Auditory Psychophysics in Birds: the Effects of Unique Noise on Sensitivity

<p>The performances of observers in auditory experiments are likely to be affected by extraneous noise from physiological or neurological sources and also by decision noise. Attempts have been made to measure the characteristics of this noise, in particular its level relative to that of masking noise provided by the experimenter. This study investigated an alternative approach, a method of analysis which seeks to reduce the effects of extraneous noise on measures derived from experimental data. Group-Operating-Characteristic (GOC) analysis was described by Watson (1963) and investigated by Boven (1976). Boven distinguished between common and unique noise. GOC analysis seeks to reduce the effects of unique noise. In the analysis, ratings of the same stimulus on different occasions are sunned. The cumulative frequency distributions of the resulting variable define a GOC curve. This curve is analogous to an ROC curve, but since the effects of unique noise tend to be averaged out during the summation, the GOC is less influenced by extraneous noise. The amount of improvement depends on the relative variance of the unique and common noise (k). Higher levels of unique noise lead to greater improvement. In this study four frequency discrimination experiments were carried out with pigeons as observers, using a three-key operant procedure. In other experiments, computer-simulated observers were used. The first two pigeon experiments, and the simulations, were based on known distributions of common noise. The ROCs for the constructed distributions provided a standard with which the GOC curve could be compared. In all cases the analysis led to improvements in the measures of performance and increased the match of the experimental results and the ideal ROC. The amount of improvement, as well as reflecting the level of unique noise, depended on the number of response categories. With smaller numbers of categories, improvement was reduced and k was underestimated. Since the pigeon observers made only "yes" or "no" responses, the results for the pigeon experiments were compared with the results of simulations with known distributions in order to obtain more accurate estimates of k. The third and fourth pigeon experiments involved frequency discrimination tasks with a standard of 450 Hz and comparison frequencies of 500, 600, 700, 800 and 900 Hz, and 650 Hz, respectively. With the multiple comparison frequencies the results were very variable. This was due to the small number of trials for each frequency and the small number of replications. The results obtained with one comparison frequency were more orderly but, like those of the previous experiment, were impossible to distinguish from those which would be expected if there was no common noise. A final set of experiments was based on a hardware simulation. Signals first used in the fourth pigeon experiment were processed by a system made up of a filter, a zero-axis crossing detector and a simulated observer. The results of these experiments were compatible with the possibility that the amount of unique noise in the pigeon experiments overwhelmed any evidence of common noise.</p>

Auditory Psychophysics in Birds: the Effects of Unique Noise on Sensitivity

<p>The performances of observers in auditory experiments are likely to be affected by extraneous noise from physiological or neurological sources and also by decision noise. Attempts have been made to measure the characteristics of this noise, in particular its level relative to that of masking noise provided by the experimenter. This study investigated an alternative approach, a method of analysis which seeks to reduce the effects of extraneous noise on measures derived from experimental data. Group-Operating-Characteristic (GOC) analysis was described by Watson (1963) and investigated by Boven (1976). Boven distinguished between common and unique noise. GOC analysis seeks to reduce the effects of unique noise. In the analysis, ratings of the same stimulus on different occasions are sunned. The cumulative frequency distributions of the resulting variable define a GOC curve. This curve is analogous to an ROC curve, but since the effects of unique noise tend to be averaged out during the summation, the GOC is less influenced by extraneous noise. The amount of improvement depends on the relative variance of the unique and common noise (k). Higher levels of unique noise lead to greater improvement. In this study four frequency discrimination experiments were carried out with pigeons as observers, using a three-key operant procedure. In other experiments, computer-simulated observers were used. The first two pigeon experiments, and the simulations, were based on known distributions of common noise. The ROCs for the constructed distributions provided a standard with which the GOC curve could be compared. In all cases the analysis led to improvements in the measures of performance and increased the match of the experimental results and the ideal ROC. The amount of improvement, as well as reflecting the level of unique noise, depended on the number of response categories. With smaller numbers of categories, improvement was reduced and k was underestimated. Since the pigeon observers made only "yes" or "no" responses, the results for the pigeon experiments were compared with the results of simulations with known distributions in order to obtain more accurate estimates of k. The third and fourth pigeon experiments involved frequency discrimination tasks with a standard of 450 Hz and comparison frequencies of 500, 600, 700, 800 and 900 Hz, and 650 Hz, respectively. With the multiple comparison frequencies the results were very variable. This was due to the small number of trials for each frequency and the small number of replications. The results obtained with one comparison frequency were more orderly but, like those of the previous experiment, were impossible to distinguish from those which would be expected if there was no common noise. A final set of experiments was based on a hardware simulation. Signals first used in the fourth pigeon experiment were processed by a system made up of a filter, a zero-axis crossing detector and a simulated observer. The results of these experiments were compatible with the possibility that the amount of unique noise in the pigeon experiments overwhelmed any evidence of common noise.</p>

