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Decoding target location using eye position

MR Megan Roussy
RL Rogelio Luna
LD Lyndon Duong
BC Benjamin Corrigan
RG Roberto A. Gulli
RN Ramon Nogueira
RM Rubén Moreno-Bote
AS Adam J. Sachs
LP Lena Palaniyappan
JM Julio C. Martinez-Trujillo
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During the cue and delay epochs, the screen was divided into 16 cells of equal dimensions. The number of foveations classified as fixations were calculated within each cell under the assumption that animals gather information from the virtual environment during such fixation periods [51]. We used a linear classifier (SVM) with fivefold cross-validation to determine whether target location could be predicted on a single trial basis by the number of fixations within each cell (i.e., the extent to which animals fixate in each part of the visual environment). This analysis was compared with a decoding analysis using neuronal ensembles utilizing the same number of features (16 neuron ensembles).

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