Mapping the brain - MIT News Office

Brain mapping and large scale brain networks, IMHO, are a fundamental new key to understanding cognitive functioning and neuro technologies

http://web.mit.edu/newsoffice/2010/brain-mapping.html

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Smart People Really Do Think Faster : NPR

Conceptually this is consistent with Jenson's neural efficiency hypothesis and Rammsayer's temporal resolution hypothesis.

http://www.npr.org/tablet/#story/?storyId=102169531

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Article: Technology for psychologists

Technology for psychologists
http://sylvainroy.blogspot.com/

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Article: What It Takes To Be a Lifelong Learner | Real World Research

What It Takes To Be a Lifelong Learner | Real World Research
http://blogs.psychcentral.com/research/2011/what-it-takes-to-be-a-lifelong-learner/

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Article: Why Don’t We Value Spatial Intelligence?

Why Don't We Value Spatial Intelligence?
http://gettingsmart.com/blog/2011/12/why-don%E2%80%99t-we-value-spatial-intelligence/

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Dissertation Dish: Gf cognitive test analysis via CFA and task analysis

A comparison of confirmatory factor analysis and task analysis of fluid intelligence cognitive subtests by Parkin, Jason R., Ph.D., University of Missouri - Columbia, 2010 , 132 pages; AAT 3488814

Abstract

Cross-battery assessment relies on the classification of cognitive subtests into the Cattell- Horn-Carroll (CHC) theory's broad and narrow ability definitions. Generally, broad ability classifications have used ability data analyzed through factor analytic methods, while narrow ability classifications have used data about subtest task demands. The purpose of this investigation is to determine whether subtest similarity judgments based on task demands data, and judgments based on ability measurement provide similar results. It includes two studies. First, middle school students (N = 63) completed six target fluid reasoning subtests that were subjected to confirmatory factor analyses to analysis subtest similarities. Second, school psychology practitioners (N = 32) sorted subtest descriptions into similarity groups. Their judgments were analyzed with multiple non-hierarchical cluster analyses. Results partially confirmed that the six target subtests were classified similarly using both data types, though need to be interpreted cautiously due to limitations. Implications for assessment practices are discussed.




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WMF Human Cognitive Abilities Archive Project: Major update 12-29-11

Here is an early New Years present to those interested in the structure of human cognitive abilities and the seminal work of Dr. John Carroll.

The free on-line WMF Human Cognitive Abilities (HCA) archive project had a MAJOR update today. An overview of the project, with a direct link to the archive, can be found at the Woodcock-Muñoz Foundation web page (click on "Current Woodcock-Muñoz Foundation Human Cognitive Abilities Archive") . Also, an on-line PPT copy of a poster presentation I made at the 2008 (Dec) ISIR conference re: this project can be found by clicking here.

Today's update added the following 38 new data sets from John "Jack" Carroll's original collection.  We now have approximately 50% of Jack Carroll's original datasets archived on-line.  Of particular interest is the addtion of one of Carroll's data sets, three by John Horn, and 17 by Guilford et al.  Big names...and some correlation matrices with big numbers of variables.  Data parasites (er....secondary data analysits) should be happy.

