Optical Illusions That Make You Fatter and Your Wallet Lighter

“Eat from small plates, drink from taller glasses.” Optical illusions lead us to eat and drink more, as illustrated by the examples in this article. There’s an old saying in cuisine…”the first bite is with the eye.”

Interesting article. I’m not sure if there is empirical data to support it but it does show that our perception of our food can affect how much we eat. Our actions are affected by so many different things, many of which we might not be aware.

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Word Superiority Effect and Parallel Processing

WordsOne experiment about cognitive brain functioning is the word superiority effect findings of Dr. Reicher in 1969. In this experiment either a word or a non-word (string of letters) is flashed on a screen. The subject is asked if the stimulus contained one of two letters, say a “C” or an “E”. When the stimulus did not resemble a word (e.g., XXCX) subjects were correct in identifying the target letter about 80% of the time. When the string of letters was similar to a word but not one (e.g., FELV) the subjects also correctly identified the target letter 80% of the time. However, the interesting finding was that when the stimulus was a word (e.g., TEND), subjects were correct in identification 90% of the time. So the word superiority effect is that subjects are most accurate in identifying a target letter when it is contained in a word as opposed to a string of letters.

This lends support to the theory that there are things that we can process in parallel and that that parallel processing (or parallel activation of word and letter) can be beneficial at times (such as helping subjects correctly identify individual letters more often when the letter is contained within a word rather than in a random string of letters). In other words, the whole word is recognized before all the letters individually are recognized. This then speeds up or aids processing because there are now a couple routes, per se, to that letter; there is the visual stimulus (seeing the letter) and the linguistic information (knowing that the letter is in the word) that both are activated and help people recognize letters better.

Image by uncommonmuse.

Dynamically filtering the brain

Researchers believe that the prefrontal cortex acts as a dynamic filter for the brain. Dynamic filtering is selecting needed information for a current task from all the information streaming through the frontal cortex. This is why the prefrontal cortex acts as a dynamic filter, it must sort through the information and pick only that which is currently relevant.Filters

Thompson-Schill et al. (1997) wanted to study the dynamic filtering hypothesis so they had subjects generate verbs associated with presented nouns. In other words, if the person saw a “cat” they might say “meow” or “nap” or something else. Thompson-Schill et al. assigned subjects to a high or low noun-verb selection condition. In the high condition, subjects were shown nouns with many associated verbs (e.g., a ball is shown and subject could produce “bounce,” “hit,” “kick,” or “throw”) whereas in the low condition subjects are shown a noun with only one (in most cases) related verb (e.g., a chair is shown and subject says “sit”).

They conducted this experiment to see if the inferior frontal cortex is associated with just semantic memory (basically long-term-memory-type information) or if it an area that supports working memory processes (retrieving information from semantic memory and working with it—in this case filtering through it for relevant associations). The experimenters found that the inferior frontal cortex (IFC) was more activated in the high-selection conditions than in the low-selection condition. If it had not been more activated then it would merely have been a semantic, long term, memory-related area. Because of the higher activation it was concluded that the IFC was associated with working memory, specifically pulling relevant information from semantic memory. It acts as a filtering mechanism, a dynamic filter.

To confirm this finding Thompson-Schill et al. (1998) conducted another study with brain-damaged patients. They selected subjects with lesions of the IFC. They found that in the high-selection condition these patients failed to produce any verbs 15% of the time. But in the low-selection condition these lesioned subjects performed the same as control subjects. The researchers concluded that because those with IFC lesions could not generate verbs to go along with displayed nouns when there were possibly many to choose between, the lesion caused a deficit in selection. It was not a semantic deficit, but a working memory one. They could not decide what verb to use and so they said nothing. This provided neuropsychological evidence for the IFC acting as a dynamic filter for the frontal cortex, at least as far as semantic information is concerned.

Thompson-Schill et al. (1999) also conducted another study where they looked at the temporal lobe in addition to the IFC. They replicated their previous experiment with one key difference. They had the subjects complete two generative trials (one of naming an action verb like in previous experiments and the other was naming an associated color) with the same list of nouns shown the second time for the subjects. Some repeated the first association task and others did the color one the second time. They found that IFC activation increased when the association task changed but temporal lobe activation decreased the second trial for both association conditions. Gazzaniga, Ivry, and Mangun (2002) sum it up best, “The fact that the decrease was observed is consistent with the idea that semantic attributes, be they relevant or irrelevant to the task at hand, were automatically activated upon presentation of the nouns” (p. 522). This is further evidence that the IFC acts as a dynamic filter for the frontal lobes.

