DOI: 10.5061/dryad.xd2547dkd
title: Calcium imaging in visual cortex during fidget behaviors in mice

description: Multiple recent studies have shown that motor activity greatly impacts the
 activity of primary sensory areas like V1. Yet, the role of this motor
 related activity in sensory processing is still unclear.  Here we
 dissect how these behavior signals are broadcast to different layers and
 areas of the visual cortex. To do so, we leveraged a standardized and
 spontaneous behavioral fidget event in passively viewing mice.
 Importantly, this behavior event had no relevance to any ongoing task
 allowing us to compare its neuronal correlates with visually relevant
 behaviors (e.g running).  A large two-photon Ca2+ imaging
 database of neuronal responses uncovered four neural response types during
 fidgets that were consistent in their proportion and response patterns
 across all visual areas and layers of the visual cortex. Indeed, the layer
 and area identity could not be decoded above chance level based only on
 neuronal recordings. In contrast to running behavior, fidget evoked neural
 responses that were independent to visual processing.  The broad
 availability of visually orthogonal standardized behavior signals could be
 a key component in how the cortex selects, learns and binds local sensory
 information with motor outputs. Contrary to behaviorally relevant motor
 outputs, irrelevant motor signals could project to separate local neural
 subspaces.
description: This dataset is a collection of fidget aligned neural events
 collected from large scale calcium imaging in the mouse brain.
 <strong>Transgenic mice</strong> All animal
 procedures were approved by the Institutional Animal Care and Use
 Committee (IACUC) at the Allen Institute for Brain Science. Triple
 transgenic mice (Ai93, tTA, Cre) were generated by first crossing Ai93
 mice with Camk2a-tTA mice, which preferentially express tTA in forebrain
 excitatory neurons. Double transgenic mice were then crossed with a Cre
 driver line to generate mice in which GCaMP6f expression is induced in the
 specific populations of neurons that express both Cre and tTA.
 Rorb-IRES2-Cre;Cam2a-tTA;Ai93 (n=10) exhibit
 GCaMP6f in excitatory neurons in cortical layer 4 (dense patches) and
 layers 5,6 (sparse). Cux2-CreERT2;Camk2a-tTA;Ai93 (n=16) expression is
 regulated by the tamoxifen-inducible Cux2 promoter, induction of which
 results in Cre-mediated expression of GCaMP6f predominantly in superficial
 cortical layers 2, 3 and 4. Slc17a7-IRES2-Cre;Camk2a-tTA;Ai93 (n=2) is a
 pan-excitatory line and shows expression throughout all cortical layers.
 Scnn1a-Tg3-Cre;Camk2a-tTA;Ai93 (n=5) exhibit GCaMP6f in excitatory neurons
 in cortical layer 4 and in restricted areas within the cortex, in
 particular primary sensory cortices. Nr5a1-Cre;Camk2a-tTA;Ai93 (n=1)
 exhibit GCaMP6f in excitatory neurons in cortical layer 4.
 Rbp4-Cre;Camk2a-tTA;Ai93 (n=11) exhibit GCaMP6f in excitatory neurons in
 cortical layer 5. Ntsr1-Cre_GN220;Ai148 (n=1) exhibit CaMP6f in excitatory
 corticothalamic neurons in cortical layer 6. 
