Danqian Liu

ORCID: 0000-0003-2604-2113
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About
Contact & Profiles
Research Areas
  • Sleep and Wakefulness Research
  • Neuroscience and Neuropharmacology Research
  • Circadian rhythm and melatonin
  • Neural dynamics and brain function
  • EEG and Brain-Computer Interfaces
  • Neuroscience of respiration and sleep
  • Obstructive Sleep Apnea Research
  • Photoreceptor and optogenetics research
  • Sleep and related disorders
  • Mitochondrial Function and Pathology
  • Neuroinflammation and Neurodegeneration Mechanisms
  • Cell Image Analysis Techniques
  • Diverse Music Education Insights
  • Electrochemical Analysis and Applications
  • Retinal Imaging and Analysis
  • Functional Brain Connectivity Studies
  • Trace Elements in Health
  • Video Surveillance and Tracking Methods
  • Epilepsy research and treatment
  • Music Education and Analysis
  • Advanced Memory and Neural Computing
  • Smart Agriculture and AI
  • Advanced Chemical Sensor Technologies
  • Memory and Neural Mechanisms

Center for Excellence in Brain Science and Intelligence Technology
2016-2024

Chinese Academy of Sciences
2016-2024

Shanghai Center for Brain Science and Brain-Inspired Technology
2023

University of California, Berkeley
2019-2022

Howard Hughes Medical Institute
2018-2022

Shanghai Institutes for Biological Sciences
2016-2018

Interneurons control brain arousal states The underlying circuit mechanisms coordinating and motor activity are poorly understood. Liu et al. found that glutamic acid decarboxylase 2 (GAD2)–expressing, but not parvalbumin-expressing, interneurons in a part of the known as substantia nigra promote sleep (see Perspective by Wisden Franks). Parvalbuminergic neurons fire at higher rates high activity, their activation increases movement termination consistent with function suppressing unwanted...

10.1126/science.aaz0956 article EN Science 2020-01-24

Studying the biology of sleep requires accurate assessment state experimental subjects, and manual analysis relevant data is a major bottleneck. Recently, deep learning applied to electroencephalogram electromyogram has shown great promise as scoring method, approaching limits inter-rater reliability. As with any machine algorithm, inputs classifier are typically standardized in order remove distributional shift caused by variability signal collection process. However, scientific data,...

10.1371/journal.pone.0224642 article EN cc-by PLoS ONE 2019-12-13

Sleep disturbances are strongly associated with cardiovascular diseases. Baroreflex, a basic regulation mechanism, is modulated by sleep-wake states. Here, we show that neurons at key stages of baroreflex pathways also promote sleep. Using activity-dependent genetic labeling, tagged in the nucleus solitary tract (NST) activated blood pressure elevation and confirmed their barosensitivity optrode recording calcium imaging. Chemogenetic or optogenetic activation these promoted non-REM sleep...

10.1016/j.neuron.2022.08.027 article EN cc-by Neuron 2022-09-27

Serial section electron microscopy (ssEM) can provide comprehensive 3D ultrastructural information of the brain with exceptional computational cost. Targeted reconstruction subcellular structures from ssEM datasets is less computationally demanding but still highly informative. We thus developed a region-CNN-based deep learning method to identify, segment, and reconstruct synapses mitochondria explore structural plasticity in auditory cortex mice subjected fear conditioning. Upon...

10.1016/j.celrep.2022.111151 article EN cc-by-nc-nd Cell Reports 2022-08-01

In the nervous system, neurons communicate through synapses. The size, morphology, and connectivity of these synapses are significant in determining functional properties neural network. Therefore, they have always been a major focus neuroscience research. Two-photon laser scanning microscopy allows visualization synaptic structures vivo, leading to many important findings. However, identification quantification structural imaging data currently rely heavily on manual annotation, method that...

10.1186/s13040-017-0161-5 article EN cc-by BioData Mining 2017-12-01

Abstract Studying the biology of sleep requires accurate assessment state experimental subjects, and manual analysis relevant data is a major bottleneck. Recently, deep learning applied to electroencephalogram electromyogram has shown great promise as scoring method, approaching limits inter-rater reliability. As with any machine algorithm, inputs classifier are typically standardized in order remove distributional shift caused by variability signal collection process. However, scientific...

10.1101/813345 preprint EN cc-by bioRxiv (Cold Spring Harbor Laboratory) 2019-10-21

Abstract From invertebrates to humans, a defining feature of sleep is behavioral immobility(Campbell and Tobler, 1984; Hendricks et al., 2000; Shaw 2000). In mammals, diminished electromyographic (EMG) activity major criterion for both rapid eye movement (REM) non-REM (NREM) sleep. However, the relationship between motor control at neuronal level remains poorly understood. Here we show that regions basal ganglia long known be essential suppression also play key role in generation....

10.1101/405324 preprint EN bioRxiv (Cold Spring Harbor Laboratory) 2018-09-02

Biologists often need to handle numerous video-based home-cage animal behavior analysis tasks that require massive workloads. Therefore, we develop an AI-based multi-species tracking and segmentation system, SiamBOMB, for real-time automatic behavioral analysis. In this a background-enhanced Siamese-based network with replaceable modular design ensures the flexibility generalizability of user-friendly interface makes it convenient use biologists. This AI system will effectively reduce burden on

10.24963/ijcai.2020/776 article EN 2020-07-01

10.1016/j.tins.2023.04.006 article EN Trends in Neurosciences 2023-05-10

Abstract Serial section electron microscopy (ssEM) can provide comprehensive 3D ultrastructural information of the brain with exceptional computational cost. Targeted reconstruction subcellular structures from ssEM datasets is less computationally demanding but still highly informative. We thus developed a Region-CNN-based deep learning method to identify, segment, and reconstruct synapses mitochondria explore structural plasticity in auditory cortex mice subjected fear conditioning. Upon...

10.1101/2021.08.05.455246 preprint EN cc-by-nc-nd bioRxiv (Cold Spring Harbor Laboratory) 2021-08-06

Serial section electron microscopy (ssEM) can provide comprehensive 3D ultrastructural information of the brain with exceptional computational cost. Targeted reconstruction subcellular structures from ssEM datasets is less computationally demanding but still highly informative. We thus developed a Region-CNN-based deep learning method to identify, segment, and reconstruct synapses mitochondria explore structural plasticity in auditory cortex mice subjected fear conditioning. Upon...

10.2139/ssrn.3952086 article EN SSRN Electronic Journal 2021-01-01
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