Showing posts with label brain location. Show all posts
Showing posts with label brain location. Show all posts

Monday, January 11, 2016

Your brain is a time machine: An oldie-but-goodie (OBG) post

This is an OBG (oldie-but-goodie) post I originally made on the IM-HOME blog

Time and space are the two fundamental dimensions of our lives. All forms of human behavior require us to process and understand information we receive from our environment in either spatial or temporal patterns. Even though mental timing (temporal processing) research is in a stage of infancy (when compared to spatial processing) important insights regarding the human brain clock have emerged.

Below is a list (albeit incomplete) of some of the major conclusions regarding the human brain clock. The sources for these statements come from my review of the temporal processing and brain clock literature during the past five years. Most of this information has been disseminated at the Brain Clock blog or the Brain Clock Evolving Web of Knowledge (EWOK). The goal of this post is to provide a Readers Digest summary of the major conclusions. This material can serve as a set of "talking points" at your next social event where you can impress your friends and family as you explain why you use the high-tech IM "clapper" (with a cowbell tone no less) either as a provider or as client.

Our brains measure time constantly. It's hard to find any complex human behavior where mental timing is not involved. Timing is required to walk, talk, perform complex movements and coordinate information flow across the brain for complex human thought. Think about moving your arm and hand to grasp a coffee cup. The messages to perform this task originate in your brain, which is not directly connected to your arm, hands and fingers. The ability to perform the necessary motor movements is possible only because the mind and extremities are connected via timing. Precisely timed neural messages connect your brain and extremities. You are a time machine.


Humans are remarkably proficient at internally perceiving and monitoring time to produce precisely timed behaviors and thinking. “We are aware of how long we have been doing a particular thing, how long it has been since we last slept, and how long it will be until lunch or dinner. We are ready, at any moment, to make complex movements requiring muscle coordination with microsecond accuracy, or to decode temporally complex auditory signals in the form of speech or music. Our timing abilities are impressive…” (Lewis & Walsh, 2005, p. 389).

To deal with time, humans have developed multiple timing systems that are active over more than 10 orders of magnitude with various degrees of precision (see figure below from Buhusi & Meck, 2005). These different timing systems can be classified into three general classes (viz., circadian, interval, and millisecond timing), each associated with different behaviors and brain structures and mechanisms. The fastest timing system (millisecond or interval timing) is involved in a numerous human behaviors such as speech and language, music perception and production, coordinated motor behaviors, attention, and thinking. This fast interval timing system is the most important timing system for understanding and diagnosing clinical disorders and for developing and evaluating effective treatment interventions for educational and rehabilitation settings. It is this timing system, and the relevant research, that is relevant to understanding Interactive Metronome. (Note.  See my conflict of interest statement at this blog.  I have an ongoing consulting relationship with IM).



Although there is consensus that the human brain contains some kind of clock, the jury is still out on the exact brain mechanisms and locations. It is also not clear whether there is one functional master clock or a series of clocks deployed in different brain areas. The areas of the brain most consistently associated with milli-second interval mental timing are the cerebellum, anterior cingulate, basal ganglia, the dorsolateral prefrontal cortex, right parietal cortex, motor cortex, and the frontal-striatal loop. That is a mouthful of technical brain terms. But, if you can memorize them and have them roll of your tongue with ease you will “shock and awe” your family and friends. Most of these areas of the brain are illustrated below. Now, if you really want to demonstrate your expertise, get your own illustrated “brain-in-a-pocket”. These images were generated by the free 3D Brain app available for your iPhone or iPad. Even cooler is the fact that you can rotate the images with your finger! You can give neuroanatomy lessons anytime…anywhere!



Research suggests that mental interval timing is controlled by two sub-systems. The automatic timing system processes discrete-event (discontinuous) timing in milliseconds. The cognitively-controlled timing system deals with continuous-event timing (in seconds) that requires controlled attention and working memory. Both systems are likely involved in IM. For example, the synchronized clapping requires motor planning and execution, functions most associated with the automatic timing system. However, the cognitive aspects of IM (focus, controlled attention, executive functions) invoke the cognitively controlled timing system. Aren’t these brain images awesome?



The dominant model in the brain clock research literature is that of a centralized internal clock that functions as per the pacemaker–accumulator model. Briefly, this is a model where an oscillator beating at a fixed frequency generates tics that are detected by a counter. For now I am just going to tease you with an image of this model. You can read more about this model at the Brain Clock blog.