• CARR01.  Carroll, J.B. (1941).  A factor analysis of verbal abilities.  Psychometrika, 6, 279-307.
• FAIR02.  Fairbank, B.A. Jr., Tirre, W., Anderson, N.S. (1991).  Measures of thirty cognitive tasks:  Intercorrelations and correlations with aptitude battery scores. In P.L. Dann, S. M. Irvine, & J. Collis (Eds.), Advances in computer-based human assessment (pp. 51-101).  Dordrecht & Boston: Kluwer Academic.
• FLAN01.  Flanagan, J.C., Davis, F.B., Dailey, J.T., Shaycoft, M.F., Orr, D.B., Goldberg, I., Neyman, C.A. Jr., (1964).  The Amercian high school student (Cooperative Research Project No. 635).  Pittsburgh:  University of Pittsburgh.
• FULG21.  Fulgosi, A., Guilford, J. P. (1966).  Fluctuation of ambiguous figures and intellectual flexibility.  American Journal of Psychology, 79, 602-607.
• GUIL11.  Guilford, J.P., Berger R.M., Christensen, P.R. (1955).  A factor-analytic stydy of planning:  II. Administration of tests and analysis of results.  Los Angeles:  Reports from the Psychological Laboratory, University of Southern California, No. 12.
• GUIL31 to GUIL46 (17).  Guilford, J.P., Lacey, J.I. (Eds.) (1947).  Printed classification tests.  Army Air Force Aviation Psychology Program Research Reports, No. 5.  Washington, DC: U.S. Government Printing Office. [discussed or re-analyzed by Lohman (1979)]
• HARG12.  Hargreaves, H.L. (1927).  The 'faculty' of imagination:  An enquiry concerning the existence of a general 'faculty,' or group factor, of imagination.  British Journal of Psychology Monograph Supplement, 3, No. 10.
• HECK01.  Heckman, R.W. (1967).  Aptitude-treatment interactions in learning from printed-instruction: A correlational study.  Unpublished Ph.D. thesis, Purdue University.  (University Microfilm 67-10202)
• HEND01.  Hendricks, M., Guilford, J. P., Hoepfner, R. (1969). Measuring creative social abilities. Los Angeles: Reports from the Psychological Laboratory, University of Southern California, No. 42.
• HEND11A.  Hendrickson, D.E. (1981). The biological basis of intelligence. Part II: Measurement. In H.J. Eysenck (Ed.), A model for intelligence (pp. 197-228). Berlin: Springer.
• HHIG01.  iggins, L. C. (1978) A factor analytic study of children's picture interpretation behavior. Educational Communication & Technology, 26, 215-232
• HISK03/04.  Hiskey, M. (1966). Manual for the Hiskey-Nebraska Test of Learning Aptitude. Lincoln, NE: Union College Press.
• HORN25/26.  Horn, J. L., & Bramble, W. J. (1967). Second-order ability structure revealed in rights and wrongs scores. Journal of Educational Psychology, 58, 115-122.
• HORN31.  Horn, J. L., & Stankov, L. (1982) Auditory and visual factors of intelligence. Intelligence, 6, 165-185.
• KEIT21.  Keith, T. Z., & Novok, C. G. (1987). What is the g that the K-ABC measures? Paper presented at the meeting of the National Association of School Psychologists, New Orleans, L.A.
• KRAN01/KRAN01A.  Kranzler, J. H. (1990). The nature of intelligence: A unitary process or a number of independent processes? Unpublished doctoral dissertation, University of California at Berkeley.
• LANS31.  Lansman, M., Donaldson, G., Hunt, E., & Yantis, S. (1982). Ability factors and cognitive processes. Intelligence, 6, 347-386.
• LORD01.  Lord, F. M. (1956). A study of speed factors in tests and academic grades. Psychometrika, 21, 31-50.
• LUN21.  Lunneborg, C. E. (1977). Choice reaction time: What role in ability measurement? Applied Psychological Measurement, 1, 309-330.
• WOTH01.  Wothke, W., Bock, R.D., Curran, L.T., Fairbank, B.A., Augustin, J.W., Gillet, A.H., Guerrero, C., Jr. (1991).  Factor analytic examination of the Armed Services Vocational Aptitude Battery (ASVAB) and the kit of factor-referenced tests.  Brooks Air Force Base, TX: Air Force Human Resources Laboratory Report AFHRL-TR-90-67.

Request for assistance: The HCA project needs help tracking down copies of old journal articles, dissertations, etc. for a number of datasets being archived. We have yet to locate copies of the original manuscripts for a significant number of datasets that have been posted to the archive. Help in locating copies of these MIA manuscripts would be appreciated.  Please visit the special "Requests for Assistance" section of this archive to view a more complete list of manuscripts that we are currently having trouble locating. If you have access to either a paper or e-copy of any of the designated "fugitive" documents, and would be willing to provide them to WMF to copy/scan (we would cover the costs), please contact Dr. Kevin McGrew at the email address listed at the site.  A copy of the complete list or datasets with missing mannuscripts (in red font) can also be downloaded directlly from here.

