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A Priori and Empirical Arguments for Multiple Realizability

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What is the multiple realizability argument?

The multiple realizability argument (MRA) is an argument directed at type-identity theories of mind, while being used for and against functionalist theories of mind. (I think Ross’ 1992 argument in Immaterial Aspects of Thought and Feser’s 2013 arguments refute functionalist theories.) First formulated by Hilary Putnam in 1975, the argument he formulated can be put like this:

P1. If type-physicalism is true, then every mental property can be realized in exactly one physical way.
P2. It is empirically highly plausible that mental properties are capable of multiple realizations.
C1. It is (empirically) highly plausible that the view of type-physicalism is false (modus tollens, P1, P2). (From Just the Arguments, 81. Putnam’s Multiple Realization Argument against Type-Physicalism)

P1 states the scope of type-physicalism—that all mental states are realizable in one and only one physical way. P2 states that it is probable that mental properties are capable of multiple realizations. This premise is an empirical one, and so we need evidence to believe it. Then, the conclusion is that type-physicalism is false sine mental states are multiply realizable. Quite obviously, this argument shows that mental states don’t reduce to brain states, which means that physicalism is false. Since P2 needs defense, I will defend it in this article while giving my own formulation of the MRA.

Here is my formulation of it:

P1: If mental properties were identical to physical properties, then any change in one entails a change in the other.
P2: Mental properties can change without any corresponding change in physical properties.
C: So mental properties aren’t identical to physical properties.

As you can see, like Putnam’s formulation, P2 is an empirical claim and so needs empirical support. So if one mental state can be realized in multiple ways, then type-physicalism (mind-brain identity) is false. I will spend the rest of this article arguing for the truth of P2 and then provide an argument from analogy showing that mental states are multiply realizable.

An a priori argument for multiple realizability

If the MRA were true, then there would be evidence of a specific mental state that is realized in multiple physical ways. While empirical evidence is irrelevant to metaphysical possibility (and to concepts), multiple realizability can be known a priori. Before I give the empirical argument from analogy for multiple realizability, I will give the a priori argument.

P1: Mental states and processes exhibit certain characteristic features and properties like intentionality, subjectivity, and causality.
P2: If mental states are multiply realizable, then they are not reducible to their underlying physical properties.
C: Thus, mental states and processes are not reducible to their underlying physical properties.

Or

P1: M has properties P1, P2, P3…
P2: If M is multiply realizable, then M is not reducible to it’s physical properties.
C: Therefore, M is irreducible to its physical properties.

Premise 1: Mental states and processes are characterized by what they do rather than what they’re “made of.” Intentionality is the ability for mental states to be “about” things, while directed at objects, events or states of affairs like when a belief or proposition is about a certain end goal. So M properties aren’t reducible to any P properties, and intentionality is a property of mental states which set them apart from physical states, since purely physical things can never have the ability to intend. Subjectivity refers to the fact that mental states are experienced through a first-personal perspective which can’t be observed or measured by others. This property sets M states apart from P states, since physical states can be studied and observed from a third-personal perspective. So while we can study brain states, since mental states don’t reduce to brain physiology, then by studying brain states we aren’t studying the mind. Lastly the property of causality refers to the fact that mental states and processes have causal effects on action and behavior, cognition and other mental states and processes. So the distinctive role that mental states and processes play in generating action, behavior, and cognition cannot be captured by studying the brain or the body.

Premise 2: This premise highlights the fact that multiple realizability implies that mental states can be realized in a multitude of physical states and processes without any loss of mental properties. So the Conclusion follows that mental states and processes are irreducible to their underlying physical properties.

So if mental states and processes have characteristic features that distinguish them from other kinds of states and processes, and if they can be realized by multiple physical systems, then they cannot be reduced to one physical system.

Defending P2: Empirical evidence for multiple realizability

The way that Putnam and I have formulated the argument for MR is an empirical claim. So empirical claims require empirical evidence. While the previous argument was a priori, it could therefore be argued without empirical evidence.

