A Comprehensive Multilevel Analysis of the Bucharest Early Intervention Project: Causal Effects on Recovery From Early Severe Deprivation.

OBJECTIVE: The Bucharest Early Intervention Project is the first randomized controlled trial of foster care as an alternative to institutional care. The authors synthesized data from nearly 20 years of assessments of the trial to determine the overall intervention effect size across time points and developmental domains. The goal was to quantify the overall effect of the foster care intervention on children's outcomes and examine sources of variation in this effect, including domain, age, and sex assigned at birth. METHODS: An intent-to-treat approach was used to examine the causal effects of the randomized controlled trial for 136 children residing in institutions in Bucharest, Romania (baseline age, 6-31 months) who were randomly assigned to either foster care (N=68) or care as usual (N=68). At ages 30, 42, and 54 months and 8, 12, and 16-18 years, children were assessed for IQ, physical growth, brain electrical activity (EEG), and symptoms of five types of psychopathology. RESULTS: Participants provided 7,088 observations across follow-up waves. Children assigned to foster care had better cognitive and physical outcomes and less severe psychopathology than did those who received care as usual. The magnitude of these effect sizes remained stable across development. The foster care intervention most influenced IQ and disorders of attachment/social relatedness. CONCLUSIONS: Young children benefit from placement in families after institutional care. The benefits of foster care for previously institutionalized children were remarkably stable across development.

Foster care leads to sustained cognitive gains following severe early deprivation.

This study examined longitudinal data from the Bucharest Early Intervention Project, a randomized controlled trial of foster care as an alternative to institutional care following exposure to severe psychosocial deprivation. We report data from 135 participants assessed in early adulthood (age 18 y). We find that 16 y after randomization occurred, those who had been randomized to high-quality foster care had significantly higher IQ scores (9 points, 0.6 SD) than those randomized to care as usual. Mediation analyses provide evidence that the causal effect of the intervention on cognitive ability in early adulthood could be explained, in part, by higher-quality caregiving and attachment security. These findings indicate that early investment in family care as an alternative to institutional care leads to sustained gains in cognitive ability. Fostering caregiving relationships is a likely mechanism of the intervention. In addition, exploratory analyses indicate that stable placements throughout childhood are associated with the greatest long-term gains in cognitive ability. Whether early interventions for infants and young children lead to lasting change has significant implications for decisions to invest in programs aimed at improving children's developmental outcomes.

A pharmacokinetic model of lead absorption and calcium competitive dynamics.

Lead is a naturally-occurring element. It has been known to man for a long time, and it is one of the longest established poisons. The current consensus is that no level of lead exposure should be deemed "safe". New evidence regarding the blood levels at which morbidities occur has prompted the CDC to reduce the screening guideline of 10 µg/dl to 2 µg/dl. Measurable cognitive decline (reduced IQ, academic deficits) have been found to occur at levels below 10 µg/dl, especially in children. Knowledge of lead pharmacology allows us to better understand its absorption and metabolization, mechanisms that produce its medical consequences. Based upon an original and very simplified compartmental model of Rabinowitz (1973) with only three major compartments (blood, bone and soft tissue), extensive biophysical models sprouted over the following two decades. However, none of these models have been specifically designed to use new knowledge of lead molecular dynamics to understand its deleterious effects on the brain. We build and analyze a compartmental model of lead pharmacokinetics, focused specifically on addressing neurotoxicity. We use traditional phase space methods, parameter sensitivity analysis and bifurcation theory to study the transitions in the system's behavior in response to various physiological parameters. We conclude that modeling the complex interaction of lead and calcium along their dynamic trajectory may successfully explain counter-intuitive effects on systemic function and neural behavior which could not be addressed by existing linear models. Our results encourage further efforts towards using nonlinear phenomenology in conjunction with empirically driven system parameters, to obtain a biophysical model able to provide clinical assessments and predictions.

An Interpretative Phenomenological Analysis of a Religious Conversion.

