Category: Neurotech

A Neurotech History Series

For centuries, the surface of the brain appeared uniform. Scientists knew brain injuries could change behaviour, but they had little idea whether different regions served different functions.

German physicians Gustav Fritsch and Eduard Hitzig applied tiny electrical currents to different locations on the cerebral cortex of dogs. Stimulating one area moved a leg, while stimulating another produced movements of the face, neck, or forelimb.

Their experiments provided the first clear evidence that the cerebral cortex is functionally organized. Different regions are responsible for different movements.

This principle underpins modern neurosurgery, transcranial magnetic stimulation, deep brain stimulation, and brain-computer interfaces.

A Neurotech History Series

Early nineteenth-century scientists knew that nerves connected the brain and spinal cord to the body, but they did not understand how information travelled. Did the same nerve carry messages in both directions?

Working independently, Charles Bell and François Magendie showed that the nerve roots entering the back of the spinal cord carry sensory information to the brain, while the roots leaving the front carry motor commands to the muscles.

The Bell–Magendie law revealed that the nervous system is organized rather than chaotic. Sensation and movement follow distinct pathways, allowing the brain to receive information from the outside world while sending precise instructions back to the body.

Physicians still rely on this principle to diagnose neurological disorders, and it continues to inform modern neurotechnology, from spinal cord stimulation to brain-computer interfaces.

A Neurotech History Series

At the end of the eighteenth century, scientists could observe electricity in lightning and static sparks, but they had no reliable way to produce it. Without a steady source of electrical current, experiments on the nervous system were difficult and often impossible.

Italian physicist Alessandro Volta investigated whether electricity originated in living tissue or from the metals used in experiments. While testing different combinations of metals, he stacked alternating discs of zinc and copper separated by cloth soaked in salt water and created the voltaic pile—the world’s first practical battery.

For the first time, scientists had a dependable source of electricity that could be used repeatedly in the laboratory. This transformed research not only in physics but also in physiology, allowing investigators to study nerves and muscles with unprecedented precision.

Modern neurotechnology still depends on the ability to generate controlled electrical currents. From laboratory stimulators to deep brain stimulation and cochlear implants, the lineage can be traced back to Volta’s simple stack of metal discs.

A Neurotech History Series

While dissecting frogs in the 1780s, Italian physician Luigi Galvani noticed something extraordinary. A dead frog’s leg suddenly twitched when a metal instrument touched an exposed nerve. The animal was no longer alive, yet its muscles contracted as if they had received a command from the brain.

At the time, no one understood how the brain communicated with the body. Many scientists believed nerves carried invisible fluids or “animal spirits.” Galvani wondered whether the twitching revealed something entirely different: that the nervous system generated its own form of electricity. He called it animal electricity.

Galvani’s interpretation would later be debated, but his experiments transformed science. They shifted the study of the nervous system from speculation toward measurable electrical phenomena and inspired a generation of researchers to investigate how nerves and muscles function.

Today we know that neurons communicate through tiny electrical signals created by the movement of charged ions across their membranes. Every major neurotechnology—from EEG and deep brain stimulation to transcranial magnetic stimulation and brain-computer interfaces—rests on the same fundamental insight that Galvani’s twitching frog helped uncover: the nervous system is electrical.

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.

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.

Neurotechnology is the use of light (such as infrared or photobiomodulation), sound (as in neurofeedback or binaural beats), vibration or ultrasound, electricity or magnetism (as in EEG, tDCS, or TMS), and plant compounds (including psychedelics), sometimes combined with feedback or digital control systems, to measure or modulate activity in the brain, nervous system, and body. It is used in meditation and medicine to treat conditions such as depression or Parkinson’s disease, and to enhance learning, attention, and states of consciousness.

Dopamine makes promises that it is in no position to keep

Three books have profoundly shaped my understanding of the mind’s duality through the lens of neuroscience. Iain McGilchrist’s The Master and His Emissary (2009) reveals how the brain’s two hemispheres—holistic and contextual (right) versus analytical and reductionist (left)—define human experience and culture. McGilchrist argues that the modern world is increasingly dominated by the left hemisphere’s narrow focus, creating a fragmented, disconnected society. Daniel Kahneman’s Thinking, Fast and Slow (2011) explores this duality through the interplay of two systems of thought—intuitive and automatic (System 1) versus deliberate and analytical (System 2). Kahneman’s work exposes the biases and heuristics that influence human decision-making. Recently, I discovered a third book that complements these perspectives: Daniel Z. Lieberman and Michael E. Long’s The Molecule of More (2018). It examines dopamine, the chemical of desire and motivation, and its pivotal role in shaping human ambition, creativity, and the tension between future aspirations and present contentment.

