The evolution of neural circuits for navigational decisions - from synapses to behavior

Introduction

Of the 1.2 million animal species described on Earth, more than 80% are insects. As for mammals, each insect is equipped with a brain that has evolved to optimally control the species’ behavior in the context of its environment.

Evolution of Neural Circuits

In more than 450 million years of evolution, the neural circuits guiding behavioral decisions have diverged from an ancestral version to enable insects to conquer every terrestrial habitat on the planet. This evolution has equipped many species with behavioral strategies that rival even mammals in complexity.

These circuits thus have to be:

• Rigid enough to maintain their ancestral, core functions
• Sufficiently adaptable to enable the addition of novel functions

The mechanisms of how this is achieved across vast evolutionary timescales are unknown.

Unique Opportunity in Insect Study

While this is true for all animals, insects, with their numerically simpler brains and a comparably rigid neuroarchitecture, offer the unique chance to unravel the evolution of decision-making circuits at the level of identified neurons and synapses.

Research Approach

Aided by recent technological breakthroughs and the establishment of rich ground-truth data in the fruit fly, I will combine:

1. Whole brain anatomy
2. Connectomics
3. Computational modeling
4. Electrophysiology
5. Behavior

This approach will allow me to dissect the evolution of the central decision-making center of insect brains, the central complex, across the entire insect phylogeny.

Objectives

I aim to reveal:

• How this region has evolved in the context of the entire brain
• How its intrinsic circuits have changed with increasing evolutionary distance (circuit phylogeny)
• Which changes in its circuitry are linked to specialized behavioral abilities (circuit adaptation)

Finally, I will directly establish behavioral correlates of identified circuit features (circuit function), attaching relevance to connectomics data in a way that is achievable only by a wide, comparative approach. This will raise our understanding of structure-function relations in animal nervous systems to a new level.