NeuroVIZR & The Anti-Aging Brain
Garnet > Lucid Studios
April 29, 2024 / May 5, 2024
Introduction – Two Views of Entropy
In physics, the concept of entropy developed in the context of thermodynamics. Entropy is a measure of the disorder of a system. Entropy also describes how much energy is not available to do work.
The more disordered a system and the higher the entropy, the less of a system's energy is available to do work. So, this perspective is one of “energy” and the “ability to do work”.
In an isolated system (aka a “closed” system), when the system's entropy reaches the maximum, the system stays there because any further change would reduce entropy. That's obviously the equilibrium position.
At equilibrium, the total entropy change is zero. So, much for the pursuit of “balance”.
It is common to hear that our universe is headed towards an inevitable entropic “doom”. This is based on pure physical thermodynamic perspectives and it doesn’t sound good for living systems like you and me.
However, living systems are said to exist in a “far-from-equilibrium” state.
We can do that because we are not “isolated” or closed systems that are cut off from everything else.
Living systems are “open” and are permitted to barter and exchange energy, resources and information with existence “at large”.
(For more detail, see Prigogine and “dissipative systems”.)
The “entropy” of physical thermodynamics should not be confused with the “entropy” of informational systems such as those applied to our human brain.
The word is the same but the concept is different.
“As recalled by Schrödinger (1944) and von Bertalanffy (1969/2009) living systems do not obey the second law of thermodynamics.
Prigogine (1967) pointed out the irreversibility of all natural processes, highlighting that irreversible conditions far from equilibrium (steady-states), may originate spontaneously and may transform from disorder (thermal chaos) into order (negentropy), emphasizing the interaction of a system with its surroundings.
Unlike thermodynamics, cognitive neuroscience works with complex systems. When entropy increases, the arrow of time progresses toward disorder, but according to Prigogine, at some point it may achieve the appearance of order, despite a loss of potential.
He called the structures resulting from an irreversible process dissipative to emphasize that they exist only in open systems far from equilibrium, in conjunction with the environment, with fluctuations, and a nonlinear interaction mechanism.
(Brain Entropy During Aging Through a Free Energy Principle Approach; Filippo Cieri, Xiaowei Zhuang, Jessica Z. K. Caldwell, Dietmar Cordes; Front. Hum. Neurosci., 22 March 2021)
This lets us jump from the physics of thermodynamic entropy into the information aspect of entropy in neurological systems like our brain.
Entropy takes on a new and radically different perspective.
Here, entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access.
Now that sounds a lot more attractive when considering “entropy” and our brain.
Brain Entropy
When looking at entropy from an information and neurological point of view, in this context, it provides us with an indicator of our brain’s general readiness to process unpredictable stimuli from our environment.
A brain with greater entropy may, in effect, be better able to model and predict the outcomes of a complex, chaotic world.
The entropic brain model proposes that within upper and lower limits, after which consciousness may be lost, the entropy of spontaneous brain activity indexes the informational richness of conscious states.
Entropy is a powerful tool for quantification of brain function and its information processing capacity.
This is evident in its broad domain of applications that range from functional interactivity between brain regions to quantification of the state of consciousness in everything from psychedelic experiences to coma and anesthesia.
Four Areas of Investigation Related to Brain Entropy
There are at least four areas of significant interest that focus on brain entropy:
- Consciousness in its Ordinary and Extraordinary qualities;
- The Aging Brain;
- Degenerative Brain Conditions;
- Dynamic information processing in Problem Solving and Creative Expression.
A quote from the article Entropy and the Brain: An Overview by Soheil Keshmiri:
“First, the study of consciousness, the ageing brain, and the brain networks’ information processing are among the most active fields of research, to the best of our knowledge, where the use of entropy has resulted in highly promising findings.
Second, the use of entropy in these areas helped realize that their seemingly different lines of research are indeed highly intertwined and related to each other.
There is growing evidence that identifies the vital role of physiologic complexity in organisms’ capacity for adaptation, thereby relating the age-related loss of complexity with diseases and disorders.
Interestingly, these propositions substantially overlap through their association with the brain capacity for information processing.”
(Entropy and the Brain: An Overview – Soheil Keshmiri; Entropy 2020, 22(9), 917)
Evolving Understandings – Brain Entropy
“Entropy, disorder, uncertainty, and complexity often are used as synonymous in neuroscientific context and actually there is an unquestionable connection between informational uncertainty and physical disorder, with an underlying unity linking generative processes of adaptation, mind, and life.”
(Friston, K., Breakspear, M., and Deco, G. (2012a). Perception and self-organized instability.)
“As a measure of uncertainty, Pincus claimed that entropy measures the randomness and predictability of stochastic processes, generally increasing with greater randomness, where more entropy corresponds to greater complexity.”
The components are in nonlinear dynamic relationship, with non-proportional interaction between input and output.
Related to this feature, the system has a hierarchical and emergent behavior, in which the whole model can behave in new and different ways than the hierarchically underlying components.
In the case of the brain, we should observe a dynamic neurocognitive adaptation.
(Pincus, S. M. (1991). Approximate entropy as a measure of system complexity.)
We can summarize this characteristic with the gestalt motto:
“The whole is more than the sum of its parts.”
