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Bennett C, Ouellette B, Ramirez TK, Cahoon A, Cabasco H, Browning Y, Lakunina A, Lynch GF, McBride EG, Belski H, Gillis R, Grasso C, Howard R, Johnson T, Loeffler H, Smith H, Sullivan D, Williford A, Caldejon S, Durand S, Gale S, Guthrie A, Ha V, Han W, Hardcastle B, Mochizuki C, Sridhar A, Suarez L, Swapp J, Wilkes J, Siegle JH, Farrell C, Groblewski PA, Olsen SR. SHIELD: Skull-shaped hemispheric implants enabling large-scale electrophysiology datasets in the mouse brain. Neuron 2024:S0896-6273(24)00450-1. [PMID: 38996587 DOI: 10.1016/j.neuron.2024.06.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Revised: 05/02/2024] [Accepted: 06/18/2024] [Indexed: 07/14/2024]
Abstract
To understand the neural basis of behavior, it is essential to measure spiking dynamics across many interacting brain regions. Although new technologies, such as Neuropixels probes, facilitate multi-regional recordings, significant surgical and procedural hurdles remain for these experiments to achieve their full potential. Here, we describe skull-shaped hemispheric implants enabling large-scale electrophysiology datasets (SHIELD). These 3D-printed skull-replacement implants feature customizable insertion holes, allowing dozens of cortical and subcortical structures to be recorded in a single mouse using repeated multi-probe insertions over many days. We demonstrate the procedure's high success rate, biocompatibility, lack of adverse effects on behavior, and compatibility with imaging and optogenetics. To showcase SHIELD's scientific utility, we use multi-probe recordings to reveal novel insights into how alpha rhythms organize spiking activity across visual and sensorimotor networks. Overall, this method enables powerful, large-scale electrophysiological experiments for the study of distributed neural computation.
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Affiliation(s)
- Corbett Bennett
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA.
| | - Ben Ouellette
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | | | | | - Hannah Cabasco
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Yoni Browning
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Anna Lakunina
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Galen F Lynch
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | | | - Hannah Belski
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Ryan Gillis
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Conor Grasso
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Robert Howard
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Tye Johnson
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Henry Loeffler
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Heston Smith
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | | | | | | | | | - Samuel Gale
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Alan Guthrie
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Vivian Ha
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Warren Han
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Ben Hardcastle
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | | | - Arjun Sridhar
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Lucas Suarez
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Jackie Swapp
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Joshua Wilkes
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | | | | | | | - Shawn R Olsen
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA.
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2
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Melin MD, Khanal A, Vasquez M, Ryan MB, Churchland AK, Couto J. Large scale, simultaneous, chronic neural recordings from multiple brain areas. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.22.572441. [PMID: 38187681 PMCID: PMC10769364 DOI: 10.1101/2023.12.22.572441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Understanding how brain activity is related to animal behavior requires measuring multi-area interactions on multiple timescales. However, methods to perform chronic, simultaneous recordings of neural activity from many brain areas are lacking. Here, we introduce a novel approach for independent chronic probe implantation that enables flexible, simultaneous interrogation of neural activity from many brain regions during head restrained or freely moving behavior. The approach, that we called indie (independent dovetail implants for electrophysiology), enables repeated retrieval and reimplantation of probes. The chronic implantation approach can be combined with other modalities such as skull clearing for cortex wide access and optogenetics with optic fibers. Using this approach, we implanted 6 probes chronically in one hemisphere of the mouse brain. The implant is lightweight, allows flexible targeting with different angles, and offers enhanced stability. Our approach broadens the applications of chronic recording while retaining its main advantages over acute recordings (superior stability, longitudinal monitoring of activity and freely moving interrogations) and provides an appealing venue to study processes not accessible by acute methods, such as the neural substrate of learning across multiple areas.
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Affiliation(s)
- Maxwell D Melin
- Department of Neurobiology, University of California Los Angeles
- UCLA-Caltech Medical Scientist Training Program
| | - Anup Khanal
- Department of Neurobiology, University of California Los Angeles
| | - Marvin Vasquez
- Department of Neurobiology, University of California Los Angeles
| | - Michael B Ryan
- Department of Neurobiology, University of California Los Angeles
| | | | - Joao Couto
- Department of Neurobiology, University of California Los Angeles
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3
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Liu Y(A, Nong Y, Feng J, Li G, Sajda P, Li Y, Wang Q. Phase synchrony between prefrontal noradrenergic and cholinergic signals indexes inhibitory control. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.17.594562. [PMID: 38798371 PMCID: PMC11118516 DOI: 10.1101/2024.05.17.594562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Inhibitory control is a critical executive function that allows animals to suppress their impulsive behavior in order to achieve certain goals or avoid punishment. We investigated norepinephrine (NE) and acetylcholine (ACh) dynamics and population neuronal activity in the prefrontal cortex during inhibitory control. Using fluorescent sensors to measure extracellular levels of NE and ACh, we simultaneously recorded the dynamics of prefrontal NE and ACh in mice performing an inhibitory control task. The prefrontal NE and ACh signals exhibited strong coherence at 0.4-0.8 Hz. Chemogenetic inhibition of locus coeruleus (LC) neurons that project to the basal forebrain region reduced inhibitory control performance to chance levels. However, this manipulation did not diminish the difference in NE/ACh signals between successful and failed trials; instead, it abolished the difference in NE-ACh phase synchrony between the successful and failed trials, indicating that NE-ACh phase synchrony is a task-relevant neuromodulatory feature. Chemogenetic inhibition of cholinergic neurons that project to the LC region did not impair the inhibitory control performance, nor did it abolish the difference in NE-ACh phase synchrony between successful or failed trials, further confirming the relevance of NE-ACh phase synchrony to inhibitory control. To understand the possible effect of NE-ACh synchrony on prefrontal population activity, we employed Neuropixels to record from the prefrontal cortex with and without inhibiting LC neurons that project to the basal forebrain during inhibitory control. The LC inhibition reduced the number of prefrontal neurons encoding inhibitory control. Demixed principal component analysis (dPCA) further revealed that population firing patterns representing inhibitory control were impaired by the LC inhibition. Disparities in NE-ACh phase synchrony relevant to inhibitory control occurred only in the prefrontal cortex, but not in the parietal cortex, somatosensory cortex, and the somatosensory thalamus. Taken together, these findings suggest that the LC modulates inhibitory control through its collective effect with cholinergic systems on population activity in the prefrontal cortex. Our results further revealed that NE-ACh phase synchrony is a critical neuromodulatory feature with important implications for cognitive control.
