Dynamic temporal neural patterns based on multichannel LFPs Identify different brain states during anesthesia in pigeons: comparison of three anesthetics.

Anesthetic-induced brain activity study is crucial in avian cognitive-, consciousness-, and sleep-related research. However, the neurobiological mechanisms underlying the generation of brain rhythms and specific connectivity of birds during anesthesia are poorly understood. Although different kinds of anesthetics can be used to induce an anesthesia state, a comparison study of these drugs focusing on the neural pattern evolution during anesthesia is lacking.

Decoding Typical Flight States Based on Neural Signals from the Midbrain Motor Nuclei of Pigeons.

Background: Exploring the neural encoding mechanism and decoding of motion state switching during flight can advance our knowledge of avian behavior control and contribute to the development of avian robots. However, limited acquisition equipment and neural signal quality have posed challenges, thus we understand little about the neural mechanisms of avian flight.

Methods: We used chronically implanted micro-electrode arrays to record the local field potentials (LFPs) in the formation reticularis medialis mesencephali (FRM) of pigeons during various motion states in their natural outdoor flight.

Progress of Micro-Stimulation Techniques to Alter Pigeons' Motor Behavior: A Review from the Perspectives of the Neural Basis and Neuro-Devices.

Pigeons have natural advantages in robotics research, including a wide range of activities, low energy consumption, good concealment performance, strong long-distance weight bearing and continuous flight ability, excellent navigation, and spatial cognitive ability, etc. They are typical model animals in the field of animal robot research and have important application value. A hot interdisciplinary research topic and the core content of pigeon robot research, altering pigeon motor behavior using brain stimulation involves multiple disciplines including animal ethology, neuroscience, electronic information technology and artificial intelligence technology, etc.

Dynamics Learning Rate Bias in Pigeons: Insights from Reinforcement Learning and Neural Correlates.

Research in reinforcement learning indicates that animals respond differently to positive and negative reward prediction errors, which can be calculated by assuming learning rate bias. Many studies have shown that humans and other animals have learning rate bias during learning, but it is unclear whether and how the bias changes throughout the entire learning process. Here, we recorded the behavior data and the local field potentials (LFPs) in the striatum of five pigeons performing a probabilistic learning task.

Phase-Amplitude Coupling between Theta Rhythm and High-Frequency Oscillations in the Hippocampus of Pigeons during Navigation.

Navigation is a complex task in which the hippocampus (Hp), which plays an important role, may be involved in interactions between different frequency bands. However, little is known whether this cross-frequency interaction exists in the Hp of birds during navigation. Therefore, we examined the electrophysiological characteristics of hippocampal cross-frequency interactions of domestic pigeons () during navigation.

The Hippocampus in Pigeons Contributes to the Model-Based Valuation and the Relationship between Temporal Context States.

Model-based decision-making guides organism behavior by the representation of the relationships between different states. Previous studies have shown that the mammalian hippocampus (Hp) plays a key role in learning the structure of relationships among experiences. However, the hippocampal neural mechanisms of birds for model-based learning have rarely been reported.

Application of deep reinforcement learning for spike sorting under multi-class imbalance.

Spike sorting is the basis for analyzing spike firing patterns encoded in high-dimensional information spaces. With the fact that high-density microelectrode arrays record multiple neurons simultaneously, the data collected often suffers from two problems: a few overlapping spikes and different neuronal firing rates, which both belong to the multi-class imbalance problem. Since deep reinforcement learning (DRL) assign targeted attention to categories through reward functions, we propose ImbSorter to implement spike sorting under multi-class imbalance.

Disarrangement and reorganization of the hippocampal functional connectivity during the spatial path adjustment of pigeons.

Background: The hippocampus plays an important role to support path planning and adjustment in goal-directed spatial navigation. While we still only have limited knowledge about how do the hippocampal neural activities, especially the functional connectivity patterns, change during the spatial path adjustment. In this study, we measured the behavioural indicators and local field potentials of the pigeon (Columba livia, male and female) during a goal-directed navigational task with the detour paradigm, exploring the changing patterns of the hippocampal functional network connectivity of the bird during the spatial path learning and adjustment.

