potentiation or depression, we have created a kinetic model of the interactions of Ca^(2+), calmodulin, and CaMKII that represents our best understanding of the dynamics of these interactions under conditions that resemble those in a postsynaptic spine. We constrained parameters of the model from data in the literature, or from our own measurements, and then predicted time courses of activation and autophosphorylation of CaMKII under a variety of conditions. Simulations showed that species of calmodulin with fewer than four bound Ca^(2+) play a significant role in activation of CaMKII in the physiological regime, supporting the notion that processing ofCa^(2+) signals in a spine involves competition among target enzymes for binding to unsaturated species of CaM in an environment in which the concentration of Ca^(2+) is fluctuating rapidly. Indeed, we showed that dependence of activation on the frequency of Ca^(2+) transients arises from the kinetics of interaction of fluctuating Ca^(2+) with calmodulin/CaMKII complexes. We used parameter sensitivity analysis to identify which parameters will be most beneficial to measure more carefully to improve the accuracy of predictions. This model provides a quantitative base from which to build more complex dynamic models of postsynaptic signal transduction during learning

A Mathematical model for Astrocytes mediated LTP at Single Hippocampal Synapses

Many contemporary studies have shown that astrocytes play a significant role in modulating both short and long form of synaptic plasticity. There are very few experimental models which elucidate the role of astrocyte over Long-term Potentiation (LTP). Recently, Perea & Araque (2007) demonstrated a role of astrocytes in induction of LTP at single hippocampal synapses. They suggested a purely pre-synaptic basis for induction of this N-methyl-D- Aspartate (NMDA) Receptor-independent LTP. Also, the mechanisms underlying this pre-synaptic induction were not investigated. Here, in this article, we propose a mathematical model for astrocyte modulated LTP which successfully emulates the experimental findings of Perea & Araque (2007). Our study suggests the role of retrograde messengers, possibly Nitric Oxide (NO), for this pre-synaptically modulated LTP.Comment: 51 pages, 15 figures, Journal of Computational Neuroscience (to appear