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Affiliation(s)
- Yuxiang (Andy) Liu
- Department of Biomedical Engineering Columbia University ET 351, 500 W. 120 Street, New York, NY 10027
| | - Yuhan Nong
- Department of Biomedical Engineering Columbia University ET 351, 500 W. 120 Street, New York, NY 10027
| | - Jiesi Feng
- State Key Laboratory of Membrane Biology, School of Life Sciences Peking University
- PKU-IDG/McGovern Institute for Brain Research, PR China
| | - Guochuan Li
- State Key Laboratory of Membrane Biology, School of Life Sciences Peking University
- PKU-IDG/McGovern Institute for Brain Research, PR China
| | - Paul Sajda
- Department of Biomedical Engineering Columbia University ET 351, 500 W. 120 Street, New York, NY 10027
| | - Yulong Li
- State Key Laboratory of Membrane Biology, School of Life Sciences Peking University
- PKU-IDG/McGovern Institute for Brain Research, PR China
| | - Qi Wang
- Department of Biomedical Engineering Columbia University ET 351, 500 W. 120 Street, New York, NY 10027
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Bimbard C, Takács F, Catarino JA, Fabre JMJ, Gupta S, Lenzi SC, Melin MD, O’Neill N, Orsolic I, Robacha M, Street JS, Teixeira J, Townsend S, van Beest EH, Zhang AM, Churchland AK, Duan CA, Harris KD, Kullmann DM, Lignani G, Mainen ZF, Margrie TW, Rochefort N, Wikenheiser AM, Carandini M, Coen P. An adaptable, reusable, and light implant for chronic Neuropixels probes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.03.551752. [PMID: 37577563 PMCID: PMC10418246 DOI: 10.1101/2023.08.03.551752] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Electrophysiology has proven invaluable to record neural activity, and the development of Neuropixels probes dramatically increased the number of recorded neurons. These probes are often implanted acutely, but acute recordings cannot be performed in freely moving animals and the recorded neurons cannot be tracked across days. To study key behaviors such as navigation, learning, and memory formation, the probes must be implanted chronically. An ideal chronic implant should (1) allow stable recordings of neurons for weeks; (2) allow reuse of the probes after explantation; (3) be light enough for use in mice. Here, we present the "Apollo Implant", an open-source and editable device that meets these criteria and accommodates up to two Neuropixels 1.0 or 2.0 probes. The implant comprises a "payload" module which is attached to the probe and is recoverable, and a "docking" module which is cemented to the skull. The design is adjustable, making it easy to change the distance between probes, the angle of insertion, and the depth of insertion. We tested the implant across eight labs in head-fixed mice, freely moving mice, and freely moving rats. The number of neurons recorded across days was stable, even after repeated implantations of the same probe. The Apollo implant provides an inexpensive, lightweight, and flexible solution for reusable chronic Neuropixels recordings.
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Affiliation(s)
- C. Bimbard
- UCL Institute of Ophthalmology, University College London, London, UK
| | - F. Takács
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK
| | - J. A. Catarino
- Champalimaud Research, Champalimaud Centre for the Unknown, Av. Brasilia, Lisbon, Portugal
| | - J. M. J. Fabre
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - S. Gupta
- Department of Psychology, University of California, Los Angeles, Los Angeles, California, USA
| | - S. C. Lenzi
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK
| | - M. D. Melin
- Department of Neurobiology, University of California Los Angeles, Los Angeles, California, USA
| | - N. O’Neill
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - I. Orsolic
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK
| | - M. Robacha
- UCL Institute of Ophthalmology, University College London, London, UK
| | - J. S. Street
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - J. Teixeira
- Champalimaud Research, Champalimaud Centre for the Unknown, Av. Brasilia, Lisbon, Portugal
| | - S. Townsend
- The FabLab, Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, UK
| | - E. H. van Beest
- UCL Institute of Ophthalmology, University College London, London, UK
| | - A. M. Zhang
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of Edinburgh, UK
| | - A. K. Churchland
- Department of Neurobiology, University of California Los Angeles, Los Angeles, California, USA
| | - C. A. Duan
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK
| | - K. D. Harris
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - D. M. Kullmann
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - G. Lignani
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Z. F. Mainen
- Champalimaud Research, Champalimaud Centre for the Unknown, Av. Brasilia, Lisbon, Portugal
| | - T. W. Margrie
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK
| | - N.L. Rochefort
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, University of Edinburgh, UK
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, UK
| | - A. M. Wikenheiser
- Department of Psychology, University of California, Los Angeles, Los Angeles, California, USA
| | - M. Carandini
- UCL Institute of Ophthalmology, University College London, London, UK
| | - P. Coen
- UCL Institute of Ophthalmology, University College London, London, UK
- Department of Cell and Developmental Biology, University College London, UK
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5
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Namima T, Kempkes E, Smith B, Smith L, Orsborn AL, Pasupathy A. Inserting a Neuropixels probe into awake monkey cortex: two probes, two methods. J Neurosci Methods 2024; 402:110016. [PMID: 37995854 PMCID: PMC10843751 DOI: 10.1016/j.jneumeth.2023.110016] [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: 06/27/2023] [Revised: 10/17/2023] [Accepted: 11/18/2023] [Indexed: 11/25/2023]
Abstract
BACKGROUND Neuropixels probes have revolutionized neurophysiological studies in the rodent, but inserting these probes through the much thicker primate dura remains a challenge. NEW METHODS Here we describe two methods we have developed for the insertion of two types of Neuropixels probes acutely into the awake macaque monkey cortex. For the fine rodent probe (Neuropixels 1.0, IMEC), which is unable to pierce native primate dura, we developed a dural-eyelet method to insert the probe repeatedly without breakage. For the thicker short NHP probe (Neuropixels NP1010), we developed an artificial dura system to insert the probe. RESULTS AND COMPARISON WITH EXISTING METHODS We have now conducted successful experiments in 3 animals across 7 recording chambers with the procedures described here and have achieved recordings with similar yields over several months in each case. CONCLUSION We hope that our hardware, surgical preparation, methods for insertion and methods for removal of broken probe parts are of value to primate physiologists everywhere.