Research suggests that the brain mechanisms underlying mental timing can be fine-tuned (modified) via experience and environmental manipulation. Modifiability of mental interval timing and subsequent transfer suggest a domain-general timing mechanism that, if harnessed via appropriately designed timing-based interventions, may improve human performance in a number of important cognitive and motor domains.

Tuesday, May 17, 2011

Journal of Cognitive Neuroscience: Simply AWESOME




I just spent some time browsing the articles lined up for forthcoming publication in the Journal of Cognitive Neuroscience. As a researcher who is looking for good research that links my primary are of interest (intelligence and measurement of intelligence) with underlying brain mechanisms, I think I have found the pot-o-gold at the end of the brain-behavior rainbow. Below is the list of articles the journal currently has "waiting in the wings." The depth and breadth is amazing. I have added this journal to my RSS feed so I can stay up-to-date when articles are published.

What a way to start my day. Finding this will sipping my morning java. Now if I could only fine time to read just a 1/4 of these articles.

Well MIT Press.

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Saturday, February 12, 2011

The Cognitive Atlas Project - way cool stuff

Very intriguing article and description of the Cognitive Atlas Project, a scientific social collaborative knowledge project.









Poldrack, R. A. (2010). Mapping Mental Function to Brain Structure: How Can Cognitive Neuroimaging Succeed? Perspectives on Psychological Science, 5(6), 753-761

Abstract

The goal of cognitive neuroscience is to identify the mapping between brain function and mental processing. In this article, I examine the strategies that have been used to identify such mappings and argue that they may be fundamentally unable to identify selective structure–function mappings. To understand the functional anatomy of mental processes, it will be necessary for researchers to move from the brain-mapping strategies that the field has employed toward a search for selective associations. This will require a greater focus on the structure of cognitive processes, which can be achieved through the development of formal ontologies that describe the structure of mental processes. In this article, I outline the Cognitive Atlas Project, which is developing such ontologies, and show how this knowledge could be used in conjunction with data-mining approaches to more directly relate mental processes and brain function.










The article , with annotations, is available here, as part of this blogs IQ's Reading feature.



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Thursday, February 10, 2011

Research Bytes: Neuro-imaging research--brain networks and public interest


Beck, D. M. (2010). The Appeal of the Brain in the Popular Press. Perspectives on Psychological Science, 5(6), 762-766.

Since the advent of human neuroimaging, and of functional magnetic resonance imaging (fMRI) in particular, the popular press has shown an increasing interest in brain-related findings. In this article, I explore possible reasons behind this interest, including recent data suggesting that people find brain images and neuroscience language more convincing than results that make no reference to the brain (McCabe & Castel, 2008; Weisberg, Keil, Goodstein, Rawson, & Gray, 2008). I suggest that part of the allure of these data are the deceptively simply messages they afford, as well as general, but sometimes misguided, confidence in biological data. In addition to cataloging some misunderstandings by the press and public, I highlight the responsibilities of the research scientist in carefully conveying their work to the general public.


Gonsalves, B. D., & Cohen, N. J. (2010). Brain Imaging, Cognitive Processes, and Brain Networks. Perspectives on Psychological Science, 5(6), 744-752.


McDonald, R. P. (2010). Structural Models and the Art of Approximation. Perspectives on Psychological Science, 5(6), 675-686

Structural equation models have provided a seemingly rigorous method for investigating causal relations in nonexperimental data in the presence of measurement error or multiple measures of putative causes or effects. Methods have been developed for fitting these very complex models globally and obtaining global fit statistics or global measures of their approximation to sample data. Structural equation models are idealizations that can serve only as approximations to real multivariate data. Further, these models are multidimensional, and the approximation is itself multidimensional. Tests of “significance” and global indices of approximation do not provide an adequate basis for judging the acceptability of the approximation. Standard applications of structural models use a composite of two models—a measurement (path) model and a path (causal) model. Separate analyses of the measurement model and the path model provide an informed judgment, whereas the composite global analysis can easily yield unreasonable conclusions. Separating the component models enables a careful assessment of the actual constraints implied by the path model, using recently developed methods. An empirical example shows how the conventional global treatment yields unacceptable conclusions


Poldrack, R. A. (2010). Mapping Mental Function to Brain Structure: How Can Cognitive Neuroimaging Succeed? Perspectives on Psychological Science, 5(6), 753-761

The goal of cognitive neuroscience is to identify the mapping between brain function and mental processing. In this article, I examine the strategies that have been used to identify such mappings and argue that they may be fundamentally unable to identify selective structure–function mappings. To understand the functional anatomy of mental processes, it will be necessary for researchers to move from the brain-mapping strategies that the field has employed toward a search for selective associations. This will require a greater focus on the structure of cognitive processes, which can be achieved through the development of formal ontologies that describe the structure of mental processes. In this article, I outline the Cognitive Atlas Project, which is developing such ontologies, and show how this knowledge could be used in conjunction with data-mining approaches to more directly relate mental processes and brain function.


