Journal articles: 'Temporal delay'

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Marcoux, Judith, David Bracco, and Rajeet S. Saluja. "Temporal delays in trauma craniotomies." Journal of Neurosurgery 125, no. 3 (September 2016): 642–47. http://dx.doi.org/10.3171/2015.6.jns15175.

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OBJECTIVE The Brain Trauma Foundation recommendation regarding the timing of surgical evacuation of epidural hematomas and subdural hematomas is to perform the procedure as soon as possible. Indeed, faster evacuation is associated with better outcome. However, to the authors' knowledge, no study has looked at where delays in intrahospital care occurred for patients suffering from traumatic intracranial mass lesions. The goals of this study were as follows: 1) to characterize the performance of a Level 1 trauma center in terms of delays for emergency trauma craniotomies, 2) to review step by step where delays occurred in patient care, and 3) to propose ways to improve performance. METHODS A retrospective review was conducted covering a 5-year period of all emergency trauma craniotomies. Demographic data, injury severity, neurological status, and functional outcome data were collected. The time elapsed between emergency department (ED) arrival and CT imaging, between CT imaging and arrival at the operating room (OR), between ED arrival and OR arrival, between OR arrival and skin incision, and between ED arrival and skin incision were calculated. Patients were also subcategorized as either having immediate life-threatening emergencies (E0) or life-threatening emergencies (E1). The operative technique was also reviewed (standard craniotomy opening vs immediate bur hole decompression followed by craniotomy). RESULTS The study included 166 patients. Of these, 58 (35%) were classified into the E0 group and 108 (64.2%) into the E1 group. The median ED-to-CT delay was 54 minutes with no significant difference between the E0 and the E1 groups. The median CT-to-OR time delay was 57 minutes. The median delay for the E0 group was 39 minutes and that for the E1 group was 70 minutes (p = 0.002). The median delay from ED to OR arrival for patients with a CT scanning done at an outside hospital was 75 minutes. The median delay from ED to OR arrival was 85 minutes for the E0 group and 127 minutes for the E1 group (p < 0.0001). The median delay from OR arrival to skin incision was 35 minutes (E0: median 27 minutes; E1: median 39 minutes; p < 0.0001). The median total time elapsed between ED arrival and skin incision was 150 minutes (E0: median 131 minutes; E1: median 180 minutes). Overall, only 17% of patients underwent immediate bur hole decompression, but the proportion climbed to 41% in the E0 group. A lower Glasgow Coma Scale score was associated with a shorter delay (p = 0.0004). CONCLUSIONS A long delay until surgery still exists for patients requiring urgent mass lesion evacuation. Many factors contribute to this delay, including performing imaging and transfer to and preparation in the OR. Strategies can be implemented to reduce delays and improve the delivery of care.

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Zhou, Weiwei, Justin Fitzgerald, Katrina Colucci-Chang, Karthik G. Murthy, and Wilsaan M. Joiner. "The temporal stability of visuomotor adaptation generalization." Journal of Neurophysiology 118, no. 4 (October 1, 2017): 2435–47. http://dx.doi.org/10.1152/jn.00822.2016.

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Movement adaptation in response to systematic motor perturbations exhibits distinct spatial and temporal properties. These characteristics are typically studied in isolation, leaving the interaction largely unknown. Here we examined how the temporal decay of visuomotor adaptation influences the spatial generalization of the motor recalibration. First, we quantified the extent to which adaptation decayed over time. Subjects reached to a peripheral target, and a rotation was applied to the visual feedback of the unseen motion. The retention of this adaptation over different delays (0–120 s) 1) decreased by 29.0 ± 6.8% at the longest delay and 2) was represented by a simple exponential, with a time constant of 22.5 ± 5.6 s. On the basis of this relationship we simulated how the spatial generalization of adaptation would change with delay. To test this directly, we trained additional subjects with the same perturbation and assessed transfer to 19 different locations (spaced 15° apart, symmetric around the trained location) and examined three delays (~4, 12, and 25 s). Consistent with the simulation, we found that generalization around the trained direction (±15°) significantly decreased with delay and distance, while locations >60° displayed near-constant spatiotemporal transfer. Intermediate distances (30° and 45°) showed a difference in transfer across space, but this amount was approximately constant across time. Interestingly, the decay at the trained direction was faster than that based purely on time, suggesting that the spatial transfer of adaptation is modified by concurrent passive (time dependent) and active (movement dependent) processes. NEW & NOTEWORTHY Short-term motor adaptation exhibits distinct spatial and temporal characteristics. Here we investigated the interaction of these features, utilizing a simple motor adaptation paradigm (recalibration of reaching arm movements in response to rotated visual feedback). We examined the changes in the spatial generalization of motor adaptation for different temporal manipulations and report that the spatiotemporal generalization of motor adaptation is generally local and is influenced by both passive (time dependent) and active (movement dependent) learning processes.

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Yan, Hao, and Xiaojuan Sun. "Impact of Partial Time Delay on Temporal Dynamics of Watts–Strogatz Small-World Neuronal Networks." International Journal of Bifurcation and Chaos 27, no. 07 (June 30, 2017): 1750112. http://dx.doi.org/10.1142/s0218127417501127.

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In this paper, we mainly discuss effects of partial time delay on temporal dynamics of Watts–Strogatz (WS) small-world neuronal networks by controlling two parameters. One is the time delay [Formula: see text] and the other is the probability of partial time delay [Formula: see text]. Temporal dynamics of WS small-world neuronal networks are discussed with the aid of temporal coherence and mean firing rate. With the obtained simulation results, it is revealed that for small time delay [Formula: see text], the probability [Formula: see text] could weaken temporal coherence and increase mean firing rate of neuronal networks, which indicates that it could improve neuronal firings of the neuronal networks while destroying firing regularity. For large time delay [Formula: see text], temporal coherence and mean firing rate do not have great changes with respect to [Formula: see text]. Time delay [Formula: see text] always has great influence on both temporal coherence and mean firing rate no matter what is the value of [Formula: see text]. Moreover, with the analysis of spike trains and histograms of interspike intervals of neurons inside neuronal networks, it is found that the effects of partial time delays on temporal coherence and mean firing rate could be the result of locking between the period of neuronal firing activities and the value of time delay [Formula: see text]. In brief, partial time delay could have great influence on temporal dynamics of the neuronal networks.

