287 resultados para Synchrony


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Surveys were conducted in the Philippines from 1995 to 1997 to examine relationships between production environment variables (agroecosystem, synchrony of planting, and varieties planted) and the occurrence of rice tungro disease epidemics using correspondence analyses. The sites covered were Isabela, Nueva Ecija, North Cotabato, and Bohol provinces as well as Bicol region. Tungro disease incidence in farmers’ fields was assessed visually based on typical symptoms. In addition, leaf samples were collected from each field and indexed serologically by enzyme-linked immunosorbent assay for the presence of Rice tungro bacilliform (RTBV) and Rice tungro spherical (RTSV) viruses. Thus, relationships between the production environment variables and four disease variables — visual incidence and double RTBV and RTSV, single RTSV, and single RTBV infections — were examined. A higher association was observed between site and varieties planted as well as site and synchrony of planting than between site and agroecosystem or site and disease variables (visual incidence, double RTBV and RTSV and single RTSV infections). Disease variables depended on both varieties planted and synchrony of planting and correspondence analysis revealed that the low disease incidence in Nueva Ecija was associated with synchronous planting while the high disease incidence in Isabela was associated with the planting of susceptible varieties and asynchronous planting. Such findings suggest that the relationship between the last two factors at a given site is critical to predicting tungro occurrence. Moreover, correspondence analysis of the relationship among disease variables revealed that tungro incidence is associated with not only double RTBV and RTSV infections but also single RTSV infections. Implications of these results on tungro epidemiology and management are discussed.

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This study investigated movement synchronization of players within and between teams during competitive association football performance. Cluster phase analysis was introduced as a method to assess synchronies between whole teams and between individual players with their team as a function of time, ball possession and field direction. Measures of dispersion (SD) and regularity (sample entropy – SampEn – and cross sample entropy – Cross-SampEn) were used to quantify the magnitude and structure of synchrony. Large synergistic relations within each professional team sport collective were observed, particularly in the longitudinal direction of the field (0.89 ± 0.12) compared to the lateral direction (0.73 ± 0.16, p < .01). The coupling between the group measures of the two teams also revealed that changes in the synchrony of each team were intimately related (Cross-SampEn values of 0.02 ± 0.01). Interestingly, ball possession did not influence team synchronization levels. In player–team synchronization, individuals tended to be coordinated under near in-phase modes with team behavior (mean ranges between −7 and 5° of relative phase). The magnitudes of variations were low, but more irregular in time, for the longitudinal (SD: 18 ± 3°; SampEn: 0.07 ± 0.01), compared to the lateral direction (SD: 28 ± 5°; SampEn: 0.06 ± 0.01, p < .05) on-field. Increases in regularity were also observed between the first (SampEn: 0.07 ± 0.01) and second half (SampEn: 0.06 ± 0.01, p < .05) of the observed competitive game. Findings suggest that the method of analysis introduced in the current study may offer a suitable tool for examining team’s synchronization behaviors and the mutual influence of each team’s cohesiveness in competing social collectives.

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The precise timing of individual signals in response to those of signaling neighbors is seen in many animal species. Synchrony is the most striking of the resultant timing patterns. One of the best examples of acoustic synchrony is in katydid choruses where males produce chirps with a high degree of temporal overlap. Cooperative hypotheses that speculate on the evolutionary origins of acousti synchrony include the preservation of the species-specific call pattern, reduced predation risks, and increased call intensity. An alternative suggestion is that synchrony evolved as an epiphenomenon of competition between males in response to a female preference for chirps that lead other chirps. Previous models investigating the evolutionary origins of synchrony focused only on intrasexual competitive interactions. We investigated both competitive and cooperative hypotheses for the evolution of synchrony in the katydid Mecopoda ``Chirper'' using physiologically and ecologically realistic simulation models incorporating the natural variation in call features, ecology, female preferences, and spacing patterns, specifically aggregation. We found that although a female preference for leading chirps enables synchronous males to have some selective advantage, it is the female preference for the increased intensity of aggregations of synchronous males that enables synchrony to evolve as an evolutionarily stable strategy.

