Strong Allee Effect Synaptic Plasticity Rule in an Unsupervised Learning Environment.

Synaptic plasticity, or the ability of a brain to change one or more of its functions or structures at the synaptic level, has generated and is still generating a lot of interest from the scientific community especially from neuroscientists. These interests went into high gear after empirical evidence was collected that challenged the established paradigm that human brain structures and functions are set from childhood and only modest changes were expected beyond. Early synaptic plasticity rules or laws to that regard include the basic Hebbian rule that proposed a mechanism for strengthening or weakening of synapses (weights) during learning and memory. This rule, however, did not account for the fact that weights must have bounded growth over time. Thereafter, many other rules that possess other desirable properties were proposed to complement the basic Hebbian rule. In particular, a desirable property in a synaptic plasticity rule is that the ambient system must account for inhibition, which is often achieved if the rule used allows for a lower bound in synaptic weights. To that regard, in this letter, we propose such a synaptic plasticity rule that is inspired by the Allee effect, a phenomenon often observed in population dynamics. We show that properties such as synaptic normalization, competition between weights, decorrelation potential, and dynamic stability are satisfied. We show that in fact, an Allee effect in synaptic plasticity can be construed as an absence of plasticity.

Discrete Dynamics of Dynamic Neural Fields.

Large and small cortexes of the brain are known to contain vast amounts of neurons that interact with one another. They thus form a continuum of active neural networks whose dynamics are yet to be fully understood. One way to model these activities is to use dynamic neural fields which are mathematical models that approximately describe the behavior of these congregations of neurons. These models have been used in neuroinformatics, neuroscience, robotics, and network analysis to understand not only brain functions or brain diseases, but also learning and brain plasticity. In their theoretical forms, they are given as ordinary or partial differential equations with or without diffusion. Many of their mathematical properties are still under-studied. In this paper, we propose to analyze discrete versions dynamic neural fields based on nearly exact discretization schemes techniques. In particular, we will discuss conditions for the stability of nontrivial solutions of these models, based on various types of kernels and corresponding parameters. Monte Carlo simulations are given for illustration.

Increased Risk of Autism Development in Children Whose Mothers Experienced Birth Complications or Received Labor and Delivery Drugs.

Autism spectrum disorder (ASD) is a perplexing and pervasive developmental disorder characterized by social difficulties, communicative deficits, and repetitive behavior. The increased rate of ASD diagnosis has raised questions concerning the genetic and environmental factors contributing to the development of this disorder; meanwhile, the cause of ASD remains unknown. This study surveyed mothers of ASD and non-ASD children to determine possible effects of labor and delivery (L&D) drugs on the development of ASD. The survey was administered to mothers; however, the results were analyzed by child, as the study focused on the development of autism. Furthermore, an independent ASD dataset from the Southwest Autism Research and Resource Center was analyzed and compared. Indeed, L&D drugs are associated with ASD (p = .039). Moreover, the Southwest Autism Research and Resource Center dataset shows that the labor induction drug, Pitocin, is significantly associated with ASD (p = .004). We also observed a synergistic effect between administrations of L&D drugs and experiencing a birth complication, in which both obstetrics factors occurring together increased the likelihood of the fetus developing ASD later in life (p = .0003). The present study shows the possible effects of L&D drugs, such as Pitocin labor-inducing and analgesic drugs, on children and ASD.

Hierarchical competition models with the Allee effect II: the case of immigration.

This is part II of an earlier paper that dealt with hierarchical models with the Allee effect but with no immigration. In this paper, we greatly simplify the proofs in part I and provide a proof of the global dynamics of the non-hyperbolic cases that were previously conjectured. Then, we show how immigration to one of the species or to both would, drastically, change the dynamics of the system. It is shown that if the level of immigration to one or to both species is above a specified level, then there will be no extinction region where both species go to extinction.

Hierarchical competition models with Allee effects.

We consider a two-species hierarchical competition model with a strong Allee effect. The Allee effect is assumed to be caused by predator saturation. Moreover, we assume that there is a 'silverback' species x that gets first choice of the resources and where growth is limited by its own intraspecific competition, while the second 'inferior' species y gets whatever is left. Both species x and y are assumed to have the property of strong Allee effect. In this paper we determine the impact of the presence of the Allee effect on the global dynamics of both species.

Seasonal variation in results of diagnostic tests for pituitary pars intermedia dysfunction in older, clinically normal geldings.

OBJECTIVE: To determine whether seasonal variations exist in endogenous plasma ACTH, plasma α-melanocyte-stimulating hormone (α-MSH), serum cortisol, and serum insulin concentrations and in the results of a dexamethasone suppression test for older, clinically normal geldings in Alabama. DESIGN: Cohort study. ANIMALS: 15 healthy mixed-breed geldings (median age, 14 years). PROCEDURES: Sample collection was repeated monthly for 12 months. Dexamethasone (0.04 mg/kg [0.02 mg/lb], IM) was administered and cortisol concentrations were determined at 15 and 19 hours. Radioimmunoassays were used to measure ACTH, α-MSH, cortisol, and insulin concentrations at each testing time. Hormone concentrations were compared between months via repeated-measures ANOVA and correlated with age within each month. RESULTS: A significant time effect was found between months for α-MSH and insulin concentrations. Endogenous cortisol and ACTH concentrations remained within existing reference ranges. Significant correlations were detected between age and ACTH concentration for several fall and winter months and between age and insulin concentration for September. CONCLUSIONS AND CLINICAL RELEVANCE: Older horses have higher ACTH concentrations in several fall and winter months and higher insulin concentrations in September than do younger horses. Seasonally specific reference ranges are required for α-MSH and insulin concentrations, with significantly higher concentrations detected in the fall. Practitioners should be advised to submit samples only to local laboratories that can provide such reference ranges for their local geographic region.