@article {47218, title = {OpenStage: a low-cost motorized microscope stage with sub-micron positioning accuracy.}, journal = {PloS One}, volume = {9}, year = {2014}, month = {2014 Feb 26}, pages = {e88977}, abstract = {

Recent progress in intracellular calcium sensors and other fluorophores has promoted the widespread adoption of functional optical imaging in the life sciences. Home-built multiphoton microscopes are easy to build, highly customizable, and cost effective. For many imaging applications a 3-axis motorized stage is critical, but commercially available motorization hardware (motorized translators, controller boxes, etc) are often very expensive. Furthermore, the firmware on commercial motor controllers cannot easily be altered and is not usually designed with a microscope stage in mind. Here we describe an open-source motorization solution that is simple to construct, yet far cheaper and more customizable than commercial offerings. The cost of the controller and motorization hardware are under $1000. Hardware costs are kept low by replacing linear actuators with high quality stepper motors. Electronics are assembled from commonly available hobby components, which are easy to work with. Here we describe assembly of the system and quantify the positioning accuracy of all three axes. We obtain positioning repeatability of the order of 1 μm in X/Y and 0.1 μm in Z. A hand-held control-pad allows the user to direct stage motion precisely over a wide range of speeds (10(-1) to 10(2) μm{\textperiodcentered}s(-1)), rapidly store and return to different locations, and execute "jumps" of a fixed size. In addition, the system can be controlled from a PC serial port. Our "OpenStage" controller is sufficiently flexible that it could be used to drive other devices, such as micro-manipulators, with minimal modifications.

}, keywords = {Costs and Cost Analysis, Equipment Design, Microscopy, Reproducibility of Results}, issn = {1932-6203}, doi = {10.1371/journal.pone.0088977}, author = {Campbell, Robert A A and Eifert, Robert W and Turner, Glenn C} } @article {47220, title = {Imaging a population code for odor identity in the Drosophila mushroom body.}, journal = {The Journal of Neuroscience : the official journal of the Society for Neuroscience}, volume = {33}, year = {2013}, month = {2013 Jun 19}, pages = {10568-81}, abstract = {

The brain represents sensory information in the coordinated activity of neuronal ensembles. Although the microcircuits underlying olfactory processing are well characterized in Drosophila, no studies to date have examined the encoding of odor identity by populations of neurons and related it to the odor specificity of olfactory behavior. Here we used two-photon Ca(2+) imaging to record odor-evoked responses from \>100 neurons simultaneously in the Drosophila mushroom body (MB). For the first time, we demonstrate quantitatively that MB population responses contain substantial information on odor identity. Using a series of increasingly similar odor blends, we identified conditions in which odor discrimination is difficult behaviorally. We found that MB ensemble responses accounted well for olfactory acuity in this task. Kenyon cell ensembles with as few as 25 cells were sufficient to match behavioral discrimination accuracy. Using a generalization task, we demonstrated that the MB population code could predict the flies{\textquoteright} responses to novel odors. The degree to which flies generalized a learned aversive association to unfamiliar test odors depended upon the relative similarity between the odors{\textquoteright} evoked MB activity patterns. Discrimination and generalization place different demands on the animal, yet the flies{\textquoteright} choices in these tasks were reliably predicted based on the amount of overlap between MB activity patterns. Therefore, these different behaviors can be understood in the context of a single physiological framework.

}, keywords = {Animals, Calcium, Discrimination (Psychology), Drosophila, Generalization (Psychology), Image Processing, Computer-Assisted, Learning, Linear Models, Mushroom Bodies, Neuroimaging, Odors, Olfactory Pathways, Olfactory Perception, Psychomotor Performance, Synaptic Transmission}, issn = {1529-2401}, doi = {10.1523/JNEUROSCI.0682-12.2013}, author = {Campbell, Robert A A and Honegger, Kyle S and Qin, Hongtao and Li, Wanhe and Demir, Ebru and Turner, Glenn C} } @article {47221, title = {Cellular-resolution population imaging reveals robust sparse coding in the Drosophila mushroom body.}, journal = {The Journal of Neuroscience : the official journal of the Society for Neuroscience}, volume = {31}, year = {2011}, month = {2011 Aug 17}, pages = {11772-85}, abstract = {

Sensory stimuli are represented in the brain by the activity of populations of neurons. In most biological systems, studying population coding is challenging since only a tiny proportion of cells can be recorded simultaneously. Here we used two-photon imaging to record neural activity in the relatively simple Drosophila mushroom body (MB), an area involved in olfactory learning and memory. Using the highly sensitive calcium indicator GCaMP3, we simultaneously monitored the activity of \>100 MB neurons in vivo (\~{}5\% of the total population). The MB is thought to encode odors in sparse patterns of activity, but the code has yet to be explored either on a population level or with a wide variety of stimuli. We therefore imaged responses to odors chosen to evaluate the robustness of sparse representations. Different odors activated distinct patterns of MB neurons; however, we found no evidence for spatial organization of neurons by either response probability or odor tuning within the cell body layer. The degree of sparseness was consistent across a wide range of stimuli, from monomolecular odors to artificial blends and even complex natural smells. Sparseness was mainly invariant across concentrations, largely because of the influence of recent odor experience. Finally, in contrast to sensory processing in other systems, no response features distinguished natural stimuli from monomolecular odors. Our results indicate that the fundamental feature of odor processing in the MB is to create sparse stimulus representations in a format that facilitates arbitrary associations between odor and punishment or reward.

}, keywords = {Animals, Animals, Genetically Modified, Diagnostic Imaging, Drosophila, Microscopy, Fluorescence, Multiphoton, Mushroom Bodies, Odors, Olfactory Pathways, Olfactory Receptor Neurons, Random Allocation, Smell}, issn = {1529-2401}, doi = {10.1523/JNEUROSCI.1099-11.2011}, author = {Honegger, Kyle S and Campbell, Robert A A and Turner, Glenn C} } @article {47227, title = {The mushroom body (Quick guide.)}, journal = {Current Biology : CB}, volume = {20}, year = {2010}, month = {2010 Jan 12}, pages = {R11-2}, doi = {10.1016/j.cub.2009.10.031}, author = {Campbell, Robert A A and Turner, Glenn C} }