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This article develops the Synchronous Matching Adaptive Resonance Theory (SMART) neural model to explain how the brain may coordinate multiple levels of thalamocortical and corticocortical processing to rapidly learn, and stably remember, important information about a changing world. The model clarifies how bottom-up and top-down processes work together to realize this goal, notably how processes of learning, expectation, attention, resonance, and synchrony are coordinated. The model hereby clarifies, for the first time, how the following levels of brain organization coexist to realize cognitive processing properties that regulate fast learning and stable memory of brain representations: single cell properties, such as spiking dynamics, spike-timing-dependent plasticity (STDP), and acetylcholine modulation; detailed laminar thalamic and cortical circuit designs and their interactions; aggregate cell recordings, such as current-source densities and local field potentials; and single cell and large-scale inter-areal oscillations in the gamma and beta frequency domains. In particular, the model predicts how laminar circuits of multiple cortical areas interact with primary and higher-order specific thalamic nuclei and nonspecific thalamic nuclei to carry out attentive visual learning and information processing. The model simulates how synchronization of neuronal spiking occurs within and across brain regions, and triggers STDP. Matches between bottom-up adaptively filtered input patterns and learned top-down expectations cause gamma oscillations that support attention, resonance, and learning. Mismatches inhibit learning while causing beta oscillations during reset and hypothesis testing operations that are initiated in the deeper cortical layers. The generality of learned recognition codes is controlled by a vigilance process mediated by acetylcholine.

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How do our brains transform the "blooming buzzing confusion" of daily experience into a coherent sense of self that can learn and selectively attend to important information? How do local signals at multiple processing stages, none of which has a global view of brain dynamics or behavioral outcomes, trigger learning at multiple synaptic sites when appropriate, and prevent learning when inappropriate, to achieve useful behavioral goals in a continually changing world? How does the brain allow synaptic plasticity at a remarkably rapid rate, as anyone who has gone to an exciting movie is readily aware, yet also protect useful memories from catastrophic forgetting? A neural model provides a unified answer by explaining and quantitatively simulating data about single cell biophysics and neurophysiology, laminar neuroanatomy, aggregate cell recordings (current-source densities, local field potentials), large-scale oscillations (beta, gamma), and spike-timing dependent plasticity, and functionally linking them all to cognitive information processing requirements.

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© 2015 Young, Smith, Coutlee and Huettel.Individuals with autistic spectrum disorders exhibit distinct personality traits linked to attentional, social, and affective functions, and those traits are expressed with varying levels of severity in the neurotypical and subclinical population. Variation in autistic traits has been linked to reduced functional and structural connectivity (i.e., underconnectivity, or reduced synchrony) with neural networks modulated by attentional, social, and affective functions. Yet, it remains unclear whether reduced synchrony between these neural networks contributes to autistic traits. To investigate this issue, we used functional magnetic resonance imaging to record brain activation while neurotypical participants who varied in their subclinical scores on the Autism-Spectrum Quotient (AQ) viewed alternating blocks of social and nonsocial stimuli (i.e., images of faces and of landscape scenes). We used independent component analysis (ICA) combined with a spatiotemporal regression to quantify synchrony between neural networks. Our results indicated that decreased synchrony between the executive control network (ECN) and a face-scene network (FSN) predicted higher scores on the AQ. This relationship was not explained by individual differences in head motion, preferences for faces, or personality variables related to social cognition. Our findings build on clinical reports by demonstrating that reduced synchrony between distinct neural networks contributes to a range of subclinical autistic traits.

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The oceans have shown a recent rapid and accelerating rise in temperature with, given the close link between temperature and marine organisms, pronounced effects on ecosystems. Here we describe for the first time a globally synchronous pattern of pulsed short period (�1 year long) emanations of warm sea surface temperature anomalies from tropical seas towards the poles on the shelf/slope with an intensification of the warming after the 1976/1977, 1986/1987 and 1997/1998 El Nin˜os. On the eastern margins of continents the anomalies propagate towards the poles in part by largely baroclinic boundary currents, reinforced by regional atmospheric warming. The processes contributing to the less continuous warm anomalies on western margins are linked to the transfer of warmth from adjacent western boundary currents. These climate induced events show a close parallelism with the timing of ecosystem changes in shelf seas, important for fisheries and ecosystem services, and melting of sea-ice.

