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.

Low-timing-jitter, stretched-pulse passively mode-locked fiber laser with tunable repetition rate and high operation stability

We design a low-timing-jitter, repetition-rate-tunable, stretched-pulse passively mode-locked fiber laser by using a nonlinear amplifying loop mirror (NALM), a semiconductor saturable absorber mirror (SESAM), and a tunable optical delay line in the laser configuration. Low-timing-jitter optical pulses are stably produced when a SESAM and a 0.16 m dispersion compensation fiber are employed in the laser cavity. By inserting a tunable optical delay line between NALM and SESAM, the variable repetition-rate operation of a self-starting, passively mode-locked fiber laser is successfully demonstrated over a range from 49.65 to 50.47 MHz. The experimental results show that the newly designed fiber laser can maintain the mode locking at the pumping power of 160 mW to stably generate periodic optical pulses with width less than 170 fs and timing jitter lower than 75 fs in the 1.55 mu m wavelength region, when the fundamental repetition rate of the laser is continuously tuned between 49.65 and 50.47 MHz. Moreover, this fiber laser has a feature of turn-key operation with high repeatability of its fundamental repetition rate in practice.

Studies of timing for a TOF counter at external target facility

Timing and amplitude properties of a prototype scintillator TOF counter at an external target facility are studied with a cosmic rays test. The dependence of signal pulse height and time resolution on the coordinate along the scintillator TOF counter is investigated with two different discriminators. A time resolution of 165 ps can be achieved at the center of the counter with a constant fraction discriminator. Time resolution better than 150 ps is obtained at the center with a leading edge discriminator af...