Goal given moment modulates the time period of gamma oscillations in nidopallium caudolaterale during the goal-directed behavior of pigeon.

The cognitive processes of goal-directed navigation are believed to be organized around and serve the identification and selection of goals. Differences in LFP signals in avian nidopallium caudolaterale (NCL) under different goal location/distance information in the goal-directed behavior have been studied. However, for goals that are multifarious constructs that include various information, the modulation of goal time information on the LFP of NCL during goal-directed behavior remains unclear.

Research of control method for pneumatic control of pneumatic microchips.

A novel composite control method for actuated chamber air pressure of pneumatic microfluidic chip via a three-way electromagnetic microvalve is presented in this paper. The purpose of the control methods is to improve air pressure controlling precision for pneumatic control. By using the Bang-Bang (on-off) controller for pneumatic control, the step-response time, air pressure steady-state accuracy, and air pressure fluctuations are performed with different maximum thresholds and minimum thresholds.

Elevated Gamma Connectivity in Nidopallium Caudolaterale of Pigeons during Spatial Path Adjustment.

Previous studies showed that spatial navigation depends on a local network including multiple brain regions with strong interactions. However, it is still not fully understood whether and how the neural patterns in avian nidopallium caudolaterale (NCL), which is suggested to play a key role in navigation as a higher cognitive structure, are modulated by the behaviors during spatial navigation, especially involved path adjustment needs. Hence, we examined neural activity in the NCL of pigeons and explored the local field potentials' (LFPs) spectral and functional connectivity patterns in a goal-directed spatial cognitive task with the detour paradigm.

Many heads are better than one: A multiscale neural information feature fusion framework for spatial route selections decoding from multichannel neural recordings of pigeons.

The neural information at different scales exhibits spatial representations and the corresponding features are believed to be conducive for neural encoding. However, existing neural decoding studies on multiscale feature fusion have rarely been investigated. In this study, a multiscale neural information feature fusion framework is presented and we integrate these features to decode spatial routes from multichannel recordings.

Refined Multiscale Entropy Analysis of Wrist Pulse for Gender Difference in Traditional Chinese Medicine among Young Individuals.

Pulse signal analysis plays an important role in promoting the objectification of traditional Chinese medicine (TCM). Like electrocardiogram (ECG) signals, wrist pulse signals are mainly caused by cardiac activities and are valuable in analyzing cardiac diseases. A large number of studies have reported ECG signals can distinguish gender characteristics of normal healthy subjects using entropy complexity measures, consistently showing more complexity in females than males.

Spatial learning correlates with decreased hippocampal activity in the goal-directed behavior of pigeons.

Studies have suggested that the hippocampus (Hp) plays an important role in spatial learning and avian Hp is thought to have similar functions with mammals. However, the dynamic neural pattern of hippocampal activity is still unclear in the continuous spatial learning processes of birds. In this study, we recorded the behavioral data and local field potential (LFP) activity from Hp of pigeons performing goal-directed behavior.

Enhanced Hippocampus-Nidopallium Caudolaterale Connectivity during Route Formation in Goal-Directed Spatial Learning of Pigeons.

Goal-directed spatial learning is crucial for the survival of animals, in which the formation of the route from the current location to the goal is one of the central problems. A distributed brain network comprising the hippocampus and prefrontal cortex has been shown to support such capacity, yet it is not fully understood how the most similar brain regions in birds, the hippocampus (Hp) and nidopallium caudolaterale (NCL), cooperate during route formation in goal-directed spatial learning. Hence, we examined neural activity in the Hp-NCL network of pigeons and explored the connectivity dynamics during route formation in a goal-directed spatial task.

Network Pharmacology for Analyzing the Key Targets and Potential Mechanism of Wogonin in Gliomas.

To analyze the key targets and potential mechanisms underlying the volatile components of Georgi acting on gliomas through network pharmacology combined with biological experiments. We have extracted the volatile components of by gas chromatography-mass spectrometry (GC-MS) and determined the active components related to the onset and development of gliomas by combining the results with the data from the Traditional Chinese Medicine Systems Pharmacology database. We screened the same targets for the extracted active components and gliomas through network pharmacology and then constructed a protein-protein interaction network.

