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Stöckl AL, Foster JJ. Night skies through animals' eyes-Quantifying night-time visual scenes and light pollution as viewed by animals. Front Cell Neurosci 2022; 16:984282. [PMID: 36274987 PMCID: PMC9582234 DOI: 10.3389/fncel.2022.984282] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 09/09/2022] [Indexed: 11/13/2022] Open
Abstract
A large proportion of animal species enjoy the benefits of being active at night, and have evolved the corresponding optical and neural adaptations to cope with the challenges of low light intensities. However, over the past century electric lighting has introduced direct and indirect light pollution into the full range of terrestrial habitats, changing nocturnal animals' visual worlds dramatically. To understand how these changes affect nocturnal behavior, we here propose an animal-centered analysis method based on environmental imaging. This approach incorporates the sensitivity and acuity limits of individual species, arriving at predictions of photon catch relative to noise thresholds, contrast distributions, and the orientation cues nocturnal species can extract from visual scenes. This analysis relies on just a limited number of visual system parameters known for each species. By accounting for light-adaptation in our analysis, we are able to make more realistic predictions of the information animals can extract from nocturnal visual scenes under different levels of light pollution. With this analysis method, we aim to provide context for the interpretation of behavioral findings, and to allow researchers to generate specific hypotheses for the behavior of nocturnal animals in observed light-polluted scenes.
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Affiliation(s)
- Anna Lisa Stöckl
- Department of Biology, University of Konstanz, Konstanz, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
- Zukunftskolleg, Universität Konstanz, Konstanz, Germany
| | - James Jonathan Foster
- Department of Biology, University of Konstanz, Konstanz, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
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2
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Huang K, Yang Q, Han Y, Zhang Y, Wang Z, Wang L, Wei P. An Easily Compatible Eye-tracking System for Freely-moving Small Animals. Neurosci Bull 2022; 38:661-676. [PMID: 35325370 PMCID: PMC9206064 DOI: 10.1007/s12264-022-00834-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 12/03/2021] [Indexed: 12/13/2022] Open
Abstract
Measuring eye movement is a fundamental approach in cognitive science as it provides a variety of insightful parameters that reflect brain states such as visual attention and emotions. Combining eye-tracking with multimodal neural recordings or manipulation techniques is beneficial for understanding the neural substrates of cognitive function. Many commercially-available and custom-built systems have been widely applied to awake, head-fixed small animals. However, the existing eye-tracking systems used in freely-moving animals are still limited in terms of their compatibility with other devices and of the algorithm used to detect eye movements. Here, we report a novel system that integrates a general-purpose, easily compatible eye-tracking hardware with a robust eye feature-detection algorithm. With ultra-light hardware and a detachable design, the system allows for more implants to be added to the animal's exposed head and has a precise synchronization module to coordinate with other neural implants. Moreover, we systematically compared the performance of existing commonly-used pupil-detection approaches, and demonstrated that the proposed adaptive pupil feature-detection algorithm allows the analysis of more complex and dynamic eye-tracking data in free-moving animals. Synchronized eye-tracking and electroencephalogram recordings, as well as algorithm validation under five noise conditions, suggested that our system is flexibly adaptable and can be combined with a wide range of neural manipulation and recording technologies.
