Feeling anxious: anticipatory amygdalo-insular response predicts the feeling of anxious anticipation

Anticipation is a central component of anxiety and the anterior insula appears to be an important neural substrate in which this process is mediated. The anterior insula is also thought to underlie the interoceptive representation of one's affective state. However, the degree to which individual differences in anticipation-related insula reactivity are associated with variability in the subjective experience of anxious anticipation is untested. To assess this possibility, functional magnetic resonance images were acquired while participants completed an auditory anticipation task with trial-by-trial self-report ratings of anxious anticipation. We hypothesized that the anterior insula would be positively associated with an individual's subjective experience of anticipatory anxiety. The results provide evidence for an amygdalo-insular system involved in anxious auditory anticipation. Reactivity in the right anterior insula was predictive of individuals' subjective experience of anxious anticipation for both aversive and neutral stimuli, whereas the amygdala was predictive of anticipatory anxiety for aversive stimuli. In addition, anxious anticipatory activation in the left insula and left amygdala covaried with participants' level of trait anxiety, particularly when the anticipated event was proximal.

Backward Masked Snakes and Guns Modulate Spatial Attention

Fearful faces are important social cues that alert others of potential threat. Even backward masked fearful faces facilitate spatial attention. However, visual stimuli other than fearful faces can signal potential threat. Indeed, unmasked snakes and spiders modulate spatial attention. Yet, it is unclear if the rapid threat-related facilitation of spatial attention to backward masked stimuli is elicited by non-face threat cues. Evolutionary theories claim that phylogenetic threats (i.e. snakes and spiders) should preferentially elicit an automatic fear response, but it is untested as to whether this response extends to enhancements in spatial attention under restricted processing conditions. Thirty individuals completed a backward masking dot-probe task with both evolutionary relevant and irrelevant threat cues. The results suggest that backward masked visual fear stimuli modulate spatial attention. Both evolutionary relevant (snake) and irrelevant (gun) threat cues facilitated spatial attention.

Serotonin transporter genotype and depressive symptoms moderate effects of nicotine on spatial working memory

Smokers may use nicotine to self-medicate for situation-specific or person-specific cognitive or affective deficits. Although evidence suggests that nicotine replacement therapy (NRT), relative to placebo, enhances spatial working memory (SWM) in smoking-abstinent smokers with schizophrenia, the extent to which NRT may be helpful in attenuating abstinence-related SWM in other groups with deficits in SWM is unknown. Depressive symptoms are associated with both tobacco smoking and deficits in SWM. Previous studies have found that smoking abstinence increases depressive affect and depression-related hemispheric asymmetries in brain activation. Although the serotonin neurotransmitter system is closely associated with depression and the effects of nicotine, the authors are not aware of any studies that have evaluated the possible role of individual differences in serotonin transporter (5-HTT) genotype and depressive symptoms as moderators of the effects of NRT on SWM. Thus, the current study assessed the effects of NRT (nicotine patch) on SWM in relation to: (1) depressive traits and (2) 5-HTT genotype. Smoking-deprived habitual smokers (N = 64) completed the dot recall test of SWM during counterbalanced and double-blind nicotine and placebo testing sessions. There was a marginal overall effect of NRT on SWM. More importantly, NRT enhanced SWM in 5-HTT short allele carriers, relative to those with two long alleles, and this enhancement in short-allele carriers was greater for individuals with higher levels of depressive symptoms.

Rate-dependent shear bands in a shear-transformation-zone model of amorphous solids

We use shear transformation zone (STZ) theory to develop a deformation map for amorphous solids as a function of the imposed shear rate and initial material preparation. The STZ formulation incorporates recent simulation results [T. K. Haxton and A. J. Liu, Phys. Rev. Lett. 99, 195701 (2007)] showing that the steady state effective temperature is rate dependent. The resulting model predicts a wide range of deformation behavior as a function of the initial conditions, including homogeneous deformation, broad shear bands, extremely thin shear bands, and the onset of material failure. In particular, the STZ model predicts homogeneous deformation for shorter quench times and lower strain rates, and inhomogeneous deformation for longer quench times and higher strain rates. The location of the transition between homogeneous and inhomogeneous flow on the deformation map is determined in part by the steady state effective temperature, which is likely material dependent. This model also suggests that material failure occurs due to a runaway feedback between shear heating and the local disorder, and provides an explanation for the thickness of shear bands near the onset of material failure. We find that this model, which resolves dynamics within a sheared material interface, predicts that the stress weakens with strain much more rapidly than a similar model which uses a single state variable to specify internal dynamics on the interface.