[Note: Contact me if you would like the references cited in my post].

War-related traumatic brain injuries

An article in the most recent Monitor on Psychology (published by the American Psychological Association) [here’s a link to the article that is accessible for free online: Link) reminded me of something one of my professors in graduate school told our class a couple years ago. He is a clinical neuropsychologist who occasionally does some consulting for the military. After he returned from a consultation with the military he told us that between the war in Afghanistan and the Iraq war there had been 18,000 central nervous system (brain and spinal cord) injuries of soldiers and contract employees serving in those two countries. The majority of the injuries were minor and many were not combat related but there are still thousands of people with moderate to severe CNS injuries that were acquired in war zones. Quoting from the Monitor article:

“Psychologists, particularly neuropsychologists, are stepping in to assess the damage, help patients learn new strategies to compensate while their brains recover, and raise public awareness of the increasing number of servicemen and women with TBIs. In fact, 1,977 service members were treated for them at Defense and Veterans Brain Injury Center (DVBIC) sites from January 2003 to February 2007.”Soldier Helmet

One reason for high rates of traumatic brain injury in the Iraq (and Afghanistan) war(s) is the improved (compared to previous wars) body armor and other life-saving devices. The downside to fewer fatalities is that there are higher rates of people with severe injuries who survive. The mild TBI rates are shown to be: “between 10 and 20 percent [in some surveys] of soldiers returning from deployments” (Source). It’s great to have fewer fatalities but TBIs can have profound effects on people. Clinical neuropsychologists can help people with TBIs learn how to best cope with their injuries as well as understand how their lives might be different and what they can do to compensate for any difficulties. Most people with mild to moderate TBIs seem to have complete or nearly complete recoveries; however, those with moderate to severe TBIs may have deficits, many very severe, that last the rest of their lives.

There can be myriad short-term problems associated with TBIs (e.g., mental slowing, memory problems, personality changes, concentration and attentional difficulties, etc.) but there are also long-term ones. Research has shown that a person with a history of multiple TBIs is more likely to get Alzheimer’s Disease in old age (well, the research actually shows that there is an over-representation of people with multiple TBIs in the Alzheimer’s population). There is a great need for clinical neuropsychologists currently and in the future to work with and help all of our war veterans who have acquired brain injuries.

Motor learning – It’s good being in the background

This was a story I first saw on Digg today but it’s worth posting about here. Researchers at MIT recently published a study in Neuron (May 24, 2007 issue) that demonstrates a completely new way of looking at motor learning. From their article:

“In experiments on motor learning, it is often assumed that there is an underlying neural representation that is stable and that adaptation takes place on top of this stable background. Our experimental and theoretical results suggest a radically different picture. The experiments show that tuning curves of motor cortical cells are constantly changing even when performing a familiar task. Furthermore, when learning a new task, learning-related changes occur on top of this background of changing tuning curves” (Rokni, Richardson, Bizzi, & Seung, 2007, p. 661).learning_theory.jpg

They are proposing that the neuronal activity associated with motor learning is a little like a sail-less ship on the ocean. This ship not only goes up and down the waves as they come, it also drifts about somewhat randomly in response to the underlying and unstable movement of the water underneath. This analogy isn’t perfect but it is OK.

Learning is not only a component of the active responsive brain activity but also the somewhat random low-level “background noise” that is slowly “retuned” and “retunes” in response to motor learning. This background noise only affects the synapses very slowly but it has a noticeable effect: “According to our theory, this slowness is necessary to prevent the noise from erasing motor memories” (p. 663). They do believe that this unstable foundation for learning is linked to forgetting over time. The researchers also state that there may be many ways that neurons can represent essentially the same behavior: “any single behavior can be realized by multiple configurations of synaptic strengths” (p. 653).

Anyway, the article was an interesting read and well worth the time if you have any interest in cognitive psychology. [The posted image is directly from the article in Neuron and is ©2007 Elsevier Inc].

