Integration Time Window Research Articles

Time and timing in the acoustic recognition system of crickets.

The songs of many insects exhibit precise timing as the result of repetitive and stereotyped subunits on several time scales. As these signals encode the identity of a species, time and timing are important for the recognition system that analyzes these signals. Crickets are a prominent example as their songs are built from sound pulses that are broadcast in a long trill or as a chirped song. This pattern appears to be analyzed on two timescales, short and long. Recent evidence suggests that song recognition in crickets relies on two computations with respect to time; a short linear-nonlinear (LN) model that operates as a filter for pulse rate and a longer integration time window for monitoring song energy over time. Therefore, there is a twofold role for timing. A filter for pulse rate shows differentiating properties for which the specific timing of excitation and inhibition is important. For an integrator, however, the duration of the time window is more important than the precise timing of events. Here, we first review evidence for the role of LN-models and integration time windows for song recognition in crickets. We then parameterize the filter part by Gabor functions and explore the effects of duration, frequency, phase, and offset as these will correspond to differently timed patterns of excitation and inhibition. These filter properties were compared with known preference functions of crickets and katydids. In a comparative approach, the power for song discrimination by LN-models was tested with the songs of over 100 cricket species. It is demonstrated how the acoustic signals of crickets occupy a simple 2-dimensional space for song recognition that arises from timing, described by a Gabor function, and time, the integration window. Finally, we discuss the evolution of recognition systems in insects based on simple sensory computations.

A Photonic Temporal Integrator With an Ultra-Long Integration Time Window Based on an InP-InGaAsP Integrated Ring Resonator

A photonic temporal integrator with an ultra-wide integration time window implemented based on a photonic integrated circuit (PIC) in an InP-InGaAsP material system consisting of semiconductor optical amplifiers (SOAs) and current-injection phase modulators (PMs) is proposed and experimentally demonstrated. The proposed photonic integrated integrator employs a ring structure coupled with two bypass waveguides. The tunable coupling between the ring and the waveguides is realized by a multi-mode interference (MMI) Mach-Zehnder interferometer coupler. Within the ring, two SOAs are incorporated to compensate for the insertion loss. In addition, there is a current injection PM in the ring for wavelength tuning. The use of the device provides a photonic temporal integrator with an ultra-wide integration time window and a tunable operation wavelength in a single PIC. The proposed integrator is fabricated and experimentally verified. The integration time window as wide as 6331 ps is achieved, which is an order of magnitude longer than that provided by the previously reported photonic integrators.

Plasticity of GABA transporters: an unconventional route to shape inhibitory synaptic transmission

The brain relies on GABAergic neurons to control the ongoing activity of neuronal networks. GABAergic neurons control the firing pattern of excitatory cells, the temporal structure of membrane potential oscillations and the time window for integration of synaptic inputs. These actions require a fine control of the timing of GABA receptor activation which, in turn, depends on the precise timing of GABA release from pre-synaptic terminals and GABA clearance from the extracellular space. Extracellular GABA is not subject to enzymatic breakdown, and its clearance relies entirely on diffusion and uptake by specific transporters. In contrast to glutamate transporters, GABA transporters are abundantly expressed in neuronal pre-synaptic terminals. GABA transporters move laterally within the plasma membrane and are continuously trafficked to/from intracellular compartments. It is hypothesized that due to their proximity to GABA release sites, changes in the concentration and lateral mobility of GABA transporters may have a significant effect on the time course of the GABA concentration profile in and out of the synaptic cleft. To date, this hypothesis remains to be tested. Here we use 3D Monte Carlo reaction-diffusion simulations to analyze how changes in the density of expression and lateral mobility of GABA transporters in the cell membrane affect the extracellular GABA concentration profile and the activation of GABA receptors. Our results indicate that these manipulations mainly alter the GABA concentration profile away from the synaptic cleft. These findings provide novel insights into how the ability of GABA transporters to undergo plastic changes may alter the strength of GABAergic signals and the activity of neuronal networks in the brain.

Designing driver assistance systems with crossmodal signals: multisensory integration rules for saccadic reaction times apply.