The example of visual perception. Most animals on earth have vision. The visual systems of animals have evolved to help them survive in their ecologies. Humans have three cone types in their eyes which allows them to see a range of colors. On the other hand, some birds have four cone types which allow them to see a wider range of color than humans, and the fourth cone thsg birds have allows them to see more colors than humans (Stoddard et al, 2020). Bats have evolved eyesight that allows them to see in low light environments, while eagles have evolved eyesight that allows them to see objects at great distances. So despite differences in the visual systems between animals, they can all recognize objects and visually navigate their ecologies. So different animals have evolved different vision systems that help in a certain niche. Furthermore, different types of photoreceptors have evolved in different animals, with different connections between the eye and the brain, which began evolving around 600 million years ago, with the Cambrian explosion leading to body plans and systems which then supported vision (Lamb, Pugh Jr, and Collin, 2008; Lamb, Collin, and Pugh Jr, 2011; Asteriti, 2015). These photoreceptors come in two kinds—ciliary type (c-type) or rhabdomeric type (r-type); vertebrates seek to have a unique mix of these cone types which allow a wide range of vision (Marshedian and Fain, 2017). Certain eye structures have also evolved independently (Land and Nilsson, 2012). So different animals have different numbers of photoreceptors and cones, which help them to visualize their environment; the diversity of rods and photoreceptors in the animal kingdom is vast (Piechl, 2005). Thus, the evidence cited here shows that different animals have differently-evolved visual systems, but they can still visualize their environments even though the physical systems that allow it are different.

The brain’s ability to compensate from injury and the brain’s of athletes and musicians. After a traumatic brain injury occurs, the brain—being plastic—can rewire itself to carry different functions after an injury. For example, in the blind, the visual cortex is repurposed and processes tactile and auditory stimuli (Elbert et al, 2002; Lane et al, 2015; Gori et al, 2019). The primary motor cortex in musicians is larger than non-musicians, and this is due to constant practice on their instrument of choice (Toyka and Freund, 2006; Watson, 2006; Olszewska et al, 2021). Basketball players have larger cortical areas associated with visual processing and attention (Kim et al, 2022) along with athletes having different cortical neuronal networks than novices (Tan et al, 2017). This then is solid evidence for the claim that learning new skills and continously performing them at an expert level leads to changes in the brain (Park et al, 2015). Further, when it comes to the brain’s ability to heal from an injury, it has been shown that if a certain brain area is impacted, other parts of the brain will pick up the slack of the injured part, which shows the plasticity of the brain and the brain’s ability to compensate for an injury to it by directing and making new neural pathways to carry out new tasks (Nishimura et al, 2009; Su, Veeravuga, and Grant, 2016; Hylin, Kerr, and Holden, 2017). Thus, the evidence cited here shows how the brain can adapt to tasks that a person performs, and how it can adapt to changes to it (like injury) and even repurposing certain parts of itself in people with certain disabilities. This, like the example of visual perception, lends further support for the claim that different physical systems can perform the same mental function.

Brain-computer interfaces. Lastly, we have brain-computer interfaces. These interfaces “acquire brain signals, analyze them, and translate them into commands that are relayed to output devices that carry out desired actions” (Shih et al, 2012). These interfaces allow humans to control things with their thoughts, bypassing the need for physical interfaces; this technology also allows individuals to control certain kinds of devices using brain waves using their mental intentions (Mak and Wolpaw, 2010). People with these interfaces can control prosthetic limbs (Mischenko et al, 2017; Murphy et al, 2017; Asanza et al, 2022). These interfaces have also been explored to give people the ability to communicate with speech again (Brumberg et al, 2010). This also supports MR since brain-computer interfaces which use EEG to record brain activity could translate mental states into movements while interfaces that use implanted electrodes may allow an individual to control a robotic arm. Thus, the development of this technology shows that different mental states can be realized in different physical systems which is then dependent on the type of interface used.

