DOI: 10.5061/dryad.cnp5hqc4k
title: Dendritic calcium signals in rhesus macaque motor cortex drive an optical brain-computer interface

description: Calcium imaging has rapidly developed into a powerful tool for recording
 from large populations of neurons in vivo. Imaging in rhesus macaque motor
 cortex can enable the discovery of new principles of motor cortical
 function and can inform the design of next generation brain-computer
 interfaces (BCIs). Surface two-photon (2P) imaging, however, cannot
 presently access somatic calcium signals of neurons from all layers of
 macaque motor cortex due to photon scattering. Here, we demonstrate an
 implant and imaging system capable of chronic, motion-stabilized
 two-photon (2P) imaging of calcium signals from in macaques engaged in a
 motor task. By imaging apical dendrites, some of which originated from
 deep layer 5 neurons, as well as superficial cell bodies, we achieved
 optical access to large populations of deep and superficial cortical
 neurons across dorsal premotor (PMd) and gyral primary motor (M1)
 cortices. Dendritic signals from individual neurons displayed tuning for
 different directions of arm movement, which was stable across many weeks.
 Combining several technical advances, we developed an optical BCI (oBCI)
 driven by these dendritic signals and successfully decoded movement
 direction online. By fusing 2P functional imaging with CLARITY volumetric
 imaging, we verify that an imaged dendrite, which contributed to oBCI
 decoding, originated from a putative Betz cell in motor cortical layer 5.
 This approach establishes new opportunities for studying motor control and
 designing BCIs.
description: A complete write up of the data collection and analysis may be
 found in the Methods section of the publication.
 Imaging was performed using a Bruker Ultima <em>in vivo
 </em>microscope with a custom motorized orbital nosepiece (Bruker
 Inc.) to provide off-axis imaging with a Nikon 16x 0.8 NA objective lens.
 Images were acquired at 512 x 512 resolution at a single depth at 30.3Hz
 using resonant-scanning galvanometers (or occasionally at lower resolution
 and higher framerate while imaging a portion of the 512 x 512 pixel
 field). Laser power was adjusted as necessary to optimize SNR prior to
 each recording series and typical values were between 50-150mW. Using
 dichroic beam splitter (555 nm) and a pair of filters, we collected both a
 functional green channel (520/44 nm) and a static red fluorescent channel
 (624/40 nm) to facilitate registration. Typical
 sessions in which the subject was working in the imaging rig lasted
 between 90-180 minutes. Imaging was performed during decode blocks,
 typically lasting between 5-30 minutes, and different decoding sessions
 were performed in different fields of view during a single session in
 order to explore different injection sites and depths. We typically
 performed imaging (while the monkey was at rest and not performing the
 task) for several minutes in between decode blocks to localize distinct
 fields of view with neural features, or to localize an imaging field of
 view based on the surface vasculature. We did not observe photobleaching
 over the course of a decode block or across blocks within a session in the
 same region. 2P imaging sessions were collected over
 sessions spanning the following number of days in the three subjects
 included here: monkey S, 122 days; monkey W, 30 days; monkey X, 144 days.
 We note that for all three subjects, degradation of imaging quality was
 not a driver for terminating experiments, and imaging data were collected
 until we had sufficient data within the imageable injection regions. In
 particular, for monkey W, imaging quality remained excellent but as we did
 not observe functional tuning in the neurons we imaged, we did not
 continue to collect data beyond the first month of exploration after
 observing virus expression. The positioning of the
 imaging plane for each decode session was chosen to maximize the number of
 modulated processes observed in the field of view. We did not attempt to
 optimize correspondence of the imaging field of view across
 sessions. We processed each imaging
 session offline using Suite2P (https://github.com/MouseLand/suite2p) and analyzed 36 imaging decode sessions collected on eight days. Imaging datasets were aligned using the red, static fluorescence channel using a rigid coarse alignment step followed by a non-rigid block-wise alignment step. Standard settings for the algorithm were used with the following exceptions to optimize for dendritic ROIs and GCaMP6f (connected=False, tau=0.7). We identified putative dendritic/axonal ROIs in the datasets as those ROIs with a computed aspect ratio greater than 2 (ratio of long axis to short axis of ROI shape) and manually verified that this selection criterion identified only ROIs that appeared to be neuronal processes.