Modern driver assistance systems make increasing use of auditory and tactile signals in order to reduce the driver's visual information load. This entails potential crossmodal interaction effects that need to be taken into account in designing an optimal system. Here we show that saccadic reaction times to visual targets (cockpit or outside mirror), presented in a driving simulator environment and accompanied by auditory or tactile accessories, follow some well-known spatiotemporal rules of multisensory integration, usually found under confined laboratory conditions. Auditory nontargets speed up reaction time by about 80 ms. The effect tends to be maximal when the nontarget is presented 50 ms before the target and when target and nontarget are spatially coincident. The effect of a tactile nontarget (vibrating steering wheel) was less pronounced and not spatially specific. It is shown that the average reaction times are well-described by the stochastic “time window of integration” model for multisensory integration developed by the authors. This two-stage model postulates that crossmodal interaction occurs only if the peripheral processes from the different sensory modalities terminate within a fixed temporal interval, and that the amount of crossmodal interaction manifests itself in an increase or decrease of second stage processing time. A qualitative test is consistent with the model prediction that the probability of interaction, but not the amount of crossmodal interaction, depends on target–nontarget onset asynchrony. A quantitative model fit yields estimates of individual participants' parameters, including the size of the time window. Some consequences for the design of driver assistance systems are discussed.

The interaction between stimulus factors and cognitive factors during multisensory integration of audiovisual speech.

The interaction between stimulus factors and cognitive factors during multisensory integration of audiovisual speech.

Recalibration of the Multisensory Temporal Window of Integration

Recalibration of the Multisensory Temporal Window of Integration

Active Fabry-Perot cavity for photonic temporal integrator with ultra-long operation time window

In this paper, a photonic temporal integrator based on an active Fabry-Perot (F-P) cavity is proposed and theoretically investigated. The gain medium in the F-P cavity is a semiconductor optical amplifier (SOA) with high gain coefficient. Key feature of the proposed photonic integrator is that the length of integration time window is widely tunable and could be ideally extended to infinitely long when the injection current is approaching lasing condition. Based on an F-P cavity with practically feasible parameters, a photonic temporal integrator with an integration time window of 160 ns and an operation bandwidth of 180 GHz is achieved. The time-bandwidth product of this photonic temporal integrator is 28,800, which is about two-orders of magnitude higher than any previously reported results. Gain recovery effect has been also considered and analyzed for the impact on performance of the photonic integrator, followed by the simulation results of the impact of gain recovery.

Hippocampal Feedforward Inhibition Focuses Excitatory Synaptic Signals into Distinct Dendritic Compartments

Feedforward inhibition controls the time window for synaptic integration and ensures temporal precision in cortical circuits. There is little information whether feedforward inhibition affects neurons uniformly, or whether it contributes to computational refinement within the dendritic tree. Here we demonstrate that feedforward inhibition crucially shapes the integration of synaptic signals in pyramidal cell dendrites. Using voltage-sensitive dye imaging we studied the transmembrane voltage patterns in CA1 pyramidal neurons after Schaffer collateral stimulation in acute brain slices from mice. We observed a high degree of variability in the excitation-inhibition ratio between different branches of the dendritic tree. Many dendritic segments showed no depolarizing signal at all, especially the basal dendrites that received predominantly inhibitory signals. Application of the GABAA receptor antagonist bicuculline resulted in the spread of depolarizing signals throughout the dendritic tree. Tetanic stimulation of Schaffer collateral inputs induced significant alterations in the patterns of excitation/inhibition, indicating that they are modified by synaptic plasticity. In summary, we show that feedforward inhibition restricts the occurrence of depolarizing signals within the dendritic tree of CA1 pyramidal neurons and thus refines signal integration spatially.

Endogenous zinc depresses GABAergic transmission via T‐type Ca2+ channels and broadens the time window for integration of glutamatergic inputs in dentate granule cells

Zinc actions on synaptic transmission span the modulation of neurotransmitter receptors, transporters, activation of intracellular cascades and alterations in gene expression. Whether and how zinc affects inhibitory synaptic signalling in the dentate gyrus remains largely unexplored. We found that mono- and di-synaptic GABAergic inputs onto dentate granule cells were reversibly depressed by exogenous zinc application and enhanced by zinc chelation. Blocking T-type Ca2+ channels prevented the effect of zinc chelation. When recording from dentate fast-spiking interneurones, zinc chelation facilitated T-type Ca2+ currents, increased action potential half-width and decreased spike threshold. It also increased the offset of the input–output relation in a manner consistent with enhanced excitability. In granule cells, chelation of zinc reduced the time window for the integration of glutamatergic inputs originating from perforant path synapses, resulting in reduced spike transfer. Thus, zinc-mediated modulation of dentate interneurone excitability and GABA release regulates information flow to local targets and hippocampal networks.

