Self-Organized Criticality in Developing Neuronal Networks

Recently evidence has accumulated that many neural networks exhibit self-organized criticality. In this state, activity is similar across temporal scales and this is beneficial with respect to information flow. If subcritical, activity can die out, if supercritical epileptiform patterns may occur. Little is known about how developing networks will reach and stabilize criticality. Here we monitor the development between 13 and 95 days in vitro (DIV) of cortical cell cultures (n = 20) and find four different phases, related to their morphological maturation: An initial low-activity state (≈19 DIV) is followed by a supercritical (≈20 DIV) and then a subcritical one (≈36 DIV) until the network finally reaches stable criticality (≈58 DIV). Using network modeling and mathematical analysis we describe the dynamics of the emergent connectivity in such developing systems. Based on physiological observations, the synaptic development in the model is determined by the drive of the neurons to adjust their connectivity for reaching on average firing rate homeostasis. We predict a specific time course for the maturation of inhibition, with strong onset and delayed pruning, and that total synaptic connectivity should be strongly linked to the relative levels of excitation and inhibition. These results demonstrate that the interplay between activity and connectivity guides developing networks into criticality suggesting that this may be a generic and stable state of many networks in vivo and in vitro

Molecular and Behavioral Differentiation among Brazilian Populations of Lutzomyia longipalpis (Diptera: Psychodidae: Phlebotominae)

Lutzomyia longipalpis is the main vector of visceral leishmaniasis in the Americas. There is strong evidence that L. longipalpis is a species complex, but there is still no consensus regarding the number of species occurring in Brazil. We combined molecular and behavioral analyses of a number of L. longipalpis populations in order to help clarify this question. This approach has allowed us to identify two main groups of populations in Brazil. One group probably represents a single species distributed mainly throughout the coastal regions of North and Northeast Brazil and whose males produce the same type of copulation song and pheromone. The second group is more heterogeneous, probably represented by a number of incipient species with different levels of genetic divergence among the siblings that produce different combinations of copulation songs and pheromones. The high level of complexity observed raises important questions concerning the epidemiological consequences of this incipient speciation process

Learning Backward Induction: A Neural Network Agent Approach

This paper addresses the question of whether neural networks (NNs), a realistic cognitive model of human information processing, can learn to backward induce in a two-stage game with a unique subgame-perfect Nash equilibrium. The NNs were found to predict the Nash equilibrium approximately 70% of the time in new games. Similarly to humans, the neural network agents are also found to suffer from subgame and truncation inconsistency, supporting the contention that they are appropriate models of general learning in humans. The agents were found to behave in a bounded rational manner as a result of the endogenous emergence of decision heuristics

Regulation of neuronal survival by the extracellular signal-regulated protein kinase 5

The extracellular signal-regulated protein kinase 5 (ERK5) is a mitogen-activated protein kinase (MAPK) that phosphorylates and regulates various transcription factors in response to growth factors and extra-cellular stresses. To address its biological function during the development of the peripheral nervous system (PNS), we have engineered a novel model of sympathetic neurons in which the erk5 gene can be deleted in vitro. Our data provide for the first time genetic evidence that ERK5 is required to mediate the survival response of neurons to nerve growth factor (NGF). Increased cell death associated with the loss of ERK5 is caused by elevated expression of the BH3-only members of the Bcl-2 family, Bad and Bim. Further investigation indicated that ERK5 suppresses the transcription of the bad and the bim genes via Ca(++)/cAMP response element binding protein (CREB) and Forkhead box 03a (Foxo3a), respectively. Consistently, we found that the phosphorylation of both p90 ribosomal S6 kinase (RSK) and protein kinase B (PKB) is impaired in neurons lacking ERK5. Together these findings reveal a novel signaling mechanism that promotes neuronal survival during the development of the PNS

Object imagery and object identification: Object imagers are better at identifying spatially-filtered visual objects

Object imagery refers to the ability to construct pictorial images of objects. Individuals with high object imagery (high-OI) produce more vivid mental images than individuals with low object imagery (low-OI), and they encode and process both mental images and visual stimuli in a more global and holistic way. In the present study, we investigated whether and how level of object imagery may affect the way in which individuals identify visual objects. High-OI and low-OI participants were asked to perform a visual identification task with spatially-filtered pictures of real objects. Each picture was presented at nine levels of filtering, starting from the most blurred (level 1: only low spatial frequencies-global configuration) and gradually adding high spatial frequencies up to the complete version (level 9: global configuration plus local and internal details). Our data showed that high-OI participants identified stimuli at a lower level of filtering than participants with low-OI, indicating that they were better able than low-OI participants to identify visual objects at lower spatial frequencies. Implications of the results and future developments are discussed