Resting State Strength Assessment
and Stress Management

Michael Hickey, MA, Carla Hickey, MA, and John Gilbert, PhD

The Wellness IP App has within its capabilities an assessment function that allows Practitioners to assess Resting State Strength. Human beings can trigger a powerful network in the brain called the Default Mode Network, aka Resting State Network. The human brain and nervous system is composed of a highly advanced network of nerves and related oxygen and heart rate frequency functions. These functions take on a unique set of quantitative patterns when a person, in an awake state, closes their eyes and rests. These quantitative patterns create a normal distribution data set wherein significant deviation from the normative data is indicative of either poor Resting State Network functioning or optimal Resting State Network function with a clear majority of the population falling within a 2 standard deviation spread.

When the Resting State Network functions are disrupted, the individual is subject to cognitive declines in attention, working memory, problem solving capacity, and is often chronically anxious is prone to developing a significant sense of discouragement that can lead to hopelessness and in severe cases can become a clinical problem.

A basic measurement of Resting State health is composed of a measurement of the difference between the activation and deactivation of the Resting State Network. This process can be compare to a balloon inflating and then deflating. The activation of the Resting State Network acts, in a frequency specific change, as a balloon being blow up and the deactivation of the Resting State Network is like a balloon being fully deflated. The activation and deactivation differences of the Resting State Network is particularly disrupted by chronic stress. When a person is under chronic stress, the Resting State balloon function does not fully inflate and it does not fully deflate and there is less difference in the measurement and more overlap in the data space.

Many chronic diseases also cause disruptions in a normal Resting State Network. This has been shown in peer reviewed studies across a wide range of chronic diseases including Stokes, Dementia, Alzheimer’s Diabetes, Obesity, Kidney Disease, Parkinson, chronic pain and many others.

Since each of these chronic diseases can cause significant chronic stress, patients are faced with a compounding negative effect on their Resting State Networks. In other words, the Resting State Network is disrupted by the underlying disease or pain condition, and the stress effect of the disease causes additional disruptions in the Resting State Network. Although the two Resting State Network disruptions are related, they are also independent phenomenology. Therefore, they can be addressed independently.

The Resting State Network Strength can also be viewed as having an additional dimension to its structure and function. Human beings can intentionally self-regulate certain biological processes that historically seemed to be functionally autonomic and in fact are subject to intentional regulation. These are sometimes referred to as neuro-plasticity functions or, in a broader sense, biological plasticity functions. For the purposes of this review, we are focusing on three. These are Oxygen Intentional Plasticity, Parasympathetic Intentional Plasticity, and Brain Wave intentional Plasticity.

Oxygen Plasticity is the capacity of a subject to intentionally self-regulate their oxygen saturation and desaturation, thus developing a greater dynamic range of oxygen hemoglobin saturation. This increase in the dynamic range of hemoglobin saturation is correlated with increased capacity for stress management. This oxygen plasticity is achieved by intentionally raising the hemoglobin oxygen saturation by way of breath regulation and by intentionally lowering the oxygen desaturation through a “no movement” interval fitness exercise programing system. These intentional regulation effects also make significant and measurable changes in Parasympathetic and Brain Wave Plasticity dimensions.

Parasympathetic Plasticity in the current system is measured by intentional regulation of Heart Rate Variability and Galvanic Skin Conductance, each of which is a measurement of parasympathetic plasticity. These intentional self-regulation efforts also make significant measurable changes in Oxygen Plasticity and Brain Wave Plasticity.

In the current system, Brain Wave Plasticity is measured by intentional regulation of the brain wave Theta/Beta Ratio (attention), the Theta/Alpha Ratio (working memory), the Alpha Percentage increase (problem solving), and interhemispheric phase coherence (deep pattern recognition). As with the above intentional regulation activities these brain wave intentional activities also create significant measurable changes in the Oxygen and Parasympathetic Intentional Plasticity dimensions.

The Wellness IP App Resting State Strength Assessment integrates both activation and deactivation measurements with intentional plasticity measurement to derive a total Resting State Strength. Using this methodology, the Resting State Strength assessment can consider the effects of Resting State disruption by measurement of activation and deactivation as well as the potential of the patient to overcome these effects through intentional plasticity potential. This later dimension can be improved and optimized through the smart phone feedback programming.

The data from a Practitioner based Resting State Strength assessment is transmitted to the system’s AI Recommender Engine that provides for structuring the smart phone activities by recommending threshold setting, sequence of intentional programs, time per session and behavior reinforcement schedules to optimize the intentional learning program.

The Wellness IP App Resting State Strength Assessment is intended to provide a measurement of Resting State Activation and Deactivation along with an integrated measurement of oxygen, parasympathetic and brain wave intentional plasticity. This data is used in the systems AI Recommender Engine in order to structure smart phone feedback programs for stress management.