2008 Special issue

Insect navigation arises from the coordinated action of concurrent guidance systems but the neural mechanisms through which each functions, and are then coordinated, remains unknown We propose that insects require distinct strategies to retrace familiar routes (route-following) and directly return from novel to familiar terrain (homing) using different aspects of frequency encoded views that are processed in different neural pathways We also demonstrate how the Central Complex and Mushroom Bodies regions of the insect brain may work in tandem to coordinate the directional output of different guidance cues through a contextually switched ring-attractor inspired by neural recordings The resultant unified model of insect navigation reproduces behavioural data from a series of cue conflict experiments in realistic animal environments and offers testable hypotheses of where and how insects process visual cues, utilise the different information that they provide and coordinate their outputs to achieve the adaptive behaviours observed in the wild

A decentralised neural model explaining optimal integration of navigational strategies in insects.

Robust insect navigation arises from the coordinated action of concurrent guidance systems but the neural mechanisms through which they function, and are coordinated, remain unknown. Our analysis suggests that insects require distinct visual homing and route following strategies which we propose use different aspects of frequency encoded views and different neural pathways: Mushroom Bodies for visual homing and Anterior Optic Tubercles for route following. We then demonstrate how the Central Complex and Mushroom Bodies work in tandem to coordinate the directional output of different guidance cues through contextually switched ring-attractor circuits inspired by neural recordings. The resultant unified model of insect navigation reproduces behavioral data from a series of cue conflict experiments in realistic animal environments and offers testable hypotheses of where and how insects process visual cues, utilise the different information provided and coordinate their outputs to achieve the adaptive behaviours observed in the wild.

https://www.biorxiv.org/content/biorxiv/early/2020/03/05/856153.full.pdf

A Decentralised Neural Model Explaining Optimal Integration Of Navigational Strategies in Insects

Bumblebees forage widely for pollen and nectar from flowers, sometimes travelling kilometers away from their nest, but they can somehow always find their way home in a nearly straight line. These insects have been known to return to their nest from new locations almost 10 kilometers away. This homing ability is a complex neurological feat and requires the brain to combine several processes, including observing the external world, controlling bodily movements and drawing on memory. While the navigational behavior of bees has been well-studied, the neuronal circuitry behind it has not. Unfortunately, most of what is known about insects’ brain activity comes from studies in species such as locusts or fruit flies. In these species, a region of the brain known as the central complex has been shown to have an essential role in homing behaviors. However, it is unknown how similar the central complex of bumblebees might be to fruit flies’ or locusts’, or how these differences may affect navigational abilities. Sayre et al. obtained images of thin slices of the bumblebee central complex using a technique called block-face electron microscopy, which produces high-resolution image volumes. These images were used to obtain a three-dimensional map of over 1300 neurons. This cellular atlas showed that key aspects of the central complex are nearly identical between flies and bumblebees, including the internal compass that monitors what direction the insect is travelling in. However, hundreds of millions of years of independent evolution have resulted in some differences. These were found in neurons possibly involved in forming memories of the directions and lengths of travelled paths, and in the circuits that use such vector memories to steer the insects towards their targets. Sayre et al. propose that these changes underlie bees’ impressive ability to navigate. These results help explain how the structure of insects’ brains can determine homing abilities. The insights gained could be used to develop efficient autonomous navigation systems, which are challenging to build and require a lot more processing power than offered by a small part of an insect brain.

A projectome of the bumblebee central complex.

Insects have evolved diverse and remarkable strategies for navigating in various ecologies all over the world. Regardless of species, insects share the presence of a group of morphologically conserved neuropils known collectively as the central complex (CX). The CX is a navigational hub, involved in sensory integration and coordinated motor activity. Despite the fact that our understanding of navigational behavior comes predominantly from ants and bees, most of what we know about the underlying neural circuitry of such behavior comes from work in fruit flies. Here we aim to close this gap, by providing the first comprehensive map of all major columnar neurons and their projection patterns in the CX of a bee. We find numerous components of the circuit that appear to be highly conserved between the fly and the bee, but also highlight several key differences which are likely to have important functional ramifications.

https://www.biorxiv.org/content/biorxiv/early/2021/03/29/2021.03.26.437137.full.pdf

