I would not have predicted the biggest cut to oil production would come from the producer countries taking each other out 🛢️
Electric Brain by R. Douglas Fields
How the New Science of Brainwaves Reads Minds, Tells Us How We Learn, and Helps Us Change for the Better

In Electric Brain, neuroscientist R. Douglas Fields explores the hidden electrical dimension of the human brain. The book explains how rhythmic patterns of neural activity—known as brainwaves—shape perception, thought, emotion, and consciousness. Rather than being simple by-products of neural firing, these oscillations help organize communication across the brain, synchronizing networks of neurons so that information can move efficiently between regions.
Fields traces the scientific discovery of brainwaves back to the early twentieth century, when German psychiatrist Hans Berger performed the first human electroencephalogram (EEG). Berger demonstrated that the brain produces detectable electrical signals that change with mental activity. Opening the eyes, concentrating on a task, or experiencing emotion all alter the rhythm of these electrical oscillations. Berger’s work revealed for the first time that cognitive and emotional states could be directly monitored through measurements of brain activity.
The book explains how different frequency bands—delta, theta, alpha, beta, and gamma—are associated with different mental states. Delta waves dominate deep sleep, alpha waves appear during relaxed wakefulness, beta waves accompany active thinking, and gamma oscillations are linked with complex cognitive integration. These rhythms coordinate neural circuits much like sections of an orchestra playing together and separating again as needed. Through this synchronization, the brain binds information from different regions into coherent perception and thought.
Fields also examines the growing technological ability to measure and influence brain activity. EEG recordings, quantitative EEG analysis (qEEG), and neurofeedback techniques allow researchers to detect abnormal electrical patterns associated with neurological or psychological conditions. In neurofeedback therapy, patients receive real-time feedback on their brainwave activity, allowing the brain to gradually adjust its own patterns without drugs or surgery.
The electrical nature of the brain has also opened new possibilities in medicine and technology. Techniques such as deep brain stimulation and transcranial direct current stimulation (tDCS) can modulate neural activity by applying small electrical currents to specific brain regions. Research suggests that abnormal oscillations—particularly excessive beta activity—play a role in disorders such as Parkinson’s disease, and modifying these rhythms may reduce symptoms. Brain-computer interfaces are also emerging that allow people to control prosthetic devices or computers directly through neural signals.
At the same time, Fields emphasizes that the science of brainwaves remains incomplete. Many observed relationships between oscillations and mental processes are correlations rather than proven causal mechanisms. Scientists continue to debate whether brainwaves actively drive neural computation or simply reflect the underlying activity of neurons.
Ultimately, Electric Brain portrays the mind as a dynamic electrical system—a constantly shifting landscape of synchronized rhythms and interacting signals. By revealing the brain’s electrical language, Fields argues, neuroscience may gain deeper insight into consciousness, neurological disease, and the future integration of human brains with emerging technologies.
Not Digital Sovereignty, but Autonomy and Resilience
Rethinking Strength in a Post-Global Order