Strappini et al (2020) provide yet more empirical support for MR. They write:

Here, we illustrate some cases that provide empirical evidence in support of MRT. Recently, it has been proposed that foveal agnosic vision, like peripheral vision, can be restored by increasing object parts’ spacing (Crutch and Warrington, 2007Strappini et al., 2017b). Agnosic fovea and normal periphery are both limited by crowding, which impairs object recognition, and provides the signature of visual integration. Here, we define a psychological property of restored object identification, and we cross-reference the data of visually impaired patients with different etiologies. In particular, we compare the data of two stroke patients, two patients with posterior cortical atrophy, six cases of strabismic amblyopia, and one case with restored sight. We also compare these patients with unimpaired subjects tested in the periphery. We show that integration (i.e., restored recognition) seems to describe quite accurately the visual performance in all these cases. Whereas the patients have different etiologies and different neural correlates, the unimpaired subjects have no neural damage. Thus, similarity in the psychological property given the differences in the neural substrate can be interpreted in relation to MRT and provide evidence in its support

While Booth (2018: 143-144) uses the example of multilingualism to support MR:

First, there are multiple ways of speaking a second-language, based on difference between high proficiency early and late bilinguals. Second, there are multiple ways of being a speaker of a given language, specifically as a monolingual or bilingual speaker of that language, where the language is the bilingual speaker’s L1. These examples meet the conditions advanced by Polger and Shapiro for examples of multiple realization, and should therefore be accepted as genuine cases of multiple realization.

Now that I have given a good overview of the evidence in support of MR, I will not provide the argument.

The empirical argument from analogy for multiple realizability

P1: Different animals have evolved different vision systems to suite their ecologies.
P2: Humans have a trichromatic visual system while some birds have tetrachromatic visual system while some insects have compound eyes.
P3: Despite differences in these visual systems, these animals all are able to perform similar visual tasks, like spatial navigation and object recognition.
P4: Studies of brain damage and neuroplasticity show that different brain regions can take on different functions after injury or training, like blind people using the visual cortex for auditory processing, muscisians having larger motor areas for finger control, and basketball players having larger cortical areas associated with visual processing and attention.
P5: The development of brain-computer interfaces show that mental states can be translated into different forms of output, like movement, speech, and text, using different physical devices.
C: Thus, multiple realizability is true, since the mental state of visual perception (and other mental states) can be realized in different physical systems without affecting functioning.


P1: If mental states can only be realized in a single physical system, then all animals with similar cognitive tasks should have identical neural structures.
P2: Different animals have different neural structures for performing similar cognitive tasks, like visual perception.
C: Thus, mental states cannot be realized in a single physical system.


P1: If mental states can only be realized in a single physical system, then all animals with similar cognitive tasks should have identical neural structures.
P2: If all animal with similar cognitive tasks have identical neural structures, then different animals should not have different neural structures for performing similar cognitive tasks.
P3: Different animals have different neural structures for performing similar cognitive tasks, like spatial navigation, object recognition and visual perception.
C: Thus, mental states cannot be realized by a single physical system.

Conclusion

I have provided both an a priori and a posteriori argument for the MRA. The a priori argument shows that multiple realizability is metaphysically possible, while the empirical evidence I have cited along with the empirical premises in my arguments have shown that multiple realizability is an empirically defensible position. It seems to me that it is intuitive that different mental states can be realized by different physical systems and not only one kind of physical system.

The a priori argument shows that mental states and physical states have different properties; physical states cannot have the properties that mental states have. So this shows that it’s metaphysically possible the MR is true, while the empirical evidence and arguments I have mounted show that it is true in our world as well. Mental states can’t be reduced to physical states, mental states are causally efficacious, and there are multiple ways to achieve the same cognitive function, like visual perception across the animal kingdom. The example of visual perception of different animals, studies of athletes, musicians, and people with traumatic brain injuries, and even brain-computer interfaces show that different mental states can be realized in multiple physical ways.

So if this is true, then multiple realizability is true. If multiple realizability is true, then type-physicalism is false, and therefore identity theories of mind need to find another avenue to prove their thesis. Mind-brain identity is clearly false; mind doesn’t reduce to brain and mental states can be realized by different physical systems. This is yet another argument against physicalism—the attempted reduction of mind to brain. Physicalism is quite clearly false.

My Response to Jared Taylor’s Article “Breakthroughs in Intelligence”

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Here is my reply to Jared Taylor’s new article over at AmRen Breakthroughs in Intelligence:

“The human mind is not a blank slate; intelligence is biological”

The mind is not a ‘blank slate’, though there is no ‘biological’ basis for intelligence (at least in the way that hereditarians believe). They’re just correlations. (Whatever ‘intelligence’ is.)