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Ruess, Miriam, Roland Thomaschke, and Andrea Kiesel. "Earlier Effects Are More Often Perceived as One’s Own Action Effects." Timing & Time Perception 5, no. 3-4 (December 8, 2017): 228–43. http://dx.doi.org/10.1163/22134468-00002091.

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When changes occur in our environment, we usually know whether we caused these changes by our actions or not. Yet, this feeling of authorship for changes — the so-called sense of agency (SoA) — depends on the temporal relationship between action and resulting change (i.e., effect). More precisely, SoA might depend on whether the effect occurs temporally predictable, and on the duration of the delay between action and effect. In previous studies, SoA was measured either explicitly, asking for the perceived control over external stimuli, or implicitly by measuring a characteristic temporal judgement bias (intentional binding, i.e., a shortening of the perceived interval between action and effect). We used a novel paradigm for investigating explicit SoA more directly by asking participants in a forced-choice paradigm whether they caused a temporally predictable or a temporally unpredictable effect by their action. Additionally, we investigated how the temporal contiguity of the effects influenced the participants’ explicit SoA. In two experiments (48 participants each), there was no influence of temporal predictability on explicit SoA. Temporally predictable and unpredictable effects were equally often rated as own effects. Yet, effects after shorter delays were more often perceived as own effects than effects after longer delays. These findings are in line with previous results concerning the influence of effect delay on other explicit measures of SoA and concluding that explicit SoA is stronger for early effects.

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Wei, Qiang, Cheng-jun Xie, Yi Liang, Yu-jun Niu, and Da Lin. "Delay synchronization of temporal Boolean networks." AIP Advances 6, no. 1 (January 2016): 015013. http://dx.doi.org/10.1063/1.4940894.

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Dai, Junyi, Thorsten Pachur, Timothy J. Pleskac, and Ralph Hertwig. "What the Future Holds and When: A Description–Experience Gap in Intertemporal Choice." Psychological Science 30, no. 8 (July 18, 2019): 1218–33. http://dx.doi.org/10.1177/0956797619858969.

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Uncertainty about the waiting time before obtaining an outcome is integral to intertemporal choice. Here, we showed that people express different time preferences depending on how they learn about this temporal uncertainty. In two studies, people chose between pairs of options: one with a single, sure delay and the other involving multiple, probabilistic delays (a lottery). The probability of each delay occurring either was explicitly described ( timing risk) or could be learned through experiential sampling ( timing uncertainty; the delay itself was not experienced). When the shorter delay was rare, people preferred the lottery more often when it was described than when it was experienced. When the longer delay was rare, this pattern was reversed. Modeling analyses suggested that underexperiencing rare delays and different patterns of probability weighting contribute to this description–experience gap. Our results challenge traditional models of intertemporal choice with temporal uncertainty as well as the generality of inverse-S-shaped probability weighting in such choice.

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Unsworth, Nash, Richard P. Heitz, and Nathan A. Parks. "The Importance of Temporal Distinctiveness for Forgetting Over the Short Term." Psychological Science 19, no. 11 (November 2008): 1078–81. http://dx.doi.org/10.1111/j.1467-9280.2008.02203.x.

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Rapidly forgetting information once attention is diverted seems to be a ubiquitous phenomenon. The cause of this rapid decline has been debated for decades; some researchers claim that memory traces decay as a function of time out of the focus of attention, whereas others claim that prior memory traces cause confusability by interfering with the current trace. Here we demonstrate that performance after a long delay can be better than performance after a short delay if the temporal confusability between the current item and previous items is reduced. These results provide strong evidence for the importance of temporal confusability, rather than decay, as the cause of forgetting over the short term.

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Buehner, Marc J., and Jon May. "Rethinking Temporal Contiguity and the Judgement of Causality: Effects of Prior Knowledge, Experience, and Reinforcement Procedure." Quarterly Journal of Experimental Psychology Section A 56, no. 5 (July 2003): 865–90. http://dx.doi.org/10.1080/02724980244000675.

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Time plays a pivotal role in causal inference. Nonetheless most contemporary theories of causal induction do not address the implications of temporal contiguity and delay, with the exception of associative learning theory. Shanks, Pearson, and Dickinson (1989) and several replications (Reed, 1992, 1999) have demonstrated that people fail to identify causal relations if cause and effect are separated by more than two seconds. In line with an associationist perspective, these findings have been interpreted to indicate that temporal lags universally impair causal induction. This interpretation clashes with the richness of everyday causal cognition where people apparently can reason about causal relations involving considerable delays. We look at the implications of cause-effect delays from a computational perspective and predict that delays should generally hinder reasoning performance, but that this hindrance should be alleviated if reasoners have knowledge of the delay. Two experiments demonstrated that (1) the impact of delay on causal judgement depends on participants’ expectations about the timeframe of the causal relation, and (2) the free-operant procedures used in previous studies are ill-suited to study the direct influences of delay on causal induction, because they confound delay with weaker evidence for the relation in question. Implications for contemporary causal learning theories are discussed.

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Sieck, Gary C., Young-Soo Han, Christina M. Pabelick, and Y. S. Prakash. "Temporal aspects of excitation-contraction coupling in airway smooth muscle." Journal of Applied Physiology 91, no. 5 (November 1, 2001): 2266–74. http://dx.doi.org/10.1152/jappl.2001.91.5.2266.

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In airway smooth muscle (ASM), ACh induces propagating intracellular Ca2+ concentration ([Ca2+]i) oscillations (5–30 Hz). We hypothesized that, in ASM, coupling of elevations and reductions in [Ca2+]i to force generation and relaxation (excitation-contraction coupling) is slower than ACh-induced [Ca2+]i oscillations, leading to stable force generation. When we used real-time confocal imaging, the delay between elevated [Ca2+]i and contraction in intact porcine ASM cells was found to be ∼450 ms. In β-escin-permeabilized ASM strips, photolytic release of caged Ca2+ resulted in force generation after ∼800 ms. When calmodulin (CaM) was added, this delay was shortened to ∼500 ms. In the presence of exogenous CaM and 100 μM Ca2+, photolytic release of caged ATP led to force generation after ∼80 ms. These results indicated significant delays due to CaM mobilization and Ca2+-CaM activation of myosin light chain kinase but much shorter delays introduced by myosin light chain kinase-induced phosphorylation of the regulatory myosin light chain MLC20 and cross-bridge recruitment. This was confirmed by prior thiophosphorylation of MLC20, in which force generation occurred ∼50 ms after photolytic release of caged ATP, approximating the delay introduced by cross-bridge recruitment alone. The time required to reach maximum steady-state force was >15 s. Rapid chelation of [Ca2+]i after photolytic release of caged diazo-2 resulted in relaxation after a delay of ∼1.2 s and 50% reduction in force after ∼57 s. We conclude that in ASM cells agonist-induced [Ca2+]i oscillations are temporally and spatially integrated during excitation-contraction coupling, resulting in stable force production.

