The Brain: Intel Inside?

When I’m not busy studying psychology, playing karaoke or persuing any of the other wonderful pass-times that we find as university students, I do like having a play on the computer. Now, please don’t judge me, I got bored of playing Grand Theft Auto long ago, and I am certainly not addicted to World of Warcraft. I enjoy real computing: programming, making websites, getting stuff to work and so forth.

Cognitive psychology is the study of how information is processed in our minds. It’s a study of knowledge, and how our brain manages “attention, creativity, memory, perception, problem solving, thinking, and the use of language.” (Neisser, 2009) This type of psychology has developed mostly since the 1950’s, and has been quickened through the use of computers.

The idea of using computers in the study of cognitive psychology is to replicate mental processes to learn more about them. Cognitive theorists have suggested that the mind contains similar logical methods to those of a computer. Ideas have also been proposed, that use neurons and their connections as a model for data structures and neuron firing, and spreading activation as a basis for algorithms. While there is no single computational research method, studies combining computation, mind and brain work together to help us deduce new ideas . (Thagard, 2011)

Critics of the idea say that a computer uses only syntax (instructions) in order to do its job. A computer cannot change its mind, it requires user intervention. The human brain processes are so intrinsic that they cannot be fully defined by a programmer. At best, computational processes interpreting activity can only be assigned to mental processes. It is even argued that the brain is not an information processing device at all (Searle, date unknown) In addition, the rate at which technology advances brings ever changing ways in which we program, meaning new methods of programming can come to light, that disprove previously accepted computational theories. (WikiEd, University of Illinois at Urbana Champaign)

I observe that various cognitive processes can be represented better than others, the deeper processes being naturally harder to replicate. We certainly can use computers successfully to some extent to hypothesize cognitive processes and make predictions. What is interesting to me is that many of these studies began in the 1960’s, when a whole city had ‘a computer’, and programs were punched in to tape rolls. My computer now has a dual core processor, but even eight core processors are widely available. Think about that in the context of how many things the human brain can process at once. And that’s not to mention the advancements in all the other component parts of modern computers. How much more do computers represent the human mind now? And how much more could they?

Can Computers Learn?

From the 1983 film: Wargames


Is Psychological Research Empirical?

Empiricism can be defined as “the doctrine that all knowledge is derived from sense experience.” [1] In other words, it is research that comes through our observations. In a very simple sense, I drop my pen, and I can observe that it falls downwards. This is the empirical evidence that supports the law of gravity. In the Publication Manual of the American Psychological Association, an empirical study is referred to as a report of “original research” (p. 10) Empirical research is important, because it can be verified. Sensual observations can be measured, and tangible readings can be taken.

In psychology, whether our research is empirical or not is controversial. As we seek to form a scientific study, we look to gather empirical data. Often, our data comes from Introspection, where a subject describes their feelings. Immanuel Kant (1724-1804) argued that psychological research could not be considered empirical, because “mental events cannot be quantified” (Fuchs & Milar, 2002). He suggests that these mental events cannot be analysed either in the laboratory, or using mathematical analysis. As these thoughts and feelings are verbally conveyed, and then interpreted by another, meaning can change or become lost, resulting in a game of psychological Chinese whispers.

Kant suggested instead that we should use physical observations, things which can be measured. Indeed not all data is gathered by introspection, and in recent years, technological advances have allowed more and more alternative methods for gathering empirical data.

When studying the brain and the nervous system, extensive methods and tools are now available to monitor activity within these areas. The process of “Single Cell Recording”, shows us how different specialised cells are in place to detect different types of image. This has given us valuable insights on how vision works. (Gleitman, Gross & Riesberg, 2011, p.105) These processes do not use introspection, and deliver more solid results that we can work with.

While these new advances in technology often allow new and more accurate methods of empirical study, I do believe most of our research still involves a form of introspection.

