Connectome-constrained networks predict neural activity across the fly visual system

Nature, Год журнала: 2024, Номер 634(8036), С. 1132 - 1140

Опубликована: Сен. 11, 2024

Язык: Английский

---

The fly connectome reveals a path to the effectome

Nature, Год журнала: 2024, Номер 634(8032), С. 201 - 209

Опубликована: Окт. 2, 2024

Язык: Английский

---

NeuroMechFly 2.0, a framework for simulating embodied sensorimotor control in adultDrosophila

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2023, Номер unknown

Опубликована: Сен. 18, 2023

Abstract Discovering principles underlying the control of animal behavior requires a tight dialogue between experiments and neuromechanical models. Until now, such models, including NeuroMechFly for adult fly, Drosophila melanogaster , have primarily been used to investigate motor control. Far less studied with realistic body models is how brain systems work together perform hierarchical sensorimotor Here we present v2, framework that expands modeling by enabling visual olfactory sensing, ascending feedback, complex terrains can be navigated using leg adhesion. We illustrate its capabilities first constructing biologically inspired locomotor controllers use feedback path integration head stabilization. Then, add sensing this controller train it reinforcement learning multimodal navigation task in closed loop. Finally, more biorealistic two ways: our model navigates odor plume taxis strategy, uses connectome-constrained system network follow another simulated fly. With framework, accelerate discovery explanatory nervous develop machine learning-based autonomous artificial agents robots.

Язык: Английский

---

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

Journal of The Royal Society Interface, Год журнала: 2025, Номер 22(222)

Опубликована: Янв. 1, 2025

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

Язык: Английский

---

Sensorimotor delays constrain robust locomotion in a 3D kinematic model of fly walking

Опубликована: Март 20, 2025

Walking animals must maintain stability in the presence of external perturbations, despite significant temporal delays neural signaling and muscle actuation. Here, we develop a 3D kinematic model with layered control architecture to investigate how sensorimotor constrain robustness walking behavior fruit fly, Drosophila. Motivated by anatomical insect locomotor circuits, our consists three component layers: network that generates realistic joint kinematics for each leg, an optimal controller executes while accounting delays, inter-leg coordinator. The simulated resembles real fly sustains even when subjected unexpected generalizing beyond its training data. However, found model’s perturbations deteriorates delay parameters exceed physiological range. These results suggest circuits operate close limit at which they can detect respond perturbations. More broadly, show modular, be used constraints on animal behavior.

Язык: Английский

---

The fruit fly, Drosophila melanogaster , as a microrobotics platform

Proceedings of the National Academy of Sciences, Год журнала: 2025, Номер 122(15)

Опубликована: Апрель 8, 2025

Engineering small autonomous agents capable of operating in the microscale environment remains a key challenge, with current systems still evolving. Our study explores fruit fly, Drosophila melanogaster , classic model system biology and species adept at interaction, as biological platform for microrobotics. Initially, we focus on remotely directing walking paths flies an experimental arena. We accomplish this through two distinct approaches: harnessing flies’ optomotor response optogenetic modulation its olfactory system. These techniques facilitate reliable repeated guidance between arbitrary spatial locations. guide along predetermined trajectories, enabling them to scribe patterns resembling textual characters their locomotion. enhance olfactory-guided navigation additional activation attraction-inducing mushroom body output neurons. extend control collective behaviors shared spaces constrained maze-like environments. further use our technique enable carry load across designated points space, establishing upper bound weight-carrying capabilities. Additionally, demonstrate that visual can novel interactions objects, showing consistently relocate spherical object over significant distances. Last, multiagent formation control, alternating patterns. Beyond expanding tools available microrobotics, these behavioral contexts provide insights into neurological basis behavior flies.

Язык: Английский

---

The fruit fly, Drosophila melanogaster, as a micro-robotics platform.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Май 26, 2024

Abstract Engineering small autonomous agents capable of operating in the microscale environment remains a key challenge, with current systems still evolving. Our study explores fruit fly, Drosophila melanogaster , classic model system biology and species adept at interaction, as biological platform for micro-robotics. Initially, we focus on remotely directing walking paths flies an experimental arena. We accomplish this through two distinct approaches: harnessing flies’ opto-motor response optogenetic modulation its olfactory system. These techniques facilitate reliable repeated guidance between arbitrary spatial locations. guide along predetermined trajectories, enabling them to scribe patterns resembling textual characters their locomotion. enhance olfactory-guided navigation additional activation positive valence mushroom body output neurons. extend control collective behaviors shared spaces constrained maze-like environments. further use our technique enable carry load across designated points space, establishing upper bound weight carrying capabilities. Additionally, demonstrate that visual can novel interactions objects, showing consistently relocate spherical object over significant distances. Beyond expanding tools available micro-robotics, these behavioral contexts provide insights into neurological basis behavior flies.

Язык: Английский

---

Sensorimotor delays constrain robust locomotion in a 3D kinematic model of fly walking

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Апрель 22, 2024

Abstract Walking animals must maintain stability in the presence of external perturbations, despite significant temporal delays neural signaling and muscle actuation. Here, we develop a 3D kinematic model with layered control architecture to investigate how sensorimotor constrain robustness walking behavior fruit fly, Drosophila. Motivated by anatomical insect locomotor circuits, our consists three component layers: network that generates realistic joint kinematics for each leg, an optimal controller executes while accounting delays, inter-leg coordinator. The simulated resembles real fly sustains even when subjected unexpected generalizing beyond its training data. However, found model’s perturbations deteriorates delay parameters exceed physiological range. These results suggest circuits operate close limit at which they can detect respond perturbations. More broadly, show modular, be used constraints on animal behavior.

Язык: Английский

---

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

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Июль 16, 2024

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

Язык: Английский

---

Discovering and exploiting active sensing motifs for estimation with empirical observability

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Ноя. 6, 2024

ABSTRACT Organisms and machines must use measured sensory cues to estimate unknown information about themselves or their environment. Cleverly applied sensor motion can be exploited enrich the quality of data improve estimation. However, a major barrier modeling such active sensing problems is lack empirical, yet rigorous, tools for quantifying relationship between movement estimation performance. Here, we introduce “BOUNDS: Bounding Observability Uncertain Nonlinear Dynamic Systems”. BOUNDS discover patterns that increase reduce uncertainty in either real simulated data. Crucially, it suitable high dimensional partially observable nonlinear systems with noise. We demonstrate through case study on how flying insects wind properties, showing specific motifs Additionally, present framework refine sporadic estimates from sensing. When combined an artificial neural network, show gained via Drosophila flight trajectories precise direction Collectively, our work will help decode organisms inform design algorithms machines.

Язык: Английский

---