How Long Before We Can Print a Human Brain in 3-D?

The human brain is an intricately complex organ — perhaps the most complex single structure in the universe. Today, human brains simply “make themselves” in the course of human development. But what if we could print exact working “replicas” of the brains of famous persons, such as Albert Einstein?

3-D printers are already making exquisite human prostheses, and the 3-D print production of custom bone, joint, and tooth implants will soon become commonplace. 3-D printed automobiles will be available before 2020, 3-D printed homes by 2020, 3-D printed habitats on the moon will be possible by 2025, and entire human organs should be routinely printed in 3-D by 2030. Source . . . Bioprinting at University of Virginia

But the human brain is orders of magnitude more complex than other human organs. Here is a brief overview of the human connectome, and how it “makes itself.”

Nerve Fibres Human Brain Sagittal midline

Nerve Fibres Human Brain Sagittal midline

Brain function depends critically on precisely specified patterns of wiring between neurons, and failures of wiring can compromise normal function. This wiring develops during early life as axons grow and navigate to find their appropriate targets, often over long distances. Axonal navigation is guided by spatial patterns of molecular cues in the developing brain. Over the past two decades major advances have been made in identifying the genes and molecules that comprise these molecular cues (O’Donnell et al, 2009), and mutations in these genes are now known to be associated with a variety of brain disorders (Stoekli, 2012). In addition, appropriate regeneration of axons is important for recovery of function after injury, and it is thus critical to understand how to promote regrowth of axons after damage to the adult nervous system (Harel & Strittmatter, 2006).

Axonal navigation is guided by the growth cone at the axonal tip (Gordon-Weeks, 2005; Lowery & Van Vactor, 2009), and also sometimes by selective branching from the axon shaft. Molecular cues in the environment are transduced by receptors on the growth cone and shaft, and converted into changes in the cytoskeleton that generate movement. These molecular cues often take the form of concentration gradients, so that many examples of axon guidance can be seen as a form of chemotaxis. One particularly common type of axon guidance is the generation of topographic maps, whereby nearby neurons in the input structure map to nearby neurons in the target structure. …

… Some important questions include understanding better the signal transduction mechanisms that convert an external cue into directed movement, and how multiple different cues interact to determine guidance decisions in vivo.

Another important emerging area is understanding the role mechanical forces play in axon guidance (Franze, 2013). Growth cones can sense mechanical tension, and their growth is affected by substrate stiffness. Recent advances in technologies for controlling substrate stiffness, and measuring the forces involved, will make it possible to directly assess the degree to which mechanical forces work together with molecular cues to shape brain wiring in vivo. __

Human Brain Connectome Coronal View

Human Brain Connectome Coronal View

the first axons that appear in the developing brain grow in a largely axon-free environment, navigating superficially through undifferentiated neuroepithelial cells. These early axons are termed “pioneers,” and are thought to lay down the path followed by later growing axons (Easter et al. 1994). Later arriving axons tend to fasciculate with the pioneers through an established “scaffold” that provides a basic framework for “follower” axons. Time-lapse studies have shown that the growth cone morphology, behavior and actin dynamics of pioneer axons are distinct from those of the follower axons, that are less complex, grow at a higher speed through choice points, and have higher actin dynamics (Bak and Fraser 2003; Kulkarni et al. 2007).