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Affiliation(s)
- Kang Huang
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Qin Yang
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Yaning Han
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yulin Zhang
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Zhiyi Wang
- Harbin Institute of Technology Shenzhen, Shenzhen, 518055, China
| | - Liping Wang
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Pengfei Wei
- Shenzhen Key Lab of Neuropsychiatric Modulation and Collaborative Innovation Center for Brain Science, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Center for Excellence in Brain Science and Intelligence Technology, Brain Cognition and Brain Disease Institute, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
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3
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Lankford CK, Umino Y, Poria D, Kefalov V, Solessio E, Baker SA. Cone-Driven Retinal Responses Are Shaped by Rod But Not Cone HCN1. J Neurosci 2022; 42:4231-4249. [PMID: 35437278 PMCID: PMC9145265 DOI: 10.1523/jneurosci.2271-21.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 04/01/2022] [Accepted: 04/07/2022] [Indexed: 11/21/2022] Open
Abstract
Signal integration of converging neural circuits is poorly understood. One example is in the retina where the integration of rod and cone signaling is responsible for the large dynamic range of vision. The relative contribution of rods versus cones is dictated by a complex function involving background light intensity and stimulus temporal frequency. One understudied mechanism involved in coordinating rod and cone signaling onto the shared retinal circuit is the hyperpolarization activated current (Ih) mediated by hyperpolarization-activated cyclic nucleotide-gated 1 (HCN1) channels expressed in rods and cones. Ih opposes membrane hyperpolarization driven by activation of the phototransduction cascade and modulates the strength and kinetics of the photoreceptor voltage response. We examined conditional knock-out (KO) of HCN1 from mouse rods using electroretinography (ERG). In the absence of HCN1, rod responses are prolonged in dim light which altered the response to slow modulation of light intensity both at the level of retinal signaling and behavior. Under brighter intensities, cone-driven signaling was suppressed. To our surprise, conditional KO of HCN1 from mouse cones had no effect on cone-mediated signaling. We propose that Ih is dispensable in cones because of the high level of temporal control of cone phototransduction. Thus, HCN1 is required for cone-driven retinal signaling only indirectly by modulating the voltage response of rods to limit their output.SIGNIFICANCE STATEMENT Hyperpolarization gated hyperpolarization-activated cyclic nucleotide-gated 1 (HCN1) channels carry a feedback current that helps to reset light-activated photoreceptors. Using conditional HCN1 knock-out (KO) mice we show that ablating HCN1 from rods allows rods to signal in bright light when they are normally shut down. Instead of enhancing vision this results in suppressing cone signaling. Conversely, ablating HCN1 from cones was of no consequence. This work provides novel insights into the integration of rod and cone signaling in the retina and challenges our assumptions about the role of HCN1 in cones.
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Affiliation(s)
- Colten K Lankford
- Department of Biochemistry and Molecular Biology, University of Iowa, Iowa City, Iowa 52242
| | - Yumiko Umino
- Center for Vision Research, Department of Ophthalmology and Visual Sciences, State University of New York Upstate Medical University, Syracuse, New York 13210
| | - Deepak Poria
- Department of Ophthalmology, Gavin Herbert Eye Institute, University of California, Irvine, California 92697
| | - Vladimir Kefalov
- Department of Ophthalmology, Gavin Herbert Eye Institute, University of California, Irvine, California 92697
- Department of Physiology and Biophysics, University of California, Irvine, California 92697
| | - Eduardo Solessio
- Center for Vision Research, Department of Ophthalmology and Visual Sciences, State University of New York Upstate Medical University, Syracuse, New York 13210
| | - Sheila A Baker
- Department of Biochemistry and Molecular Biology, University of Iowa, Iowa City, Iowa 52242
- Department of Ophthalmology and Visual Sciences and Institute for Vision Research, University of Iowa, Iowa City, Iowa 52242
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Eckley SS, Villano JS, Kuo NS, Wong KY. Acepromazine and Chlorpromazine as Pharmaceutical-grade Alternatives to Chlorprothixene for Pupillary Light Reflex Imaging in Mice. JOURNAL OF THE AMERICAN ASSOCIATION FOR LABORATORY ANIMAL SCIENCE 2020; 59:197-203. [PMID: 31915106 DOI: 10.30802/aalas-jaalas-19-000094] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Studies of visual responses in isoflurane-anesthetized mice often use the sedative chlorprothixene to decrease the amount of isoflurane used because excessive isoflurane could adversely affect light-evoked responses. However, data are not available to justify the use of this nonpharmaceutical-grade chemical. The current study tested whether pharmaceutical-grade sedatives would be appropriate alternatives for imaging pupillary light reflexes. Male 15-wk-old mice were injected intraperitoneally with 1 mg/kg chlorprothixene, 5 mg/kg acepromazine, 10 mg/kg chlorpromazine, or saline. After anesthetic induction, anesthesia maintenance used 0.5% and 1% isoflurane for sedative- and saline-injected mice, respectively. A photostimulus (16.0 log photons cm-2 s-1; 470 nm) was presented to the right eye for 20 min, during which the left eye was imaged for consensual pupillary constriction and involuntary pupil drift. Time to immobilization, loss of righting reflex, physiologic parameters, gain of righting reflex, and degree of recovery were assessed also. The sedative groups were statistically indistinguishable for all measures. By contrast, pupillary drift occurred far more often in saline-treated mice than in the sedative groups. Furthermore, saline-treated mice took longer to reach maximal pupil constriction than all sedative groups and had lower heart rates compared with chlorpromazine- and chlorprothixene-sedated mice. Full recovery (as defined by purposeful movement, response to tactile stimuli, and full alertness) was not regularly achieved in any sedative group. In conclusion, at the doses tested, acepromazine and chlorpromazine are suitable pharmaceutical-grade alternatives to chlorprothixene for pupil imaging and conceivably other in vivo photoresponse measurements; however, given the lack of full recovery, lower dosages should be investigated further for use in survival procedures.
