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Updated: Jan 15, 2026

Investigating Object Representations in the Macaque Dorsal Visual Stream Using Single-unit Recordings
Published on: August 1, 2018
Contentopic mapping in ventral and dorsal association cortex: The topographical organization of manipulable object
J Almeida1, S Kristensen1, Z Tal1
1Proaction Lab, Faculty of Psychology and Educational Sciences, University of Coimbra, Portugal; CINEICC, Faculty of Psychology and Educational Sciences, University of Coimbra, Portugal.
Abstract:
Understanding how object information is neurally organized is fundamental to unravel object recognition. The best-known neural organizational principle of information is topographical mapping of specific dimensions. Such maps have been shown for sensorimotor information within sensorimotor cortices (e.g., retinotopy). Here we ask whether there are topographic maps - by analogy, contentopic maps - for mid-level object-related dimensions. We used functional magnetic resonance imaging and population receptive field analysis to measure tuning of neural populations to selected manipulable object-related action-based dimensions. We show maps in dorsal and ventral occipital cortex that code for the score of each object on each target dimension in a linear progression following a particular direction along the cortical surface. Maps for each dimension are distinct, are consistent across individuals, and are not exhausted by participant-specific eccentricity maps, nor by high-definition eccentricity maps derived from available databases. Thus, object information is potentially coded in multiple topographical maps - i.e., contentopic maps. These contentopic maps refer to intermediate level visual and visuomotor representations, potentially computed from the interaction of lower-level visual features through non-linear transformation following gestalt principles. This suggests that topography is a widespread and non-incidental strategy for the organization of information in the brain that leads to greatly reduced connectivity-related metabolic costs and fast and efficient readouts of information for stimuli discrimination.
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