Religious conversion is an important phenomenon in contemporary religious climate, but existing psychology research work is mostly based on quantitative methods. In an attempt to contribute to this field, the present study proposes a qualitative exploration of religious conversion. The in-depth interview of a French woman is examined in order to investigate her experience of religious conversion, 40 years prior. The interview was analysed using interpretative phenomenological analysis, with the purpose of revealing how the participant experienced the process of religious conversion, what was its impact on her life, identity and personality and how she coped with this impact. The four emerging themes were: conflicted relationship with Judaism, the pursuit of a spiritual quest, changes after conversion and life after conversion. These themes painted the image of a powerful spiritual transformation, a profound and dynamic lifelong process, integrating concepts and practices, life changes and developments. The findings are explained with the help of available literature.

Global and local excitation and inhibition shape the dynamics of the cortico-striatal-thalamo-cortical pathway.

The cortico-striatal-thalamo-cortical (CSTC) pathway is a brain circuit that controls movement execution, habit formation and reward. Hyperactivity in the CSTC pathway is involved in obsessive compulsive disorder (OCD), a neuropsychiatric disorder characterized by the execution of repetitive involuntary movements. The striatum shapes the activity of the CSTC pathway through the coordinated activation of two classes of medium spiny neurons (MSNs) expressing D1 or D2 dopamine receptors. The exact mechanisms by which balanced excitation/inhibition (E/I) of these cells controls the network dynamics of the CSTC pathway remain unclear. Here we use non-linear modeling of neuronal activity and bifurcation theory to investigate how global and local changes in E/I of MSNs regulate the activity of the CSTC pathway. Our findings indicate that a global and proportionate increase in E/I pushes the system to states of generalized hyper-activity throughout the entire CSTC pathway. Certain disproportionate changes in global E/I trigger network oscillations. Local changes in the E/I of MSNs generate specific oscillatory behaviors in MSNs and in the CSTC pathway. These findings indicate that subtle changes in the relative strength of E/I of MSNs can powerfully control the network dynamics of the CSTC pathway in ways that are not easily predicted by its synaptic connections.

Applying fMRI complexity analyses to the single subject: a case study for proposed neurodiagnostics.

Nonlinear dynamic tools have been statistically validated at the group level to identify subtle differences in system wide regulation of brain meso-circuits, often increasing clinical sensitivity over conventional analyses alone. We explored the feasibility of extracting information at the single-subject level, illustrating two pairs of healthy individuals with psychological differences in stress reactivity. We applied statistical and nonlinear dynamic tools to capture key characteristics of the prefrontal-limbic loop. We compared single subject results with statistical results for the larger group. We concluded that complexity analyses may identify important differences at the single-subject level, supporting their potential towards neurodiagnostic applications.

Neural Network Spectral Robustness under Perturbations of the Underlying Graph.

Recent studies have been using graph-theoretical approaches to model complex networks (such as social, infrastructural, or biological networks) and how their hardwired circuitry relates to their dynamic evolution in time. Understanding how configuration reflects on the coupled behavior in a system of dynamic nodes can be of great importance, for example, in the context of how the brain connectome is affecting brain function. However, the effect of connectivity patterns on network dynamics is far from being fully understood. We study the connections between edge configuration and dynamics in a simple oriented network composed of two interconnected cliques (representative of brain feedback regulatory circuitry). In this article our main goal is to study the spectra of the graph adjacency and Laplacian matrices, with a focus on three aspects in particular: (1) the sensitivity and robustness of the spectrum in response to varying the intra- and intermodular edge density, (2) the effects on the spectrum of perturbing the edge configuration while keeping the densities fixed, and (3) the effects of increasing the network size. We study some tractable aspects analytically, then simulate more general results numerically, thus aiming to motivate and explain our further work on the effect of these patterns on the network temporal dynamics and phase transitions. We discuss the implications of such results to modeling brain connectomics. We suggest potential applications to understanding synaptic restructuring in learning networks and the effects of network configuration on function of regulatory neural circuits.

The Effects of Early Institutionalization and Foster Care Intervention on Children's Social Behaviors at Age 8.