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Arunachalam, Ravishankar, Ronald DeShawn Blanton, and Lawrence T. Pileggi. "Accurate Coupling-centric Timing Analysis Incorporating Temporal and Functional Isolation." VLSI Design 15, no. 3 (January 1, 2002): 605–18. http://dx.doi.org/10.1080/1065514021000012228.

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Neighboring line switching can contribute to a large portion of the delay of a line for today's deep submicron designs. The impact of this switching on delay is usually estimated by scaling the coupling capacitances (often by a factor of 2) and modeling them as grounded. This simple approach has been shown to be overly pessimistic in some cases, while somewhat optimistic in others. Apart from the delay modeling inaccuracies, the temporal and functional isolation of the aggressors can contribute to the pessimism. This paper introduces TACO, a timing analysis approach that addresses both these issues. TACO captures the provably worst-and best-case delays as a function of the timing-window inputs to the gates. We then present a comprehensive ATPG-based approach that uses functional information to identify valid interactions between coupled lines. Our algorithm accounts for glitches on aggressors that can be caused by static and dynamic hazards in the circuit. Results on industrial examples and benchmark circuits show the value of our approach.

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Pomper, Ulrich, Thomas Ditye, and Ulrich Ansorge. "Contralateral delay activity during temporal order memory." Neuropsychologia 129 (June 2019): 104–16. http://dx.doi.org/10.1016/j.neuropsychologia.2019.03.012.

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Casteigts, Arnaud, Paola Flocchini, Bernard Mans, and Nicola Santoro. "Measuring Temporal Lags in Delay-Tolerant Networks." IEEE Transactions on Computers 63, no. 2 (February 2014): 397–410. http://dx.doi.org/10.1109/tc.2012.208.

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Hagiwara, Masafumi. "Time-Delay ART for spatio-temporal patterns." Neurocomputing 6, no. 5-6 (October 1994): 513–21. http://dx.doi.org/10.1016/0925-2312(94)90003-5.

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Leen, T., T. Williams, T. Swiney, G. Leslie, and L. Brearley. "Temporal trends in discharge delay from ICU." Australian Critical Care 25, no. 2 (May 2012): 128. http://dx.doi.org/10.1016/j.aucc.2011.12.020.

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Zhao, Zhihong, and Erhua Rong. "Reaction diffusion equation with spatio-temporal delay." Communications in Nonlinear Science and Numerical Simulation 19, no. 7 (July 2014): 2252–61. http://dx.doi.org/10.1016/j.cnsns.2013.11.006.

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Manabe, Kazuchika. "ADDITIONAL-DELAY SCHEDULES: A CONTINUUM OF TEMPORAL CONTINGENCIES BY VARYING FOOD DELAY." Journal of the Experimental Analysis of Behavior 54, no. 2 (September 1990): 85–95. http://dx.doi.org/10.1901/jeab.1990.54-85.

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Walther, Hans-Otto. "Algebraic-Delay Differential Systems, State-Dependent Delay, and Temporal Order of Reactions." Journal of Dynamics and Differential Equations 21, no. 1 (February 10, 2009): 195–232. http://dx.doi.org/10.1007/s10884-009-9129-6.

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Grüneberg, C., J. Duysens, F. Honegger, and J. H. J. Allum. "Spatio-Temporal Separation of Roll and Pitch Balance-Correcting Commands in Humans." Journal of Neurophysiology 94, no. 5 (November 2005): 3143–58. http://dx.doi.org/10.1152/jn.00538.2004.

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This study was designed to provide evidence for the hypothesis that human balance corrections in response to pitch perturbations are controlled by muscle action mainly about the ankle and knee joints, whereas balance corrections for roll perturbations are controlled predominantly by motion about the hip and lumbro-sacral joints. A dual-axis rotating support surface delivered unexpected random perturbations to the stance of 19 healthy young adults through eight different directions in the pitch and the roll planes and three delays between pitch and roll directions. Roll delays with respect to pitch were no delay, a short 50-ms delay of roll with respect to pitch movements, (chosen to correspond to the onset time of leg muscle stretch reflexes), and a long 150-ms delay between roll and pitch movements (chosen to shift the time when trunk roll velocity peaks to the time when trunk peak pitch velocity normally occurs). Delays of stimulus roll with respect to pitch resulted in delayed roll responses of the legs, trunk, arms, and head consistent with stimulus delay without any changes in roll velocity amplitude. Delayed roll perturbations induced only small changes in the pitch motion of the legs and trunk; however, major changes were seen in the time when roll motion of the trunk was arrested. Amplitudes and directional sensitivity of short-latency (SL) stretch reflexes in ankle muscles were not altered with increasing roll delay. Small changes to balance correcting responses in ankle muscles were observed. SL stretch reflexes in hip and trunk muscles were delayed, and balance-correcting responses in trunk muscles became split into two distinct responses with delayed roll. The first of these responses was small and had a directional responsiveness aligned more along the pitch plane. The main, larger, response occurred with an onset and time-to-peak consistent with the delay in trunk roll displacement and its directional responsiveness was roll oriented. The sum of the amplitudes of these two types of balance-correcting responses remained constant with roll delay. These results support the hypothesis that corrections of the body's pitch and roll motion are programmed separately by neural command signals and provide insights into possible triggering mechanisms. The evidence that lower leg muscle balance-correcting activity is hardly changed by delayed trunk roll also indicates that lower leg muscle activity is not predominant in correcting roll motion of the body. Lower leg and trunk muscle activity appears to have a dual action in balance corrections. In trunk muscles the main action is to correct for roll perturbations and the lesser action may be an anticipatory stabilizing reaction for pitch perturbations. Likewise, the small changes in lower leg muscle activity may result from a generalized stabilizing reaction to roll perturbations, but the main action is to correct for pitch perturbations.

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Neuert, Veronika, Jesko L. Verhey, and Ian M. Winter. "Temporal Representation of the Delay of Iterated Rippled Noise in the Dorsal Cochlear Nucleus." Journal of Neurophysiology 93, no. 5 (May 2005): 2766–76. http://dx.doi.org/10.1152/jn.00774.2004.

