Hidden Markov Model-Based Behavioral Classification Reveals Visual Function Recovery After Retinal Organoid...

Area of Science:

• Neuroscience
• Ophthalmology
• Regenerative Medicine

Background:

• Retinal degenerative diseases cause irreversible vision loss.
• Photoreceptor degeneration leads to severe visual impairment.
• Current visual function tests lack sensitivity for assessing natural behavior.

Purpose of the Study:

• To evaluate functional vision recovery after photoreceptor transplantation using a novel behavioral analysis method.
• To assess depth perception and its recovery in rd1-2J mice following retinal organoid transplantation.
• To demonstrate the utility of Hidden Markov Model (HMM)-based behavioral analysis for vision restoration research.

Main Methods:

• Applied Hidden Markov Model (HMM)-based behavioral analysis to the visual cliff test.
• Tracked locomotor state transitions in wild-type (WT) and rd1-2J (RD) mice.
• Evaluated depth perception and recovery following photoreceptor transplantation.

Main Results:

• WT mice showed strong cliff avoidance; RD mice showed no response, validating the model.
• Transplanted RD mice regained depth perception by 2 weeks post-transplantation.
• Behavioral state analysis revealed dynamic changes in vision recovery and habituation.

Conclusions:

• Behavioral state-based analysis offers a sensitive measure of functional vision recovery.
• This approach captures the integration of sensory recovery into adaptive behavior.
• The method can refine clinical evaluations of vision restoration therapies.