Predictive Regulation and Network Dynamics in Efficient Performance Adaptation – Opinion Statement

Kenneth Jay, MSc, PhD



Michael Phelps in swimming, Serena Williams in tennis, Usain Bolt at the track, Connor McGregor in the octagon, Simone Biles in gymnastics and the legendary hurdler Jackie Joyner-Kersee. Those are all athletes that were at one point, or still is, at the top of their sport. Ever since Dan Coyle’s “The Talent Code” and Malcolm Gladwell’s “Outliers”, the key variable that seems to set the elite apart from everyone else is largely due to the deliberate practice model and 10,000 hour rule proposed by Ericsson and colleagues (1,2). Indeed, legendary golfer Arnold Palmer had it right when he said: “The more I practice, the luckier I get”.

Research in psychology and behavioral science have tried to identify what key characteristics in personality traits and behavior the best in the world have over the general population. For instance, Brown et al (2017) identified up to 15 personality traits that influence the success of top athletes. Personality traits and characteristics as keeping an optimistic mindset and staying focused under pressure (3) are variables that have been identified and are also addressed by Dan Coyle and Malcolm Gladwell in their respective books. Furthermore, being good at managing stress, setting challenging goals and trusting and committing to the process of growth (3) are variables in personality and behavior that cannot be ignored when chasing the Olympic gold or the Wimbledon title.

Broadening the scope of athletic success to include not just psychological and social components and constructs but to encompass intricate physiological and neural network processes and thus enabling the biology of the athlete to adapt to changing stimuli and environmental interactions provides additional insight into what truly makes the best the best.

We, as human beings, constantly interact with our surroundings and our environment. Our success largely depends on our ability to sustain internal stability against outside perturbations – a dynamic process that follows three fundamental strategies of physiological adaptation: 1) homeostasis, 2) allostasis, and 3) the general adaptation syndrome, combined referred to as The reactive scope model (4). These concepts of behavioral strategies correspond to basic forms of behavior (i.e. ordered, chaotic, and static) when modification in complex systems are viewed as an integrated framework of physiological adaptation from a biopsychosocial neuromatrix perspective (5–9).


The homeostatic model in medicine refers to maintaining stability through consistency. Ever since the French physiologist Claude Bernard declared that: “All the vital mechanisms...have only one object – to preserve constant the conditions of ... the internal environment” the homeostatic model of physiological regulation has been dominant. Bernard’s dictum has been interpreted to mean that the purpose of physiological regulation is to hold each internal factor at a “set point” by sensing errors and correcting it via a negative feedback loop mechanism (10). Illustrated in figure 1, the homeostatic model describes mechanisms that holds a controlled variable constant by sensing and regulating its deviation from a predetermined “set point”.

Fig 1: The model of homeostasis.

The reactive strategy of homeostasis is exemplified by a sudden drop in the oxygen content of the blood when it is detected by chemoreceptors in the carotid and aortic bodies that are synaptically linked to the brain stem and thereby adjusting the respiratory rate consequently increasing blood oxygen content back to normal values (11,12). Other examples of homeostatic control are easily found in the physiology of the body. For instance, human brain tissue such as the intact retina or a slice of the cerebral cortex can function in a simple medium at room temperature for hours (13). Furthermore, for each ten degrees, a neuron’s depolarization sensitivity is a staggering two-fold lower than for the optimal 37° C (14), which inherently exemplifies the sensitivity of biochemical reactions in our brain and nervous system. Nevertheless, the sensitivity for the optimal operating temperature may not reflect a predetermined “set point” but rather reflect an evolutionary trait to provide the best possible chance for survival. To survive our bodies must be able to move and with clear and present danger lurking in the bushes of our hunter-gatherer ancestor’s daily life, moving with speed could mean the difference between having lunch or being lunch. To move fast we must also see and think fast. This requires the photoreceptors in the retina of the eye to be small, which in turn sets the survival traits of retinal circuits (13). Basically, this means that a “mean value” of operation does not imply a predetermined “set point” but rather reflects the most frequent demand (15). The network dynamics in regulating responses to environmental stimuli may very well extend further that negative feedback loops by adding the element of predictive regulation through learning.


Predictive regulation is what the model of allostasis describes. In sharp contrast to the homeostatic - stability through consistency – model, allostasis refers to stability through change. The model suggests that consistency is not the goal regulation but rather fitness under natural selection. Regulation needs to be efficient to ensure survival. This implies preventing errors and minimizing costs of adaptation, which is accomplished by using prior information to predict pending demands and then adjusting variables to meet the demand (figure 2) (15).

Fig 2: The model of allostasis.

The underlying tenants of the model of allostasis takes offset in the survival of the species is prioritized over performance of the species. Hence the human being did survive so we could evolve but rather evolved so we could survive. The human being is basically wired for survival and to survive we must be efficient (16). For instance, the capacity to burn the available fuel is closely matched with the capacity for our lungs and circulatory to supply the necessary oxygen and the mitochondrial capacity in our muscles provides the optimal furnace to turn the fuel into energy. If an organ provided more capacity than could be used downstream or an organ downstream provided more capacity than could be supplied from upstream the system would be inefficient and less optimal. Additionally, efficiency requires reciprocal trade-offs and the governance of central control mechanisms (17). Regulation based on sharing resources between organs is efficient but requires precise monitoring to ensure the highest priorities are matched and less important mechanisms overwritten momentarily. For instance, blood flow will, during muscular skeletal work, “borrow” blood from other organs to ensure enough delivery of oxygen. Blood from the digestive system, renal and splanchnic circulation is diverted to the musculoskeletal system to support the current work rate. Even within the brain there is reciprocity or resources. The weight of the human brain is approximately 2% of total bodyweight but it requires 20-25% of the resting blood flow – a proportion so great that it does not receive extra blood flow from the rest of the body but rather diverts circulation to the areas of the brain that has increased neuronal activity(15). The brain also acts as the controlling organ in prioritizing distribution of resources and it enforces this changing hierarchy by deciding under which conditions resources are best distributed to ensure survival. For instance, when muscular- and cardiovascular effort is high but you have just eaten the brain may trigger a “vomiting reflex” or when cooling is more urgent that performance the brain may trigger the “vaso-vagal reflex” by slowing the heart and dilating the blood vessels causing a drop in blood pressure and loss of muscle tone, which ultimately results in fainting (18). When this happens, it is usually accompanied by nausea or dizziness – also provided by the brain – to reduce the likelihood of it happening again (associative learning) (18,19).

