Since the last century, many studies have shown that human intelligence is continuously rising. Scientists have also tried to use a standard value to explain what intelligence is. However, there is currently no unified theory to tell us what intelligence is from the perspective of anatomy and genetics. Scientists are working hard and IQ will continue to improve.
In 1987, James Flynn, a political scientist at the University of Otago in New Zealand, recorded a strange phenomenon: the intelligence of many human groups generally improved over time. Over the past few decades, the average IQ scores of the population in 14 countries have all increased, some of which are even extremely large. Flynn initially suspected that the trend was a test failure. However, in the next few years, more data and analysis have proved that human intelligence does increase with time. People call this trend Flynn Effect. He thinks that the reasons for the increase of intelligence include: the increase of education, the improvement of nutrition, the development of technology, and the reduction of lead exposure, etc.
To understand the Flynn effect, one must first define intelligence. At the beginning of the 20th century, British psychologist Charles Spearman discovered that one can use one’s performance in unrelated intellectual tasks to predict his performance in other tasks. Spearman proposed the standard quantity of conventional intelligence, which he called G, and believed that G was the reason for this commonality.
Now, scientists have proposed the biological mechanism of G level difference between individuals, from brain size and density, synchronization of neuronal activity to overall connectivity of cerebral cortex. However, the exact physiological origin of G is still inconclusive, and researchers cannot explain the differences in intelligence between individuals. A recent cognitive test for 1,475 European teenagers showed that intelligence is associated with a wide range of biological characteristics, including known genetic markers, epigenetic modification of genes related to dopamine signaling pathways, gray matter density in striatum ( key brain regions for motion control and reward response ), and striatum response to unexpected reward cues.
Looking for g
Since the Spearman era, G and IQ tests designed to measure it have proved very reliable. He found that the correlation between different tests is measurable, and now many studies also support this view. Many studies have shown that high IQ is related to high income and education level, as well as lower risks of chronic diseases, disability and early death.
Early research on brain injury patients pointed out that frontal lobe is crucial for human beings to solve problems. In the late 1980s, Richard Haier of the University of California at Irvine and his colleagues recorded brain images of people when solving abstract reasoning problems. He found that the problem-solving process activated specific areas of the frontal, parietal and occipital lobes of the brain and strengthened their connections. Frontal lobe is related to planning and attention. The parietal lobe is responsible for integrating sensory information; The occipital lobe processes visual information – these capabilities are very useful in solving puzzles. However, Haier pointed out that more activities do not mean stronger cognitive ability. ” The person with the highest test score actually has the lowest brain activity, which shows that intelligence does not depend on how hard your brain works, but on how efficient it is.”
A well-known hypothesis supported by brain scans and research on patients with brain damage suggests that intelligence is located in specific neuronal clusters in the brain, mostly in prefrontal cortex and parietal cortex.
In 2007, Haier and Rex Jung of the University of New Mexico put forward the theory of frontal integration, that is, brain regions related to intelligence centers, based on this and other neuroimaging studies. Researchers found that even when people with similar intelligence perform the same psychological tasks, their activation patterns will be different. He said this shows that the brain can solve the same problem in many ways. The person with the highest test score actually has the lowest brain activity, which indicates that what makes you smart is not how hard your brain works, but how efficient it is.
Some people think that the accuracy of existing instruments is not accurate enough to locate G by brain imaging. For example, Haier used PET scanning in the 1980s to track radiolabeled glucose in the brain to obtain an image of metabolic activity, with a period of 30 minutes, and brain cell communication in milliseconds. Modern fMRI scans, although more accurate in time, can only track blood flow through the brain, not the actual activity of individual neurons. Duncan said: ” It’s like trying to understand human language, but what you hear is the noise of the whole city.”
A model of intelligence
Apart from the lack of precise tools, some researchers believe that the key to solving intelligence problems lies in the anatomical structure of the brain. ” 20th century brain research believes that anatomical structure is the most important.” Earl Miller, a neurophysiologist at MIT’s Pikael Institute of Learning and Memory, said, but in the past 10 to 15 years, academics have found this view too simple.
Researchers have suggested that other brain characteristics may also be the foundation of intelligence. Miller, for example, has been tracking brain wave activity generated when multiple neurons discharge simultaneously, which he believes may be related to IQ. In the latest study, he and his colleagues connected electroencephalogram electrodes to the heads of monkeys, which responded when they saw the same object. This task relies on memory and the ability to access and extract relevant information, and this behavior will generate high frequency gamma waves and low frequency beta peaks.
From left to right: brainwaves: harmonics of beta and gamma waves generated by synchronous discharges of neurons in the cortex, which are necessary to complete cognitive tasks; Network neuroscience theory: intelligence comes from the overall communication within the brain; Plasticity: Response of Brain to Changes
Miller speculates that these waves direct the ” traffic” of the brain, ensuring that nerve signals go to the corresponding neurons. Gamma waves are bottom-up and carry what you are thinking about. Beta waves are top-down and carry control signals that determine thoughts, ” he said.” If your beta waves are not strong enough to control gamma waves, your brain will be distracted. ”
The ” whole pattern of brain communication” is another possible explanation of intelligence. Earlier this year, Aron Barbey, a psychology researcher at the University of Illinois at Urbana – Champaign, put forward the theory of network neuroscience, citing relevant research on the connections between brain regions. Bobby is not the first to put forward the view that ” brain area communication is the main cause of intelligence”, but the theoretical model of network neuroscience is more mature.
