Claude Shannon [1] did not concern himself with information [2] or meaning [3] proper. In his 1948 paper [4] he wrote:
“Frequently the messages have meaning; that is they refer to or are correlated according to some system with certain physical or conceptual entities. These semantic aspects of communication are irrelevant to the engineering problem.”
It seems the main point of the framework he proposed was the management and delivery of selected physical patterns, especially across channels with noise [5], by means of the identification of a subset of forms within a larger set.
Although he talks about the contrast between certainty and uncertainty to define the forms and symbols as objects of communications, I did not find any place in the paper nor in the subsequent book [6] where he said “information is the reduction of uncertainty” [7].
However, the underlying engineering problem; that is, managing meaningful forms within a sea of noise; is the same for the brain [8].
After all, at the microscopic cellular level, kinetics, brownian motion, quantum mechanics, and other dynamics [9] make the environment like the Madison Square Garden, with a heavy metal band, packed with 25000 hooligans all shouting at the same time.
Compared to a 0 and a 1 in computer science [10], the communications vectors or units in the brain are too many [11]:
Membrane potential gradients – membrane chemical gradients – ion types (Na+, Cl-, K+, Ca++, etc.) – spontaneous brain activity – synapses – synapse count – synapse form – synapse area – neurotransmitter type – neurotransmitter quantity – neurotransmitter frequency – ion summation – summation threshold – action potential – action potential frequency – post synaptic potential – polarization – depolarization – hyper polarization – where the summation takes place – intra cellular potential oscillations – extracellular potential oscillations – dendrite volumes and density – axon terminal volumes and density – pre and post synaptic connection strength – excitation – inhibition – excitation and inhibition differentials and oscillations – stimulus types – cells that are active with no stimulus – cells that are active with stimulus – stimulus intensity – stimulus frequency – stimulus area – ion channel types – channel density – channel interaction modes – neuron types – neuron connection formation patterns – neuron groupings – neuron interaction patterns – axon length – axon reach – axon area – short range signals – long range signals – axon to dendrite connections – axon to muscle connections – axon to gland connections – sensory vs motor interactions and feedback – voluntary vs involuntary – etc, etc, etc…
Each one of the above could be considered a unit of communication in the brain and other parts. Even feedback from glands in the form of hormones [12] is communication.
In other words, the level of complexity [13] explodes very quickly.
Given the above, I think studies regarding how behavioral traits evolved and how they work in the mind have to be grossly speculative.
What I have seen about neural networks and experiments with artificial intelligence [14] seem like how computer science was in the 1950s. Even listening to conferences of neuroscientists speaking about depression, brain pathologies, or abstractions as knowledge and consciousness [15] is like hearing shamans or druids giving their speeches about happiness or black magic.
Brain waves (gamma, alpha, beta, theta, and delta) [16] are only superficial, but dopamine, norepinephrine, serotonin, GABA, glutamate, and acetylcholine do have notable macro effects [17]. Nevertheless, the underlying details are still very far away from our understanding, in my humble opinion.
It could be said that each state, format, and intensity of the features of the brain I listed (and there are many more) is like one letter in an alphabet. Only that ours is 26 letters, and the brain’s must be thousands.
As with the Heisenberg uncertainty principle [18] in quantum physics [19], when neuron potentials fluctuate or fire [20], they actually change the state of the system locally or globally in the form of subthreshold membrane potential oscillations [21] or forming dipoles [22] in the extracellular fluid [23], so it seems there is much more information than just action potentials between cells [24] or discrete identifiable signals between them.
However, one thing to pay attention to, that may not be too complicated to roughly model, is that, even if there is ample competition between them for security reasons, neurons and brain regions work in a trusted environment within the organism (i.e. all have the same DNA [25]), and are constantly trying to figure out and decode untrusted signals from the outside (e.g. from the environment, from other neurons from other organisms of the same species, organisms of other species, predators, etc.) and to come to some sort of consensus through a mechanism as to what is the truth, or at least the best approximation of it.
