Jamie Hale

Jamie Hale

Sunday, November 14, 2021

Exercise Doesn't Always Improve Cognition...BUT


 Some types of exercise impair components of cognition.

Abstract (Dietrich and Sparling 2004)

“Two experiments are reported that examine the possibility that exercise selectively influences different types of cognition. To our knowledge, these experiments represent the first attempt to study higher-cognitive processes during exercise. Theoretical thinking was guided by the transient hypofrontality hypothesis. In both experiments, athletes who exercised at a sustained, moderate pace were compared to sedentary controls on two neuropsychological tests, one that is generally regarded as heavily dependent on prefrontal cognition and one that is relatively insensitive to prefrontal operation. Results showed that during exercise performance on tests demanding prefrontal-dependent cognition was impaired, while at the same time, cognitive processes requiring little prefrontal activity were unaffected.” 

from the Discussion: 

“The results of the two experiments reported here provide convergent evidence consistent with the hypothesis that prolonged exercise might result in a state of transient hypofrontality.” Transient hypofrontality is a decrease in frontal lobe, particularly prefrontal cortex activity (associated with executive functions- higher order cognitive processes). 

“ At the very least, these results indicate that during endurance exercise different cognitive functions are affected to different degrees”  The endurance protocols used in these experiments show different influences on different aspects of thinking.

“Although several EEG studies have already demonstrated that treadmill running of the same intensity used in the present study reduces prefrontal activity (for a review, see Kubitz & Pothakos, 1997),” It would be highly desirable to replicate the present results in a study that also makes use of physiological measures.” Additionally, other physiological measures such as optical imaging or ERP combined with other selective neuropsychological measures are needed to further explore the complex interaction between exercise and mental function”  Future studies should aim to replicate and extend these findings. A variety of measures can be used. 

“The present findings and the broader theoretical framework have potential implications for the use of exercise in the treatment of depression and anxiety disorders. PET studies have demonstrated that the right ventromedial prefrontal cortex, along with the amygdala and the anterior cingulate gyrus, are hyperactive during depression (see Mayberg, 1997).”  Neuroimaging studies of individuals with anxiety disorders implicate hyper prefrontal cortex activity in  a similar manner. In obsessive– compulsive the prefrontal cortex exhibits hypermetabolism as well. “Given the analytical, emotional, and attentional capacities of the prefrontal cortex, the excessive activity is thought to generate a state of hyper-vigilance and hyper-awareness.”

 

“ Recent advances in psychology and neuroscience have greatly enhanced our understanding of the contribution of the prefrontal cortex to cognition. In the future, this knowledge will allow exercise scientists to ask more specific questions regarding the effects of exercise on cognition.” Specific questions including what type of exercise?- what is the measure of cognition? - is the measure acute or chronic?

full paper  Endurance exercise selectively impairs prefrontal-dependent cognition

Exercise- a foundation of brain health 

Exercise may lead to an array of benefits regarding brain and cognitive health. The finding that some types of executive function may be negatively impacted by some types of exercise doesn’t mean exercise is bad for the brain. In fact, to reiterate, there is a plethora of research showing a range of benefits for brain health and cognitive processes. We should avoid saying or over generalizing and asserting all exercise benefits thinking, but at the same time acknowledging the range of potential benefits that exercise may offer to the brain.

Why is Exercise Good for the Brain?

Computerized brain training games and dietary supplements will make your brain healthier, and you will get smarter—according to companies selling those products. There are many products aimed at improving brain health and cognition, but research is inconclusive regarding the benefits of many of these products. So what has been shown to enhance brain functioning? 

Exercise may lead to better cardiovascular health, stronger bones and muscles, stronger connective tissue, general fitness, athleticism, treatment of type 2 diabetes, treatment of insulin resistance, prevention of osteoporosis, and improved appearance. Better brain functioning is another possible benefit of exercise. Extensive research indicates exercise may offer an array of benefits, including physiological, behavioral, and cognitive (van Praag 2009).  full article 


 

Sunday, October 31, 2021

I am Not Biased- You Are!?

You are biased and so is everyone else. “I am not biased” says the uninformed consumer, researcher, policy maker, minister, spiritual guru, coach, therapist etc....... 

Myside bias: is the tendency for people to evaluate evidence, generate evidence, and test hypotheses in a manner biased toward their own opinions. The weight of evidence doesn’t matter when making decisions or determining belief. It is reasonable to suggest everyone is influenced at some level of bias (conscious and unconscious- not being aware of bias).

