Biology subjects

Mangan, M.

Publications and source records attributed to Mangan, M..

9 recordsLinked to original sources

bioRxiv2026

What do navigating animals see? Reconstructing the visual histories of desert ants

To understand how brains translate sensory input into behavioural outputs requires a fuller account of the sensory experience of individual animals in their natural settings. Previously we developed a visual rendering software capable of reconstructing the information that insect's compound eyes perceive (Millward et al, 2022). In this work, we extend this software pipeline to integrate data from animal tracking, habitat mapping, and compound eye modelling methods. The result is a new type of dataset that documents the natural foraging behaviour of desert ants (a model species for the study of animal navigation) within their natural habitat, combined with simulation tools to accurately reconstruct the visual experience of each forager as they learned to navigate their surroundings. This addresses a long-held need to create realistic training input for brain models complimented with verification tests in the same real ecologically relevant scenarios.

animal behavior and cognition↗

bioRxiv2026

Involvement of Mitophagy in Endothelin-1 Mediated Neurodegeneration in Rodent Models of Glaucoma

The ultimate cause of blindness in glaucoma is the death of retinal ganglion cells, and understanding the mechanism behind retinal ganglion cell loss during glaucoma could lead to the development of novel treatments for glaucoma. Endothelin-1 has been shown to mediate retinal ganglion cell death during glaucoma through impairment of mitochondrial function. Retinal ganglion cells are highly metabolically active, and susceptible to oxidative damage and decreased respiratory capacity. Mitophagy is the process whereby damaged mitochondria are degraded to prevent further propagation of oxidative damage. The current study evaluates the effect of endothelin-1 on mitophagy in retinal ganglion cells. Electron microscopy revealed endothelin-1 administration lead to a decrease in healthy mitochondria in the optic nerve. The MitoQC mouse was used to evalute mitophagy in response to endothelin-1, along with immunohistochemical analysis of mitophagy proteins. Mitophagy follows different trends in the optic nerve and retinal ganglion cell bodies following endothelin-1 administration, mitophagy was increased in the optic nerve but decreased in the retina following endothelin administration. With elevation of intraocular pressure, mitophagy was increased in the retina but decreased in the optic nerve. In retinal ganglion cells, parkin expression and activation was unchanged 24 hours after endothelin-1 administration, but was decreased 72 hours following endothelin-1 administration. Taken together, these results suggest that endothelin-1 impacts mitophagy through parkin-independent mechanisms in retinal ganglion cell bodies, and the ganglion cell bodies and optic nerve appear to have different responses to endothelin-1.

neuroscience↗

bioRxiv2024

I2Bot: an open-source tool for multi-modal and embodied simulation of insect navigation

Achieving a comprehensive understanding of animal intelligence demands an integrative approach that acknowledges the interplay between an organisms brain, body, and environment. Insects like ants, despite their limited computational resources, demonstrate remarkable abilities in navigation. Existing computational models often fall short in faithfully replicating the morphology of real insects and their interactions with the environment, hindering validation and practical application in robotics. To address these gaps, we present I2Bot, a novel simulation tool based on the morphological characteristics of desert ants. This tool empowers robotic models with dynamic sensory capabilities, realistic modelling of insect morphology, physical dynamics, and sensory capacity. By integrating gait controllers and computational models into I2Bot, we have implemented classical embodied navigation behaviours and revealed some fundamental navigation principles. By open-sourcing I2Bot, we aim to accelerate the understanding of insect intelligence and foster advances in the development of autonomous robotic systems.

animal behavior and cognition↗

bioRxiv2021

CompoundRay: An open-source tool for high-speed and high-fidelity rendering of compound eyes

Revealing the functioning of non-standard visual systems such as compound eyes is of interest to biologists and engineers alike. A key investigative method is to replicate the sensory apparatus using artificial systems, allowing for investigation of the visual information that drives animal behaviour when exposed to environmental cues. To date, Compound Eye Models (CEMs) have largely explored the impact of features such as spectral sensitivity, field of view, and angular resolution on behaviour. Yet, the role of shape and overall structure have been largely overlooked due to modelling complexity. However, modern real-time raytracing technologies are enabling the construction of a new generation of computationally fast, high-fidelity CEMs. This work introduces new open-source CEM software (CompoundRay) alongside standardised usage techniques, while also discussing the diffculties inherent with visual data display and analysis of compound eye perceptual data. CompoundRay is capable of accurately rendering the visual perspective of a desert ant at over 5,000 frames per second in a 3D mapped natural environment. It supports ommatidial arrangements at arbitrary positions with per-ommatidial heterogeneity.