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Wednesday, November 03, 2010

Research bytes: Gf and Gv related to higher level math achievement




To cite this Article: Prescott, James , Gavrilescu, Maria , Cunnington, Ross , O'Boyle, Michael W. and Egan, Gary F. (2010) 'Enhanced brain connectivity in math-gifted adolescents: An fMRI study using mental rotation', Cognitive Neuroscience, 1:4, 277 - 288, First published on: 09 August 2010 (iFirst)

Abstract

Mathematical giftedness is a form of intelligence related to enhanced mathematical reasoning that can be tested using a variety of numerical and spatial tasks. A number of neurobiological mechanisms related to exceptional mathematical reasoning ability have been postulated, including enhanced brain connectivity. We aimed to further investigate this possibility by comparing a group of mathematically gifted adolescents with an average math ability control group performing mental rotation of complex three-dimensional block figures. Functional magnetic resonance imaging (fMRI) data were collected and differences in intrahemispheric and interhemispheric connectivity between the groups were assessed using structural equation modeling (SEM). The math-gifted showed heightened intrahemispheric frontoparietal connectivity, as well as enhanced interhemispheric frontal connectivity between the dorsolateral prefrontal and premotor cortex. These enhanced connectivity patterns are consistent with previous studies linking increased activation of the frontal and parietal regions with high fluid intelligence, and may be a unique neural characteristic of the mathematically gifted brain.





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Thursday, June 25, 2009

Neural efficiency, executive function and intelligence (g, IQ): An embarrasment of riches

I give up. I don't have the time, or maybe the neural efficiency, to read, digest, integrate, and summarize a wave of recent research articles dealing with the concept of neural efficiency (oscillations) and intelligence. That being said, I'm simply going to post the references and abstracts. Maybe an interested IQ's Corner blog reader would be interested in reading these articles and attempting to summarize (via a guest blog post)...something I had hoped to do.

When less is more and when more is more: The mediating roles of capacity and speed in brain-behavior efficiency (Bart Rypma and Vivek Prabhakaran). Intelligence 37 (2009) 207–22.
An enduring enterprise of experimental psychology has been to account for individual differences in human performance. Recent advances in neuroimaging have permitted testing of hypotheses regarding the neural bases of individual differences but this burgeoning literature has been characterized by inconsistent results. We argue that careful design and analysis of neuroimaging studies is required to separate individual differences in processing capacity from individual differences in processing speed to account for these differences in the literature. We utilized task designs which permitted separation of processing capacity influences on brainbehavior relationships from those related to processing speed. In one set of studies, participants performed verbal delayed-recognition tasks during blocked and event-related fMRI scanning. The results indicated that those participants with greater working memory (WM) capacity showed greater prefrontal cortical activity, strategically capitalized on the additional processing time available in the delay period, and evinced faster WM-retrieval rates than low-capacity participants. In another study, participants performed a digit-symbol substitution task (DSST) designed to minimize WM storage capacity requirements and maximize processing speed requirements during fMRI scanning. In some prefrontal cortical (PFC) brain regions, participants with faster processing speed showed less PFC activity than slower

