From Brain Scans to Body Suits in 21st‑Century Neuroscience 

By: Yishika Gupta

In a quiet lab, a volunteer sits beneath a strange silver cap. Hundreds of tiny sensors rest against her scalp. A technician dims the lights, and a screen flashes a series of images: faces, words, shifting patterns. On a monitor across the room, her brain responds in real time: waves of invisible electricity rendered into color and motion. Click. One button pressed. All she was, all she had thought about, felt, and dreamt for, was transferred into a revolutionary disk.   

Sounds like sci-fi, doesn’t it? 

We are still far from “uploading” a mind into a machine. But breakthroughs in neuroscience, especially in brain imaging and neural interfaces, are bringing us closer to a world where thoughts, sensations, and even movement can be read, restored, and perhaps one day enhanced in ways that once sounded like pure science fiction. 

Two families of tools are leading that charge: advanced brain imaging like SQUID‑based MEG, and electrical/muscular interfaces like EMS body suits. Together, they hint at a future in which minds don’t just live inside bodies and machines, but flow between them. 

Reading the Whisper of Neurons: MEG and SQUID Imaging 

Every thought you’ve ever had is built on electricity. Neurons signal one another with tiny voltage changes that, in vast coordinated patterns, generate faint electric and magnetic fields. Electroencephalography (EEG) has recorded these electrical patterns for over a century. But EEG’s picture is blurry: skull and tissue distort the signals, and it’s hard to pinpoint exactly where in the brain they come from. 

Magnetoencephalography (MEG) takes a different route. Instead of measuring electric potentials, MEG records the magnetic fields produced by neuronal currents. These fields are unimaginably weak—on the order of femtotesla (10⁻¹⁵ tesla), far smaller than the magnetic field of the Earth. To sense them, we need one of the most sensitive instruments humans have ever built: the SQUID. 

Inside the SQUID 

Think of a SQUID—Superconducting Quantum Interference Device—as a quantum loop that throws a tantrum when a magnetic field changes. In its superconducting state, current flows with almost no resistance, and quantum effects become large enough to detect minute shifts in

magnetic flux. The result is a sensor so sensitive it can detect the magnetic signature of a few hundred thousand neurons firing together deep in the brain. 

Traditional MEG systems place an array of SQUID sensors very close to the scalp, cooled with liquid helium to just a few degrees above absolute zero. When neurons fire, they produce small magnetic fields that thread through these loops, altering the quantum interference pattern and giving researchers a moment‑by‑moment map of brain activity. 

Unlike MRI, MEG doesn’t show brain structure in exquisite anatomical detail. Instead, it tracks timing—it can follow brain activity millisecond by millisecond. That temporal precision is what makes MEG so powerful for understanding how networks of brain regions talk to each other in real time. 

What can MEG and SQUIDs do today?

Researchers and clinicians already use MEG in three main ways. First, to map language, vision, and motor functions before surgery. In patients with epilepsy or brain tumors, neurosurgeons use MEG to locate critical areas—like those involved in speech or hand movement—so they can avoid them during surgery. The U.S. National Institute of Neurological Disorders and Stroke (NINDS) notes that MEG “is particularly useful for localizing the source of epileptic activity and for mapping brain areas responsible for critical functions” before operations. 

Second, MEG can reveal altered communication patterns in neurological and psychiatric disease, including schizophrenia, autism, and Alzheimer’s disease—changes in rhythm and 

connectivity that may serve as early biomarkers. 

Third, in research settings, MEG has been used to decode perception and intention. In some studies, scientists can tell which image a person is viewing based solely on their brain activity; others have gone further, decoding which of several words or categories a subject is thinking about from MEG data alone. 

A 2017 review in Nature Reviews Neuroscience highlighted how MEG, especially when combined with structural MRI, can reconstruct source activity across the brain and track fast dynamics in neural networks. 

For all its strengths, MEG is not a magic mind‑reader. The technology is expensive, bulky, and available at only a limited number of centers worldwide. It is most sensitive to activity in the outer layers of the cortex and struggles to pick up signals from deep brain structures. Localising sources also relies on mathematical models and assumptions about head shape and tissue properties, which introduce uncertainty. MEG usually has to be combined with other tools—like structural MRI, EEG, or clinical assessment—to give a complete picture. 

