1,721,264 research outputs found
Temporal dynamics of trauma memory persistence
Full text linkTraumatic events lead to distressing memories, but such memories are made all the worse when they intrude to mind unbidden and recurrently. Intrusive memories and flashbacks after trauma are prominent in several mental disorders, including post-traumatic stress disorder and can persist for years. Critically, the reduction of intrusive memories provides a treatment target. While cognitive and descriptive models for psychological trauma exist, these lack formal quantitative structure and robust empirical validation. Here, using techniques from stochastic process theory, we develop a mechanistically driven, quantitative framework to extend understanding of the temporal dynamic processes of trauma memory. Our approach is to develop a probabilistic description of memory mechanisms to link to the broader goals of trauma treatment. We show how the marginal gains of treatments for intrusive memories can be enhanced as key properties (intervention strength and reminder strength) of the intervention and memory consolidation (probability memories are labile) vary. Parametrizing the framework with empirical data highlights that while emerging interventions to reduce occurrence of intrusive memories can be effective, counterintuitively, weakening multiple reactivation cues may help reduce intrusive memories more than would stronger cues. More broadly, the approach provides a quantitative framework for associating neural mechanisms of memory with broader cognitive processes
The impact of structured higher order interactions on ecological network stability
Full text linkThe impact of higher-order interactions, those involving more than two species, is increasingly appreciated as having the potential to strongly influence the dynamics of complex ecological systems. However, although the critical importance of the structure of pairwise interaction networks is well established, studies of higher-order interactions still largely assume random structures. Here, we demonstrate the strong impact of structured higher-order interactions on simulated ecological communities. We focus on effects caused by interaction modifications within food webs, where a consumer resource interaction is modified by a third species, and for which plausible structures can be hypothesised. We show how interaction modifications introduced under a range of non-random distributions may impact the overall network structure. Local stability and the size of the feasibility domain are critically dependent on the inter-relationship between trophic and non-trophic effects. Where interaction modifications are structured into mutual interference motifs (associated with consumers switching between resources) synergistic signs and topological effects have particularly consequential impacts. Furthermore, we show that previous results of the impact of higher-order interactions on diversity-stability relationships can be reversed when higher-order interactions are structured, not random. Empirical data on interaction modifications will be a key part of improving understanding the dynamics of communities, particularly the distribution of interaction modification signs across networks
Identifying important interaction modifications in ecological systems
No full textTrophic interaction modifications, where a consumer‐resource link is affected by additional species, are widespread and significant causes of non‐trophic effects in ecological networks. The sheer number of potential interaction modifications in ecological systems poses a considerable challenge, making prioritisation for empirical study essential. Here, we introduce measures to quantify the topological relationship of individual interaction modifications relative to the underlying network. We use these, together with measures for the strength of trophic interaction modifications, to identify features of modifications that are most likely to exert significant effects on the dynamics of whole systems. Using a set of simulated food webs and randomly distributed interaction modifications, we test whether a subset of interaction modifications important for the local stability and direction of species responses to perturbation of complex networks can be identified. We show that trophic interaction modifications have particular importance for dynamics when they affect interactions with a high biomass flux, connect species otherwise distantly linked, and where high trophic‐level species modify interactions lower in the food web. In contrast, the centrality of modifications in the network provided little information. This work demonstrates that analyses of interaction modifications can be tractable at the network scale and highlights the importance of understanding the relationship between the distributions of trophic and non‐trophic effects
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Spatial variation in the magnitude and functional form of density-dependent processes on the large skipper butterfly Ochlodes sylvanus
No full text1. Understanding the underlying ecological processes that govern population dynamics is essential for identifying the risk of extinction faced by a population. Ecological processes are driven by a number of different density-dependent and density-independent factors. Influential factors may vary between species and are often classified for large areas of a species' geographical range.
2. Here we test the hypothesis that these factors vary on a relatively small spatial scale across a species' range. The population dynamics of the large skipper butterfly Ochlodes sylvanus is investigated for each 100 km2 region within its British range.
3. Different forms of density dependence, including Allee effects, and different density-independent factors are found to influence population change significantly in different regions. The possible underlying mechanisms responsible for each are discussed.
4. In addition to this qualitative spatial variation in influencing factors, the relative contribution of density dependence and density-independent factors to temporal dynamics within each region is quantified. As the range of O. sylvanus is crossed from north-west to east, there appears to be a switch from density independence being more influential to density dependence having a greater impact on population change
Pavlovian threat conditioning can generate intrusive memories that persist over time
Full text linkAlthough Pavlovian threat conditioning has proven to be a useful translational model for the development
of anxiety disorders, it remains unknown if this procedure can generate intrusive memories – a symptom of
many anxiety-related disorders, and whether intrusions persist over time. Social support has been related to
better adjustment after trauma however, experimental evidence regarding its effect on the development of
anxiety-related symptoms is sparse. We had two aims: to test whether threat conditioning generates intrusive
memories, and whether different social support interactions impacted expression of emotional memories.