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It has been suggested that the dorsal cochlear nucleus (DCN) is involved in the temporal representation of both envelope periodicity and pitch. This hypothesis is tested using iterated rippled noise (IRN), which is generated by a cascade of delay and add [IRN(+)] or delay and subtract [IRN(−)] operations. The autocorrelation functions (ACFs) of the waveform and the envelope of IRN(+) have a first peak at the delay, which corresponds to the perceived pitch of the IRN. With the same delay, the pitch of IRN(−) is generally an octave lower than for IRN(+). This is reflected in a first peak at twice the delay in the ACF of the waveform for IRN(−). In contrast, for identical delays, the ACF of the envelope for both IRN(−) and IRN(+) is the same. Thus the use of IRN allows the distinction between envelope - or fine-structure sensitivity. Recordings were made from 135 single units (BFs <5 kHz) in the DCN of the anesthetized guinea pig using IRN with delays ranging from 1 to 32 ms. In our sample 42% were sensitive to the periodicity of IRN(+) and were tuned to a particular delay in their first-order interspike interval histograms (ISIHs). This tuning was highly correlated with their response to white noise. Most units with best frequencies (BFs) <500 Hz show a different all-order ISIH for IRN(+) and IRN(−), which corresponds to the perceived pitch difference, whereas units with higher BFs show a similar response to IRN(+) and IRN(−). The results indicate that low-frequency units (BF <500 Hz) in the DCN may be involved in the representation of the waveform fine structure, although units with BFs >500 Hz are able to encode only the envelope periodicity of broadband IRN in their temporal discharge characteristics.

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Striano, Tricia, Anne Henning, and Daniel Stahl. "Sensitivity to interpersonal timing at 3 and 6 months of age." Epigenetic robotics 7, no. 2 (June 29, 2006): 251–71. http://dx.doi.org/10.1075/is.7.2.08str.

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Sensitivity to interpersonal timing was assessed in mother–infant interaction. In Study 1, 3-month-old infants interacted with their mothers over television and the mothers’ audio-visual presentation was either live or temporally delayed by 1 second. Infants gazed longer when the mother was presented live compared to delayed by 1 second, indicating that they detected the temporal delay. In Study 2, mothers interacted with their 3-month-old infants over television and the infants’ audio-visual presentation was either live or temporally delayed by 1 second. Mothers’ behavior was not altered by a 1-second delay in their infants’ behavior compared to a live presentation. In Study 3 and 4, the results were replicated with 6-month-old infants. Whereas infants detected the temporal delay in maternal responses, mothers likely adjusted to the delay in infant behavior. The discussion focuses on the role of interpersonal timing for detecting social contingency in dyadic and triadic communication.

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Hiriotappa, Kittipong, Suttipong Thajchayapong, Pimwadee Chaovalit, and Suporn Pongnumkul. "A Streaming Algorithm for Online Estimation of Temporal and Spatial Extent of Delays." Journal of Advanced Transportation 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/4018409.

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Knowing traffic congestion and its impact on travel time in advance is vital for proactive travel planning as well as advanced traffic management. This paper proposes a streaming algorithm to estimate temporal and spatial extent of delays online which can be deployed with roadside sensors. First, the proposed algorithm uses streaming input from individual sensors to detect a deviation from normal traffic patterns, referred to as anomalies, which is used as an early indication of delay occurrence. Then, a group of consecutive sensors that detect anomalies are used to temporally and spatially estimate extent of delay associated with the detected anomalies. Performance evaluations are conducted using a real-world data set collected by roadside sensors in Bangkok, Thailand, and the NGSIM data set collected in California, USA. Using NGSIM data, it is shown qualitatively that the proposed algorithm can detect consecutive occurrences of shockwaves and estimate their associated delays. Then, using a data set from Thailand, it is shown quantitatively that the proposed algorithm can detect and estimate delays associated with both recurring congestion and incident-induced nonrecurring congestion. The proposed algorithm also outperforms the previously proposed streaming algorithm.

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Lebedev, Mikhail A., Joseph E. O'Doherty, and Miguel A. L. Nicolelis. "Decoding of Temporal Intervals From Cortical Ensemble Activity." Journal of Neurophysiology 99, no. 1 (January 2008): 166–86. http://dx.doi.org/10.1152/jn.00734.2007.

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Neurophysiological, neuroimaging, and lesion studies point to a highly distributed processing of temporal information by cortico-basal ganglia-thalamic networks. However, there are virtually no experimental data on the encoding of behavioral time by simultaneously recorded cortical ensembles. We predicted temporal intervals from the activity of hundreds of neurons recorded in motor and premotor cortex as rhesus monkeys performed self-timed hand movements. During the delay periods, when animals had to estimate temporal intervals and prepare hand movements, neuronal ensemble activity encoded both the time that elapsed from the previous hand movement and the time until the onset of the next. The neurons that were most informative of these temporal intervals increased or decreased their rates throughout the delay until reaching a threshold value, at which point a movement was initiated. Variability in the self-timed delays was explainable by the variability of neuronal rates, but not of the threshold. In addition to predicting temporal intervals, the same neuronal ensemble activity was informative for generating predictions that dissociated the delay periods of the task from the movement periods. Left hemispheric areas were the best source of predictions in one bilaterally implanted monkey overtrained to perform the task with the right hand. However, after that monkey learned to perform the task with the left hand, its left hemisphere continued and the right hemisphere started contributing to the prediction. We suggest that decoding of temporal intervals from bilaterally recorded cortical ensembles could improve the performance of neural prostheses for restoration of motor function.

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Ruess, Miriam, Roland Thomaschke, and Andrea Kiesel. "The Time Course of Intentional Binding for Late Effects." Timing & Time Perception 6, no. 1 (April 10, 2018): 54–70. http://dx.doi.org/10.1163/22134468-00002099.

