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Andrew Persichetti, Lauren Aulet, Daniel Dilks, Stella Lourenco; Conjoint and independent representation of numerosity and area in human intraparietal cortex. Journal of Vision 2017;17(10):174. doi: https://doi.org/10.1167/17.10.174.
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© ARVO (1962-2015); The Authors (2016-present)
The posterior parietal cortex in primates has been implicated in representing different abstract quantities such as numerosity and spatial extent (e.g., object size). However, there is heated debate about the functional organization of the underlying representations. Recent evidence from single-unit recording in monkeys and population receptive field models in humans suggests that there are overlapping groups of parietal neurons tuned for both quantities. Here, using a continuous carry-over functional magnetic resonance imaging adaptation design, we asked whether the overlap in these representations reflects independent populations of neurons coding for each quantity separately, or a single neural population that is conjointly tuned to both quantities. Specifically, we presented images of dot arrays that varied concurrently in numerosity (2-5 dots) and cumulative area in a continuous, counterbalanced sequence. We modeled adaptation along these two dimensions with both a City-block and Euclidean contraction covariate. In the case of independent populations, neural adaptation will reflect the additive combinations of adaptation for number and area in isolation, as modeled by the City-block covariate. In the case of a single conjoint population, the amount of adaptation for a combined change will be subadditive, as modeled by the Euclidean contraction covariate. We found a subadditive amount of adaptation in a posterior region in the right intraparietal sulcus (rIPS), which overlaps with previously reported topographic maps for both dimensions. In contrast, we found an additive amount of adaptation in a more anterior region of the rIPS, as well as in both a posterior and anterior region in the left IPS (lIPS). Thus, we found evidence for both conjoint and independent populations of neurons, with neurons in the posterior rIPS conjointly representing numerosity and area, and neurons in the anterior regions of the rIPS and in the lIPS independently representing these dimensions.
Meeting abstract presented at VSS 2017
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