“there is no known environmental intervention—including breast feeding”

There is a causal effect of breast feeding on IQ:

While reported associations of breastfeeding with child BP and BMI are likely to reflect residual confounding, breastfeeding may have causal effects on IQ. Comparing associations between populations with differing confounding structures can be used to improve causal inference in observational studies.

Brion, M. A., Lawlor, D. A., Matijasevich, A., Horta, B., Anselmi, L., Araújo, C. L., . . . Smith, G. D. (2011). What are the causal effects of breastfeeding on IQ, obesity and blood pressure? Evidence from comparing high-income with middle-income cohorts. International Journal of Epidemiology, 40(3), 670-680. doi:10.1093/ije/dyr020

Breastfeeding is related to improved performance in intelligence tests. A positive effect of breastfeeding on cognition was also observed in a randomised trial. This suggests that the association is causal.

Horta, B. L., Mola, C. L., & Victora, C. G. (2015). Breastfeeding and intelligence: a systematic review and meta-analysis. Acta Paediatrica, 104, 14-19. doi:10.1111/apa.13139

before long we should be able to change genes and the brain itself in order to raise intelligence.

Which genes? 84 percent of genes are expressed in the brain. Good luck ‘finding’ them…

These results corroborate with the results from previous studies, which have shown 84% of genes to be expressed in the adult human brain 

Negi, S. K., & Guda, C. (2017). Global gene expression profiling of healthy human brain and its application in studying neurological disorders. Scientific Reports, 7(1). doi:10.1038/s41598-017-00952-9

“Normal people can have extraordinary abilities. Prof. Haier writes about a non-savant who used memory techniques to memorize 67,890 digits of π! He also notes that chess grandmasters have an average IQ of 100; they seem to have a highly specialized ability that is different from normal intelligence. Prof. Haier asks whether we will eventually understand the brain well enough to endow anyone with special abilities of that kind.”

Evidence that intelligence is not related to expertise.

“It is only after a weight of evidence has been established that we should have any degree of confidence in a finding, and Prof. Haier issues another warning: “If the weight of evidence changes for any of the topics covered, I will change my mind, and so should you.” It is refreshing when scientists do science rather than sociology.”

Even with the “weight of evidence”, most people will not change their views on this matter.

“Once it became possible to take static and then real-time pictures of what is going on in the brain, a number of findings emerged. One is that intelligence appears to be related to both brain efficiency and structure”

Patterns of activation in response to various fluid reasoning tasks are diverse, and brain regions activated in response to ostensibly similar types of reasoning (inductive, deductive) appear to be closely associated with task content and context. The evidence is not consistent with the view that there is a unitary reasoning neural substrate. (p. 145)

Nisbett R. E., Aronson J., Blair C., Dickens W., Flynn J., Halpern D. F., Turkheimer E. Intelligence: New findings and theoretical developments. American Psychologist. 2012;67:130–159. doi: 10.1037/a0026699.

“Early findings suggested that smart people’s brains require less glucose—the main fuel for brain activity—than those of dullards.”

Cause and correlation aren’t untangled; they could be answering questions in a familiar format, for instance, and this could be why their brains show less glucose consumption.

“It now appears that grey matter is where “thinking” takes place, and white matter provides connections between different areas of grey matter. Some brains seem to be organized with shorter white-matter connections, which appear to allow more efficient communication, and there seem to be sex differences in the ways the part of the brain are connected. One of the effects of aging is deterioration of the white-matter connections, which reduces intelligence.”

Read this commentary (pg. 162): Norgate, S., & Richardson, K. (2007). On images from correlations. Behavioral and Brain Sciences, 30(02), 162. doi:10.1017/s0140525x07001379

“Brain damage never makes people smarter”

This is wrong:

You would think that cutting out one-half of people’s brains would kill them, or at least leave them vegetables needing care for the rest of their lives. But it does not. Consider this striking story. A boy starts having seizures at 10 years of age when his right cerebral hemisphere atrophies. By the time he is 12, the left side of his body is paralyzed. When he is 19, surgeons decide to operate and remove the right side of his brain, as it is causing gits in his intact left one. You might think this would lower his IQ or leave him severely retarded, but no. His IQ shoots up 14 points, to 142! The mystery is not so great when you realize that the operation has gotten rid of the source of his fits, which had previously hampered his intelligence. When doctors saw him 15 years later, they described him as “having obtained a university diploma . . . [and now holding] a responsible administrative position with a local authority.”

