51
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Bennett M. An Attempt at a Unified Theory of the Neocortical Microcircuit in Sensory Cortex. Front Neural Circuits 2020; 14:40. [PMID: 32848632 PMCID: PMC7416357 DOI: 10.3389/fncir.2020.00040] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 06/15/2020] [Indexed: 11/13/2022] Open
Abstract
The neocortex performs a wide range of functions, including working memory, sensory perception, and motor planning. Despite this diversity in function, evidence suggests that the neocortex is made up of repeating subunits ("macrocolumns"), each of which is largely identical in circuitry. As such, the specific computations performed by these macrocolumns are of great interest to neuroscientists and AI researchers. Leading theories of this microcircuit include models of predictive coding, hierarchical temporal memory (HTM), and Adaptive Resonance Theory (ART). However, these models have not yet explained: (1) how microcircuits learn sequences input with delay (i.e., working memory); (2) how networks of columns coordinate processing on precise timescales; or (3) how top-down attention modulates sensory processing. I provide a theory of the neocortical microcircuit that extends prior models in all three ways. Additionally, this theory provides a novel working memory circuit that extends prior models to support simultaneous multi-item storage without disrupting ongoing sensory processing. I then use this theory to explain the functional origin of a diverse set of experimental findings, such as cortical oscillations.
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Affiliation(s)
- Max Bennett
- Independent Researcher, New York, NY, United States
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52
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Cell-Type-Specific Outcome Representation in the Primary Motor Cortex. Neuron 2020; 107:954-971.e9. [PMID: 32589878 DOI: 10.1016/j.neuron.2020.06.006] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 04/14/2020] [Accepted: 06/02/2020] [Indexed: 12/18/2022]
Abstract
Adaptive movements are critical for animal survival. To guide future actions, the brain monitors various outcomes, including achievement of movement and appetitive goals. The nature of these outcome signals and their neuronal and network realization in the motor cortex (M1), which directs skilled movements, is largely unknown. Using a dexterity task, calcium imaging, optogenetic perturbations, and behavioral manipulations, we studied outcome signals in the murine forelimb M1. We found two populations of layer 2-3 neurons, termed success- and failure-related neurons, that develop with training, and report end results of trials. In these neurons, prolonged responses were recorded after success or failure trials independent of reward and kinematics. In addition, the initial state of layer 5 pyramidal tract neurons contained a memory trace of the previous trial's outcome. Intertrial cortical activity was needed to learn new task requirements. These M1 layer-specific performance outcome signals may support reinforcement motor learning of skilled behavior.
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53
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McColgan P, Joubert J, Tabrizi SJ, Rees G. The human motor cortex microcircuit: insights for neurodegenerative disease. Nat Rev Neurosci 2020; 21:401-415. [PMID: 32555340 DOI: 10.1038/s41583-020-0315-1] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/04/2020] [Indexed: 12/22/2022]
Abstract
The human motor cortex comprises a microcircuit of five interconnected layers with different cell types. In this Review, we use a layer-specific and cell-specific approach to integrate physiological accounts of this motor cortex microcircuit with the pathophysiology of neurodegenerative diseases affecting motor functions. In doing so we can begin to link motor microcircuit pathology to specific disease stages and clinical phenotypes. Based on microcircuit physiology, we can make future predictions of axonal loss and microcircuit dysfunction. With recent advances in high-resolution neuroimaging we can then test these predictions in humans in vivo, providing mechanistic insights into neurodegenerative disease.
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Affiliation(s)
- Peter McColgan
- Huntington's Disease Research Centre, UCL Institute of Neurology, University College London, London, UK.
| | - Julie Joubert
- Huntington's Disease Research Centre, UCL Institute of Neurology, University College London, London, UK
| | - Sarah J Tabrizi
- Huntington's Disease Research Centre, UCL Institute of Neurology, University College London, London, UK.,Dementia Research Institute at UCL, London, UK
| | - Geraint Rees
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, UK.,UCL Institute of Cognitive Neuroscience, University College London, London, UK
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54
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Matteucci G, Riggi M, Zoccolan D. A template-matching algorithm for laminar identification of cortical recording sites from evoked response potentials. J Neurophysiol 2020; 124:102-114. [PMID: 32490704 PMCID: PMC7474457 DOI: 10.1152/jn.00033.2020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 05/11/2020] [Accepted: 05/11/2020] [Indexed: 11/22/2022] Open
Abstract
In recent years, the advent of the so-called silicon probes has made it possible to homogeneously sample spikes and local field potentials (LFPs) from a regular grid of cortical recording sites. In principle, this allows inferring the laminar location of the sites based on the spatiotemporal pattern of LFPs recorded along the probe, as in the well-known current source-density (CSD) analysis. This approach, however, has several limitations, since it relies on visual identification of landmark features (i.e., current sinks and sources) by human operators - features that can be absent from the CSD pattern if the probe does not span the whole cortical thickness, thus making manual labelling harder. Furthermore, as any manual annotation procedure, the typical CSD-based workflow for laminar identification of recording sites is affected by subjective judgment undermining the consistency and reproducibility of results. To overcome these limitations, we developed an alternative approach, based on finding the optimal match between the LFPs recorded along a probe in a given experiment and a template LFP profile that was computed using 18 recording sessions, in which the depth of the recording sites had been recovered through histology. We show that this method can achieve an accuracy of 79 µm in recovering the cortical depth of recording sites and a 76% accuracy in inferring their laminar location. As such, our approach provides an alternative to CSD that, being fully automated, is less prone to the idiosyncrasies of subjective judgment and works reliably also for recordings spanning a limited cortical stretch.
