Why Astronomy Belongs in Human Brain Mapping

Mars, Andromeda, the Pillars of Creation, and Orion may seem far removed from the human brain. Yet the images through which we know them are built by many of the same intellectual and computational disciplines used to map neural structure and function.

What are we actually seeing when we look at an image of Mars, the Andromeda Galaxy, the Pillars of Creation, or the Orion Nebula?

The immediate answer is obvious: a planet, a galaxy, and regions in which stars are being formed. The more important answer is that we are looking at measurements translated into images. Each apparently seamless picture is the final product of instruments, acquisition conditions, calibration, alignment, filtering, integration, reconstruction, color assignment, and interpretation. Its beauty is real, but so is the methodological labor behind it.

The same is true of human brain maps.

An EEG trace is not a neuron speaking directly. A magnetoencephalography map is not a photograph of thought. A functional MRI image does not show neuronal activity itself; it represents physiological changes associated with it. A connectivity map is not a set of anatomical wires laid bare. In each case, a hidden biological process is inferred from an indirect signal. The final map becomes meaningful only through the quality and transparency of the path that produced it.

This is where astronomy and human brain mapping meet. They are both sciences of inference under conditions of distance: physical distance in one case, and biological and measurement distance in the other.

Detailed telescopic image of Mars showing dark surface markings and the bright south polar cap. — **Mars, 15 August 2018,** recorded through a 16-inch telescope and processed by Rafeed Alkawadri. Captured during the decay phase of the 2018 planet-encircling dust event, the image is also a record of observational state rather than of Mars alone. Even a familiar planetary disk is a reconstruction shaped by atmosphere, optics, acquisition, selection, and processing. Open the full-resolution Mars image.

Mars: The Familiar Object That Still Changes With the Measurement

Mars is comparatively near, familiar, and recognizable. Yet even Mars does not present a single, fixed appearance. NASA’s Hubble observations across several decades show differences associated with seasons, viewing geometry, polar ice, clouds, dust storms, and successive generations of cameras. Orbiters, landers, rovers, and telescopes observe the same planet from different positions and through different instruments, each contributing a distinct form of evidence.

A clear planetary image therefore does not eliminate the measurement problem; it makes that problem easy to overlook. Atmospheric turbulence, optical alignment, sensor response, exposure, motion, frame selection, and image processing all influence what becomes visible. Repeated observations help determine which features belong to the planet, which reflect a temporary planetary state, and which arise from the observing system.

The parallel with brain mapping is immediate. A person’s neural signals vary with sleep, attention, medication, movement, disease state, and the task being performed. Recordings also vary with electrode placement, scanner characteristics, environmental noise, preprocessing choices, and the physiological quantity being measured. A finding that appears in one session or one modality may be important, but reproducibility across time, states, and instruments makes it more trustworthy.

Mars therefore offers the first lesson: proximity is not the same as direct access. Even when an object appears familiar, a reliable map requires repeated measurement, calibration, and careful separation of the object from the conditions under which it was observed.

Andromeda: A Unified Image Built From Many Pieces

Hubble photomosaic of the Andromeda Galaxy, with a bright central core, blue outer disk, dark dust lanes, and jagged mosaic boundaries. — **The Andromeda Galaxy as a mosaic.** Hubble’s PHAT and PHAST programs assembled approximately 600 overlapping fields collected over more than a decade—a unified portrait constructed from partial observations. Credit: NASA, ESA, Benjamin F. Williams, Zhuo Chen, and L. Clifton Johnson; image processing by Joseph DePasquale (STScI). Read NASA’s Andromeda source.

The panoramic Hubble view of the Andromeda Galaxy looks like a single, continuous portrait. It is not. NASA describes it as a mosaic assembled from approximately 600 overlapping fields observed over more than a decade. The resulting image contains at least 2.5 billion pixels and resolves an estimated 200 million stars.

Andromeda makes the hidden architecture of image construction visible. Individual observations must be calibrated, spatially registered, corrected, and stitched together. Overlapping regions must agree. Differences in exposure and background must be reconciled. A coherent whole emerges only after numerous partial views have been placed into a shared geometry.

Human brain mapping faces the same problem at several scales. An individual electrode samples only a limited region. A scan captures one person in one state at one time. A group atlas requires brains of different shapes and sizes to be aligned to a common space. Longitudinal studies must determine whether an apparent change reflects biology, motion, instrumentation, or the registration process itself.

Like the Andromeda mosaic, a brain atlas is not simply collected; it is assembled. Its apparent continuity can conceal boundaries between measurements, uncertainties in alignment, and regions that were sampled more densely than others. This does not make the final map artificial or untrustworthy. It means that trust depends on whether the assembly process is visible, reproducible, and appropriately validated.