Lieberman and Long explain the brain’s division of the world into two domains—peripersonal space (what is within immediate reach) and extrapersonal space (what lies beyond). Peripersonal space is regulated by chemicals tied to present-moment awareness, fostering contentment and connection. Extrapersonal space, however, is dopamine’s realm, focused on anticipation, ambition, and the pursuit of what could be. Evolutionarily, this split was critical. Immediate resources like food or shelter required urgent action, while extrapersonal resources demanded exploration and strategic planning. Dopamine ensured survival by driving humans to seek novelty and improvement.

Desire originates deep within the ventral tegmental area, a dopamine-rich structure that scans the environment for potential opportunities—be they food, shelter, or social connections. When dopamine is triggered, it signals the brain to “wake up and pay attention,” sparking a sense of excitement. This response is automatic, beyond conscious control, yet it is not synonymous with pleasure. Dopamine is the molecule of anticipation, not satisfaction. It thrives on the unexpected, propelling us toward uncertainty and novelty. Classic experiments, such as B.F. Skinner’s studies on variable reward schedules, highlight dopamine’s role in addictive behaviors like gambling, as well as its influence on the design of video games, which capitalize on progress and anticipation.

Happiness in the dopamine framework lies not in achieving a goal but in the pursuit itself. Once a desired object is attained, dopamine activity wanes, leaving a sense of emptiness. This dynamic explains why chasing a goal often feels more rewarding than reaching it. To savor the present, the brain must shift from dopamine-driven anticipation to the “here-and-now” (H&N) chemicals, such as serotonin, oxytocin, and endorphins. These neurotransmitters enable us to experience pleasure through relationships, sensory engagement, and mindfulness.

Dopamine’s love of novelty also explains the waning excitement in long-term relationships. Early in a partnership, unpredictability triggers dopamine-fueled attraction. As familiarity grows, dopamine subsides, often leaving individuals restless or searching for new excitement. Yet, this same neurochemical underpins creativity. Artists and scientists frequently describe the act of creation as their most euphoric experience, fueled by dopamine’s capacity to bypass inhibitions and spark originality. Fascinatingly, dopamine-boosting medications, such as those for Parkinson’s disease, have been linked to increased creativity. Lieberman and Long share the case of a poet who, after beginning Parkinson’s treatment, wrote an award-winning poem despite no prior history of creative writing. Similarly, painters on dopamine therapies increased their use of vivid color.

This phenomenon resonates with me personally. After my Parkinson’s diagnosis this year, I began treatment with levodopa, which converts to dopamine in the brain. I marked an improvement in my mental clarity and creative drive. It felt as though I had reclaimed my younger mind. My hobby of writing, neglected for a few years, became a passion again. My neurologist said this effect is not commonly reported, but Lieberman and Long’s observations align with my experience. A similar effect is reported in an episode of the Parkinson’s podcast, Movers and Shakers.

Dopamine’s influence shapes political ideologies. Liberals, often dopamine-driven, focus on progress, innovation, and solving systemic problems. Conservatives, more grounded in H&N chemicals, emphasize stability and tradition, valuing the present over the uncertain future. These neurological differences fuel polarization, as each group struggles to comprehend the other’s perspective. Interestingly, research suggests that small interventions—such as reducing vulnerability—can temporarily shift conservative leanings toward liberalism by enhancing dopamine activity.

Dopamine is both a blessing and a challenge. It has propelled humanity forward, enabling remarkable achievements in science, art, and culture. Yet its insatiable nature demands balance. To avoid the trap of perpetual dissatisfaction, individuals must engage the H&N chemicals that anchor them in the present. These neurochemical systems offer the contentment and joy needed to appreciate life as it is, not as it could be. In this interplay between dopamine and the present lies the secret to balancing ambition with fulfillment, ensuring that humanity continues to progress without losing sight of what truly matters.