Skoyles, J. R., & Sagan, D. (2002). Up from dragons: the evolution of human intelligence. New York: McGraw-Hill (pg. 282)

“Prof. Haier wants a concerted effort: “What if a country ignored space exploration and announced its major scientific goal was to achieve the capability to increase every citizen’s g-factor [general intelligence] by a standard deviation?””

Don’t make me laugh. You need to prove that ‘g’ exists first. Glad to see some commentary on epigenetics that isn’t bashing it (it is a real phenomenon, though the scope of it in regards to health, disease and evolution remains to be discovered).

As most readers may know, I’m skeptical here and a huge contrarian. I do not believe that g is physiological and if it were then they better start defining it/talking about it differently because I’ve shown that if it were physiological then it would not mimick any known physiological process in the body. I eagerly await some good neuroscience studies on IQ that are robust, with large ns, their conclusions show the arrow of causality, and they’re not just making large sweeping claims that they found X “just because they want to” and are emotionally invested in their work. That’s my opinion about a lot of intelligence research; like everyone, they are invested in their own theories and will do whatever it takes to save face no matter the results. The recent Amy Cuddy fiasco is the perfect example of someone not giving up when it’s clear they’re incorrect.

I wish that Mr. Taylor would actually read some of the literature out there on TBI and IQ along with how people with chunks of their brains missing can have IQs in the normal range, showing evidence that most a lot of our brain mass is redundant. How can someone survive with a brain that weighs 1.5 pounds (680 gms) and not need care for the rest of his life? That, in my opinion, shows how incredible of an organ the human brain is and how plastic it is—especially in young age. People with IQs in the normal range need to be studied by neuroscientists because anomalies need explaining.

If large brains are needed for high IQs, then how do these people function in day-to-day life? Shouldn’t they be ‘as dumb as an erectus’, since they have erectus-sized brains living in the modern world? Well, the human body and brain are two amazing aspects of evolution, so even sudden brain damage and brain removal (up to half the brain) does not show deleterious effects in a lot of people. This is a clue, a clue that most of our brain mass after erectus is useless for our ‘intelligence’ and that our brains must have expanded for another reason—family structure, sociality, expertise, etc. I will cover this at length in the future.

Traumatic Brain Injury and IQ

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What is the relationship between traumatic brain injury (TBI) and IQ? Does IQ decrease? Stay the same? Increase? A few studies have looked at the relationship between TBI and IQ, and the results may be quite surprising to some. Tonight I will look through a few studies and see what the relationship is between TBI and IQ—does IQ decrease substantially or is there only a small decrease? Does it decrease for all subtests or only some?

TBI and IQ

In a sample of 72 people with TBI who had significant brain injuries had an average IQ of 90 (study 1; Bigler, 1995). Bigler also says that whatever correlation exists between brain size and IQ “does not persist post injury” (pg 387). This finding has large implications: can there be a minimal hit to IQ depending on age/severity of injury/brain size/education level?

As will be seen when I review another study on IQ and brain injury, every individual in the cohort in Bigler (1995) was tested after 42 days of brain injury. This does matter, as I will get into below.

Table 1 in study 1 shows that whatever positive relationship between IQ and brain size that is there before injury does not persist after injury (Bigler, 1995: 387). Study 1 showed that, even with mild-to-severe brain damage, there was little change in measured IQ—largely because the correlation between brain size and IQ is .51 at the high end (which I will use—the true correlation is between .24 [Pietschnig et al, 2015] to .4 [Rushton and Ankney, 2009]), this means that if the correlation were to be that high, brain size would only explain 25 percent of the variation in IQ (Skoyles, 1999). That leaves a lot of room for other reasons for differences in brain size and IQ in individuals and groups.

In study 2 (Bigler, 1995: 389-391), he looked into whether or not there were differences in IQ between high and low brain volume people (95 men). Results summed in table 3 (pg 390). Those with low brain volume (1185), aged 28, had an IQ of 82.61 while those with high brain volume (1584), aged 34 had an IQ of 92 (both cohorts had similar education). Bigler showed in study 1 IQ was maintained post injury, so we can say that this was their IQ preinjury.

