A Neural Network of Adaptively Timed Reinforcement Learning and Hippocampal Dynamics

A neural model is described of how adaptively timed reinforcement learning occurs. The adaptive timing circuit is suggested to exist in the hippocampus, and to involve convergence of dentate granule cells on CA3 pyramidal cells, and NMDA receptors. This circuit forms part of a model neural system for the coordinated control of recognition learning, reinforcement learning, and motor learning, whose properties clarify how an animal can learn to acquire a delayed reward. Behavioral and neural data are summarized in support of each processing stage of the system. The relevant anatomical sites are in thalamus, neocortex, hippocampus, hypothalamus, amygdala, and cerebellum. Cerebellar influences on motor learning are distinguished from hippocampal influences on adaptive timing of reinforcement learning. The model simulates how damage to the hippocampal formation disrupts adaptive timing, eliminates attentional blocking, and causes symptoms of medial temporal amnesia. It suggests how normal acquisition of subcortical emotional conditioning can occur after cortical ablation, even though extinction of emotional conditioning is retarded by cortical ablation. The model simulates how increasing the duration of an unconditioned stimulus increases the amplitude of emotional conditioning, but does not change adaptive timing; and how an increase in the intensity of a conditioned stimulus "speeds up the clock", but an increase in the intensity of an unconditioned stimulus does not. Computer simulations of the model fit parametric conditioning data, including a Weber law property and an inverted U property. Both primary and secondary adaptively timed conditioning are simulated, as are data concerning conditioning using multiple interstimulus intervals (ISIs), gradually or abruptly changing ISis, partial reinforcement, and multiple stimuli that lead to time-averaging of responses. Neurobiologically testable predictions are made to facilitate further tests of the model.

The Synthesis of Arbitrary Stable Dynamics in Non-linear Neural Networks II: Feedback and Universality

We wish to construct a realization theory of stable neural networks and use this theory to model the variety of stable dynamics apparent in natural data. Such a theory should have numerous applications to constructing specific artificial neural networks with desired dynamical behavior. The networks used in this theory should have well understood dynamics yet be as diverse as possible to capture natural diversity. In this article, I describe a parameterized family of higher order, gradient-like neural networks which have known arbitrary equilibria with unstable manifolds of known specified dimension. Moreover, any system with hyperbolic dynamics is conjugate to one of these systems in a neighborhood of the equilibrium points. Prior work on how to synthesize attractors using dynamical systems theory, optimization, or direct parametric. fits to known stable systems, is either non-constructive, lacks generality, or has unspecified attracting equilibria. More specifically, We construct a parameterized family of gradient-like neural networks with a simple feedback rule which will generate equilibrium points with a set of unstable manifolds of specified dimension. Strict Lyapunov functions and nested periodic orbits are obtained for these systems and used as a method of synthesis to generate a large family of systems with the same local dynamics. This work is applied to show how one can interpolate finite sets of data, on nested periodic orbits.

Creation of a complex butterfly attractor using a novel Lorenz-type system

A novel Lorenz-type system of nonlinear differential equations is proposed. Unlike the original Lorenz system, where the chaotic dynamics remain confined to the positive half-space with respect to the Z state variable due to a limiting threshold effect, the proposed system enables bipolar swing of this state variable. In addition, the classical set of parameters (a, b, c) controlling the behavior of the Lorenz system are reduced to a single parameter, namely a. Two possible modes of operation are admitted by the system; switching between these two modes results in the creation of a complex butterfly chaotic attractor. Numerical simulations and results from an experimental setup are presented

Use of semiconductor optical amplifiers in signal processing applications

We describe a 42.6 Gbit/s all-optical pattern recognition system which uses semiconductor optical amplifiers (SOAs). A circuit with three SOA-based logic gates is used to identify the presence of specific port numbers in an optical packet header.

On classical and other methods of discriminant analysis and estimation of log-odds

For two multinormal populations with equal covariance matrices the likelihood ratio discriminant function, an alternative allocation rule to the sample linear discriminant function when n1 ≠ n2 ,is studied analytically. With the assumption of a known covariance matrix its distribution is derived and the expectation of its actual and apparent error rates evaluated and compared with those of the sample linear discriminant function. This comparison indicates that the likelihood ratio allocation rule is robust to unequal sample sizes. The quadratic discriminant function is studied, its distribution reviewed and evaluation of its probabilities of misclassification discussed. For known covariance matrices the distribution of the sample quadratic discriminant function is derived. When the known covariance matrices are proportional exact expressions for the expectation of its actual and apparent error rates are obtained and evaluated. The effectiveness of the sample linear discriminant function for this case is also considered. Estimation of true log-odds for two multinormal populations with equal or unequal covariance matrices is studied. The estimative, Bayesian predictive and a kernel method are compared by evaluating their biases and mean square errors. Some algebraic expressions for these quantities are derived. With equal covariance matrices the predictive method is preferable. Where it derives this superiority is investigated by considering its performance for various levels of fixed true log-odds. It is also shown that the predictive method is sensitive to n1 ≠ n2. For unequal but proportional covariance matrices the unbiased estimative method is preferred. Product Normal kernel density estimates are used to give a kernel estimator of true log-odds. The effect of correlation in the variables with product kernels is considered. With equal covariance matrices the kernel and parametric estimators are compared by simulation. For moderately correlated variables and large dimension sizes the product kernel method is a good estimator of true log-odds.

