ArticleCerebral cortex communications2022
Integration of allocentric and egocentric visual information in a convolutional/multilayer perceptron network model of goal-directed gaze shifts.
Article in Cerebral cortex communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 6 citations in OpenAlex.
- A machine learning framework using urinary biomarkers for pancreatic ductal adenocarcinoma prediction with post hoc validation via single-cell transcriptomics.Briefings in bioinformatics · 2025Article
- Spatial navigation entropy suggests allocentric dysfunction in PPPD.Frontiers in neurology · 2025Article
- Article
- Position- and scale-invariant object-centered spatial localization in monkey frontoparietal cortex dynamically adapts to cognitive demand.Nature communications · 2024Article
- Integration of landmark and saccade target signals in macaque frontal cortex visual responses.Communications biology · 2023Article
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Allocentric (landmark-centered) and egocentric (eye-centered) visual codes are fundamental for spatial cognition, navigation, and goal-directed movement. Neuroimaging and neurophysiology suggest these codes are initially segregated, but then reintegrated in frontal cortex for movement control. We created and validated a theoretical framework for this process using physiologically constrained inputs and outputs. To implement a general framework, we integrated a convolutional neural network (CNN) of the visual system with a multilayer perceptron (MLP) model of the sensorimotor transformation. The network was trained on a task where a landmark shifted relative to the saccade target. These visual parameters were input to the CNN, the CNN output and initial gaze position to the MLP, and a decoder transformed MLP output into saccade vectors. Decoded saccade output replicated idealized training sets with various allocentric weightings and actual monkey data where the landmark shift had a partial influence (
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