Subthreshold dynamics of a single neuron from a Hamiltonian perspective

We use Hamilton's equations of classical mechanics to investigate the behavior of a cortical neuron on the approach to an action potential. We use a two-component dynamic model of a single neuron, due to Wilson, with added noise inputs. We derive a Lagrangian for the system, from which we construct Hamilton's equations. The conjugate momenta are found to be linear combinations of the noise input to the system. We use this approach to consider theoretically and computationally the most likely manner in which such a modeled neuron approaches a firing event. We find that the firing of a neuron is a result of a drop in inhibition, due to a temporary increase in negative bias of the mean noise input to the inhibitory control equation. Moreover, we demonstrate through theory and simulation that, on average, the bias in the noise increases in an exponential manner on the approach to an action potential. In the Hamiltonian description, an action potential can therefore be considered a result of the exponential growth of the conjugate momenta variables pulling the system away from its equilibrium state, into a nonlinear regime

Noise addendum experimental clean combustor program, phase 1

The development of advanced CTOL aircraft engines with reduced exhaust emissions is discussed. Combustor noise information provided during the basic emissions program and used to advantage in securing reduced levels of combustion noise is included. Results are presented of internal pressure transducer measurements made during the scheduled emissions test program on ten configurations involving variations of three basic combustor designs

Space debris measurement program at Phillips Laboratory

Ground-based optical sensing was identified as a technique for measuring space debris complementary to radar in the critical debris size range of 1 to 10 cm. The Phillips Laboratory is building a staring optical sensor for space debris measurement and considering search and track optical measurement at additional sites. The staring sensor is implemented in collaboration with Wright Laboratory using the 2.5 m telescope at Wright Patterson AFB, Dayton, Ohio. The search and track sensor is designed to detect and track orbital debris in tasked orbits. A progress report and a discussion of sensor performance and search and track strategies will be given

Phase transitions in single neurons and neural populations: Critical slowing, anesthesia, and sleep cycles

The firing of an action potential by a biological neuron represents a dramatic transition from small-scale linear stochastics (subthreshold voltage fluctuations) to gross-scale nonlinear dynamics (birth of a 1-ms voltage spike). In populations of neurons we see similar, but slower, switch-like there-and-back transitions between low-firing background states and high-firing activated states. These state transitions are controlled by varying levels of input current (single neuron), varying amounts of GABAergic drug (anesthesia), or varying concentrations of neuromodulators and neurotransmitters (natural sleep), and all occur within a milieu of unrelenting biological noise. By tracking the altering responsiveness of the excitable membrane to noisy stimulus, we can infer how close the neuronal system (single unit or entire population) is to switching threshold. We can quantify this “nearness to switching” in terms of the altering eigenvalue structure: the dominant eigenvalue approaches zero, leading to a growth in correlated, low-frequency power, with exaggerated responsiveness to small perturbations, the responses becoming larger and slower as the neural population approaches its critical point–-this is critical slowing. In this chapter we discuss phase-transition predictions for both single-neuron and neural-population models, comparing theory with laboratory and clinical measurement

Cortical patterns and gamma genesis are modulated by reversal potentials and gap-junction diffusion

In this chapter we describe a continuum model for the cortex that includes both axon-to-dendrite chemical synapses and direct neuron-to-neuron gap-junction diffusive synapses. The effectiveness of chemical synapses is determined by the voltage of the receiving dendrite V relative to its Nernst reversal potential Vrev. Here we explore two alternative strategies for incorporating dendritic reversal potentials, and uncover surprising differences in their stability properties and model dynamics. In the “slow-soma” variant, the (Vrev - V) weighting is applied after the input flux has been integrated at the dendrite, while for “fast-soma”, the weighting is applied directly to the input flux, prior to dendritic integration. For the slow-soma case, we find that–-provided the inhibitory diffusion (via gap-junctions) is sufficiently strong–-the cortex generates stationary Turing patterns of cortical activity. In contrast, the fast-soma destabilizes in favor of standing-wave spatial structures that oscillate at low-gamma frequency ( 30-Hz); these spatial patterns broaden and weaken as diffusive coupling increases, and disappear altogether at moderate levels of diffusion. We speculate that the slow- and fast-soma models might correspond respectively to the idling and active modes of the cortex, with slow-soma patterns providing the default background state, and emergence of gamma oscillations in the fast-soma case signaling the transition into the cognitive state