The present study compared the social behaviors of 8-year-old previously institutionalized Romanian children from the Bucharest Early Intervention Project (BEIP) in two groups: 1) children randomized to foster care homes (FCG), and 2) children randomized to care as usual (remaining in institutions) (CAUG). Children were observed interacting with an age and gender-matched unfamiliar, non-institutionalized peer from the community (NIG) during six interactive tasks, and their behavior was coded for speech reticence, social engagement, task orientation, social withdrawal, and conversational competence. Group comparisons revealed that FCG children were rated as significantly less reticent during a speech task than CAUG children. For CAUG children, longer time spent in institutional care was related to greater speech reticence and lower social engagement. Using an Actor-Partner Interdependence Model, CAUG children's behaviors, but not FCG, were found to influence the behavior of unfamiliar peers. These findings are the first to characterize institutionalized children's observed social behaviors towards new peers during middle childhood and highlight the positive effects of foster care intervention in the social domain.

Input statistics and Hebbian cross-talk effects.

As an extension of prior work, we studied inspecific Hebbian learning using the classical Oja model. We used a combination of analytical tools and numerical simulations to investigate how the effects of synaptic cross talk (which we also refer to as synaptic inspecificity) depend on the input statistics. We investigated a variety of patterns that appear in dimensions higher than two (and classified them based on covariance type and input bias). We found that the effects of cross talk on learning dynamics and outcome is highly dependent on the input statistics and that cross talk may lead in some cases to catastrophic effects on learning or development. Arbitrarily small levels of cross talk are able to trigger bifurcations in learning dynamics, or bring the system in close enough proximity to a critical state, to make the effects indistinguishable from a real bifurcation. We also investigated how cross talk behaves toward unbiased ("competitive") inputs and in which circumstances it can help the system productively resolve the competition. Finally, we discuss the idea that sophisticated neocortical learning requires accurate synaptic updates (similar to polynucleotide copying, which requires highly accurate replication). Since it is unlikely that the brain can completely eliminate cross talk, we support the proposal that is uses a neural mechanism that "proofreads" the accuracy of the updates, much as DNA proofreading lowers copying error rate.

Network connectivity modulates power spectrum scale invariance.

Measures of complexity are sensitive in detecting disease, which has made them attractive candidates for diagnostic biomarkers; one complexity measure that has shown promise in fMRI is power spectrum scale invariance (PSSI). Even if scale-free features of neuroimaging turn out to be diagnostically useful, however, their underlying neurobiological basis is poorly understood. Using modeling and simulations of a schematic prefrontal-limbic meso-circuit, with excitatory and inhibitory networks of nodes, we present here a framework for how network density within a control system can affect the complexity of signal outputs. Our model demonstrates that scale-free behavior, similar to that observed in fMRI PSSI data, can be obtained for sufficiently large networks in a context as simple as a linear stochastic system of differential equations, although the scale-free range improves when introducing more realistic, nonlinear behavior in the system. PSSI values (reflective of complexity) vary as a function of both input type (excitatory, inhibitory) and input density (mean number of long-range connections, or strength), independent of their node-specific geometric distribution. Signals show pink noise (1/f) behavior when excitatory and inhibitory influences are balanced. As excitatory inputs are increased and decreased, signals shift towards white and brown noise, respectively. As inhibitory inputs are increased and decreased, signals shift towards brown and white noise, respectively. The results hold qualitatively at the hemodynamic scale, which we modeled by introducing a neurovascular component. Comparing hemodynamic simulation results to fMRI PSSI results from 96 individuals across a wide spectrum of anxiety-levels, we show how our model can generate concrete and testable hypotheses for understanding how connectivity affects regulation of meso-circuits in the brain.

Human gender differences in the perception of conspecific alarm chemosensory cues.

