Category Archives: EXP6506

Reaction to “Language comprehension and production” by Clifton, Meyer, Wurm, & Treiman (2013)

Reaction to Clifton, Meyer, Wurm, & Treiman (2013) by Richard Thripp
EXP 6506 Section 0002: Fall 2015 – UCF, Dr. Joseph Schmidt
November 19, 2015 [Week 13]

Clifton, Meyer, Wurm, and Treiman (2013) review many themes in current language research. The idea that linguistic rules might be cognitively processed with probabilities, rather than rules (p. 539), seems particularly applicable to English; there are so many oddities and exceptions in English that rule-based processing is often untenable. While we know from Jean Berko Gleason’s research (1958) that young children develop rules fairly early, being able to pluralize the nonsense word “wug,” it may be plausible that a probabilistic approach becomes tenable with a larger database of linguistic rules that is developed in later childhood and adolescence. Having a broader understanding of the language might help us make lexical, semantic, syntactic, and other decisions based on probabilities rather than rules, even for unfamiliar linguistic elements, based on our tacit and explicit memories.

While the authors note that the interactive view of language processing is not falsifiable (Clifton et al., 2013, pp. 539–540), this does not necessarily mean that it is wrong. The modular view is easier to model, conceptualize, and theorize about, and is conveniently similar to how computers and other machines operate. However, the human brain is complex, enigmatic, and far more advanced than computers in many ways—for example, given that unconscious precursors have been found to precede volitional motor movement by as much as several hundred milliseconds (Shibasaki & Hallett, 2006), one might conclude by conventional models that parts of the brain are able to travel backward through time—a manifestly ludicrous conclusion. Adhering to the modular view might be similarly ludicrous. Even “flow” and so-called “a-ha!” moments seem to favor interactive views and preclude modular views, albeit not with respect to language processing. The idea that we may process language in any order, at any time, with any available information, does make the phenomenon difficult to study, unfortunately.

Giving unnecessary information may be easier than paring down our speech output to what is needed (Clifton et al., 2013, p. 536). This is reminiscent of the quote commonly attributed to Mark Twain: “If I had more time I would write a shorter letter.” Unlike other brain processes, the idea of distillation taking more effort and processing power parallels computers; consider simply Phil Katz’s DEFLATE algorithm, commonly used by the Linux gzip function. It takes exponentially more computing power to apply and decode increasing levels of lossless compression to digital data. However, translating or distilling language, particularly spoken language, is an art, and certainly a lossy process, although the degree of lossiness and whether such lossiness is acceptable varies between individuals, dyads, and larger groups. Consider that academics are required to write abstracts for their scholarly articles—a process made arduous merely by severe length constraints. If abstracts were lossless, we would never have to read a journal article, but the abstract would probably take a lot longer to read than the article itself, despite being technically shorter. Therefore, producing a good abstract, a short letter, or effective utterances conveying only necessary information is not easy. While it requires more thought and effort than simply spewing out the necessary information among a sea of garbage, doing too good a job of compressing the required information can backfire, resulting in confusion or requests for reiteration. I can think of times in my life where I have explained something concisely and elegantly, yet unsuccessfully. Success may paradoxically require both lossiness and repetition in unexpected places that vary between individuals and subcultures.


Berko, J. (1958). The child’s learning of English morphology. Word, 14, 150–177.

Clifton, C. J., Meyer, A. S., Wurm, L. H., & Treiman, R. (2013). Language comprehension and production. In A. F. Healy, R. W. Proctor, I. B. Weiner, A. F. Healy, R. W. Proctor, I. B. Weiner (Eds.), Handbook of psychology, Vol. 4: Experimental psychology (2nd ed.) (pp. 523–547). Hoboken, NJ, US: John Wiley & Sons, Inc.