A projectome of the bumblebee central complex

The lateral accessory lobes (LALs), paired structures that are homologous among all insect species, have been well studied for their role in pheromone tracking in silkmoths and phonotaxis in crickets, where their outputs have been shown to correlate with observed motor activity. Further studies have shown more generally that the LALs are crucial both for an insect's ability to steer correctly and for organising the outputs of the descending pathways towards the motor centres. In this context, we propose a framework by which the LALs may be generally involved in generating steering commands across a variety of insects and behaviours. Across different behaviours, we see that the LAL is involved in generating two kinds of steering: (1) search behaviours and (2) targeted steering driven by direct sensory information. Search behaviours are generated when the current behaviourally relevant cues are not available, and a well-described LAL subnetwork produces activity which increases sampling of the environment. We propose that, when behaviourally relevant cues are available, the LALs may integrate orientation information from several sensory modalities, thus leading to a collective output for steering driven by those cues. These steering commands are then sent to the motor centres, and an additional efference copy is sent back to the orientation-computing areas. In summary, we have taken known aspects of the neurophysiology and function of the insect LALs and generated a speculative framework that suggests how LALs might be involved in steering control for a variety of complex real-world behaviours in insects.

/pdf/connecting-brain-to-behaviour-a-role-for-general-purpose-4nbr9h6ye2.pdf

Connecting brain to behaviour: a role for general purpose steering circuits in insect orientation?

We develop a spiking neural network model of an insect-inspired CPG which is used to underpin steering behaviour for a Braitenberg-like vehicle. We show that small scale search behaviour, produced by the CPG, improves navigation by recovering useful sensory signals.

Can Small Scale Search Behaviours Enhance Large-Scale Navigation?

Navigation in ever-changing environments requires effective motor behaviours. Many insects have developed adaptive movement patterns which increase their success in achieving navigational goals. A conserved brain area in the insect brain, the Lateral Accessory Lobe, is involved in generating small scale search movements which increase the efficacy of sensory sampling. When the reliability of an essential navigational stimulus is low, searching movements are initiated whereas if the stimulus reliability is high, a targeted steering response is elicited. Thus the network mediates an adaptive switching between motor patterns. We developed Spiking Neural Network models to explore how an insect inspired architecture could generate adaptive movements in relation to changing sensory inputs. The models are able to generate a variety of adaptive movement patterns, the majority of which are of the zig-zagging kind, as seen in a variety of insects. Furthermore, these networks are robust to noise. Because a large spread of network parameters lead to the zig-zagging movement dynamics, we conclude that the investigated network architecture is inherently well suited to generating adaptive movement patterns.

/pdf/production-of-adaptive-movement-patterns-via-an-insect-2onsa6nk.pdf

Production of adaptive movement patterns via an insect inspired spiking neural network central pattern generator

Navigation in ever-changing environments requires effective motor behaviours. Many insects have developed adaptive movement patterns which increase their success in achieving navigational goals. A conserved brain area in the insect brain, the Lateral Accessory Lobe, is involved in generating small scale search movements which increase the efficacy of sensory sampling. When the reliability of an essential navigational stimulus is low, searching movements are initiated whereas if the stimulus reliability is high, a targeted steering response is elicited. Thus the network mediates an adaptive switching between motor patterns. We developed Spiking Neural Network models to explore how an insect inspired architecture could generate adaptive movements in relation to changing sensory inputs. The models are able to generate a variety of adaptive movement patterns, the majority of which are of the zig-zagging kind, as seen in a variety of insects. Furthermore, these networks are robust to noise. Because a large spread of network parameters lead to the zig-zagging movement dynamics, we conclude that the investigated network architecture is inherently well suited to generating adaptive movement patterns. 

Fabian Steinbeck

Papers

Connecting brain to behaviour: a role for general purpose steering circuits in insect orientation?

Can Small Scale Search Behaviours Enhance Large-Scale Navigation?

Production of adaptive movement patterns via an insect inspired spiking neural network central pattern generator

Production of adaptive movement patterns via an insect inspired Spiking Neural Network Central Pattern Generator.

Spatial Cognition: Allowing Natural Behaviours to Flourish in the Lab.