Non-clinical participants (n=81) underwent threat conditioning to neutral stimuli. Participants were then
assigned to a supportive, unsupportive, or no social interaction group, and asked to report intrusive
memories for seven days. As predicted, threat conditioning can generate intrusions, with greater number of
intrusions of CS+ (M=2.35, SD=3.09) than CS- (M=1.39, SD=2.17). Contrary to predictions, compared to
no social interaction, supportive social interaction did not reduce, and unsupportive interaction did not
increase skin conductance of learned threat or number of intrusions. Unsupportive interaction resulted in a
relative difference in number of intrusions to CS+ vs CS-, suggesting that unsupportive interaction might
have increased image-based threat memories. Intrusions were still measurable one year after conditioning
(one-year follow-up; n=54), when individuals with higher trait anxiety and greater number of previous
trauma experiences reported more intrusions. Our findings show that threat conditioning can create longlasting intrusions, offering a novel experimental psychopathology model of intrusive memories with
implications for both research on learning and clinical applications
Interaction modifications lead to greater robustness than pairwise non-trophic effects in food webs
Full text link1.Considerable emphasis has been placed recently on the importance of incorporating non-trophic effects in to our understanding of ecological networks. Interaction modifications are well established as generating strong non-trophic impacts by modulating the strength of inter-specific interactions. 2.For simplicity and comparison with direct interactions within a network context, the consequences of interaction modifications have often been described as direct pairwise interactions. The consequences of this assumption have not been examined in non-equilibrium settings where unexpected consequences of interaction modifications are most likely.3.To test the distinct dynamic nature of these ‘higher-order’ effects we directly compare, using dynamic simulations, the robustness to extinctions under perturbation of systems where interaction modifications are either explicitly modelled or represented by corresponding equivalent pairwise non-trophic interactions.4.Full, multi-species representations of interaction modifications resulted in a greater robustness to extinctions compared to equivalent pairwise effects. Explanations for this increased stability despite apparent greater dynamic complexity can be found in additional routes for dynamic feedbacks. Furthermore, interaction modifications changed the relative vulnerability of species to extinction from those trophically connected close to the perturbed species towards those receiving a large number of modifications. 5.Future empirical and theoretical research into non-trophic effects should distinguish interaction modifications from direct pairwise effects in order to maximise information about the system dynamics. Interaction modifications have the potential to shift expectations of species vulnerability based exclusively on trophic networks.<br/
Positive moods are all alike? Differential affect amplification effects of ‘elated’ versus ‘calm’ mental imagery in young adults reporting hypomanic-like experiences
Full text linkPositive mood amplification is a hallmark of the bipolar disorder spectrum (BPDS). We need better understanding of cognitive mechanisms contributing to such elevated mood. Generation of vivid, emotionally compelling mental imagery is proposed to act as an ‘emotional amplifier’ in BPDS. We used a positive mental imagery generation paradigm to manipulate affect in a subclinical BPDS-relevant sample reporting high (n = 31) vs. low (n = 30) hypomanic-like experiences on the Mood Disorder Questionnaire (MDQ). Participants were randomized to an ‘elated’ or ‘calm’ mental imagery condition, rating their momentary affect four times across the experimental session. We hypothesized greater affect increase in the high (vs. low) MDQ group assigned to the elated (vs. calm) imagery generation condition. We further hypothesized that affect increase in the high MDQ group would be particularly apparent in the types of affect typically associated with (hypo)mania, i.e., suggestive of high activity levels. Mixed model and time-series analysis showed that for the high MDQ group, affect increased steeply and in a sustained manner over time in the ‘elated’ imagery condition, and more shallowly in ‘calm’. The low-MDQ group did not show this amplification effect. Analysis of affect clusters showed high-MDQ mood amplification in the ‘elated’ imagery condition was most pronounced for active affective states. This experimental model of BPDS-relevant mood amplification shows evidence that positive mental imagery drives changes in affect in the high MDQ group in a targeted manner. Findings inform cognitive mechanisms of mood amplification, and spotlight prevention strategies targeting elated imagery, while potentially retaining calm imagery to preserve adaptive positive emotionality
Allee effects and the spatial dynamics of a locally-endangered butterfly, the High Brown Fritillary (Argynnis adippe)
No full textConservation of endangered species necessitates a full appreciation of the ecological processes affecting the regulation, limitation, and persistence of populations. These processes are influenced by birth, death, and dispersal events, and characterizing them requires careful accounting of both the deterministic and stochastic processes operating at both local and regional population levels. We combined ecological theory and observations on Allee effects by linking mathematical analysis and the spatial and temporal population dynamics patterns of a highly endangered butterfly, the high brown fritillary, Argynnis adippe. Our theoretical analysis showed that the role of density-dependent feedbacks in the presence of local immigration can influence the strength of Allee effects. Linking this theory to the analysis of the population data revealed strong evidence for both negative density dependence and Allee effects at the landscape or regional scale. These regional dynamics are predicted to be highly influenced by immigration. Using a Bayesian state-space approach, we characterized the local-scale births, deaths, and dispersal effects together with measurement and process uncertainty in the metapopulation. Some form of an Allee effect influenced almost three-quarters of these local populations. Our joint analysis of the deterministic and stochastic dynamics suggests that a conservation priority for this species would be to increase resource availability in currently occupied and, more importantly, in unoccupied sites<br/
Trophic interaction modifications: an empirical and theoretical framework
Full text linkConsumer–resource interactions are often influenced by other species in the community. At present these ‘trophic interaction modifications’ are rarely included in ecological models despite demonstrations that they can drive system dynamics. Here, we advocate and extend an approach that has the potential to unite and represent this key group of non‐trophic interactions by emphasising the change to trophic interactions induced by modifying species. We highlight the opportunities this approach brings in comparison to frameworks that coerce trophic interaction modifications into pairwise relationships. To establish common frames of reference and explore the value of the approach, we set out a range of metrics for the ‘strength’ of an interaction modification which incorporate increasing levels of contextual information about the system. Through demonstrations in three‐species model systems, we establish that these metrics capture complimentary aspects of interaction modifications. We show how the approach can be used in a range of empirical contexts; we identify as specific gaps in current understanding experiments with multiple levels of modifier species and the distributions of modifications in networks. The trophic interaction modification approach we propose can motivate and unite empirical and theoretical studies of system dynamics, providing a route to confront ecological complexity
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