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Updated README.

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@@ -33,9 +33,14 @@ The data is organized into a highly efficient, indexed HDF5 format, allowing for
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  | Sessions | 14 sessions of registered neural activity |
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  | Stimuli | 3 categories (`Clip`, `Monet2`, `Trippy`) identified by unique condition hashes |
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  | Neural Data | Calcium traces from thousands of neurons across V1, LM, RL, AL |
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- | Behavioral Data | Synchronized treadmill speed and pupil size (major/minor radius) |
 
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  | Eye Tracking | Pupil center coordinates (x, y) for gaze analysis |
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  ---
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  ## 🗂️ Internal HDF5 Structure
 
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  | Sessions | 14 sessions of registered neural activity |
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  | Stimuli | 3 categories (`Clip`, `Monet2`, `Trippy`) identified by unique condition hashes |
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  | Neural Data | Calcium traces from thousands of neurons across V1, LM, RL, AL |
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+ | Treadmill | Running speed (cm/s) synchronized to stimulus frames |
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+ | Pupil Size | Major and minor radius of the fitted pupil ellipse (in pixels) |
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  | Eye Tracking | Pupil center coordinates (x, y) for gaze analysis |
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+ ### Temporal alignment & sampling
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+ All data streams — neural responses, pupil, and treadmill — were independently interpolated to 30 Hz to match the stimulus frame rate, aligning every signal to a common stimulus clock. The full 30 Hz timeseries was then uniformly downsampled by a factor of 4, yielding a final sampling rate of **7.5 Hz** for all stored signals. As a result, `responses`, `treadmill`, `pupil`, and `stim_times` share an identical time axis within every trial, with each sample corresponding to a stimulus frame spaced ~133 ms apart.
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  ---
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  ## 🗂️ Internal HDF5 Structure