Reference

Rokni, U., Richardson, A. G., Bizzi, E., & Seung, H. S. (2007). Motor learning with unstable
neural representations. Neuron, 54, 653-666.

Acute Respiratory Distress Syndrome

Acute respiratory distress syndrome is a common cause of mortality and morbidity, affecting an estimated 150,000 people per year in the United States (Rubenfeld, Doyle, & Matthay, 1995) however, recent evidence suggests the incidence may be higher (Rubenfeld, 2003). Compared to 20 years ago mortality has decreased from 80% to 30% of ARDS participants (Milberg, Davis, Steinberg, & Hudson, 1995; Brower et al., 2000) resulting in approximately 100,000 people who survive ARDS each year in the United States (Bersten, Edibam, Hunt, & Moran, 2002). Acute respiratory distress syndrome occurs in response to a variety of insults including sepsis, trauma, pneumonia, massive transfusion and other medical/surgical conditions. Treatment of ARDS requires aggressive supportive care including positive pressure ventilation (Brower et al., 2000) and increased oxygen concentrations with risks of barotrauma, oxygen toxicity, and nosocomial infection.

Acute respiratory distress syndrome may be a consequence of multiple organ system dysfunction, including the central nervous system (Bell, Coalson, Smith, & Johanson, 1983; Montgomery, Stager, Carrico, & Hudson, 1985). Participants who survive ARDS are at risk for neuropsychological deficits (Hopkins et al., 1999; Rothenhausler, Ehrentraut, Schelling, & Kapfhammer, 2001; Al-Saidi et al., 2003; Hopkins, Weaver, Chan, & Orme, 2004) 6 to 12 months following hospital discharge. Approximately 33% of general medical ICU survivors, some with ARDS, have cognitive impairments (Jackson et al., 2003) 6 months after hospital discharge. In 1999, Hopkins and colleagues found that 45% of ARDS survivors had neurocognitive impairments including impaired memory, attention, concentration, mental processing speed, and global intellectual decline one year post-discharge.

Others have since made similar observations (Marquis et al. 2000; Rothenhausler et al., 2001; Al-Saidi et al., 2003; Jackson et al., 2003). The prevalence of neurocognitive impairments varies from 25% (Rothenhausler et al., 2001) to 78% in participants with more severe ARDS (Hopkins et al., 1999). Neurocognitive impairments are a major determinant in return to work, work productivity, and life satisfaction following ARDS (Rothenhausler et al., 2001).

 References

Al-Saidi, F., McAndrews, M. P., Cheunt, A. M., Tansey, C. M., Matte-Martyn, A., Diaz-Granados, N., et al. (2003). Neuropsychological sequelae in ARDS survivors. American Journal of Respiratory and Critical Care Medicine, 167, A737.

Bell, R. C., Coalson, J. J., Smith, J. D., & Johanson, W. G., Jr. (1983). Multiple organ system failure and infection in adult respiratory distress syndrome. Annals of Internal Medicine, 99, 293–298.

Bersten, A. D., Edibam, C., Hunt, T., & Moran, J. (2002). Incidence and mortality of acute lung injury and the acute respiratory distress syndrome in three Australian States. American Journal of Respiratory and Critical Care Medicine, 165, 443–448.

Brower, R. G., Matthay, M. A., Morris, A., Schoenfeld, D., Thompson, B. T., & Wheeler, A. (2000). Ventilation with lower tidal volumes as compared with traditional tidal volumes for acute lung injury and the acute respiratory distress syndrome. New England Journal of Medicine, 342, 1301–1308.

Hopkins, R. O., Weaver, L. K., Chan, K. J., & Orme, J. F. (2004). Quality of life, emotional, and cognitive function following acute respiratory distress syndrome. Journal of the International Neuropsychological Society, 10, 1005–1017.

Hopkins, R. O., Weaver, L. K., Pope, D., Orme, J. F., Bigler, E. D., & Larson-Lohr, V. (1999). Neuropsychological sequelae and impaired health status in survivors of severe acute respiratory distress syndrome. American Journal of Respiratory and Critical Care Medicine, 160, 50–56.