Effects of nicotine and depressive traits on affective priming of lateralized emotional word identification

Based on evidence suggesting that depressive traits, emotional information processing, and the effects of nicotine may be mediated by lateralized brain mechanisms, analyses assessed the influence of depressive traits and nicotine patch on emotional priming of lateralized emotional word identification in 61 habitual smokers. Consistent with hypotheses, nicotine as compared to placebo patch enhanced right visual field (RVF) emotional word identification while decreasing performance of emotional word identification in the left visual field (LVF). Nicotine also enhanced positive affect and decreased negative affect. Consistent with the Heller model of depression, scoring high in depressive traits was associated with a general decrease in LVF emotional word identification. Additionally, this general LVF deficit was especially pronounced for positive word identification in individuals scoring high in trait depression. Positive primes facilitated positive target identification in the RVF and negative primes facilitated negative target identification in the LVF. Thus, nicotine promoted a LVF word-identification deficit similar to that observed in those with depressive traits. However, nicotine also enhanced RVF processing and reduced negative affect, whereas it enhanced positive affect.

Strain localization in a shear transformation zone model for amorphous solids

We model a sheared disordered solid using the theory of shear transformation zones (STZs). In this mean-field continuum model the density of zones is governed by an effective temperature that approaches a steady state value as energy is dissipated. We compare the STZ model to simulations by Shi [Phys. Rev. Lett. 98, 185505 (2007)], finding that the model generates solutions that fit the data, exhibit strain localization, and capture important features of the localization process. We show that perturbations to the effective temperature grow due to an instability in the transient dynamics, but unstable systems do not always develop shear bands. Nonlinear energy dissipation processes interact with perturbation growth to determine whether a material exhibits strain localization. By estimating the effects of these interactions, we derive a criterion that determines which materials exhibit shear bands based on the initial conditions alone. We also show that the shear band width is not set by an inherent diffusion length scale but instead by a dynamical scale that depends on the imposed strain rate.

Wildfires, complexity, and highly optimized tolerance

Recent, large fires in the western United States have rekindled debates about fire management and the role of natural fire regimes in the resilience of terrestrial ecosystems. This real-world experience parallels debates involving abstract models of forest fires, a central metaphor in complex systems theory. Both real and modeled fire-prone landscapes exhibit roughly power law statistics in fire size versus frequency. Here, we examine historical fire catalogs and a detailed fire simulation model; both are in agreement with a highly optimized tolerance model. Highly optimized tolerance suggests robustness tradeoffs underlie resilience in different fire-prone ecosystems. Understanding these mechanisms may provide new insights into the structure of ecological systems and be key in evaluating fire management strategies and sensitivities to climate change.

Three mechanisms for power laws on the Cayley tree

We compare preferential growth, critical phase transitions, and highly optimized tolerance (HOT) as mechanisms for generating power laws in the familiar and analytically tractable context of lattice percolation and forest fire models on the Cayley tree. All three mechanisms have been widely discussed in the context of complexity in natural and technological systems. This parallel study enables direct comparison of the mechanisms and associated lattice solutions. Criticality fits most naturally into the category of random processes, where power laws are a consequence of fluctuations in an ensemble with no intrinsic scale. The power laws in preferential growth can be understood in the context of competing exponential growth and decay processes. HOT generalizes this functional mechanism involving exponentials of exponentials to a broader class of nonexponential functions, which arise from optimization.

Evolutionary dynamics and highly optimized tolerance

We develop a numerical model of a lattice community based on Highly Optimized Tolerance (HOT), which relates the evolution of complexity to robustness tradeoffs in an uncertain environment. With the model, we explore scenarios for evolution and extinction which are abstractions of processes which are commonly discussed in biological and ecological case studies. These include the effects of different habitats on the phenotypic traits of the organisms, the effects of different mutation rates on adaptation, fitness, and diversity, and competition between generalists and specialists. The model exhibits a wide variety of microevolutionary and macroevolutionary phenomena which can arise in organisms which are subject to random mutation, and selection based on fitness evaluated in a specific environment. Generalists arise in uniform habitats, where different disturbances occur with equal frequency, while specialists arise when the relative frequency of different disturbances is skewed. Fast mutators are seen to play a primary role in adaptation, while slow mutators preserve well-adapted configurations. When uniform and skewed habitats are coupled through migration of the organisms, we observe a primitive form of punctuated equilibrium. Rare events in the skewed habitat lead to extinction of the specialists, whereupon generalists invade from the uniform habitat, adapt to their new surroundings, ultimately leading their progeny to become vulnerable to extinction in a subsequent rare disturbance.

