A computational model for angular velocity integration in a locust heading circuit DOI Creative Commons
Kathrin Pabst, Evripidis Gkanias, Barbara Webb

et al.

PLoS Computational Biology, Journal Year: 2024, Volume and Issue: 20(12), P. e1012155 - e1012155

Published: Dec. 20, 2024

Accurate navigation often requires the maintenance of a robust internal estimate heading relative to external surroundings. We present model for angular velocity integration in desert locust circuit, applying concepts from early theoretical work on circuits mammals novel biological context insects. In contrast similar models proposed fruit fly, this circuit uses single 360° direction representation and is updated by neuromodulatory inputs. Our computational was implemented using steady-state firing rate neurons with dynamical synapses. The connectivity constrained data, remaining degrees freedom were optimised machine learning approach yield physiologically plausible neuron activities. demonstrate that noise. signal can be effectively used as input an existing insect goal-directed steering adapted outbound locomotion steady resembles migration. study supports possibility computations orientation may differently neural hardware fly locust.

Language: Английский

Advances in neural information detection sensors for spatial cognition research: a review DOI Creative Commons
Mingchuan Wang,

Shiya Lv,

Yu Wang

et al.

Sensors and Actuators Reports, Journal Year: 2024, Volume and Issue: unknown, P. 100274 - 100274

Published: Dec. 1, 2024

Language: Английский

Citations

0
A computational model for angular velocity integration in a locust heading circuit DOI Creative Commons
Kathrin Pabst, Evripidis Gkanias, Barbara Webb

et al.

PLoS Computational Biology, Journal Year: 2024, Volume and Issue: 20(12), P. e1012155 - e1012155

Published: Dec. 20, 2024

Accurate navigation often requires the maintenance of a robust internal estimate heading relative to external surroundings. We present model for angular velocity integration in desert locust circuit, applying concepts from early theoretical work on circuits mammals novel biological context insects. In contrast similar models proposed fruit fly, this circuit uses single 360° direction representation and is updated by neuromodulatory inputs. Our computational was implemented using steady-state firing rate neurons with dynamical synapses. The connectivity constrained data, remaining degrees freedom were optimised machine learning approach yield physiologically plausible neuron activities. demonstrate that noise. signal can be effectively used as input an existing insect goal-directed steering adapted outbound locomotion steady resembles migration. study supports possibility computations orientation may differently neural hardware fly locust.

Language: Английский

Citations

0