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Affiliation(s)
- Tomoyuki Namima
- Department of Biological Structure and Washington National Primate Research Center, University of Washington, Seattle, WA 98195, USA; Graduate School of Frontier Biosciences, Osaka University, and Center for Information and Neural Networks, National Institute of Information and Communications Technology, Suita, Osaka 565-0871, Japan
| | - Erin Kempkes
- Department of Biological Structure and Washington National Primate Research Center, University of Washington, Seattle, WA 98195, USA
| | - Bob Smith
- Washington National Primate Research Center Instrumentation Services, University of Washington, Seattle, WA 98195, USA
| | - Lydia Smith
- Washington National Primate Research Center, University of Washington, Seattle, WA 98195, USA
| | - Amy L Orsborn
- Washington National Primate Research Center, University of Washington, Seattle, WA 98195, USA
| | - Anitha Pasupathy
- Department of Biological Structure and Washington National Primate Research Center, University of Washington, Seattle, WA 98195, USA; Washington National Primate Research Center, University of Washington, Seattle, WA 98195, USA.
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6
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Song Z, Alpers A, Warner K, Iacobucci F, Hoskins E, Disterhoft JF, Voss JL, Widge AS. Chronic, Reusable, Multiday Neuropixels Recordings during Free-Moving Operant Behavior. eNeuro 2024; 11:ENEURO.0245-23.2023. [PMID: 38253540 PMCID: PMC10849027 DOI: 10.1523/eneuro.0245-23.2023] [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: 06/28/2023] [Revised: 12/13/2023] [Accepted: 12/17/2023] [Indexed: 01/24/2024] Open
Abstract
Electrophysiological recording is a powerful technique to examine neuronal substrates underlying cognition and behavior. Neuropixels probes provide a unique capacity to capture neuronal activity across many brain areas with high spatiotemporal resolution. Neuropixels are also expensive and optimized for acute, head-fixed use, both of which limit the types of behaviors and manipulations that can be studied. Recent advances have addressed the cost issue by showing chronic implant, explant, and reuse of Neuropixels probes, but the methods were not optimized for use in free-moving behavior. There were specific needs for improvement in cabling/connection stability. Here, we extend that work to demonstrate chronic Neuropixels recording, explant, and reuse in a rat model during fully free-moving operant behavior. Similar to prior approaches, we house the probe and headstage within a 3D-printed housing that avoids direct fixation of the probe to the skull, enabling eventual explant. We demonstrate innovations to allow chronic headstage connection with protection against environmental factors and a more stable cabling setup to reduce the tension that can interrupt recording. We demonstrate this approach with rats performing two different behavioral tasks, in each case showing: (1) chronic single- or dual-probe recordings in free-moving rats in operant chambers and (2) reusability of Neuropixels 1.0 probes with continued good single-unit yield after retrieval and reimplant. We thus demonstrate the potential for Neuropixels recordings in a wider range of species and preparations.
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Affiliation(s)
- Zhimin Song
- Department of Psychiatry, University of Minnesota, Minneapolis, 55455 Minnesota
| | - Abigail Alpers
- Department of Psychiatry, University of Minnesota, Minneapolis, 55455 Minnesota
| | - Kasey Warner
- Department of Psychiatry, University of Minnesota, Minneapolis, 55455 Minnesota
| | - Francesca Iacobucci
- Department of Psychiatry, University of Minnesota, Minneapolis, 55455 Minnesota
| | - Eric Hoskins
- Department of Psychiatry, University of Minnesota, Minneapolis, 55455 Minnesota
| | - John F Disterhoft
- Department of Neuroscience, Northwestern University, Evanston, 60208 Illinois
| | - Joel L Voss
- Department of Neurology, University of Chicago, Chicago, 60637 Illinois
| | - Alik S Widge
- Department of Psychiatry, University of Minnesota, Minneapolis, 55455 Minnesota
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7
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Horváth C, Ulbert I, Fiáth R. Propagating population activity patterns during spontaneous slow waves in the thalamus of rodents. Neuroimage 2024; 285:120484. [PMID: 38061688 DOI: 10.1016/j.neuroimage.2023.120484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 11/08/2023] [Accepted: 12/04/2023] [Indexed: 01/13/2024] Open
Abstract
Slow waves (SWs) represent the most prominent electrophysiological events in the thalamocortical system under anesthesia and during deep sleep. Recent studies have revealed that SWs have complex spatiotemporal dynamics and propagate across neocortical regions. However, it is still unclear whether neuronal activity in the thalamus exhibits similar propagation properties during SWs. Here, we report propagating population activity in the thalamus of ketamine/xylazine-anesthetized rats and mice visualized by high-density silicon probe recordings. In both rodent species, propagation of spontaneous thalamic activity during up-states was most frequently observed in dorsal thalamic nuclei such as the higher order posterior (Po), lateral posterior (LP) or laterodorsal (LD) nuclei. The preferred direction of thalamic activity spreading was along the dorsoventral axis, with over half of the up-states exhibiting a gradual propagation in the ventral-to-dorsal direction. Furthermore, simultaneous neocortical and thalamic recordings collected under anesthesia demonstrated that there is a weak but noticeable interrelation between propagation patterns observed during cortical up-states and those displayed by thalamic population activity. In addition, using chronically implanted silicon probes, we detected propagating activity patterns in the thalamus of naturally sleeping rats during slow-wave sleep. However, in comparison to propagating up-states observed under anesthesia, these propagating patterns were characterized by a reduced rate of occurrence and a faster propagation speed. Our findings suggest that the propagation of spontaneous population activity is an intrinsic property of the thalamocortical network during synchronized brain states such as deep sleep or anesthesia. Additionally, our data implies that the neocortex may have partial control over the formation of propagation patterns within the dorsal thalamus under anesthesia.
