A variety of empirically-supported treatments for individuals with autism spectrum disorders (ASD) exist, however given the vast heterogeneity and comorbidity in ASD (Simonoff et al., 2008), predicting an individual’s likelihood to respond to treatment remains challenging. Subjective-report and behavioral measures capture a broad-range of symptoms collapsed within a single measure, which are not ideal for understanding within- and between-person variability in discrete constructs that might best predict treatment response. In contrast, electroencephalography (EEG) provides unique insights into the neural mechanisms of discrete constructs in ASD such as threat sensitivity in anxiety (Meyers et al., 2013), approach-withdrawal behaviors (Sutton & Davidson, 1997), incidental face-memory (Key et al., 2013), and suppression of interfering information (Faja et al., 2016). This specificity makes EEG measures ideal predictors/outcome measures of construct-specific treatment response. The coordination of these presentations aims to outline “who will respond to which treatment” by discussing the development and application of specific EEG measures that either suggest an individual has a propensity to improve or experience an attenuation in social skills and anxiety after targeted intervention. The goal of this panel is evaluate different EEG measures for their use in determining the best course of treatment for a particular individual with ASD.