Selected Abstracts of Conference Presentations at the 2015 International Society for Neurofeedback and Research (ISNR) 23rd Conference, Denver, Colorado, USA

Neurofeedback is gaining widespread attention across clinical and research domains. As our knowledge of the brain and its enigmatic mechanisms increase, so does the interest in harnessing these mechanisms to promote improved mental processes and reduce symptomatic issues. Neuroscience advances and neurofeedback will continue to evolve into a primary focus for learning, performance, and reduction of symptoms in psychopathology. Likewise, electroencephalographic (EEG) and source localization techniques will improve our understanding and identification of biomarker EEG patterns to better identify and ultimately classify specific patterns associated with psychological and neurological syndromes. As technology and production of devices become more prevalent, there is a growing need to define the parameters used in neurofeedback, as well as to classify the processes into specific or nonspecific factors to avoid further confounds and problems across disciplines.

EEG electrode impedance measurements of 5,000 ohms or less are required by common standards of practice to minimize artifacts due to electro-magnetic interference (EMI). Some manufacturers of amplifiers geared toward the neurofeedback market do not provide on-board impedance monitoring, but provide DC offset measurements. To discover if DC offset is a reliable measure of connection quality, measurements of DC offset and impedance, each independently taken by students in a university graduate level course in neurofeedback over a one year period were analyzed retrospectively. DC offset was not found to have predictive value of a standard impedance level. Additionally, 19 channel EEGs collected within manufacturer recommended parameters of DC offset using a high-impedance amplifier were analyzed to assess the level of EMI pollution of QEEG data. Visible peaks of EMI in the spectra in at least one channel in each of these recordings were identified. A sample of EMI pollution of QEEG results is presented. Together, these findings suggest that DC offset is not a reliable measure of electrode connection quality.

Infra-slow Fluctuation (ISF) electroencephalogram (EEG) biofeedback is a recent development in neurofeedback training. This form of training is focused on the lowest energy the brain produces (< 0.1 Hz). The intervention is performed with a Direct Current (DC) coupled neurofeedback amplifier. It is distinct from Slow Cortical Potential (SCP) training and Infra-Low Frequency (ILF) training. It shares a similar optimization process with ILF that focuses on emergent state shifts within sessions. These state shifts require frequency adjustments that optimize client response to the training in real time. Due to the technical difficulties inherent in recording these frequencies, EEG investigators largely neglected this low energy until recently. As DC amplifiers improved, the slow frequencies became a signal of increasing interest to researchers. Research has demonstrated an important role for the infra-slow oscillations in clinical work. Positive clinical case outcomes suggest that a larger controlled study is warranted. The technical, clinical, and equipment requirements of the intervention make this form of neurofeedback unique in the pantheon of EEG biofeedback interventions.