It has previously been established that, in threatening situations, animals use alarm pheromones to communicate danger. There is emerging evidence of analogous chemosensory "stress" cues in humans. For this study, we collected alarm and exercise sweat from "donors," extracted it, pooled it and presented it to 16 unrelated "detector" subjects undergoing fMRI. The fMRI protocol consisted of four stimulus runs, with each combination of stimulus condition and donor gender represented four times. Because olfactory stimuli do not follow the canonical hemodynamic response, we used a model-free approach. We performed minimal preprocessing and worked directly with block-average time series and step-function estimates. We found that, while male stress sweat produced a comparably strong emotional response in both detector genders, female stress sweat produced a markedly stronger arousal in female than in male detectors. Our statistical tests pinpointed this gender-specificity to the right amygdala (strongest in the superficial nuclei). When comparing the olfactory bulb responses to the corresponding stimuli, we found no significant differences between male and female detectors. These imaging results complement existing behavioral evidence, by identifying whether gender differences in response to alarm chemosignals are initiated at the perceptual versus emotional level. Since we found no significant differences in the olfactory bulb (primary processing site for chemosensory signals in mammals), we infer that the specificity in responding to female fear is likely based on processing meaning, rather than strength, of chemosensory cues from each gender.

The role of simvastatin in the therapeutic approach of rheumatoid arthritis.

The pleiotropic effects of statins, especially the anti-inflammatory and immunomodulatory ones, indicate that their therapeutic potential might extend beyond cholesterol lowering and cardiovascular disease to other inflammatory disorders such as rheumatoid arthritis. Therefore, we undertook a prospective cohort study to evaluate the efficacy and safety of simvastatin used for inflammation control in patients with rheumatoid arthritis. One hundred patients with active rheumatoid arthritis divided into two equal groups (the study one who received 20 mg/day of simvastatin in addition to prior DMARDs and the control one) were followed up over six months during three study visits. The results of the study support the fact that simvastatin at a dose of 20 mg/day has a low anti-inflammatory effect in patients with rheumatoid arthritis with a good safety profile.

Effects of early intervention and the moderating effects of brain activity on institutionalized children's social skills at age 8.

The present study examined the social skills of previously institutionalized, 8-y-old Romanian children from the Bucharest Early Intervention Project and the influence of attachment security and brain electrical activity (alpha power) on these skills. Participants included children randomized to an intervention involving foster care [Foster Care Group (FCG)], children randomized to remain in institutions [Care As Usual Group (CAUG)], and never-institutionalized children living with their families in the Bucharest community [Never-Institutionalized Group (NIG)]. A continuous rating of children's attachment security to their primary caregiver was assessed at 42 mo of age. When children were 8 y old, teachers rated their social skills, and the children's resting electroencephalogram alpha power was recorded. Teachers rated social skills of FCG children who were placed into foster care before 20 mo of age as no different from NIG children, and both of these groups were higher than CAUG children and FCG children placed after 20 mo. Electroencephalogram alpha power at age 8 significantly moderated the relations between attachment security and social skills. These findings characterize institutionalized children's social skills in middle childhood within the context of a randomized intervention while highlighting the roles of both relational and biological factors in these developmental trajectories.

Power spectrum scale invariance identifies prefrontal dysregulation in paranoid schizophrenia.

Theory and experimental evidence suggest that complex living systems function close to the boundary of chaos, with erroneous organization to an improper dynamical range (too stiff or chaotic) underlying system-wide dysregulation and disease. We hypothesized that erroneous organization might therefore also characterize paranoid schizophrenia, via optimization abnormalities in the prefrontal-limbic circuit regulating emotion. To test this, we acquired fMRI scans from 35 subjects (N = 9 patients with paranoid schizophrenia and N = 26 healthy controls), while they viewed affect-valent stimuli. To quantify dynamic regulation, we analyzed the power spectrum scale invariance (PSSI) of fMRI time-courses and computed the geometry of time-delay (Poincaré) maps, a measure of variability. Patients and controls showed distinct PSSI in two clusters (k(1) : Z = 4.3215, P = 0.00002 and k(2) : Z = 3.9441, P = 0.00008), localized to the orbitofrontal/medial prefrontal cortex (Brodmann Area 10), represented by ß close to white noise in patients (ß ≈ 0) and in the pink noise range in controls (ß ≈ -1). Interpreting the meaning of PSSI differences, the Poincaré maps indicated less variability in patients than controls (Z = -1.9437, P = 0.05 for k(1) ; Z = -2.5099, P = 0.01 for k(2) ). That the dynamics identified Brodmann Area 10 is consistent with previous schizophrenia research, which implicates this area in deficits of working memory, executive functioning, emotional regulation and underlying biological abnormalities in synaptic (glutamatergic) transmission. Our results additionally cohere with a large body of work finding pink noise to be the normal range of central function at the synaptic, cellular, and small network levels, and suggest that patients show less supple responsivity of this region.

