Differential dynamics of spatial attention, position, and color coding within the parietofrontal network
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Updated: Apr 17, 2026

Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity
Published on: March 18, 2019
Elaine Astrand1, Guilhem Ibos1, Jean-René Duhamel1
1Centre de Neuroscience Cognitive, CNRS UMR 5229, Université Claude Bernard Lyon I, 69675 Bron cedex, France.
Abstract:
Despite an ever growing knowledge on how parietal and prefrontal neurons encode low-level spatial and color information or higher-level information, such as spatial attention, an understanding of how these cortical regions process neuronal information at the population level is still missing. A simple assumption would be that the function and temporal response profiles of these neuronal populations match that of its constituting individual cells. However, several recent studies suggest that this is not necessarily the case and that the single-cell approach overlooks dynamic changes in how information is distributed over the neuronal population. Here, we use a time-resolved population pattern analysis to explore how spatial position, spatial attention and color information are differentially encoded and maintained in the macaque monkey prefrontal (frontal eye fields) and parietal cortex (lateral intraparietal area). Overall, our work brings about three novel observations. First, we show that parietal and prefrontal populations operate in two distinct population regimens for the encoding of sensory and cognitive information: a stationary mode and a dynamic mode. Second, we show that the temporal dynamics of a heterogeneous neuronal population brings about complementary information to that of its functional subpopulations. Thus, both need to be investigated in parallel. Last, we show that identifying the neuronal configuration in which a neuronal population encodes given information can serve to reveal this same information in a different context. All together, this work challenges common views on neural coding in the parietofrontal network.
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