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Affiliation(s)
- Csaba Horváth
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Eötvös Loránd Research Network, Budapest, Hungary; János Szentágothai Doctoral School of Neurosciences, Semmelweis University, Budapest, Hungary
| | - István Ulbert
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Eötvös Loránd Research Network, Budapest, Hungary; Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary.
| | - Richárd Fiáth
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Eötvös Loránd Research Network, Budapest, Hungary; Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
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8
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Coughlin B, Muñoz W, Kfir Y, Young MJ, Meszéna D, Jamali M, Caprara I, Hardstone R, Khanna A, Mustroph ML, Trautmann EM, Windolf C, Varol E, Soper DJ, Stavisky SD, Welkenhuysen M, Dutta B, Shenoy KV, Hochberg LR, Mark Richardson R, Williams ZM, Cash SS, Paulk AC. Modified Neuropixels probes for recording human neurophysiology in the operating room. Nat Protoc 2023; 18:2927-2953. [PMID: 37697108 DOI: 10.1038/s41596-023-00871-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 06/08/2023] [Indexed: 09/13/2023]
Abstract
Neuropixels are silicon-based electrophysiology-recording probes with high channel count and recording-site density. These probes offer a turnkey platform for measuring neural activity with single-cell resolution and at a scale that is beyond the capabilities of current clinically approved devices. Our team demonstrated the first-in-human use of these probes during resection surgery for epilepsy or tumors and deep brain stimulation electrode placement in patients with Parkinson's disease. Here, we provide a better understanding of the capabilities and challenges of using Neuropixels as a research tool to study human neurophysiology, with the hope that this information may inform future efforts toward regulatory approval of Neuropixels probes as research devices. In perioperative procedures, the major concerns are the initial sterility of the device, maintaining a sterile field during surgery, having multiple referencing and grounding schemes available to de-noise recordings (if necessary), protecting the silicon probe from accidental contact before insertion and obtaining high-quality action potential and local field potential recordings. The research team ensures that the device is fully operational while coordinating with the surgical team to remove sources of electrical noise that could otherwise substantially affect the signals recorded by the sensitive hardware. Prior preparation using the equipment and training in human clinical research and working in operating rooms maximize effective communication within and between the teams, ensuring high recording quality and minimizing the time added to the surgery. The perioperative procedure requires ~4 h, and the entire protocol requires multiple weeks.
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Affiliation(s)
- Brian Coughlin
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - William Muñoz
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Yoav Kfir
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Michael J Young
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Domokos Meszéna
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Mohsen Jamali
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Irene Caprara
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Richard Hardstone
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Arjun Khanna
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Martina L Mustroph
- Department of Neurosurgery, Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
| | - Eric M Trautmann
- Department of Neuroscience, Columbia University Medical Center, New York, NY, USA
- Zuckerman Institute, Columbia University, New York, NY, USA
- Grossman Center for the Statistics of Mind, Columbia University Medical Center, New York, NY, USA
| | - Charlie Windolf
- Department of Statistics, Zuckerman Institute, Columbia University, New York, NY, USA
| | - Erdem Varol
- Department of Statistics, Zuckerman Institute, Columbia University, New York, NY, USA
- Department of Computer Science and Engineering, Zuckerman Institute, Columbia University, New York, NY, USA
| | - Dan J Soper
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Sergey D Stavisky
- Department of Neurological Surgery, University of California Davis, Davis, CA, USA
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute and Bio-X Institute, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
| | | | | | - Krishna V Shenoy
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute and Bio-X Institute, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Neurobiology, Stanford University, Stanford, CA, USA
| | - Leigh R Hochberg
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- VA RR&D Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Providence VA Medical Center, Providence, RI, USA
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, USA
| | - R Mark Richardson
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Ziv M Williams
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA.
| | - Sydney S Cash
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Department of Neurology, Harvard Medical School, Boston, MA, USA.
| | - Angelique C Paulk
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Department of Neurology, Harvard Medical School, Boston, MA, USA.
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9
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Namima T, Kempkes E, Smith B, Pasupathy A. Inserting a Neuropixels probe into awake monkey cortex: two probes, two methods. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.26.546631. [PMID: 37425930 PMCID: PMC10326968 DOI: 10.1101/2023.06.26.546631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Neuropixels probes have revolutionized neurophysiological studies in the rodent, but inserting these probes through the much thicker primate dura remains a challenge. Here we describe two methods we have developed for the insertion of two types of Neuropixels probes acutely into the awake monkey cortex. For the fine rodent probe, which is unable to pierce native primate dura, we developed a dural-eyelet method to insert the probe repeatedly without breakage. For the thicker NHP probe, we developed an artificial dura system to insert the probe. We have now conducted successful experiments in 3 animals across 7 recording chambers with the procedures described here and have achieved stable recordings over several months in each case. Here we describe our hardware, surgical preparation, methods for insertion and methods for removal of broken probe parts. We hope that our methods are of value to primate physiologists everywhere.