Shibasaki, H., & Hallett, M. (2006). What is the Bereitschaftspotential? Clinical Neurophysiology, 117, 2341–2356. doi:10.1016/j.clinph.2006.04.025

Reaction to “Retrieval practice enhances new learning: The forward effect of testing” by Pastoötter & Bäuml (2014)

Reaction to Pastoötter & Bäuml (2014) by Richard Thripp
EXP 6506 Section 0002: Fall 2015 – UCF, Dr. Joseph Schmidt
November 11, 2015 [Week 12]

This brief literature review discusses the forward effect of testing, which, to me, implies the brain actually changes modes, so to speak, when tested, perhaps becoming more focused and less distractible. This carries over, improving retention for material studied immediately after the test, even if no test is given on the subsequent material. The retrieval explanation (p. 2) may be related. To me, the encoding explanation (p. 2) seems similar to the retrieval explanation, rather than being a distinct counterpoint—the improvements in list segregation following recall testing might be characterized as recoding rather than a retrieval effect. Basically, this would mean that list memories are partly updated upon retrieval, which is a type of encoding similar to the Unix “diff” command or a rolling backup of computer files that only updates files that have been changed. Retrieval would thus enhance memory through the compartmentalization effect the authors’ describe, as well as perhaps an indexing effect similar to a full-text computer search engine, which builds an index of words that speeds search at the cost of increasing data storage and processing requirements. The retrieval process itself may give the brain time to recode memories and compile or improve this index.

The results from studies of testing before misinformation are intriguing; they seem a plausible explanation for the unreliability of eyewitness accounts (p. 3). Though the authors did not discuss implications, I infer that ensuring students have correct understandings of curriculum materials may be more important than generally known. If students are allowed to encode misinformation, whether due to instructor error, vagueness in course material, or student error, it may be especially persistent if testing immediately follows.

Overall, the forward effect of testing is an exciting phenomenon that might help explain other mysteries and improve educational practice, as researchers continue to study it.


Pastötter, B., & T. Bäuml, K. T. (2014). Retrieval practice enhances new learning: The forward effect of testing. Frontiers in Psychology, 5(286), 1–4. doi:10.3389/fpsyg.2014.00286

Reaction to “Test-enhanced learning: Taking memory tests improves long-term retention” by Roediger & Karpicke (2006)

Reaction to Roediger & Karpicke (2006) by Richard Thripp
EXP 6506 Section 0002: Fall 2015 – UCF, Dr. Joseph Schmidt
November 11, 2015 [Week 12]

Roediger and Karpicke (2006) found that students have improved retention when taking memory tests in lieu of studying, which was defined as re-reading a prose passage. Students who were in the repeated study conditions predicted they would perform better, but actually did not. This has many implications for student beliefs and teaching practices; perhaps the practice of only giving 2–3 exams in lecture courses is not ideal for retention, for instance (p. 249).

The big question on my mind while reading the article was: what if the students just had poor reading habits? The only thing we know is that in experiment 2, subjects read each passage about 3.5 times per 5-minute study period, a rate of about 190 words per minute (pp. 250–252), which is reasonable. Unfortunately, we do not know how they were reading the passages. Were they “actively” reading where they highlight, underline, and write notes in the margin? Probably not, given their reading rate is fairly fast. We should ask ourselves rather these results are generalizable to people who are good at reading for retention. In experiment 1, subjects were tested by being asked to write down as much as they could remember (p. 250); this is similar to active reading, which is a useful tool for comprehension and retention. If they had been actively reading during the study periods, performance may have been similar.

Textbook chapters often give problems or discussion questions at the end of each chapter. Performing these exercises may show a similar benefit to what the authors found. It would be nice if the authors had considered student habits and behavior in their discussion, rather than just focusing on educational practice (pp. 253–254). I know that I usually skip exercises in textbooks; I and other students would probably be better off spending less time reading the chapter and more time doing the exercises.

