This is justified by our previous work showing that chronic alcoholics do not lose neocortical neurons Jensen and Pakkenberg , and by the absence of cases dying with coma, cachexia, or otherwise any prolonged agonal interval. None of the included cases had met exclusion criteria for drug abuse, psychiatric disturbances, diabetes, hypertension, or dementia.
Right or left hemisphere was chosen systematically at random. The frontal-, temporal-, parietal-, and occipital lobes were delineated and painted with different colors of water-proof ink to distinguish the brain regions from each other Pakkenberg and Gundersen The sampled hemispheres were embedded in agar before being cut into 4. All the slabs were then photographed for estimating the total volumes, surface areas, and cortical thickness using point counting, test-lines, and the Cavalieri estimator Gundersen and Jensen Then, 2-mm thick columns i.
About 8—12 rods were subsampled from each cortical lobe before being dehydrated in a gradient ethanol series and randomly rotated around the vertical axis Fig. The seemingly low number of tissue samples required for sampling in one brain is calculated from the principles of systematic, uniform, and random sampling, which allows the investigator to obtain any desired precision. During the preparation of the rods intended for cell counting, extra rods were collected to measure shrinkage before and after processing.
No net shrinkage was detected. To estimate the total cell numbers Gundersen , we used optical disectors, which are 3D probes consisting of an unbiased counting frame Gundersen that can be moved in the z -direction down through the tissue section.
The different cell types were identified by accepted morphological criteria, with neurons having a large nucleus, single dark stained nucleolus and a visible cytoplasm. Oligodendrocytes were small and rounded, with no visible cytoplasm, astrocytes were larger than oligodendrocytes and with a pale nucleus and a granulated appearance, and microglia were small, comma-shaped cells Garcia-Cabezas et al.
Since the cell counts were performed using Giemsa-stained sections, our results are based on cell morphology alone. However, astroglia-, oligodendroglia-, microglia-, and neuron-specific immunohistochemistry has ongoingly corroborated our cell-identification criteria Salvesen et al. A uniform distribution of the cells within the disector height was confirmed by analyzing the z -distribution of particles.
Finally, the total number of each cell type was estimated by multiplying by two, to obtain bilateral numbers. These estimated results can have varying degrees of precision as determined by the investigator indicated by the coefficient of error CE. According to this formula, we are able to adjust the CE to suit the CV by adjusting the amount of sampling. We retrieved the scores from the Danish Conscription Database, which has authorization from the Danish Data Registration Agency to release such data to be used in studies of intelligence and health jr.
The BPP has four subtests, totaling 78 items. The total score for the BPP has very satisfactory psychometric properties Nielsen et al. The 50 men in the sample were born between and , such that their BPP testing occurred during a period with markedly improved BPP performance Teasdale and Owen This was achieved as follows.
Although there is little variation in the age at which IQ was measured, the ages at death ranged between 20 and 52 years. The statistical analyses were performed using SPSS vers. Graphical presentation was completed using GraphPad Prism vers. As can be seen in Table 2 , correlations do not deviate significantly from zero and the confidence limits deviate widely around that value. In our sample of 50 male brains, IQ scores did not correlate significantly with the total number of neurons Fig.
This also applied to estimates of the four separate lobes frontal-, temporal-, parietal-, and occipital cortices; see Supplementary Material. Neither did IQ score correlate significantly with the volumes of white matter Fig. All of these correlation coefficients were less than 0. Finally, the total number of neurons correlated negatively with age of death Fig. Large brains contain not only more neurons, but also more glia cells, more subcortical gray matter and a larger white matter fiber network compared with small brains Marner et al.
The repeated demonstration of a marked genetic contribution to intelligence Bouchard implies some neural basis to variance in intelligence, but the present negative results in our sample of 50 male brains are not consistent with any important association with neocortical neuron numbers but rather could have relation to other factors such as network properties, synapse numbers or other structural components.
One limitation of the present study is the small sample size, and our negative results must be interpreted with caution. Further, cell quantification was performed using Giemsa-stained sections, and our results are therefore based on cell morphology alone. However, neuron-, oligodendroglia-, astroglia-, and microglia-specific immunohistochemistry verified our cell identification criteria. As stated above, various reports correlating IQ-scores to estimates of brain size such as brain weight, head circumference, computed tomography- CT and MR imaging MRI -based brain volume estimates, have shown results with correlations ranging from 0 to 0.
However, the great preponderance of studies on this topic is based on CT and MR imaging, which is uninformative about cell populations. In contrast to many IQ studies, our stereological data did not find that IQ correlates with macroscopic brain weight, volumes, cortical thickness, and surface area estimates. However, while MRI-based volumetric quantification offers high-resolution brain images of living participants, the results from CT or MRI studies cannot always be directly compared with results from physical sections.
For example, Furlong et al. The authors concluded that the major cause for the differences was due to the resolution of the MR images which was not sufficient to always allow reliable delineation of the cerebral sulci.
Further, it should be recognized that the present lack of significant correlation between IQ and brain volumes may reflect the number of brains available for this analysis, which consequently affects the statistical power.
This is a value above most reported studies finding positive brain volume-IQ correlations. Our results found only minor relationships between IQ and neuroanatomical measures obtained from stereological analysis of physical sections.