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Stimuli elicited by one’s own actions (i.e., effects) are perceived as temporally earlier compared to stimuli not elicited by one’s own actions. This phenomenon is referred to as intentional binding (IB), and is commonly used as an implicit measure of sense of agency. Typically, IB is investigated by employing the so-called clock paradigm, in which participants are instructed to press a key (i.e., perform an action), which is followed by a tone (i.e., an effect), while presented with a rotating clock hand. Participants are then asked to estimate the position of the clock hand at tone onset. This time point estimate is compared to a baseline estimate where the tone is presented without any preceding action. In the present study, we investigated IB for effects occurring after relatively long delay durations (500 ms, 650 ms, 800 ms), while manipulating the temporal predictability of the delay duration. We observed an increase of IB for longer delay durations, whereas the temporal predictability did not significantly influence the magnitude of IB. This extends previous findings obtained with the clock paradigm, which have shown an increase of IB for very short delay ranges (<250 ms), but a decrease for intermediate delay ranges up to delay durations of 650 ms. Our findings, thus, indicate rather complex temporal dynamics of IB that might look similar to a wave-shaped function.

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Beer, Susanne, and Lambert Wanninger. "Temporal Stability of GPS Transmitter Group Delay Variations." Sensors 18, no. 6 (May 29, 2018): 1744. http://dx.doi.org/10.3390/s18061744.

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Kirby, Kris N. "One-year temporal stability of delay-discount rates." Psychonomic Bulletin & Review 16, no. 3 (June 2009): 457–62. http://dx.doi.org/10.3758/pbr.16.3.457.

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Ibbotson, Michael R., and Colin W. G. Clifford. "Characterising temporal delay filters in biological motion detectors." Vision Research 41, no. 18 (August 2001): 2311–23. http://dx.doi.org/10.1016/s0042-6989(01)00126-2.

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Leibold, Christian, and J. Leo van Hemmen. "Temporal receptive fields, spikes, and Hebbian delay selection." Neural Networks 14, no. 6-7 (July 2001): 805–13. http://dx.doi.org/10.1016/s0893-6080(01)00081-8.

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Bhowmick, Sourav K., Dibakar Ghosh, Pousali Roy, Syamal K. Dana, K. Murali, and Sudeshna Sinha. "Targeting Temporal Patterns in Time-Delay Chaotic Systems." International Journal of Bifurcation and Chaos 24, no. 02 (February 2014): 1450014. http://dx.doi.org/10.1142/s021812741450014x.

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We report a control of chaos in time-delayed nonlinear systems, which constitute an important class of infinite-dimensional systems. Our method simply entails clipping of a single state variable of the chaotic system to a threshold value. The method is easier to implement since only a single variable is needed to be accessible for measurement and resetting. A variation of the threshold level yields a wide variety of regular temporal patterns. The important advantage of this method is that it generates a look-up table, which can be readily used to obtain a desired behavior by just setting the corresponding threshold value. Such a feature makes this control of chaotic systems attractive for potential applications. We physically verify the technique in an electronic experiment.

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CHEN, KE, DAHONG XIE, and HUISHENG CHI. "SPEAKER IDENTIFICATION USING TIME-DELAY HMEs." International Journal of Neural Systems 07, no. 01 (March 1996): 29–43. http://dx.doi.org/10.1142/s012906579600004x.

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In this paper, we extend the Hierarchical Mixture of Experts (HME) to temporal processing and explore it for a substantial problem, that of text-dependent speaker identification. For a specific multiway classification, we propose a generalized Bernoulli density instead of the multinomial logit density to avoid the instability during training. Time-delay technique is applied for spatio-temporal processing in the HME and a combining scheme is presented for combining multiple time-delay HMEs in order to complete a multi-scale analysis for the temporal data. Using the time-delay HME along with the EM algorithm as well as the combination of multiple time-delay HMEs, the speaker identification system has a good performance and yields significantly fast training. We have also addressed some issues about the time-delay techniques in the HME.

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Fascianelli, Valeria, Satoshi Tsujimoto, Encarni Marcos, and Aldo Genovesio. "Autocorrelation Structure in the Macaque Dorsolateral, But not Orbital or Polar, Prefrontal Cortex Predicts Response-Coding Strength in a Visually Cued Strategy Task." Cerebral Cortex 29, no. 1 (December 8, 2017): 230–41. http://dx.doi.org/10.1093/cercor/bhx321.

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Abstract In previous work, we studied the activity of neurons in the dorsolateral (PFdl), orbital (PFo), and polar (PFp) prefrontal cortex while monkeys performed a strategy task with 2 spatial goals. A cue instructed 1 of 2 strategies in each trial: stay with the previous goal or shift to the alternative goal. Each trial started with a fixation period, followed by a cue. Subsequently, a delay period was followed by a “go” signal that instructed the monkeys to choose one goal. After each choice, feedback was provided. In this study, we focused on the temporal receptive fields of the neurons, as measured by the decay in autocorrelation (time constant) during the fixation period, and examined the relationship with response and strategy coding. The temporal receptive field in PFdl correlated with the response-related but not with the strategy-related modulation in the delay and the feedback periods: neurons with longer time constants in PFdl tended to show stronger and more prolonged response coding. No such correlation was found in PFp or PFo. These findings demonstrate that the temporal specialization of neurons for temporally extended computations is predictive of response coding, and neurons in PFdl, but not PFp or PFo, develop such predictive properties.

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Smotherman, Michael, and Walter Metzner. "Auditory-Feedback Control of Temporal Call Patterns in Echolocating Horseshoe Bats." Journal of Neurophysiology 93, no. 3 (March 2005): 1295–303. http://dx.doi.org/10.1152/jn.00653.2004.

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During flight, auditory feedback causes horseshoe bats to adjust the duration and repetition rate of their vocalizations in a context-dependent manner. As these bats approach a target, they make finely graded adjustments in call duration and interpulse interval (IPI), but their echolocation behavior is also characterized by abrupt transitions in overall temporal calling patterns. We investigated the relative contributions of two prominent acoustic cues, echo frequency and delay, toward the control of both graded and transitional changes in call duration and IPI. Echoes returning at frequencies above the emitted call frequency caused bats to switch from long single calls to pairs of short calls (doublets). Alternatively, increasing echo delay caused progressive increases in IPI but caused no accompanying changes in call duration. When frequency shifts were combined with changing echo delays, echo delay altered the IPIs occurring between doublets but not the IPI within a doublet. When the echo mimic was replaced by presentation of either an artificial constant-frequency (CF) stimulus or a frequency-modulated (FM) stimulus, each designed to mimic major components of the echo acoustic structure, we found that CF stimuli could trigger the switch to doublets, but changing CF delay had no influence on IPI, whereas the timing of an FM-sweep presentation had a strong effect on IPI. Because CF and FM sounds are known to be processed separately in the bat auditory system, the results indicate that at least two distinct neural feedback pathways may be used to control the temporal patterns of vocalization in echolocating horseshoe bats.