Neuroanatomical correlates of intelligence (Eileen Luders, Katherine L. Narr, Paul M. Thompson and Arthur W. Toga). Intelligence 37 (2009) 156–163.
With the advancement of image acquisition and analysis methods in recent decades, unique opportunities have emerged to study the neuroanatomical correlates of intelligence. Traditional approaches examining global measures have been complemented by insights from more regional analyses based on pre-defined areas. Newer state-of-the-art approaches have further enhanced our ability to localize the presence of correlations between cerebral characteristics and intelligence with high anatomic precision. These in vivo assessments have confirmed mainly positive correlations, suggesting that optimally increased brain regions are associated with better cognitive performance. Findings further suggest that the models proposed to explain the anatomical substrates of intelligence should address contributions from not only (pre)frontal regions, but also widely distributed networks throughout the whole brain.
Exploring possible neural mechanisms of intelligence differences using processing speed and working memory tasks: An fMRI study (Gordon D. Waiter, Ian J. Deary, Roger T. Staff, Alison D. Murray, Helen C. Fox, John M. Starr and Lawrence J. Whalley). Intelligence 37 (2009) 199–206
To explore the possible neural foundations of individual differences in intelligence test scores, we examined the associations between Raven's Matrices scores and two tasks that were administered in a functional magnetic resonance imaging (fMRI) setting. The two tasks were an n-back working memory (N = 37) task and inspection time (N = 47). The subjects were members of the Aberdeen Birth Cohort 1936, aged in their mid–late 60s when tested for this study. Performance on both tasks was correlated significantly with scores on Raven's Matrices. In the inspection time task there were regions with significant correlations between the neural activity (BOLD response) and performance but not between BOLD response and scores on Raven's Matrices. In the working memory task there were no significant correlations between BOLD response and either performance or scores on Raven's Matrices. Moreover, there was almost no mediation of the Raven's Matrices versus n-back and inspection time scores correlations by the respective BOLD response. These findings partially replicate important aspects of a prominent report in this field [Gray, J.R., Chabris, C.F., & Braver, T.S. (2003). Neural mechanisms of general fluid intelligence. Nature Neuroscience, 6, 316–322.], but have also extended the those finding into both a unique population and a novel functional task.
Intelligence and neural efficiency: Measures of brain activation versus measures of functional connectivity in the brain (Aljoscha C. Neubauer and Andreas Fink). Intelligence 37 (2009) 223–229
The neural efficiency hypothesis of intelligence suggests a more efficient use of the cortex (or even the brain) in brighter as compared to less intelligent individuals. This has been shown in a series of studies employing different neurophysiological measurement methods and a broad range of different cognitive task demands. However, most of the studies dealing with the brain–IQ relationship used parameters of absolute or relative brain activation such as the eventrelated (de-)synchronization of EEG alpha activity, allowing for interpretations in terms of more or less brain activation when individuals are confronted with cognitively demanding tasks. In order to investigate the neural efficiency hypothesis more thoroughly, we also used measures that inform us about functional connectivity between different brain areas (or functional coupling, respectively) when engaged in cognitive task performance. Analyses reveal evidence that higher intelligence is associated with a lower brain activation (or a lower ERD, respectively) and a stronger phase locking between short-distant regions of the frontal cortex.
Gray matter and intelligence factors: Is there a neuro-g? (Richard J. Haier, Roberto Colom, David H. Schroeder, Christopher A. Condon, Cheuk Tang, Emily Eaves and Kevin Head). Intelligence 37 (2009) 136–144
Heterogeneous results among neuro-imaging studies using psychometric intelligence measures may result from the variety of tests used. The g-factor may provide a common metric across studies. Here we derived a g-factor from a battery of eight cognitive tests completed by 6929 young adults, 40 of whom also completed structural MRI scans. Regional gray matter (GM) was determined using voxel-based-morphometry (VBM) and correlated to g-scores. Results showed correlations distributed throughout the brain, but there was limited overlap with brain areas identified in a similar study that used a different battery of tests to derive g-scores. Comparable spatial scores (with g variance removed) also were derived from both batteries, and there was considerable overlap in brain areas where GM was correlated to the respective spatial scores. The results indicate that g-scores derived from different test batteries do not necessarily have equivalent neuro-anatomical substrates, suggesting that identifying a “neurog” will be difficult. The neuro-anatomical substrate of a spatial factor, however, appears more consistent and implicates a distributed network of brain areas that may be involved with spatial ability. Future imaging studies directed at identifying the neural basis of intelligence may benefit from usinga psychometric test battery chosen with specific criteria.

Intergenerational transmission of neuropsychological executive functioning ("Jennifer M. Jester, Joel T. Nigg, Leon I. Puttler, Jeffrey C. Long, Hiram E. Fitzgerald and Robert A. Zucker"). Brain and Cognition 70 (2009) 145–153
Relationships between parent and child executive functioning were examined, controlling for the critical potential confound of IQ, in a family study involving 434 children (130 girls and 304 boys) and 376 parents from 204 community recruited families at high risk for the development of substance use disorder. Structural equation modeling found evidence of separate executive functioning and intelligence (IQ) latent variables. Mother’s and father’s executive functioning were associated with child’s executive functioning (beta = 0.34 for father–child and 0.51 for mother–child), independently of parental IQ, which as expected was associated with child’s IQ (beta = 0.52 for father–child and 0.54 for mother–child). Familial correlations also showed a significant relationship of executive functioning between parents and offspring. These findings clarify that key elements of the executive functioning construct are reliably differentiable from IQ, and are transmitted in families. This work supports the utility of the construct of executive function in further study of the mechanisms and etiology of externalizing psychopathologies.

