1
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King CW, Ledochowitsch P, Buice MA, de Vries SEJ. Saccade-Responsive Visual Cortical Neurons Do Not Exhibit Distinct Visual Response Properties. eNeuro 2023; 10:ENEURO.0051-23.2023. [PMID: 37591733 PMCID: PMC10506534 DOI: 10.1523/eneuro.0051-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 07/05/2023] [Accepted: 07/24/2023] [Indexed: 08/19/2023] Open
Abstract
Rapid saccadic eye movements are used by animals to sample different parts of the visual scene. Previous work has investigated neural correlates of these saccades in visual cortical areas such as V1; however, how saccade-responsive neurons are distributed across visual areas, cell types, and cortical layers has remained unknown. Through analyzing 818 1 h experimental sessions from the Allen Brain Observatory, we present a large-scale analysis of saccadic behaviors in head-fixed mice and their neural correlates. We find that saccade-responsive neurons are present across visual cortex, but their distribution varies considerably by transgenically defined cell type, cortical area, and cortical layer. We also find that saccade-responsive neurons do not exhibit distinct visual response properties from the broader neural population, suggesting that the saccadic responses of these neurons are likely not predominantly visually driven. These results provide insight into the roles played by different cell types within a broader, distributed network of sensory and motor interactions.
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Affiliation(s)
- Chase W King
- MindScope Program, Allen Institute, Seattle, Washington 98109
- Department of Computer Science, University of Washington, Seattle, Washington 98195-2350
| | | | - Michael A Buice
- MindScope Program, Allen Institute, Seattle, Washington 98109
- Department of Applied Mathematics, University of Washington, Seattle, Washington 98195-3925
| | - Saskia E J de Vries
- MindScope Program, Allen Institute, Seattle, Washington 98109
- Department of Physiology & Biophysics, University of Washington, Seattle, Washington 98195-7290
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2
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Baratham VL, Dougherty ME, Hermiz J, Ledochowitsch P, Maharbiz MM, Bouchard KE. Columnar Localization and Laminar Origin of Cortical Surface Electrical Potentials. J Neurosci 2022; 42:3733-3748. [PMID: 35332084 PMCID: PMC9087723 DOI: 10.1523/jneurosci.1787-21.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 02/09/2022] [Accepted: 03/09/2022] [Indexed: 11/21/2022] Open
Abstract
Electrocorticography (ECoG) methodologically bridges basic neuroscience and understanding of human brains in health and disease. However, the localization of ECoG signals across the surface of the brain and the spatial distribution of their generating neuronal sources are poorly understood. To address this gap, we recorded from rat auditory cortex using customized μECoG, and simulated cortical surface electrical potentials with a full-scale, biophysically detailed cortical column model. Experimentally, μECoG-derived auditory representations were tonotopically organized and signals were anisotropically localized to less than or equal to ±200 μm, that is, a single cortical column. Biophysical simulations reproduce experimental findings and indicate that neurons in cortical layers V and VI contribute ∼85% of evoked high-gamma signal recorded at the surface. Cell number and synchrony were the primary biophysical properties determining laminar contributions to evoked μECoG signals, whereas distance was only a minimal factor. Thus, evoked μECoG signals primarily originate from neurons in the infragranular layers of a single cortical column.SIGNIFICANCE STATEMENT ECoG methodologically bridges basic neuroscience and understanding of human brains in health and disease. However, the localization of ECoG signals across the surface of the brain and the spatial distribution of their generating neuronal sources are poorly understood. We investigated the localization and origins of sensory-evoked ECoG responses. We experimentally found that ECoG responses were anisotropically localized to a cortical column. Biophysically detailed simulations revealed that neurons in layers V and VI were the primary sources of evoked ECoG responses. These results indicate that evoked ECoG high-gamma responses are primarily generated by the population spike rate of pyramidal neurons in layers V and VI of single cortical columns and highlight the possibility of understanding how microscopic sources produce mesoscale signals.