A passive cable to excite oligodendrocyte precursor glia

A passive cable to excite oligodendrocyte precursor glia

COLIBRI: partial camera readout and sliding trigger for the Cherenkov Telescope Array CTA

Plans for the future Cherenkov telescope array CTAinclude replacing the monolithic camera designs used in H.E.S.S. and MAGIC-I by one that is built up from a number of identical segments. These so-called clusters will be relatively autonomous, each containing its own triggering and readout hardware. While this choice was made for reasons of flexibility and ease of manufacture and maintenance, such a concept with semi-independent sub-units lends itself quite naturally to the possibility of new, and more flexible, readout modes. In all previously-used concepts, triggering and readout of the camera is centralised, with a single camera trigger per event that starts the readout of all pixels in the camera at the same time and within the same integration time window. The limitations of such a trigger system can reduce the performance of a large array such as CTA, due to the huge amount of useless data created by night-sky background if trigger thresholds are set low enough to achieve the desired 20 GeV energy threshold, and to image losses at high energies due to the rigid readout window.In this study, an alternative concept (``COLIBRI'' = Concept for an Optimised Local Image Building and Readout Infrastructure) is presented, where only those parts of the camera which are likely to actually contain image data (usually a small percentage of the total pixels) are read out. This leads to a significant reduction of the expected data rate and the dead-times incurred in the camera. Furthermore, the quasi-independence of the individual clusters can be used to read different parts of the camera at slightly different times, thus allowing the readout to follow the slow development of the shower image across the camera field of view. This concept of flexible, partial camera readout is presented in the following, together with a description of Monte-Carlo studies performed to evaluate its performance as well as a hardware implementation proposed for CTA.

Cholinergic Dysfunction Alters Synaptic Integration between Thalamostriatal and Corticostriatal Inputs in DYT1 Dystonia

Projections from thalamic intralaminar nuclei convey sensory signals to striatal cholinergic interneurons. These neurons respond with a pause in their pacemaking activity, enabling synaptic integration with cortical inputs to medium spiny neurons (MSNs), thus playing a crucial role in motor function. In mice with the DYT1 dystonia mutation, stimulation of thalamostriatal axons, mimicking a response to salient events, evoked a shortened pause and triggered an abnormal spiking activity in interneurons. This altered pattern caused a significant rearrangement of the temporal sequence of synaptic activity mediated by M(1) and M(2) muscarinic receptors in MSNs, consisting of an increase in postsynaptic currents and a decrease of presynaptic inhibition, respectively. Consistent with a major role of acetylcholine, either lowering cholinergic tone or antagonizing postsynaptic M(1) muscarinic receptors normalized synaptic activity. Our data demonstrate an abnormal time window for synaptic integration between thalamostriatal and corticostriatal inputs, which might alter the action selection process, thereby predisposing DYT1 gene mutation carriers to develop dystonic movements.

Single-shot photonic time-intensity integration based on a time-spectrum convolution system

Real-time and single-shot ultra-fast photonic time-intensity integration of arbitrary temporal waveforms is proposed and demonstrated. The intensity-integration concept is based on a time-spectrum convolution system, where the use of a multi-wavelength laser with a flat envelope, employed as the incoherent broadband source, enables single-shot operation. The experimental implementation is based on optical intensity modulation of the multi-wavelength laser with the input waveform, followed by linear dispersion. In particular, photonic temporal intensity integration with a processing bandwidth of 36.8 GHz over an integration time window of 1.24 ns is verified by experimentally measuring the integration of an ultra-short microwave pulse and an arbitrary microwave waveform.