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Affiliation(s)
- Samantha S Eckley
- Unit for Laboratory Animal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Jason S Villano
- Unit for Laboratory Animal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Nora S Kuo
- Unit for Laboratory Animal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Kwoon Y Wong
- Department of Ophthalmology and Visual Sciences, and Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, Michigan;,
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Rod Photoreceptors Signal Fast Changes in Daylight Levels Using a Cx36-Independent Retinal Pathway in Mouse. J Neurosci 2019; 40:796-810. [PMID: 31776212 DOI: 10.1523/jneurosci.0455-19.2019] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Revised: 11/11/2019] [Accepted: 11/17/2019] [Indexed: 11/21/2022] Open
Abstract
Temporal contrast detected by rod photoreceptors is channeled into multiple retinal rod pathways that ultimately connect to cone photoreceptor pathways via Cx36 gap junctions or via chemical synapses. However, we do not yet understand how the different rod pathways contribute to the perception of temporal contrast (changes in luminance with time) at mesopic light levels, where both rods and cones actively respond to light. Here, we use a forced-choice, operant behavior assay to investigate rod-driven, temporal contrast sensitivity (TCS) in mice of either sex. Transgenic mice with desensitized cones (GNAT2 cpfl3 line) were used to identify rod contributions to TCS in mesopic lights. We found that at low mesopic lights (400 photons/s/μm2 at the retina), control and GNAT2 cpfl3 mice had similar TCS. Surprisingly, at upper mesopic lights (8000 photons/s/μm2), GNAT2 cpfl3 mice exhibited a relative reduction in TCS to low (<12 Hz) while maintaining normal TCS to high (12-36 Hz) temporal frequencies. The rod-driven responses to high temporal frequencies developed gradually over time (>30 min). Furthermore, the TCS of GNAT2 cpfl3 and GNAT2 cpfl3 ::Cx36-/- mice matched closely, indicating that transmission of high-frequency signals (1) does not require the rod-cone Cx36 gap junctions as has been proposed in the past; and (2) a Cx36-independent rod pathway(s) (e.g., direct rod to OFF cone bipolar cell synapses and/or glycinergic synapses from AII amacrine cells to OFF ganglion cells) is sufficient for fast, mesopic rod-driven vision. These findings extend our understanding of the link between visual circuits and perception in mouse.SIGNIFICANCE STATEMENT The contributions of specific retinal pathways to visual perception are not well understood. We found that the temporal processing properties of rod-driven vision in mice change significantly with light level. In dim lights, rods relay relatively slow temporal variations. However, in daylight conditions, rod pathways exhibit high sensitivity to fast but not to slow temporal variations, whereas cone-driven responses supplement the loss in rod-driven sensitivity to slow temporal variations. Our findings highlight the dynamic interplay of rod- and cone-driven vision as light levels rise from night to daytime levels. Furthermore, the fast, rod-driven signals do not require the rod-to-cone Cx36 gap junctions as proposed in the past, but rather, can be relayed by alternative Cx36-independent rod pathways.
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Rod Photoresponse Kinetics Limit Temporal Contrast Sensitivity in Mesopic Vision. J Neurosci 2019; 39:3041-3056. [PMID: 30737308 DOI: 10.1523/jneurosci.1404-18.2019] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2018] [Revised: 01/29/2019] [Accepted: 01/30/2019] [Indexed: 11/21/2022] Open
Abstract
The mammalian visual system operates over an extended range of ambient light levels by switching between rod and cone photoreceptors. Rod-driven vision is sluggish, highly sensitive, and operates in dim or scotopic lights, whereas cone-driven vision is brisk, less sensitive, and operates in bright or photopic lights. At intermediate or mesopic lights, vision transitions seamlessly from rod-driven to cone-driven, despite the profound differences in rod and cone response dynamics. The neural mechanisms underlying such a smooth handoff are not understood. Using an operant behavior assay, electrophysiological recordings, and mathematical modeling we examined the neural underpinnings of the mesopic visual transition in mice of either sex. We found that rods, but not cones, drive visual sensitivity to temporal light variations over much of the mesopic range. Surprisingly, speeding up rod photoresponse recovery kinetics in transgenic mice improved visual sensitivity to slow temporal variations, in the range where perceptual sensitivity is governed by Weber's law of sensation. In contrast, physiological processes acting downstream from phototransduction limit sensitivity to high frequencies and temporal resolution. We traced the paradoxical control of visual temporal sensitivity to rod photoresponses themselves. A scenario emerges where perceptual sensitivity is limited by: (1) the kinetics of neural processes acting downstream from phototransduction in scotopic lights, (2) rod response kinetics in mesopic lights, and (3) cone response kinetics as light levels rise into the photopic range.SIGNIFICANCE STATEMENT Our ability to detect flickering lights is constrained by the dynamics of the slowest step in the visual pathway. Cone photoresponse kinetics limit visual temporal sensitivity in bright (photopic) lights, whereas mechanisms in the inner retina limit sensitivity in dim (scotopic) lights. The neural mechanisms underlying the transition between scotopic and photopic vision in mesopic lights, when both rods are cones are active, are unknown. This study provides a missing link in this mechanism by establishing that rod photoresponse kinetics limit temporal sensitivity during the mesopic transition. Surprisingly, this range is where Weber's Law of Sensation governs temporal contrast sensitivity in mouse. Our results will help guide future studies of complex and dynamic interactions between rod-cone signals in the mesopic retina.
