Inducible cAMP Early Repressor (ICER) and Brain Functions

The inducible cAMP early repressor (ICER) is an endogenous repressor of cAMP-responsive element (CRE)-mediated gene transcription and belongs to the CRE-binding protein (CREB)/CRE modulator (CREM)/activating transcription factor 1 (ATF-1) gene family. ICER plays an important role in regulating the neuroendocrine system and the circadian rhythm. Other aspects of ICER function have recently attracted heightened attention. Being a natural inducible CREB antagonist, and more broadly, an inducible repressor of CRE-mediated gene transcription, ICER regulates long-lasting plastic changes that occur in the brain in response to incoming stimulation. This review will bring together data on ICER and its functions in the brain, with a special emphasis on recent findings highlighting the involvement of ICER in the regulation of long-term plasticity underlying learning and memory

Early phase of plasticity-related gene regulation and SRF dependent transcription in the hippocampus

Hippocampal organotypic cultures are a highly reliable in vitro model for studying neuroplasticity: in this paper, we analyze the early phase of the transcriptional response induced by a 20 \ub5M gabazine treatment (GabT), a GABA-Ar antagonist, by using Affymetrix oligonucleotide microarray, RT-PCR based time-course and chromatin-immuno-precipitation. The transcriptome profiling revealed that the pool of genes up-regulated by GabT, besides being strongly related to the regulation of growth and synaptic transmission, is also endowed with neuro-protective and pro-survival properties. By using RT-PCR, we quantified a time-course of the transient expression for 33 of the highest up-regulated genes, with an average sampling rate of 10 minutes and covering the time interval [10 3690] minutes. The cluster analysis of the time-course disclosed the existence of three different dynamical patterns, one of which proved, in a statistical analysis based on results from previous works, to be significantly related with SRF-dependent regulation (p-value<0.05). The chromatin immunoprecipitation (chip) assay confirmed the rich presence of working CArG boxes in the genes belonging to the latter dynamical pattern and therefore validated the statistical analysis. Furthermore, an in silico analysis of the promoters revealed the presence of additional conserved CArG boxes upstream of the genes Nr4a1 and Rgs2. The chip assay confirmed a significant SRF signal in the Nr4a1 CArG box but not in the Rgs2 CArG box

Emergent Behavior of Interacting Groups of Communicative Agents

This paper presents a simulation of the behavior of different species of birds, which share the same habitat, but manage to use different times of the day to sing their songs. Therefore, they avoid a vocal competition and improve the conditions to find a mate. Communicative agents are used to model the birds and their behavior. A simple set of rules is used to make the decisions when and how to change the time for the search for a mate. By incorporating damping and amplifying feedback loops the collective behavior of each species led the system to a solution which was favorable to all agents

An associative memory for autonomous agents

To improve the abilities of a behavior based autonomous agent a biologically inspired memory is introduced. The memory content is built up from scratch. The data containers, called mnemograms, are general and flexible enough to handle different kinds of data. Using a reinforcement mechanism valuable mnemograms are separated from those of lesser value. Mnemograms are stored in three hierarchically ordered layers to separate new from older ones. This is important for organizing search runs. The data containers are linked together, thus, a first level of semantical information is created. A first simple behavior takes advantage of these structures. It enables the agent learn to distinguish between food particles and other particles

Organizing an Agent&apos;s Memory

The architecture of a memory for autonomous agents is presented. It is base

Organizing an agent's memory

The architecture of a memory for autonomous agents is presented. It is based on an interconnected network of data containers. The memory design principles follow the requirements of supporting action selection mechanisms, planning, and learning capabilities. Different types of data are organized in four segments

Simulation of the Coevolution Of Insects And Flowers

Flowers need insects for their pollination and insects rely on the nectar and the pollen as a food resource. But instead of visiting all flowers, the insects limit their visits to a small number. This paper presents a simulation of the behavior of the insects which results in a specialized perception of blossom colors and fragrances by the insects.

Memory-based Behavior Coordination in Animats

This paper presents an action selection mechanism which makes use of a memory, especially designed for autonomous agents, to choose actions while considering earlier experiences. A reinforcement mechanism separates the more successful choices from the others. But the selection mechanism is still kept open to new actions or older ones, which failed more often, to be adaptable to future changes in the animat&apos;s environment