Category Archives: fMRI

On Anatomy, Physiology & IQ

from reference 1

Although the relationship between Spearman’s IQ test scores (g) and the concept referred to as intelligence can be debated, there is no doubt about the clinical utility of such tests in diagnosing psychiatric disorder. Beyond this, IQ scores say something about human intellect, though perhaps not as much as we’d like.

A study published in the Journal of Neuroscience gives new insight into the biological basis of the subparts of the test, fluid (gF) and crystallizeed (gC) components1. Specifically, using fMRI (a brain-scanning technique which indirectly measures blood-oxygenation and can also be utilized to estimate the size of pieces of brain-tissue), these researchers found that performance on the crystallized component of the test was better correlated with cortical thickness, while the fluid component was better correlated with the magnitude of the blood-oxygenation signal while performing test-tasks.

This finding represents an advance from a study that had previously explored the relationship between overall IQ and the volume/location of grey matter2.

References:
1. Choi YY, Shamosh NA, Cho SH, DeYoung CG, Lee MJ, Lee J-M, Kim SI, Cho Z-H, Kim K, Gray JR, Lee KH. Multiple Bases of Human Intelligence Revealed by Cortical Thickness and Neural Activation. J Neurosci, 28: 10323-10329, 2008.
2. Haier RJ, Jung RE, Yeo RA, Head K, Alkire MT. Structural brain variation and general intelligence. Neuroimage, 23: 425-33, 2004.

On Reading Minds

Nature1

Who hasn’t had the desire to see through another’s eyes? Some researchers at Berkeley think they’ve taken the first steps towards achieving such a goal.

Jack L. Gallant and his lab-mates have managed the feat of decoding human fMRI measurements in such a way that they can infer the image that generated the recorded neuronal activity1. fMRI as a technique assesses brain excitation indirectly, through blood-flow. The degree of excitation is clearly in some way related to the BOLD (Blood-oxygen-level dependent) signal obtained, but it is a bit crude in the sense that it isn’t very spatially or temporally precise2. The data can pinpoint activity to a few square millimeters, and within a window of about 6 seconds.

The paper detailing their results, appearing in Nature, describes how this remarkable trick was accomplished. First, the researchers consulted fMRI signals from subjects viewing a wide variety of natural images. They correlated this information with the pixels in the pictures themselves, and this allowed them to construct a model which predicted the pattern of blood-flow one might observe with fMRI in response to an arbitrary image. Once this was done, they essentially turned the model on it’s head so that they could ascertain the viewed image from the fMRI data. In fact, at present it’s quite a brute force approach that requires that the scientist have a set of images which are fed into the model to generate synthetic fMRI data to compare with the measured signals. However, it is possible that models of this form will eventually be sophisticated enough to avoid this.

If these techniques could, for example, be extended to other forms of mental reckoning, we might some day be able to see into the thoughts of those who are unable to communicate. Regardless of the practical applications, and however far from sneaking a peek the richly textured visual experience we each have, this type of savvy utilization of data and modeling techniques is exciting because it tickles the basic desire we all have to know another’s being.

Notes/References:

1. Kay KN, Naselaris T, Prenger RJ, Gallant JL. (2008) Identifying natural images from human brain activity. Nature, 452;352-355
2. Other technologies sacrifice the large volume of brain space that fMRI can cover for spatial precision (over 10000x better, single cells) and temporal precision (over 100000 times better, though that much is not necessary).

On Believing Yourself

I have always been quite troubled by the fact that I can remember things that never happened. If I am confident that a childhood friend’s name was Paul when it was actually Roger, how am I to be certain that I correctly remember how to perform the act of addition, or my distaste for the texture of most mushrooms?

Perhaps even more troubling is the fact that studies devoted to exploring the interplay between confidence and memory have found that, in general, the memories we’re most confident in are most likely to be authentic1 (see figure, below).

The paradox is fairly clear: how can we be confident in a false memory, if confidence correlates with accuracy?

The authors of a recent study suggest, and go a ways towards demonstrating, that two distinct mechanisms are at work, one at work when we express confidence in veridical memories, and one for when we express confidence in false recollections2.

Specifically, these authors use fMRI, and a categorized word recall task, to demonstrate that distinct brain areas are active when we’re sure of veracious retrospection and another when we’re confident in specious anamnesis. The researchers speculate that the latter is due to the familiarity of certain events based on the anatomy of the active sites revealed by the scan (see figure, below).

As a final note, the two areas identified in this study are quite far apart in brain terms, once again pointing to the notion that memory is physiologically and anatomically diffuse. So when you can’t remember your first pet’s name, don’t get too worried, your brain is a big place to search.

References

1. Lindsay DS, Read JD, Sharma K (1998) Accuracy and confidence in person identification: the relationship is strong when witnessing conditions vary widely. Psychol Sci 9:215–218.
2. Kim H, & Cabeza R (2007) Trusting Our Memories: Dissociating the Neural Correlates of Confidence in Veridical versus Illusory Memories. J. Neurosci 27(45):12190-12197