The authors used undergraduates aged 18–24 from their institution, Washington University, for both their experiments. This is basically a convenience sample, which may not generalize to graduate students and others. Amazingly, the authors do not even mention how the students were selected or what programs and backgrounds they came from. They enrolled for “partial fulfilment of course requirements” (pp. 250–251), which could mean they self-selected in a system similar to University of Central Florida’s Psychology Research Participation System, where psychology undergraduates, as part of their course requirements, must participate in the research of graduate students, but are allowed to choose the experiments they will participate in. A volunteer sample may not be representative of even Washington University undergraduate students as a whole, let alone the general public.

Using a wholly between-subjects design in experiment 2 may have weakened the statistical power of the experiment (pp. 251–253). We have no information about whether each of the six groups of 30 students were homogeneous. Using a within-subjects design with a greater number of different reading passages may have worked, and participants could have received more course credit to incentivize a larger commitment.

Using five minutes, two days, and a week as their testing intervals in experiment 1, and then eliminating the two days condition in experiment 2, seems tenuous. For keeping the study simple, it is convenient. A condition where the interval was a few hours may have been valuable. In experiment 1, after scoring one third of the recall tests, one of the two raters bailed (p. 250) and was allegedly not needed because of the high interrater reliability observed. The authors have intriguing results, but it seems like they “cut corners” in several places.


Roediger, H. L., III, & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17(3), 249–255.

Reaction to “Re-imagining motor imagery” by Moran, Guillot, MacIntyre, & Collet (2012)

Reaction to Moran, Guillot, MacIntyre, & Collet (2012) by Richard Thripp
EXP 6506 Section 0002: Fall 2015 – UCF, Dr. Joseph Schmidt
October 26, 2015 [Week 10]

As a piano player, this quote was very salient to me: “Note, however, that there are some instances where slow/fast imagery might still be beneficial to performers, such as during the early stages of motor learning where slow imagery is useful for helping athletes to assimilate key components of the motor task” (Moran, Guillot, MacIntyre, & Collet, 2012, p. 235). When I was teaching myself piano at 10, I would use the digital display on a Casio electronic keyboard to learn to play pieces including abridged versions of “Let it Be” by the Beatles, “Hungarian Dance No. 5” by Johannes Brahms, and “The Entertainer” by Scott Joplin. I would use slow imagery by slowing the tempo of the playback down to 20 beats per minute—the lowest the keyboard would allow. The display would indicate the keys currently being depressed at that point in the piece, and I would mimic the display throughout the piece, hundreds of times, until I could play at the correct tempo. Since this is how I began to learn the piano, I was not only learning patterns and movements for specific musical pieces, but I was also learning the motor task of playing piano in general. It is a large shortcoming, in my opinion, that the authors talk about athletes at length but give no notice to musicians!

It is somewhat counter-intuitive that motor imagery takes roughly the same amount of time as physical motor action. Why are we seemingly incapable of visualizing motor imagery at a much faster pace? Is it possible to train ourselves to become faster at visualizing motor imagery? I have many questions, and there are presently few answers.

I particularly enjoyed the section on confounding and confusing visualization instructions (pp. 229–230). The criticism of instructing participants to visualize themselves golfing in first-person but to imagine a shot “easily reaches the green,” which will elicit a third-person perspective for some subjects, was powerful (p. 230). Being clear and isolating the type of visualization you are trying to study is a mighty task in and of itself. The tone and body language with which the instructions are communicated could even be important—we may not get the whole picture just from a textual printing of the prompts. English is a peculiar language, varying by region and culture; certain instructions may elicit conflicting visualizations from different people, based on their respective backgrounds. The aim should be to be as clear as reasonably possible—perfection is impossible. However, the standards of present research are too low.

The grievance of motor skills research having been focused on simple, constrained movements (p. 237) parallels the problems with generalizing auditory processing research to speech perception. When we have been focused mainly on “simple sounds such as tones, clicks, and noise bursts” (Holt & Lotto, 2010, p. 10), how can we accurately infer these to speech perception, which is much more complicated? How can we apply constrained finger movements to real athletic activity (Moran et al., 2012, p. 237)? The dichotomy of naturalistic versus controlled research is ever-present. It would appear that both groups of authors would like to see a greater number of naturalistic studies. Such studies might identify threads to isolate in future controlled studies, though naturalistic observation cannot infer causality due to a plethora of potential confounds.


