Quantitative determination of the timing of otolith ring formation from marginal increments in four marine teleost species from northwestern Australia

The sectioned otoliths of four fish species from a tropical demersal trawl fishery in Western Australia revealed a series of alternating trans-lucent and opaque zones in reflected light. The translucent zones, referred to as growth rings, were counted to determine fish ages. The width of the opaque zone on the periphery of the otolith section as a proportion of the width of the previous opaque zone (index of completion) was used to determine the periodicity of growth-ring formation. This article describes a method for modeling changes in the index of ring completion over time, from which a parameter for the most probable time of growth-ring formation (with confidence intervals) can be determined. The parameter estimate for the timing of new growth-ring formation for Lethrinus sp. 3 was from mid July to mid September, for Lutjanus vitta from early July to the end of August, for Nemipterus furcosus from mid July to late September, and for Lutjanus sebae from mid July to mid November. The confidence intervals for the timing of formation of growth rings was variable between species, being smallest for L. vitta, and variable between fish of the same species with different numbers of growth rings. The stock assessments of these commercially important species relies on aging information for all the age classes used in the assessment. This study demonstrated that growth rings on sectioned otoliths were laid down annually, irrespective of the number of growth rings, and also demonstrated that the timing of ring formation for these tropical species can be determined quantitatively (with confidence intervals.

Low short term timing jitter in an integrated monolithic extended cavity semiconductor mode-locked laser

Jitter measurements were performed on a monolithically integrated active/passive cavity multiple quantum well laser, actively mode-locked at 10 GHz via modulation of an absorber section. Sub-10 ps pulses were produced upon optimization of the drive conditions to the gain, distributed Bragg reflector, and absorber sections. A model was also developed using travelling wave rate equations. Simulation results suggest that spontaneous emission is the dominant cause of jitter, with carrier dynamics having a time constant of the order of 1 ns.

Internal representations of temporal statistics and feedback calibrate motor-sensory interval timing.

Humans have been shown to adapt to the temporal statistics of timing tasks so as to optimize the accuracy of their responses, in agreement with the predictions of Bayesian integration. This suggests that they build an internal representation of both the experimentally imposed distribution of time intervals (the prior) and of the error (the loss function). The responses of a Bayesian ideal observer depend crucially on these internal representations, which have only been previously studied for simple distributions. To study the nature of these representations we asked subjects to reproduce time intervals drawn from underlying temporal distributions of varying complexity, from uniform to highly skewed or bimodal while also varying the error mapping that determined the performance feedback. Interval reproduction times were affected by both the distribution and feedback, in good agreement with a performance-optimizing Bayesian observer and actor model. Bayesian model comparison highlighted that subjects were integrating the provided feedback and represented the experimental distribution with a smoothed approximation. A nonparametric reconstruction of the subjective priors from the data shows that they are generally in agreement with the true distributions up to third-order moments, but with systematically heavier tails. In particular, higher-order statistical features (kurtosis, multimodality) seem much harder to acquire. Our findings suggest that humans have only minor constraints on learning lower-order statistical properties of unimodal (including peaked and skewed) distributions of time intervals under the guidance of corrective feedback, and that their behavior is well explained by Bayesian decision theory.

Functional requirements for reward-modulated spike-timing-dependent plasticity.

Recent experiments have shown that spike-timing-dependent plasticity is influenced by neuromodulation. We derive theoretical conditions for successful learning of reward-related behavior for a large class of learning rules where Hebbian synaptic plasticity is conditioned on a global modulatory factor signaling reward. We show that all learning rules in this class can be separated into a term that captures the covariance of neuronal firing and reward and a second term that presents the influence of unsupervised learning. The unsupervised term, which is, in general, detrimental for reward-based learning, can be suppressed if the neuromodulatory signal encodes the difference between the reward and the expected reward-but only if the expected reward is calculated for each task and stimulus separately. If several tasks are to be learned simultaneously, the nervous system needs an internal critic that is able to predict the expected reward for arbitrary stimuli. We show that, with a critic, reward-modulated spike-timing-dependent plasticity is capable of learning motor trajectories with a temporal resolution of tens of milliseconds. The relation to temporal difference learning, the relevance of block-based learning paradigms, and the limitations of learning with a critic are discussed.

