The results are very interesting but difficult to assess in their current format. The presentation of the results could be strengthen by using scatterplots instead of bar graphs. In particular, when comparing a patient group to a control group, it is essential to be able to estimate group overlap. Also, for repeated-measure effects, scatterplots of the pairwise differences would help assess effect sizes and inter-participant differences.
The confidence intervals are incorrect, spanning undefined values of percent correct inferior to 0 and larger than 100. That’s probably because the confidence intervals were derived from a t-test formula, which assumes unbounded variables, and it is not the case for percent correct data.
The SD rule to remove outliers is not robust. A simple alternative is to use the median as a measure of central tendency for reaction times. The mean is anyway inappropriate for skewed distributions.
These references could help improve the presentation of the results:
Allen, E.A., Erhardt, E.B. & Calhoun, V.D. (2012) Data visualization in the neurosciences: overcoming the curse of dimensionality. Neuron, 74, 603-608.
Weissgerber, T.L., Milic, N.M., Winham, S.J. & Garovic, V.D. (2015) Beyond bar and line graphs: time for a new data presentation paradigm. PLoS Biol, 13, e1002128.
Wilcox RR, Keselman HJ. 2003. Modern Robust Data Analysis Methods: Measures of Central Tendency. Psychological Methods 8: 254-74