Please join the WMF HCA listserv to receive routine email updates regarding the WMF HCA project.

All posts regarding this project can be found here.

Technorati Tags: psychology, educational psychology, cognitive, cognition, intelligence, neuropsychology, IQ, IQ tests, IQ scores, HCA, Human Cognitive Abilities, Woodcock-Munoz-Foundation, WMF, John Carroll, CHC, Cattell-Horn-Carroll, HCA project, correlation matrices

The most awesome quantoid XMAS gift ever - for the geeks (me)

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Book nook: Review of Cambridge Handbook of Intelligence

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Test---Finally BlogPress may have fixed IOS5 bug

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Woodcock-Muñoz Foundation News and Notes

http://www.woodcock-munoz-foundation.org/newsnotes.html

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Does attentional training improve numerical processing in developmental dyscalculia?

Objective: Recently, a deficit in attention was found in those with pure developmental dyscalculia (DD). Accordingly, the present study aimed to examine the influence of attentional training on attention abilities, basic numerical abilities, and arithmetic in participants who were diagnosed as having DD. Method: Nine university students diagnosed as having DD (IQ and reading abilities in the normal range and no indication of attention-deficit hyperactivity disorder) and nine matched controls participated in attentional training (i.e., video game training). Results: First, training modulated the orienting system; after training, the size of the validity effect (i.e., effect of valid vs. invalid) decreased. This effect was comparable in the two groups. Training modulated abnormalities in the attention systems of those with DD, that is, it reduced their enlarged congruity effect (i.e., faster responding when flanking arrows pointed to the same location as a center arrow). Second, in relation to the enumeration task, training reduced the reaction time of the DD group in the subitizing range but did not change their smaller-than-normal subitizing range. Finally, training improved performance in addition problems in both the DD and control groups. Conclusions: These results imply that attentional training does improve most of the attentional deficits of those with DD. In contrast, training did not improve the abnormalities of the DD group in arithmetic or basic numerical processing. Thus, in contrast to the domain-general hypothesis, the deficits in attention among those with DD and the deficits in numerical processing appear to originate from different sources. (PsycINFO Database Record (c) 2011 APA, all rights reserved)

http://feedproxy.google.com/~r/apa-journals-neu/~3/pIxQNkUpWVM/45

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Differential aging of components of executive function and memory

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Measuring motor speed via typing: Surrogate for finger tapping test

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Use of CART to predict SB5 preschool IQs

Interesting application of CART methids, methods that are unfortunately underappreciated in the behaviorial sciences. More information rgarding these execellent exploratory methods can be found at links below.

http://en.wikipedia.org/wiki/Decision_tree_learning

http://www.salford-systems.com/



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IQs Corner Intelligent Insights e-paper now more comprehensive

IQs Corner e-paper is now greatly expanded in coverage.



Go to the subscribe box on the ledt sidebar of this blog to subscribe.





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IQs Corner Recent Literature of Interest 01-24-12

IQs Corners Recent Literature of Interest for 01-24-12 is now available.

Do you know how smart you are?

The finding of an overall correlation between self-estimates and tested IQ, although significant (.33), suggests that self-estimates are not good proxies for tested IQ---only approximately 10% shared variance. Yet, this information could still be useful in counseling contexts..to evaluate possible significant discrepancies between self-perception and measured abilities. Of course, self-estimates might be more related to intellectal "performance"..how one actually performs in the real world due to other factors (motivations, etc). Would be interesting study to pursue.





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JPA issue on gifted

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Some evidence for real multi-tasking@ELSneuroscience, 12/26/11 9:05 AM

Elsevier Neuro (@ELSneuroscience) 12/26/11 9:05 AM A cognitive neurophysiology specialist shows evidence that we can focus on more than one thing at a time. ow.ly/88Ssn

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The Four Regions of the Thinking Brain Made Simple - Part Two | Building Personal Strength

http://www.buildingpersonalstrength.com/2011/07/four-regions-of-thinking-brain-made_11.html

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The Four Regions of the Thinking Brain Made Simple - Part Two | Building Personal Strength

http://www.buildingpersonalstrength.com/2011/07/four-regions-of-thinking-brain-made_11.html