Slowness: an objective for spike-timing-dependent plasticity?

Our nervous system can efficiently recognize objects in spite of changes in contextual variables such as perspective or lighting conditions. Several lines of research have proposed that this ability for invariant recognition is learned by exploiting the fact that object identities typically vary more slowly in time than contextual variables or noise. Here, we study the question of how this "temporal stability" or "slowness" approach can be implemented within the limits of biologically realistic spike-based learning rules. We first show that slow feature analysis, an algorithm that is based on slowness, can be implemented in linear continuous model neurons by means of a modified Hebbian learning rule. This approach provides a link to the trace rule, which is another implementation of slowness learning. Then, we show analytically that for linear Poisson neurons, slowness learning can be implemented by spike-timing-dependent plasticity (STDP) with a specific learning window. By studying the learning dynamics of STDP, we show that for functional interpretations of STDP, it is not the learning window alone that is relevant but rather the convolution of the learning window with the postsynaptic potential. We then derive STDP learning windows that implement slow feature analysis and the "trace rule." The resulting learning windows are compatible with physiological data both in shape and timescale. Moreover, our analysis shows that the learning window can be split into two functionally different components that are sensitive to reversible and irreversible aspects of the input statistics, respectively. The theory indicates that irreversible input statistics are not in favor of stable weight distributions but may generate oscillatory weight dynamics. Our analysis offers a novel interpretation for the functional role of STDP in physiological neurons.

Timing feedback control of a rhythmic system

This paper addresses the question relative to the role of sensory feedback in rhythmic tasks. We study the properties of a sinusoidally vibrating wedge-billiard as a model for 2-D bounce juggling. If this wedge is actuated with an harmonic sinusoidal input, it has been shown that some periodic orbits are exponentially stable. This paper explores an intuitive method to enlarge the parametric stability region of the simplest of these orbits. Accurate processing of timing is proven to be an important key to achieve frequency-locking in rhythmic tasks. © 2005 IEEE.

Inhibitory Synaptic Plasticity - Spike timing dependence and putative network function.

While the plasticity of excitatory synaptic connections in the brain has been widely studied, the plasticity of inhibitory connections is much less understood. Here, we present recent experimental and theoretical □ndings concerning the rules of spike timing-dependent inhibitory plasticity and their putative network function. This is a summary of a workshop at the COSYNE conference 2012.

Daily timing of emersion and elevated atmospheric CO2 concentration affect photosynthetic performance of the intertidal macroalga Ulva lactuca (Chlorophyta) in sunlight

The lunar day differs in length from the solar day so that times of low tide vary from day to day. Thus, aerial exposure of intertidal seaweeds may be during the day or during the night. We measured photosynthetic CO, assimilation rates of the intertidal green macroalga Ulva lactuca during exposures of varied daily timings during sunny days of summer to establish how photosynthetic performance responds to emersion timing under varied CO2 levels [at ambient (360 ppmv) and 2x ambient (720 ppmv) atmospheric CO2 concentrations]. There was an increase in net photosynthetic rates following some duration of exposure when the initial timing of exposure occurred during early morning (06.30 h) and late afternoon (17.15 h). In contrast, net rates exhibited a sharp decline with exposure duration when the initial timing of exposure occurred at 09.30 h, 15.30 h and especially at noon (12.30 h), implying the occurrence of a severe photoinhibition resulting from mid-day insolation. Doubled atmospheric CO2 concentration significantly enhanced the emersed photosynthetic rates, indicating that the emersed photosynthesis is CO2-limited at ambient CO2 levels. However, increasing CO2 barely stimulates the emersed photosynthetic rates during mid-day insolation.

Study of high performance re-timing using a 40 Gb/s hybrid-integrated mach-zehnder all-optical regenerator

We experimentally show that a hybrid-integrated Mach-Zehnder switch with a high performance gate profile allows retiming of optical signals with an accuracy of 500-700fs even if the input timing jitter is increased to 3ps. © 2004 Optical Society of America.