Active Role of Self-Sustained Neural Activity on Sensory Input Processing: A Minimal Theoretical Model

Area of Science:

• Computational neuroscience
• Systems neuroscience
• Neural oscillations

Background:

• Ongoing neural oscillations are crucial for sensory processing and sensorimotor behaviors.
• Sensory-evoked neural oscillations arise from sensory input modulating inherent self-sustained neural activity (SSA).

Purpose of the Study:

• To develop a methodology for quantifying the contributions of SSA and sensory inputs to sensory-evoked oscillations.
• To investigate these dynamics within a computational model of sensorimotor behavior.

Main Methods:

• An abstract computational model using three Kuramoto oscillators was developed.
• A simulated agent performed a categorical perception task.
• The influence of SSA and sensory inputs was quantified using phase space vector cross products.

Main Results:

• Sensory-evoked activity during the task was primarily driven by SSA (93.10%), with sensory inputs contributing only 6.90%.
• Reducing sensory input influence by 10.4% resulted in a minimal 2% performance decay.
• Dynamical analysis revealed oscillations stem from network sensitivity and input signal intensity coupling.

Conclusions:

• Self-sustained neural activity plays a dominant role in generating sensory-evoked oscillations during sensorimotor tasks.
• Sensory inputs have a relatively minor, yet potentially reducible, influence on these oscillations.
• Findings suggest avenues for neurophysiological research into SSA's role in sensory processing and behavior.