Highly optimized tolerance and power laws in dense and sparse resource regimes

Power law cumulative frequency (P) versus event size (l) distributions P > or =l) approximately l(-alpha) are frequently cited as evidence for complexity and serve as a starting point for linking theoretical models and mechanisms with observed data. Systems exhibiting this behavior present fundamental mathematical challenges in probability and statistics. The broad span of length and time scales associated with heavy tailed processes often require special sensitivity to distinctions between discrete and continuous phenomena. A discrete highly optimized tolerance (HOT) model, referred to as the probability, loss, resource (PLR) model, gives the exponent alpha=1/d as a function of the dimension d of the underlying substrate in the sparse resource regime. This agrees well with data for wildfires, web file sizes, and electric power outages. However, another HOT model, based on a continuous (dense) distribution of resources, predicts alpha=1+1/d . In this paper we describe and analyze a third model, the cuts model, which exhibits both behaviors but in different regimes. We use the cuts model to show all three models agree in the dense resource limit. In the sparse resource regime, the continuum model breaks down, but in this case, the cuts and PLR models are described by the same exponent.

A supershear transition mechanism for cracks

Seismic data indicate that fault ruptures follow complicated paths with variable velocity because of inhomogeneities in initial stress or fracture energy. We report a phenomenon unique to three-dimensional cracks: Locally stronger fault sections, rather than slowing ruptures, drive them forward at velocities exceeding the shear wave speed. This supershear mechanism differentiates barrier and asperity models of fault heterogeneity, which previously have been regarded as indistinguishable. High strength barriers concentrate energy, producing potentially destructive pulses of strong ground motion.

One-year follow-up results of the STARS for Families alcohol prevention program

This study examined the 1-year follow-up effects of the STARS (Start Taking Alcohol Risks Seriously) for Families program, a 2-year preventive intervention based on a stage of acquisition model, and consisting of nurse consultations and parent materials. A randomized controlled trial was conducted, with participants receiving either the intervention or a minimal intervention control. Participants included a cohort of 650 sixth-grade students from two urban middle schools-one magnet (bused) and one neighborhood. Trained project staff administered questionnaires to students following a standardized protocol in the schools. For the magnet school sample, significantly fewer intervention students (5%) were planning to drink in the next 6 months than control students (18%), chi2 = 11.53, 1 d.f., P = 0.001. Magnet school intervention students also had less intentions to drink in the future, greater motivation to avoid drinking and less total alcohol risk than control students, Ps < 0.05. For the neighborhood school, intervention students (m = 7.90, SD = 1.87) had less total alcohol risk than control students (m = 8.42, SD = 1.83), F(1,205) = 4.09, P = 0.04. These findings suggest that a brief, stage and risk/protective factor tailored program holds promise for reducing risk for alcohol use among urban school youth 1 year after intervention, and has the unique advantage of greater 'transportability' over classroom-based prevention programs.

Design degrees of freedom and mechanisms for complexity

We develop a discrete spectrum of percolation forest fire models characterized by increasing design degrees of freedom (DDOF's). The DDOF's are tuned to optimize the yield of trees after a single spark. In the limit of a single DDOF, the model is tuned to the critical density. Additional DDOF's allow for increasingly refined spatial patterns, associated with the cellular structures seen in highly optimized tolerance (HOT). The spectrum of models provides a clear illustration of the contrast between criticality and HOT, as well as a concrete quantitative example of how a sequence of robustness tradeoffs naturally arises when increasingly complex systems are developed through additional layers of design. Such tradeoffs are familiar in engineering and biology and are a central aspect of the complex systems that can be characterized as HOT.

Complexity and robustness

Highly optimized tolerance (HOT) was recently introduced as a conceptual framework to study fundamental aspects of complexity. HOT is motivated primarily by systems from biology and engineering and emphasizes, (i) highly structured, nongeneric, self-dissimilar internal configurations, and (ii) robust yet fragile external behavior. HOT claims these are the most important features of complexity and not accidents of evolution or artifices of engineering design but are inevitably intertwined and mutually reinforcing. In the spirit of this collection, our paper contrasts HOT with alternative perspectives on complexity, drawing on real-world examples and also model systems, particularly those from self-organized criticality.

Mutation, specialization, and hypersensitivity in highly optimized tolerance

We introduce a model of evolution in which competing organisms are represented by percolation lattice models. Fitness is based on the number of occupied sites remaining after removing a cluster connected to a randomly selected site. High-fitness individuals arising through mutation and selection must trade off density versus robustness to loss, and are characterized by cellular barrier patterns that prevent large cascading losses to common disturbances. This model shows that Highly Optimized Tolerance (HOT), which links complexity to robustness in designed systems, arises naturally through Darwinian mechanisms. Although the model is a severe abstraction of biology, it produces a surprisingly wide variety of micro- and macroevolutionary features strikingly similar to real biological evolution.