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Affiliation(s)
- Tomoyuki Namima
- Department of Biological Structure and Washington National Primate Research Center, University of Washington, Seattle, WA 98195, USA
- Graduate School of Frontier Biosciences, Osaka University, and Center for Information and Neural Networks, National Institute of Information and Communications Technology, Suita, Osaka, 565-0871, Japan
| | - Erin Kempkes
- Department of Biological Structure and Washington National Primate Research Center, University of Washington, Seattle, WA 98195, USA
| | - Bob Smith
- Washington National Primate Research Center Instrumentation Services, University of Washington, Seattle, WA 98195, USA
| | - Anitha Pasupathy
- Department of Biological Structure and Washington National Primate Research Center, University of Washington, Seattle, WA 98195, USA
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10
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Purohit P, Dutta P, Roy PK. Empirically validated theoretical analysis of visual-spatial perception under change of nervous system arousal. Front Comput Neurosci 2023; 17:1136985. [PMID: 37251600 PMCID: PMC10213702 DOI: 10.3389/fncom.2023.1136985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 04/03/2023] [Indexed: 05/31/2023] Open
Abstract
Introduction Visual-spatial perception is a process for extracting the spatial relationship between objects in the environment. The changes in visual-spatial perception due to factors such as the activity of the sympathetic nervous system (hyperactivation) or parasympathetic nervous system (hypoactivation) can affect the internal representation of the external visual-spatial world. We formulated a quantitative model of the modulation of visual-perceptual space under action by hyperactivation or hypoactivation-inducing neuromodulating agents. We showed a Hill equation based relationship between neuromodulator agent concentration and alteration of visual-spatial perception utilizing the metric tensor to quantify the visual space. Methods We computed the dynamics of the psilocybin (hyperactivation-inducing agent) and chlorpromazine (hypoactivation-inducing agent) in brain tissue. Then, we validated our quantitative model by analyzing the findings of different independent behavioral studies where subjects were assessed for alterations in visual-spatial perception under the action of psilocybin and under chlorpromazine. To validate the neuronal correlates, we simulated the effect of the neuromodulating agent on the computational model of the grid-cell network, and also performed diffusion MRI-based tractography to find the neural tracts between the cortical areas involved: V2 and the entorhinal cortex. Results We applied our computational model to an experiment (where perceptual alterations were measured under psilocybin) and found that for n (Hill-coefficient) = 14.8 and k = 1.39, the theoretical prediction followed experimental observations very well (χ2 test robustly satisfied, p > 0.99). We predicted the outcome of another psilocybin-based experiment using these values (n = 14.8 and k = 1.39), whereby our prediction and experimental outcomes were well corroborated. Furthermore, we found that also under hypoactivation (chlorpromazine), the modulation of the visual-spatial perception follows our model. Moreover, we found neural tracts between the area V2 and entorhinal cortex, thus providing a possible brain network responsible for encoding visual-spatial perception. Thence, we simulated the altered grid-cell network activity, which was also found to follow the Hill equation. Conclusion We developed a computational model of visuospatial perceptual alterations under altered neural sympathetic/parasympathetic tone. We validated our model using analysis of behavioral studies, neuroimaging assessment, and neurocomputational evaluation. Our quantitative approach may be probed as a potential behavioral screening and monitoring methodology in neuropsychology to analyze perceptual misjudgment and mishaps by highly stressed workers.
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Affiliation(s)
- Pratik Purohit
- School of Biomedical Engineering, Indian Institute of Technology (BHU), Varanasi, India
| | - Prasun Dutta
- Department of Physics, Indian Institute of Technology (BHU), Varanasi, India
| | - Prasun K. Roy
- School of Biomedical Engineering, Indian Institute of Technology (BHU), Varanasi, India
- Department of Life Sciences, Shiv Nadar University (SNU), Greater Noida, India
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11
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Durand S, Heller GR, Ramirez TK, Luviano JA, Williford A, Sullivan DT, Cahoon AJ, Farrell C, Groblewski PA, Bennett C, Siegle JH, Olsen SR. Acute head-fixed recordings in awake mice with multiple Neuropixels probes. Nat Protoc 2023; 18:424-457. [PMID: 36477710 DOI: 10.1038/s41596-022-00768-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 08/09/2022] [Indexed: 12/12/2022]
Abstract
Multi-electrode arrays such as Neuropixels probes enable electrophysiological recordings from large populations of single neurons with high temporal resolution. By using such probes, the activity from functionally interacting, yet distinct, brain regions can be measured simultaneously by inserting multiple probes into the same subject. However, the use of multiple probes in small animals such as mice requires the removal of a sizable fraction of the skull, while also minimizing tissue damage and keeping the brain stable during the recordings. Here, we describe a step-by-step process designed to facilitate reliable recordings from up to six Neuropixels probes simultaneously in awake, head-fixed mice. The procedure involves four stages: the implantation of a headframe and a removable glass coverslip, the precise positioning of the Neuropixels probes at targeted points on the brain surface, the placement of a perforated plastic imaging window and the insertion of the probes into the brain of an awake mouse. The approach provides access to multiple brain regions and has been successfully applied across hundreds of mice. The procedure has been optimized for dense recordings from the mouse visual system, but it can be adapted for alternative recording configurations to target multiple probes in other brain areas. The protocol is suitable for users with experience in stereotaxic surgery in mice.
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Affiliation(s)
| | - Greggory R Heller
- Allen Institute, Seattle, WA, USA.,Department of Brain and Cognitive Sciences, Massachussetts Institute of Technology, Cambridge, MA, USA
| | - Tamina K Ramirez
- Allen Institute, Seattle, WA, USA.,Department of Neurobiology and Behavior, Columbia University, New York, NY, USA
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12
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Wang Y, LeDue JM, Murphy TH. Multiscale imaging informs translational mouse modeling of neurological disease. Neuron 2022; 110:3688-3710. [PMID: 36198319 DOI: 10.1016/j.neuron.2022.09.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 05/26/2022] [Accepted: 09/06/2022] [Indexed: 11/05/2022]
Abstract
Multiscale neurophysiology reveals that simple motor actions are associated with changes in neuronal firing in virtually every brain region studied. Accordingly, the assessment of focal pathology such as stroke or progressive neurodegenerative diseases must also extend widely across brain areas. To derive mechanistic information through imaging, multiple resolution scales and multimodal factors must be included, such as the structure and function of specific neurons and glial cells and the dynamics of specific neurotransmitters. Emerging multiscale methods in preclinical animal studies that span micro- to macroscale examinations fill this gap, allowing a circuit-based understanding of pathophysiological mechanisms. Combined with high-performance computation and open-source data repositories, these emerging multiscale and large field-of-view techniques include live functional ultrasound, multi- and single-photon wide-scale light microscopy, video-based miniscopes, and tissue-penetrating fiber photometry, as well as variants of post-mortem expansion microscopy. We present these technologies and outline use cases and data pipelines to uncover new knowledge within animal models of stroke, Alzheimer's disease, and movement disorders.
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Affiliation(s)
- Yundi Wang
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, 2255 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada; Djavad Mowafaghian Centre for Brain Health, University of British Columbia, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada
| | - Jeffrey M LeDue
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, 2255 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada; Djavad Mowafaghian Centre for Brain Health, University of British Columbia, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada
| | - Timothy H Murphy
- University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Detwiller Pavilion, 2255 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada; Djavad Mowafaghian Centre for Brain Health, University of British Columbia, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada.