Jackson, J. C., Hart, R. P., Gordon, S. M., Shintani, A., Truman, B., May, L., et al. (2003). Six-month neuropsychological outcome of medical intensive care unit participants. Critical Care Medicine, 31, 1226–1234.

Marquis, K., Curtis, J., Caldwell, E., Davidson, T., Davis, J., Sanchez, P., et al. (2000). Neuropsychological sequelae in survivors of ARDS compared with critically ill control participants. American Journal of Respiratory and Critical Care Medicine, 161, A383.

Milberg, J. A., Davis, D. R., Steinberg, K. P., & Hudson, L. D. (1995). Improved survival of participants with acute respiratory distress syndrome (ARDS): 1983-1993. Journal of the American Medical Association, 273, 306–309.

Montgomery, A. B., Stager, M. A., Carrico, C. J., & Hudson, L. D. (1985). Causes of mortality in participants with the adult respiratory distress syndrome. American Review of Respiratory Disease, 132, 485–489.

Rothenhausler, H. B., Ehrentraut, S., Stoll, C., Schelling, G., & Kapfhammer, H. P. (2001). The relationship between cognitive performance and employment and health status in long-term survivors of the acute respiratory distress syndrome: Results of an exploratory study. General Hospital Psychiatry, 23, 90–96.

Rubenfeld, G. D. (2003). Epidemiology of acute lung injury. Critical Care Medicine, 31, S276–S284.

Rubenfeld, G. D., Doyle, R. L., & Matthay, M. A. (1995). Evaluation of definitions of ARDS. American Journal of Respiratory and Critical Care Medicine, 151, 1270–1271.

Brain Injury Video

Here’s a decent video about brain injury that does a good job of showing how brain injury affects people.


Unfortunately, we don’t have the ability to completely reverse the effects of acquired brain injury. Therapy and rehabilitation can help but if the injuries are severe, completely normal functioning is unlikely ever to return. Prevention is the best medicine in this case; it is unfortunate that prevention is not always possible.The parts of the brain that are most often affected with brain injury are those that have to do with memory.

Another common outcome of brain injury is cognitive slowing – people just don’t seem to think or move or act as quickly after brain injury as they did before. This slowing is due in part to the diffuse axonal injury that occurs (the connections between brain cells {neurons} are broken or twisted as the brain compresses and stretches) with traumatic brain injuries. Even non traumatic brain injuries (e.g., carbon monoxide poisoning) can result in overall cognitive slowing (this slowing often greatly improves over time with mild to moderate brain injuries).It is also fairly common to see personality changes in someone with a recent brain injury – this is mainly due to damage to the frontal lobes. These changes in personality can be the source of great frustration and concern for family, friends, and everyone around the injured person. Dealing with a severe brain injury requires a lot of loving, patience, and care.

Recent alcohol research

drinking_woman.jpg

There was an interesting recent news story from Reuters. Researchers at the University of Missouri-Columbia found that, “Young adults who binge drink frequently are more likely to show disadvantageous decision-making patterns than their peers who don’t drink as heavily” (from the news article). You can’t assume that just because drinking and poor decision making are correlated that the drinking causes the poor decisions (because people who are poorer at decision making in general may drink more) but as I like to say, “Correlation does not imply causation but neither does does it deny causation.”

On the other hand, there is some evidence that drinking alcohol might slow down the progression and/or onset of dementia (e.g., Alzheimer’s Disease): Alcohol and dementia article. Again, the study is correlational so firm causations should not be inferred.

These two articles demonstrate that there is still a lot of  uncertainty about the long-term effects of alcohol consumption.

Dopamine, the Basal Ganglia, and Learning

A significant proportion of dopamine (DA) is produced in the substantia nigra pars compacta (SNpc) and is carried to the striatum via the nigrostriatal pathway. While this pathway has been traditionally linked with motor functioning, recent research has implicated striatal DA involvement in language (Crosson, 2003) and learning (Seger, 2006). One disease in which there is considerable DA disruption is Huntington’s Disease (HD). In HD the head of the caudate is typically the first brain structure affected by neuronal cell loss. This cell loss not only affects connections with the SNpc but also affects the connections between the striatum and the prefrontal cortex. In HD the disruption of these dopaminergic pathways leads to disruptions in motor and cognitive functioning.

