A method for single-neuron chronic recording from the retina in awake mice

Hong, Guosong; Fu, Tian-Ming; Qiao, Mu; Viveros, Robert D.; Yang, Xiao; Zhou, Tao; Lee, Jung Min; Park, Hong Gyu; Sanes, Joshua R.; Lieber, Charles M.

doi:10.1126/science.aas9160

Cited by 149 publications

(144 citation statements)

References 43 publications

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“…~60% of RGCs died between 3 and 7dpc, with ~74% dead by 14dpc ( Figure 4E). In contrast, less than 10% of cells were lost over two weeks of recordings from uninjured retinas (Hong et al, 2018), indicating that the loss reflects ONC-related death rather than recording instability. Moreover, the survival dynamics mirror those determined histologically (Figure 3I), suggesting that neurons are not silent for substantial periods prior to their death.…”

Section: Physiological Characteristics Of Resilient and Susceptible Rgcsmentioning

confidence: 91%

“…However, visual responses are currently unknown for most molecularly defined types. Therefore, we monitored physiological characteristics of individual injured RGCs over time, using our recently developed method for in vivo recording (Hong et al, 2018). Briefly, a flexible electro-recording mesh carrying 32 electrodes is injected intravitreally, where it coats the inner retina without disturbing normal eye function; spike sorting protocols identify up to 4 cells per electrode, and provide wave-form signatures that allow longitudinal tracking of the same cell over multiple recording sessions (Figures 4A,B).…”

Section: Physiological Characteristics Of Resilient and Susceptible Rgcsmentioning

confidence: 99%

“…Implantation of mesh electrodes. Fabrication and non-coaxial implantation of the mesh on the retina surface have been reported by (Hong et al, 2018) except that the mesh electronic probe produced for our experiments carried 32 independently addressable recording electrodes rather than 16 electrodes in the previous report. The mesh was loaded into a sterile borosilicate capillary needle Inner diameter: 200µm, outer diameter: 330µm; Produstrial LLC, Fredon, NJ).…”

Section: In Vivo Electrophysiologymentioning

confidence: 99%

“…The external portion of the mesh has all input/output (I/O) pads, which were unfolded onto a 32channel flexible flat cable (FFC, #0150200339, Molex, Lisle, IL) for individually addressable I/O connection (Fu et al, 2016;Hong et al, 2018;Hong et al, 2015). After I/O connection, the bonding region of mesh on the FFC was carefully covered with dental cement to the skull with METABOND®.…”

Section: In Vivo Electrophysiologymentioning

confidence: 99%

“…Mice were placed in a Tailveiner restrainer (Braintree Scientific LLC., Braintree, MA) with the head-plate secured to reduce mechanical noise during recording and fix the visual field of the recorded eye during visual stimulation. The FFC was connected to the signal amplifier and digitizer (Intan Technologies, Los Angeles, CA) and RGC activities were recorded while visual stimuli were presented to the mouse on a computer screen (20.5"×12.5"), placed a distance of 20cm from both eyes of the mouse, covering an azimuth angle range of ±52°, similar to previously reported protocols (Hong et al, 2018). Recordings were made from the following visual stimuli:…”

Section: In Vivo Electrophysiologymentioning

confidence: 99%

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Single-cell profiles of retinal neurons differing in resilience to injury reveal neuroprotective genes

Tran¹,

Shekhar

Whitney³

et al. 2019

Preprint

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Neuronal types in the central nervous system differ dramatically in their resilience to injury or insults. Here we studied the selective resilience of mouse retinal ganglion cells (RGCs) following optic nerve crush (ONC), which severs their axons and leads to death of ~80% of RGCs within 2 weeks. To identify expression programs associated with differential resilience, we first used single-cell RNA-seq (scRNA-seq) to generate a comprehensive molecular atlas of 46 RGC types in adult retina. We then tracked their survival after ONC, characterized transcriptomic, physiological, and morphological changes that preceded degeneration, and identified genes selectively expressed by each type. Finally, using loss-and gain-of-function assays in vivo, we showed that manipulating some of these genes improved neuronal survival and axon regeneration following ONC. This study provides a systematic framework for parsing type-specific responses to injury, and demonstrates that differential gene expression can be used to reveal molecular targets for intervention.