This consensus mechanism dynamic may be related to base noise, which seems to be leveraged to create meaning; signal strength to overcome the noise; initial skepticism through inhibition [26]; affirmation of the supposed truth through repetition, frequency, and intensity; and so on.
By “ample competition between them for security reasons” I mean that once the data is inside the brain, neurons seem to still be skeptical of the knowledge of other neurons and brain parts when communicating. To solve this, they cycle and recycle the data several times (e.g. the thalamus, neocortex columns and layers, and basal ganglia interactions and loops [27]) until they finally select an action [28] or a mental conclusion, or rough consensus [29], about something.
In the same line of trust minimization, or healthy skepticism, especially with the growing “mental health” industry and its dangerous antics and politics, I think individuals should have a sufficient knowledge of these things about neurology to at least be able to ask the doctor what is X medication? What is its function? Where in the brain? What are the collateral effects for example in neocortex thickness [30 a, b]? What is the proof that it helps resolve Y condition?
The same with other organ systems, pathways, and functions.
References and Notes
[1] Claude Shannon – by Wikipedia: https://en.wikipedia.org/wiki/Claude_Shannon
[2] What is Information? – by Donald McIntyre: https://etherplan.com/2020/11/02/what-is-information/13378/
[3] What is Meaning? – by Donald McIntyre: https://etherplan.com/2020/12/08/what-is-meaning/14028/
[4] A Mathematical Theory of Communication – by C. E. Shannon: http://etherplan.com/a-mathematical-theory-of-communication.pdf
[5] Noisy-channel coding theorem – by Wikipedia: https://en.wikipedia.org/wiki/Noisy-channel_coding_theoremby Claude E. Shannon (Author), Warren Weaver (Author)
[6] The Mathematical Theory of Communication – by Claude E. Shannon and Warren Weaver – on Amazon: https://www.amazon.com/Mathematical-Theory-Communication-Claude-Shannon/dp/0252725484
[7] When/where did Claude Shannon say “information is the resolution of uncertainty”? – on Quora: https://www.quora.com/When-where-did-Claude-Shannon-say-information-is-the-resolution-of-uncertainty%E2%80%9D
[8] The Brain Is Always Active – by Georg Northoff M.D., Ph.D., FRCPC – on Psychology Today: https://www.psychologytoday.com/us/blog/learning-the-unwell-brain/201601/the-brain-is-always-active
[9] Noise in the nervous system – by A. Aldo Faisal, Luc P. J. Selen & Daniel M. Wolpert – on Nature: https://www.nature.com/articles/nrn2258
[10] Binary – by TechTerms: https://techterms.com/definition/binary
[11] Allen Brain Map – by Allen Institute: https://portal.brain-map.org/
[12] Hormones: Communication between the Brain and the Body – by Brain Facts: https://www.brainfacts.org/brain-anatomy-and-function/cells-and-circuits/2012/hormones-communication-between-the-brain-and-the-body
[13] Complexity – by Wikipedia: https://en.wikipedia.org/wiki/Complexity
[14] A Theory of How Columns in the Neocortex Enable Learning the Structure of the World – by Jeff Hawkins, Subutai Ahmad and Yuwei Cui: https://www.frontiersin.org/articles/10.3389/fncir.2017.00081/full
[15] What is Consciousness? (Featuring Joel Frohlich) – by Professor Dave: https://professordavedebates.simplecast.com/episodes/consciousness-6eda16b2
[16] Neural oscillations – by Wikipedia: https://en.wikipedia.org/wiki/Neural_oscillation
[17] What are the Main Neurotransmitters? – by Dr. Robert Pastore – on PowerOnPowerOff:
“Neurotransmitters all serve a different purpose in the brain and body. Although there are several different minor and major neurotransmitters, we will focus on these major six: acetylcholine, dopamine, norepinephrine, serotonin, GABA, and glutamate.”
