Contributed Talks I: Fixational eye movements and retinal adaptation: optimizing drift to maximize information...

Area of Science:

• Neuroscience
• Computational Vision
• Sensory Systems

Background:

• Fixational eye movements (FEMs) are subtle, involuntary motions during visual fixation.
• Retinal adaptation, or the fading of perception for static images, poses a challenge for visual processing.
• The functional role and optimality of FEMs remain areas of active investigation.

Purpose of the Study:

• To theoretically investigate the influence of FEMs on visual information transmission.
• To model how FEMs interact with retinal adaptation and other visual processing factors.
• To determine the conditions under which FEMs optimize stimulus information and signal detection.

Main Methods:

• Development of a computational model incorporating temporal stimulus modulation, FEM-induced retinal image motion, optical blurring, receptor sampling, and adaptation.
• Analysis of information transmission using mutual information, stimulus estimation, and contrast detection thresholds.
• Quantification of FEM contribution to signal detection for varying target sizes and durations.

Main Results:

• A common quantity, representing summed transmitted power influenced by temporal modulation and FEM-induced phase shifts, must be maximized for optimal information transfer.
• Information transmission can be enhanced by incorporating local persistence into the model's diffusive process.
• FEMs significantly contribute to signal detection, with predictions aligning qualitatively with human psychophysical data.

Conclusions:

• FEMs play a crucial role in overcoming retinal adaptation and enhancing visual information processing.
• The model demonstrates that specific dynamics introduced by FEMs can optimize the detection and perception of external stimuli.
• Theoretical predictions regarding FEMs' impact on signal detection offer insights into human visual performance.