In table 2, Bigler (1995) compares IQs and brain volumes of mild-to-moderate and moderate-to-severe individuals with TBI. Brain volume in the moderate-to-severe group was 1289.2 whereas for the mild-to-moderate TBI-suffering individuals had a mean brain volume of 1332.9. Amazingly, both groups had IQ scores in the normal range (90.0 for moderate-to-severe TBI and 90.7 for individuals suffering from mild-to-moderate TBI. In study 3, Bigler (1995) shows that trauma-induced atrophic changes in the brain aren’t related to IQ postinjury, nor to the amount of focal lesion volume.

Nevertheless, Bigler (1995) shows that those with bigger brains had less of a cognitive hit after TBI than those with smaller brains. PumpkinPerson pointed me to a study that shows that TBI stretches far back into our evolutionary history, with TBI seen in australopithecine fossils along with erectus fossils found throughout the world. This implies that TBI was a driver for brain size (Shivley et al, 2012); if the brain is bigger, then if/when TBI is acquired, the cognitive hit will be lessened (Stern, 2002). This is a great theory for explaining why we have large brains despite the negatives that come with them—if we were to acquire TBI in our evolutionary past, then the hit to our cognition would not be too great, and so we could still pass our genes to the next generation.

The fact that changes in IQ are minimal when brain damage is acquired shows that brain size isn’t as important as some brain-size-fetishists would like you to believe. Though, preinjury (PI) IQ was not tested, I have one study where it was.

Wood and Rutterford (2006) showed results similar to Bigler (1995)—minimal change to IQ occurs after TBI. The whole cohort pre-injury (PI) had a 99.79 IQ. T1 (early measure) IQ for the cohort was 90.96 while T2 (late measure) IQ for the cohort was 92.37. For people with greater than 11th-grade education (n=30), IQ decreased from 106.57 PI to 95.19 in T1 to 100.17 in T2. For people with less than an 11th-grade education (n=44), IQ PI was 95.16 and decreased to 86.99 in T1 and increased to 87.96 in T2. Male (n=51) and female (n=23) were similar, with male PI IQ being 99.04 to women’s 101.44 with a 90.13 IQ in T1 for men with a 90.72 IQ in T1 for women. In T2 for men it was 92.94 and for women, it was 92.83. So this cohort shows the same trends as Bigler (1995).

The most marked difference in subtests post-injury was in vocabulary (see table 3) with similarities staying the same, and digit symbol, and block design increasing between T1 and T2. Neither group differed between T1 and T2. The only significant association in performance change over time was years of education. Less educated people were at greater risk for cognitive decline (see table 2).

The difference for PI IQ after T2 for less educated people was 7.2 whereas for more educated people it was 6.4. Though more educated people gained back more IQ points between T1 and T2 (4.98 points) compared to less educated people (.97 IQ points). And: “The participants in our study represent a subgroup of patients with severe head injury reported in a larger study assessing long‐term psychosocial outcome.

Bigler (1995) didn’t have PI IQ, but Wood and Rutterford (2006) did, and from T1 to T2 (Bigler 1995 tested what would be equivalent to T1 in the Wood and Rutterford 2006 study), IQ hardly increased for those with lower education (.97 points) but substantially increased for those with higher education (4.98 points) with there being a similar difference between PI IQ and T2 IQ for both groups.

Brain-derived neurotrophic protective factor (BDNF) also promotes survival and synaptic plasticity in the human brain (Barbey et al, 2014). They genotyped 156 Vietnam War soldiers with frontal lobe lesion and “focal penetrating head injuries” for the BDNF polymorphism. Though they did find differences in the groups with and without the BDNF polymorphism, writing that there were “substantial average differences between these groups in general intelligence (≈ half a standard deviation or 8 IQ points), verbal comprehension (6 IQ points), perceptual organization (6 IQ points), working memory (8 IQ points), and processing speed (8 IQ points) after TBI” (Barbey et al, 2014). This supports the hypothesis that BDNF is protective against TBI; and since BDNF was important in our evolutionary history which is secreted by the brain while endurance running (Raichlen and Polk, 2012), this could have also been another protective factor against hits to cognition that were acquired, say, during hunts or fights.

