Protocol

Mouse visual flash-rate accumulation task

Freely moving mice initiate a trial at a center port, view a one-second sequence of visual flashes, and choose between side ports according to whether the flash sequence was generated by a low-rate or high-rate process.

Task structure

Stimulus, choice, feedback, and training as declared in the protocol record.

Stimulus

evidence_schedule
Visual flashes occur over a 1000 ms stimulus period with trial-specific rate and timing; brightness manipulations are present in some sessions.
evidence_type
pulse-train
modalities
visual
notes
units
flashes per second, seconds
variables
flash rate, flash timing, flash brightness, stimulus duration

Choice

action_mapping
Left and right response ports map to low-rate or high-rate choices, with contingency manipulations in some animals.
alternatives
low rate, high rate
choice_type
2afc
notes
response_modalities
nose-poke

Feedback

feedback_type
mixed
notes
penalty
Timeout after incorrect choices.
reward
Water reward for correct choices.

Training

notes
stages
port initiation, low-rate versus high-rate discrimination, manipulation sessions

Trial timing

  1. center_hold
    at least 1100 ms

    Mouse waits at the center port before and during stimulus delivery.

  2. visual_flash_train
    1000 ms

    Visual evidence is delivered as a flash sequence.

  3. go_tone
    brief auditory event

    Auditory cue signals the response epoch.

  4. response
    response-limited

    Mouse chooses a side port.

Vertical slices

Expected analyses

  • psychometric curve by flash rate
  • psychophysical kernel over stimulus time
  • brightness-manipulation sensitivity
  • previous-outcome and previous-choice effects

Interpretive claims

  • evidence accumulation
    Confidence: high · ref.odoemene-2018-visual-accumulation

    Accumulation claims require preserving the pulse timing stream, not only aggregate flash rate.

Open questions

  • Verify one full local source-file run and record exact subject/session counts in generated artifacts.
  • Represent brightness manipulations as task variables rather than nuisance metadata.