Human Brain Connectome Transverse View

Human Brain Connectome Transverse View

,,, What is established is that throughout the neuraxis both attractive and repulsive guidance mechanisms operate to guide axons. In the forebrain, midbrain and spinal cord, Draxin acts as a repellent (Islam et al. 2009; Naser et al. 2009) expressed by the roof plate in the spinal cord and the glial wedge in the forebrain. Molecules of the Neuropilin and Semaphorin families mediate guidance through both attraction and repulsion and play an important role in the guidance and positioning of the corpus callosum and anterior commissure (Falk et al. 2005; Niquille et al. 2009; Piper et al. 2009; Hatanaka et al., 2009). Netrin1 acts as an attractant for corticofugal (Metin et al. 1997; Richards et al. 1997) and thalamocortical pathways (Braisted et al. 2000). These tracts, as well as many of the other commissural projections in the brain, are affected in both Netrin1 and DCC mutant mice (Serafini et al. 1996; Fazeli et al. 1997). In the visual system Netrin1 guides axons at the optic disk to enter the optic nerve (Deiner et al. 1997). Slits have been shown to act as chemorepulsive signals for decussating axons at the optic chiasm (Erskine et al. 2000; Plump et al. 2002) as well as callosal axons (Shu and Richards 2001; Bagri et al. 2002; Shu et al. 2003c) but their role in mediating the guidance of other forebrain commissural projections has not been thoroughly investigated. In a number of systems Slits and their receptors, Robos, have also been shown to regulate the fasciculation of axon tracts. As described earlier, the formation of pioneering axon tracts in the brain allows for later arriving axons to use the pioneers for guidance by fasciculating with these axons. Fasciculation occurs through axon–axon interactions and may be mediated by cell adhesion molecules (CAMs), such as NCAM, L1-CAM or TAG-1 or through receptor homophilic interactions between axons mediated by Robo or Eph receptors. __

The image below displays simple connections between the retina and the superior colliculus. It looks simple, but if you consider the entire brain “connectome,” one learns to be humble.

From Colliculus to Retina Scholarpedia

From Colliculus to Retina

There is compelling evidence that many psychiatric disorders have their origins in disturbed neurodevelopment, resulting in altered connectivity [1,2] …

The establishment of the circuitry of the brain follows an intricate developmental programme involving cell fate specification, cell migration, axon pathfinding, target selection, and synaptogenesis [4]. The last four of these processes are mediated by small numbers of molecules in highly dynamic cellular substructures such as filopodia and dendritic spines [5]. As such, they are subject to a significant amount of noise at the biochemical level [6], because of fluctuations in the amounts of specific proteins, for example [7]. The complexity of the system as a whole results in buffering of this noise to give a reproducible developmental outcome [8]; in engineering terms the system is “robust” [9]. This robustness is due not only to molecular redundancy, but also to the involvement of multiple parallel pathways at each “choice point” (“degeneracy” [10,11]). Removal or alteration of many components individually may thus have little effect but will tend to sensitise the system to alterations in other components or to environmental stresses. __

Printing the connectome will be difficult enough, but if you consider all the other structures in the brain besides the white matter connectome — massively interconnected grey matter nuclei, several varieties of cortical tissues, glial substructures, venous and arterial vessels, capillaries!!!, cerebrospinal fluid apparatus and pathways etc. — we begin to understand the qualitative complexity involved. But if we consider that the average brain has about 85 billion neurons, with 100 quadrillion neuron – neuron interconnections (not to mention capillaries!), the fine quantitative aspect of the project becomes clearer.

Timeline of Brain Development Processes Wikipedia

Timeline of Brain Development Processes

Brain construction in the fetus and infant proceeds in stages. The formation of brain structures and connections is heavily influenced by the genes, but also by environmental factors such as nutrition, exposure to drugs and hormones from the mother’s blood or milk, possible physical injuries, and other factors beyond the control of the fetus or its genes.

As different parts of the brain develop, they become primed for specific types of learning. Such learning paves the way for future learning in later developing parts of the brain, or in the brain as a whole.

The impact of training or experience is not the same at all points in development. Children who receive music lessons, or learn a second language before age 7–8 are more proficient as adults. Early exposure to drugs or trauma makes people more likely to become addicted or depressed later life. Rat pups exposed to specific frequencies from 9 to 13 days post-partum show expanded cortical representations of these frequencies. Young birds must hear and copy their native song within 1–2 months of birth or they may never learn it at all. These are examples of sensitive periods: developmental windows where maturation and specific experience interact to produce differential long-term effects on the brain and behavior…

… experience-dependent behavioral or brain plasticity accrued during one sensitive period can serve as a scaffold on which later experience and plasticity can build.