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55
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Weible AP, Stebritz AJ, Wehr M. 5XFAD mice show early-onset gap encoding deficits in the auditory cortex. Neurobiol Aging 2020; 94:101-110. [PMID: 32599514 DOI: 10.1016/j.neurobiolaging.2020.05.013] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 05/19/2020] [Accepted: 05/24/2020] [Indexed: 12/26/2022]
Abstract
Early detection will be crucial for effective treatment or prevention of Alzheimer's disease. The identification and validation of early, noninvasive biomarkers is therefore key to avoiding the most devastating aspects of Alzheimer's disease. Measures of central auditory processing such as gap detection have recently emerged as potential biomarkers in both human patients and the 5XFAD mouse model of Alzheimer's disease. Full validation of gap detection deficits as a biomarker will require detailed understanding of the underlying neuropathology, including which brain structures are involved and how the operation of neural circuits is affected. Here we show that 5XFAD mice exhibit gap detection deficits as early as 2 months of age, well before development of Alzheimer's disease-associated pathology. We then examined responses of neurons in the auditory cortex to gaps in white noise. Both gap responses and baseline firing rates were robustly and progressively degraded in 5XFAD mice compared to littermate controls. These impairments were first evident at 2-4 months of age in males, and 4-6 months in females. This demonstrates early-onset impairments to the central auditory system, which could be due to damage in the auditory cortex, upstream subcortical structures, or both.
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Affiliation(s)
- Aldis P Weible
- Department of Psychology, Institute of Neuroscience, Eugene, OR, USA
| | - Amanda J Stebritz
- Department of Psychology, Institute of Neuroscience, Eugene, OR, USA
| | - Michael Wehr
- Department of Psychology, Institute of Neuroscience, Eugene, OR, USA.
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56
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Simultaneous multiplane imaging with reverberation two-photon microscopy. Nat Methods 2020; 17:283-286. [PMID: 32042186 DOI: 10.1038/s41592-019-0728-9] [Citation(s) in RCA: 61] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2019] [Accepted: 12/19/2019] [Indexed: 11/08/2022]
Abstract
Multiphoton microscopy has gained enormous popularity because of its unique capacity to provide high-resolution images from deep within scattering tissue. Here, we demonstrate video-rate multiplane imaging with two-photon microscopy by performing near-instantaneous axial scanning while maintaining three-dimensional micrometer-scale resolution. Our technique, termed reverberation microscopy, enables the monitoring of neuronal populations over large depth ranges and can be implemented as a simple add-on to a conventional design.
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57
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Brunk MGK, Deane KE, Kisse M, Deliano M, Vieweg S, Ohl FW, Lippert MT, Happel MFK. Optogenetic stimulation of the VTA modulates a frequency-specific gain of thalamocortical inputs in infragranular layers of the auditory cortex. Sci Rep 2019; 9:20385. [PMID: 31892726 PMCID: PMC6938496 DOI: 10.1038/s41598-019-56926-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Accepted: 12/16/2019] [Indexed: 12/22/2022] Open
Abstract
Reward associations during auditory learning induce cortical plasticity in the primary auditory cortex. A prominent source of such influence is the ventral tegmental area (VTA), which conveys a dopaminergic teaching signal to the primary auditory cortex. Yet, it is unknown, how the VTA influences cortical frequency processing and spectral integration. Therefore, we investigated the temporal effects of direct optogenetic stimulation of the VTA onto spectral integration in the auditory cortex on a synaptic circuit level by current-source-density analysis in anesthetized Mongolian gerbils. While auditory lemniscal input predominantly terminates in the granular input layers III/IV, we found that VTA-mediated modulation of spectral processing is relayed by a different circuit, namely enhanced thalamic inputs to the infragranular layers Vb/VIa. Activation of this circuit yields a frequency-specific gain amplification of local sensory input and enhances corticocortical information transfer, especially in supragranular layers I/II. This effects persisted over more than 30 minutes after VTA stimulation. Altogether, we demonstrate that the VTA exhibits a long-lasting influence on sensory cortical processing via infragranular layers transcending the signaling of a mere reward-prediction error. We thereby demonstrate a cellular and circuit substrate for the influence of reinforcement-evaluating brain systems on sensory processing in the auditory cortex.