Andromeda therefore provides the second lesson: a unified map may be constructed from many incomplete observations. The scientific question is not whether a map was processed—it inevitably was—but whether the processing preserved the structures that matter.

The Pillars of Creation: Different Instruments Reveal Different Realities

James Webb Space Telescope near-infrared image of the Pillars of Creation, showing semi-transparent towers of gas and dust surrounded by a dense field of stars. — **The Pillars of Creation in Webb’s near-infrared view.** NIRCam reveals young stars and semi-transparent gas and dust within the star-forming region—structure that differs from, and complements, Hubble’s visible-light view. Credit: NASA, ESA, CSA, STScI; image processing by Joseph DePasquale, Anton Koekemoer, and Alyssa Pagan (STScI). Read NASA’s Webb image source.

The Pillars of Creation provide one of the clearest demonstrations that there is no single, instrument-independent view of nature. In Hubble’s visible-light view, dense dust forms a dramatic dark silhouette. In Webb’s near-infrared view shown here, much of that dust becomes semi-transparent, revealing newly formed stars within and behind the cloud. Neither image is the uniquely correct one. Each records a different interaction between matter, wavelength, and instrument.

This is precisely how brain-mapping modalities relate to one another. Structural MRI emphasizes anatomy. Functional MRI tracks hemodynamic changes associated with neural activity. EEG and MEG measure electrical and magnetic consequences of neuronal currents with high temporal resolution. Intracranial recordings sample local field activity more directly but only where electrodes have been placed. Stimulation introduces yet another form of evidence by testing how the nervous system responds to perturbation.

These modalities should not be expected to produce identical maps, because they do not measure identical phenomena. Their disagreements may reveal limitations, but they may also reveal complementary layers of organization. Just as infrared light can disclose stars hidden in a visible-light image, one brain-mapping method may expose activity or structure that another method cannot detect.

The colors in these images also require intellectual discipline. In astronomy, color may represent wavelengths beyond normal human vision. In brain mapping, color may encode voltage, power, blood-oxygen change, statistical confidence, connectivity strength, or model output. Color makes invisible quantities perceptible, but it can also create an illusion of directness. The color is not the phenomenon itself; it is a visual language used to represent a measurement.

The Pillars therefore offer the third lesson: what becomes visible depends on how we choose to measure it. Multimodal disagreement is not always a flaw to be eliminated. Sometimes it is the evidence that the system has more than one layer.

Orion: Fusion Can Reveal Structure That No Single View Contains

Five-filter Hubble mosaic of the Orion Nebula, showing glowing gas, dust, young stars, and sweeping red, pink, blue, and green structures. — **The Orion Nebula in Hubble’s five-filter mosaic.** Assembled from 520 Hubble exposures, with ground-based observations filling the gaps, the image is itself a reconstruction. A related NASA visualization combines Hubble and Spitzer observations to show how visible and infrared measurements further constrain hidden structure. Credit: NASA, ESA, M. Robberto (STScI/ESA), and the Hubble Space Telescope Orion Treasury Project Team. Read NASA’s Hubble Orion source or compare the visible and infrared views.

The Orion Nebula extends this principle from comparison to integration. The Hubble image shown here is a mosaic assembled from 520 exposures obtained through five filters. In a related NASA visualization, visible-light observations from Hubble are combined with infrared observations from Spitzer. Warm gas, hydrocarbon dust, young stars, shadows, and cavities contribute differently to each view; together, the measurements provide clues to the nebula’s complex three-dimensional organization, in which depth is inferred rather than directly observed.

The combined view is not valuable because it makes two instruments agree perfectly. It is valuable because each instrument constrains the interpretation of the other. Visible light supplies information that infrared lacks, and infrared penetrates structures that visible light cannot. Fusion produces a richer inference than either modality could support alone.

This is also the ambition of multimodal human brain mapping. Anatomy can constrain electrophysiological source estimates. EEG and MEG can add temporal precision to hemodynamic maps. Stimulation can test whether a predicted functional region is clinically consequential. Behavior can determine whether a physiological change corresponds to a meaningful human experience or ability. The strongest map is often not the one produced by the most sophisticated instrument, but the one in which independent forms of evidence converge without concealing their differences.

Orion therefore supplies the fourth lesson: integration should preserve complementarity. Multimodal fusion is not the averaging away of disagreement. It is the disciplined use of distinct measurements to narrow the range of plausible explanations.

A Shared Methodological Language

Across these examples, astronomy and human brain mapping converge on a common set of practices.

