05/13/2016 10:29 am ET Updated Dec 06, 2017

What do your brain maps have in common with Neil deGrasse Tyson's? More than you might think.

One of the cool things about being human is that you know you're you and that you have skills and abilities that others don't have. For example, qualities that differentiate you from astrophysicist Neil deGrasse Tyson and vice versa. Despite the individual abilities of our brains that may make us different from one another, there are also both structural and functional aspects of our brains that we all share. For example, individuals without brain damage each have the same number of lobes in the brain. Additionally, whether you know it or not, we also each have many different types of functional brain maps.

Functional brain maps share a few basic qualities: (1) they are located within particular anatomical locations (e.g. specific places in the front or back of the brain, for example), (2) there is a (relatively) smooth transition from one feature of the map to the next, and (3) they can be identified in brains of different people. For example, one of our primary senses is seeing, and our brains organize visual information into multiple maps. The layout of these maps is similar between people - so similar that recent research has shown that the boundaries of some of these maps can be predicted just from how the brain is folded in a given individual. This means that just given the folding of the back of the brain depicted in the image, the boundaries of multiple visual maps can be defined. They can be predicted in you, in Neil deGrasse Tyson, and whoever your favorite person is as long as they are willing to get their brain scanned as we learned last time.

Visual maps in the brain. This is an example reconstruction of a left hemisphere zoomed in on the back of the brain where the occipital lobe is located (click for hi-res version). Dark gray pixels illustrate dips in the cortex called sulci. Light gray pixels illustrate hills of the cortex called gyri. The different colors (red, green, and blue) represent the portion of our visual world encoded by that cortical location. Your intuition is correct: This map shows that our brains contain an inverted representation of our visual world. The upper (blue) portion of our visual world is represented in the bottom portion of the first visual area (V1), and vice versa. So, when staring at the center of Neil's photograph, the top of his hair would be represented in the blue portion of the maps and the bottom of his tie in the red portion of the maps. Your intuition is correct yet again: We have multiple visual maps in the brain, which we will learn more about together in future posts.

Now, just because we all have these maps does not mean that they are exactly the same between you and me. While the layout of the map is similar from person to person, there are features of the map that may be different. For example, in visual cortex, the size of these maps can vary by a factor of three from one person to the next. Interestingly these size differences have been linked to a person's perceptual ability, where differences in surface area of these maps can predict variability in the conscious experience of individuals.

In future articles, we will learn more about all sorts of different maps that our brain has formed across the senses, and even for different aspects of cognition. Until then, as you walk around the office or wait for a coffee or order a drink from the bar, keep in mind that while the people you see may look and act differently from you, they actually have brain maps that are surprisingly similar to yours. Even Neil deGrasse Tyson.

Kevin S. Weiner is a neuroscientist, as well as member of the Organization for Human Brain Mapping (OHBM) and writes for the Communications/Media Team. The OHBM Media Team brings cutting edge information and research on the human brain to your laptops, desktops and mobile devices in a way that is neurobiologically pleasing. For more information about brain mapping, follow or @OHBMSci_News

Further reading:
Benson et al., 2014 PLoS Computational Biology

Schwarzkopf et al., 2011 Nature Neuroscience

Wandell and Winawer, 2011, Vision Research