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Affiliation(s)
- Vyassa L Baratham
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720
- Department of Physics, University of California-Berkeley, Berkeley, California 94720
| | - Maximilian E Dougherty
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - John Hermiz
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | | | - Michel M Maharbiz
- Center for Neural Engineering and Prosthesis, University of California-Berkeley/San Francisco, Berkeley, California 94720-3370
- Department of Electrical Engineering and Computer Science, University of California-Berkeley, Berkeley, California 94720
| | - Kristofer E Bouchard
- Center for Neural Engineering and Prosthesis, University of California-Berkeley/San Francisco, Berkeley, California 94720-3370
- Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience, University of California-Berkeley, Berkeley, California 94720
- Scientific Data Division, Lawerence Berkeley National Lab, Berkeley, California 94720
- Biological Systems and Engineering Division, Lawerence Berkeley National Lab, Berkeley, California 94720
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3
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Lecoq J, Oliver M, Siegle JH, Orlova N, Ledochowitsch P, Koch C. Removing independent noise in systems neuroscience data using DeepInterpolation. Nat Methods 2021; 18:1401-1408. [PMID: 34650233 PMCID: PMC8833814 DOI: 10.1038/s41592-021-01285-2] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 08/30/2021] [Indexed: 11/09/2022]
Abstract
Progress in many scientific disciplines is hindered by the presence of independent noise. Technologies for measuring neural activity (calcium imaging, extracellular electrophysiology and functional magnetic resonance imaging (fMRI)) operate in domains in which independent noise (shot noise and/or thermal noise) can overwhelm physiological signals. Here, we introduce DeepInterpolation, a general-purpose denoising algorithm that trains a spatiotemporal nonlinear interpolation model using only raw noisy samples. Applying DeepInterpolation to two-photon calcium imaging data yielded up to six times more neuronal segments than those computed from raw data with a 15-fold increase in the single-pixel signal-to-noise ratio (SNR), uncovering single-trial network dynamics that were previously obscured by noise. Extracellular electrophysiology recordings processed with DeepInterpolation yielded 25% more high-quality spiking units than those computed from raw data, while DeepInterpolation produced a 1.6-fold increase in the SNR of individual voxels in fMRI datasets. Denoising was attained without sacrificing spatial or temporal resolution and without access to ground truth training data. We anticipate that DeepInterpolation will provide similar benefits in other domains in which independent noise contaminates spatiotemporally structured datasets.
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Affiliation(s)
- Jérôme Lecoq
- MindScope Program, Allen Institute, Seattle, WA, USA.
| | | | | | | | | | - Christof Koch
- MindScope Program, Allen Institute, Seattle, WA, USA
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4
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Siegle JH, Ledochowitsch P, Jia X, Millman DJ, Ocker GK, Caldejon S, Casal L, Cho A, Denman DJ, Durand S, Groblewski PA, Heller G, Kato I, Kivikas S, Lecoq J, Nayan C, Ngo K, Nicovich PR, North K, Ramirez TK, Swapp J, Waughman X, Williford A, Olsen SR, Koch C, Buice MA, de Vries SEJ. Reconciling functional differences in populations of neurons recorded with two-photon imaging and electrophysiology. eLife 2021; 10:e69068. [PMID: 34270411 PMCID: PMC8285106 DOI: 10.7554/elife.69068] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 07/02/2021] [Indexed: 11/20/2022] Open
Abstract
Extracellular electrophysiology and two-photon calcium imaging are widely used methods for measuring physiological activity with single-cell resolution across large populations of cortical neurons. While each of these two modalities has distinct advantages and disadvantages, neither provides complete, unbiased information about the underlying neural population. Here, we compare evoked responses in visual cortex recorded in awake mice under highly standardized conditions using either imaging of genetically expressed GCaMP6f or electrophysiology with silicon probes. Across all stimulus conditions tested, we observe a larger fraction of responsive neurons in electrophysiology and higher stimulus selectivity in calcium imaging, which was partially reconciled by applying a spikes-to-calcium forward model to the electrophysiology data. However, the forward model could only reconcile differences in responsiveness when restricted to neurons with low contamination and an event rate above a minimum threshold. This work established how the biases of these two modalities impact functional metrics that are fundamental for characterizing sensory-evoked responses.