Properties and applications of injection locking in 1.55 μm quantum-dash mode-locked semiconductor lasers

Mode-locked semiconductor lasers are compact pulsed sources with ultra-narrow pulse widths and high repetition-rates. In order to use these sources in real applications, their performance needs to be optimised in several aspects, usually by external control. We experimentally investigate the behaviour of recently-developed quantum-dash mode-locked lasers (QDMLLs) emitting at 1.55 μm under external optical injection. Single-section and two-section lasers with different repetition frequencies and active-region structures are studied. Particularly, we are interested in a regime which the laser remains mode-locked and the individual modes are simultaneously phase-locked to the external laser. Injection-locked self-mode-locked lasers demonstrate tunable microwave generation at first or second harmonic of the free-running repetition frequency with sub-MHz RF linewidth. For two-section mode-locked lasers, using dual-mode optical injection (injection of two coherent CW lines), narrowing the RF linewidth close to that of the electrical source, narrowing the optical linewidths and reduction in the time-bandwidth product is achieved. Under optimised bias conditions of the slave laser, a repetition frequency tuning ratio >2% is achieved, a record for a monolithic semiconductor mode-locked laser. In addition, we demonstrate a novel all-optical stabilisation technique for mode-locked semiconductor lasers by combination of CW optical injection and optical feedback to simultaneously improve the time-bandwidth product and timing-jitter of the laser. This scheme does not need an RF source and no optical to electrical conversion is required and thus is ideal for photonic integration. Finally, an application of injection-locked mode-locked lasers is introduced in a multichannel phase-sensitive amplifier (PSA). We show that with dual-mode injection-locking, simultaneous phase-synchronisation of two channels to local pump sources is realised through one injection-locking stage. An experimental proof of concept is demonstrated for two 10 Gbps phase-encoded (DPSK) channels showing more than 7 dB phase-sensitive gain and less than 1 dB penalty of the receiver sensitivity.

All-optical signal processing using semiconductor optical amplifiers for next generation optical networks

This thesis details an experimental and simulation investigation of some novel all-optical signal processing techniques for future optical communication networks. These all-optical techniques include modulation format conversion, phase discrimination and clock recovery. The methods detailed in this thesis use the nonlinearities associated with semiconductor optical amplifiers (SOA) to manipulate signals in the optical domain. Chapter 1 provides an introduction into the work detailed in this thesis, discusses the increased demand for capacity in today’s optical fibre networks and finally explains why all-optical signal processing may be of interest for future optical networks. Chapter 2 discusses the relevant background information required to fully understand the all-optical techniques demonstrated in this thesis. Chapter 3 details some pump-probe measurement techniques used to calculate the gain and phase recovery times of a long SOA. A remarkably fast gain recovery is observed and the wavelength dependent nature of this recovery is investigated. Chapter 4 discusses the experimental demonstration of an all-optical modulation conversion technique which can convert on-off- keyed data into either duobinary or alternative mark inversion. In Chapter 5 a novel phase sensitive frequency conversion scheme capable of extracting the two orthogonal components of a quadrature phase modulated signal into two separate frequencies is demonstrated. Chapter 6 investigates a novel all-optical clock recovery technique for phase modulated optical orthogonal frequency division multiplexing superchannels and finally Chapter 7 provides a brief conclusion.

