Western Association for Biofeedback and Neuroscience — Spring 2017 12 Introduction Neurofeedback has played a large role in enhancing performance. From helping surgeons increase precision and technical surgery performance (Ros, et al., 2009) to helping NASA pilots reduce mental work- load while performing a navigational task (Prinzel, Pope, & Freeman, 2002), neuro- feedback has shown powerful wide-reach- ing effects in optimizing brain function and performances. Particular neurofeed- back protocols have been shown to mod- ify the cognitive aspects of performance. Reviewing the specific protocols that enhance performance and deep state training can be helpful for specialists to further increase their skill-sets and pro- vide additional opportunities to help im- prove the lives of their clients. Here, the definition of performance is focused on enhancing both deep state training and cognitive processing. Figure 1 depicts the multidimensional cognitive aspects of performance. Alpha-Theta Training and Deep States Alpha-theta neurofeedback training is a form of “deep state” training (Demos, 2005) in which the aim is to increase the production of brainwave frequency am- plitude within the alpha (8 – 12 Hz) and theta (4 – 7 Hz) electroencephalographic (EEG) frequency bands. Alpha-theta Figure 1. Multidimensional cognitive as- pects of performance training has its roots in early conscious- ness research. Groundbreaking research of the association between EEG activity and changes in subjective states of con- sciousness began in the 1960’s and 1970’s and explored self-regulation of brainwave activity. The early pioneers of this re- search included Joe Kamiya (1962, 1968, 1969), Elmer and Alyce Green (1970, 1977, 1993), Dale Walters (Green, Green & Walters, 1970), Steven Fahrion (1992, 1995), Barbara Brown (1970, 1974), Les- ter Fehmi (1978), and Thomas Budzyns- ki (1971, 1973), to name a few. The Expanding Psychophysiological Applications Part 2: Neurofeedback and Optimal Cognitive Performance Mark Johnson, Amir Ramezani, Traci Sitzer, and Arash Ramezani Peer Review Scholarly Section