Neuron Maps & an Atlas of the Brain

I have been looking into the wide range of brain maps created and disseminated by the Allen Institute for Brain Science in their publicly available Brain Atlas. The atlas, which has its own website, contains a huge amount of information on both human and mouse brains, including 3-D maps of adult and infant brains, data on gene activation in specific areas of the brain, and information on over 200 individually mapped neurons.

It is this latter set of maps that I have been exploring and trying to make sense of. They are part of the Brain Cell Database, which the Allen Institute describes as “a survey of biological features derived from single cell data, from human and mouse.” To create this database, the Institute has relied on samples from brain surgeries taking place in the Seattle area. Patients undergoing surgery for epilepsy or brain tumors often have small amounts of healthy brain tissue removed in the course of surgery; some of these patients can then choose to have this tissue passed on to the Allen institute. The institute, in turn, isolates individual neurons, testing their responses to electrical stimuli and creating morphological models of some neurons. The data currently available on the institute’s website comes from the brains of 36 donors, each of who has donated 1 to 26 brain cells.

The Brain Atlas website also contains a Cell Feature Search page, which allows anyone to look through the database of individual neurons and to refine their search based on a wide variety of criteria, incuding species (human or mouse), disease (epilepsy or tumor), and part of the brain (frontal lobe, temporal lobe, etc).  In my search through the database, I found myself most interested in the neurons from human brains that had available both electrophysiological data and morphological data.

This is an example of the kind of map you can get of a single neuron:

The top image shows the morphological information on a neuron taken from a 67-year-old man. The first two images show front and side projections of the neuron, while the third shows a 3-D model that can be rotated and zoomed in on. The bottom images shows the electrophysiological data from the same neuron. In the screenshot, data on all types of electrical stimuli are all being shown at once, but on the actual page you can have the visualization only show certain types of stimuli or individual tests (just one electrical shock and the resultant cell response).

I find these visualizations of individual neurons to be fascinating, even though, unfortunately, I don’t have the type of biological literacy required to fully understand their significance. The articles I’ve read on this project say that this work is part of a larger effort to create an atlas of the types of cells present in the human brain, based on their shape, physiology, connective properties, and gene expression (1). John Ngai, one of the researchers on the team, says that their task is to understand how all the different types of brain cells “wire up, to serve as a basis for understanding how the human brain functions in health and disease” (2). The work done to map and categorize the mouse brain, as well as the less comprehensive work done on the human brain, can be used to better understand neural pathways, as well as the roles of different cells take in making the brain function.

My interest in these neuron maps is not only in their scientific utility, however. The maps are also interesting because they are beautiful and engaging. In my explorations of different neurons I found myself having strong reactions to the maps – some seemed exciting, intriguing, others grossed me out with the density of their axons.  The neural maps are highly suggestive; they resemble rivers, cities, veins, roots. Their irregularity is both familiar and unfamiliar, and the images they create are both highly specific (a single neuron in a specific person’s brain) and easily abstracted.



I find the many potential approaches to and uses for these maps to be a strength of theirs, to a degree. However, I also think that the sheer volume of data included, not only in the neuron maps but in the Brain Atlas as a whole, makes the project difficult to approach and understand, even if you’re only trying to understand part of it. As a layperson, I had to do a few hours of research and reading on the project to even begin to understand what types of data these maps contain and why it is important. The website is clearly geared towards people involved in the field and people who are conducting research on brain structure and function – even the summarizing Data Highlights page is mostly made of headings like “Mouse Connectivity BDA/AAV Comparison.” I don’t think that the Brain Atlas website should necessarily have to be accessible to laypeople – the goal of the Institute isn’t to engage beginners in science but to advance high-level research – but on a personal level I wish it was more accessible. In the future, I would love to see more elements of the website that offer more straightforward ways to approach some of the huge amounts of data available, even if its just map keys with a link to an explanation of the difference between dendrites and apical dendrites.

These maps have prompted me to think more about my own atlas project and what makes a map enjoyable to engage with. I’ve realized that the maps I personally enjoy the most are often maps that draw you in and make you want to explore the many ways of engaging with them. While there is definitely a space in the world for clear, straightforward maps, I think that there is also a simple joy in getting lost in a complex map, in figuring out what everything means and imagining the many ways you could wander through it.

My personal mapping work has involved taking a personal, small-scale approach to feelings of fear and enjoyment, both in the consumption of media and in everyday life (and in the places where these types of experiences intersect). My exploration of the neuron maps has encouraged me to consider the pleasure involved in reading and interacting with a multifaceted, multilayered map, and I have been reflecting on the ways I could incorporate this type of density in my own maps. For my prototype, I made a small, strip-map style map of the route I take when walking or biking from my house to the town I live in (Pleasantville, NY). I then overlaid four pieces of clear film on the map and noted different kinds of experiences I have with on my walk on each – places I enjoy passing or feel safe in, places that make me anxious or scared, places that I have rich imagined stories about, and a depiction of the routes I usually take. I like the way that the information, when separated this way, can be selected and interacted with.