 <strong>Animal
 head-implants and cortical window implantation</strong>
 Transgenic mice expressing GCaMP6f were
 weaned and genotyped at ~p21, and surgery was performed between p37 and
 p63. Surgical protocols were described in previous publications associated
 with the two-photon datasets4. <strong>Intrinsic imaging and mapping of the visual cortex</strong> Retinotopic mapping was used to delineate functionally defined visual area boundaries and enable targeting of the in vivo two-photon calcium imaging to retinotopically defined locations in primary and secondary visual areas. Retinotopic mapping protocols were described in previous publications associated with the two-photon datasets4. <strong>In vivo two-photon chronic imaging</strong> Calcium imaging was performed using a two-photon-imaging instrument, Nikon A1R MP+. The Nikon system was adapted to provide space to accommodate the behavior apparatus). Laser excitation was provided by a Ti:Sapphire laser (ChameleonVision – Coherent) at 910 nm. Pre-compensation was set at ~10,000 fs2. Movies were recorded at 30Hz using resonant scanners over a 400 μm field of view. Mice were head-fixed on top of a rotating disk and free to walk at will. The disk was covered with a layer of removable foam (Super-Resilient Foam, 86375K242, McMaster) to alleviate motion-induced artifacts during imaging sessions. An experiment container consisted of three imaging sessions (60 min each) at a given field of view during which mice passively observed three different stimuli. The same location was targeted for imaging on all three recording days to allow repeat comparison of the same neurons across sessions. One imaging session was performed per day, for a maximum of 16 sessions for each mouse. On the first day of imaging at a new field of view, the ISI targeting map was used to select spatial coordinates. A comparison of surface vasculature patterns was used to verify the appropriate location by imaging over a field of view of ~800 μm using epi-fluorescence and blue light illumination. Once a cortical region was selected, the imaging objective was shrouded from stray light from the stimulus screen using opaque black tape. In two-photon imaging mode, the desired depth of imaging was set to record from a specific cortical depth. On subsequent imaging days, we returned to the same location by matching (1) the pattern of vessels in epi-fluorescence with (2) the pattern of vessels in two photon imaging and (3) the pattern of cellular labelling in two photon imaging at the previously recorded location. Calcium imaging data was collected at the four cortical depths of 175, 275, 350 and 375 micrometers. Throughout our analysis, data from the cortical depth of 175 micrometers were classified as layer 2/3, 275 and 350 micrometers as layer 4, and 375 as layer 5. <strong>Processing of two-photon calcium imaging movies</strong> For each two-photon imaging session, the image processing pipeline performed: (1) spatial or temporal calibration, (2) motion correction, (3) image normalization to minimize confounding random variations between sessions, (4) segmentation of connected shapes and (5) classification of soma-like shapes from remaining clutter. The motion correction algorithm relied on phase correlation and only corrected for rigid translational errors. Each movie was partitioned into 400 consecutive frame blocks, representing 13.3 s of video. Each block was registered iteratively to its own average three times. A second stage of registration integrated the periodic average frames themselves into a single global average frame through six additional iterations. The global average frame served as the reference image for the final resampling of every raw frame in the video. Fluorescence movies were processed using a segmentation algorithm to identify somatic regions of interest (ROIs) that was described previously2. Segmented ROIs were matched across imaging sessions. For each ROI, events were detected from ΔF/F by using an L0-regularized algorithm. For each neuron, we z-score ΔF/F trial activity and compute the mean z-scored response of each neuron aligned to the time of fidget onset (0 seconds). To determine the significance of neural activity modulation post-fidget, we apply several threshold criteria to clustered neuronal activity. The threshold criteria were used in previous calcium imaging literature, and here we present two that gave very different results: One criteria where the mean ΔF/F is larger than 6%, and one criteria where the maximum ΔF/F during the post-fidget period is greater than 5%. <strong>Fidget neuronal response analysis</strong> Neural responses were aligned to the onset of the fidget behavior and cropped to keep 100 frames (~ 3 seconds) preceding the initiation of the fidget and 200 frames (~ 6 seconds) post fidget initiation. Neural activity was normalized on a trial-by-trial basis by subtracting the mean activity of the 100 frames (~3 seconds) of baseline neural activity preceding the initiation of the fidget response and dividing by the standard deviation of activity. Across trial z-scored neural activity was then averaged to get the mean z-scored activity for each neuron.
description: Matlab and/or Python are needed to open data. This data
 submission includes 144 mat files. They can be accessed with the matlab or
 python function "load". Files are named
 Fidget_Fluorescence_XXXXXXXX.mat where XXXXXXXX represents the session
 number.