Spatial Phase Synchronisation of Pistachio Alternate Bearing

Nonlinear physics and agroecosystems can be of great relevance in the synchronisations of chaotic oscillators. The endogenous dynamics of the seed production of perennial plant species which include alternate bearing and masting, portray typical synchronisation patterns in nature and can be modelled using a tent map known as a resource budget model (RBM). This study investigates the collective rhythm in 9,562 pistachio trees caused by their endogenous network dynamics and exogenous forces (common noise). Common noise and a local coupling of RBMs are the two primary factors emerging from the bearing phase synchronisation in this orchard. The in-phase/out-of-phase analysis technique quantifying the strength of the phase synchronisation in trees (population /individual) allows us to study the observed spatial synchrony in detail. We demonstrate how three essential factors, i.e. (a) common noise, (b) local direct coupling, and (c) the gradient of the cropping coefficient, explain the spatial synchrony of the orchard. Here, we also show that the methodology employing nonlinear physics to study agroecological systems can be useful for resolving practical problems in agriculture including yield variability and spatial synchrony which often compromise efficient resource management.

Activity Stabilization in a Population Model of Working Memory by Sinusoidal and Noisy Inputs

According to mechanistic theories of working memory (WM), information is retained as stimulus-dependent persistent spiking activity of cortical neural networks. Yet, how this activity is related to changes in the oscillatory profile observed during WM tasks remains a largely open issue. We explore joint effects of input gamma-band oscillations and noise on the dynamics of several firing rate models of WM. The considered models have a metastable active regime, i.e., they demonstrate long-lasting transient post-stimulus firing rate elevation. We start from a single excitatory-inhibitory circuit and demonstrate that either gamma-band or noise input could stabilize the active regime, thus supporting WM retention. We then consider a system of two circuits with excitatory intercoupling. We find that fast coupling allows for better stabilization by common noise compared to independent noise and stronger amplification of this effect by in-phase gamma inputs compared to anti-phase inputs. Finally, we consider a multi-circuit system comprised of two clusters, each containing a group of circuits receiving a common noise input and a group of circuits receiving independent noise. Each cluster is associated with its own local gamma generator, so all its circuits receive gamma-band input in the same phase. We find that gamma-band input differentially stabilizes the activity of the “common-noise” groups compared to the “independent-noise” groups. If the inter-cluster connections are fast, this effect is more pronounced when the gamma-band input is delivered to the clusters in the same phase rather than in the anti-phase. Assuming that the common noise comes from a large-scale distributed WM representation, our results demonstrate that local gamma oscillations can stabilize the activity of the corresponding parts of this representation, with stronger effect for fast long-range connections and synchronized gamma oscillations.

Continuous-Time Mean Field Games with Finite State Space and Common Noise

We formulate and analyze a mathematical framework for continuous-time mean field games with finitely many states and common noise, including a rigorous probabilistic construction of the state process and existence and uniqueness results for the resulting equilibrium system. The key insight is that we can circumvent the master equation and reduce the mean field equilibrium to a system of forward-backward systems of (random) ordinary differential equations by conditioning on common noise events. In the absence of common noise, our setup reduces to that of Gomes, Mohr and Souza (Appl Math Optim 68(1): 99–143, 2013) and Cecchin and Fischer (Appl Math Optim 81(2):253–300, 2020).

Controlled diffusion Mean Field Games with common noise and McKean-Vlasov second order backward SDEs

Рассматривается игра среднего поля с одним внешним шумом, коэффициент диффузии которого включает управление. Доказывается существование слабого решения с релаксацией при некоторых условиях на коэффициент диффузии. Далее, показывается, что при отсутствии этого внешнего шума игра среднего поля описывается обратным стохастическим дифференциальным уравнением типа Маккина-Власова второго порядка.