Focused attention vs. crossmodal signals paradigm: deriving predictions from the time-window-of-integration model

In the crossmodal signals paradigm (CSP) participants are instructed to respond to a set of stimuli from different modalities, presented more or less simultaneously, as soon as a stimulus from any modality has been detected. In the focused attention paradigm (FAP), on the other hand, responses should only be made to a stimulus from a pre-defined target modality and stimuli from non-target modalities should be ignored. Whichever paradigm is being applied, a typical result is that responses tend to be faster to crossmodal stimuli than to unimodal stimuli, a phenomenon often referred to as “crossmodal interaction.” Here, we investigate predictions of the time-window-of-integration (TWIN) modeling framework previously proposed by the authors. It is shown that TWIN makes specific qualitative and quantitative predictions on how the two paradigms differ with respect to the probability of multisensory integration and the amount of response enhancement, including the effect of stimulus intensity (“inverse effectiveness”). Introducing a decision-theoretic framework for TWIN further allows comparing the two paradigms with respect to the predicted optimal time window size and its dependence on the prior probability that the crossmodal stimulus information refers to the same event. In order to test these predictions, experimental studies that systematically compare crossmodal effects under stimulus conditions that are identical except for the CSP-FAP instruction should be performed in the future.

Optimizing read-out of the NECTAr front-end electronics

We describe the optimization of the read-out specifications of the NECTAr front-end electronics for the Cherenkov Telescope Array (CTA). The NECTAr project aims at building and testing a demonstrator module of a new front-end electronics design, which takes an advantage of the know-how acquired while building the cameras of the CAT, H.E.S.S.-I and H.E.S.S.-II experiments.The goal of the optimization work is to define the specifications of the digitizing electronics of a CTA camera, in particular integration time window, sampling rate, analog bandwidth using physics simulations. We employed for this work real photomultiplier pulses, sampled at 100ps with a 600MHz bandwidth oscilloscope.The individual pulses are drawn randomly at the times at which the photo-electrons, originating from atmospheric showers, arrive at the focal planes of imaging atmospheric Cherenkov telescopes. The timing information is extracted from the existing CTA simulations on the GRID and organized in a local database, together with all the relevant physical parameters (energy, primary particle type, zenith angle, distance from the shower axis, pixel offset from the optical axis, night-sky background level, etc.), and detector configurations (telescope types, camera/mirror configurations, etc.).While investigating the parameter space, an optimal pixel charge integration time window, which minimizes relative error in the measured charge, has been determined. This will allow to gain in sensitivity and to lower the energy threshold of CTA telescopes. We present results of our optimizations and first measurements obtained using the NECTAr demonstrator module.

Cell-Type-Specific Modulation of Feedback Inhibition by Serotonin in the Hippocampus

Midbrain raphe nuclei provide strong serotonergic projections to the hippocampus, in which serotonin (5-HT) exerts differential effects mediated by multiple 5-HT receptor subtypes. The functional relevance of this diversity of information processing is poorly understood. Here we show that serotonin via 5-HT(1B) heteroreceptors substantially reduces synaptic excitation of cholecystokinin-expressing interneurons in area CA1 of the rat hippocampus, in contrast to parvalbumin-expressing basket cells. The reduction is input specific, affecting only glutamatergic synaptic transmission originating from CA1 pyramidal cells. As a result, serotonin selectively decreases feedback inhibition via 5-HT(1B) receptor activation and subsequently increases the integration time window for spike generation in CA1 pyramidal cells. Our data imply an important role for serotonergic modulation of GABAergic action in subcortical control of hippocampal output.

Computing an optimal time window of audiovisual integration in focused attention tasks: illustrated by studies on effect of age and prior knowledge

The concept of a "time window of integration" holds that information from different sensory modalities must not be perceived too far apart in time in order to be integrated into a multisensory perceptual event. Empirical estimates of window width differ widely, however, ranging from 40 to 600ms depending on context and experimental paradigm. Searching for theoretical derivation of window width, Colonius and Diederich (Front Integr Neurosci 2010) developed a decision-theoretic framework using a decision rule that is based on the prior probability of a common source, the likelihood of temporal disparities between the unimodal signals, and the payoff for making right or wrong decisions. Here, this framework is extended to the focused attention task where subjects are asked to respond to signals from a target modality only. Evoking the framework of the time-window-of-integration (TWIN) model, an explicit expression for optimal window width is obtained. The approach is probed on two published focused attention studies. The first is a saccadic reaction time study assessing the efficiency with which multisensory integration varies as a function of aging. Although the window widths for young and older adults differ by nearly 200ms, presumably due to their different peripheral processing speeds, neither of them deviates significantly from the optimal values. In the second study, head saccadic reactions times to a perfectly aligned audiovisual stimulus pair had been shown to depend on the prior probability of spatial alignment. Intriguingly, they reflected the magnitude of the time-window widths predicted by our decision-theoretic framework, i.e., a larger time window is associated with a higher prior probability.