Bias Blind Spot

“Research involving the assessment of one’s own biases indicates people often feel that they are less biased than others. Bias blind spot is conceptualized as a tendency to recognize bias in others, while not recognizing bias in ourselves (Pronin et al. 2002). Emily Pronin and colleagues conducted a study that asked participants to rate themselves and others on their susceptibility to a variety of biases. The results indicated across eight biases people felt they were less biased than their peers. In summary, people acknowledge the value of scientific findings on biased processing, but they don’t believe those findings apply to them.

A key factor involved with bias blind spot is placing too much emphasis on introspective evidence (monitoring one’s own conscious processes), despite the tendency for biases to occur unconsciously (below our awareness). Another factor driving bias blind spot is the tendency for people to assume their perceptions directly reflect reality (naive realism), and that those who don’t agree are biased. Indeed, “People’s tendency to deny their own bias, even while recognizing bias in others, reveals a profound shortcoming in self-awareness, with important consequences for interpersonal and intergroup conflict” (Pronin 2007)Full article 

Intelligence & Myside Processing

Toplak & Stanovich (2003) presented 112 undergraduate university students with an informal reasoning test in which they were asked to generate arguments both for and against the position they endorsed on three separate issues. Performance on the task was evaluated by comparing the number of arguments they generated which endorsed (myside arguments) and which refuted (otherside arguments) their own position on that issue. Participants generated more myside arguments than otherside arguments on all three issues, thus consistently showing a myside bias effect on each issue. Differences in cognitive ability were not associated with individual differences in myside bias. However, year in university was a significant predictor of myside bias. The degree of myside bias decreased systematically with year in university. Year in university remained a significant predictor of myside bias even when both cognitive ability and age were statistically partialled out. 
Myside bias was displayed on all three issues, but there was no association in the level of myside bias shown across the different issues  Read more  

Proxies of Intelligence Do Not Predict Avoidance of Myside Bias

In Experiment 1, the researchers concluded, there was "no evidence at all that myside bias effects are smaller for students of higher cognitive ability" (p.140). The main purpose of Experiment 2 was to investigate the association of cognitive abilities with myside and one side bias. "The results... were quite clear cut. SAT total scores displayed a nonsignificant 7.03 correlation with the degree of myside bias and a correlation of .09 with the degree of one-side bias (onebias1), which just missed significance on a twotailed test but in any case was in the unexpected direction" (p.147). It was also revealed that stronger beliefs usually imply heavier myside bias. In Experiment 3 "the degree of myside bias was uncorrelated with SAT scores", and "[t]he degree of one-side bias was uncorrelated with SAT scores" (p.156). Myside bias was weakly correlated with thinking dispositions. One side bias showed no correlation with thinking dispositions. From In Evidence We Trust 2nd Edition  


Sunday, October 10, 2021

Measures in Science

 An instrument can provide accuracy and preciseness but lack value if the measurement is non-valid. When determining the validity of the measurement one must ask does the measurement really measure the concept in question?

The key aspects concerning the quality of scientific measures are reliability and validity (Hale, 2011). Reliability is a measure of the internal consistency and stability of a measuring device. Validity gives us an indication of whether the measuring device measures what it claims to.

Internal consistency is the degree in which the items or questions on the measure consistently assess the same construct. With an internally consistent measure items are positively correlated with each other. This measure of internal consistency is particularly important regarding self-report measures. It isn't as important when considering performance based measures, tests or surveys. Each question should be aimed at measuring the same thing. Stability is often measured by test / retest reliability. The same person takes the same test twice and the scores from each test are compared. Interrater reliability is sometimes used in assessing reliability. With interrater reliability different judges or raters (two or more) make observations, record their findings and then compare their observations. If the raters are reliable then the percentage of agreement should be high.

When asking if a measure is valid we are asking if it measures what is supposed to. Validity is a judgment based on collected data; it is not a statistical test. Two primary ways to determine validity include: existing measures and known group differences.

The existing measures test determines if the new measure correlates with existing relevant valid measures. The new measure should be similar to measures that have been recorded with already-established valid measuring devices. Known group differences determine whether the new measure distinguishes between known group differences. An illustration of known group differences is seen when different groups are given the same measure, and are expected to score differently. As an example, if you were to give Democrats and Republicans a test assessing the strength of certain political views, you would expect them to score differently. Various sub-categories of validity (external, internal, statistical and construct) are also important in some contexts. Validity rating is not overly objective; in fact, it is relatively subjective in some areas. There isn't a perfect validity.

It is possible to have a reliable but not valid measure. However, a valid measure is always a reliable measure,

Often, when using unsystematic (non-scientific) approaches to knowledge measures are not reliable or valid. That is, they do not measure the trait or characteristic of interest consistently nor do they measure what they are intended to measure. Quality scientific approaches generally make great efforts to ensure reliability and validity.

