Compressive Light Field microscopy for optogenetic neural activity tracking
Compressive Light Field microscopy for optogenetic neural activity tracking
批准号:
9244514
负责人:
Laura Waller
金额:
$22.47万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-09-30 至 2018-07-31
关键词:
AlgorithmsAnimal ModelAnimalsAreaBRAIN initiativeBackBehaviorBrainBrain imagingCerebrumCognitionCommunitiesDataData AnalysesDevicesElectrodesFour-dimensionalFunctional ImagingGoalsHeadImageImaging TechniquesImaging technologyIndividualLifeLightMachine LearningMapsMeasurementMeasuresMediatingMethodologyMethodsMicroscopeMicroscopyModelingMusNeuronsNeurosciencesPathway interactionsPerceptionPhasePhotonsPopulationPositioning AttributeProcessRecords ControlsResolutionSamplingSchemeSensorySideSignal TransductionSpecimenSpeedSystemTechniquesTechnologyTestingTimeTissuesWorkawakebrain tissuebrain volumecostdensitydesigndetectorimage reconstructionimaging modalityimaging systemin vivolight emissionlight scatteringneural patterningneurophysiologynovelnovel strategiesoperationoptical imagingoptogeneticsreconstructionrelating to nervous systemresearch studyscale upsensortemporal measurementtooltwo-photon
中文摘要
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英文摘要
SUMMARY: Understanding the mechanisms by which the living brain derives perception, cognition and behavior
requires the ability to record and control electrical activity in many neurons simultaneously. Completely
reconstructing the pattern of neural activity that mediates a specific neural operation is critical for fully
understanding its underlying mechanism. This requires an approach that can measure neural activity on a large
scale with high spatial and temporal resolution. Functional imaging of genetically encoded activity sensors is one
of the most promising avenues towards achieving this goal because it permits dense sampling and unambiguous
separation of nearby neurons1, 2. However, even techniques currently available cannot capture neural activity in
large volumes of the brain simultaneously, at high speed, and with cellular resolution. Furthermore, these existing
approaches rely on expensive and sophisticated hardware, and cannot be readily adapted for imaging in
unrestrained animals. Since a central goal of the BRAIN initiative is to achieve large-scale recording of neural
activity in behaving animals, a new imaging approach is needed to overcome these technical challenges.
To achieve high speed, volumetric imaging in a compact and inexpensive device, we propose to develop
a new imaging modality - compressive four-dimensional (4D) light field microscopy (LFM). In this approach, we
will combine the advantages of light field microscopy with compressed sensing to extract the activity of
thousands of individual neurons with high spatial and temporal resolution, through scattering tissue. In
conventional microscopy, the photo-detector only samples the intensity of photons. In LFM, the sensor also
captures the angle of the light. This allows 3D reconstruction, since position and angle enable back-tracing of
rays of light. Such a scheme can be achieved simply by placing a lenslet array in the imaging pathway (Fig. 1A).
The resulting 4D light field gives complete volumetric data at each time frame3-6. 3D activity can thus be sampled
at camera-limited frame rates, much faster than conventional methods such as multiphoton or light sheet
microscopy. For these reasons, LFM for functional brain imaging could revolutionize experimental neuroscience.
Unfortunately, imaging methods which operate in the one-photon regime suffer from light scattering. To
image activity in the mammalian brain, we must consider the effects of tissue scattering through the 3D volume.
We propose to apply a new approach to processing light field data for better reconstructions of neurons through
scattering media37,38. Since the effect of scattering is to spread the angles of propagation of light, measuring
angle information inherently helps to characterize and mitigate scatter effects. Our method leverages
compressed sensing algorithms, which exploit the sparsity of the light emission in 3D space and time.
Importantly, the volume and resolution limits of our method are not set by the number of pixels captured, but
rather by the number of active neurons at any given time. Thus, we will be able to localize and measure the
activity of thousands or millions of individually active neurons in large volumes of cerebral cortical tissue.
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