(a) LDA classification of all 8 task pictures based on single unit spiking data or LFP. For 8 categories, chance decoding is 12.5%. Picture identity could be decoded from both spikes and LFPs above chance, with peak accuracy approximately 250 ms after stimulus onset, though spikes provided higher accuracy than LFPs. Each line shows mean accuracy ±SEM across 44 behavioral sessions for both subjects. Pictures were decoded from both spikes and LFPs above chance. (b) Confusion matrices with colored number blocks referring to ordinal picture value 1 to 4. There were two pictures of each value level, one predicting a primary reward and one predicting a secondary reward. Accurate classifications are along the main diagonal. Classifier confusions of pictures with the same value but different reward types are the off-diagonal shaded squares. Most misclassifications occurred between primary and secondary pictures of the same value level. In these cases, the decoder accurately identified the picture’s reward value but misidentified the reward type (primary or secondary). (c) Percent of trials correctly classified and those classified as the correct value but wrong reward type (primary or secondary) for each subject. Overall, the decoder based on spiking data provided more accurate picture classification. This was largely because the LFP decoder was just as likely to misidentify as correctly identify the reward type. Bars show the mean ± SEM across behavioral sessions for each subject. ** paired t-test p ≤ 0.005, *** p ≤ 0.001.