If someone says the human brain makes predictions, please ask, what exactly in the brain makes predictions? And how? If the individual mentions neurons, ask what, in the anatomy or physiology of neurons, qualifies them to make predictions? Since neurons are cells, why [axons, dendrites?] would they be able to do so and not other cells? And if neurons are making predictions in clusters, how so?
Are the clusters changing shape or location? How does it explain prediction error? If a prediction interprets a sensory experience, then what is the architecture of that sensory experience that neurons were able to construct, predict, and then correct? Simply, what is the architecture of sensory experiences, and why would neurons be directly involved?
There is a new [September 17, 2025] spotlight by The Institute of Art and Ideas Reality is a creation of consciousness, stating that:
“The basic idea is that the brain is a very constructive organ. It generates predictions, hypotheses, fantasies, and explanations that best explain the sensory impressions on our eyes and our ears, and our bodies. The idea is that if I’ve got a good grip on the world, if I’m doing good sense-making, then I should be able to predict exactly what is arriving on my sensory epithelia. In other words, if I’m tracking the world in the right kind of way, there will be no prediction error, there will be no mismatch between my predictions and what I’m actually sensing.”
“And that leads to the notion of predictive coding, the imperative to minimize one’s prediction errors—the mismatch between what we predict should happen and the sensory evidence we receive. If the predictions are not correct, then we have a prediction error, and we have to update our beliefs. And then those prediction errors—the surprising sensory information—you use to update your beliefs, to drive changes in your brain, literally changing your mind, so that you adjust your model of the world to then generate better predictions.”
Neurons
What does it mean that the brain makes predictions? Is it the entire brain or just neurons? Now, of everything established in empirical neuroscience, what about neurons makes them to predictions? Neurons have sprawling axons. How can axons be used to explain predictions? How about dendrites? Or, what else might be the option? Now, whatever can predict must be able to represent what was predicted. So, saying neurons make predictions is saying that neurons construct smell, sight, sound, and others?
It is unlikely that neurons construct sensory experiences because neurons are cells. Individually, or in populations, they do not have the dynamism for the large extent of all there is to represent. Also, for all the sensory types and their measures, neurons cannot make those work. Neurons [in whole, in the CNS/PNS] are not often traveling large distances [for any reason, let alone prediction]. Simply, whatever is involved in constructing sensory experiences is involved in long-distance transport as well as in whatever is observed as prediction.
Saltatory Conduction
In neuroscience, there is a phenomenon called saltatory conduction. It is different from what is called continuous conduction. Saltatory conduction is the leap, from node to node in myelinated axons, of electrical signals, going faster by skipping sections. Simply, electrical signals, when traveling across axons with myelin sheaths, they skip the sheaths and jump from a node of Ranvier to the next node of Ranvier. Myelin is an insulator, while the action potential gets stronger across nodes.
Continuous conduction is the travel of electrical signals in axons without myelin. They travel directly, since there is no insulator to skip. So, they travel or touch the whole length, going slower.
Theorizing Predictive Coding
The closest evidence to postulate prediction can be extracted from saltatory conduction. Simply, because electrical signals travel faster, it is theorized that, in sets, across clusters of neurons, some go faster, ahead of others. It is those who go first that result in the [so-called] predictive experience.
The initial traveling signals go ahead towards an initial prediction, then the incoming one comes with the latest, such that if it matches, then it ends in the same direction as the initial, if not, it goes elsewhere, becoming what is called correcting the predictive error.
A real case could be seeing a paper, looking [initially] like a cloth, but after checking gazing, within a second, seeing the right thing. It is the same with hearing something first, or smelling, and so on.
This is how the label prediction is proposed to work in the brain.
Electrical and chemical configurators
In the brain, it is postulated that electrical and chemical signals, in sets, are the configurators and graders of all functions. Simply, neurons are in clusters; it is within clusters that they configure functions by interacting. It is also within clusters that they grade the extent to which they interact. Splits of electrical signals — in a set — can be a measure of interactions, explaining predictions. There are several others like their paths, or sequences, [old and new] thick sets and thin sets, and so forth.
Free Energy Principle and Bayesian Brain
The free energy principle is a theory without merit. It is seeking to explain the brain by predictions, but how about several other attributes? If prediction explains an aspect of, say, human intelligence, mental health, or addiction, how about other aspects?
How does the free energy principle advance psychiatry by explaining all the conditions in the DSM-5? What components in the brain have the free energy principle identified as responsible for constructing functions and to also grade them? How does the free energy principle explain human intelligence, consciousness? How can it be useful to answer new questions on what is now called AI psychosis?
Bayesian brain and the free energy principle have nothing to do with hopes for progress in this century’s neuroscience. They are vibes of uncontrolled hallucination with zero potential but too much noise.
Mental Health
There is a recent [September 15, 2025] survey report on Axios, Workers with mental health needs face access woes, stating that, “The findings from the Employee Benefit Research Institute provide more evidence that having health insurance doesn’t automatically translate to having access, especially for people with mental health needs. Just over a quarter (27%) of 3,103 respondents surveyed in March and April said they or someone on their health coverage had a mental health condition.”
“But 31% of that cohort said they’ve been unable to get some form of necessary medical care in the last six months, compared with 15% of those who reported no mental health conditions.”
“62% of respondents with a mental health condition on their plan said they’d gone to the emergency room in the past six months — meaning they were 50% likelier to seek emergency care. 32% of people with mental health needs who couldn’t get care said their doctor refused to accept their insurance, compared with 17% of people without mental health conditions.”
This article was written for WHN by Dave Steve, who currently does research in conceptual brain science with a focus on the electrical and chemical signals for how they mechanize the human mind, with implications for mental health, disorders, neurotechnology, consciousness, learning, artificial intelligence, and nurture. He was a visiting scholar in medical entomology at the University of Illinois at Urbana-Champaign, IL. He did computer vision research at Rovira i Virgili University, Tarragona.
As with anything you read on the internet, this article should not be construed as medical advice; please talk to your doctor or primary care provider before changing your wellness routine. WHN neither agrees nor disagrees with any of the materials posted. This article is not intended to provide a medical diagnosis, recommendation, treatment, or endorsement.
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