Spatial Preference-Weighted Representation of Multiple Stimuli in Cortical Area MT

Area of Science:

• Neuroscience
• Visual Perception
• Computational Neuroscience

Background:

• Object segregation and background differentiation are crucial for visual perception in natural environments.
• Neurons in higher visual areas possess large receptive fields (RFs) that often contain multiple, spatially distinct stimuli.
• The mechanisms by which neurons represent and segregate multiple stimuli within their RFs, and the role of spatial cues, remain unclear.

Purpose of the Study:

• To investigate how neurons in the middle-temporal (MT) cortex represent and segregate spatially separated visual stimuli.
• To determine the role of spatial cues and RF spatial selectivity in processing multiple motion components.

Main Methods:

• Recorded neuronal responses in the MT cortex of male rhesus macaques.
• Presented spatially separated random-dot stimuli moving simultaneously in two directions.
• Utilized a spatial preference-weighted normalization model to analyze neuronal responses.

Main Results:

• MT neuronal responses to bidirectional stimuli were systematically biased toward the stimulus component located in the neuron's preferred RF subregion.
• This spatial-location bias was predictable based on the neuron's spatial preference for isolated single stimuli.
• The bias was stimulus-driven, persisted when attention was diverted, and changed predictably with stimulus shifts, indicating a spatial weighting mechanism.

Conclusions:

• MT neurons leverage RF spatial selectivity to represent multiple motion components, rather than simply averaging them.
• A spatial preference-weighted normalization model accurately described bidirectional responses, highlighting the role of RF spatial selectivity in weighting motion signals.
• This coding strategy provides a neural basis for segregating spatially separated moving stimuli within the visual cortex.