Nevertheless, one study found in a sample of 181 children Crowe et al (2012) found that children with mild-to-moderate TBI had IQ scores in the average range, whereas children with severe TBI had IQ scores in the low average range (80 to 90; table 3).

Infants with mild TBI had IQ scores of 99.9 (n=20) whereas infants with moderate TBI has IQs of 98.0 (n=23) and infants with severe TBI had IQs of 90.7 (n=7); preschoolers with mild TBI had IQ scores of 103.8 (n=11), whereas preschoolers with moderate TBI had IQ scores of 100.1 (n=19) and preschoolers with severe TBI had IQ scores of 85.8 (n=13); middle schoolers with mild TBI had IQ scores of 93.9 (n=10), whereas middle schoolers with moderate TBI had IQ scores of 93.5 (n=21), and middle schoolers with severe TBI had IQ scores of 86.1 (n=14); finally, children with mild TBI in late childhood had a mean FSIQ of 107.3 (n=17), while children with moderate TBI had IQs of 99.5 in late childhood (n=15), and children with severe TBI in late childhood had FSIQs of 94.7 (Crowe et al, 2012; table 3). This shows that age of acquisition and severity influence IQ scores (along with their subtests), and that brain maturity matters for maintaining average intelligence post-TBI. Königs et al (2016) also show the same trend; the outlook is better for children with mild TBI, while children faired far worse with severe TBI compared to mild when compared to adults (also seen in Crowe et al, 2012).

People who got into motor vehicle accidents suffered a loss of 14 IQ points (n=33) after being tested 20 months postinjury (Parker and Rosenblum, 1996). The WAIS-IV Technical and Interpretive Manual also shows a similar loss of 16 points (pg 111-112), however, the 22 subjects were tested within 6 to 18 months within acquiring their TBI, with no indication of whether or not a follow-up was done. IQ will recover postinjury, but education, brain size, age, and severity all are factors that contribute to how many IQ points will be gained. However, adults who suffer mild, moderate, and severe TBIs have IQs in the normal range. TBI severity also had a stronger effect on children aged 2 to 7 years of age at injury, with white matter volume and results on the Glasgow Coma Scale (which is used to assess consciousness after a TBI) were related to the severity of the injury (Levin, 2012).

Conclusion

TBI can occur with a minimal hit to IQ (Bigler, 1995; Wood and Rutterford, 2006; Crowe et al, 2012). IQs can still be in the average range at a wide range of ages/severities, however the older one is when they suffer a TBI, the more likely it is that they will incur little to no loss in IQ (depending on the severity, and even then they are still in the average range). It is interesting to note that TBI may have been a selective factor in our brain evolution over the past 3 million years from australopithecines to erectus to Neanderthals to us. However, the fact that people with severe TBI can have IQ scores in the normal range shows that the brain size/IQ correlation isn’t all it’s cracked up to be.

References

Barbey AK, Colom R, Paul E, Forbes C, Krueger F, Goldman D, et al. (2014) Preservation of General Intelligence following Traumatic Brain Injury: Contributions of the Met66 Brain-Derived Neurotrophic Factor. PLoS ONE 9(2): e88733. https://doi.org/10.1371/journal.pone.0088733

Bigler, E. D. (1995). Brain morphology and intelligence. Developmental Neuropsychology,11(4), 377-403. doi:10.1080/87565649509540628

Crowe, L. M., Catroppa, C., Babl, F. E., Rosenfeld, J. V., & Anderson, V. (2012). Timing of Traumatic Brain Injury in Childhood and Intellectual Outcome. Journal of Pediatric Psychology,37(7), 745-754. doi:10.1093/jpepsy/jss070

Green, R. E., Melo, B., Christensen, B., Ngo, L., Monette, G., & Bradbury, C. (2008). Measuring premorbid IQ in traumatic brain injury: An examination of the validity of the Wechsler Test of Adult Reading (WTAR). Journal of Clinical and Experimental Neuropsychology,30(2), 163-172. doi:10.1080/13803390701300524

Königs, M., Engenhorst, P. J., & Oosterlaan, J. (2016). Intelligence after traumatic brain injury: meta-analysis of outcomes and prognosis. European Journal of Neurology,23(1), 21-29. doi:10.1111/ene.12719

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