What about Replication in Science??

Replicable (reproducible) findings are important to science; they are a sub-component of converging evidence. When referring to the replication crisis it is important to understand that what is meant- is lack of replicating statistically significant findings. It would be more precise to say there is a "statistically significant replication crisis." Consider replication from another perspective; the original study failed to detect stat...sign.. (using criteria NHST prevalent with use of frequentist stats), but additional studies detect statistical significance.  What would the implications be??  College instructors should make an effort to address this condition- non-significant precedes significant findings. Students are often advised no need to try to replicate non-significant findings, but sign..findings should be replicated. This implies that the non-sign....findings must be accurate (if they occurred first), even though all studies are susceptible to flaws.  Read more 

Learn more about the need for science, rationality and statistics  - In Evidence We Trust  

 

  

 

Monday, April 26, 2021

Nonsense Detection Kit 2.0

The Nonsense Detection Kit 2.0 is a revision of The Nonsense Detection Kit. The contents of the full kit can be found in In Evidence We Trust 2nd Edition.

The impetus for writing the Nonsense Detection Kit was previous suggestions made by Sagan (1996), Lilienfeld et al. (2012) and Shermer (2001). The Nonsense Detection Kit is referring to nonsense in terms of “scientific nonsense”. So, nonsense as it is referred to here refer to “nonscientific information” that is often perpetuated as scientific, when in fact it is not scientific.

The Nonsense Detection Kit provides guidelines that can be used to separate sense from nonsense. There is no single criterion for distinguishing sense from nonsense, but it is possible to identify indicators, or warning signs. The more warnings signs that appear the more likely that claims are nonsense.

Below is a brief description of indicators that should be useful when separating sense from nonsense. These indicators should be useful when evaluating claims made by the media, on the Internet, in peer-reviewed publications, in lectures, by friends, or in everyday conversations with colleagues.

Nonsense indicator- claims haven’t been verified by an independent source

Nonsense perpetuators often claim special knowledge. That is, they have made specific discoveries that only they know about. Others lack know how, or do not have the proper equipment to make the finding. These findings are often reflected in phrases such as, “revolutionary breakthrough”, “what scientists don’t want you to know”, “what only a limited few have discovered”, and so on. These findings are not subject to criticism or replication. That is not how science works. When conducting studies it is imperative that researchers operationalize (provide operational definition- precise observable operation used to manipulate or measure a variable) variables so the specifics can be criticized and replicated. Non-scientists are not concerned with others being able to replicate their findings; because they know attempted replications will probably be unsuccessful. If a finding cannot be replicated this is a big problem, and it is unreasonable to consider a single finding as evidence. It is also problematic when only those making the original finding have replicated successfully. When independent researchers using the same methods as those used in the original study are not able to replicate this is a sign that something was faulty with the original research.

Nonsense indicator- claimant has only searched for confirmatory evidence

The confirmation bias is a cognitive error (cognitive bias) defined as tendency to seek out confirmatory evidence while rejecting or ignoring non-confirming evidence (Gilovich, 1991). Confirmation bias is pervasive, and may be the most common cognitive bias. Most people have a tendency to look for supporting evidence, while ignoring or not looking very hard for disconfirmatory evidence (showing a dislike for disconfirmatory evidence). This is displayed when people cherry pick the evidence. Of course, when you’re a lawyer this is what you need to do. You don’t want any evidence entering into the case that may be incongruent with the evidence you present. However, as a scientist it is important to look for disconfirming evidence. In fact, it has been suggested that a good scientist goes out of their way to look for disconfirmatory evidence. Why look for disconfirmatory evidence? Because when discovering reality is the objective it is necessary to look at all the available data, not just the data supporting one’s own assertions. Confirmation bias occurs when the only good evidence, according to the claimant, is the evidence that supports their claim. Often, perpetuators of nonsense may not even be aware of disconfirmatory evidence. They have no interest in even looking at it.

A study by Frey & Stahlberg (1986) examined how people cherry-pick the evidence. The participants took an IQ test and were given feedback indicating their IQ was either high or low. After receiving feedback participants had a chance to read magazine articles about IQ tests. The participants that were told they had low IQ scores spent more time looking at articles that criticized the validity of IQ tests, but those who were told they had high IQ scores spent more time looking at articles that supported the claim that IQ tests were valid measures of intelligence.

Scientific thinking should involve an effort to minimize confirmation bias. However, science does involve confirmation bias to a degree; this if often demonstrated in publication bias and forms of myside bias. The late Richard Feynman (Nobel Laureate, Physics) suggested that science is a set of processes that detects self-deception (Feynman, 1999). That is, science makes sure we don’t fool ourselves.