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Affiliation(s)
- Michael G K Brunk
- Department of Systems Physiology of Learning, Leibniz Institute for Neurobiology, 39118, Magdeburg, Germany.
| | - Katrina E Deane
- Department of Systems Physiology of Learning, Leibniz Institute for Neurobiology, 39118, Magdeburg, Germany
| | - Martin Kisse
- Department of Systems Physiology of Learning, Leibniz Institute for Neurobiology, 39118, Magdeburg, Germany
| | - Matthias Deliano
- Department of Systems Physiology of Learning, Leibniz Institute for Neurobiology, 39118, Magdeburg, Germany
| | - Silvia Vieweg
- Department of Systems Physiology of Learning, Leibniz Institute for Neurobiology, 39118, Magdeburg, Germany
| | - Frank W Ohl
- Department of Systems Physiology of Learning, Leibniz Institute for Neurobiology, 39118, Magdeburg, Germany
- Center for Behavioral Brain Sciences (CBBS), 39106, Magdeburg, Germany
- Institute for Biology, Otto-von-Guericke-University, 39120, Magdeburg, Germany
| | - Michael T Lippert
- Department of Systems Physiology of Learning, Leibniz Institute for Neurobiology, 39118, Magdeburg, Germany
- Center for Behavioral Brain Sciences (CBBS), 39106, Magdeburg, Germany
| | - Max F K Happel
- Department of Systems Physiology of Learning, Leibniz Institute for Neurobiology, 39118, Magdeburg, Germany.
- Institute for Biology, Otto-von-Guericke-University, 39120, Magdeburg, Germany.
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58
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Koren V, Andrei AR, Hu M, Dragoi V, Obermayer K. Reading-out task variables as a low-dimensional reconstruction of neural spike trains in single trials. PLoS One 2019; 14:e0222649. [PMID: 31622346 PMCID: PMC6797168 DOI: 10.1371/journal.pone.0222649] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2019] [Accepted: 09/03/2019] [Indexed: 11/18/2022] Open
Abstract
We propose a new model of the read-out of spike trains that exploits the multivariate structure of responses of neural ensembles. Assuming the point of view of a read-out neuron that receives synaptic inputs from a population of projecting neurons, synaptic inputs are weighted with a heterogeneous set of weights. We propose that synaptic weights reflect the role of each neuron within the population for the computational task that the network has to solve. In our case, the computational task is discrimination of binary classes of stimuli, and weights are such as to maximize the discrimination capacity of the network. We compute synaptic weights as the feature weights of an optimal linear classifier. Once weights have been learned, they weight spike trains and allow to compute the post-synaptic current that modulates the spiking probability of the read-out unit in real time. We apply the model on parallel spike trains from V1 and V4 areas in the behaving monkey macaca mulatta, while the animal is engaged in a visual discrimination task with binary classes of stimuli. The read-out of spike trains with our model allows to discriminate the two classes of stimuli, while population PSTH entirely fails to do so. Splitting neurons in two subpopulations according to the sign of the weight, we show that population signals of the two functional subnetworks are negatively correlated. Disentangling the superficial, the middle and the deep layer of the cortex, we show that in both V1 and V4, superficial layers are the most important in discriminating binary classes of stimuli.
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Affiliation(s)
- Veronika Koren
- Neural Information Processing Group, Institute of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Germany
- * E-mail:
| | - Ariana R. Andrei
- Department of Neurobiology and Anatomy, University of Texas Medical School, Houston, Texas, United States of America
| | - Ming Hu
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Valentin Dragoi
- Department of Neurobiology and Anatomy, University of Texas Medical School, Houston, Texas, United States of America
| | - Klaus Obermayer
- Neural Information Processing Group, Institute of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Germany
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59
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Cadwell CR, Bhaduri A, Mostajo-Radji MA, Keefe MG, Nowakowski TJ. Development and Arealization of the Cerebral Cortex. Neuron 2019; 103:980-1004. [PMID: 31557462 PMCID: PMC9245854 DOI: 10.1016/j.neuron.2019.07.009] [Citation(s) in RCA: 249] [Impact Index Per Article: 41.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Revised: 05/15/2019] [Accepted: 07/03/2019] [Indexed: 12/16/2022]
Abstract
Adult cortical areas consist of specialized cell types and circuits that support unique higher-order cognitive functions. How this regional diversity develops from an initially uniform neuroepithelium has been the subject of decades of seminal research, and emerging technologies, including single-cell transcriptomics, provide a new perspective on area-specific molecular diversity. Here, we review the early developmental processes that underlie cortical arealization, including both cortex intrinsic and extrinsic mechanisms as embodied by the protomap and protocortex hypotheses, respectively. We propose an integrated model of serial homology whereby intrinsic genetic programs and local factors establish early transcriptomic differences between excitatory neurons destined to give rise to broad "proto-regions," and activity-dependent mechanisms lead to progressive refinement and formation of sharp boundaries between functional areas. Finally, we explore the potential of these basic developmental processes to inform our understanding of the emergence of functional neural networks and circuit abnormalities in neurodevelopmental disorders.