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13
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Mazzucato L. Neural mechanisms underlying the temporal organization of naturalistic animal behavior. eLife 2022; 11:76577. [PMID: 35792884 PMCID: PMC9259028 DOI: 10.7554/elife.76577] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 06/07/2022] [Indexed: 12/17/2022] Open
Abstract
Naturalistic animal behavior exhibits a strikingly complex organization in the temporal domain, with variability arising from at least three sources: hierarchical, contextual, and stochastic. What neural mechanisms and computational principles underlie such intricate temporal features? In this review, we provide a critical assessment of the existing behavioral and neurophysiological evidence for these sources of temporal variability in naturalistic behavior. Recent research converges on an emergent mechanistic theory of temporal variability based on attractor neural networks and metastable dynamics, arising via coordinated interactions between mesoscopic neural circuits. We highlight the crucial role played by structural heterogeneities as well as noise from mesoscopic feedback loops in regulating flexible behavior. We assess the shortcomings and missing links in the current theoretical and experimental literature and propose new directions of investigation to fill these gaps.
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Affiliation(s)
- Luca Mazzucato
- Institute of Neuroscience, Departments of Biology, Mathematics and Physics, University of Oregon
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14
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Chung JE, Sellers KK, Leonard MK, Gwilliams L, Xu D, Dougherty ME, Kharazia V, Metzger SL, Welkenhuysen M, Dutta B, Chang EF. High-density single-unit human cortical recordings using the Neuropixels probe. Neuron 2022; 110:2409-2421.e3. [PMID: 35679860 DOI: 10.1016/j.neuron.2022.05.007] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 04/10/2022] [Accepted: 05/10/2022] [Indexed: 10/18/2022]
Abstract
The action potential is a fundamental unit of neural computation. Even though significant advances have been made in recording large numbers of individual neurons in animal models, translation of these methodologies to humans has been limited because of clinical constraints and electrode reliability. Here, we present a reliable method for intraoperative recording of dozens of neurons in humans using the Neuropixels probe, yielding up to ∼100 simultaneously recorded single units. Most single units were active within 1 min of reaching target depth. The motion of the electrode array had a strong inverse correlation with yield, identifying a major challenge and opportunity to further increase the probe utility. Cell pairs active close in time were spatially closer in most recordings, demonstrating the power to resolve complex cortical dynamics. Altogether, this approach provides access to population single-unit activity across the depth of human neocortex at scales previously only accessible in animal models.
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Affiliation(s)
- Jason E Chung
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Kristin K Sellers
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA; Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Matthew K Leonard
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA; Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Laura Gwilliams
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA; Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Duo Xu
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA; Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Maximilian E Dougherty
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA; Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Viktor Kharazia
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Sean L Metzger
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA; Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA; University of California Berkeley, University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA 94720, USA
| | | | | | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA; Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA 94158, USA.
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15
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Guardamagna M, Eichler R, Pedrosa R, Aarts AAA, Meyer AF, Battaglia F. The Hybrid Drive: a chronic implant device combining tetrode arrays with silicon probes for layer-resolved ensemble electrophysiology in freely moving mice. J Neural Eng 2022; 19. [PMID: 35421850 DOI: 10.1088/1741-2552/ac6771] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 04/10/2022] [Indexed: 10/18/2022]
Abstract
Objective. Understanding the function of brain cortices requires simultaneous investigation at multiple spatial and temporal scales and to link neural activity to an animal's behavior. A major challenge is to measure within- and across-layer information in actively behaving animals, in particular in mice that have become a major species in neuroscience due to an extensive genetic toolkit. Here we describe the Hybrid Drive, a new chronic implant for mice that combines tetrode arrays to record within-layer information with silicon probes to simultaneously measure across-layer information.Approach. The design of our device combines up to 14 tetrodes and 2 silicon probes, that can be arranged in custom arrays to generate unique areas-specific (and multi-area) layouts.Main Results. We show that large numbers of neurons and layer-resolved local field potentials can be recorded from the same brain region across weeks without loss in electrophysiological signal quality. The drive's lightweight structure (~3.5 g) leaves animal behavior largely unchanged, compared to other tetrode drives, during a variety of experimental paradigms. We demonstrate how the data collected with the Hybrid Drive allow state-of-the-art analysis in a series of experiments linking the spiking activity of CA1 pyramidal layer neurons to the oscillatory activity across hippocampal layers.Significance. Our new device fits a gap in the existing technology and increases the range and precision of questions that can be addressed about neural computations in freely behaving mice.
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Affiliation(s)
| | - Ronny Eichler
- Radboud University, Heyendaalseweg 135, Nijmegen, 6500 HC, NETHERLANDS
| | - Rafael Pedrosa
- Radboud University, Heyendaalseweg 135, Nijmegen, 6500 HC, NETHERLANDS
| | - Arno A A Aarts
- ATLAS Neuroengineering, Kapeldreef 75, Leuven, B-3000, BELGIUM
| | - Arne F Meyer
- Radboud University, Heyendaalseweg 135, Nijmegen, 6500 HC, NETHERLANDS
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Zhang Q, Turner KL, Gheres KW, Hossain MS, Drew PJ. Behavioral and physiological monitoring for awake neurovascular coupling experiments: a how-to guide. NEUROPHOTONICS 2022; 9:021905. [PMID: 35639834 PMCID: PMC8802326 DOI: 10.1117/1.nph.9.2.021905] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 12/28/2021] [Indexed: 06/15/2023]
Abstract
Significance: Functional brain imaging in awake animal models is a popular and powerful technique that allows the investigation of neurovascular coupling (NVC) under physiological conditions. However, ubiquitous facial and body motions (fidgeting) are prime drivers of spontaneous fluctuations in neural and hemodynamic signals. During periods without movement, animals can rapidly transition into sleep, and the hemodynamic signals tied to arousal state changes can be several times larger than sensory-evoked responses. Given the outsized influence of facial and body motions and arousal signals in neural and hemodynamic signals, it is imperative to detect and monitor these events in experiments with un-anesthetized animals. Aim: To cover the importance of monitoring behavioral state in imaging experiments using un-anesthetized rodents, and describe how to incorporate detailed behavioral and physiological measurements in imaging experiments. Approach: We review the effects of movements and sleep-related signals (heart rate, respiration rate, electromyography, intracranial pressure, whisking, and other body movements) on brain hemodynamics and electrophysiological signals, with a focus on head-fixed experimental setup. We summarize the measurement methods currently used in animal models for detection of those behaviors and arousal changes. We then provide a guide on how to incorporate this measurements with functional brain imaging and electrophysiology measurements. Results: We provide a how-to guide on monitoring and interpreting a variety of physiological signals and their applications to NVC experiments in awake behaving mice. Conclusion: This guide facilitates the application of neuroimaging in awake animal models and provides neuroscientists with a standard approach for monitoring behavior and other associated physiological parameters in head-fixed animals.