Instabilities of the cortex during natural sleep

The electrical signals generated by the human cortex during sleep have been widely studied over the last 50 years. The electroencephalogram (EEG) observed during natural sleep exhibits structures with frequencies from 0.5 Hz to over 50 Hz and complicated waveforms such as spindles and K-complexes. Understanding has been enhanced by comprehensive intra-cellular measurements from the cortex and thalamus such as those performed by Steriade et al [1] and Sanchez-Vives and McCormick [2]. Models of the cerebal cortex have been developed in order to explain many of the features observed. These can be classified in terms of individual neuron models or collective models. Since we wish to compare predictions with gross features of the human EEG, we choose a collective model, where we average over a population of neurons in macrocolumns. A number of models of this form have been developed recently; that developed at Waikato draws from a number of different sources to describe the temporal and spatial dynamics of the system

A continuum model for the dynamics of the phase transition from slow-wave sleep to REM sleep

Previous studies have shown that activated cortical states (awake and rapid eye-movement (REM) sleep), are associated with increased cholinergic input into the cerebral cortex. However, the mechanisms that underlie the detailed dynamics of the cortical transition from slow-wave to REM sleep have not been quantitatively modeled. How does the sequence of abrupt changes in the cortical dynamics (as detected in the electrocorticogram) result from the more gradual change in subcortical cholinergic input? We compare the output from a continuum model of cortical neuronal dynamics with experimentally-derived rat electrocorticogram data. The output from the computer model was consistent with experimental observations. In slow-wave sleep, 0.5–2-Hz oscillations arise from the cortex jumping between “up” and “down” states on the stationary-state manifold. As cholinergic input increases, the upper state undergoes a bifurcation to an 8-Hz oscillation. The coexistence of both oscillations is similar to that found in the intermediate stage of sleep of the rat. Further cholinergic input moves the trajectory to a point where the lower part of the manifold in not available, and thus the slow oscillation abruptly ceases (REM sleep). The model provides a natural basis to explain neuromodulator-induced changes in cortical activity, and indicates that a cortical phase change, rather than a brainstem “flip-flop”, may describe the transition from slow-wave sleep to REM

Attitudes of surgeons to the use of postoperative markers of the systemic inflammatory response following elective surgery

Background: Cancer is responsible for 7.6 million deaths worldwide and surgery is the primary modality of a curative outcome. Postoperative care is of considerable importance and it is against this backdrop that a questionnaire based study assessing the attitudes of surgeons to monitoring postoperative systemic inflammation was carried out. Method: A Web based survey including 10 questions on the “attitudes of surgeons to the use of postoperative markers of the systemic inflammatory response following elective surgery” was distributed via email. Two cohorts were approached to participate in the survey. Cohort 1 consisted of 1092 surgeons on the “Association of Coloproctology of Great Britain and Ireland (ACPGBI)” membership list. Cohort 2 consisted of 270 surgeons who had published in this field in the past as identified by two recent reviews. A reminder email was sent out 21 days after the initial email in both cases and the survey was closed after 42 days in both cases. Result: In total 29 surgeons (2.7%) from cohort 1 and 40 surgeons (14.8%) from cohort 2 responded to the survey. The majority of responders were from Europe (77%), were colorectal specialists (64%) and were consultants (84%) and worked in teaching hospitals (54%) and used minimally invasive techniques (87%). The majority of responders measured CRP routinely in the post-operative period (85%) and used CRP to guide their decision making (91%) and believed that CRP monitoring should be incorporated into postoperative guidelines (81%). Conclusion: Although there was a limited response the majority of surgeons surveyed measure the systemic inflammatory response following elective surgery and use CRP measurements together with clinical findings to guide postoperative care. The present results provide a baseline against which future surveys can be compared

Customer premise service study for 30/20 GHz satellite system

Satellite systems in which the space segment operates in the 30/20 GHz frequency band are defined and compared as to their potential for providing various types of communications services to customer premises and the economic and technical feasibility of doing so. Technical tasks performed include: market postulation, definition of the ground segment, definition of the space segment, definition of the integrated satellite system, service costs for satellite systems, sensitivity analysis, and critical technology. Based on an analysis of market data, a sufficiently large market for services is projected so as to make the system economically viable. A large market, and hence a high capacity satellite system, is found to be necessary to minimize service costs, i.e., economy of scale is found to hold. The wide bandwidth expected to be available in the 30/20 GHz band, along with frequency reuse which further increases the effective system bandwidth, makes possible the high capacity system. Extensive ground networking is required in most systems to both connect users into the system and to interconnect Earth stations to provide spatial diversity. Earth station spatial diversity is found to be a cost effective means of compensating the large fading encountered in the 30/20 GHz operating band