Size does matter: Larger brains can hold more!

Size-mattersA long time ago in a galaxy far, far away, people didn’t have mobile phones to store their phone numbers in. People actually had to use their own memory to store these long numbers. But getting these numbers into long-term memory could be a real pain. People had to write the number down, say it over and over again to themselves and with each verbal iteration, something annoying would happen – the number would fade out of memory. To get the number into long-term memory you had to keep repeating the number, over and over again, fast enough to beat the fade away.

This short-term, fast fading memory is called working memory. It’s like the RAM in a computer: it holds everything in your mind ready for action, simulation or a decision. Working memory is related to our IQ and even to some mental disorders, but we don’t know why some people can fit a lot more information into their working memory than others. Yes, it’s very unfair. As I mentioned before in the post on extending your mind, some people can hold huge amounts of information in their mind and even manipulate it, trying out different ideas etc, while other brains or minds can only hold small amounts.

Why do you have the particular capacity you have? How can we investigate these differences between people? It turns out the key to answering these questions is to get people to remember information in only one of their 5 senses, such as vision. By doing this we narrow down the field of things to investigate and can look at the precise brain anatomy related to just that one sense in different people and figure out which parts of your brain allow greater information capacity.

14618772953_45f8cbf809_zThis is exactly what we did in a recent paper from my lab. We found that people with larger brains could hold more temporary information in their mind. Specifically, people with larger visual parts of their brains were the ones who could hold more visual information in their minds. This is interesting for a number of reasons. One reason is it suggests that the physical parameters of our brains set the limits to what we can do with non-physical things like the contents of our mind. In other words, the visual cortex is like a bucket: the larger the bucket the more water it can hold. The larger your visual cortex the more visual information you can hold in mind. With more information in mind, you can do… well, a lot more.

Visual working memory capacity is predicted by anatomical properties of V1.

Visual working memory capacity is predicted by anatomical properties of primary visual cortex.

But all this doesn’t make it any fairer for those that can’t hold much ‘in mind’. The next logical question is: Why do I have a large or small brain? Well, when it comes to visual cortex, data suggests that our genes play a role. The cortex, the outer layer of the brain, is a like a gooey grey sheet that is all wrinkled up on itself. In fact, there are two different components to the size or volume of the primary visual cortex: thickness and surface area. These two different measures seem unrelated to each other, but both have a heritable component. In other words, it seems that your parents or ancestors might have passed your visual cortex down to you, or at least it’s size.

So does all this come down to luck? Well, as with most things, yes and no. There is now some promising research looking at how training or practice can literally change the architecture of your brain.

The now famous book, The brain that changes itself is a great general read on the topic. However, there are many more specific research papers, investigating how practicing visual tasks can change not only your vision, but parts of your brain as well.


Here is the reference and link to our original paper:

Bergmann, J., Genç, E., Kohler, A., Singer, W.A. & Pearson, J. (2014). Neural anatomy of primary visual cortex limits visual working memory. Cerebral Cortex.

Want to know more about all of this? How to measure visual working memory or brain size? Let us know in the comments.

Measuring the mind’s private images

Mental imagery, the voluntary retrieval and representation of sensory information from memory, has a fascinating biography. Historically, mental-imagery research suffered criticism because of methodological constraints caused by imagery’s inherent private nature. Recently, many objective research methods have been introduced that allow a more direct investigation into the mechanisms and neural substrates of mental imagery. These new methods have spurred numerous new discoveries, culminating in a flurry of impactful publications over the past few years.

Although imagery played a distinct role in discussions of mental function for thousands of years, empirical work on imagery did not gain strong traction until the last 30 or 40 years. Despite this recent traction, mental-imagery research has still not enjoyed the same degree of investigative attention that other psychological topics have. For example, this graph, shows that the number of articles published each year tfigure_1hat include the phrase “mental imagery” in the title, compared with those that include “visual attention” or “visual working memory,” is relatively low.

In the 1970s cognitive psychologists started to develop tricky methods to measure and study mental imagery objectively. Some of the early discoveries demonstrated a clear relationship between the content of mental images and the time it took to generate or manipulate them (Kosslyn et al., 1978; Shepard et al., 1971). The larger the imagery manipulation, the longer it took to complete, suggesting a correspondence between imagery and physical space.

More recently, there has been a jump in brain-imaging work investigating mental imagery. A recent trend of analyzing the information content of fMRI patterns (instead of the mean amplitude change) has yielded interesting results. This work is often described as decoding because one of the more popular methods trains an algorithm to decode, or make a prediction about, the experimental condition or task, on the basis of the spatial pattern of the fMRI signal across a brain area.

More recently there has been a jump in brain imaging work investigating mental imagery. A recent trend of analysing the information content of fMRI patterns (instead of the mean amplitude change) has yielded interesting results. This work is often described as ‘decoding’, as one of the more popular methods trains an algorithm to decode, or make a prediction about the experimental condition or task, based on the spatial pattern of the fMRI signal across a brain area (Tong et al., 2012).

Recent work from our lab has demonstrated that imagery can facilitate subsequentperception (Pearson et al., 2008). By separating the period of imagery generation and perception in time, the effects of imagery can be examined without the potential confounds of attention (Carrasco et al., 2004). This work demonstrated that when individuals imagine one of two patterns, that pattern has a much higher probability of being perceptually dominant in a subsequent brief binocular rivalry presentation (Pearson et al., 2008; 2011). In other words, the content of the mental image primes subsequent dominance in binocular rivalry – it changes visual awareness of the rivalry display. Binocular rivalry is a visual phenomenon that occurs when two different visual stimuli are presented one to each eye, such that they are forced to coexist at the same visual location. One pattern tends to be dominant over the other, forcing it out of awareness. Binocular rivalry has been a hugely popular tool to study visual awareness in recent times (Tong et al., 2006). However, this work used rivalry as a tool to measure the sensory strength or ‘visual energy’ of mental imagery, enabling individual episodes of imagery to be assessed in an indirect and objective sensory manner. This discovery is also interesting in its own right, as it demonstrates that what we imagine can literally change how we see the world.

To read more on recent developments in objective methods to measure mental imagery check out the recent paper from which some of the above text was taken:

Pearson, J. (2014). New directions in mental imagery research: the binocular rivalry technique and decoding fMRI patterns. Current Directions in Psychological Science. 23(3), 178-183.


Or catch my upcoming tutorial at the 2014 ASSC meeting: Seeing what’s not there and measuring it: Conscious perception without a stimulus




Carrasco, M. et al. (2004). Attention alters appearance. Nature neuroscience, 7(3), 308–313. doi:10.1038/nn1194

Kosslyn, S. M. et al. (1978). Visual images preserve metric spatial information: evidence from studies of image scanning. J Exp Psychol Hum Percept Perform, 4(1), 47–60.

Pearson, J. et al. (2008). The functional impact of mental imagery on conscious perception. Current biology : CB, 18(13), 982–986. doi:10.1016/j.cub.2008.05.048

Pearson, J. et al. (2011). Evaluating the Mind’s Eye: The Metacognition of Visual Imagery. Psychol Sci. doi:10.1177/0956797611417134

Shepard, R. N. et al. (1971). Mental rotation of three-dimensional objects. Science (New York, NY), 171(3972), 701–703.

Tong, F. et al. (2006). Neural bases of binocular rivalry. Trends Cogn Sci, 10(11), 502–511. doi:10.1016/j.tics.2006.09.003

Tong, F. et al. (2012). Decoding Patterns of Human Brain Activity. Annual review of psychology, 63(1), 483–509. doi:10.1146/annurev-psych-120710-100412