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2 Janelia Publications

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    07/29/19 | Kilohertz frame-rate two-photon tomography.
    Kazemipour A, Novak O, Flickinger D, Marvin JS, Abdelfattah AS, King J, Borden P, Kim J, Al-Abdullatif S, Deal P, Miller E, Schreiter E, Druckmann S, Svoboda K, Looger L, Podgorski K
    Nature Methods. 2019 Jul 29;16(8):778-86. doi: 10.1101/357269

    Point-scanning two-photon microscopy enables high-resolution imaging within scattering specimens such as the mammalian brain, but sequential acquisition of voxels fundamentally limits imaging speed. We developed a two-photon imaging technique that scans lines of excitation across a focal plane at multiple angles and uses prior information to recover high-resolution images at over 1.4 billion voxels per second. Using a structural image as a prior for recording neural activity, we imaged visually-evoked and spontaneous glutamate release across hundreds of dendritic spines in mice at depths over 250 microns and frame-rates over 1 kHz. Dendritic glutamate transients in anaesthetized mice are synchronized within spatially-contiguous domains spanning tens of microns at frequencies ranging from 1-100 Hz. We demonstrate high-speed recording of acetylcholine and calcium sensors, 3D single-particle tracking, and imaging in densely-labeled cortex. Our method surpasses limits on the speed of raster-scanned imaging imposed by fluorescence lifetime.

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    Svoboda LabDruckmann LabScientific Computing Software
    01/15/19 | An orderly single-trial organization of population dynamics in premotor cortex predicts behavioral variability.
    Wei Z, Inagaki H, Li N, Svoboda K, Druckmann S
    Nature Communications. 2019 Jan 15;10(1):216. doi: 10.1038/s41467-018-08141-6

    Animals are not simple input-output machines. Their responses to even very similar stimuli are variable. A key, long-standing question in neuroscience is to understand the neural correlates of such behavioral variability. To reveal these correlates, behavior and neural population activity must be related to one another on single trials. Such analysis is challenging due to the dynamical nature of brain function (e.g., in decision making), heterogeneity across neurons and limited sampling of the relevant neural population. By analyzing population recordings from mouse frontal cortex in perceptual decision-making tasks, we show that an analysis approach tailored to the coarse grain features of the dynamics is able to reveal previously unrecognized structure in the organization of population activity. This structure is similar on error and correct trials, suggesting dynamics that may be constrained by the underlying circuitry, is able to predict multiple aspects of behavioral variability and reveals long time-scale modulation of population activity.

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