Abstract
Object recognition is achieved through neural mechanisms reliant on the activity of distributed coordinated neural assemblies. In the initial steps of this process, an object's features are thought to be coded very rapidly in distinct neural assemblies. These features play different functional roles in the recognition process - while colour facilitates recognition, additional contours and edges delay it. Here, we selectively varied the amount and role of object features in an entry-level categorization paradigm and related them to the electrical activity of the human brain. We found that early synchronizations (approx. 100 ms) increased quantitatively when more image features had to be coded, without reflecting their qualitative contribution to the recognition process. Later activity (approx. 200–400 ms) was modulated by the representational role of object features. These findings demonstrate that although early synchronizations may be sufficient for relatively crude discrimination of objects in visual scenes, they cannot support entry-level categorization. This was subserved by later processes of object model selection, which utilized the representational value of object features such as colour or edges to select the appropriate model and achieve identification.
Highlights
In the initial steps of the recognition process, an object’s features are thought to be coded very rapidly in distinct but coordinated neural assemblies
Object features to be processed? In the experiment, we manipulated the amount of visual complexity in the image
This is due to the fact that, unlike subjective visual complexity ratings, objective measures are independent of culture-specific expectations about the ‘‘best’’ way to represent a given concept
Summary
In the initial steps of the recognition process, an object’s features are thought to be coded very rapidly in distinct but coordinated neural assemblies. Objects are recognised at the entry-level of recognition, which combines basic and subordinate levels. This means that while more typical exemplars will be recognised at basic-level (e.g., sparrow classed as a ‘bird’), exemplars with distinct attributes will be recognised at a subordinate level (e.g., ‘an ostrich’ or ‘a peacock’). Surface detail (texture, shading and colour) and visual complexity (intricacy of lines and detail) represent the two most obvious forms of object-image properties that can impact on entry-level recognition processes. Their functional roles differ - while colour facilitates recognition [1], additional amount of contours and edges delays it [2]
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