iCube data visually impaired

Here, I report the codebook of the dataset for the variable names that are harder to interpret:

group: 'early-blind', 'late-blind' or 'control'

main_group: 'blind' or 'sighted'

trial_type: 'memorize' or 'recall'

conf: the configuration of pins locations used in the specific trial

subject_orientation: oreintation of the subject in absolute coordinates while doing the test (e.g. 'north' if facing North)

pin_facet_1: number of pins in facet 1

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pin_facet_6: number of pins in facet 6

cond_facet_1: kind of face based on pin number (even or odd)

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cond_facet_6: kind of face based on pin number (even or odd)

correct: correct response (i.e. 'same' or 'different') for that trial

response: actual response of the subject

accuracy: 1 = correct; 0 = wrong

n_tocchi_trial = number (unfiltered) of active cells of the cube in the whole trial

n_tocchi_facet_1 = number (unfiltered) of active cells in face #1 of the cube in the whole trial

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n_tocchi_facet_6 = number (unfiltered) of active cells in face #6 of the cube in the whole trial

filt_n_tocchi_trial = number (filtered, i.e., explorative touches only) of active cells of the cube in the whole trial

filt_n_tocchi_facet_1 = number (filtered, i.e., explorative touches only) of active cells in face#1 of the cube in the whole trial

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filt_n_tocchi_facet_6 = number (filtered, i.e., explorative touches only) of active cells in face#6 of the cube in the whole trial

touch_density_trial = unfiltered touch frequency (active cells/second) in the whole trial

touch_density_facet_1 = unfiltered touch frequency (active cells/second) in face#1 in the whole trial

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touch_density_facet_6 = unfiltered touch frequency (active cells/second) in face#6 in the whole trial

filt_touch_density_trial = filtered (i.e. explorative touches only) touch frequency (active cells/second) in the whole trial

filt_touch_density_facet_1 = filtered touch frequency (active cells/second) in face#1 in the whole trial

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filt_touch_density_facet_6 = filtered touch frequency (active cells/second) in face#6 in the whole trial

duration_trial = duration of exploration in s

dur_facet_1 = duration of exploration in face#1 in the whole trial

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dur_facet_6 = duration of exploration in face#6 in the whole trial

filt_dur_facet_1 = filtered (explorative touches only) duration of exploration in face#1 in the whole trial

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filt_dur_facet_6 = filtered (explorative touches only) duration of exploration in face#6 in the whole trial

rot_abs_total = amount of rotation in deg in the whole trial

raw_mean_rot_velocity = unfiltered rotation velocity (deg/s)

filtered_mean_rot_velocity = filtered (removed rotations < 1deg/s) rotation velocity (deg/s)

facce_esplorate_0.8s = sequence of explored faces

orient_face_deg = faces orientation in spherical coordinates at the beginning of exploration of the faces reported in 'facce_esplorate_0.8s'. All cube faces are considered (i.e. list of 6 couples of coordinates for each initial timepoint of exploration of a face)

orient_face_world_coord = same as above but translated to world labels (e.g. 'north', 'up', 'west', etc.)

orient_face_local = same as above but translated to labels relative to the participants (e.g. 'left', 'down', 'rear'...)

timepoints_facce_esplorate_0.8s = timepoints in s of the beginning of exploration of a face (see 'facce_esplorate_0.8s')

mean_delta_timepoints = mean time to move from one explored face to the next (mean of 'timepoints_facce_esplorate_0.8s')

std_delta_timepoints = standard deviation of 'mean_delta_timepoints'

transition_local = position of explored face (see 'facce_esplorate_0.8s') relative to the participants

trans_matrices = matrices expressing the probability (prop) of moving from one location to another (e.g. from 'front' to 'left')

ritorni_0.8s = number of returns to already explored faces expressed as array (e.g. [0 0 0 2 0 0] = face#4 explored twice)

ritorni = total number of returns to already explored faces for that trial (sum of the array coded in ‘ritorni_0.8s’)