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Section: Physiological Characteristics Of Resilient and Susceptible Rgcsmentioning

confidence: 91%

Section: Physiological Characteristics Of Resilient and Susceptible Rgcsmentioning

confidence: 99%

Section: In Vivo Electrophysiologymentioning

confidence: 99%

Section: In Vivo Electrophysiologymentioning

confidence: 99%

Section: In Vivo Electrophysiologymentioning

confidence: 99%

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Single-cell profiles of retinal neurons differing in resilience to injury reveal neuroprotective genes

Tran¹,

Shekhar

Whitney³

et al. 2019

Preprint

Self Cite

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Engineering Materials for Neurotechnology

Ghezzi

2023

Adv Eng Mater

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A crucial issue for a neural interface is the chronic foreign body reaction (FBR) upon implantation. [1][2][3] Avoiding the FBR, or at least reducing its severity, is necessary to preserve the long-term functioning of neural interfaces. [4][5][6] Yet, this is still an open research question. The FBR is traditionally described as a passive barrier encapsulating the device, altering the neural interface, and impairing implant-to-cell communication. [2,7,8] Besides acting as a passive insulating barrier, soluble factors released during the inflammatory and fibrotic process can accelerate device degradation and electrode corrosion. [9] The FBR is inevitable whenever any material becomes in contact with body fluids. [10] In contrast, materials engineering and advanced fabrication processes can minimize its severity, for example, by improving the mechanical compliance of the implant, decreasing the device size, and reducing implantation and chronic trauma. [3] One of the most common limitations of neural interfaces is the mechanical mismatch between the stiff neural implant and the soft neural tissue. This mismatch intensifies the neural damage and FBR caused by insertion, compression, and motion. [11] The neural tissue is curved, soft, dynamic, and subject to deformations caused, for example, by blood pulsation, respiratory pressure, and natural body movements. [11,12] By contrast, most neural interfaces are static and struggle to conform to neural tissue in static and dynamic conditions. A large body of research in neural interfaces addresses this issue using flexible, conformable, or stretchable neural interfaces (Figure 1).Polyimide (PI), parylene-C, and SU-8 are widely used materials in flexible neural interfaces. [13][14][15][16][17][18][19][20][21][22] The advantages of these materials are their biochemical and thermal stability, and their compatibility with clean-room microfabrication processes. [23][24][25] However, they exhibit high Young's modulus (GPa range) and limited elastic deformation (<3%). [26] Ultra-thin neural interfaces made of these materials still reach low bending stiffness if sufficiently thin (<15 μm) despite the high Young's modulus. [27] They can conform to a cylindrical body such as a nerve or a smooth brain surface (Figure 1a), thus reducing the FBR severity. [23] Moreover, ultra-thin neural interfaces with a small cross-sectional area also can minimize tissue damage during penetration (Figure 1b). [22,24,28] Conformability to cylindrical or smooth surfaces is sufficient in rodents, but more is needed for large and complex surfaces with gyri, like in primates, where spherical conformability is required. Because of the limited elastic deformation, conformability to convoluted surfaces is difficult to achieve with these materials. Compliance with neural macro-and micro-movements is also reduced. [26] Elastomers exhibit a lower Young's modulus of at least three orders of magnitude (MPa range) and a much broader elastic regime under strain (>20%). Bending stiffness is influenced by both thick...

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Engineering Implantable Bioelectronics for Electrophysiological Monitoring in Preclinical Animal Models

Lee,

Kim,

Chung

et al. 2024

Adv Eng Mater

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Implantable bioelectronics capable of electrophysiological monitoring intimately interfacing with biological tissue have provided massive information for profound understanding of biological systems. However, their invasive nature induces a potential risk of acute tissue damage, limiting accurate and chronic monitoring of electrophysiological signals. To address this issue, advanced studies have developed effective strategies to engineer the soft, flexible device using preclinical animal models. In addition, the optional but innovative approaches to improve the device’s function have been also explored. Here, we summarize these strategies satisfying essential and supplemental requirements for engineering implantable bioelectronics. Three types of implantable devices, classified by their structural designs, are introduced to describe the approaches using suitable strategies for their specific purpose. We conclude with the further advancement of engineering implantable bioelectronics to address the remaining challenges. Such advancements have the potential to contribute to enhanced functionality, encouraging a more delicate understanding of the physiology of biological systems and further broadening the applicability of implantable bioelectronics in the field of biomedical technology.This article is protected by copyright. All rights reserved.

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A method for single-neuron chronic recording from the retina in awake mice

Cited by 149 publications

References 43 publications

Single-cell profiles of retinal neurons differing in resilience to injury reveal neuroprotective genes

Single-cell profiles of retinal neurons differing in resilience to injury reveal neuroprotective genes

Engineering Materials for Neurotechnology

Engineering Implantable Bioelectronics for Electrophysiological Monitoring in Preclinical Animal Models

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