Abstract

The reconstruction of large-scale nervous systems represents a major scientific and engineering challenge in current neuroscience research that needs to be resolved in order to understand the emergent properties of such systems. We focus on insect nervous systems because they represent a good compromise between architectural simplicity and the ability to generate a rich behavioral repertoire. In insects, several sensory maps have been reconstructed so far. We provide an overview over this work including our reconstruction of population activity in the primary olfactory network, the antennal lobe. Our reconstruction approach, that also provides functional connectivity data, will be refined and extended to allow the building of larger scale neural circuits up to entire insect brains, from sensory input to motor output.

Highlights

  • The brain is the most important information processing and control system in more highly developed animal organisms

  • Can we reasonably hope to understand how nervous systems work without considering them as entities that can only be dissociated with some compromises? Are not the non-neural constituents of an animal’s body and the environmental factors it is exposed to be included in our analyses? To work toward such an integrative approach, we have focused on insects, which have simple nervous systems compared to mammals, yet rich behavioral repertoires

  • Identifiable neurons are cells that can be uniquely recognized in each individual of a species, allowing the accumulation of physiological, morphological, pharmacological, and genetic information from different experiments

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Summary

Introduction

The brain is the most important information processing and control system in more highly developed animal organisms. We describe basic techniques for the reconstruction of sensory maps and future directions toward the modeling of entire behaviorally relevant neural circuits and whole insect brains. They generally have the same physiological, anatomical, and genetic properties so that we can compare and integrate the experimental data from different individuals.

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