Multi-parametric metabolic assessment of cells under stress conditions

Glycolysis, glutaminolysis, the Krebs cycle and oxidative phosphorylation are the main metabolic pathways. Exposing cells to key metabolic substrates (glucose, glutamine and pyruvate); investigation of the contribution of substrates in stress conditions such as uncoupling and hypoxia was conducted. Glycolysis, O2 consumption, O2 and ATP levels and hypoxia inducible factor (HIF) signalling in PC12 cells were investigated. Upon uncoupling with FCCP mitochondria were depolarised similarly in all cases, but a strong increase in respiration was only seen in the cells fed on glutamine with either glucose or pyruvate. Inhibition of glutaminolysis reversed the glutamine dependant effect. Differential regulation of the respiratory response to FCCP by metabolic environment suggests mitochondrial uncoupling has a potential for substrate-specific inhibition of cell function. At reduced O2 availability (4 % and 0 % O2), cell bioenergetics and local oxygenation varied depending on the substrate composition. Results indicate that both supply and utilisation of key metabolic substrates can affect the pattern of HIF-1/2α accumulation by differentially regulating iO2¬, ATP levels and Akt/Erk/AMPK pathways. Inhibition of key metabolic pathways can modulate HIF regulatory pathways, metabolic responses and survival of cancer cells in hypoxia. Hypoxia leads to transcriptional activation, by HIF, of pyruvate dehydrogenase (PDH) kinase which phosphorylates and inhibits PDH, a mitochondrial enzyme that converts pyruvate into acetyl-CoA. The levels of PDH (total and phosphorylated), PDH kinase and HIF-1α were analysed in HCT116 and HCT116 SCO2-/- (deficient in complex IV of the respiratory chain) grown under 20.9 % and 3 % O2. Data indicate that regulation of PDH can occur in a manner independent of the HIF-1/PDH kinase 1 axis, mitochondrial respiration and the demand for acetyl-CoA. Collectively these results can be applied to many diseases; reduced nutrient supply and O2 during ischemia/stroke, hypoglycaemia in diabetes mellitus and cancer associated changes in uncoupling protein expression levels.

Typical delay determines waiting time on periodic-food schedules: Static and dynamic tests.

Pigeons and other animals soon learn to wait (pause) after food delivery on periodic-food schedules before resuming the food-rewarded response. Under most conditions the steady-state duration of the average waiting time, t, is a linear function of the typical interfood interval. We describe three experiments designed to explore the limits of this process. In all experiments, t was associated with one key color and the subsequent food delay, T, with another. In the first experiment, we compared the relation between t (waiting time) and T (food delay) under two conditions: when T was held constant, and when T was an inverse function of t. The pigeons could maximize the rate of food delivery under the first condition by setting t to a consistently short value; optimal behavior under the second condition required a linear relation with unit slope between t and T. Despite this difference in optimal policy, the pigeons in both cases showed the same linear relation, with slope less than one, between t and T. This result was confirmed in a second parametric experiment that added a third condition, in which T + t was held constant. Linear waiting appears to be an obligatory rule for pigeons. In a third experiment we arranged for a multiplicative relation between t and T (positive feedback), and produced either very short or very long waiting times as predicted by a quasi-dynamic model in which waiting time is strongly determined by the just-preceding food delay.

The short and long of it: neural correlates of temporal-order memory for autobiographical events.

Previous functional neuroimaging studies of temporal-order memory have investigated memory for laboratory stimuli that are causally unrelated and poor in sensory detail. In contrast, the present functional magnetic resonance imaging (fMRI) study investigated temporal-order memory for autobiographical events that were causally interconnected and rich in sensory detail. Participants took photographs at many campus locations over a period of several hours, and the following day they were scanned while making temporal-order judgments to pairs of photographs from different locations. By manipulating the temporal lag between the two locations in each trial, we compared the neural correlates associated with reconstruction processes, which we hypothesized depended on recollection and contribute mainly to short lags, and distance processes, which we hypothesized to depend on familiarity and contribute mainly to longer lags. Consistent with our hypotheses, parametric fMRI analyses linked shorter lags to activations in regions previously associated with recollection (left prefrontal, parahippocampal, precuneus, and visual cortices), and longer lags with regions previously associated with familiarity (right prefrontal cortex). The hemispheric asymmetry in prefrontal cortex activity fits very well with evidence and theories regarding the contributions of the left versus right prefrontal cortex to memory (recollection vs. familiarity processes) and cognition (systematic vs. heuristic processes). In sum, using a novel photo-paradigm, this study provided the first evidence regarding the neural correlates of temporal-order for autobiographical events.

Cell cycle Start is coupled to entry into the yeast metabolic cycle across diverse strains and growth rates.

Cells have evolved oscillators with different frequencies to coordinate periodic processes. Here we studied the interaction of two oscillators, the cell division cycle (CDC) and the yeast metabolic cycle (YMC), in budding yeast. Previous work suggested that the CDC and YMC interact to separate high oxygen consumption (HOC) from DNA replication to prevent genetic damage. To test this hypothesis, we grew diverse strains in chemostat and measured DNA replication and oxygen consumption with high temporal resolution at different growth rates. Our data showed that HOC is not strictly separated from DNA replication; rather, cell cycle Start is coupled with the initiation of HOC and catabolism of storage carbohydrates. The logic of this YMC-CDC coupling may be to ensure that DNA replication and cell division occur only when sufficient cellular energy reserves have accumulated. Our results also uncovered a quantitative relationship between CDC period and YMC period across different strains. More generally, our approach shows how studies in genetically diverse strains efficiently identify robust phenotypes and steer the experimentalist away from strain-specific idiosyncrasies.

