Temporal and spatial adaptation of transient responses to local features - O'Carroll, David C.; Barnett, Paul; Nordström, Karin (Frontiers in Neural Circuits, 2012)
Interpreting visual motion within the natural environment is a challenging task, particularly considering that natural scenes vary enormously in brightness, contrast and spatial structure. Current models for the detection of self-generated optic flow depend heavily on these very parameters, but despite this, animals manage to successfully navigate within a broad range of scenes. Within global scenes local areas with more salient features are common. Recent work has highlighted the influence that local, salient features have on the encoding of optic flow, but it has been difficult to quantify how local transient responses affect responses to subsequent features and thus contribute to the global neural response. To investigate this in more detail we used experimenter-designed stimuli and recorded intracellularly from motion-sensitive neurons. We limited the stimulus to a small vertically elongated strip, to investigate local and global neural responses to pairs of local ‘doublet’ features that were designed to interact with each other in the temporal and spatial domain. We show that the passage of a high contrast doublet feature produces a complex transient response from local motion detectors consistent with predictions of a simple computational model. In the neuron, the passage of a high-contrast feature induces a local reduction in responses to subsequent low contrast features. However, this neural contrast gain reduction appears to be recruited only when features stretch vertically (i.e. orthogonal to the direction of motion) across at least several aligned neighbouring ommatidia. Horizontal displacement of the components of elongated features abolishes the local adaptation effect. It is thus likely that features in natural scenes with vertically aligned edges, such as tree trunks, would be expected to recruit the greatest amount of response suppression, which could emphasize the local responses to such features vs those in nearby texture within the scene.