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The Four Regions of the Thinking Brain Made Simple - Part One | Building Personal Strength

http://www.buildingpersonalstrength.com/2011/07/four-regions-of-thinking-brain-made.html

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Brain Clock "Times" now more comprehensive

New and more comprehensice version now available. Go to www.brainclock.net to find subscription box





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Smart Guide to 2012: Mapping the human brain - health - 23 December 2011 - New Scientist

The human connectome project. This is important and is related to recent posts made at this blog regarding large scale brain networks.

http://www.newscientist.com/article/mg21228444.700-smart-guide-to-2012-mapping-the-human-brain.html

http://www.brainclock.net/2011/12/brain-as-set-of-networks-fine-tunning.html

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Awesome present --- the quantoid geek watch

Internet Changes How We Remember: Scientific American

I saw this article when reading The NeuronClub Daily on the Paper.li Mobile Edition and thought you might be interested:

Internet Changes How We Remember: Scientific American

Head Lines | Mind & Brain See Inside Knowing we can retrieve facts online later alters memory By Anne Casselman  | December 24, 2011 Image: Mike Kemp/Corbis Four years ago Columbia University psych...
Read the full article on scientificamerican.com

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The Flynn Effect – A Summary

Visit Cog-Iq link for info

http://www.cogn-iq.org/archives/641

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PEBS Neuroethics Roundup (JHU)

http://kolber.typepad.com/ethics_law_blog/2011/12/pebs-neuroethics-roundup-jhu-3.html

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Correlations between the JCCES and other measures (update #2)

Here is a new updated table of correlations that were observed between the Jouve-Cerebrals Crystallized Educational Scale (JCCES) and other measures of cognitive abilities or achievement.

http://www.cogn-iq.org/archives/633

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Beyond IQ: IQ, self-control, tested achievement and grades

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Gifted identification: Forthcoming issue of JPA

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Auditory processing based dyslexia@PsyPost, 12/21/11 3:37 PM

PsyPost.org (@PsyPost) 12/21/11 3:37 PM Abnormality in auditory processing underlies dyslexia bit.ly/tzoumo

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Quieting the unquiet wandering mind

My recent post regarding large scale brain networks and how neurotechnology and mediation may facilitate the silencing of the default brain network, to allow better on-demand controlled focus, has been reposted at the IM-HOME blog.

Retrieval-induced forgetting of arithmetic facts.

Retrieval-induced forgetting (RIF) is a widely studied phenomenon of human memory, but RIF of arithmetic facts remains relatively unexplored. In 2 experiments, we investigated RIF of simple addition facts (2 + 3 = 5) from practice of their multiplication counterparts (2 × 3 = 6). In both experiments, robust RIF expressed in response times occurred only for high-strength small-number addition facts with sums ≤ 10, indicating that RIF from multiplication practice was interference dependent. RIF of addition-fact memory was produced by multiplication retrieval (2 × 3 = ?) but not multiplication study (2 × 3 = 6), supporting an inhibitory mechanism of RIF in arithmetic memory. Finally, RIF occurred with multiplication practiced in word format (three × four) and addition tested later in digit format (3 + 4), which provides evidence that digit and written-word formats for arithmetic accessed a common semantic retrieval network. The results support the view that addition and multiplication facts are stored in an interrelated semantic network and that RIF of competing addition facts is an intrinsic process of multiplication fact retrieval. (PsycINFO Database Record (c) 2011 APA, all rights reserved)

http://feedproxy.google.com/~r/apa-journals-xlm/~3/rZXisSZKc3M/118

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Memory inhibition, aging, and the executive deficit hypothesis.

