Building a model of the brain: from detailed connectivity maps to network organization

TL;DR

This paper reviews recent computational models of brain circuits based on experimental connectivity maps, highlighting their features and guiding modelers in selecting appropriate models for neurobiological questions.

Contribution

It provides a comprehensive tutorial review of models derived from connectivity maps, aiding researchers in understanding and choosing suitable brain network models.

Findings

Comparison of different brain circuit models

Guidelines for selecting models based on connectivity data

Emphasis on the importance of connectivity maps in modeling

Abstract

The field of computational modeling of the brain is advancing so rapidly that now it is possible to model large scale networks representing different brain regions with a high level of biological detail in terms of numbers and synapses. For a theoretician approaching a neurobiological question, it is important to analyze the pros and cons of each of the models available. Here, we provide a tutorial review on recent models for different brain circuits, which are based on experimentally obtained connectivity maps. We discuss particularities that may be relevant to the modeler when choosing one of the reviewed models. The objective of this review is to give the reader a fair notion of the computational models covered, with emphasis on the corresponding connectivity maps, and how to use them.