Cell cycle start is coupled to entry into the yeast metabolic cycle across diverse strains and growth rates

© 2016 Burnetti et al. Cells have evolved oscillators with different frequencies to coordinate periodic processes. Here we studied the interaction of two oscillators, the cell division cycle (CDC) and the yeast metabolic cycle (YMC), in budding yeast. Previous work suggested that the CDC and YMC interact to separate high oxygen consumption (HOC) from DNA replication to prevent genetic damage. To test this hypothesis, we grew diverse strains in chemostat and measured DNA replication and oxygen consumption with high temporal resolution at different growth rates. Our data showed that HOC is not strictly separated from DNA replication; rather, cell cycle Start is coupled with the initiation of HOC and catabolism of storage carbohydrates. The logic of this YMC-CDC coupling may be to ensure that DNA replication and cell division occur only when sufficient cellular energy reserves have accumulated. Our results also uncovered a quantitative relationship between CDC period and YMC period across different strains. More generally, our approach shows how studies in genetically diverse strains efficiently identify robust phenotypes and steer the experimentalist away from strain-specific idiosyncrasies.

Supercontinuum generation in air-silica microstructured fibers with nanosecond and femtosecond pulse pumping

We study the generation of supercontinua in air-silica microstructured fibers by both nanosecond and femtosecond pulse excitation. In the nanosecond experiments, a 300-nm broadband visible continuum was generated in a 1.8-m length of fiber pumped at 532 nm by 0.8-ns pulses from a frequency-doubled passively Q-switched Nd:YAG microchip laser. At this wavelength, the dominant mode excited under the conditions of continuum generation is the LP 11 mode, and, with nanosecond pumping, self-phase modulation is negligible and the continuum generation is dominated by the interplay of Raman and parametric effects. The spectral extent of the continuum is well explained by calculations of the parametric gain curves for four-wave mixing about the zero-dispersion wavelength of the LP11 mode. In the femtosecond experiments, an 800-nm broad-band visible and near-infrared continuum has been generated in a 1-m length of fiber pumped at 780 nm by 100-fs pulses from a Kerr-lens model-locked Ti:sapphire laser. At this wavelength, excitation and continuum generation occur in the LP01 mode, and the spectral width of the observed continuum is shown to be consistent with the phase-matching bandwidth for parametric processes calculated for this fiber mode. In addition, numerical simulations based on an extended nonlinear Schrödinger equation were used to model supercontinuum generation in the femtosecond regime, with the simulation results reproducing the major features of the experimentally observed spectrum. © 2002 Optical Society of America.

No-flow underfill flip chip assembly–an experimental and modeling analysis

In the flip-chip assembly process, no-flow underfill materials have a particular advantage over traditional underfill: the application and curing of the former can be undertaken before and during the reflow process. This advantage can be exploited to increase the flip-chip manufacturing throughput. However, adopting a no-flow underfill process may introduce reliability issues such as underfill entrapment, delamination at interfaces between underfill and other materials, and lower solder joint fatigue life. This paper presents an analysis on the assembly and the reliability of flip-chips with no-flow underfill. The methodology adopted in the work is a combination of experimental and computer-modeling methods. Two types of no-flow underfill materials have been used for the flip chips. The samples have been inspected with X-ray and scanning acoustic microscope inspection systems to find voids and other defects. Eleven samples for each type of underfill material have been subjected to thermal shock test and the number of cycles to failure for these flip chips have been found. In the computer modeling part of the work, a comprehensive parametric study has provided details on the relationship between the material properties and reliability, and on how underfill entrapment may affect the thermal–mechanical fatigue life of flip chips with no-flow underfill.

Semi-Parametric Analysis of Extreme Forest Fires

Forest fires can cause extensive damage to natural resources and properties. They can also destroy wildlife habitat, affect the forest ecosystem and threaten human lives. In this paper incidences of extreme wildland fires are modelled by a point process model which incorporates time-trend. A model based on a generalised Pareto distribution is used to model data on acres of wildland burnt by extreme fire in the US since 1825. A semi-parametric smoothing approach, which is very useful in exploratory analysis of changes in extremes, is illustrated with the maximum likelihood method to estimate model parameters.