After providing all the funding for The Brain from Top to Bottom for over 10 years, the CIHR Institute of Neurosciences, Mental Health and Addiction informed us that because of budget cuts, they were going to be forced to stop sponsoring us as of March 31st, 2013.

We have approached a number of organizations, all of which have recognized the value of our work. But we have not managed to find the funding we need. We must therefore ask our readers for donations so that we can continue updating and adding new content to The Brain from Top to Bottom web site and blog.

Please, rest assured that we are doing our utmost to continue our mission of providing the general public with the best possible information about the brain and neuroscience in the original spirit of the Internet: the desire to share information free of charge and with no adverstising.

Whether your support is moral, financial, or both, thank you from the bottom of our hearts!

Bruno Dubuc, Patrick Robert, Denis Paquet, and Al Daigen

Thursday, 11 February 2021
Revisiting an optical illusion in terms of predictive processing

I recently came across a little experiment that I posted years ago on this website to show how the blind spot in each of your eyes works. The blind spot is a part of the retina where there are no photoreceptors, because it is where the axons of the retina’s ganglion cells converge and exit the eye, forming the optical nerve. As a result, there’s a corresponding area in your field of vision that doesn’t register on the retina. Hence, in theory, you shouldn’t see anything there. But in reality, you don’t see any such blank spot in your field of vision.

To find out why not, let’s revisit this optical illusion from the standpoint of predictive-processing theory, which has become more and more accepted in cognitive science over the past 10 years or so. In the traditional view, the brain passively waits to receive inputs, then processes them and ultimately produces outputs, as if it were nothing more than a biologically based computer. In contrast, according to predictive-processing theory, the brain is a proactive organ that is constantly making predictions about its environment and what may be about to happen there, so as to operate within it more effectively.

According to predictive-processing theory, the reason that you don’t notice your blind spot is that your brain makes you blind, so to speak, to the blindness in that part of your field of vision. It does so by filling this area in with the visual information that is most likely to occur there, according to the experience of the world stored in your memory.

The two graphics above give you two ways of experiencing your blind spot.

For the top graphic, close your right eye, look at the + sign with your left eye, then move your head toward or away from the screen slowly while continuing to watch the + sign. The big black dot will disappear as it passes through the blind spot of the retina of your left eye, because your brain projects the surrounding white background onto the corresponding spot in your field of vision.

For the bottom graphic, do the same thing. This time, when the image is at the right distance from your eye, the two lines will look like one solid line. This seems like pure magic, until you apply the theory of predictive processing to explain it: the brain predicts what is most likely to appear in the space between the two lines—a continuation of them—and inserts it there!

You can readily imagine the evolutionary advantages of your brain’s operating in this way. Most of the signals that it receives from the outside world involve a certain degree of ambiguity. If your brain couldn’t project its predictions about the world based on your past experiences, you might, for example, have to wait until the catlike form jumped out of the high grass on the trail ahead of you before you recognized it as a tiger. By then it would probably be too late to run. If your humanoid ancestors’ brains had worked like that, you might not be around here now to worry about it.

The Senses | Comments Closed

Thursday, 14 January 2021
Being rich makes you less empathetic (even when it’s just Monopoly money)

Today I’m going to talk about the work of social psychologist Paul Piff, whose research interests revolve around social hierarchies, economic inequality, altruism and co-operation. I learned about Piff while working on a French-language documentary inspired by the book Capital in the 21st Century, by French economist Thomas Piketty. In this documentary, Piff explains an experiment in which people playing the board game Monopoly showed disturbing changes in behaviour when they won repeatedly because the researchers had rigged the rules in their favour (more money to begin with, more dice to roll to pass Go more often, etc.)—in other words, had given them more power. I have touched on this same subject in an earlier blog post, about Dacher Keltner’s research on how wealth alienates the wealthy from their humanity. And it turns out to be no accident that these two authors’ findings are so consistent: as I just discovered this morning, they have published many articles together! (more…)

Emotions and the Brain | Comments Closed

Monday, 14 December 2020
Using science to create art.

Some scientists use science to create art. One good example is Greg Dunn, a neurobiologist and visual artist. They are a startling combination of the precise images captured by neuron-imaging technology and the traditional techniques of Japanese ink-wash painting, also known as sumi-e.

More recently, I have discovered the impressive image of David Goodsell, who transforms deadly viruses into stunning works of art. Goodsell is a biologist who studies the molecular structure of cells at Scripps Research in San Diego, California. The watercolours that he paints with such precision represent the molecules that compose human cells and the bacteria and viruses that attack them constantly (such as the HIV, Ebola and Zika viruses below, as well as coronaviruses). (more…)

From the Simple to the Complex | Comments Closed

Friday, 13 November 2020
Serious problems in the reproducibility of brain imaging results

As I’ve pointed out in previous posts, the results produced by brain-imaging technologies such as fMRI are subject to at least two limitations. First. they detect neural activation only indirectly, by monitoring blood flows in the brain. Second, the methods used to analyze such images are subject to many forms of bias. These limitations were confirmed in a troubling study by Tom Schonberg, Thomas Nichols and Russell Poldrack, entitled “Variability in the analysis of a single neuroimaging data set by many teams ”, published in the May 20, 2020 issue of the journal Nature. (more…)

From the Simple to the Complex, From Thought to Language | Comments Closed

Monday, 26 October 2020
Behaviour as a control loop located outside the organism

With his famous Chinese Room Argument, philosopher John Searl raised an important question: can a computer understand Chinese (or French or English)? Probably not, if the results of some of today’s computer-translation programs are any indication. Unlike computers, we human beings can usually grasp the meaning of things fairly effortlessly, while a computer cannot. Many neuroscientists believe that to explain why, we must look more closely at the biological substrate of the brain, and in particular its long evolutionary history. (more…)

Uncategorized | Comments Closed