Mechanisms explaining transitions between tonic and phasic firing in neuronal populations as predicted by a low dimensional firing rate model.

Several firing patterns experimentally observed in neural populations have been successfully correlated to animal behavior. Population bursting, hereby regarded as a period of high firing rate followed by a period of quiescence, is typically observed in groups of neurons during behavior. Biophysical membrane-potential models of single cell bursting involve at least three equations. Extending such models to study the collective behavior of neural populations involves thousands of equations and can be very expensive computationally. For this reason, low dimensional population models that capture biophysical aspects of networks are needed. The present paper uses a firing-rate model to study mechanisms that trigger and stop transitions between tonic and phasic population firing. These mechanisms are captured through a two-dimensional system, which can potentially be extended to include interactions between different areas of the nervous system with a small number of equations. The typical behavior of midbrain dopaminergic neurons in the rodent is used as an example to illustrate and interpret our results. The model presented here can be used as a building block to study interactions between networks of neurons. This theoretical approach may help contextualize and understand the factors involved in regulating burst firing in populations and how it may modulate distinct aspects of behavior.

A principal component network analysis of prefrontal-limbic functional magnetic resonance imaging time series in schizophrenia patients and healthy controls.

We investigated neural regulation of emotional arousal. We hypothesized that the interactions between the components of the prefrontal-limbic system determine the global trajectories of the individual's brain activation, with the strengths and modulations of these interactions being potentially key components underlying the differences between healthy individuals and those with schizophrenia. Using affect-valent facial stimuli presented to 11 medicated schizophrenia patients and 65 healthy controls, we activated neural regions associated with the emotional arousal response during functional magnetic resonance imaging (fMRI). Performing first a random effects analysis of the fMRI data to identify activated regions, we obtained 352 data-point time series for six brain regions: bilateral amygdala, hippocampus and two prefrontal regions (Brodmann Areas 9 and 45). Since standard statistical methods are not designed to capture system features and evolution, we used principal component analyses on two types of pre-processed data: contrasts and group averages. We captured an important characteristic of the evolution of our six-dimensional brain network: all subject trajectories are almost embedded in a two-dimensional plane. Moreover, the direction of the largest principal component was a significant differentiator between the control and patient populations: the left and right amygdala coefficients were substantially higher in the case of patients, and the coefficients of Brodmann Area 9 were, to a lesser extent, higher in controls. These results are evidence that modulations between the regions of interest are the important determinant factors for the system's dynamical behavior. We place our results within the context of other principal component analyses used in neuroimaging, as well as of our existing theoretical model of prefrontal-limbic dysregulation.

Hebbian errors in learning: an analysis using the Oja model.

BACKGROUND: Recent work on long term potentiation in brain slices shows that Hebb's rule is not completely synapse-specific, probably due to intersynapse diffusion of calcium or other factors. We previously suggested that such errors in Hebbian learning might be analogous to mutations in evolution. METHODS AND FINDINGS: We examine this proposal quantitatively, extending the classical Oja unsupervised model of learning by a single linear neuron to include Hebbian inspecificity. We introduce an error matrix E, which expresses possible crosstalk between updating at different connections. When there is no inspecificity, this gives the classical result of convergence to the first principal component of the input distribution (PC1). We show the modified algorithm converges to the leading eigenvector of the matrix EC, where C is the input covariance matrix. In the most biologically plausible case when there are no intrinsically privileged connections, E has diagonal elements Q and off-diagonal elements (1-Q)/(n-1), where Q, the quality, is expected to decrease with the number of inputs n and with a synaptic parameter b that reflects synapse density, calcium diffusion, etc. We study the dependence of the learning accuracy on b, n and the amount of input activity or correlation (analytically and computationally). We find that accuracy increases (learning becomes gradually less useful) with increases in b, particularly for intermediate (i.e., biologically realistic) correlation strength, although some useful learning always occurs up to the trivial limit Q=1/n. CONCLUSIONS AND SIGNIFICANCE: We discuss the relation of our results to Hebbian unsupervised learning in the brain. When the mechanism lacks specificity, the network fails to learn the expected, and typically most useful, result, especially when the input correlation is weak. Hebbian crosstalk would reflect the very high density of synapses along dendrites, and inevitably degrades learning.