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Tuesday, June 16, 2009

WCST: Does it really measure frontal lobe executive functions?



Does the WCST measure executive functioning? There is little doubt that the WCST is one of the predominant tests used in neuropsychological assessment to assess executive functions. However, studies have recently questioned the validity of drawing inferences about the site of executive functions (the frontal lobes of the brain) from performance on the WCST. The following "in press" article, which presents a nice review of the literature, suggests that in it's current administration formats the WCST is not the sensitive measure of frontal lobe executive functioning as is often thought. Below I present the abstract, a few select passages, and the primary conclusion from this excellent review article.

Nyhus, E., & Barceló, F. (in press). The Wisconsin Card Sorting Test and the cognitive assessment of prefrontal executive functions: A critical update. Brain and Cogntion.

Abstract

For over four decades the Wisconsin Card Sorting Test (WCST) has been one of the most distinctive tests of prefrontal function. Clinical research and recent brain imaging have brought into question the validity and specificity of this test as a marker of frontal dysfunction. Clinical studies with neurological patients have confirmed that, in its traditional form, the WCST fails to discriminate between frontal and non-frontal lesions. In addition, functional brain imaging studies show rapid and widespread activation across frontal and non-frontal brain regions during WCST performance. These studies suggest that the concept of an anatomically pure test of prefrontal function is not only empirically unattainable, but also theoretically inaccurate. The aim of the present review is to examine the causes of these criticisms and to resolve them by incorporating new methodological and conceptual advances in order to improve the construct validity of WCST scores and their relationship to prefrontal executive functions. We conclude that these objectives can be achieved by drawing on theory-guided experimental design, and on precise spatial and temporal sampling of brain activity, and then exemplify this using an integrative model of prefrontal function [i.e., Miller, E. K. (2000). The prefrontal cortex and cognitive control. Nature Reviews Neuroscience, 1, 59–65.] combined with the formal information theoretical approach to cognitive control [Koechlin, E., & Summerfield, C. (2007). An information theoretical approach to prefrontal executive function. Trends in Cognitive Sciences, 11, 229–235.].

According to the authors, there are at least two different systems of administration and scoring of the WCST. There is the "standard version by Grant and Berg (1948) with Milner´s (1963) correction criteria and the shortened version by Heaton (Heaton, 1981; Heaton, Chelune, Talley, Kay, & Curtis, 1993 ). Furthermore, the test has been administered in modified versions by Nelson (1976), Delis, Squire, Bihrle, and Massman (1992), and Barceló (1999, 2003)."

In the conventional administration:
the WCST consists of four key cards and 128 response cards with geometric figures that vary according to three perceptual dimensions (color, form, or number). The task requires subjects to find the correct classification principle by trial and error and examiner feedback. Once the subject chooses the correct rule they must maintain this sorting principle (or set) across changing stimulus conditions while ignoring the other – now irrelevant – stimulus dimensions. After ten consecutive correct matches, the classification principle changes without warning, demanding a flexible shift in set. The WCST is not timed and sorting continues until all cards are sorted or a maximum of six correct sorting criteria have been reached.
Conclusions
The present interest in prefrontal cortex function has renewed the use of the WCST in clinical and experimental settings. However, much criticism has questioned the utility of this test as a marker of prefrontal function. A critical review of clinical studies suggests that the original WCST does not distinguish between frontal and non-frontal lesions. Likewise, functional neuroimaging studies confirm that delivery of negative feedback during WCST rule transitions activates a widespread network of frontal and non-frontal regions within a split-second time scale. New methodological and conceptual advances from theory-guided experimental designs, precise spatial and temporal sampling of brain activity, and modern integrative models of prefrontal function (Miller, 2000) combined with a formal information theoretical approach to cognitive control (Koechlin & Summerfield, 2007) can improve our understanding of the WCST and its relationship to prefrontal executive functions. These advances suggest that simple modifications of the original version of the WCST may offer more valid and reliable measures of key component operations, such as the maintenance, shifting, and updating of task-set information over trials. Fast brain imaging techniques help us put into perspective the specificity of the test as a marker of prefrontal function as a key node within the widely distributed and tightly interconnected neural networks subserving human cognition.