The predictive ability of the human brain and its ability to change outputs as more information is added has been described as Bayesian inference, which basically is a statistical model that updates the probability for a hypothesis as more evidence or information becomes available (20,21). An example of this can be found in the performance of elite athletes. For instance, it has been reported that members of the Harvard rowing crew would, in the anticipation of an important race, raise blood glucose levels so high that it spilled into the urine, hitting diabetic levels (22). This predictive regulation happens to all of us. In the face of emergency, adrenaline and other corticosteroids are released into the bloodstream to mobilize fatty acids and glucose just in case a physiological response with strong, fast and powerful muscle constrictions is required for survival (23–25).

The General Adaptation Syndrome

The human body has an innate drive to maintain biological stability. Stressors such as pain, sickness, fear or intense exercise disrupt the stability and trigger a natural response from the body, aimed at returning to an improved level of stability. Briefly, this natural response can be described as a tri-phasic phenomenon (26–30). The first phase is an alarm phase representing a somatic shock. This is followed by the second phase, which is resistance to the shock where the body will fight the alarming threat and work to stabilize conditions. The first two stages are repeated throughout an individual’s life as the person faces new challenges and obstacles. However, should the body remain in the second stage for prolonged periods of time, the body may enter the exhaustion phase. Models of the exhaustion stage indicate that it is the inability to adapt to the causing stressors or to an extended duration of time being subjected to the stressors that creates the symptoms describing the stress state (26–30).

Efficient performance adaptation

The quintessence of athletic development and performance adaptation is indeed driven by psychological and social factors as demonstrated by Brown and colleagues (2017) but fundamentally, none of these personality traits and characteristics would be developed or enhanced had the athlete not had the ability to adapt to changing circumstances by using Bayesian modelling of probability of specific outcomes (20). For instance, the ability to stay focused under pressure and managing stress comes from being repeatedly exposed to the stressors in the right amounts and duration to allow the brain to predict what will happen next and rewire necessary neuronal chunks of networks to optimize performance. Basically, the athlete is subjected to a stimulus that is challenging enough to bring about an alarm phase and resistance phase (1st and 2nd stage) and a requirement for stabilization. Instead of homeostatic stabilization where brain networks and plasticity is not augmented, the allostatic model suggests that stabilization is achieved at a higher level through predicting possible outcomes, choosing which one is most likely to happen and make the necessary adjustments in a continuous loop constantly building on what was just previously learned. If the learning environment for the athlete follows a deliberate practice model (1,2) with frequent stimulation, performance adaptations will occur the fastest and most efficiently.

However, one caveat exists. For the brain being able to predict accurately, the interpretation of incoming signals from visual, vestibular and proprioceptive pathways must likewise be accurate. If they are not, the interpretation will be based on false assumptions and the command programs of the brain will be written accordingly. From computer science, this is referred to as “garbage in, garbage out” where nonsensical information going in, produces a flawed output. This potential flaw in motor learning and athletic development is the first parameter that needs to be corrected if athletic optimization is the goal, and failure to do so will result in a stressed brain pushing towards the exhaustion phase. Therefore, any increase in performance is preceded by reducing the threat of survival by accurate signal interpretation. Only then can the brain rewire itself for enhanced performance.

Practical applications and call to action

Clinicians, sports coaches, strength and conditioning coaches, fitness professionals, and others in the performance industry who see a need to understand and apply a predictive framework to train from with their athletes, should consider submerging themselves into robust educational programs designed bridge the gap between functional neurology and performance enhancement. Programs such as Visual- and Vestibular Performance reset, Clinical Applications of Eye Movements, Pain or the upcoming Human Performance Program are all substance-matter programs available at the Carrick Institute. All programs are designed to optimize and enhance your current abilities and knowledge as a professional in the field of serving others. Helping people thrive in whatever life they lead is the greatest gift you can give and it starts by understanding how the brain and body communicates.


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About the author

Corresponding author: Dr. Kenneth Jay, PhD at


Carrick Institute – Institute of Clinical Neuroscience and Rehabilitation
8910 Astronaut Blvd, Suite 102
Cape Canaveral, FL 32920 USA


  Kenneth Jay is an exercise physiologist with a PhD in Sports Science and Clinical Biomechanics from the University of Southern Denmark specializing in stress-pain interactions. As an assistant professor at the Carrick Institute of Clinical Neuroscience and Rehabilitation and head of research at KOMPIS –Data driven Health Solutions, Kenneth Jay has more than 35 published peer-reviewed papers in the field of pain, stress and performance. He has been a consultant to many of Denmark’s best athletes in swimming, wrestling, table-tennis, badminton, and mixed martial arts and has worked extensively with the Danish Special Forces. Having a brain-bias towards health, performance and overall well-being, his position at the Carrick Institute leading the Human Performance program is a perfect fit to bring neuroscience into the world of performance enhancement under the tutelage of the father of functional neurology himself, Dr. Frederick Carrick.  


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