A multi-etiology model of systemic degeneration in schizophrenia.

We discuss the possibility of multiple underlying etiologies of the condition currently labeled as schizophrenia. We support this hypothesis with a theoretical model of the prefrontal-limbic system. We show how the dynamical behavior of this model depends on an entire set of physiological parameters, representing synaptic strengths, vulnerability to stress-induced cortisol, dopamine regulation and rates of autoantibody production. Malfunction of such different parameters produces similar outward dysregulation of the system, which may readily lead to diagnostic difficulties for a clinician. Techniques that provide a spectrum/profile of neural and steroid functions may be helpful in clarifying these diagnostic dilemmas.

A systems approach to prefrontal-limbic dysregulation in schizophrenia.

INTRODUCTION: Using a prefrontal-limbic dysregulation model for schizophrenia, we tested whether a dynamic control systems approach in conjunction with neuroimaging might increase detection sensitivity in characterizing the illness. Our analyses were modeled upon diagnostic tests for other dysregulatory diseases, such as diabetes, in which trajectories for the excitatory and inhibitory components of the negative feedback loops that reestablish homeostasis are measured after system perturbation. We hypothesized that these components would show distinct coupling dynamics within the patient population, as compared to healthy controls, and that these coupling dynamics could be quantified statistically using cross-correlations between excitatory and inhibitory time series using fMRI. METHODS: As our perturbation, we activated neural regions associated with the emotional arousal response, using affect-valent facial stimuli presented to 11 schizophrenic patients (all under psychotropic medication) and 65 healthy controls (including 11 individuals age- and sex-matched to the patients) during fMRI scanning. We first performed a random-effects analysis of the fMRI data to identify activated regions. Those regions were then analyzed for group differences, using both standard analyses with respect to the time series peaks, as well as a dynamic analysis that looked at cross-correlations between excitatory and inhibitory time series and group differences over the entire time series. RESULTS: Patients and controls showed significant differences in signal dynamics between excitatory and inhibitory components of the negative feedback loop that controls emotional arousal, specifically between the right amygdala and Brodmann area 9 (BA9), when viewing angry facial expressions (p = 0.002). Further analyses were performed with respect to activation amplitudes for these areas in response to angry faces, both over the entire time series as well as for each time point along the time series. While the amygdala responses were not significantly different between groups, patients showed significantly lower BA9 activation during the beginning of the response (0.000

Schizophrenia--a parameters' game?

Schizophrenia is a severe, currently incurable, relatively common mental condition. Its symptoms are complex and widespread. It structurally and functionally affects cortical and subcortical regions involved in cognitive, emotional and motivational aspects of behavior. Its diagnosis is based on statistical behavior rather than on its actual cause and its treatment is elusive. We elaborate a theoretical paradigm that accounts for some of the most important features of this illness. Our nonlinear mathematical model, built upon recent hypotheses of neural vulnerability and limbic dysregulation, addresses the amygdala-hippocampus-prefrontal interactions and their evolution under perturbation. The dependence of the dynamics on the system's parameters offers an analytical context for the "normality/disease" dichotomy. The concept of bifurcation could be the key to understanding the threshold between these two states. The nonlinearity parameter (Lyapunov number) is responsible in our setup for tuning the limbic vulnerability characteristic to schizophrenia. Studying its effect on the dynamics helps us understand how stressful events and medication can switch the system from a regime of safety to one of instability, and conversely. The approach has potential for pre-symptomatic risk assessments and for long-term predictions.