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Visual Temporal Contrast Sensitivity in the Behaving Mouse Shares Fundamental Properties with Human Psychophysics. eNeuro 2018; 5:eN-NWR-0181-18. [PMID: 30225342 PMCID: PMC6140104 DOI: 10.1523/eneuro.0181-18.2018] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Revised: 07/17/2018] [Accepted: 07/23/2018] [Indexed: 01/09/2023] Open
Abstract
The mammalian visual system has a remarkable capacity to detect differences in contrast across time, which is known as temporal contrast sensitivity (TCS). Details of the underlying neural mechanisms are rapidly emerging as a result of a series of elegant electrophysiological studies performed largely with the mouse as an experimental model. However, rigorous psychophysical methods are necessary to pair the electrophysiology with temporal visual behavior in mouse. The optomotor response is frequently used as a proxy for retinal temporal processing in rodents. However, subcortical reflexive pathways drive the optomotor response rather than cortical decision-making areas. To address this problem, we have developed an operant behavior assay that measures TCS in behaving mice. Mice were trained to perform a forced-choice visual task and were tested daily on their ability to distinguish flickering from nonflickering overhead lights. Correct responses (Hit and Correct Rejections) were rewarded. Contrast, temporal frequency, and mean illumination of the flicker were the independent variables. We validated and applied the theory of signal detection to estimate the discriminability factor (d´), a measure of performance that is independent of response bias and motivation. The empirical contrast threshold was defined as the contrast necessary to elicit d´ = 1 and TCS as the inverse of the contrast threshold. With this approach, we established in the mouse a model of human vision that shares fundamental properties of human temporal psychophysics such as Weber adaptation in response to low temporal frequency flicker and illumination-dependent increases in critical flicker frequency as predicted by the Ferry–Porter law.
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Han Z, Zhang X, Zhu J, Chen Y, Li CT. High-Throughput Automatic Training System for Odor-Based Learned Behaviors in Head-Fixed Mice. Front Neural Circuits 2018; 12:15. [PMID: 29487506 PMCID: PMC5816819 DOI: 10.3389/fncir.2018.00015] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2017] [Accepted: 01/30/2018] [Indexed: 11/17/2022] Open
Abstract
Understanding neuronal mechanisms of learned behaviors requires efficient behavioral assays. We designed a high-throughput automatic training system (HATS) for olfactory behaviors in head-fixed mice. The hardware and software were constructed to enable automatic training with minimal human intervention. The integrated system was composed of customized 3D-printing supporting components, an odor-delivery unit with fast response, Arduino based hardware-controlling and data-acquisition unit. Furthermore, the customized software was designed to enable automatic training in all training phases, including lick-teaching, shaping and learning. Using HATS, we trained mice to perform delayed non-match to sample (DNMS), delayed paired association (DPA), Go/No-go (GNG), and GNG reversal tasks. These tasks probed cognitive functions including sensory discrimination, working memory, decision making and cognitive flexibility. Mice reached stable levels of performance within several days in the tasks. HATS enabled an experimenter to train eight mice simultaneously, therefore greatly enhanced the experimental efficiency. Combined with causal perturbation and activity recording techniques, HATS can greatly facilitate our understanding of the neural-circuitry mechanisms underlying learned behaviors.
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Affiliation(s)
- Zhe Han
- State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.,School of Future Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Xiaoxing Zhang
- State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Jia Zhu
- State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.,School of Future Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Yulei Chen
- State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Chengyu T Li
- State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
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