description: This DRYAD dataset contains two photon calcium imaging data
 accompanying the 2021 manuscript "Dendritic calcium signals in rhesus
 macaque motor cortex drive an optical brain-computer interface" by
 Trautmann, O'Shea, Sun et al., to be published in Nature
 Communications. The dataset was assembled by Dan
 O'Shea (djoshea at stanford). Data may be loaded in MATLAB without
 any accompanying software.
 aggregated_roi_stats <em>This contains
 a Matlab table of analysis on ROIs aggregated from all 36 imaging
 datasets.</em> dataset: to which session does
 each ROI belong roiInd: index of ROI within that
 session best_move_zscore (best_target_zscore,
 best_go_zscore): zscore value with largest absolute value over time for
 each ROIs Z-scored peri-movement (post target onset, post go cue)
 responses pval_move_ranksum (pval_target_ranksum,
 pval_go_ranksum): p value from rank sum test comparing pre-movement to
 peri-movement (post target onset, post go cue) responses, for detecting a
 significant response during movement (post target onset, post go
 cue) pval_tuning_anova : p value for ANOVA for a fixed
 effect of reach direction on peri-movement responses, for detecting
 significantly tuned responses aspect_ratio : related to
 ROI geometry from Suite2P, ratio between major and minor axes of a 2D
 Gaussian fit to mask<br>Is_neural_process : considered to be a
 putative dendritic / axonal process in analysis
 npixTotal : number of pixels in overall ROI mask
 npixDominant: number of pixels where this ROI is given the
 greatest weight of all ROIs that a given pixel contributes to
 beta : x and y beta coefficients for each ROIs velocity tuning
 regression r : r-squared statistic for the velocity
 tuning regression  p :  p value for the F-test for the
 velocity tuning regression theta : preferred movement
 direction from cosine tuning curve amp : amplitude of
 ROI tuning curve cmap : RGB color associated with each
 ROI for plotting preferred direction in a cyclic color map (colorcet
 CET-C2). delta_tuning_early_late : change in preferred
 direction angle for the last 25% of the session relative to the first 25%
 of the session. pval_tuning_changed : p value
 associated with a bootstrap test for significant drift in preferred
 direction across the session pixel_theta_rel_roi :
 preferred direction angle of each pixel in the ROI individually, relative
 to the preferred direction of the cluster pixel_beta :
 x and y beta regression coefficients for each pixel in the ROI
 individually pixel_optimal_clusters : optimal number of
 pixel-wise subclusters within each ROI. (Computed for reviewer
 request). tseries_metadata
 <em>This contains a collection of metadata saved by Prairie
 regarding the imaging timeseries collection
 parameters.</em> response_data
 stat : ROI statistics computed by Suite2P and described here [
 https://suite2p.readthedocs.io/en/latest/outputs.html#stat-npy-fields
 ]. dfof, dfof_tvec_ms : ΔF/F responses of each ROI vs
 image frames, and time vector in ms meanImg, meanImgLog
 : session-mean image (and log-transformed mean image)
 x/y_um_per_pixel: scale factors associated with each image (to
 microns) mask_dendrite, mask_responsive, mask_tuned :
 indicates which ROIs were considered putative dendrites, responsive to
 movement, and tuned to movement direction
 move_response_tensor, move_response_tvec : 4 reach direction
 conditions x time x ROIs array of trial-averaged ROI responses during
 reaching movements as a function of target direction (equivalent to a
 peri-movement PSTH). Time vector is in ms relative to movement
 onset.