Neuroptimal Research Papers

The two most common questions we receive are: does it work and how does neurofeedback work?  The answer to both questions are in a research paper by social psychologist and neurofeedback trainer, Jean Alvarez, EdD.

EEG Biofeedback Research & The Chemo Brain

The paper The Effect of EEG Biofeedback on Reducing Postcancer Cognitive Impairment describes the efficacy of neurofeedback for the cognitive impairment some patients have after chemotherapy, called "chemo brain".  Her description of how this technology works, it's design and the theory behind it (if you have a science-minded brain) is so concise that I asked her if I could share it.  If you are interested in the science behind the NeurOptimal neurofeedback equipment, read on!  

The Science

Because the science behind this brain training technology is based, in part, on how the brain functions similarly to non-linear, chaos theory mathmatics, it is hard find layperson's language to explain it. Here's what Dr. Alvarez told me about her process of writing about how it works:

"I'm a social psychologist, trained in systems thinking, and pretty comfortable with science.  I needed to figure out the scientific explanation for NeurOptimal because the reviewers for this journal demanded it, and Val Brown [co-developer of the technology] was unwilling to say anything about it. As I got clearer about how I thought it worked, I talked with a couple of physicists, and then spent a morning with Walter J. Freeman, whose thinking I quoted in my paper.  Freeman was a great biologist, [and theoretical neuroscientist] primarily interested in the brain.  After I explained the techonology, he said, 'I don't have any way of knowing whether this is how the software actually works, but I can tell you that I think this would be an effective way of training the brain.'"

The Two Types of Neurofeedback: Protocol-Based and the Latest, Dynamical-Based Technology

Dr. Alvarez writes about protocol neurofeedback and how it interacts with brain functioning:

Similar to trends in cognitive neuroscience, current neurofeedback strategies reflect two different but complementary directions: one driven by a focus on localization and the other by a focus on global brain function. The more common approach [protocol-based neurofeedback], with its roots in the localization school of neuroscience, could be characterized as a “diagnosis and treatment” approach, in which abnormalities in brainwave frequencies at particular locations are identified, ordinarily by means of a quantitative EEG. Researchers and clinicians have identified EEG patterns commonly associated with particular symptoms, and the neurofeedback equipment can be programmed to reward the brain for shifting its activity away from the symptom-associated patterns. For example, attention-deficit hyperactivity disorder (ADHD) in children frequently is associated with slow (theta) wave to fast (beta) wave ratios greater than 3:1 along the cingulate gyrus, located on the innermost surface of each hemisphere above the corpus callosum. A child with ADHD evidencing this pattern would be trained over a series of sessions to lower his/her theta wave amplitude. (from Getting Started With Neurofeedback)


How Dynamical Neurofeedback Works As A Global Approach:

The feedback delivered by the Zengar system [NeurOptimal] is systemic—based on the whole brain’s dynamic activity over time, not its achievement of prescribed states in prescribed locations. The fundamental assumption is that lowering the amplitude of any specific frequency (eg, 8-12 Hz in the left prefrontal cortex) will, by necessity, affect other frequencies in other parts of the brain in the same way that strengthening a single muscle group will affect alignment in other parts of the body, and so it is more realistic to train the brain as a whole system rather than focus on a single location or set of frequencies. This approach recognizes that the brain has a natural tendency toward self-regulation and resilience, allowing flexible cognitive and behavioral responses to a challenging and changing environment.

The Brain As A Non-Linear Sytem of Change (Nonlinear Neurodynamics):

In Modeling Phase Transitions in the Brain, [neuroscientist Walter] Freeman asserts that “abrupt global reorganizations by phase transition in larger brain systems implement a wide variety of intellectual and intentional brain functions . . . including the switch from prodrome [early symptoms] to epilepsy and from from sleep to wake or REM. . . . In each aggregate [of neurons] there are certain conditions that specify a critical point in the phase space at which the system is particularly susceptible to transit from one phase to another, as when the neurons in the sensory cortex transit from a disorganized state of expectation to an organized state of categorization, from noise to signal” 

The Zengar system is rooted in this view of brain organization. Its software detects phase state changes, the precursors to phase transitions. Alerted by feedback that a phase transition is imminent, the brain is able either to reorganize to return to its prior phase (as when the mind refocuses on a task after wandering) or to transit to a new phase (as in the movement from wakefulness to sleep). Neither phase is preferred, or sought, or avoided by the software. Instead, feedback simply is given when the phase transition is about to occur. Because there is no diagnosis required for this form of neurofeedback, and no specific protocol is developed on the basis of that diagnosis, this approach is considered to be training the brain in flexibility and resilience rather than treating particular symptoms. 

And as a result of the practice of being "alerted" thousands of times per training session, the brain is able to "unstick" itself from any habitual patterning and return to present here-and-now events, and it learns to apply this practice of coming back to more and more circumstances so that focusing on a math problem, after little sister has disturbed our concentration by screaming, and be resumed because it is the current activity and the brain is now able to transition back.

What are the EEG sensors measuring?  

Dr. Alvarez Writes: Practically, a single sensor for each [brain] hemisphere is placed at C3 on the left and C4 on the right, midway between the top of the ear and the crown of the head. The sensors simultaneously analyze the EEG activity at 8 clusters of frequencies within each hemisphere. The identification of phase state changes occurs through the analysis of 16 clusters of frequencies (eg, 1-6 Hz, 9-19 Hz), 8 for each hemisphere.

How was the current software protocol developed?

The software developer established the 16 frequency clusters through analysis of the EEG data associated with 20,000 neurofeedback sessions, half named by trainer and client as having had positive outcomes and half as not having had positive outcomes. The use of this general criterion was necessitated by the clients having undertaken neurofeedback for a variety of reasons and on all available neurofeedback equipment, making more specific outcome measures impossible to devise. The developer reports that this approach did reveal distinct differences in filtering characteristics between the more-effective and less-effective sessions and led directly to the frequency clusters now used in the Zengar software (V. Brown, PhD, e-mail and oral communication, December 18, 2012).

Learn more about how NeurOptimal's brain training technology works from their website.  

Thank you, Dr. Alvarez, for your contribution to educating the public!

Want to start brain training today? 

Renting a home system is the most cost-effective option  – we ship throughout US & Canada.



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