Although memory inhibition seems to underlie retrieval-induced forgetting (RIF), there is some controversy about the precise nature of this effect. Because normal RIF is observed in people with deficits in executive control (i.e., older adults), some have proposed that an automatic-like inhibitory process is responsible for the effect. On the contrary, neurocognitive and dual-task findings with young people support the view that an executive control process underlies RIF. In the present study, we address this apparent controversy by comparing young and older participants under different dual-task conditions. Our results indicate that memory inhibition in older adults also depends on executive control, which is more easily disrupted by a secondary task in older than in young adults. Thus, the fact that RIF in older adults is sometimes present is not incompatible with a decline in executive control with aging. The results also shed some light into the discussion regarding the effect of dual tasking on retrieval. (PsycINFO Database Record (c) 2011 APA, all rights reserved)

http://feedproxy.google.com/~r/apa-journals-xlm/~3/PUs1fXJ_Sn8/178

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Unborn brain growing connections@Neuroscience_WB, 12/20/11 3:45 AM

Neuroscience (@Neuroscience_WB) 12/20/11 3:45 AM An unborn brain flowering connections goo.gl/EKr7Y [research] #neuroscience

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Data mining@Neuro_Skeptic, 12/18/11 3:17 AM

For my quantoid readers.  This is goof stuff

Neuroskeptic (@Neuro_Skeptic) 12/18/11 3:17 AM Interesting (seriously, it is) new approach to statistics talyarkoni.org/blog/2011/12/1… Good at finding non-linear associations... maybe *too* good

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Brain waves or oscillation rate influences short term memory@BrainCosmos, 12/17/11 12:57 AM

Brain (@BrainCosmos) 12/17/11 12:57 AM What determines the capacity of short-term memory? bit.ly/ryT1Vi

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The networked brain: Fine-tunning and controlling your network(s)

Man has always known that the brain is the center of human behavior.  Early attempts at understanding which locations in the brain controlled different functions were non-scientific and included such practices as phrenology.  This pseudoscience believed that by feeling the bumps of a persons head it was possible to draw conclusions about specific brain functions and traits of the person.

(double click on any image to enlarge)

Eventually brain science revealed that different regions of the brain where specialized for different specific cognitive processes (but it was not related to the phrenological brain bump maps).  This has been called the modular or functional specialization view of the brain, which is grounded in the conclusion that different brain areas acted more-or-less as independent mechanisms for completing specific cognitive functions.

One of the most exciting developments in contemporary neuroscience is the recognition that the human brain processes information via different brain circuits or loops which at a higher level can be studied as large scale brain networks. Although the modular view still provides important brain insights, the accumulating evidence suggests that it has serious limitations and might in fact be misleading (Bresslor and Menon, 2010).  One of the best summaries of this cutting edge research is that by Bresslor and Menon.

Large scale brain network research suggests that congitive functioning is the result of interactions or communication between different brain systems distributed throughout the brain. That is, when performing a particular task, just one isolated brain area is not working alone.  Instead, different areas of the brain, often far apart from each other within the geogrpahic space of the brain, are communicating through a fast-paced sychronized set of brain signals.  These networks can be considered preferred pathways for sending signals back and forth to perform a specific set of cognitive or motor behaviors. 

To understand preferred neural pathways, think of walking on a college campus where there are paved sidewalks connecting different buildings that house specialized knowledge and activities.  If you have spent anytime on a college campus, one typically finds foot-worn short cuts in the grass that are the preferred (and more efficient) means by which most people move between building A and B.  The combined set of frequently used paved and unpaved pathways are the most efficient or preferred pathways for moving efficiently between buildings.  The human brain has developed preferred communication pathays that link together different brain circuits or loops in order to quickly and efficiently complete specific tasks. 

According to Bresslor and Menon (2010), “a large-scale functional network can therefore be defined as a collection of interconnected brain areas that interact to perform circumscribed functions.”  More importantly, component brain areas in these large-scale brain networks perform different roles.  Some act as controllers or task switchers that coordinate, direct and synchronize the involvement of other brain networks.  Other brain networks handle the flow of sensory or motor information and engage in concious manipulation of the information in the form of “thinking.” 

As illustrated in the figure above, neuroscientists have identified a number of core brain network nodes or circuits.  The important new insight is that these various nodes or circuits are integrated together into a grander set of higher-level core functional brain networks.  Three important core networks are receiving considerable attention in explaining human beavhior. 