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Laying hens generally choose to aggregate, but the extent to which the environments in which we house them impact on social group dynamics is not known. In this paper the effect of pen environment on spatial clustering is considered. Twelve groups of four laying hens were studied under three environmental conditions: wire floor (W), shavings (Sh) and perches, peat, nestbox and shavings (PPN). Groups experienced each environment twice, for five weeks each time, in a systematic order that varied from group to group. Video recordings were made one day per week for 30 weeks. To determine level of clustering, we recorded positional data from a randomly selected 20-min excerpt per video (a total of 20 min x 360 videos analysed). On screen, pens were divided into six equal areas. In addition, PPN pens were divided into an additional four (sub) areas, to account for the use of perches (one area per half perch). Every 5 s, we recorded the location of each bird and calculated location use over time, feeding synchrony and cluster scores for each environment. Feeding synchrony and cluster scores were compared against unweighted and weighted (according to observed proportional location use) Poisson distributions to distinguish between resource and social attraction.

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During various periods of Late Quaternary glaciation, small ice-sheets, -caps, -fields and valley glaciers, occupied the mountains and uplands of Far NE Russia (including the Verkhoyansk, Suntar-Khayata, and Chersky Mountains; the KolymaeAnyuy and Koryak Highlands; and much of the Kamchatka and Chukchi
Peninsulas). Here, the margins of former glaciers across this region are constrained through the comprehensive mapping of moraines from remote sensing data (Landsat 7 ETM+ satellite images; ASTER Global Digital Elevation Model (GDEM2); and Viewfinder Panorama DEM data). A total of 8414 moraines
are mapped, and this record is integrated with a series of published age-estimates (n = 25), considered to chronologically-constrain former ice-margin positions. Geomorphological and chronological data are compiled in a Geographic Information System (GIS) to produce ‘best estimate’ reconstructions of ice extent during the global Last Glacial Maximum (gLGM) and, to a lesser degree, during earlier phases of glaciation. The data reveal that much of Far NE Russia (~1,092,427 km2) preserves a glaciated landscape (i.e. is bounded by moraines), but there is no evidence of former ice masses having extended more than 270 km beyond mountain centres (suggesting that, during the Late Quaternary, the region has not been occupied by extensive ice sheets). During the gLGM, specifically, glaciers occupied ~253,000 km2, and rarely extended more than 50 km in length. During earlier (pre-gLGM) periods, glaciers were more extensive, though the timing of former glaciation, and the maximum Quaternary extent, appears to have been asynchronous across the region, and out-of-phase with ice-extent maxima elsewhere in the Northern Hemisphere. This glacial history is partly explained through consideration of climatic-forcing
(particularly moisture-availability, solar insolation and albedo), though topographic-controls upon the former extent and dynamics of glaciers are also considered, as are topographic-controls upon moraine deposition and preservation. Ultimately, our ability to understand the glacial and climatic history of this region is restricted when the geomorphological-record alone is considered, particularly as directly-dated glacial deposits are few, and topographic and climatic controls upon the moraine record are difficult to
distinguish.

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Behavioural synchrony has been a popular topic of research in group living animals, but has so far lacked a standard approach. Previous studies have varied greatly in the number of behavioural states they have considered and the size of groups investigated. Here, a model of behavioural synchrony was used to test four measures of synchrony commonly used (proportion observations 100% conforming, mean proportion of conforming individuals, Ruckstuhl's group mean and the kappa coefficient). The model used scan samples of the behaviour of laying hens, originally categorised in 10 different behavioural states, as a basis for determining the agents' probability of performing behaviour states. We systematically varied the group size and the number of behavioural states in the model. The measures calculated from the behaviour of the model agents were compared against a synchrony factor that determined the 'motivation' of agents in the model to conform to the behaviour of other agents, for model runs with different group sizes and behavioural categories. The results of the model suggest that, of the measures considered, the kappa coefficient is the most suitable measure of synchrony. The kappa coefficient was the only measure of the four tested to control for expected levels of synchrony. Expected levels of synchrony are sensitive to both the number of behaviour states being examined and the size of the group, therefore observed levels of synchrony should be compared against expected levels to provide meaningful standardised measures. © 2012 Elsevier B.V.