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Read, Jenny C. A., and Bruce G. Cumming. "Effect of Interocular Delay on Disparity-Selective V1 Neurons: Relationship to Stereoacuity and the Pulfrich Effect." Journal of Neurophysiology 94, no. 2 (August 2005): 1541–53. http://dx.doi.org/10.1152/jn.01177.2004.

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The temporal properties of disparity-sensitive neurons place important temporal constraints on stereo matching. We examined these constraints by measuring the responses of disparity-selective neurons in striate cortex of awake behaving monkeys to random-dot stereograms that contained interocular delays. Disparity selectivity was gradually abolished by increasing interocular delay (when the delay exceeds the integration time, the inputs from the 2 eyes become uncorrelated). The amplitude of the disparity-selective response was a Gaussian function of interocular delay, with a mean of 16 ms (±5 ms, SD). Psychophysical measures of stereoacuity, in both monkey and human observers, showed a closely similar dependency on time, suggesting that temporal integration in V1 neurons is what determines psychophysical matching constraints over time. There was a slight but consistent asymmetry in the neuronal responses, as if the optimum stimulus is one in which the right stimulus leads by about 4 ms. Because all recordings were made in the left hemisphere, this probably reflects nasotemporal differences in conduction times; psychophysical data are compatible with this interpretation. In only a few neurons (5/72), interocular delay caused a change in the preferred disparity. Such tilted disparity/delay profiles have been invoked previously to explain depth perception in the stroboscopic version of the Pulfrich effect (and other variants). However, the great majority of the neurons did not show tilted disparity/delay profiles. This suggests that either the activity of these neurons is ignored when viewing Pulfrich stimuli, or that current theories relating neuronal properties to perception in the Pulfrich effect need to be reevaluated.

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Chen, Wei, Zongping Li, Can Liu, and Yi Ai. "A Deep Learning Model with Conv-LSTM Networks for Subway Passenger Congestion Delay Prediction." Journal of Advanced Transportation 2021 (May 15, 2021): 1–10. http://dx.doi.org/10.1155/2021/6645214.

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When urban rail transit is faced with a large number of commuter passengers during peak periods, passengers are often waiting for the next train because the subway is running at full load, which causes delays to the overall travel time of passengers. The calculation and prediction of the congestion delay in subway stations can guide the operation department and passengers to make better planning and selection. In this paper, we use a new method based on deep learning technology to evaluate the congestion delay of subway stations. Firstly, we use automatic fare collection (AFC) system data to evaluate the congestion delays of stations. Then, we use a convolutional long short-term memory (Conv-LSTM) network to extract spatial and temporal characteristics to solve the short-term prediction problem of the subway congestion delay in the network structure. The spatiotemporal variables include inbound passenger flow, outbound passenger flow, number of passengers delayed, and average delay time. As a spatiotemporal sequence, the input and prediction targets are both spatiotemporal three-dimensional tensors in the end-to-end training model. The effectiveness of the method is verified by a case study of the Chongqing Rail Transit. Experimental results show that Conv-LSTM is better than the benchmark models in capturing spatial and temporal correlation.

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Kirui, Pius Kipng’etich, Eike Reinosch, Noorlaila Isya, Björn Riedel, and Markus Gerke. "Mitigation of Atmospheric Artefacts in Multi Temporal InSAR: A Review." PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science 89, no. 3 (April 19, 2021): 251–72. http://dx.doi.org/10.1007/s41064-021-00138-z.

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AbstractThe complexity of the atmosphere renders the modelling of the atmospheric delay in multi temporal InSAR difficult. This limits the potential of achieving millimetre accuracy of InSAR-derived deformation measurements. In this paper we review advances in tropospheric delay modelling in InSAR, tropospheric correction methods and integration of the correction methods within existing multi temporal algorithms. Furthermore, we investigate ingestion of the correction techniques by different InSAR applications, accuracy performance metrics and uncertainties of InSAR derived measurements attributed to tropospheric delay. Spatiotemporal modelling of atmospheric delay has evolved and can now be regarded as a spatially correlated turbulent delay with varying degree of anisotropy random in time and topographically correlated seasonal stratified delay. Tropospheric corrections methods performance is restricted to a case by case basis and ingestion of these methods by different applications remains limited due to lack of their integration into existing algorithms. Accuracy and uncertainty assessments remain challenging with most studies adopting simple statistical metrics. While advances have been made in tropospheric modelling, challenges remain for the calibration of atmospheric delay due to lack of data or limited resolution and fusion of multiple techniques for optimal performance.

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Urgolites, Zhisen J., Ramona O. Hopkins, and Larry R. Squire. "Medial temporal lobe and topographical memory." Proceedings of the National Academy of Sciences 114, no. 32 (July 24, 2017): 8626–30. http://dx.doi.org/10.1073/pnas.1708963114.

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There has been interest in the idea that medial temporal lobe (MTL) structures might be especially important for spatial processing and spatial memory. We tested the proposal that the MTL has a specific role in topographical memory as assessed in tasks of scene memory where the viewpoint shifts from study to test. Building on materials used previously for such studies, we administered three different tasks in a total of nine conditions. Participants studied a scene depicting four hills of different shapes and sizes and made a choice among four test images. In the Rotation task, the correct choice depicted the study scene from a shifted perspective. MTL patients succeeded when the study and test images were presented together but failed the moment the study scene was removed (even at a 0-s delay). In the No-Rotation task, the correct choice was a duplicate of the study scene. Patients were impaired to the same extent in the No-Rotation and Rotation tasks after matching for difficulty. Thus, an inability to accommodate changes in viewpoint does not account for patient impairment. In the Nonspatial–Perceptual task, the correct choice depicted the same overall coloring as the study scene. Patients were intact at a 2-s delay but failed at longer, distraction-filled delays. The different results for the spatial and nonspatial tasks are discussed in terms of differences in demand on working memory. We suggest that the difficulty of the spatial tasks rests on the neocortex and on the limitations of working memory, not on the MTL.

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Sugano, Yoshimori, Mirjam Keetels, and Jean Vroomen. "The build-up and transfer of sensorimotor temporal recalibration measured via a synchronization task." Seeing and Perceiving 25 (2012): 136. http://dx.doi.org/10.1163/187847612x647685.

