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Advances in Birds' Neural Mechanisms
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Advances in Birds' Neural Mechanisms

A Special Issue of Animals (ISSN 2076-2615) belonging to the section "Birds".

Deadline for manuscript submissions: 30 April 2027 | Viewed by 2417

Editors

Prof. Dr. Zhigang Shang

E-Mail Website
Guest Editor
School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China
Interests: neural networks
Dr. Mengmeng Li

E-Mail Website
Guest Editor Assistant
School of Electrical and Information Engineering, Zhengzhou University, Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, Zhengzhou 450001, China
Interests: brain-computer interface; neural decoding and regulation; machine learning
Dr. Lifang Yang

E-Mail Website
Guest Editor Assistant
School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China
Interests: bird; nerve

Special Issue Information

Dear Colleagues,

This Special Issue focuses on "Advances in Birds' Neural Mechanisms." Avian species have long fascinated scientists and enthusiasts alike with their outstanding cognitive capacities. These range from intricate problem-solving skills, enabling them to navigate complex environments and obtain food, as well as to dynamic social behaviors that facilitate group living and cooperation.

The neural substrates that underlie these remarkable abilities are a treasure trove of knowledge. They offer a unique window into the intricate mechanics of cognition and the broader evolutionary trajectories of intelligence across different species. Electrophysiological techniques, which capture the electrical activities within the bird brain, have emerged as powerful tools, allowing us to observe how neural circuits operate during various cognitive processes.

This Special Issue aims to further decode the complex interplay between avian neural mechanisms and their manifest behaviors. It seeks submissions on neural mechanisms of learning, spatial navigation, sensory processing, decision making, working memory, social cognition, and emotion regulation. Through this comprehensive exploration, we hope to significantly advance the field of avian cognitive neuroscience.

Prof. Dr. Zhigang Shang
Guest Editor

Dr. Mengmeng Li
Dr. Lifang Yang
Guest Editor Assistants

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Animals is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • avian neural mechanisms
  • electrophysiological techniques
  • neuronal activity
  • avian intelligence
  • spatial navigation
  • cognition and decision-making
  • sensory processing
  • working memory

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Published Papers (3 papers)