Decoding route selection of pigeon during goal-directed behavior: A joint spike-LFP study.

How to reach the goal is one of the core problems that animals must solve to complete goal-directed behavior. Studies have proved the important role of hippocampus (Hp) in spatial navigation and shown that hippocampal neural activities can represent the current location and goal location. However, for the different routes linking these two locations, the neural representation mechanism of the route selection in Hp is not clear.

The Role of Hp-NCL Network in Goal-Directed Routing Information Encoding of Bird: A Review.

Goal-directed navigation is a crucial behavior for the survival of animals, especially for the birds having extraordinary spatial navigation ability. In the studies of the neural mechanism of the goal-directed behavior, especially involving the information encoding mechanism of the route, the hippocampus (Hp) and nidopallium caudalle (NCL) of the avian brain are the famous regions that play important roles. Therefore, they have been widely concerned and a series of studies surrounding them have increased our understandings of the navigation mechanism of birds in recent years.

Functional connectivity changes in the intra- and inter-brain during the construction of the multi-brain network of pigeons.

Multi-brain network, also known as social cooperative network, is formed by multiple animal or human brains, whose changes of functional connectivity in the intra- and inter-brain during construction are unclear at present. To investigate the intra- and inter-brain functional connectivity of pigeons while performing a social cooperation task, we designed an inter-brain synchronization task to train three pigeons to synchronize their neural activities using cross-brain neurofeedback. Then the neural signals of three pigeons were simultaneously recorded by using a hyperscanning approach, and inter-brain synchronization was calculated using the phase-locked value (PLV) online.

Ependymoma and pilocytic astrocytoma: Differentiation using radiomics approach based on machine learning.

Mandatory accurate and specific diagnosis demands have brought about increased challenges for radiologists in pediatric posterior fossa tumor prediction and prognosis. With the development of high-performance computing and machine learning technologies, radiomics provides increasing opportunities for clinical decision-making. Several studies have applied radiomics as a decision support tool in intracranial tumors differentiation.

[A spike denoising method combined principal component analysis with wavelet and ensemble empirical mode decomposition].

Spike recorded by multi-channel microelectrode array is very weak and susceptible to interference, whose noisy characteristic affects the accuracy of spike detection. Aiming at the independent white noise, correlation noise and colored noise in the process of spike detection, combining principal component analysis (PCA), wavelet analysis and adaptive time-frequency analysis, a new denoising method (PCWE) that combines PCA-wavelet (PCAW) and ensemble empirical mode decomposition is proposed. Firstly, the principal component was extracted and removed as correlation noise using PCA.

Automatic bad channel detection in implantable brain-computer interfaces using multimodal features based on local field potentials and spike signals.

"Bad channels" in implantable multi-channel recordings bring troubles into the precise quantitative description and analysis of neural signals, especially in the current "big data" era. In this paper, we combine multimodal features based on local field potentials (LFPs) and spike signals to detect bad channels automatically using machine learning. On the basis of 2632 pairs of LFPs and spike recordings acquired from five pigeons, 12 multimodal features are used to quantify each channel's temporal, frequency, phase and firing-rate properties.

Hippocampus-nidopallium caudolaterale interactions exist in the goal-directed behavior of pigeon.

Avian hippocampus (Hp) and nidopallium caudolaterale (NCL) are believed to play key roles in goal-directed behavior. However, it is still unclear whether there are interactions between the two brain regions in the goal-directed behavior of pigeons. To investigate the interactions between the Hp and the NCL in the goal-directed behavior, we recorded local field potential (LFP) signals from the two regions simultaneously when the pigeons performed a goal-directed decision-making task.

Sequential neural information processing in nidopallium caudolaterale of pigeons during the acquisition process of operant conditioning.

The avian nidopallium caudolaterale, a key region of information integration and processing, is considered to be playing an important role in operant conditioning acquisition and extinction. To reveal sequential neural information processing in the process, neural signals of different experimental periods (induction, acquisition, and extinction) from the nidopallium caudolaterale of pigeons were acquired and the energy of the specific frequency band was analyzed from the light stimulation input to the pecking action output. We found that during the induction period, the pigeons establish a relationship between the visual cue and decision behavior.