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The timing relation between a motor action and the sensory consequences of that action can be adapted by exposing participants to artificially delayed feedback (temporal recalibration; Heron et al., 2009; Keetels and Vroomen, 2012; Stekelenburg et al., 2011; Stetson et al., 2006; Sugano et al., 2010). Here, we demonstrate that a sensorimotor synchronization task (i.e., tapping the index finger in synchrony with a pacing signal) can be used as a measure of temporal recalibration. Participants were first exposed to a constant delay (∼150 ms) between a voluntary action (a finger tap) and an external feedback stimulus of that action (a visual flash or auditory tone). A subjective ‘no-delay’ condition (∼50 ms) served as baseline. After a short exposure phase to delayed feedback participants performed the tapping task in which they tapped their finger in synchrony with a flash or tone. Temporal recalibration manifested itself in that taps were given ∼20 ms earlier after exposure to 150 ms delays than 50 ms delays. This effect built up quickly (within 60 taps) and was bigger for auditory than visual adapters. In Experiment 2, we tested whether temporal recalibration would transfer across modalities by switching the modality of the adapter and pacing signal. Temporal recalibration transferred from visual adapters to auditory pacers, but not from auditory adapters to visual pacers. This asymmetric transfer suggests that sensory-specific effects are at play.

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Senn, Walter, Martin Schneider, and Berthold Ruf. "Activity-Dependent Development of Axonal and Dendritic Delays, or, Why Synaptic Transmission Should Be Unreliable." Neural Computation 14, no. 3 (March 1, 2002): 583–619. http://dx.doi.org/10.1162/089976602317250915.

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Systematic temporal relations between single neuronal activities or population activities are ubiquitous in the brain. No experimental evidence, however, exists for a direct modification of neuronal delays during Hebbian-type stimulation protocols. We show that in fact an explicit delay adaptation is not needed if one assumes that the synaptic strengths are modified according to the recently observed temporally asymmetric learning rule with the downregulating branch dominating the upregulating branch. During development, slow, unbiased fluctuations in the transmission time, together with temporally correlated network activity, may control neural growth and implicitly induce drifts in the axonal delays and dendritic latencies. These delays and latencies become optimally tuned in the sense that the synaptic response tends to peak in the soma of the postsynaptic cell if this is most likely to fire. The nature of the selection process requires unreliable synapses in order to give successful synapses an evolutionary advantage over the others. The width of the learning function also determines the preferred dendritic delay and the preferred width of the postsynaptic response. Hence, it may implicitly determine whether a synaptic connection provides a precisely timed or a broadly tuned “contextual” signal.

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Lo, E. H., J. Rogowska, P. Bogorodzki, M. Trocha, K. Matsumoto, B. Saffran, and G. L. Wolf. "Temporal Correlation Analysis of Penumbral Dynamics in Focal Cerebral Ischemia." Journal of Cerebral Blood Flow & Metabolism 16, no. 1 (January 1996): 60–68. http://dx.doi.org/10.1097/00004647-199601000-00007.

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A novel temporal correlation technique was used to map the first-pass transit of iodinated contrast agents through the brain. Transit profiles after bolus injections were measured with dynamic computed tomography (CT) scanning (1 image/s over 50 s). A rabbit model of focal cerebral ischemia (n = 6) was used, and dynamic CT scans were performed at 30, 60, 90, and 120 min postocclusion. Within the ischemic core, no bolus transit was detectable, demonstrating that complete ischemia was present after arterial occlusion. In the periphery of the ischemic distribution, transit dynamics showed smaller peaks, broadened profiles, and overall delay in bolus transit. A cross-correlation method was used to generate maps of delays in ischemic transit profiles compared with normal transit profiles from the contralateral hemisphere. These maps showed that penumbral regions surrounding the ischemic core had significantly delayed bolus transit profiles. Enlargement of the ischemic core over time (from 30 to 120 min postocclusion) was primarily accomplished by the progressive deterioration of the penumbral regions. These results suggest that (a) temporal correlation methods can define regions of abnormal perfusion in focal cerebral ischemia, (b) peripheral regions of focal cerebral ischemia are characterized by delays in bolus transit profiles, and (c) these regions of bolus transit delay deteriorate over time and thus represent a hemodynamic penumbra.

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Toutounji, Hazem, Johannes Schumacher, and Gordon Pipa. "Homeostatic Plasticity for Single Node Delay-Coupled Reservoir Computing." Neural Computation 27, no. 6 (June 2015): 1159–85. http://dx.doi.org/10.1162/neco_a_00737.

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Supplementing a differential equation with delays results in an infinite-dimensional dynamical system. This property provides the basis for a reservoir computing architecture, where the recurrent neural network is replaced by a single nonlinear node, delay-coupled to itself. Instead of the spatial topology of a network, subunits in the delay-coupled reservoir are multiplexed in time along one delay span of the system. The computational power of the reservoir is contingent on this temporal multiplexing. Here, we learn optimal temporal multiplexing by means of a biologically inspired homeostatic plasticity mechanism. Plasticity acts locally and changes the distances between the subunits along the delay, depending on how responsive these subunits are to the input. After analytically deriving the learning mechanism, we illustrate its role in improving the reservoir’s computational power. To this end, we investigate, first, the increase of the reservoir’s memory capacity. Second, we predict a NARMA-10 time series, showing that plasticity reduces the normalized root-mean-square error by more than 20%. Third, we discuss plasticity’s influence on the reservoir’s input-information capacity, the coupling strength between subunits, and the distribution of the readout coefficients.

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Fisher, Brian T., Howard A. Johnsen, Steven G. Buckley, and David W. Hahn. "Temporal Gating for the Optimization of Laser-Induced Breakdown Spectroscopy Detection and Analysis of Toxic Metals." Applied Spectroscopy 55, no. 10 (October 2001): 1312–19. http://dx.doi.org/10.1366/0003702011953667.

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Optimal temporal gating for laser-induced breakdown spectroscopy (LIBS) analysis was investigated for a select group of toxic metals, namely the Resource Conservation and Recovery Act (RCRA) metals arsenic, beryllium, cadmium, chromium, lead, and mercury. The differing rates of decay between the continuum plasma emission and the atomic emission were used as a means to maximize the signal-to-noise ratio of the atomic emission lines for these six metal species. Detection windows were investigated corresponding to delay times from 2 to 50 μs following the plasma-initiating laser pulse. For the current experimental conditions, it is concluded that the relatively short delay time of 12 μs is optimal for the detection of arsenic, beryllium, cadmium, and mercury, while a longer delay time of 50 μs is optimal for the detection of chromium and lead. The reduced atomic emission intensity at relatively long delay times is compensated for by the use of long detector gate widths. Estimated detection limits are reported for the six metal species based on the optimized temporal gating and ensemble averaging of multiple laser pulses, and the implications for simultaneous metals monitoring are discussed.