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Affiliation(s)
- Qingguang Zhang
- The Pennsylvania State University, Center for Neural Engineering, Department of Engineering Science and Mechanics, University Park, Pennsylvania, United States
| | - Kevin L. Turner
- The Pennsylvania State University, Department of Biomedical Engineering, University Park, Pennsylvania, United States
| | - Kyle W. Gheres
- The Pennsylvania State University, Graduate Program in Molecular Cellular and Integrative Biosciences, University Park, Pennsylvania, United States
| | - Md Shakhawat Hossain
- The Pennsylvania State University, Department of Biomedical Engineering, University Park, Pennsylvania, United States
| | - Patrick J. Drew
- The Pennsylvania State University, Center for Neural Engineering, Department of Engineering Science and Mechanics, University Park, Pennsylvania, United States
- The Pennsylvania State University, Department of Biomedical Engineering, University Park, Pennsylvania, United States
- The Pennsylvania State University, Department of Neurosurgery, University Park, Pennsylvania, United States
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17
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Sun C, Cao Y, Huang J, Huang K, Lu Y, Zhong C. Low-cost and easy-fabrication lightweight drivable electrode array for multiple-regions electrophysiological recording in free-moving mice. J Neural Eng 2022; 19. [PMID: 34996053 DOI: 10.1088/1741-2552/ac494e] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 01/07/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Extracellular electrophysiology has been widely applied to neural circuit dissections. However, long-term multiregional recording in free-moving mice remains a challenge. Low-cost and easy-fabrication of elaborate drivable electrodes is required for their prevalence. APPROACH A three-layer nested construct (OD ~1.80 mm, length ~10 mm, <0.1g) was recruited as a drivable component, which consisted of an ethylene-vinyl acetate copolymer (EVA) heat-shrinkable tube, non-closed loop ceramic bushing, and stainless ferrule with a bulge twining silver wire. The supporting and working components were equipped with drivable components to be assembled into a drivable microwire electrode array with a nested structure (drivable MEANS). Two drivable microwire electrode arrays were independently implanted for chronic recording in different brain areas at respective angles. An optic fiber was easily loaded into the drivable MEANS to achieve optogenetic modulation and electrophysiological recording simultaneously. MAIN RESULTS The drivable MEANS had lightweight (~ 0.37 g), small (~ 15 mm ×15 mm × 4 mm), and low cost (≤ $64.62). Two drivable MEANS were simultaneously implanted in mice, and high-quality electrophysiological recordings could be applied ≥ 5 months after implantation in freely behaving animals. Electrophysiological recordings and analysis of the lateral septum (LS) and lateral hypothalamus (LH) in food-seeking behavior demonstrated that our drivable MEANS can be used to dissect the function of neural circuits. An optical fiber-integrated drivable MEANS (~ 0.47 g) was used to stimulate and record LS neurons, which suggested that changes in working components can achieve more functions than electrophysiological recordings, such as optical stimulation, drug release, and calcium imaging. SIGNIFICANCE Drivable MEANS is an easily fabricated, lightweight drivable microwire electrode array for multiple-region electrophysiological recording in free-moving mice. Our design is likely to be a valuable platform for both current and prospective users, as well as for developers of multifunctional electrodes for free-moving mice.
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Affiliation(s)
- Chongyang Sun
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences, 1068 Xueyuan Boulevard, University Town of Shenzhen, Xili Nanshan, Shenzhen, Guangdong, 518055, CHINA
| | - Yi Cao
- University of Science and Technology of China, No.96, JinZhai Road Baohe District, Hefei, Anhui, 230026, CHINA
| | - Jianyu Huang
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences, 1068 Xueyuan Boulevard, University Town of Shenzhen, Xili Nanshan, Shenzhen, Guangdong, 518055, CHINA
| | - Kang Huang
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences, 1068 Xueyuan Boulevard, University Town of Shenzhen, Xili Nanshan, Shenzhen, Guangdong, 518055, CHINA
| | - Yi Lu
- Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences, 1068 Xueyuan Boulevard, University Town of Shenzhen, Xili Nanshan, Shenzhen, Guangdong, 518055, CHINA
| | - Cheng Zhong
- Chinese Academy of Sciences, 1068 Xueyuan Boulevard, University Town of Shenzhen, Xili Nanshan, Beijing, 100864, CHINA
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Autry AE, O'Connell LA. The Parental Dilemma: How Evolution of Diverse Strategies for Infant Care Informs Social Behavior Circuits. Front Neural Circuits 2021; 15:734474. [PMID: 34867211 PMCID: PMC8636452 DOI: 10.3389/fncir.2021.734474] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 10/27/2021] [Indexed: 11/14/2022] Open
Affiliation(s)
- Anita E Autry
- Dominick P. Purpura Department of Neuroscience, Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY, United States
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Strohl JJ, Gallagher JT, Gómez PN, Glynn JM, Huerta PT. Framework for automated sorting of neural spikes from Neuralynx-acquired tetrode recordings in freely-moving mice. Bioelectron Med 2021; 7:17. [PMID: 34809706 PMCID: PMC8609830 DOI: 10.1186/s42234-021-00079-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 10/21/2021] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Extracellular recording represents a crucial electrophysiological technique in neuroscience for studying the activity of single neurons and neuronal populations. The electrodes capture voltage traces that, with the help of analytical tools, reveal action potentials ('spikes') as well as local field potentials. The process of spike sorting is used for the extraction of action potentials generated by individual neurons. Until recently, spike sorting was performed with manual techniques, which are laborious and unreliable due to inherent operator bias. As neuroscientists add multiple electrodes to their probes, the high-density devices can record hundreds to thousands of neurons simultaneously, making the manual spike sorting process increasingly difficult. The advent of automated spike sorting software has offered a compelling solution to this issue and, in this study, we present a simple-to-execute framework for running an automated spike sorter. METHODS Tetrode recordings of freely-moving mice are obtained from the CA1 region of the hippocampus as they navigate a linear track. Tetrode recordings are also acquired from the prelimbic cortex, a region of the medial prefrontal cortex, while the mice are tested in a T maze. All animals are implanted with custom-designed, 3D-printed microdrives that carry 16 electrodes, which are bundled in a 4-tetrode geometry. RESULTS We provide an overview of a framework for analyzing single-unit data in which we have concatenated the acquisition system (Cheetah, Neuralynx) with analytical software (MATLAB) and an automated spike sorting pipeline (MountainSort). We give precise instructions on how to implement the different steps of the framework, as well as explanations of our design logic. We validate this framework by comparing manually-sorted spikes against automatically-sorted spikes, using neural recordings of the hippocampus and prelimbic cortex in freely-moving mice. CONCLUSIONS We have efficiently integrated the MountainSort spike sorter with Neuralynx-acquired neural recordings. Our framework is easy to implement and provides a high-throughput solution. We predict that within the broad field of bioelectronic medicine, those teams that incorporate high-density neural recording devices to their armamentarium might find our framework quite valuable as they expand their analytical footprint.