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Affiliation(s)
| | | | - Xiaoxuan Jia
- MindScope Program, Allen InstituteSeattleUnited States
| | | | | | | | - Linzy Casal
- MindScope Program, Allen InstituteSeattleUnited States
| | - Andy Cho
- MindScope Program, Allen InstituteSeattleUnited States
| | - Daniel J Denman
- Allen Institute for Brain Science, Allen InstituteSeattleUnited States
| | | | | | - Gregg Heller
- MindScope Program, Allen InstituteSeattleUnited States
| | - India Kato
- MindScope Program, Allen InstituteSeattleUnited States
| | - Sara Kivikas
- MindScope Program, Allen InstituteSeattleUnited States
| | - Jérôme Lecoq
- MindScope Program, Allen InstituteSeattleUnited States
| | - Chelsea Nayan
- MindScope Program, Allen InstituteSeattleUnited States
| | - Kiet Ngo
- Allen Institute for Brain Science, Allen InstituteSeattleUnited States
| | - Philip R Nicovich
- Allen Institute for Brain Science, Allen InstituteSeattleUnited States
| | - Kat North
- MindScope Program, Allen InstituteSeattleUnited States
| | | | - Jackie Swapp
- MindScope Program, Allen InstituteSeattleUnited States
| | - Xana Waughman
- MindScope Program, Allen InstituteSeattleUnited States
| | - Ali Williford
- MindScope Program, Allen InstituteSeattleUnited States
| | - Shawn R Olsen
- MindScope Program, Allen InstituteSeattleUnited States
| | - Christof Koch
- MindScope Program, Allen InstituteSeattleUnited States
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5
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Huang L, Ledochowitsch P, Knoblich U, Lecoq J, Murphy GJ, Reid RC, de Vries SE, Koch C, Zeng H, Buice MA, Waters J, Li L. Relationship between simultaneously recorded spiking activity and fluorescence signal in GCaMP6 transgenic mice. eLife 2021; 10:51675. [PMID: 33683198 PMCID: PMC8060029 DOI: 10.7554/elife.51675] [Citation(s) in RCA: 88] [Impact Index Per Article: 29.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Accepted: 03/05/2021] [Indexed: 12/11/2022] Open
Abstract
Fluorescent calcium indicators are often used to investigate neural dynamics, but the relationship between fluorescence and action potentials (APs) remains unclear. Most APs can be detected when the soma almost fills the microscope’s field of view, but calcium indicators are used to image populations of neurons, necessitating a large field of view, generating fewer photons per neuron, and compromising AP detection. Here, we characterized the AP-fluorescence transfer function in vivo for 48 layer 2/3 pyramidal neurons in primary visual cortex, with simultaneous calcium imaging and cell-attached recordings from transgenic mice expressing GCaMP6s or GCaMP6f. While most APs were detected under optimal conditions, under conditions typical of population imaging studies, only a minority of 1 AP and 2 AP events were detected (often <10% and ~20–30%, respectively), emphasizing the limits of AP detection under more realistic imaging conditions. Neurons, the cells that make up the nervous system, transmit information using electrical signals known as action potentials or spikes. Studying the spiking patterns of neurons in the brain is essential to understand perception, memory, thought, and behaviour. One way to do that is by recording electrical activity with microelectrodes. Another way to study neuronal activity is by using molecules that change how they interact with light when calcium binds to them, since changes in calcium concentration can be indicative of neuronal spiking. That change can be observed with specialized microscopes know as two-photon fluorescence microscopes. Using calcium indicators, it is possible to simultaneously record hundreds or even thousands of neurons. However, calcium fluorescence and spikes do not translate one-to-one. In order to interpret fluorescence data, it is important to understand the relationship between the fluorescence signals and the spikes associated with individual neurons. The only way to directly measure this relationship is by using calcium imaging and electrical recording simultaneously to record activity from the same neuron. However, this is extremely challenging experimentally, so this type of data is rare. To shed some light on this, Huang, Ledochowitsch et al. used mice that had been genetically modified to produce a calcium indicator in neurons of the visual cortex and simultaneously obtained both fluorescence measurements and electrical recordings from these neurons. These experiments revealed that, while the majority of time periods containing multi-spike neural activity could be identified using calcium imaging microscopy, on average, less than 10% of isolated single spikes were detectable. This is an important caveat that researchers need to take into consideration when interpreting calcium imaging results. These findings are intended to serve as a guide for interpreting calcium imaging studies that look at neurons in the mammalian brain at the population level. In addition, the data provided will be useful as a reference for the development of activity sensors, and to benchmark and improve computational approaches for detecting and predicting spikes.
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Affiliation(s)
- Lawrence Huang
- Allen Institute for Brain Science, Seattle, United States
| | | | - Ulf Knoblich
- Allen Institute for Brain Science, Seattle, United States
| | - Jérôme Lecoq
- Allen Institute for Brain Science, Seattle, United States
| | - Gabe J Murphy
- Allen Institute for Brain Science, Seattle, United States
| | - R Clay Reid
- Allen Institute for Brain Science, Seattle, United States
| | | | - Christof Koch
- Allen Institute for Brain Science, Seattle, United States
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, United States
| | | | - Jack Waters
- Allen Institute for Brain Science, Seattle, United States
| | - Lu Li
- Allen Institute for Brain Science, Seattle, United States.,Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Medical Research Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
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6