A study on facial emotional expressions revealed that some basic emotional expressions are found across different cultures. (Ekman & Friesen, 1975) In this study, participants were shown faces and asked to categorise each face, as to what type of emotion it was displaying. Participants were given six different emotions to choose from. Based upon this research, a further study was carried out more recently, which used the same method of asking participants to categorise facial emotions, however this time, eye-movement was tracked using modern equipment. (Corden, B.; Chilvers, R. & Skuse, D. 2008) This study found that people’s eyes avoided looking at “emotionally arousing” stimuli, such as “fearful and sad expressions”.

During these experiments, introspection was used, in conjunction with modern technology, in order to assess participant’s perceptions, before further studies and conclusions could be made.

So, are psychological studies empirical? The introspective data is not entirely tangible, it is opinion based. The same stimulus could be described or categorised differently by different people. At the same time, introspection is still a very useful way to gather data. In my view, the question of validity plays a role. Does it measure what it claims to measure? I believe that generally it does. I admit that that will result in the results having a weaker foundation, but in most cases they are sufficiently valid to draw valuable conclusions from.



Alfred H. Fuchs & Katherine S. Milar (2002). Psychology as a Science

Gleitman, Gross & Riesberg (2011). Psychology 8th Edition.

Ekman, Paul & Friesen, Wallace V. (1975). Unmasking the face: A guide to recognizing emotions from facial clues.

Corden, B.; Chilvers, R. & Skuse, D. (2008) Avoidance of emotionally arousing stimuli predicts social–perceptual impairment in Asperger’s syndrome.

Why is Reliability Important?

Last week I read an interesting post on validity, and this week I am going to talk about its brother, reliability. So, why is reliability important? It’s easy when learning about scientific research and writing to feel like we’re given a whole set of rules and standards to follow and stick to, extra bits to think about and boxes to tick, when what we really want to be doing is researching psychology.

Ask Joe Bloggs on the street what he thinks about reliability, and he’ll probably say something like: “Because if your results aren’t reliable then they’ll be wrong”. And he’s right. (Do you not agree?) But are these methods helping us? Or are they a psychological form of ‘politically correct gone too far’?

Reliability and validity come together hand in hand to ensure the results of an experiment are trustworthy, realistic and correctly obtained. Validity is defined as the “extent to which a measure assesses what it is claimed to measure” (p. 261 Howitt, D & Cramer, D 2008), whereas reliability concerns consistency across different times or circumstances. An experiment could produce results which may be valid, and therefore are correctly measured, and could help us draw a conclusion, however they might not be reliable.

Reliability tells us that if one week, an experiment produces results to support hypothesis A, and that then in another experiment, either with a different sample, or a similar (if not the same) sample at a different time hypothesis A is then proven wrong, the results aren’t very reliable, and therefore there is insufficient evidence to draw a conclusion.

Reliability in psychology is often measured using statistical methods. ‘Internal reliability’ refers to how well each data value on a scale measures the concept in question. If the data is reliable, then theoretically any data value used will give the same as any other value, or indeed, all values together. Methods are used, such as ‘split half reliability’, where the first and second halves of results are separated, and then the Pearson correlation for these results is calculated. Other mathematical functions such as ‘Spearman-Brown formula’ and ‘Guttman reliability’ are also used.

More practically, tests can be repeated, either as a simple repeat (‘Test-retest reliability’) or in a different form (‘Alternate form reliability’) however this in turn can adversely affect the results, since the circumstances of participants may change, or memories of the first test can affect how participants handle the second test. Alternate forms reliability attempts to overcome the latter problem, by using a slightly different test, which resolves the issue to some extent.

Internal reliability still works hand in hand with these practical methods of ensuring reliability, e.g. after a repeat test, if we see that the value calculated for internal reliability are different from that of the original test, we can determine that results may not be reliable.

While statistics seem so lifeless, dull and uninteresting, we can see here how mathematical formulas can compensate where practical work falls short, but also vice-versa. Obviously, results must be reliable, and here we have a selection of methods that, when used in conjunction with our scientific judgement can and will help us ensure both validity and reliability of our research.