We recorded PD0332991 chemical structure scalp EEG signals from 15 human participants who viewed a rapid stream of eight oriented Gabor patterns presented at a rate of 4 Hz (Figure 1A).

Following each stream, participants reported whether, on average, the tilt of the eight elements fell closer to the cardinal or diagonal axes. We defined two parametric quantities indexing two types of information provided by each element on each trial: (1) the perceptual update (or PUk), corresponding to the absolute difference in tilt between a given element k and the previous element k−1, and (2) the decision update (or DUk), corresponding to the amount of categorical evidence provided by element k. In other words, perceptual updates reflect how much each new element differs visually from the previous one—i.e., the successive visual transients occurring at the onset of each new element—whereas decision updates reflect how much each new element differs from the decision criterion—i.e., the incremental quantity that the internal decision variable should be Autophagy inhibitor updated with (see Figure S1 available online). Critically, the use of a cardinal/diagonal decision axis ensured that PUk and DUk were uncorrelated across trials—i.e.,

two elements could give rise to identical perceptual updates but different decision updates (see Experimental Procedures; Figure S1). Perceptual updates are irrelevant to performing the task, whereas decision updates correspond to the quantity that subjects should integrate over time: the sum of the eight decision updates, each signed with its corresponding category. Finally, we ensured that successive decision updates were not correlated across trials by sampling them randomly from independent uniform distributions (Figure S1); this feature allowed us to regress individual decision weights with the highest statistical power. Categorization accuracy was titrated for each participant prior to the

experiment by adjusting the average categorical evidence available at the end of the trial over five evenly spaced levels (Figure 1B). We then estimated the decision weight (or wk) Casein kinase 1 associated with each element k, defined as its multiplicative contribution to the subsequent choice. We calculated these weights across trials via a multivariate parametric regression of choice on the basis of a linear combination of the eight decision updates: P(cardinal)=Φ[b+∑k=18wk·DUk],where P(cardinal) corresponds to the probability of judging the stream as cardinal, Φ to the cumulative normal function, and b to an additive response bias toward one of the two categories. We found that decision weights were all positive (t test against zero, all p < 0.