PSY 340 Brain and Behavior Class 13: Research Methods

NOTE: Until the advent of modern technologies [described below] in the late 20th and early 21st centuries, it was not possible to examine directly brain damage in a living human being. As Broca's work showed, brain damage could only be seen at autopsy after the death of a patient.

In the 19th & early 20th centuries, physiologists began to stimulate the brains of experimental animals (dogs in particular) by using an electrical stimulus. This research established that some important areas of the brain were responsible for certain sensory experiences and motor skills.

Computerized Tomography (CT) (formerly called Computerized Axial Tomography (CAT)

Regular MRIs (see above) tell us about the structure of the brain. In the last decade, though, functional MRI (fMRI) scanners can tell us about the functioning or activity of the brain. The scanners detect where blood is being used by focusing upon the hemoglobin molecule which gives up oxygen. This is called looking for the BOLD (= Blood Oxygen Level Dependent) signal.

In an fMRI scan, a baseline structural image (MRI) of the brain is taken. Then, the brain is scanned (1) when it is not doing any task (Scan 1) and then (2) when it IS doing a specific task or activity (Scan 2). Scan 1 is subtracted from Scan 2 in order to identify those areas which are particularly active during the task.

The image to the left shows the brain as an individual is focusing upon a complex moving visual image. The areas highlighted in yellow and orange represent greater levels of activity compared to when the individual is focused upon a blank screen.

Head Movement: A major difficulty with fMRI imaging is the problem of head movement. Even very small motions can cause the wrong areas of the brain to display when someone is doing a task.

Limited Resolution Scale: Another major concern is the impossibility (at least now) to capture the activity of just a small number of neurons (that is, having very high and focused resolution) rather than the functions of many thousands of neurons together. Recent estimates note that cubic millimeter of cortical tissue contains anywhere from 50,000 to 100,000 neurons (e.g., see Shapson-Coe et al. 2021). Until recently, many fMRI studies could only "see" the activity of a volume of brain tissue measuring 3 cubic millimeters. That means, the joint activity of a million or more neurons being measured as a group is the best resolution scale in many past studies. Newer fMRI equipment with much higher magnetic fields are now emerging and the resolution scale is improving.

Brain Size and Intelligence

1. Humans do not have the largest brains across animal species. We do not even have the largest ratio between brain size & body size.

2. Animals with larger brains often have larger neurons so that comparing the volume of animal with human brains is not equivalent.

3. Humans: Brains vs. IQ (Intelligence)

There is a moderate correlation between brain size and IQ tests (r = ~.30-40, which equals explaining about 9% to 16% of IQ differences due to size).

CAUTION: IQ test scores may not be adequate to evaluate "intelligence" which is a notoriously difficult concept to quantify.

Hevern: Intelligence involves those abilities to cope successfully within whatever environments (physical, interpersonal, or cultural) individuals find themselves.

Because IQ tests only measure a range of cognitive functions appropriate for life in an industrialized or economically-developed world, they are not necessarily measures of the full range of coping abilities (=intelligence) that are associated with differing environments.

Males generally do have larger brains than females (roughly 8-10%). However, there are no overall IQ differences between men and women.

Males vs. Females

Differences of specific skills or ability levels between men and women are sometimes found. However, within the context of differing developmental pathways (boys and girls often experience growing up with different opportunities and emphases), many such differences are not biological, but actually cultural, e.g., the superiority of boys in math may reflect the opportunities boys take to take part in activities involving numbers or geometric shapes.

There are differences in the amount of gray vs. white matter across the sexes. Women have deeper & more sulci than men and, despite females brains being roughly 8-10% smaller in volume, there is equal cortical surface for men and women.

Some structural differences have been found in the wiring between female and male brains. The significance of these findings is not clear.

And, when such structural differences are found, it is not immediately clear that there is any relationship between such structural differences and actual behavioral outcome. For example, Liu et al. (2020) reported that males have a larger face processing cortical area than females; yet, studies such as Rennels & Cummings (2013) affirm that women do better than men in actual face processing tasks.

Is there a sex/gender (s/g) difference in the human brain? Except for an overall size difference as noted above, comprehensive meta-analyses of sex/gender brain differences and their relationship to actual behavior shows very little difference. As Eliot et al. (2021) concluded their very broad review of the research literature

Despite clear behavioral differences between men and women, s/g differences in the brain are small and inconsistent, once individual brain size is accounted for. … the present synthesis indicates that such “real” or universal sex-related difference do not exist. Or at best, they are so small as to be buried under other sources of individual variance arising from countless genetic, epigenetic, and experiential factors. Thus, s/g differences in brain architecture may be similar to sex effects in gene-phenotype architecture; while statistically discernable in a very large (>100,000) sample, such effects contributed only 1.4 % to the accuracy of genotype-phenotype prediction...In layperson’s terms, these findings can be interpreted as rebutting popular discourse about the “male brain” and “female brain” as distinct organs." (p. 690)

Deisseroth, K. (2015). Optogenetics: 10 years of microbial opsins in neuroscience. Nature Neuroscience, 18,(9), 1213-1225.

DeWitt, I., & Rauschecker, J. P. (2012). Phoneme and word recognition in the auditory ventral stream. PNAS, published online before print, February 1, 2012. https://doi.org/10.1073/pnas.1113427109

Eliot, L., Ahmed, A., Khan, H., & Patel, J. (2021) Dump the “dimorphism”: Comprehensive synthesis of human brain studies reveals few male-female differences beyond size. Neuroscience and Biobehavioral Reviews, 125, 667-697. https://doi.org/10.1016/j.neubiorev.2021.02.026

Liu, S., Seidlitz, J., Blumenthal, J. D., Clasen, L. S., & Razhahan, A. (2020). Intergrative structural, functional, and transcriptomic analyses of sex-biased brain organization in humans. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1919091117

Rauschecker, J. P., & Scott, S. K. (2009). Maps and streams in the auditory cortex: Nonhuman primates illuminate human speech processing. Nature Neuroscience, 12(6), 718-724. https://doi.org/10.1038/nn.2331

Rennels, J. L., & Cummings, A. J. (2013). Sex differences in facial scanning - Similarities and dissimilarities between infants and adults. International Journal of Behavioral Development, 37(2), 111-117. https://doi.org/10.1177/0165025412472411

Shapson-Coe, A., Januszewski, M., Berger, D. R., Pope, A., Wu, Y., Blakely, T., ... & Lichtman, J. W. (2021). A connectomic study of a petascale fragment of human cerebral cortex. BioRxiv, 2021-05. https://www.biorxiv.org/content/10.1101/2021.05.29.446289.full.pdf