systems biology↗

bioRxiv2021

How the insect central complex could coordinate multimodal navigation

The central complex of the insect midbrain is thought to coordinate insect guidance strategies. Computational models can account for specific behaviours but their applicability across sensory and task domains remains untested. Here we assess the capacity of our previous model explaining visual navigation to generalise to olfactory navigation and its coordination with other guidance in flies and ants. We show that fundamental to this capacity is the use of a biologically-realistic neural copy-and-shift mechanism that ensures sensory information is presented in a format compatible with the insect steering circuit regardless of its source. Moreover, the same mechanism is shown to transfer cues from unstable/egocentric to stable/geocentric frames of reference providing a first account of the mechanism by which foraging insects robustly recover from environmental disturbances. We propose that these circuits can be flexibly repurposed by different insect navigators to address their unique ecological needs.

animal behavior and cognition↗

bioRxiv2020

Spatio-temporal Memory for Navigation in a Mushroom Body Model

Insects, despite relatively small brains, can perform complex navigation tasks such as memorising a visual route. The exact format of visual memory encoded by neural systems during route learning and following is still unclear. Here we propose that interconnections between Kenyon cells in the Mushroom Body (MB) could encode spatio-temporal memory of visual motion experienced when moving along a route. In our implementation, visual motion is sensed using an event-based camera mounted on a robot, and learned by a biologically constrained spiking neural network model, based on simplified MB architecture and using modified leaky integrate-and-fire neurons. In contrast to previous image-matching models where all memories are stored in parallel, the continuous visual flow is inherently sequential. Our results show that the model can distinguish learned from unlearned route segments, with some tolerance to internal and external noise, including small displacements. The neural response can also explain observed behaviour taken to support sequential memory in ant experiments. However, obtaining comparable robustness to insect navigation might require the addition of biomimetic pre-processing of the input stream, and determination of the appropriate motor strategy to exploit the memory output.

animal behavior and cognition↗

bioRxiv2019

BTK operates a phospho-tyrosine switch to regulate NLRP3 inflammasome activity

Activity of the NLRP3 inflammasome, a critical mediator of inflammation (1), is controlled by accessory proteins (2, 3), post-translational modifications (4, 5), cellular localization (6, 7) and oligomerization (8). How these factors relate, is unclear. We show that the established drug target, Brutons Tyrosine Kinase (BTK) (2, 9), integrates several levels of NLRP3 regulation: BTK phosphorylation of four conserved tyrosine residues, by neutralizing the charge of a polybasic linker region, weakens the interaction of NLRP3 with Golgi phospholipids and may thus guide NLRP3 cytosolic localization. BTK activity also promotes NLRP3 oligomerization and subsequent formation of inflammasomes. As NLRP3 tyrosine modification ultimately also impacts on IL-1{beta} release, we propose BTK-mediated, charge-switch-based NLRP3 regulation as a novel and therapeutically tractable step in the control of inflammation. One Sentence SummaryMulti-phosphorylation of NLRP3 by Brutons tyrosine kinase modulates NLRP3 cellular localization, inflammasome assembly, and IL-1{beta} release.

immunology↗

bioRxiv2019

Modelling the Insect Navigation Toolkit: How the Mushroom Bodies and Central Complex Coordinate Guidance Strategies

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.

animal behavior and cognition↗

bioRxiv2018

From skylight input to behavioural output: a computational model of the insect polarised light compass

Many insects navigate by integrating the distances and directions travelled on an outward path, allowing direct return to the starting point. Fundamental to the reliability of this process is the use of a neural compass based on external celestial cues. Here we examine how such compass information could be reliably computed by the insect brain, given realistic constraints on the sky polarisation pattern and the insect eye sensor array. By processing the degree of polarisation in different directions for different parts of the sky, our model can directly estimate the solar azimuth and also infer the confidence of the estimate. We introduce a method to correct for tilting of the sensor array, as might be caused by travel over uneven terrain. We also show that the confidence can be used to approximate the change in sun position over time, allowing the compass to remain fixed with respect to true north during long excursions. We demonstrate that the compass is robust to disturbances and can be effectively used as input to an existing neural model of insect path integration. We discuss the plausibility of our model to be mapped to known neural circuits, and to be implemented for robot navigation.\n\nAuthor summaryWe propose a new hypothesis for how insects process polarised skylight to extract global orientation information that can be used for accurate path integration. Our model solves the problem of solar/anti-solar meridian ambiguity by using a biologically constrained sensor array, and includes methods to deal with tilt and time, providing a complete insect celestial compass output. We analyse the performance of the model using a realistic sky simulation and various forms of disturbances, and compare the results to both engineering approaches and biological data.

animal behavior and cognition↗