Simulating in vivo-like Synaptic Input Patterns in Multicompartmental Models

In the laboratory of Dr. Dieter Jaeger at Emory University, we use computer simulations to study how the biophysical properties of neurons—including their three-dimensional structure, passive membrane resistance and capacitance, and active membrane conductances generated by ion channels—affect the way that the neurons transfer synaptic inputs into the action potential streams that represent their output. Because our ultimate goal is to understand how neurons process and relay information in a living animal, we try to make our computer simulations as realistic as possible. As such, the computer models reflect the detailed morphology and all of the ion channels known to exist in the particular neuron types being simulated, and the model neurons are tested with synaptic input patterns that are intended to approximate the inputs that real neurons receive in vivo. The purpose of this workshop tutorial was to explain what we mean by ‘in vivo-like’ synaptic input patterns, and how we introduce these input patterns into our computer simulations using the freely available GENESIS software package (http://www.genesis-sim.org/GENESIS). The presentation was divided into four sections: first, an explanation of what we are talking about when we refer to in vivo-like synaptic input patterns

Curricular Integration of Simulations in Neuroscience - Instructional and Technical Perspectives

In recent years interactive media and tools, like scientific simulations and simulation environments or dynamic data visualizations, became established methods in the neural and cognitive sciences. Hence, university teachers of neural and cognitive sciences are faced with the challenge to integrate these media into the neuroscientific curriculum. Especially simulations and dynamic visualizations offer great opportunities for teachers and learners, since they are both illustrative and explorable. However, simulations bear instructional problems: they are abstract, demand some computer skills and conceptual knowledge about what simulations intend to explain. By following two central questions this article provides an overview on possible approaches to be applied in neuroscience education and opens perspectives for their curricular integration: (i) How can complex scientific media be transformed for educational use in an efficient and (for students on all levels) comprehensible manner and (ii) by what technical infrastructure can this transformation be supported? Exemplified by educational simulations for the neurosciences and their application in courses, answers to these questions are proposed a) by introducing a specific educational simulation approach for the neurosciences b) by introducing an e-learning environment for simulations, and c) by providing examples of curricular integration on different levels which might help academic teachers to integrate newly created or existing interactive educational resources in their courses.