Membrane Potential-Dependent Modulation of Recurrent Inhibition in Rat Neocortex

Dynamic balance of excitation and inhibition is crucial for network stability and cortical processing, but it is unclear how this balance is achieved at different membrane potentials (V m) of cortical neurons, as found during persistent activity or slow V m oscillation. Here we report that a V m-dependent modulation of recurrent inhibition between pyramidal cells (PCs) contributes to the excitation-inhibition balance. Whole-cell recording from paired layer-5 PCs in rat somatosensory cortical slices revealed that both the slow and the fast disynaptic IPSPs, presumably mediated by low-threshold spiking and fast spiking interneurons, respectively, were modulated by changes in presynaptic V m. Somatic depolarization (>5 mV) of the presynaptic PC substantially increased the amplitude and shortened the onset latency of the slow disynaptic IPSPs in neighboring PCs, leading to a narrowed time window for EPSP integration. A similar increase in the amplitude of the fast disynaptic IPSPs in response to presynaptic depolarization was also observed. Further paired recording from PCs and interneurons revealed that PC depolarization increases EPSP amplitude and thus elevates interneuronal firing and inhibition of neighboring PCs, a reflection of the analog mode of excitatory synaptic transmission between PCs and interneurons. Together, these results revealed an immediate V m-dependent modulation of cortical inhibition, a key strategy through which the cortex dynamically maintains the balance of excitation and inhibition at different states of cortical activity.

Spike-Based Population Coding and Working Memory

Compelling behavioral evidence suggests that humans can make optimal decisions despite the uncertainty inherent in perceptual or motor tasks. A key question in neuroscience is how populations of spiking neurons can implement such probabilistic computations. In this article, we develop a comprehensive framework for optimal, spike-based sensory integration and working memory in a dynamic environment. We propose that probability distributions are inferred spike-per-spike in recurrently connected networks of integrate-and-fire neurons. As a result, these networks can combine sensory cues optimally, track the state of a time-varying stimulus and memorize accumulated evidence over periods much longer than the time constant of single neurons. Importantly, we propose that population responses and persistent working memory states represent entire probability distributions and not only single stimulus values. These memories are reflected by sustained, asynchronous patterns of activity which make relevant information available to downstream neurons within their short time window of integration. Model neurons act as predictive encoders, only firing spikes which account for new information that has not yet been signaled. Thus, spike times signal deterministically a prediction error, contrary to rate codes in which spike times are considered to be random samples of an underlying firing rate. As a consequence of this coding scheme, a multitude of spike patterns can reliably encode the same information. This results in weakly correlated, Poisson-like spike trains that are sensitive to initial conditions but robust to even high levels of external neural noise. This spike train variability reproduces the one observed in cortical sensory spike trains, but cannot be equated to noise. On the contrary, it is a consequence of optimal spike-based inference. In contrast, we show that rate-based models perform poorly when implemented with stochastically spiking neurons.

Ih-mediated depolarization enhances the temporal precision of neuronal integration

Feed-forward inhibition mediated by ionotropic GABAA receptors contributes to the temporal precision of neuronal signal integration. These receptors exert their inhibitory effect by shunting excitatory currents and by hyperpolarizing neurons. The relative roles of these mechanisms in neuronal computations are, however, incompletely understood. In this study, we show that by depolarizing the resting membrane potential relative to the reversal potential for GABAA receptors, the hyperpolarization-activated mixed cation current (Ih) maintains a voltage gradient for fast synaptic inhibition in hippocampal pyramidal cells. Pharmacological or genetic ablation of Ih broadens the depolarizing phase of afferent synaptic waveforms by hyperpolarizing the resting membrane potential. This increases the integration time window for action potential generation. These results indicate that the hyperpolarizing component of GABAA receptor-mediated inhibition has an important role in maintaining the temporal fidelity of coincidence detection and suggest a previously unrecognized mechanism by which Ih modulates information processing in the hippocampus.