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Siegle JH, Jia X, Durand S, Gale S, Bennett C, Graddis N, Heller G, Ramirez TK, Choi H, Luviano JA, Groblewski PA, Ahmed R, Arkhipov A, Bernard A, Billeh YN, Brown D, Buice MA, Cain N, Caldejon S, Casal L, Cho A, Chvilicek M, Cox TC, Dai K, Denman DJ, de Vries SEJ, Dietzman R, Esposito L, Farrell C, Feng D, Galbraith J, Garrett M, Gelfand EC, Hancock N, Harris JA, Howard R, Hu B, Hytnen R, Iyer R, Jessett E, Johnson K, Kato I, Kiggins J, Lambert S, Lecoq J, Ledochowitsch P, Lee JH, Leon A, Li Y, Liang E, Long F, Mace K, Melchior J, Millman D, Mollenkopf T, Nayan C, Ng L, Ngo K, Nguyen T, Nicovich PR, North K, Ocker GK, Ollerenshaw D, Oliver M, Pachitariu M, Perkins J, Reding M, Reid D, Robertson M, Ronellenfitch K, Seid S, Slaughterbeck C, Stoecklin M, Sullivan D, Sutton B, Swapp J, Thompson C, Turner K, Wakeman W, Whitesell JD, Williams D, Williford A, Young R, Zeng H, Naylor S, Phillips JW, Reid RC, Mihalas S, Olsen SR, Koch C. Survey of spiking in the mouse visual system reveals functional hierarchy. Nature 2021; 592:86-92. [PMID: 33473216 PMCID: PMC10399640 DOI: 10.1038/s41586-020-03171-x] [Citation(s) in RCA: 148] [Impact Index Per Article: 49.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Accepted: 12/09/2020] [Indexed: 12/14/2022]
Abstract
The anatomy of the mammalian visual system, from the retina to the neocortex, is organized hierarchically1. However, direct observation of cellular-level functional interactions across this hierarchy is lacking due to the challenge of simultaneously recording activity across numerous regions. Here we describe a large, open dataset-part of the Allen Brain Observatory2-that surveys spiking from tens of thousands of units in six cortical and two thalamic regions in the brains of mice responding to a battery of visual stimuli. Using cross-correlation analysis, we reveal that the organization of inter-area functional connectivity during visual stimulation mirrors the anatomical hierarchy from the Allen Mouse Brain Connectivity Atlas3. We find that four classical hierarchical measures-response latency, receptive-field size, phase-locking to drifting gratings and response decay timescale-are all correlated with the hierarchy. Moreover, recordings obtained during a visual task reveal that the correlation between neural activity and behavioural choice also increases along the hierarchy. Our study provides a foundation for understanding coding and signal propagation across hierarchically organized cortical and thalamic visual areas.
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Affiliation(s)
| | - Xiaoxuan Jia
- Allen Institute for Brain Science, Seattle, WA, USA.
| | | | - Sam Gale
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Nile Graddis
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Hannah Choi
- Allen Institute for Brain Science, Seattle, WA, USA.,Department of Applied Mathematics, University of Washington, Seattle, WA, USA
| | | | | | | | | | - Amy Bernard
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Dillan Brown
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Nicolas Cain
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Linzy Casal
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Andrew Cho
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Timothy C Cox
- University of Missouri-Kansas City School of Dentistry, Kansas City, MO, USA
| | - Kael Dai
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Daniel J Denman
- Allen Institute for Brain Science, Seattle, WA, USA.,The University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | | | | | | | | | - David Feng
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | | | | | - Brian Hu
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Ross Hytnen
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - India Kato
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Jerome Lecoq
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Arielle Leon
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Yang Li
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Fuhui Long
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Kyla Mace
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | - Lydia Ng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Kiet Ngo
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Kat North
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | - Jed Perkins
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - David Reid
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Sam Seid
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Ben Sutton
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Jackie Swapp
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | | | | | - Rob Young
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Sarah Naylor
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - R Clay Reid
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Shawn R Olsen
- Allen Institute for Brain Science, Seattle, WA, USA.
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7
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Garrett M, Manavi S, Roll K, Ollerenshaw DR, Groblewski PA, Ponvert ND, Kiggins JT, Casal L, Mace K, Williford A, Leon A, Jia X, Ledochowitsch P, Buice MA, Wakeman W, Mihalas S, Olsen SR. Experience shapes activity dynamics and stimulus coding of VIP inhibitory cells. eLife 2020; 9:e50340. [PMID: 32101169 PMCID: PMC7043888 DOI: 10.7554/elife.50340] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 02/05/2020] [Indexed: 02/07/2023] Open
Abstract
Cortical circuits can flexibly change with experience and learning, but the effects on specific cell types, including distinct inhibitory types, are not well understood. Here we investigated how excitatory and VIP inhibitory cells in layer 2/3 of mouse visual cortex were impacted by visual experience in the context of a behavioral task. Mice learned a visual change detection task with a set of eight natural scene images. Subsequently, during 2-photon imaging experiments, mice performed the task with these familiar images and three sets of novel images. Strikingly, the temporal dynamics of VIP activity differed markedly between novel and familiar images: VIP cells were stimulus-driven by novel images but were suppressed by familiar stimuli and showed ramping activity when expected stimuli were omitted from a temporally predictable sequence. This prominent change in VIP activity suggests that these cells may adopt different modes of processing under novel versus familiar conditions.
