# Neural Correlates of Flight Acceleration in Pigeons: Gamma-Band Activity and Local Functional Network Dynamics in the AId Region

## TL;DR

This study shows that brain activity in a pigeon's AId region changes with flight acceleration, revealing how birds' brains control movement during flight.

## Contribution

The study provides the first evidence that gamma-band brain activity in pigeons encodes flight acceleration.

## Key findings

- Gamma-band activity in the AId region correlates with flight acceleration phases.
- Local functional network dynamics in the AId show a U-shaped relationship with flight acceleration.
- Machine learning models using LFP signals confirm gamma-band dynamics' role in flight control.

## Abstract

Flight acceleration is a key indicator of how motor behavior is dynamically regulated during aerial navigation. In this study, we conducted outdoor free-flight experiments in homing pigeons and analyzed brain activity from the dorsal intermediate arcopallium (AId), a region functionally similar to the mammalian motor cortex. The results showed that both the power spectral density (PSD) proportion and the local Functional Network of gamma-band brain networks varied with flight acceleration, suggesting that neural activity in the AId region encodes changes in flight states. These findings highlight how brain activity adapts to varying motor demands and provide new insights into the neural basis of flight control in birds.

Flight behavior in pigeons is governed by intricate neural mechanisms that regulate movement patterns and flight dynamics. Among various kinematic parameters, flight acceleration provides critical information for the brain to modulate movement intensity, speed, and direction. However, the neural representation mechanisms underlying flight acceleration remain insufficiently understood. To address this, we conducted outdoor free-flight experiments in homing pigeons, during which GPS data, flight posture, and eight-channel local field potentials (LFPs) were synchronously recorded. Our analysis revealed that gamma-band activity in the dorsal intermediate arcopallium (AId) region was more prominent during behaviorally demanding phases of flight. In parallel, local functional network analysis showed that the clustering coefficient of gamma-band activity in the AId followed a nonlinear, U-shaped relationship with flight acceleration—exhibiting the strongest and most widespread connectivity during deceleration, moderate connectivity during acceleration, and the weakest network coupling during steady flight. This pattern likely reflects the increased neural demands associated with flight phase transitions, where greater cognitive and sensorimotor integration is required. Furthermore, using LFP signals from five distinct frequency bands as input, machine learning models were developed to decode flight acceleration, further confirming the role of gamma-band dynamics in motor regulation during natural flight. This study provides the first evidence that gamma-band activity in the avian AId region encodes flight acceleration, offering new insights into the neural representation of motor states in natural flight and implications for bio-inspired flight control systems.