It may be, however, that dynamic functional measures, such as position emission tomography PET or functional MRI, have greater promise as correlates of intelligence. These methods measure neural metabolism and activity or functional connectivity between brain regions, which maybe therefore have a stronger functional correlation to intelligence as a property of living brains.
However, follow-up studies have produced conflicting results showing both increased and decreased brain metabolism in subjects with high RAPM-scores Neubauer and Fink , Basten et al.
In summary, this is the first study to estimate and correlate the total number of neocortical cells with IQ. In our unique collection of 50 consecutive collected male brains, we found no correlation between cell numbers and IQ. We speculate that this lack of correlation could be due to other factors being more important for IQ such as the neuronal circuit complexity, synapse numbers, or dendritic arborization.
We thank Professor Merete Osler M. Dr Med. Conflict of Interest : None declared. Where smart brains are different: a quantitative meta-analysis of functional and structural brain imaging studies on intelligence.
Dermatol Int. Google Scholar. Bouchard T. Genes, evolution and intelligence. Behav Genet. Design-based stereology: introduction to basic concepts and practical approaches for estimation of cell number. Toxicol Pathol. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.
Researchers say that a remarkable data set on the developing brain adds to the idea that IQ is a meaningful concept in neuroscience. The study, which is published on page of this issue, suggests that performance in IQ tests is associated with changes in the brain during adolescence. Claims that IQ is a valid measure of intelligence tend to attract angry responses, in part because of studies that have attempted to link group differences in IQ with race.
In their book The Bell Curve , political scientist Charles Murray and psychologist Richard Herrnstein argued that the lower-income status of some US ethnic minorities was linked to below-average IQ scores among those groups. These were in turn attributed to mainly genetic factors. Before that, Harvard University entomologist Edward Wilson provoked outrage with work that proposed evolutionary explanations for human behaviour and individual differences in intelligence; critics called the work racist.
And this month, the journal Intelligence printed an editorial note defending its policy regarding the publication of controversial papers. The note comes after a study linking IQ and skin colour D. Templer and H. Arikawa Intelligence 34, —; , published online last November, prompted a string of complaints from scientists. Yet researchers studying IQ say the social climate is becoming more receptive to such studies, in part because it is now widely agreed that cognitive abilities are shaped by environmental factors as well as genetic ones.
The latest result, from a team led by Philip Shaw at the National Institute of Mental Health in Bethesda, Maryland, adds to the debate by linking IQ with changes in the brain over time, rather than fixed attributes such as brain size. Shaw's team tracked a group of more than children as they aged from 6 to 19, running them through a series of cognitive tests — IQ is determined by combining scores from tests of a range of verbal and non-verbal abilities.
The team also measured the size of brain structures using magnetic resonance imaging at roughly two-year intervals: more than half the children had at least two scans, and around a third were scanned three or more times.
When the researchers split the children into three groups according to their initial IQ scores, they noticed a characteristic pattern of changes in the brains of the group with the highest scores. The thickness of the cortex — the outer layer of the brain that controls high-level functions such as memory — started off thinner than that of the other groups, but rapidly gained depth until it was thicker than normal during the early teens.
All three groups converged, with the children having cortexes of roughly equal thickness by age The strongest effect was seen in the prefrontal cortex, which controls planning and reasoning. He made the switch and, with hard work, indeed did well.
IQ is one such ability. Self-control is another. Both help people focus their attention when they need to, such as at school. The brain cells behind executive function are known as the executive control network. This network turns on when someone is taking an IQ test. Many of the same brain areas are involved in fluid intelligence. But personal intelligence is more than just executive function.
They might daydream about a project even while not actively working on it. Although daydreaming may seem like a waste of time to outsiders, it can have major benefits for the person doing it.
When engaged in some task, such as learning, people want to keep at it, Kaufman explains. That means they will push forward, long after they might otherwise have been expected to give up.
Engagement also lets a person switch between focused attention and mind wandering. That daydreaming state can be an important part of intelligence. While daydreaming, a so-called default mode network within the brain kicks into action. Its nerve cells are active when the brain is at rest. For a long time, psychologists thought the default mode network was active only when the executive control network rested.
In other words, you could not focus on an activity and daydream at the same time. To see if that was really true, last year Kaufman teamed up with researchers at the University of North Carolina in Greensboro and at the University of Graz in Austria.
They scanned the brains of volunteers using functional magnetic resonance imaging , or fMRI. This tool uses a strong magnetic field to record brain activity.
As they scanned the brains of 25 college students, the researchers asked the students to think of as many creative uses as they could for everyday objects.
And as students were being as creative as possible, parts of both the default mode network and the executive control network lit up. Rather, Kaufman suspects, the two networks work together to make creativity possible.
And he thinks it is essential for problem-solving. She works at the University of Pennsylvania in Philadelphia. Like many other psychologists, Duckworth wondered what makes one person more successful than another.
In , she interviewed people from all walks of life. She asked each what they thought made someone successful. Most people believed intelligence and talent were important. When Duckworth dug deeper, she found that the people who performed best — those who were promoted over and over, or made a lot of money — shared a trait independent of intelligence.
They had what she now calls grit. Grit has two parts: passion and perseverance. Passion points to a lasting interest in something. People who persevere work through challenges to finish a project. Duckworth developed a set of questions to assess passion and perseverance. In one study of people 25 and older, she found that as people age, they become more likely to stick with a project.
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