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Affiliation(s)
| | - Sahar Manavi
- Allen Institute for Brain ScienceSeattleUnited States
| | - Kate Roll
- Allen Institute for Brain ScienceSeattleUnited States
| | | | | | | | | | - Linzy Casal
- Allen Institute for Brain ScienceSeattleUnited States
| | - Kyla Mace
- Allen Institute for Brain ScienceSeattleUnited States
| | - Ali Williford
- Allen Institute for Brain ScienceSeattleUnited States
| | - Arielle Leon
- Allen Institute for Brain ScienceSeattleUnited States
| | - Xiaoxuan Jia
- Allen Institute for Brain ScienceSeattleUnited States
| | | | | | - Wayne Wakeman
- Allen Institute for Brain ScienceSeattleUnited States
| | | | - Shawn R Olsen
- Allen Institute for Brain ScienceSeattleUnited States
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8
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de Vries SEJ, Lecoq JA, Buice MA, Groblewski PA, Ocker GK, Oliver M, Feng D, Cain N, Ledochowitsch P, Millman D, Roll K, Garrett M, Keenan T, Kuan L, Mihalas S, Olsen S, Thompson C, Wakeman W, Waters J, Williams D, Barber C, Berbesque N, Blanchard B, Bowles N, Caldejon SD, Casal L, Cho A, Cross S, Dang C, Dolbeare T, Edwards M, Galbraith J, Gaudreault N, Gilbert TL, Griffin F, Hargrave P, Howard R, Huang L, Jewell S, Keller N, Knoblich U, Larkin JD, Larsen R, Lau C, Lee E, Lee F, Leon A, Li L, Long F, Luviano J, Mace K, Nguyen T, Perkins J, Robertson M, Seid S, Shea-Brown E, Shi J, Sjoquist N, Slaughterbeck C, Sullivan D, Valenza R, White C, Williford A, Witten DM, Zhuang J, Zeng H, Farrell C, Ng L, Bernard A, Phillips JW, Reid RC, Koch C. A large-scale standardized physiological survey reveals functional organization of the mouse visual cortex. Nat Neurosci 2020; 23:138-151. [PMID: 31844315 PMCID: PMC6948932 DOI: 10.1038/s41593-019-0550-9] [Citation(s) in RCA: 134] [Impact Index Per Article: 33.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Accepted: 10/28/2019] [Indexed: 11/16/2022]
Abstract
To understand how the brain processes sensory information to guide behavior, we must know how stimulus representations are transformed throughout the visual cortex. Here we report an open, large-scale physiological survey of activity in the awake mouse visual cortex: the Allen Brain Observatory Visual Coding dataset. This publicly available dataset includes the cortical activity of nearly 60,000 neurons from six visual areas, four layers, and 12 transgenic mouse lines in a total of 243 adult mice, in response to a systematic set of visual stimuli. We classify neurons on the basis of joint reliabilities to multiple stimuli and validate this functional classification with models of visual responses. While most classes are characterized by responses to specific subsets of the stimuli, the largest class is not reliably responsive to any of the stimuli and becomes progressively larger in higher visual areas. These classes reveal a functional organization wherein putative dorsal areas show specialization for visual motion signals.
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Affiliation(s)
| | | | | | | | | | | | - David Feng
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Kate Roll
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Tom Keenan
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Leonard Kuan
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Shawn Olsen
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Jack Waters
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Chris Barber
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | - Linzy Casal
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Andrew Cho
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Sissy Cross
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Chinh Dang
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Tim Dolbeare
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | | | | | | | | | - Sean Jewell
- Department of Statistics, University of Washington, Seattle, WA, USA
| | - Nika Keller
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Ulf Knoblich
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Chris Lau
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Eric Lee
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Felix Lee
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Arielle Leon
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Lu Li
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Fuhui Long
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Kyla Mace
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Jed Perkins
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Sam Seid
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Eric Shea-Brown
- Allen Institute for Brain Science, Seattle, WA, USA
- Department of Applied Mathematics, University of Washington, Seattle, WA, USA
| | - Jianghong Shi
- Department of Applied Mathematics, University of Washington, Seattle, WA, USA
| | | | | | | | - Ryan Valenza
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Casey White
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Daniela M Witten
- Department of Statistics, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Jun Zhuang
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Lydia Ng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Amy Bernard
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - R Clay Reid
- Allen Institute for Brain Science, Seattle, WA, USA
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9
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Tsyboulski D, Orlova N, Ledochowitsch P, Saggau P. Two-photon frequency division multiplexing for functional in vivo imaging: a feasibility study. Opt Express 2019; 27:4488-4503. [PMID: 30876067 DOI: 10.1364/oe.27.004488] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Accepted: 01/19/2019] [Indexed: 06/09/2023]
Abstract
Recently, we presented a new approach to create high-speed amplitude modulation of femtosecond laser pulses and tag multiple excitation beams with specific modulation frequencies. In this work, we discuss the utility of this method to record calcium signals in brain tissue with two-photon frequency-division multiplexing (2P-FDM) microscopy. While frequency-multiplexed imaging appears slightly inferior in terms of image quality as compared to conventional two-photon laser scanning microscopy due to shot noise-induced cross-talk between frequency channels, applying this technique to record average signals from regions of interest (ROI) such as neuronal cell bodies was found to be promising. We use phase information associated with each pixel or waveform within a selected ROI to phase-align and recombine the signals into one extended amplitude-modulated waveform. This procedure narrows the frequency detection window, effectively decreasing noise contributions from other frequency channels. Using theoretical analysis, numerical simulations, and in vitro imaging, we demonstrate a reduction of cross-talk by more than an order of magnitude and predict the usefulness of 2P-FDM for functional studies of brain activity.