The next generation: wearable MEG and beyond

Bank‑vault‑sized MEG machines are slowly giving way to more flexible systems. Cutting‑edge research prototypes use optically pumped magnetometers (OPMs)—small, room‑temperature sensors that can be worn like a helmet. That means people can move naturally during scanning: walking, reaching, or interacting, while their brain activity is recorded in great temporal detail.  

Although OPM‑MEG doesn’t always rely on SQUIDs, it grows from the same lineage: the quest for exquisitely sensitive measurements of the brain’s subtle electromagnetic fields. 

Looking ahead, portable and pediatric MEG could allow earlier detection of neurodevelopmental disorders. Integration with AI may make it possible to decode complex mental states—intentions, emotional valence, or imagined movements—from real-time brain signals. And closed-loop brain–computer interfaces (BCIs) could eventually use fast imaging signals from MEG or related technologies to adjust stimulation in real time, automatically helping to calm seizures or tremors.

Writing Motion into the Body: EMS Suits and Neuroprosthetic Interfaces 

We often imagine future neuroscience as purely in the head: brain scans, neural decoding, thoughts on screens. But an equally radical revolution is happening in the body, where technologies like electrical muscle stimulation (EMS) and functional electrical stimulation (FES) are starting to bridge the gap between neural intention and physical action. If brain imaging tools like MEG and SQUIDs let us read the whisper of neurons, EMS suits and neuroprosthetic systems give us a way to write motion back into the body, and, in some cases, into machines that become part of the body’s extended self. 

In one rehab clinic, a woman with a spinal cord injury straps into an FES bike. Electrodes line her thighs and calves. When the therapist starts the program, her legs begin to pedal—not because her spinal cord carried the signal, but because a computer did. 

How EMS and FES Work: Hijacking the Final Common Path  

All voluntary movement, from typing this sentence to taking a step, ultimately converges on a simple pathway. Motor areas in the brain decide to move. Signals travel down the spinal cord. Peripheral nerves activate muscle fibers. Muscle contraction moves. 

In paralysis from spinal cord injury or certain neurological diseases, the early parts of this chain may still function—the brain still “wants” to move—but the signals can’t reach their destination. EMS and FES work by bypassing part of that broken link. 

● Electrical pulses are delivered through electrodes on the skin (or sometimes implanted near nerves or within muscles).

● These pulses depolarise motor nerves or muscle fibers, causing muscles to contract—even if the person cannot voluntarily move that limb. 

● With the right timing and intensity, sequences of contractions can approximate functional movements: grasping, standing, and taking a step. 

What makes FES more than a simple muscle zapper is its intentionality. In clinical systems, stimulation is carefully coordinated—sometimes triggered by residual voluntary signals, sometimes by a brain-computer interface, sometimes by preprogrammed patterns—so that the resulting movement feels purposeful, not random. 

From Wheelchairs to Walking: FES in Rehabilitation  

Instead of a static, seated existence, FES and EMS technologies offer a different narrative for people with paralysis or severe weakness. FES cycling and stepping systems can help spinal cord injury patients pedal a stationary bike or perform stepping motions, preserving muscle bulk, improving circulation, and supporting cardiovascular health. Stroke rehabilitation programs use EMS to assist weakened muscles during therapy sessions, pairing stimulation with attempts to move. Over time, this can help retrain surviving neural circuits, harnessing neuroplasticity. 

A widely cited review in the Annual Review of Biomedical Engineering by Peckham and Knutson describes FES as a way to “restore useful function” to paralysed muscles, not just prevent atrophy. Stimulating the right muscle groups at the right moments can enable tasks like: 

● Grasping and releasing objects with the hand. 

● Standing up from a seated position. 

● Taking supported steps with a walker or harness. 

For these patients, an EMS-based system is more than a gadget; it’s a partial rewriting of the boundary between what their brain wants and what their body can do. 

When the Brain Drives the Suit: BCIs and Neuroprosthetics 

The next frontier is merging brain decoding with body stimulation and prosthetic devices—closing a loop from thought to movement and back again. 