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Affiliation(s)
- Cathryn R Cadwell
- Department of Anatomic Pathology, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Aparna Bhaduri
- Department of Neurology, University of California, San Francisco, San Francisco, CA 94122, USA; The Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research at the University of California, San Francisco, San Francisco, CA 94143, USA
| | - Mohammed A Mostajo-Radji
- Department of Neurology, University of California, San Francisco, San Francisco, CA 94122, USA; The Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research at the University of California, San Francisco, San Francisco, CA 94143, USA
| | - Matthew G Keefe
- Developmental and Stem Cell Biology Graduate Program, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Anatomy, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Psychiatry, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Tomasz J Nowakowski
- The Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research at the University of California, San Francisco, San Francisco, CA 94143, USA; Department of Anatomy, University of California, San Francisco, San Francisco, CA 94143, USA; Department of Psychiatry, University of California, San Francisco, San Francisco, CA 94143, USA.
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60
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Abstract
Tactile sensory information from facial whiskers provides nocturnal tunnel-dwelling rodents, including mice and rats, with important spatial and textural information about their immediate surroundings. Whiskers are moved back and forth to scan the environment (whisking), and touch signals from each whisker evoke sparse patterns of neuronal activity in whisker-related primary somatosensory cortex (wS1; barrel cortex). Whisking is accompanied by desynchronized brain states and cell-type-specific changes in spontaneous and evoked neuronal activity. Tactile information, including object texture and location, appears to be computed in wS1 through integration of motor and sensory signals. wS1 also directly controls whisker movements and contributes to learned, whisker-dependent, goal-directed behaviours. The cell-type-specific neuronal circuitry in wS1 that contributes to whisker sensory perception is beginning to be defined.
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61
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Sikkens T, Bosman CA, Olcese U. The Role of Top-Down Modulation in Shaping Sensory Processing Across Brain States: Implications for Consciousness. Front Syst Neurosci 2019; 13:31. [PMID: 31680883 PMCID: PMC6802962 DOI: 10.3389/fnsys.2019.00031] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Accepted: 07/05/2019] [Indexed: 11/24/2022] Open
Abstract
Top-down, feedback projections account for a large portion of all connections between neurons in the thalamocortical system, yet their precise role remains the subject of much discussion. A large number of studies has focused on investigating how sensory information is transformed across hierarchically-distributed processing stages in a feedforward fashion, and computational models have shown that purely feedforward artificial neural networks can even outperform humans in pattern classification tasks. What is then the functional role of feedback connections? Several key roles have been identified, ranging from attentional modulation to, crucially, conscious perception. Specifically, most of the major theories on consciousness postulate that feedback connections would play an essential role in enabling sensory information to be consciously perceived. Consequently, it follows that their efficacy in modulating target regions should drastically decrease in nonconscious brain states [non-rapid eye movement (REM) sleep, anesthesia] compared to conscious ones (wakefulness), and also in instances when a given sensory stimulus is not perceived compared to when it is. Until recently, however, this prediction could only be tested with correlative experiments, due to the lack of techniques to selectively manipulate and measure the activity of feedback pathways. In this article, we will review the most recent literature on the functions of feedback connections across brain states and based on the presence or absence of perception. We will focus on experiments studying mismatch negativity, a phenomenon which has been hypothesized to rely on top-down modulation but which persists during nonconscious states. While feedback modulation is generally dampened in nonconscious states and enhanced when perception occurs, there are clear deviations from this rule. As we will discuss, this may pose a challenge to most theories of consciousness, and possibly require a change in how the level of consciousness in supposedly nonconscious states is assessed.
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Affiliation(s)
- Tom Sikkens
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands.,Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Conrado A Bosman
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands.,Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Umberto Olcese
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands.,Research Priority Area Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
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