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Jun JJ, Steinmetz NA, Siegle JH, Denman DJ, Bauza M, Barbarits B, Lee AK, Anastassiou CA, Andrei A, Aydın Ç, Barbic M, Blanche TJ, Bonin V, Couto J, Dutta B, Gratiy SL, Gutnisky DA, Häusser M, Karsh B, Ledochowitsch P, Lopez CM, Mitelut C, Musa S, Okun M, Pachitariu M, Putzeys J, Rich PD, Rossant C, Sun WL, Svoboda K, Carandini M, Harris KD, Koch C, O'Keefe J, Harris TD. Fully integrated silicon probes for high-density recording of neural activity. Nature 2017; 551:232-236. [PMID: 29120427 PMCID: PMC5955206 DOI: 10.1038/nature24636] [Citation(s) in RCA: 947] [Impact Index Per Article: 135.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2017] [Accepted: 10/16/2017] [Indexed: 12/24/2022]
Abstract
Sensory, motor and cognitive operations involve the coordinated action of large neuronal populations across multiple brain regions in both superficial and deep structures. Existing extracellular probes record neural activity with excellent spatial and temporal (sub-millisecond) resolution, but from only a few dozen neurons per shank. Optical Ca2+ imaging offers more coverage but lacks the temporal resolution needed to distinguish individual spikes reliably and does not measure local field potentials. Until now, no technology compatible with use in unrestrained animals has combined high spatiotemporal resolution with large volume coverage. Here we design, fabricate and test a new silicon probe known as Neuropixels to meet this need. Each probe has 384 recording channels that can programmably address 960 complementary metal-oxide-semiconductor (CMOS) processing-compatible low-impedance TiN sites that tile a single 10-mm long, 70 × 20-μm cross-section shank. The 6 × 9-mm probe base is fabricated with the shank on a single chip. Voltage signals are filtered, amplified, multiplexed and digitized on the base, allowing the direct transmission of noise-free digital data from the probe. The combination of dense recording sites and high channel count yielded well-isolated spiking activity from hundreds of neurons per probe implanted in mice and rats. Using two probes, more than 700 well-isolated single neurons were recorded simultaneously from five brain structures in an awake mouse. The fully integrated functionality and small size of Neuropixels probes allowed large populations of neurons from several brain structures to be recorded in freely moving animals. This combination of high-performance electrode technology and scalable chip fabrication methods opens a path towards recording of brain-wide neural activity during behaviour.
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Affiliation(s)
- James J. Jun
- HHMI Janelia Research Campus, 19700 Helix Dr., Ashburn, VA 20147
| | - Nicholas A. Steinmetz
- UCL Institute of Neurology, University College London, London WC1N 3BG, UK
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6DE, UK
- UCL Institute of Ophthalmology, University College London, London EC1V 9EL, UK
| | - Joshua H. Siegle
- Allen Institute for Brain Science, 615 Westlake Ave N, Seattle, WA 98109
| | - Daniel J. Denman
- Allen Institute for Brain Science, 615 Westlake Ave N, Seattle, WA 98109
| | - Marius Bauza
- Department of Cell and Developmental Biology, University College London, London WC1E 6BT, UK
- Sainsbury Wellcome Center, University College London, London W1T 4JG, UK
| | - Brian Barbarits
- HHMI Janelia Research Campus, 19700 Helix Dr., Ashburn, VA 20147
| | - Albert K. Lee
- HHMI Janelia Research Campus, 19700 Helix Dr., Ashburn, VA 20147
| | | | | | - Çağatay Aydın
- Neuro-Electronics Research Flanders, Kapeldreef 75, 3001 Leuven Belgium
- KU Leuven, Department of Biology, Naamsestraat 59, 3000 Leuven, Belgium
| | - Mladen Barbic
- HHMI Janelia Research Campus, 19700 Helix Dr., Ashburn, VA 20147
| | - Timothy J. Blanche
- Allen Institute for Brain Science, 615 Westlake Ave N, Seattle, WA 98109
- White Matter LLC, Seattle, USA
| | - Vincent Bonin
- imec, Kapeldreef 75, 3001 Heverlee, Leuven Belgium