Since Donald Trump began speaking openly about Canada as a potential “51st state,” a phrase has begun circulating more widely in Canadian discussions of technology: digital sovereignty. The term often arises when considering the growing dependence on cloud infrastructure and digital platforms owned by large American technology companies such as Microsoft and Google.
At first glance, the concern seems straightforward. If a country’s digital infrastructure is owned or controlled elsewhere, then its independence may be compromised. Many organizations and institutions understandably want reassurance that their information remains under Canadian control.
Technology vendors are quick to offer that reassurance. Microsoft, for example, operates Canadian data centres and promotes data residency as evidence that Canadian information remains safely within Canadian borders. Yet the company also acknowledges an uncomfortable reality. As a U.S. corporation, it remains subject to American law. If the U.S. government demanded access to certain data, the company could be compelled to provide it, regardless of where the servers physically sit.
Encryption can mitigate risk, but even that is not a complete guarantee. Control over key management, platform architecture, and operational access can still introduce dependencies. And residency itself is only part of the picture. Increasingly the deeper dependency lies in compute. Data may sit in Canada, but the systems that analyze it, particularly AI models, are often developed, trained, and controlled elsewhere. The intelligence applied to the data may remain outside the country even when the data does not.
These realities have helped fuel the growing language of data sovereignty. Yet the phrase itself can feel somewhat overblown.
Mark Carney made a related observation at Davos. Canada is not a “first power.” It does not dominate the global technological order in the way the United States or China might aspire to do. That reality does not imply weakness. It simply describes the scale at which Canada operates.
Consider Carney’s announcement of Telesat Lightspeed, often framed as Canada’s $7-billion rival to Starlink. The language of sovereignty suggests a head-to-head contest for technological dominance. But that is not really the point. Lightspeed will not replace Starlink globally, nor does it need to. Its value lies elsewhere. It strengthens Canada’s capabilities, improves resilience, and ensures that critical infrastructure is not wholly dependent on foreign systems.
That is not digital sovereignty. It is something more modest and perhaps more realistic.
I would call it digital autonomy.
Sovereignty implies ultimate authority, usually tied to the nation-state. Autonomy, by contrast, exists at many levels. An individual can maintain autonomy over personal data. Communities can build and operate their own digital infrastructure. Companies can reduce dependence on external platforms. Nations can cultivate strategic capacity in critical technologies. None of these actors possesses total sovereignty, but each can strengthen its ability to act independently.
Seen this way, digital resilience emerges not from absolute control but from distributed autonomy. Political institutions, commercial organizations, geographic infrastructure, local communities, and individuals all contribute to the system’s stability. The goal is not domination but balance: reducing fragile dependencies while accepting that modern networks are inherently interconnected.
There is also a certain humility in this perspective. Canada does not need to control the global digital order in order to function well within it. What matters is the capacity to operate, adapt, and endure within a system shaped by larger powers.
Digital autonomy recognizes the world as it is: interconnected, asymmetrical, and dynamic. Rather than promising sovereignty we cannot fully possess, it focuses on the practical work of building resilience across the many layers of our digital lives.
Training the Brain for a Lifetime
What meditation research suggests about alpha, gamma, and long-term cognitive health

Meditation research often searches for dramatic findings. Exotic states. Rare neurological signatures. Yet the most consistent observations are quieter and perhaps more consequential.
Across many studies, regular meditation is associated with stronger alpha rhythms. The brain settles into a state of relaxed, attentive stability. In long-term practitioners another pattern sometimes appears: distinctive gamma synchrony, the fast oscillations linked with large-scale coordination across brain networks.
These patterns appear often enough that they begin to look less like curiosities and more like markers of training. The nervous system seems to learn how to quiet internal noise while maintaining clarity, and how to coordinate widely separated regions of the brain with unusual precision.
If sustained over years, such changes may reflect deeper biological effects. A brain operating with greater coherence may manage energy more efficiently, support mitochondrial function, encourage neuroplasticity and neurogenesis, and assist the brain’s own waste-clearing systems. These mechanisms are increasingly studied in relation to long-term cognitive health.
The conclusions must remain measured. Meditation is not a cure-all, and research continues to evolve. But one implication is difficult to ignore.
Just as the body benefits from lifelong physical exercise, the brain may benefit from lifelong training of attention. People who neglect cognitive health often experience decline earlier than they expect. Practices that stabilize and integrate the mind may help preserve clarity longer.
Seen this way, meditation is not merely a method for occasional calm. It is a discipline that may support the long-term maintenance of the brain itself — a quiet investment in cognitive health over the course of a lifetime.
Intelligence on Twenty Watts
Comparing the energy of the human brain and artificial intelligence