In some cutting-edge research, implanted brain–computer interfaces record activity directly from the motor cortex. Patterns of firing are decoded into intended movements—like “move hand forward” or “open grip.” These intentions can then be used to: 

● Control a robotic arm, as in the landmark work by Hochberg and colleagues, where people with tetraplegia were able to reach and grasp objects with a neurally controlled robotic limb. 

● Drive FES systems that stimulate a person’s own arm or hand, effectively reanimating paralyzed muscles using the person’s own cortical activity as the command signal.

Lebedev and Nicolelis, in a sweeping review of brain–machine interfaces, describe this class of technology as extending the brain’s motor outputs into “artificial actuators”—robotic devices or stimulated muscles that behave as if they were natural limbs.³ Over time, many users begin to experience these devices not as external tools, but as part of their body schema—a psychological shift that hints at how deeply our brains can incorporate technology into our sense of self.  

In this sense, FES and EMS suits are embryonic forms of neuroprosthetics: systems in which artificial components (electrodes, controllers, robotic joints) and biological tissues (nerves, muscles, skin) function as a single, integrated unit. 

Luxury, Gaming, and the Strange New Sensation of Shared Control 

Not all EMS technology is confined to rehab hospitals and research labs. A growing ecosystem of commercial EMS suits and “smart training” systems has begun to market electrical stimulation as: 

● A fitness enhancer—intensifying workouts by activating multiple muscle groups simultaneously. 

● A performance tool—fine-tuning posture, core engagement, or specific muscle recruitment. 

Beyond fitness, designers and game developers are experimenting with EMS as a new immersive interface: 

● In virtual reality, EMS could simulate the sensation of recoil when firing a weapon, the pull of a grappling hook, or the resistance of pushing a heavy object. 

● In interactive art and dance, choreographers can create performances where some movements are voluntarily chosen, and others are “suggested” by timed EMS patterns—turning the dancer into a collaborator with the machine. 

This is where the technology starts to feel like sci‑fi again. If an external system can nudge your muscles into motion, even gently, where is the line between your choice and the device’s script? 

For healthy users, this can be playful—a novel sensation, like riding a roller coaster your body helps to drive. But the ethical issues are real: 

● Consent and control: Who decides when and how the suit activates? ● Safety: Poorly calibrated stimulation can cause injury or pain. 

● Data privacy: If EMS suits and neuroprosthetic systems are connected to cloud platforms to adapt and personalise stimulation, what happens to that movement and health data? 

As with MEG and brain imaging, NIH and major neuroscience texts emphasise the need for strict safeguards when technologies touch our nervous systems, particularly when they can influence behavior or bodily autonomy.

Bridging Brain and Body 

We’re still far from uploading a mind in any literal sense. Consciousness, identity, and subjective experience are deeply tied to biological processes that we don’t fully understand. But emerging neuroscience technologies are enabling narrower kinds of “uploads”: 

● Functional 

○ Decoding motor intentions and using them to move a cursor, wheelchair, or robot arm. 

○ Capturing the neural patterns of speech or imagined handwriting and turning them into text on a screen. 

● Physiological 

○ Recreating sensory experiences (like stimulation that mimics touch or movement) through electrical or haptic interfaces. 

○ Using EMS or neural stimulation to “write back” into the body in ways that mirror natural signals. 

● Model-Based 

○ Building detailed computational models of a person’s brain networks from MEG, MRI, and EEG data. 

○ Using these models to predict responses to stimulation, medications, or surgery—a kind of digital twin for clinical decision-making. 

These are not immortality schemes, but they are profound shifts in how tightly mind and machine can intertwine. 

As imaging grows more sensitive and body suits more powerful, the potential for misuse grows as well: 

● Could detailed brain recordings reveal private thoughts or vulnerabilities?
● What happens if EMS or neural stimulators are hacked or misconfigured? ● Who owns your neural data—and the models built from it? 

Each of these questions raises others. The answers, whatever they turn out to be, will nudge us closer to a world where aspects of who we are—our skills, movement patterns, reactions—can be mapped, modeled, and partially replicated outside our biological bodies. The “future upload” may not look like a sci‑fi brain in a jar, but rather a constantly evolving web of sensors, stimulators, data, and models that extend our minds into the machines around us.