Major functional brain networks

The default mode (DMN) or default brain network (shown in blue) is what your brain does when not engaged in specific tasks.  It is the busy or active part of your brain when you are mentally passive.  According to Bresslor and Brennon the “DMN is seen to collectively comprise an integrated system for autobiographical, self-monitoring and social cognitive functions.”  It has also been characterized as responsible for REST (rapid episodic spontaneous thinking).  In other words, this is the spontaneous mind wandering and internal self-talk and thinking we engage in when not working on a specific task or, when completing a task that is so automatized (e.g., driving a car) that our mind starts to wander and generate spontaneous thoughts.  As I have discussed previously (at IM-HOME blog), the default network is responsible for the unquiet or noisy mind.  And, it is likely that people differ in amount of spontaneous mind wandering (which can be both positive creative thinking or distracting thoughts), with some having a very unquiet mind that is hard to turn off, while others can turn off the inner thought generation and self-talk and display tremendous self-focus or controlled attention to perform a cognitively or motorically demanding task.  A very interesting discussion of the serendipitous discovery and explanation of the default brain network is in the following soon to be published scientific article.

The salience network (shown in yellow) is a controllor or network switcher.  It monitors information from within (internal input) and from the external world arounding us, which is constantly bombarding us with information.  Think of the salience network as the air traffic controllor of the brain.  Its job is to scan all information bombarding us from the outside world and also that from within our own brains.  This controller decides which information is most urgent, task relevant, and which should receive priority in the que of sending brain signals to areas of the brain for processing.  This controlling network must suppress either the default or executive networks depending on the task at hand.  It must supress one, and activiate the other.  Needless to say, this decision making and distribution of information must require exquisite and efficienct neural timing as regulated by the brain clock(s).

Finally, the central-executive network (CEN; shown in red) “is engaged in higher-order cognitive and attentional control.”  In other words, when you must engage your concious brain to work on a problem, place information in your working memory as you think, focus your attention on a task or problem, etc., you are  “thinking” and must focus your controlled attention.  As I understand this research, the salience or controller network is a multi-switching mechanism that is constantly initiating dynamic switching between the REST (sponatenous and often creative unquie mind wandering) and thinking networks to best match the current demands you are facing.

According to Bresslor and Melon, not only is this large scale brain network helping us better understand normal cognitive and motor behavior, it is providing insights into clinical disorders of the brain.  Poor synchronization between the three major brain networks has been implicated in Alzheimer’s, schizophrenia, autism, the manic phase of biploar and Parkinson’s (Bresslor and Melon, 2010), disorders that have all been linked to a brain or neural timing (i.e, the brain clock or clocks).  I also believe that ADHD would be implicated.  If the synchronized milli-second based communicaiton between and within these large networks is compromised, and if the network traffic controller (the salience network) is disrupted in particular, efficient and normal cognition or motor behavior can be compromised.

I find this emerging research fascinating.  I believe it provides a viable working hypothesis to explain why different brain fitness or training neurotechnologies have shown promise in improving cognitive function in working memory, ADHD, and other clinical disorders.  It is my current hypothesis that various brain training technologies may focus on different psychological constructs (e.g., working memory; planning; focus or controlled attention), but their effectiveness may all be directly or indirectly facilitating the sychronization between the major brain networks.  More specifically, by strengthing the ability to invoke the salience or controller network, a person can learn to supress, inhibit or silence the REST-producing default brain network more efficiently, long enough to exert more controlled attention or focus when invoking the thinking central executive network.  Collectively these brain fitness techonologies may all improving the use of those abilities called executive function, or what I have called the personal brain manager.  Those technologies that focus on rhythm or brain timing are those I find most fascinating.  For example, the recent example of the use of melodic intonation therapy with Congresswoman Gabby Giffords (she suffered serious brain trauma due to a gun shot) demonstrates how rhythm-based brain timing therapies may help repair destroyed preferred and efficient neural pathways or, develop new pathways, much like the development of a new foot worn pathway in the grass on a college campus if a preferred pathway is disrupted by a new building, temporary work or rennovation, or some other destruction of a preferred and efficient network of movement path.

To understand the beauty of the synchronized brain, it is best to see the patterns of brain network connections in action.  Below is a video called the “Meditating Mind.”  I urge you to view the video for a number of reasons.  

