Introduction to Realistic Neural Modeling

This document corresponds to the tutorial on realistic neural modeling given by David Beeman at WAM-BAMM*05, the first annual meeting of the World Association of Modelers (WAM) Biologically Accurate Modeling Meeting (BAMM) on March 31, 2005 in San Antonio, TX. Part I - Introduction to Realistic Neural Modeling for the Beginner: This is a general overview and introduction to compartmental cell modeling and realistic network simulation for the beginner. Although examples are drawn from GENESIS simulations, the tutorial emphasizes the general modeling approach, rather than the details of using any particular simulator. Part II - Getting Started with Modeling Using GENESIS: This builds upon the background of Part I to describe some details of how this approach is used to construct cell and network simulations in GENESIS. It serves as an introduction and roadmap to the extended hands-on GENESIS Modeling Tutorial.

Using P-GENESIS for Parallel Simulation of GENESIS Models

P-GENESIS is an extension to the GENESIS neural simulator that allows users to take advantage of parallel machines to speed up the simulation of their network models or concurrently simulate multiple models. P-GENESIS adds several commands to the GENESIS script language that let a script running on one processor execute remote procedure calls on other processors, and that let a script synchronize its execution with the scripts running on other processors. We present here some brief comments on the mechanisms underlying parallel script execution. We also offer advice on parallelizing parameter searches, partitioning network models, and selecting suitable parallel hardware on which to run P-GENESIS.

Analyzing online communication from a social network point of view: questions, problems, perspectives

This programmatic paper investigates the possibilities, chances, and risks of analyzing personal and professional online communication from the point of view of interactional sociolinguistics combined with modern social network analysis (SNA). Thus, it has two complementing goals: One is the exploration of adequate, innovative concepts and methods for analyzing online communication, the other is to use online communication and its ontological and functional specificities to enrich the conceptual and methodological background of SNA. The paper is organized in two parts. It begins with an introduction to recent developments in sociolinguistic social network analysis. Here, three interesting new concepts and tools are discussed: latent versus emergent networks (Watts 1991), coalitions (Fitzmaurice 2000a, Fitzmaurice 2000b), and communities of practice (Wenger 1998

SNNAP: A Tool for Teaching Neuroscience

Simulation tools aid in learning neuroscience by providing the student with an interactive environment to carry out simulated experiments and test hypotheses. The field of neuroscience is well suited for the use of simulation tools since nerve cell signaling can be described by mathematical equations and solved by computer. Neural signaling entails the propagation of electrical current along nerve membrane and transmission to neighboring neurons through synaptic connections. Action potentials and synaptic transmission can be simulated and results displayed for visualization and analysis. The neurosimulator SNNAP (Simulator for Neural Networks and Action Potentials) is a simulation environment that provides users with editors for model building, simulator engine and visual display editor. This paper presents several modeling examples that illustrate some of the capabilities and features of SNNAP. First, the Hodgkin-Huxley (HH) model is presented and the threshold phenomenon is illustrated. Second, small neural networks are described with HH models using various synaptic connections available with SNNAP. Synaptic connections may be modulated through facilitation or depression with SNNAP. A study of vesicle pool dynamics is presented using an AMPA receptor model. Finally, a central pattern generator model of the Aplysia feeding circuit is illustrated as an example of a complex network that may be studied with SNNAP. Simulation code is provided for each case study described and tasks are suggested for further investigation.

Simbrain: A visual framework for neural network analysis and education

Simbrain is a visually-oriented framework for building and analyzing neural networks. It emphasizes the analysis of networks which control agents embedded in virtual environments, and visualization of the structures which occur in the high dimensional state spaces of these networks. The program was originally intended to facilitate analysis of representational processes in embodied agents, however it is also well suited to teaching neural networks concepts to a broader audience than is traditional for neural networks courses. Simbrain was used to teach a course at a new university, UC Merced, in its inaugural year. Experiences from the course and sample lessons are provided.

Perceived Influence and Friendship as Antecedents of Cooperation in Top Management Teams: A Network Approach

Using the relational dyad as unit of analysis this study examines the effects of perceived influence and friendship ties on the formation and maintenance of cooperative relationships between corporate top executives. Specifically, it is argued that perceived influence as well as friendship ties between any two managers will enhance the likelihood that these managers collaborate with each other. Additionally, a negative interaction effect between perceived influence and friendship on cooperation is proposed. The empirical analyses draw on network data that have been collected among all members of the top two organizational levels for the strategy-making process in two multinational firms headquartered in Germany. Applying logistic regression based on QAP the empirical results support our hypotheses on the direct effects between perceived influence, friendship ties, and cooperative relationships in both companies. In addition, we find at least partial support for our assumption that perceived influence and friendship interact negatively with respect to their effect on cooperation. Seemingly, perceived influence is partially substituted by managerial friendship ties.