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2 Janelia Publications

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    Darshan Lab
    09/02/19 | Idiosyncratic choice bias in decision tasks naturally emerges from neuronal network dynamics.
    Lebovich L, Darshan R, Lavi Y, Hansel D, Loewenstein Y
    Nature Human Behavior. 2019 Sep 02;3(11):1190-1202. doi: 10.1101/284877

    Idiosyncratic tendency to choose one alternative over others in the absence of an identified reason, is a common observation in two-alternative forced-choice experiments. It is tempting to account for it as resulting from the (unknown) participant-specific history and thus treat it as a measurement noise. Indeed, idiosyncratic choice biases are typically considered as nuisance. Care is taken to account for them by adding an ad-hoc bias parameter or by counterbalancing the choices to average them out. Here we quantify idiosyncratic choice biases in a perceptual discrimination task and a motor task. We report substantial and significant biases in both cases. Then, we present theoretical evidence that even in idealized experiments, in which the settings are symmetric, idiosyncratic choice bias is expected to emerge from the dynamics of competing neuronal networks. We thus argue that idiosyncratic choice bias reflects the microscopic dynamics of choice and therefore is virtually inevitable in any comparison or decision task.

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    09/02/19 | Software for lattice light-sheet imaging of FRET biosensors, illustrated with a new Rap1 biosensor.
    O’Shaughnessy EC, Stone OJ, LaFosse PK, Azoitei ML, Tsygankov D, Heddleston JM, Legant WR, Wittchen ES, Burridge K, Elston TC, Betzig E, Chew T, Adalsteinsson D, Hahn KM
    The Journal of Cell Biology. 2019 Sep 2;218(9):3153-3160. doi: 10.1083/jcb.201903019

    Lattice light-sheet microscopy (LLSM) is valuable for its combination of reduced photobleaching and outstanding spatiotemporal resolution in 3D. Using LLSM to image biosensors in living cells could provide unprecedented visualization of rapid, localized changes in protein conformation or posttranslational modification. However, computational manipulations required for biosensor imaging with LLSM are challenging for many software packages. The calculations require processing large amounts of data even for simple changes such as reorientation of cell renderings or testing the effects of user-selectable settings, and lattice imaging poses unique challenges in thresholding and ratio imaging. We describe here a new software package, named ImageTank, that is specifically designed for practical imaging of biosensors using LLSM. To demonstrate its capabilities, we use a new biosensor to study the rapid 3D dynamics of the small GTPase Rap1 in vesicles and cell protrusions.

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