A number of observations should be clear.  First, during the first part of the video the brain is seen as active even during a resting state.  This is visual evidence of the silent private dialouge (REST) of the default mode or network of the brain.  Next, the video mentions the rhythm of increased and decreased neural activation as the brain responds to no visual information or presentation of a video.  The changes in color and sound demonstrate the rich rhthymic sychronization of large and different parts of the brain, depending on whether the brain is engaged in a passive or active cognitive task.  The beauty of the rapidly changing and spreading communication should make it obvious that efficient rhythmic synchronization of timing of brain signals to and from different networks or ciruits is critical to efficient brain functioning.

Finally, the contrast between the same brain under normal conditions and when engaged in a form of meditation is striking.  Clearly when this person’s brain is mediating, the brain is responding with a change in rates and frequency of brain network activation and synchrony.  As I described in my personal IM-HOME based experience post, mastering Interactive Metronome (IM) therapy requires “becoming one with the tone”…which sounds similar to the language of those who engage in various forms of meditation.  Could it be that the rhythmic demans of IM, which require an individual to “lock on” to the auditory tone and stay in that synchronized, rhythmic and repetitive state for as long as possible, might be similar to the underlying mechanics of some forms of meditation, which also seek to suppress irrelevant and distracting thoughts and eventually “let the mind go"---posibbly to follow a specific train of thought with complete and distraction free focus. 

Yes…this is speculation.  I am trying to connect research-based and personal experience dots.  It is exciting.  My IM-HOME based induce personal focus experience  makes sense from the perspective of the function and interaction between the three major large scale brain networks.

Book Nook-New APA book on the adolescent brain@TheNeuroScience, 12/16/11 6:42 AM

Neuro Science (@TheNeuroScience) 12/16/11 6:42 AM Book on teen brains can help improve decision making sns.mx/q0izy5

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Oxygen therapy for brain injury and possible age-related decline

I find this particularly interesting.  My 88 year old seriously diabetic father had a leg amputated last May.  He had major post-surgical delirium that went on for months.  Then his remaining toe went south. He underwent 60 HBO sessions, and after 20 his cognition showed major improvement.  By the end his cognition was better than pre-surgery.  Everyone, including the treatment staff, observed the change and were amazed. 

April Christopherson (@maxachieveinc) 12/15/11 7:59 PM More about Oxygen Therapy for trauma, PTSD, and TBI - goo.gl/e8GZa #HBOT #Braintrauma

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Cognitive neuroscience of learning conference@NeurosciUpdate, 12/15/11 6:07 PM

Neurosci Update (@NeurosciUpdate) 12/15/11 6:07 PM Cognitive Neuroscience of Learning - The New York Academy of Sciences bit.ly/ssnTdP

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Brain Clock (temporal processing) disorder implicated in autism

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Research Bytes: Journal of Educational Psychology 2011, 23 (4)

Florit, E., & Cain, K. (2011). The Simple View of Reading: Is It Valid for Different Types of Alphabetic Orthographies? Educational Psychology Review, 23(4), 553-576.

Gegenfurtner, A., Lehtinen, E., & Saljo, R. (2011). Expertise Differences in the Comprehension of Visualizations: a Meta-Analysis of Eye-Tracking Research in Professional Domains. Educational Psychology Review, 23(4), 523-552.

Anthony, J. L., Williams, J. M., Duran, L. K., Gillam, S. L., Liang, L., Aghara, R., Swank, P. R., Assel, M. A., & Landry, S. H. (2011). Spanish Phonological Awareness: Dimensionality and Sequence of Development During the Preschool and Kindergarten Years. Journal of Educational Psychology, 103(4), 857-876.

Pan, J., McBrideChang, C., Shu, H., Liu, H. Y., Zhang, Y. P., & Li, H. (2011). What Is in the Naming? A 5-Year Longitudinal Study of Early Rapid Naming and Phonological Sensitivity in Relation to Subsequent Reading Skills in Both Native Chinese and English as a Second Language. Journal of Educational Psychology, 103(4), 897-908

Swanson, H. L. (2011). Working Memory, Attention, and Mathematical Problem Solving: A Longitudinal Study of Elementary School Children. Journal of Educational Psychology, 103(4), 821-837.