Source: https://poweronpoweroff.com/blogs/guide/what-are-the-main-neurotransmitters
[18] Heisenberg uncertainty principle – by Wikipedia: https://en.wikipedia.org/wiki/Uncertainty_principle
[19] Quantum physics – by Britannica: https://www.britannica.com/science/quantum-mechanics-physics
[20] Biological neuron model – by Wikipedia: https://en.wikipedia.org/wiki/Biological_neuron_model
[21] Subthreshold membrane potential oscillations – by Wikipedia: https://en.wikipedia.org/wiki/Subthreshold_membrane_potential_oscillations
[22] Understanding EEG Signal Generation: From Neuron to Electrode – by PURSUE Initiative – University of Richmond: https://pursue.richmond.edu/learn-eeg-erp/animations/
[23] Brain Rhythms: Functional Brain Networks Mediated by Oscillatory Neural Coupling – by Phillip M. Gilley – Research Associate, Institute of Cognitive Science (ICS)- University of Colorado Boulder: https://youtu.be/OCpYdSN_kts
[24] Action potential – by Wikipedia: https://en.wikipedia.org/wiki/Action_potential
[25] The Individual vs the Collective Fallacy – by Donald McIntyre: https://etherplan.com/2020/07/04/the-individual-vs-the-collective-fallacy/11957/
[26] Neuron inhibition, keeping the brain’s traffic in check – by Knowing Neurons: https://knowingneurons.com/2014/11/05/inhibitory-neurons-keeping-the-brains-traffic-in-check/
[27] Cortico-basal ganglia-thalamo-cortical loop – by Wikipedia: https://en.wikipedia.org/wiki/Cortico-basal_ganglia-thalamo-cortical_loop
[28] Action selection – by Prof. Tony J. Prescott, Dept. Psychology, University of Sheffield, UK – on Scholarpedia: http://www.scholarpedia.org/article/Action_selection
[29] Rough consensus – by Wikipedia: https://en.wikipedia.org/wiki/Rough_consensus
[30 a] Drug Receptor Profiles Matter – by John J. Miller, MD – Psychiatric Times, Vol 37, Issue 4:
“With this background, I would like to turn your attention to a recent publication in the February 2020 online issue of JAMA Psychiatry: ‘Effects of Antipsychotic Medication on Brain Structure in Patients With Major Depressive Disorder and Psychotic Features.’ Voineskos and colleagues analyzed the cortical thickness in gray matter of 72 patients with major depressive disorder with psychotic features. Patients were treated with the sertraline/olanzapine combination for 12 to 20 weeks, including an 8-week period of remission of psychosis, as well as remission or near remission of depression.
This cohort was then randomized in a double-blind fashion to continue the combination regimen or to be switched from olanzapine to placebo (and remain on sertraline) for an additional 36 weeks. For the patients with sustained symptom remission at 36 weeks compared with the placebo-sertraline group, the olanza- pine-sertraline group demonstrated a significant decrease in cortical thickness. A decrease in cortical thickness was also seen in a post-hoc analyses of the patients who relapsed in the placebo-sertraline group compared with the group with sustained remission.
During the several weeks following its online publication, I have read many reviews of this article in various online psychiatric resources, all of which infer that the finding of this study is generalizable to all antipsychotics. Notably, and to the authors’ credit, they recognize a limitation to their study results:
Finally, our data were obtained with 1 specific antipsychotic, olanzapine, and it is possible they do not apply to other antipsychotics. However, based on the wealth of data demonstrating equivalent efficacy among antipsychotics and similar effects of different antipsychotics on brain structure in both animal and human studies, we speculate that our findings are likely to apply across all medications in this class.”
Source: https://www.psychiatrictimes.com/view/drug-receptor-profiles-matter
[30 b] Effects of Antipsychotic Medication on Brain Structure in Patients With Major Depressive Disorder and Psychotic Features – by Aristotle N. Voineskos, MD, PhD; Benoit H. Mulsant, MD, MS; Erin W. Dickie, PhD; et al: https://jamanetwork.com/journals/jamapsychiatry/article-abstract/2761879