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Research

22 pages, 4385 KB  
Article
Dynamic Hippocampal–Striatal Information Flow Accompanies Behavioral Strategy Transitions During Sequential Learning in Pigeons: A Preliminary Study
by Lifang Yang, Ying Ma, Zhihui Li and Mengmeng Li
Animals 2026, 16(17), 2755; https://doi.org/10.3390/ani16172755 - 2 Sep 2026
Viewed by 351
Abstract
Sequential decision-making requires animals to flexibly balance model-based (MB) and model-free (MF) strategies to adapt to changing environments. The hippocampus (Hp) and striatum (ST) are two important components of the broader neural networks supporting these processes; however, how their dynamic interactions reorganize during [...] Read more.
Sequential decision-making requires animals to flexibly balance model-based (MB) and model-free (MF) strategies to adapt to changing environments. The hippocampus (Hp) and striatum (ST) are two important components of the broader neural networks supporting these processes; however, how their dynamic interactions reorganize during learning-dependent strategy transitions remains poorly understood. Here, we trained pigeons on a two-step sequential decision-making task while simultaneously recording local field potentials (LFPs) from the Hp and ST. A dynamic reinforcement learning framework combined with a sliding-window approach was used to characterize temporal changes in behavioral strategies, and phase transfer entropy (PTE) was applied to estimate directed information flow between the Hp and ST across theta, beta, and broad gamma (30–80 Hz) frequency bands. Behavioral modeling revealed a gradual transition from early MB-like, task-structure-sensitive control toward later MF-like value-guided behavior as learning progressed. PTE analysis demonstrated a consistent Hp-to-ST directional bias across all analyzed frequency bands during task acquisition. Notably, gamma-band Hp-to-ST information flow exhibited a consistent decline over training, whereas theta- and beta-band interactions showed less consistent changes across individuals. Additional analyses showed that relative MB model evidence and gamma-band Hp-to-ST information flow covaried across learning, but this association was no longer significant after controlling for learning progression, indicating parallel rather than independently coupled changes. These preliminary findings indicate that hippocampal–striatal communication undergoes frequency-specific reorganization during sequential learning. The reduction in gamma-band Hp-to-ST information flow accompanies, rather than independently predicts, the behavioral strategy transition, suggesting learning-related modulation of interregional coordination as task demands change. Full article
(This article belongs to the Special Issue Advances in Birds' Neural Mechanisms)
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16 pages, 7017 KB  
Article
Hippocampal Local Field Potentials Encode Continuous Flight Speed in Homing Pigeons via Complementary Gamma and Theta Signatures
by Long Yang, Xin Guo, Aimin Tao and Zhihui Li
Animals 2026, 16(16), 2569; https://doi.org/10.3390/ani16162569 - 18 Aug 2026
Viewed by 478
Abstract
Although the role of the mammalian hippocampus in representing locomotor speed has been widely investigated, how the avian hippocampus represents continuous flight speed under free-flight conditions in the outdoor environment remains unclear. In this study, we used homing pigeons as a model system [...] Read more.
Although the role of the mammalian hippocampus in representing locomotor speed has been widely investigated, how the avian hippocampus represents continuous flight speed under free-flight conditions in the outdoor environment remains unclear. In this study, we used homing pigeons as a model system and synchronously recorded hippocampal formation (HF) local field potentials (LFPs), global positioning system (GPS) trajectories, and inertial measurement unit (IMU) data during natural homing flights. We aimed to determine whether and how the avian HF encodes flight speed. Flight-speed-related neural features were extracted from both frequency-domain and time-domain signals, including the 50–70 Hz power spectral density (PSD) ratio and theta-demodulated amplitude (DAmp). We then constructed models for discrete flight-speed state decoding and continuous flight-speed prediction. The results showed that the 50–70 Hz PSD ratio in the HF was significantly negatively correlated with flight speed, whereas DAmp was significantly positively correlated with flight speed. Both features exhibited consistent speed-related trends across different spatial release sites. Support vector machine (SVM)-based classification showed that PSD, DAmp, and their combined features could effectively decode four flight-speed states, including non-flight, low-speed, medium-speed, and high-speed states, with the combined features achieving the best performance. Further Gaussian process regression (GPR) analysis demonstrated that the combined features predicted continuous flight speed more accurately than either single feature. These findings provide evidence that the avian hippocampal formation encodes continuous flight speed during natural navigation through the complementary integration of frequency-domain and time-domain features, extending the known role of the avian hippocampal formation from static spatial mapping to dynamic self-motion representation. Full article
(This article belongs to the Special Issue Advances in Birds' Neural Mechanisms)
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18 pages, 2086 KB  
Article
Stage-Associated Reorganization of Epidural ECoG Functional Networks During Pigeon Homing Flight
by Fuli Jin, Yue Qin, Youtang Gao, Yanna Ping, Xiaomi Qi, Dongyun Wang and Xinyu Liu
Animals 2026, 16(13), 2025; https://doi.org/10.3390/ani16132025 - 2 Jul 2026
Viewed by 388
Abstract
Pigeon homing provides an important model for studying navigation after displacement, yet how large-scale brain activity is organized across different phases of homing flight remains unclear. In this study, we recorded 16-channel epidural electrocorticographic signals from freely flying pigeons during outdoor homing flights [...] Read more.
Pigeon homing provides an important model for studying navigation after displacement, yet how large-scale brain activity is organized across different phases of homing flight remains unclear. In this study, we recorded 16-channel epidural electrocorticographic signals from freely flying pigeons during outdoor homing flights initiated approximately 6 km from the home loft. GPS trajectories were used to divide the homing process into waiting, hovering, fuzzy positioning, precise positioning, and home stages. Correlation-based inter-channel functional networks were constructed across alpha, beta, gamma, and high-gamma frequency bands, and their topological properties were quantified using the clustering coefficient and global efficiency. The results showed that ECoG functional network topology varied across homing stages. Network measures were generally higher during the precise positioning stage near the home loft and lower during the fuzzy positioning stage. Gamma-band networks showed a relatively stronger tendency toward the precise positioning stage, whereas alpha-band networks showed a relatively stronger tendency toward the hovering stage. Together, these findings suggest that natural pigeon homing flight is accompanied by stage-associated reorganization of epidural ECoG functional networks. Full article
(This article belongs to the Special Issue Advances in Birds' Neural Mechanisms)
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