Swanson, H. L., Orosco, M. J., Lussier, C. M., Gerber, M. M., & GuzmanOrth, D. A. (2011). The Influence of Working Memory and Phonological Processing on English Language Learner Children's Bilingual Reading and Language Acquisition. Journal of Educational Psychology, 103(4), 838-856

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Silencing the unquiet mind: Interactive Metronome and controlled attention

See my task analysis (based on pesonal experience) of the brain clock based Interactive Metronome neurotechology at the following link. Using focus or controlled attention to silence the default brain network that produces REST (rapid episodic spontaneous thinking)

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Mental imagery and visual working memory@BrainCosmos, 12/15/11 10:55 AM

Brain (@BrainCosmos) 12/15/11 10:55 AM Mental Imagery and Visual Working Memory :PLoS ONE, Neuroscience bit.ly/unpcH3

Sent from Kevin McGrew's iPad

Kevin McGrew, PhD

Educational Psychologist

IQs Corner Recent Literature of Interest: 12-15-11

This weeks installment can be found at:

Http://www.iapsych.com/recentlit/lit121511.pdf

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BOOK NOOK: PsycCRITIQUES - Volume 56, Issue 50 is now available online

A new issue of PsycCRITIQUES is available online. If you would like subscription information, please go to http://www.apa.org/pubs/databases/psyccritiques/. If you have a subscription to the product and experience any access problems, please go to http://psycinfo.apa.org/help/technical/public/. December 14, 2011 Volume 56, Issue 50 Book Reviews 1. Pathways to Individuality: Evolution and Development of Personality Traits Author: Arnold H. Buss Reviewer: Larry C. Bernard 2. The Signs of a Savant: Language Against the Odds Authors: Neil Smith, Ianthi Tsimpli, Gary Morgan, and Bencie Woll Reviewer: Ian M. Evans 3. Encouragement Makes Good Things Happen Authors: Theo Schoenaker (R. John Huber, Trans., with Jutta Street and Sandra Losa) Reviewer: Patricia T. Ashton 4. Braintrust: What Neuroscience Tells Us About Morality Author: Patricia S. Churchland Reviewer: Susan Gordon 5. Formal Approaches in Categorization Authors: Emmanuel M. Pothos and Andy J. Wills (Eds.) Reviewer: Jeffrey K. Smith 6. The Mindfulness Revolution: Leading Psychologists, Scientists, Artists, and Meditation Teachers on the Power of Mindfulness in Daily Life Authors: Barry Boyce and the Editors of Shambhala Sun (Eds.) Reviewers: Larissa G. Duncan and Joseph G. Cook 7. Acceptance and Mindfulness in Cognitive Behavior Therapy: Understanding and Applying the New Therapies Authors: James D. Herbert and Evan M. Forman (Eds.) Reviewer: Jonathan Bricker 8. Cognitive Development and Working Memory: A Dialogue Between Neo-Piagetian Theories and Cognitive Approaches Authors: Pierre Barrouillet and Vinciane Gaillard (Eds.) Reviewer: Jason T. Ramsay 9. Exposure Therapy for Anxiety: Principles and Practice Authors: Jonathan S. Abramowitz, Brett J. Deacon, and Stephen P. H. Whiteside Reviewer: John E. Carr Film Review 10. The Way Back Director: Peter Weir Reviewer: Jason A. Cantone

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Miyake and Shah's (1999) book on models of working memory

The complete PDF copy of this chapter is available at Dr. Miyake's web page (link below).

http://psych-www.colorado.edu/~miyake/MWM%20Chapter%201.pdf

Info regarding the book is available at the followowing link.

http://www.amazon.com/Models-Working-Memory-Mechanisms-Maintenance/dp/0521587212









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Roberts and Lipnevich in "General to Multiple Intelligences": CHC model and WJ III, WISC-IV Integrated, SB5, KABC-III

This chapter is part of the above refernced book available at the following link:

http://www.apa.org/pubs/books/4311503.aspx










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