Holt, L. L., & Lotto, A. J. (2010). Speech perception as categorization. Author manuscript, Department of Psychology, Carnegie Mellon University, Pittsburgh, PA.

Moran, A., Guillot, A., MacIntyre, T., & Collet, C. (2012). Re-imagining motor imagery: Building bridges between cognitive neuroscience and sport psychology. British Journal of Psychology, 103, 224–247. doi:10.1111/j.2044-8295.2011.02068.x

Reaction to “The relationship between visual perception and visual mental imagery” by Bartolomeo (2002)

Reaction to Bartolomeo (2002) by Richard Thripp
EXP 6506 Section 0002: Fall 2015 – UCF, Dr. Joseph Schmidt
October 26, 2015 [Week 10]

One big takeaway from this article: For neuropsychological impairments that have previously been “bundled” (my terminology—not Bartolomeo’s) under one mechanism in speculative conceptualizations, this bundling should only be entertained as long as contrary evidence is not discovered (pp. 360–361). For example, if perceptual and imagery abilities are postulated as a bundle, but a patient is discovered who has intact imagery abilities but impaired perceptual abilities, the postulation should be discarded or adapted to account for the new evidence. This is logical, but remains a problem for researchers who have so much time, energy, reputation, and funding dependent on their models—the temptation is strong to “explain away” the data, which is possibly what has been done with the Kosslyn model (p. 361). While exceptional patients may exist, we should always be wary when the source of the explanation is someone who has a vested interest in maintaining their position, even when that someone is a scholar supposedly committed to the search for truth.

Postulating a unitary mechanism, however, might still be tenable in the face of conflicting evidence if these conflicts can be explained by physiological differences in a proportion of the population. We have discussed evidence in EXP 6506 class that only 2–5% of people can truly multitask, while 95–98% of people just switch between tasks, degrading performance. It might be proposed that the 2–5% of people who are “true” multitaskers have physiological brain differences from the majority. Similarly, if we postulate that overt and covert facial recognition are bundled, and then patients are discovered who can covertly but not overtly recognize faces, we do not necessarily have to discard our model—the newly discovered patients could just be part of a special class due to potential physiological differences, like the “true” multitaskers.

The poor writing quality of this article was distracting. From the first paragraph, the author gives an example about “loosing further credibility” (p. 357), which, of course, should be “losing.” Portions of page 362 were particularly awkward and badly written, and there were run-on sentences throughout the article. I was surprised when I read “for face imagery, the available anatomical evidence is really scanty” (p. 373)—firstly, “scanty” is a funny word and I have never seen it in a journal article, and secondly, using “really” in this context is something I would expect in a teenager’s text message, not Cortex. However, this can be partly forgiven because the author is from France; English may not be his native language.

The research Bartolomeo has reviewed is intriguing, but it is very sad that so many studies omit critical information, such as imaginal experience of a patient (Shuren, Brott, Schefft, & Houston, 1996 as cited by Bartolomeo, 2002, pp. 366–367), the locations of anatomical lesions in two studies from 1883 and 1952 (pp. 367–368), and the precise location of a brain lesion following an aneurysm and subsequent but unrelated trauma (Shuttleworth, Syring, & Allen, 1982 as cited by Bartolomeo, 2002, p. 368). While this is forgivable in older studies, it is vexing when contemporary researchers neglect to collect or include such information, especially when are trying to examine their evidence in a new light as Bartolomeo has attempted. My only complaint about Bartolomeo is that he does not indicate whether he contacted Shuren et al. or Shuttleworth et al. asking them if they possessed or could recall the information, although they should have assessed imaginal experience and pinpointed the brain lesion for inclusion in their original papers.


Bartolomeo, P. (2002). The relationship between visual perception and visual mental imagery: A reappraisal of the neuropsychological evidence. Cortex, 38, 357–378.