- Neuro-Electronics Research Flanders, Kapeldreef 75, 3001 Leuven Belgium
- KU Leuven, Department of Biology, Naamsestraat 59, 3000 Leuven, Belgium
- VIB, 3001 Leuven, Belgium
| | - João Couto
- Neuro-Electronics Research Flanders, Kapeldreef 75, 3001 Leuven Belgium
- KU Leuven, Department of Biology, Naamsestraat 59, 3000 Leuven, Belgium
| | | | - Sergey L. Gratiy
- Allen Institute for Brain Science, 615 Westlake Ave N, Seattle, WA 98109
| | | | - Michael Häusser
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6DE, UK
- Wolfson Institute for Biomedical Research, University College London, Gower Street, London WC1E 6BT, UK
| | - Bill Karsh
- HHMI Janelia Research Campus, 19700 Helix Dr., Ashburn, VA 20147
| | | | | | - Catalin Mitelut
- Allen Institute for Brain Science, 615 Westlake Ave N, Seattle, WA 98109
| | - Silke Musa
- imec, Kapeldreef 75, 3001 Heverlee, Leuven Belgium
| | - Michael Okun
- UCL Institute of Neurology, University College London, London WC1N 3BG, UK
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6DE, UK
- Centre for Systems Neuroscience, University of Leicester, Leicester LE1 7QR, UK
| | - Marius Pachitariu
- UCL Institute of Neurology, University College London, London WC1N 3BG, UK
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6DE, UK
| | - Jan Putzeys
- imec, Kapeldreef 75, 3001 Heverlee, Leuven Belgium
| | - P. Dylan Rich
- HHMI Janelia Research Campus, 19700 Helix Dr., Ashburn, VA 20147
| | - Cyrille Rossant
- UCL Institute of Neurology, University College London, London WC1N 3BG, UK
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6DE, UK
| | - Wei-lung Sun
- HHMI Janelia Research Campus, 19700 Helix Dr., Ashburn, VA 20147
| | - Karel Svoboda
- HHMI Janelia Research Campus, 19700 Helix Dr., Ashburn, VA 20147
| | - Matteo Carandini
- UCL Institute of Ophthalmology, University College London, London EC1V 9EL, UK
| | - Kenneth D. Harris
- UCL Institute of Neurology, University College London, London WC1N 3BG, UK
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6DE, UK
| | - Christof Koch
- Allen Institute for Brain Science, 615 Westlake Ave N, Seattle, WA 98109
| | - John O'Keefe
- Department of Cell and Developmental Biology, University College London, London WC1E 6BT, UK
- Sainsbury Wellcome Center, University College London, London W1T 4JG, UK
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Yazdan-Shahmorad A, Diaz-Botia C, Hanson T, Kharazia V, Ledochowitsch P, Maharbiz M, Sabes P. A Large-Scale Interface for Optogenetic Stimulation and Recording in Nonhuman Primates. Neuron 2016; 89:927-39. [DOI: 10.1016/j.neuron.2016.01.013] [Citation(s) in RCA: 76] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2014] [Revised: 07/28/2015] [Accepted: 01/05/2016] [Indexed: 12/15/2022]
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Ledochowitsch P, Koralek AC, Moses D, Carmena JM, Maharbiz MM. Sub-mm functional decoupling of electrocortical signals through closed-loop BMI learning. Annu Int Conf IEEE Eng Med Biol Soc 2015; 2013:5622-5. [PMID: 24111012 DOI: 10.1109/embc.2013.6610825] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Volitional control of neural activity lies at the heart of the Brain-Machine Interface (BMI) paradigm. In this work we investigated if subdural field potentials recorded by electrodes < 1mm apart can be decoupled through closed-loop BMI learning. To this end, we fabricated custom, flexible microelectrode arrays with 200 µm electrode pitch and increased the effective electrode area by electrodeposition of platinum black to reduce thermal noise. We have chronically implanted these arrays subdurally over primary motor cortex (M1) of 5 male Long-Evans Rats and monitored the electrochemical electrode impedance in vivo to assess the stability of these neural interfaces. We successfully trained the rodents to perform a one-dimensional center-out task using closed-loop brain control to adjust the pitch of an auditory cursor by differentially modulating high gamma (70-110 Hz) power on pairs of surface microelectrodes that were separated by less than 1 mm.