Sensitive Developmental Periods

Sensitive Developmental Periods

Research into sensitive periods—or the interaction between development and specific experience—has entered a new phase as evidenced by the range of contributions brought together in this volume. Until very recently, sensitive periods were considered to be relatively narrow phenomena, often associated with the acquisition of specific perceptual abilities. This narrow definition has now evolved into a broader concept suggesting that the timing of individual experience interacts with developmental changes in the brain to produce synergistic effects on perceptual, cognitive, and motor function. __

The phenomenon of sensitive and critical periods of brain plasticity is an important aspect of brain formation and maturation. If the brain is properly trained during these periods, the future range of the child’s competencies will be expanded significantly.

Across multiple sensory systems, learning and plasticity during sensitive periods is a “bottom-up” process, characterized by a perceptual narrowing in which perceptual discrimination and underlying neural representations become increasingly selective in their responsiveness to environmental input (Werker and Tees, 1984; Scott et al., 2006, 2007; Kuhl and Rivera-Gaxiola, 2008). It is this initial under-specification of neural systems that is thought to drive the rapid changes that are observed during this time in response to exposure to environmental stimuli (Knudsen, 2004). Within the auditory system, perceptual narrowing during specific sensitive periods in development characterizes how infants learn to group speech sounds into language-specific phonetic categories (Werker and Tees, 1984), process culture-specific musical rhythms (Hannon and Trehub, 2005a,b) and harmonic relationships (Lynch et al., 1990), as well as encode basic auditory features in the primary auditory cortex A1 (Zhang et al., 2002). __

Age of Cortical Peak Development by Region

Age of Cortical Peak Development by Region

Normally-developing infants can learn any of the world languages as nicely stated by Patricia Kuhl: “children are born citizens of the world” (Kuhl, 2002). Unfortunately, this wonderful ability seems to quickly disappear as shown in an elegant experiment by Cheour et al. (1998). These authors used the well-known Mismatch Negativity (MMN) paradigm (Näätänen et al., 1978) to test for the idea of a sensitive period in phoneme perception. Results showed that by one year of age, Finnish phonemes had acquired a special status for Finnish children compared to a phoneme (in Estonian) that did not belong to the Finnish phoneme repertory. These results are clear evidence in favor of an early critical period for phoneme acquisition.

… _

As we can see from the above images and excerpts, the brain continues developing into the 3rd decade, or the “twenties.”

In addition, throughout brain development, the growing and maturing brain is constantly immersed in information and sensations from the rest of the body and the larger world outside. These information pathways are actually two-way, but it is useful to reflect upon the impact upon brain development that the rest of the body (and outside world) plays.

All of this makes our task of printing a 3-D brain all the harder — at least if it is done as a “batch process,” or all at once. How can a 3-D printed brain develop normally — even if it is a “precise replica” of an actual brain — if it is not fed by body impulses, and if it is not allowed to be fine-tuned by experience over the time period of development and maturation? The brain is constantly being shaped by experience.

Perhaps some form of “continuous process” 3-D printing can be developed, to combine construction and experiential fine-tuning over a certain time period. And perhaps enough of a “spinal cord” can be printed and grown integrally with the brain, to allow for a type of embodiment, with body sensations and systems controls.

Alternatively, we may find it better to print the brain of an “infant Albert Einstein,” and implant it into a gene-engineered body — allowing it to experience physical sensations, growth, adaptation, and maturation similar to what normal human infants experience?

A large number of considerations remain to be sorted, including questions of immune compatibility, ideal nature of circulating fluids, and whether to do away with that vulnerable neck, which can often be too easily broken — and more.

But we have plenty of time to consider all of those things. And we may well find that there are better ways of building better brains than using a 3-D printer. Even so, it is the type of challenge that should excite most conventional brains of a curious nature.


Brian Wang looks at a brain nano-imaging approach which may provide early seeds to a far more powerful approach to nano-imaging and nano-printing of the brain in the future.

The current state of nano-printing is rather crude, in comparison to what is needed for our grand project.

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