Highly optimized tolerance in epidemic models incorporating local optimization and regrowth

In the context of a coupled map model of population dynamics, which includes the rapid spread of fatal epidemics, we investigate the consequences of two new features in highly optimized tolerance (HOT), a mechanism which describes how complexity arises in systems which are optimized for robust performance in the presence of a harsh external environment. Specifically, we (1) contrast global and local optimization criteria and (2) investigate the effects of time dependent regrowth. We find that both local and global optimization lead to HOT states, which may differ in their specific layouts, but share many qualitative features. Time dependent regrowth leads to HOT states which deviate from the optimal configurations in the corresponding static models in order to protect the system from slow (or impossible) regrowth which follows the largest losses and extinctions. While the associated map can exhibit complex, chaotic solutions, HOT states are confined to relatively simple dynamical regimes.

Effects of a stage-based alcohol preventive intervention for inner-city youth

The purpose of this study was to examine first year outcomes of an alcohol preventive intervention within inner-city middle schools. Subjects consisted of 650 sixth grade students from one neighborhood inner-city school (n = 262) and one bused school (n = 388). At posttest, chi-square analyses showed that significantly fewer neighborhood intervention students initiated alcohol use, used alcohol during the past seven-day and thirty-day periods, drank heavily during the past thirty days, and drank over any period of time, compared to control students (p's < .05). Significant group x prior alcohol consequences interaction effects were found for bused students, showing those with past alcohol consequences who received the intervention had less intentions to use alcohol and less frequent use of alcohol (p's < .05). These results suggest that a brief, stage-based preventive intervention may result in significant reductions in alcohol initiation and consumption among some inner-city youth.

Dynamics and changing environments in highly optimized tolerance

Highly optimized tolerance (HOT) is a mechanism for power laws in complex systems based on the robust design of systems in uncertain environments. Once the system, the environment, and the optimization scheme have been specified, the HOT state is fixed and corresponds to the set of measure zero (typically a single point) in the configuration space which minimizes a cost function U. Here we explore the U-dependent structures in configuration space which are associated with departures from the optimal state. We introduce dynamics, quantified by an effective temperature T, such that T=0 corresponds to the original HOT state, while T-->infinity corresponds to completely random configurations. More generally, T defines the range in state space over which fluctuations are likely to be observed. In a fixed environment fluctuations always raise the average cost. However, in a time-dependent environment, mobile configurations can lower the average U because they adjust more efficiently to changes.

Results of a social norm intervention to prevent binge drinking among first-year residential college students

The effects of a primary prevention social norm intervention on binge drinking among 1st-year residential college students were examined. Six hundred thirty-four students attending a medium-sized public university in the South were randomly assigned to receive a two-phase social norm intervention or the standard campus psychoeducational prevention program. At posttest, no differences were found between intervention and control group students on any of the alcohol use and alcohol-use risk factor measures. Significant subgroup differences were found by stage of initiating binge drinking behaviors, for frequency of alcohol use, F(3, 507) = 3.69, p = .01; quantity of alcohol use, F(3, 507) = 2.51, p = .05; and social norms, F(3, 505) = 2.53, p = .05. These findings suggest the need for tailoring social norm binge drinking interventions to students' stage of initiating heavy drinking and carefully monitoring for potential negative, as well as positive, effects of norm-based prevention messages.

Power laws, highly optimized tolerance, and generalized source coding

We introduce a family of robust design problems for complex systems in uncertain environments which are based on tradeoffs between resource allocations and losses. Optimized solutions yield the "robust, yet fragile" features of highly optimized tolerance and exhibit power law tails in the distributions of events for all but the special case of Shannon coding for data compression. In addition to data compression, we construct specific solutions for world wide web traffic and forest fires, and obtain excellent agreement with measured data.

Highly optimized tolerance: robustness and design in complex systems

Highly optimized tolerance (HOT) is a mechanism that relates evolving structure to power laws in interconnected systems. HOT systems arise where design and evolution create complex systems sharing common features, including (1) high efficiency, performance, and robustness to designed-for uncertainties, (2) hypersensitivity to design flaws and unanticipated perturbations, (3) nongeneric, specialized, structured configurations, and (4) power laws. We study the impact of incorporating increasing levels of design and find that even small amounts of design lead to HOT states in percolation.