Emiliano Santarnecchi of Harvard University and Simone Rossi of the University of Siena in Italy also believe that intelligence is the characteristic of the whole brain, but they believe that the plasticity of the whole is the key to intelligence, that is, the ability to reorganize the brain. The brain responds to transcranial magnetic stimulation or electrical stimulation to produce activity, which can be used to measure plasticity, Santanage said. ” Some individuals do not react at the point we stimulate, but react at other nodes in the same network,” he said, while others’ brains ” begin to spread signals everywhere.” His research team found that higher intelligence measured by IQ tests corresponds to more specific network responses. Santanage concluded that this ” partly reflects that the smarter the brain, the more efficient it is.”
G in gene
When neuroscientists explore the basis of intelligence from the structure and direction of brain activity, geneticists are doing research from different angles. So far, Sophie von Stumm, a psychology researcher at the London School of Economics, has estimated that about 25% of individual intelligence differences can be explained by single nucleotide polymorphisms in the genome.
In order to find genes that determine intelligence, researchers scanned the genomes of thousands of people. For example, earlier this year, economist Daniel Benjamin of the University of Southern California and his colleagues analyzed the data of more than 1.1 million European descendants and determined that more than 1,200 loci in the genome are related to educational level, which can reflect intellectual level to some extent. ” Intelligence is highly correlated with academic performance, and genetics shows the same correlation,” said von Stourm, who recently co-authored a review on intelligence genetics. In Benjamin’s research, the contribution of genes to individual educational level difference is 11%; In contrast, the contribution to family income is 7%.
Other genes seem to indicate that intelligence is associated with various brain diseases. For example, in last year’s GWAS preprinted edition, Danielle Posthuma of Amsterdam Free University and his colleagues found negative correlation between cognitive test scores and genetic variation and depression, hyperactivity and schizophrenia. Researchers also found a positive correlation between intelligence-related variation and autism.
Benjamin and his colleagues designed a polygenic score related to educational level. Benjamin said that although this score is not enough to predict an individual’s ability, it should be very useful to researchers. Von Stourm plans to use Benjamin’s polygene score to piece together the mechanism of gene-environment interaction. ” For the first time, we can directly test,” Von Stourm said. ” If children grow up in poor families, they will get less educational resources. If these genetic differences really exist, then educational resources should be allocated according to genetic talents, which will be more efficient. ”
The idea of manipulating intelligence is tempting and there are many attempts. Brain training games were once believed to improve intelligence. Through practice, players can improve their performance in these simple video games, which require skills such as quick response or short-term memory. However, a review of numerous studies shows that there is no convincing evidence that this game can enhance the overall cognitive ability. Now these brain trainings are generally considered to be not worthy of the name.
In recent decades, transcranial brain stimulation through slight electrical or magnetic pulses penetrating the skull has shown the potential to enhance intelligence. For example, in 2015, neuroscientist Emiliano Santarnecchi of Harvard Medical School and his colleagues found that under one mode of transcranial alternating current stimulation, subjects could solve difficult problems faster, while in 2015, a meta-analysis ( research on existing research results ) found that another mode of transcranial direct current stimulation also had ” significant and reliable effects”.
A method known by researchers to effectively increase intelligence is good classical education. In a meta-analysis published earlier this year, a research team led by Stuart Ritchie, then a neuropsychologist at the University of Edinburgh ( currently working at King’s College London ), screened confounding factors from data reported in several studies and found that school education, regardless of age and educational level, increases intelligence by one to five points per year. Researchers including Adele Diamond, a developmental cognitive neuroscientist at the University of British Columbia, are trying to study which elements of education are most beneficial to the brain.
The biological basis of intelligence is still a black box. Not only that, researchers are still trying to recognize the concept itself. Although G’s practicability and predictive ability are widely accepted, supporters of the replacement model believe that it is the average or sum of cognitive ability, rather than the cause of cognitive ability.
A study published last year by Cambridge University neuroscientist Rogier Kievit and his colleagues showed that intelligence is a comprehensive indicator of special cognitive abilities that reinforce each other. Through algorithm prediction, researchers found that the most suitable intelligence model is the mutual benefit model, that is, different cognitive abilities support each other to form positive feedback.
In 2016, Andrew Conway of clermont Graduate University in California and Kristóf Kovács of Roland University in Hungary put forward different views on the multiple cognitive processes of intelligence. In their models, neural networks with specific functions, such as those used to perform simple mathematical or navigation tasks, and advanced overall execution processes, such as decomposing problems into small pieces, all play a role in helping a person to complete cognitive tasks. Researchers believe that, in fact, many tasks use the same execution process, which explains why individual performance on different tasks is interrelated. G to measure the entire complex process from the average level, not just looking at individual capabilities. Kovac said that in order to make greater progress in understanding intelligence, neuroscientists may need to focus on brain features that perform specific processes, rather than the G factor.
When researchers are trying to study thorny intellectual problems, some people say: Is our species smart enough to understand the basis of our own intelligence? Although researchers generally believe that there is still a long way to go to solve this problem, most people are optimistic and believe that there will be important opinions on this problem in the coming decades.
” The current development not only focuses on the mapping of human brain connections, but also begins to focus on synaptic mapping,” Haier said. ” This will bring our understanding of basic biological mechanisms such as intelligence to a completely new level.”