DOI: 10.5061/dryad.tqjq2bw9n
title: Data from: Remote activation of place codes by gaze in a highly visual animal

description: Vision enables many animals to perform spatial reasoning from remote
 locations. By viewing distant landmarks, animals recall spatial memories
 and plan future trajectories. Although these spatial functions depend on
 hippocampal place cells, the relationship between place cells and active
 visual behavior is unknown. Here, we studied a highly visual animal, the
 chickadee, in a behavior that required alternating between remote visual
 search and spatial navigation. We leveraged the head-directed nature of
 avian vision to track gaze in freely moving animals. We discovered a
 profound link between place coding and gaze. Place cells activated not
 only when the chickadee was in a specific location, but also when it
 simply gazed at that location from a distance. Gaze coding was precisely
 timed by fast, ballistic head movements called “head saccades”. On each
 saccadic cycle, the hippocampus switched between encoding a prediction of
 what the bird was about to see and a reaction to what it actually saw. The
 temporal structure of these responses was coordinated by subclasses of
 interneurons that fired at different phases of the saccade. We suggest
 that place and gaze coding are components of a unified process by which
 the hippocampus represents the location that is currently relevant to the
 animal. This process allows the hippocampus to implement both local and
 remote spatial functions. This dataset includes spike sorted data from all
 cells in the paper, as well as behavioral data from the corresponding
 sessions. 
description: # Data from: Remote activation of place codes by gaze in a highly visual
 animal Dataset DOI: [10.5061/dryad.tqjq2bw9n](10.5061/dryad.tqjq2bw9n) ##
 Description of the data and file structure Parameters, behavioral, and
 neural data are given for each session in the paper. See Payne &
 Aronov 2025 for methodological details.  ### Files and variables Data is
 included in the "data" folder. Files are stored in MATLAB (.mat)
 format. #### SESSIONS.xlsx Excel spreadsheet containing information for
 each experimental recording session. #### SURGERY.xlsx Excel spreadsheet
 containing information for each probe implant. #### Session folders In the
 format `BIRD_YYMMDD` ##### params.mat Parameters for this session.
 **`P_expmt`**: parameters stored during the experiment. Key parameters
 useful for analysis are: `task`: task type `track_type`: type of gaze used
 to trigger sites `p_feeders`: locations of feeders and other session
 parameters. `r_gaze`: gaze radius to trigger sites **`P_calib`**: position
 and vectors of eye relative to head reference frame `v_eye_R_head`: vector
 of the R eye relative to the head `v_eye_L_head`: vector of the L eye
 relative to the head `p_eye_R_head`: position of the R eye relative to the
 head `p_eye_L_head`: position of the L eye relative to the head
 `p_beak_head`: position of the beak tip relative to the head Coordinates
 are given in the form [x,y,z], with the origin at the midpoint of the two
 eyes, the x axis pointing forward along the beak, the y axis pointing
 towards the left eye (but orthogonal to the x axis), and the z axis
 pointing up. **`P_hmm`**: parameters for hidden markov model
 classification of behavioral states. Key parameters useful for analysis
 are: `state_text`: description of each of the states in `state_id`
 `types`: state types used for catergorization. "node" =
 fixations, "saccade" = saccades, "feed" = feeding,
 "edge" = dashing. **`fps`**: frames per second of the behavioral
 data. ##### behavior.mat Note: due to occasional gaps in tracking, the
 average frame rate is not equal to the mean difference in timestamps. For
 the frame rate, use variable `fps` in params.mat, calculated by removing
 long gaps in tt. `tt`: [ntx1] time stamp for each behavior frame, as
 recorded in neural recording software. Use to align to spike data
 `p_head`: [3×nt] head position relative to the arena. `R_head`: [3×3×nt]
 head orientation relative to the arena. Axes are as described in P_beh
 `lin_speed`: [nt×1] linear head speed. Calculated by taking the
 frame-by-frame difference in 3D head position, then smoothed with a
 lowpass Butterworth filter with 25 Hz cutoff frequency. `ang_speed`:
 [ntx1] angular head speed. Calculated by taking the frame-by-frame
 difference in 3D head angle, then smoothed with a lowpass Butterworth
 filter with 25 Hz cutoff frequency. `state_id`: [ntx1] states categorized
 by hidden Markov model algorithm. Refer to labels in params.mat #####
 behavior\_hmm.mat `T_sac`: table of detected gaze saccades `T_fix`: table
 of detected gaze fixations `T_dash`: table of detected dashes `T_feed`:
 table of detected feeding periods ##### events.mat `M`: table of event
 times (`time`) and indices (`ind`, closest index into tt in behavior.mat)
 and what happened (`light` = light state changed, `motor` = motor state
 changed). A number from 1 to 5 indicates which site was opened or turned
 on. A 0 indicates that all sites were closed or turned off. Sites arranged
 as in variable `p_feeders` in params.mat. ##### spikes.mat Structure array
 containing spike data for each hippocampal cell included in the paper
 `data`: spike times `chanlabel`: name of the cell, including session name
 and cell ID `chanval`: channel on which the spike was recorded with max
 amplitude `samplerate`: "event", indicating this is event rather
 than continuous data `tstart`: time of first spike `tend`: time of last
 spike `units`: seconds `wavemark`: unit ID given by kilosort 2.0
 `waveform`: waveform on max channel `info`: additional information ##
 Code/software Example MATLAB code is given in the "code"
 folder.  Edit `RUNME.m` so the `data_dir` variable points to where the
 data is stored on your computer. Change directories to the
 "code" folder. Run `RUNME.m`. Edit to plot results for different
 example cells.