“Complexity is achieved in systems where integration and segregation are balanced and coexist. A complex system can combine the presence of functionally specialized (segregated) modules with a strong number of intermodular (integrating) links.”
(Rubinov, M., and Sporns, O. (2010). Complex network measures of brain connectivity.)
“The human mindbrain system has a larger repertoire of potential neurocognitive states than other species, and this factor is a key property of its greater complex behavior.”
(Tononi, G. (2012). Integrated information theory of consciousness: an updated account.)
“One of the features related to this greater complexity is an entropy-extension, rather than an entropy-reduction, as one of the processes of human consciousness evolution, subsequently followed by entropy-reduction, through a reorganization of the system.”
(Carhart-Harris, R. L., et al. (2014). The entropic brain: a theory of conscious states informed by neuroimaging research with psychedelic drugs.)
Primary and Secondary Consciousness
“The entropic brain hypothesis first arose to answer the question: ‘What happens to human neurocognitive functionality when non-ordinary states occur?’”
The neurodynamics of primary states are more entropic than secondary states.
One of the most important actions of psychedelic compounds is to increase Brain Entropy, with a direct behavioral effect of increasing the richness of conscious experience.
The psychedelic state is considered an archetype of primitive states of consciousness that preceded—from an ontogenetic and phylogenetic view—the development and evolution of modern, human, adult, ordinary waking consciousness.
(Carhart-Harris, R. L., et al. (2014). The Entropic Brain; Carhart-Harris, R. L. (2018). The Entropic Brain – Revisited.)
Following the Entropic Brain model, Secondary Consciousness is an entropy-reduced state and Primary Consciousness is an entropy-extended state.
With the NeuroVIZR, Secondary Consciousness (entropy-reduced) is known as the Ordinary Mind and Primary Consciousness (entropy-extended) is the Extraordinary Mind.
Complexity becomes super-critical in the primary states of Extraordinary Mind.
On the other hand, complexity naturally decreases during aging and is abnormally reduced during neurodegeneration, becoming “pathologically sub-critical”.
“Primary consciousness is associated with unconstrained cognition and less ordered (higher-entropy) neurodynamics, whereas secondary consciousness is associated with constrained cognition and more ordered neurodynamics.”
“Relaxed beliefs under psychedelics (REBUS) describes an anarchic neural activity, in which there is increased bottom-up signaling and greater sensitivity to external and internal stimuli.”
At the same time, the system is exposed to decreased top-down sensory inhibition, meaning less perceptual restriction.
These two dimensions of the system are mutually dependent and critical in their dynamic balance.
(Carhart-Harris, R. L., and Friston, K. J. (2019). REBUS and the anarchic brain.)
Criticality and the Brain
In a healthy and awake condition, the adult mindbrain system must be able to maintain a dynamic and complex level of criticality.
Criticality is intended as a transition “zone” rather than a static and fixed point.
The brain is considered a system that wanders near a critical dynamic zone between states of order and disorder.
Under normal conditions, the system self-organizes into transiently stable spatiotemporal configurations.
This instability is maximal at a point where the global system is critically poised in a transition zone between order and chaos.
In the current context, the “metastability” of a neural network is a measure of the variance in the network’s intrinsic synchrony over time.
Brain Entropy and Aging
Aging is associated with changes in the complexity and adaptability of the brain.
As we age, the brain may experience a gradual reduction in the variety and complexity of its available neurocognitive states.
This reduction in complexity can affect the brain’s capacity to adapt to changing environments and process new information.
Research increasingly suggests that age-related loss of complexity may be associated with disease and disorders.
The ability of the brain to maintain dynamic complexity therefore appears to be an important feature of healthy aging.
A healthy brain is not simply a brain in perfect balance or complete stability.
It must remain dynamic, adaptable and capable of moving between different states.
This requires a continuing interaction between integration and segregation, order and variability, stability and change.
The Anti-Aging Brain
From the perspective of Brain Entropy, healthy brain aging may involve maintaining the capacity for complexity, adaptability and access to a rich repertoire of neurocognitive states.
The brain must remain capable of responding to novelty and unpredictable information rather than becoming increasingly rigid and restricted.
The relationship between Brain Entropy, criticality and neuroplasticity therefore becomes especially important.
A brain that can maintain dynamic complexity may be better prepared to adapt, learn and respond to the changing demands of life.
At the same time, the goal is not simply to increase entropy without limits.
Both excessive disorder and excessive order can reduce effective brain function.
The objective is to maintain a dynamic range in which the brain can move between different states while remaining organized and responsive.
NeuroVIZR and Brain Complexity
The NeuroVIZR approach explores the potential of sensory stimulation to engage the brain and introduce greater variability into habitual patterns of activity.
Through changing Light and Sound experiences, the NeuroVIZR is designed to challenge predictable patterns and encourage Brain Engagement.
This sensory approach may support the brain's natural capacity for adaptability and neuroplastic change.
Rather than attempting to create one fixed brain state, the NeuroVIZR explores the relationship between variability, complexity and dynamic brain function.
The objective is to provide a rich sensory experience capable of encouraging the brain to remain alert, responsive and open to changing patterns.
From this perspective, “anti-aging” is not simply about preventing change.
It may also be about preserving the brain's capacity to continue changing, adapting and engaging with the world throughout life.