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Affiliation(s)
- Joshua J. Strohl
- Laboratory of Immune & Neural Networks, Institute of Molecular Medicine, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York, USA, 350 Community Drive, Manhasset, NY 11030 USA
- Department of Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, 500 Hofstra Blvd, Hempstead, NY 11549 USA
| | - Joseph T. Gallagher
- Laboratory of Immune & Neural Networks, Institute of Molecular Medicine, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York, USA, 350 Community Drive, Manhasset, NY 11030 USA
| | - Pedro N. Gómez
- Laboratory of Immune & Neural Networks, Institute of Molecular Medicine, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York, USA, 350 Community Drive, Manhasset, NY 11030 USA
| | - Joshua M. Glynn
- Laboratory of Immune & Neural Networks, Institute of Molecular Medicine, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York, USA, 350 Community Drive, Manhasset, NY 11030 USA
- Department of Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, 500 Hofstra Blvd, Hempstead, NY 11549 USA
| | - Patricio T. Huerta
- Laboratory of Immune & Neural Networks, Institute of Molecular Medicine, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York, USA, 350 Community Drive, Manhasset, NY 11030 USA
- Department of Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, 500 Hofstra Blvd, Hempstead, NY 11549 USA
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Steinmetz NA, Aydin C, Lebedeva A, Okun M, Pachitariu M, Bauza M, Beau M, Bhagat J, Böhm C, Broux M, Chen S, Colonell J, Gardner RJ, Karsh B, Kloosterman F, Kostadinov D, Mora-Lopez C, O'Callaghan J, Park J, Putzeys J, Sauerbrei B, van Daal RJJ, Vollan AZ, Wang S, Welkenhuysen M, Ye Z, Dudman JT, Dutta B, Hantman AW, Harris KD, Lee AK, Moser EI, O'Keefe J, Renart A, Svoboda K, Häusser M, Haesler S, Carandini M, Harris TD. Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings. Science 2021; 372:eabf4588. [PMID: 33859006 PMCID: PMC8244810 DOI: 10.1126/science.abf4588] [Citation(s) in RCA: 333] [Impact Index Per Article: 111.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 03/01/2021] [Indexed: 12/22/2022]
Abstract
Measuring the dynamics of neural processing across time scales requires following the spiking of thousands of individual neurons over milliseconds and months. To address this need, we introduce the Neuropixels 2.0 probe together with newly designed analysis algorithms. The probe has more than 5000 sites and is miniaturized to facilitate chronic implants in small mammals and recording during unrestrained behavior. High-quality recordings over long time scales were reliably obtained in mice and rats in six laboratories. Improved site density and arrangement combined with newly created data processing methods enable automatic post hoc correction for brain movements, allowing recording from the same neurons for more than 2 months. These probes and algorithms enable stable recordings from thousands of sites during free behavior, even in small animals such as mice.
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Affiliation(s)
- Nicholas A Steinmetz
- UCL Institute of Ophthalmology, University College London, London, UK.
- Department of Biological Structure, University of Washington, Seattle, WA, USA
| | | | - Anna Lebedeva
- Sainsbury Wellcome Centre, University College London, London, UK
| | - Michael Okun
- Centre for Systems Neuroscience and Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Marius Pachitariu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Marius Bauza
- Sainsbury Wellcome Centre, University College London, London, UK
| | - Maxime Beau
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Jai Bhagat
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Claudia Böhm
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Susu Chen
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Jennifer Colonell
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Richard J Gardner
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - Bill Karsh
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Fabian Kloosterman
- Neuroelectronics Research Flanders, Leuven, Belgium
- IMEC, Leuven, Belgium
- Vlaams Instituut voor Biotechnologie (VIB), Leuven, Belgium
- Brain and Cognition, KU Leuven, Leuven, Belgium
| | - Dimitar Kostadinov
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | | | | | - Junchol Park
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Britton Sauerbrei
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Rik J J van Daal
- ATLAS Neuroengineering, Leuven, Belgium
- Neuroelectronics Research Flanders, Leuven, Belgium
- Micro- and Nanosystems, KU Leuven, Leuven, Belgium
| | - Abraham Z Vollan
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | | | | | - Zhiwen Ye
- Department of Biological Structure, University of Washington, Seattle, WA, USA
| | - Joshua T Dudman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Adam W Hantman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Kenneth D Harris
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Albert K Lee
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Edvard I Moser
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - John O'Keefe
- Sainsbury Wellcome Centre, University College London, London, UK
| | | | - Karel Svoboda
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Michael Häusser
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Sebastian Haesler
- Neuroelectronics Research Flanders, Leuven, Belgium
- Vlaams Instituut voor Biotechnologie (VIB), Leuven, Belgium
| | - Matteo Carandini
- UCL Institute of Ophthalmology, University College London, London, UK.
| | - Timothy D Harris
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
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