How DA disruptions affect cognition has been explained by theories that are modifications of Mink’s model (1996) of center and surround (i.e., direct and indirect) basal ganglia regulation. Within the caudate there are two main families of DA receptors – D1 and D2. These receptors have been shown to have different functioning within the basal ganglia (Seger, 2006) – the D1 receptor is involved with the direct pathway and the D2 receptor is involved in the indirect pathway. The D1, or direct pathway, can be viewed as increasing the strength of the signal of the desired response while the D2, or indirect pathway, serves to reduce the noise of the competing undesired responses. Dopaminergic systemic disruption in HD should thus decrease the signal-to-noise ratio, which results in the person having a greater difficulty selecting the desired response (see model below).

Center-surround model of basal ganglia-based learning and memory

*Model based on Mink (1996) and Frank, Seeberger, and O’Reilly (2004)

There is evidence that in early stages of Huntington’s disease, D2 receptors are the first to be affected, with less binding occurring at D2 receptors presumably due to receptor loss. As the disease progresses, the D1 receptors also start to become depleted, with the end result of widespread DA dysfunction (Glass, Dragunow, & Faull, 2000). This DA dysfunction possibly affects verbal learning and recall by impacting the indirect pathway in the early stages of HD and indiscriminately the whole direct and indirect system in later stages of the disease process.

References

Crosson (2003). Left and right basal ganglia and frontal activity during language generation: Contributions to lexical, semantic, and phonological processes. Journal of the International Neuropsychological Society, 9, 1061-1077.

Frank, M. J., Seeberger, L. C., & O’Reilly, R. C. (2004). By carrot or by stick: Cognitive reinforcement learning in Parkinsonism. Science, 306, 1940-1943.

Glass, M., Dragunow, M., & Faull, R. L. M. (2000). The pattern of neurodegeneration in Huntington’s disease: A comparative study of cannabinoid, dopamine, adenosine and GABAA receptor alterations in the human basal ganglia in Huntington’s disease. Neuroscience, 97(3), 505-19.

Seger, C. A. (2006). The basal ganglia in human learning. Neuroscientist, 12(4), 285-290.

The basal ganglia and cognition

The basal ganglia are a collection of subcortical structures that were traditionally viewed as only being involved in movement. The basal ganglia include the caudate, globus pallidus, putamen, and nucleus accumbens (the subthalamic nucleus and the substantia nigra are also often included as part of the basal ganglia). Scientists have known about the basal ganglia’s role in movement for a number of years but have only recently really started studying their role in cognition, executive function, and memory.

Dissections of the brain have shown that there are a number of white matter “loops” exiting and entering the basal ganglia. We know that the striatum, which consists of the putamen and the caudate and is so named because there are connections between the two structures that look like stripes (striations), receives excitatory input from all over the cortex (Seger & Cincotta, 2002). The prefrontal cortex (roughly the very front of the brain) connects to the anterior putamen and the head of the caudate but the tail of the caudate and the posterior parts of the putamen receive inputs from parts of the temporal and parietal lobes. The frontal lobes are involved in tasks such as planning, remembering, organizing, and many other of the “higher-order” cognitive abilities. The parietal lobes are involved in visuo-spatial tasks and the temporal lobes are involved in memory and object recognition (these are gross simplifications of lobular function – all lobes have more functions than I wrote about). So if parts of the basal ganglia receive inputs from the frontal lobes, what are the basal ganglia doing if not just moderating movement?

Seger and Cincotta (2002) demonstrated that the striatum is involved in a type of learning. Lamar, Price, Libon, Penney, Kaplan, Grossman, and Heilman (2007) demonstrated that dementia patients with higher levels of white matter disruption (which likely interferes with basal ganglia connectivity) have poorer working memory performance. One example of what working memory is is performing a multiplication task in your head without using any paper – having to remember the digits and manipulate them is a process of working memory. Benke, Delazer, Bartha, and Auer (2003) reported on two clinical cases of patients with hematoma disrupting the left basal ganglia. Both patients had “executive function” disruption, short- and long-term memory impairment, and attentional difficulties. Many other researchers have demonstrated the role the basal ganglia has in cognition but we are still in the early stages of this area of research.