Data from: A novel behavioral paradigm using mice to study predictive postural control
Data files
Abstract
Postural control circuitry performs the essential function of maintaining balance and body position in response to perturbations that are either self-generated (e.g. reaching to pick up an object) or externally delivered (e.g. being pushed by another person). Human studies have shown that anticipation of predictable postural disturbances can modulate such responses. This indicates that postural control could involve higher-level neural structures associated with predictive functions, rather than being purely reactive. However, the underlying neural circuitry remains largely unknown. To enable studies of predictive postural control circuits, we developed a novel experimental paradigm for mice. In this paradigm, modeled after human studies, a dynamic platform generated reproducible translational perturbations. While mice stood bipedally atop a perch to receive water rewards, they experienced backward translations that were either unpredictable or preceded by an auditory cue. To validate the paradigm, we investigated the effect of the auditory cue on postural responses to perturbations across multiple days in three mice. These preliminary results serve to validate a new postural control experimental paradigm, opening the door to the types of neural recordings and circuit manipulations that are currently possible in mice.
Dataset Overview
- Subject ID: CB5, CB6 and CB10
- Sessions: 16 sessions(CB5, CB6), 13 sessions (CB10)
- Files per session:
trajectory_nose_spout_CB[X]_session[N].mat- Contains
trajectory_data: position data (nose and spout coordinates over time)
- Contains
trial_events_CB[X]_session[N].mat- Contains
trial: trial-level metadata and event logs
- Contains
Each session includes multiple trials. Trials are aligned by index across the two files:
trajectory_data(i) <--> trial(i)
Trajectory Data Structure (trajectory_data)
Each entry contains:
| Field | Description | Type |
|---|---|---|
noseX, noseY |
Nose position over time (mm) | [N×1 double] |
spoutX, spoutY |
Spout position over time (mm) | [N×1 double] |
noseLH, spoutLH |
DeepLabCut likelihood/confidence values | [N×1 double] |
processed |
(optional) derived metrics for each trial | struct or empty |
processed Fields (if available):
| Field | Description |
|---|---|
disturbance_onset |
Frame number where perturbation begins |
noseDist_bs_corrected |
Baseline-subtracted nose-to-spout distance over time (mm) |
max_noseDist |
Max nose-to-spout distance after perturbation (mm) |
Notes:
- Sampling rate = 200 Hz
- Units = millimeters
- Baseline = mean distance from -2250 ms to -250 ms before perturbation
Trial Metadata (trial)
Each trial contains behavioral metadata and timing logs.
daq_events
| Field | Description |
|---|---|
time_start |
Trial start time (ms) |
time_end |
Trial end time (ms) |
lick |
Time-stamped log of lick detections |
sound |
Time-stamped log of sound cue |
water |
Time-stamped log of water reward delivery |
led |
Time-stamped log of LED |
relay |
Time-stamped log of relay activation (initiates perturbation motor) |
trialtypettl |
Time-stamped digital pulse (TTL) marking trial type |
bswitch |
Time-stamped manual abort due to bad posture (mouse facing the wrong direction) |
esync |
Time-stamped frame sync pulses from the eSync2 device |
count_of_trialtypettl |
Number of TTL pulses encoding trial type and outcome |
results
| Field | Description |
|---|---|
SF |
'Success' or 'Failure' |
Success Definition (summary):
- Trial is considered a success if the mouse obtains at least one water droplet within 600 ms after the perturbation, indicating continued licking and postural control.
- For full operational criteria, see the Methods section of the main manuscript.