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Ledochowitsch P, Yazdan-Shahmorad A, Bouchard KE, Diaz-Botia C, Hanson TL, He JW, Seybold BA, Olivero E, Phillips EAK, Blanche TJ, Schreiner CE, Hasenstaub A, Chang EF, Sabes PN, Maharbiz MM. Strategies for optical control and simultaneous electrical readout of extended cortical circuits. J Neurosci Methods 2015; 256:220-31. [PMID: 26296286 DOI: 10.1016/j.jneumeth.2015.07.028] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2014] [Revised: 07/27/2015] [Accepted: 07/27/2015] [Indexed: 01/06/2023]
Abstract
BACKGROUND To dissect the intricate workings of neural circuits, it is essential to gain precise control over subsets of neurons while retaining the ability to monitor larger-scale circuit dynamics. This requires the ability to both evoke and record neural activity simultaneously with high spatial and temporal resolution. NEW METHOD In this paper we present approaches that address this need by combining micro-electrocorticography (μECoG) with optogenetics in ways that avoid photovoltaic artifacts. RESULTS We demonstrate that variations of this approach are broadly applicable across three commonly studied mammalian species - mouse, rat, and macaque monkey - and that the recorded μECoG signal shows complex spectral and spatio-temporal patterns in response to optical stimulation. COMPARISON WITH EXISTING METHODS While optogenetics provides the ability to excite or inhibit neural subpopulations in a targeted fashion, large-scale recording of resulting neural activity remains challenging. Recent advances in optical physiology, such as genetically encoded Ca(2+) indicators, are promising but currently do not allow simultaneous recordings from extended cortical areas due to limitations in optical imaging hardware. CONCLUSIONS We demonstrate techniques for the large-scale simultaneous interrogation of cortical circuits in three commonly used mammalian species.
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Affiliation(s)
- P Ledochowitsch
- The UC Berkeley-UCSF Graduate Program in Bioengineering, Berkeley, CA, United States; The Center for Neural Engineering and Prostheses (CNEP), United States.
| | - A Yazdan-Shahmorad
- UCSF Center for Integrative Neuroscience, San Francisco, CA, United States; The Center for Neural Engineering and Prostheses (CNEP), United States
| | - K E Bouchard
- UCSF Center for Integrative Neuroscience, San Francisco, CA, United States; LBNL, Life Sciences and Computational Research Divisions, Berkeley, CA, United States; The Center for Neural Engineering and Prostheses (CNEP), United States
| | - C Diaz-Botia
- The UC Berkeley-UCSF Graduate Program in Bioengineering, Berkeley, CA, United States; The Center for Neural Engineering and Prostheses (CNEP), United States
| | - T L Hanson
- UCSF Center for Integrative Neuroscience, San Francisco, CA, United States; The Center for Neural Engineering and Prostheses (CNEP), United States
| | - J-W He
- UCSF Center for Integrative Neuroscience, San Francisco, CA, United States; The Center for Neural Engineering and Prostheses (CNEP), United States
| | - B A Seybold
- UCSF Center for Integrative Neuroscience, San Francisco, CA, United States; The Center for Neural Engineering and Prostheses (CNEP), United States
| | - E Olivero
- Department of Electrical Engineering and Computer Science, Berkeley, CA, United States
| | - E A K Phillips
- UCSF Center for Integrative Neuroscience, San Francisco, CA, United States
| | - T J Blanche
- UC Berkeley-Redwood Center for Theoretical Neuroscience, Berkeley, CA, United States
| | - C E Schreiner
- UCSF Center for Integrative Neuroscience, San Francisco, CA, United States; The Center for Neural Engineering and Prostheses (CNEP), United States
| | - A Hasenstaub
- UCSF Center for Integrative Neuroscience, San Francisco, CA, United States
| | - E F Chang
- UCSF Center for Integrative Neuroscience, San Francisco, CA, United States; The Center for Neural Engineering and Prostheses (CNEP), United States
| | - P N Sabes
- UCSF Center for Integrative Neuroscience, San Francisco, CA, United States; The Center for Neural Engineering and Prostheses (CNEP), United States
| | - M M Maharbiz
- Department of Electrical Engineering and Computer Science, Berkeley, CA, United States; The Center for Neural Engineering and Prostheses (CNEP), United States
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Ledochowitsch P, Olivero E, Blanche T, Maharbiz MM. A transparent μECoG array for simultaneous recording and optogenetic stimulation. Annu Int Conf IEEE Eng Med Biol Soc 2011; 2011:2937-2940. [PMID: 22254956 DOI: 10.1109/iembs.2011.6090808] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
In this paper we report for the first time the design, fabrication and characterization of an optically transparent electrode array for micro-electrocorticography. We present a 49-channel μECoG array with an electrode pitch of 800 μm and a 16-channel linear μECoG array with an electrode pitch of 200 μm. The backing material was Parylene C. Transparent, sputtered indium tin oxide (ITO) was used in conjunction with e-beam evaporated gold to fabricate the electrodes. We provide electrochemical impedance characterization and light transmission data for the fabricated devices.
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Affiliation(s)
- Peter Ledochowitsch
- Bioengineering Department, University of California, Berkeley, CA 94720, USA
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