Comparison of shared methodological disciplines in astronomy and human brain mapping
Shared discipline	In astronomy	In human brain mapping
Calibration	Separates detector and optical behavior from the incoming signal.	Separates amplifier, scanner, electrode, and environmental effects from physiological activity.
Registration	Aligns exposures, fields, epochs, and wavelengths to a common geometry.	Aligns sessions, modalities, electrodes, anatomy, and individuals to a common space.
Artifact control	Addresses atmosphere, tracking, cosmic rays, glare, and sensor noise.	Addresses motion, muscle, cardiac, device, line-noise, and scanner artifacts.
Integration	Stacks exposures and combines telescopes or wavelength bands.	Combines repeated trials and integrates EEG, MEG, MRI, fMRI, stimulation, and behavior.
Inverse reasoning	Infers the properties and locations of sources from received radiation.	Infers neural sources and networks from fields, signals, and physiological responses.
Visualization	Maps intensity or wavelength into visible form.	Maps physiology, statistics, or connectivity into color and geometry.
Validation	Tests consistency across instruments, epochs, and physical models.	Tests reproducibility across methods, sessions, patients, centers, and clinical outcomes.
Uncertainty	Quantifies confidence in a feature through signal-to-noise estimates, error ranges, and agreement across observations.	Quantifies confidence through intervals, posterior distributions, stability analyses, and replication across models or datasets.

The table reveals why the comparison is more than metaphor. The objects are different, but the epistemic work is strikingly similar. Both fields transform incomplete signals into claims about structures that cannot be inspected directly. Both depend on models. Both can be seduced by beautiful visualizations. Both become stronger when the full path from acquisition to inference is open to examination.

Multimodal brain figure showing intracranial electrode sites and Granger-in and Granger-out connectivity maps across vestibular, motor, sensory, and negative-response stimulation sites. — **Different object, related inference.** Recorded functions, stimulation sites, and directed Granger connectivity reconstructed from intracranial EEG across vestibular, motor, sensory, and negative-response stimulation sites. Figure 2 from Plute, Spencer, and Alkawadri, *Brain Informatics* (2022), 9:30. Licensed under CC BY 4.0; converted to sRGB and resized without altering content. Open the full-resolution brain figure.

Related Methodological Frontiers

This same discipline runs through our work in intracranial EEG and brain–computer interfaces, methodological innovation in MEG, and the clinically responsible use of AI. Each frontier asks how a measurement becomes a trustworthy and useful inference rather than merely an impressive output.

Where the Analogy Ends

The comparison must also retain its limits. A galaxy does not change because it has been measured. The human brain can adapt, learn, compensate, and respond to stimulation. Neural measurements are also embedded in individual lives and clinical decisions. Errors can affect diagnosis, surgery, treatment, identity, autonomy, and privacy.

There is also an important mathematical asymmetry. Direct imaging generally fixes an astronomical source’s angular position on the sky from the incoming radiation, whereas the EEG and MEG inverse problem is non-unique: multiple—and without constraints, infinitely many—source configurations can produce the same sensor-level fields. A usable neural source estimate emerges only after anatomical, biophysical, and mathematical constraints are imposed; those constraints are part of the inference, not neutral scaffolding.

For those reasons, brain mapping requires all the methodological care of astronomy plus additional ethical and clinical accountability. A technically elegant map may still be clinically irrelevant. A statistically reproducible difference may not matter to an individual patient. A model may be accurate on average yet unreliable for the population or decision in which it is used.

Recognizing these differences strengthens the analogy rather than weakening it. Astronomy offers a model of disciplined reconstruction; medicine adds the obligation to connect that reconstruction to human meaning and consequence.

Why Astronomy Belongs Here

Astronomy belongs on a Human Brain Mapping site because it sharpens the central question of mapping: How do we responsibly represent what we cannot observe directly?

Together, these four objects remind us that a map is neither a raw fact nor a mere artistic product. It is a scientific argument made visible.

That principle is as important when looking inward as when looking outward. The value of an astronomical image on a human brain-mapping site is therefore not decorative. It asks readers to pause before the apparent immediacy of any image—celestial or neural—and consider the instruments, assumptions, transformations, and uncertainties that stand between signal and sight.

Different objects, same discipline: do not mistake a beautiful reconstruction for direct reality. Make the pipeline visible, allow independent measurements to challenge one another, and ask which structures remain when the method changes.

Astronomy does not sit at the edge of human brain mapping. Methodologically, it stands beside it.

From Other Worlds to Inner Worlds: Why Astronomy Belongs in Human Brain Mapping