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Friday, April 03, 2009

WAIS-III brain injury lession mapping research

Interesting 2006 WAIS-III brain injury lesion mapping study by Glascher et al. in Neuron.  I have some concerns about the interpretation of the results (see below), but see this as a neat study because of the large sample size for lesion-specific subjects (n=241) and the very interesting visual-graphic presentation of the results...esp. the grand summary figure in the discussion section.  Also, a supplementary report to the article is also available.

My concerns are related to the presence of construct irrelvant variance (when viewed from a CHC lense - and the results of CHC-based cross-battery studies) in some of the WAIS-III index scores used.  The Verbal Comprehension Index (VCI) is a good indicator of Gc.  Processing Speed (PSI) is a good index for Gs.  However, the Working Memory Index (WMI) is a mixed measure of Gsm (Digit Span and Letter-Number Sequencing) and Gq (see prior post about Arithmetic test Gq classification), and the Perceptual Organization Index (POI) is a mixed measure of Gv (Block Design and Picture Completion) and Gf (Matris Reasoning).  This suggests caution when trying to interpret the research findings from a CHC perspective.  However, I can see the practical and functional utility of knowing the relations between WAIS-III index scores, even if some are not the most valid CHC indicators, and possible brain lessions.

We need more research like this using more construct valid indicators of CHC abilities.

Abstract

The Wechsler Adult Intelligence Scale (WAIS) assesses a wide range of cognitive abilities and impairments. Factor analyses have documented four underlying indices that jointly comprise intelligence as assessed with the WAIS: verbal comprehension (VCI), perceptual organization (POI), working memory (WMI), and processing speed (PSI). We used nonparametric voxel-based lesion-symptom mapping in 241 patients with focal brain damage to investigate their neural underpinnings. Statistically significant lesion-deficit relationships were found in left inferior frontal cortex for VCI, in left frontal and parietal cortex for WMI, and in right parietal cortex for POI. There was no reliable single localization for PSI. Statistical power maps and cross-validation analyses quantified specificity and sensitivity of the index scores in predicting lesion locations. Our findings provide comprehensive lesion maps of intelligence factors, and make specific recommendations for interpretation and application of the WAIS to the study of intelligence in health and disease.
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Tuesday, March 31, 2009

Brain structures and impulsivity

Thanks to MIND BLOG

http://mindblog.dericbownds.net/2009/03/brain-structures-that-correlate-with.html


Kevin McGrew PhD
Educational/School Psych.
IAP (www.iapsych.com)

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Monday, March 30, 2009

Free brain videos

Thanks to BRAIN INJURY blog.

http://braininjury.blogs.com/braininjury/2009/03/free-brain-videos.html


Kevin McGrew PhD
Educational/School Psych.
IAP (www.iapsych.com)

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Saturday, March 28, 2009

Brain atlas project

Check it out at WIRED

http://www.wired.com/medtech/health/multimedia/2009/03/ff_brainatlas_gallery


Kevin McGrew PhD
Educational/School Psych.
IAP (www.iapsych.com)

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Thursday, March 19, 2009

SES and brain functions

How does SES related to neurological functioning?

Much has been written and summarized regarding the relation between SES, achievement, and intelligence. More recently on the scene are researchers trying to establish links between SES and neurological functioning. In the recent edition of Trends in Cognitive Sciences (on of my favorite science journals for providing brief overview summaries of topics), Hackman and Farah summarize much of this literature. I found the strongest links between SES and the executive function and language systems of the brain (they organized their review around five primary brain systems) of most interest. The discussion of the operationalization of the construct of SES was also informative and should be reviewed by those doing research on the relations between SES and intelligence and/or those who design representative norm samples for intelligence and achievement tests.

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Saturday, March 14, 2009

From the past: Phrenology favorites

Thanks to IMPROVABLE RESEARCH for this post.

http://improbable.com/2009/03/14/phrenology-favorites/


Kevin McGrew PhD
Educational/School Psych.
IAP (www.iapsych.com)

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Saturday, January 17, 2009

Thursday, January 15, 2009

Interactive brain tour

Thanks to HAPPY NEURON for the tip regarding this resource.

http://blog.happy-neuron.com/brain-anatomy-and-imaging/how-does-the-brain-work/


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Wednesday, December 24, 2008

Vintage brain graphic art t-shirt

http://www.cafepress.com/2swell/2771882


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Sunday, November 16, 2008