It is often remarked, sometimes with unease, that artificial intelligence consumes enormous amounts of energy while the human brain runs on little more than the power of a small light bulb. The contrast is striking. But before we marvel too quickly at the efficiency of the brain, we should pause and ask whether we are making a fair comparison.
What exactly is the human equivalent of an AI system answering a question?
The simplest comparison would be a single answer. You ask a question and either a person or an AI replies. But that framing quietly hides a large part of the machine’s cost. An AI answer depends on a vast training process that took place earlier in large data centres. The electricity used to train the model does not appear in the moment of answering. If we compare a human reply with a single AI response, we are ignoring the energy required to build the machine’s knowledge in the first place.
Another possibility is to compare a trained AI model with a trained human expert. A PhD, for example, represents decades of learning. The AI equivalent is its training phase, during which the model absorbs enormous amounts of text and data. Both systems require a long investment before they are able to produce sophisticated answers.
We could widen the frame further. AI models are trained on the accumulated output of millions of people: books, research papers, code, and conversations. In that sense an AI model resembles a compressed form of collective knowledge. The human comparison might not be a single expert at all, but something closer to a research community.
There is an even deeper perspective. Human intelligence itself is the product of hundreds of millions of years of evolution. If we tried to account for the energy required to evolve brains capable of language and reasoning, biological intelligence would hardly look inexpensive.
For practical purposes, however, the clearest comparison is this: a trained AI model and a trained human expert.
Once we make that comparison, the numbers become interesting. Training a frontier AI model today can require several million kilowatt-hours of electricity. The cost is paid up front during training, after which the model can generate answers at relatively low additional cost.
The human brain, by contrast, runs on about twenty watts of power. Over a full day that amounts to roughly half a kilowatt-hour. Within that modest energy budget the brain performs perception, memory, learning, language, and reasoning.
The real puzzle is not that AI systems use a great deal of energy. Modern computers were built for speed and scale, not for metabolic thrift. The deeper puzzle is why the brain is so efficient.
Evolution had a strict energy budget. Brains that wasted energy did not survive. Neurons fire sparsely, meaning most of the brain is quiet most of the time. Memory and computation happen in the same place, reducing the need to move information around. And the brain relies heavily on prediction, focusing effort on what changes rather than recalculating everything continuously.
The result is a form of intelligence that runs steadily on the power of a small light bulb.
Perhaps the real surprise is not that artificial intelligence consumes so much energy, but that human intelligence runs on just twenty watts.
Join us for Meditation in Person this Sunday, March 1, at the Biblio Wakefield Library at 1:30 pm

If you are in the Wakefield, Quebec area, the Meditation in the Library group has kindly invited me to share my approach to meditation. Join us for Meditation in Person this Sunday, March 1, at the Biblio Wakefield Library at 1:30 pm.
I bring my lifelong experience in meditation and cognitive psychology. I currently facilitate an online Meditation Community informed by traditional vipassana practice and modern neuroscience. I will outline this hybrid approach to meditation, showing how traditional and scientific perspectives can blend smoothly for greater personal benefit and deeper service to the community.
Everyone is welcome to attend this free event. The library is located at Centre Wakefield La Pêche, 38 Chemin de la Vallée-de-Wakefield, Wakefield, QC J0X 3G0
The term, meditation, sticks
I’m creating a new taxonomy for my meditation series and writing after years of careful study and analysis. I have no sentimentality, and am dropping long-favored terms like mindfulness and awakening. The basic term, meditation, however, denies change. I know it has too many meanings and uses, and is prey to misuse by charlatans, but it is still the best term for the modern practice I describe, grounded in traditional Buddhism, bolstered with neuroscience and neurotech, and creatively expressed with sound art. I think the term, meditation, sticks. I remain open to your thoughts.
Everything is going to be.
Everything is going to be. Just be.
(Nod KB.)
Everything Is Going to Be All Right
By Derek Mahon

How should I not be glad to contemplate
the clouds clearing beyond the dormer window
and a high tide reflected on the ceiling?
There will be dying, there will be dying,
but there is no need to go into that.
The lines flow from the hand unbidden
and the hidden source is the watchful heart.
The sun rises in spite of everything
and the far cities are beautiful and bright.
I lie here in a riot of sunlight
watching the day break and the clouds flying.
Everything is going to be all right.
Depart is the Final Meditation in this Series
Join us this Sunday, February 8, 2026, at 10:00 a.m. EST

“Depart” is the final meditation in this series. It is a bookend to our first “Arrive” meditation, a gentle practice of letting go and gratitude. It invites you to rest in a posture of ease, calm the mind, and soften the body, mind, and heart. With quiet guidance and unhurried silence, this meditation helps you release what no longer serves you and recognize what sustains you. You leave the online sanctuary renewed and better equipped for the world, with the understanding that every departure carries the possibility of return.
Please join us this Sunday, February 8, 2026, at 10:00 a.m. EST at the link below. We look forward to seeing you.
https://meet.google.com/ogf-dnbs-ved
You can always find the latest information on my website. I recommend subscribing to my newsletter for invitations and essays. You can contact me via the email listed on my About page, or by replying to any newsletter. Thank you, John Miedema.