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Rouby, Catherine, and André Holley. "Temporal Competition between Odorants: Effect of Different Time Intervals on the Perception of Monorhinic and Dichorhinic Binary Mixtures." Perception 24, no. 9 (September 1995): 1083–97. http://dx.doi.org/10.1068/p241083.

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Backward masking and its possible connection with the perception of odour mixtures has been investigated. Temporal competition between odorants in a binary mixture was tested by artificially creating a delay between one odour (the target) and a second, stronger, odour (the mask) during a single natural sniff. To test the influence of central versus peripheral competition, the same mixture was presented either monorhinically or dichorhinically. The delay (100 to 400 ms) did not influence intensity perception, indicating that intensities are integrated during the sniff irrespective of the temporal arrangement. In contrast, the number of qualities perceived was influenced by the delay: delays of 200 to 400 ms gave significant increases in the frequency of detection of a mixture, whereas synchronous mixtures favoured the perception of a single odour. Masking was also significantly stronger in dichorhinic mixtures. These effects are discussed in terms of retroactive masking which seems to be enhanced by dichorhinic mixtures, suggesting that masking has an important central component.

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Hales, J. B., and J. B. Brewer. "The timing of associative memory formation: frontal lobe and anterior medial temporal lobe activity at associative binding predicts memory." Journal of Neurophysiology 105, no. 4 (April 2011): 1454–63. http://dx.doi.org/10.1152/jn.00902.2010.

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The process of associating items encountered over time and across variable time delays is fundamental for creating memories in daily life, such as for stories and episodes. Forming associative memory for temporally discontiguous items involves medial temporal lobe structures and additional neocortical processing regions, including prefrontal cortex, parietal lobe, and lateral occipital regions. However, most prior memory studies, using concurrently presented stimuli, have failed to examine the temporal aspect of successful associative memory formation to identify when activity in these brain regions is predictive of associative memory formation. In the current study, functional MRI data were acquired while subjects were shown pairs of sequentially presented visual images with a fixed interitem delay within pairs. This design allowed the entire time course of the trial to be analyzed, starting from onset of the first item, across the 5.5-s delay period, and through offset of the second item. Subjects then completed a postscan recognition test for the items and associations they encoded during the scan and their confidence for each. After controlling for item-memory strength, we isolated brain regions selectively involved in associative encoding. Consistent with prior findings, increased regional activity predicting subsequent associative memory success was found in anterior medial temporal lobe regions of left perirhinal and entorhinal cortices and in left prefrontal cortex and lateral occipital regions. The temporal separation within each pair, however, allowed extension of these findings by isolating the timing of regional involvement, showing that increased response in these regions occurs during binding but not during maintenance.

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Guo, Ziyu, Guangxu Mei, Shijun Liu, Li Pan, Lei Bian, Hongwu Tang, and Diansheng Wang. "SGDAN—A Spatio-Temporal Graph Dual-Attention Neural Network for Quantified Flight Delay Prediction." Sensors 20, no. 22 (November 11, 2020): 6433. http://dx.doi.org/10.3390/s20226433.

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There has been a lot of research on flight delays. But it is more useful and difficult to estimate the departure delay time especially three hours before the scheduled time of departure, from which passengers can reasonably plan their travel time and the airline and airport staff can schedule flights more reasonably. In this paper, we develop a Spatio-temporal Graph Dual-Attention Neural Network (SGDAN) to learn the departure delay time for each flight with real-time conditions at three hours before the scheduled time of departure. Specifically, it first models the air traffic network as graph sequences, what is, using a heterogeneous graph to model a flight and its adjacent flights with the same departure or arrival airport in a special time interval, and using a sequence to model the flight and its previous flights that share the same aircraft. The main contributions of this paper are using heterogeneous graph-level attention to learn the influence between the flight and its adjacent flight together with sequence-level attention to learn the influence between the flight and its previous flight in the flight sequence. With aggregating features from the learned influence from both graph-level and sequence-level attention, SGDAN can generate node embedding to estimate the departure delay time. Experiments on a real-world large-scale data set show that SGDAN produces better results than state-of-the-art models in the accurate flight delay time estimation task.

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Macaskill, Anne C., Maree J. Hunt, and Taciano L. Milfont. "On the associations between delay discounting and temporal thinking." Personality and Individual Differences 141 (April 2019): 166–72. http://dx.doi.org/10.1016/j.paid.2019.01.007.

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DESMET, G. D., D. C. KNOCKAERT, and H. J. BOBBAERS. "Temporal arteritis: the silent presentation and delay in diagnosis." Journal of Internal Medicine 227, no. 4 (April 1990): 237–40. http://dx.doi.org/10.1111/j.1365-2796.1990.tb00151.x.

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Witanachchi, S., and P. Mukherjee. "Role of temporal delay in dual‐laser ablated plumes." Journal of Vacuum Science & Technology A: Vacuum, Surfaces, and Films 13, no. 3 (May 1995): 1171–74. http://dx.doi.org/10.1116/1.579856.

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Spang, K., and M. Morgan. "Cortical correlates of stereoscopic depth produced by temporal delay." Journal of Vision 8, no. 9 (July 1, 2008): 10. http://dx.doi.org/10.1167/8.9.10.

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Zhou, Mingyang, Hongjun Liu, Qibing Sun, Nan Huang, and Zhaolu Wang. "Temporal cloak based on tunable optical delay and advance." Optics Express 23, no. 5 (March 2, 2015): 6543. http://dx.doi.org/10.1364/oe.23.006543.

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Duro, Dr Richard J., and J. Santos. "Modelling Temporal Series Through Synaptic Delay-based Neural Networks." Neural Computing & Applications 11, no. 3-4 (June 1, 2003): 224–37. http://dx.doi.org/10.1007/s00521-003-0359-y.

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Niemi, Jussi, and Päivi Koivuselkä-Sallinen. "Temporal delay and lexical retrieval in narratives: Aphasiological observations." Journal of Communication Disorders 20, no. 2 (April 1987): 171–86. http://dx.doi.org/10.1016/0021-9924(87)90008-6.

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Journal articles on the topic 'Temporal delay'

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