The Human Connectome - A Structural Description of the Human Brain (Sporns et al)
One of the major limitations in the effort to improve our understanding of the brain-mind relationship is the lack of available data on the arrangement and connections of and among neurons in the brain. The authors of this article propose "connectome" as the name for this important data set, and suggest that the data set include details on neuron position (using a common coordinate system), the absence or presence of connection(s) to other neuron(s), and, if those connections are present, information on the type of connection (ie. excitatory or inhibitory) and the biochemical / biophysical details of the connection. Furthermore, the authors suggest a strategic approach to the development of the connectome: given that one of the primary uses of the connectome will be to establish the link between brain activity and cognitive activity, it would make sense to establish the connectome of the cortex first. The authors further suggest that the connectome should first be described at a larger scale than individual neurons, given the enormous number of neurons in the human brain (approximately 10^11), the even larger number of connections among neurons (approximately 10^13), the plasticity of individual neurons and synapses, and the apparent role of groups of neurons (fibers) in brain function. Although it is difficult to isolate functional groups of fibers, the authors propose that a particular MRI method known as diffusion tensor imaging (DTI) could be useful in developing this initial draft of the connectome.
Exploring relationships among neuroscience, cognitive psychology, and learning. Sprinkled with education policy, reform, and leadership, STEM education research, and technology.
Wednesday, April 30, 2008
Monday, April 28, 2008
Development, nutrition, and learning
Compensatory Growth Impairs Adult Cognitive Performance (Fisher et al)
In this study, zebra finch birds were used to explore the consequences of poor nutrition early in life on cognitive performance later in life. The researchers found that the zebra finches that exhibited the most growth following the end of the period of poor nutrition showed the slowest performance on the learning task. What's interesting is that all birds tested for speed on a learning task as adults were of the same size, even though one group of birds had been subjected to nutritional deprivation. So, the researchers were able to compare the adult size of the bird with their size at the end of the period of poor nutrition to quantify the compensatory growth their bodies produced when a healthier diet became available. Similar studies are cited in the research that involved comparing the cognitive performance of human babies born at low birth weight, some of whom received a nutritionally-enriched diet and others of whom did not; the results were similar to those found in the zebra finch bird study. This study provides further support for the well-accepted idea that phenotypes are influenced by environmental variables such as nutrition, and that cognitive phenotypes are not an exception. However, this study adds significant detail on phenotype variability resulting from changes in the environment that take place during critical periods of development, particularly relative to the development of the brain. Although the "big picture" suggestion is certainly not to withhold better nutrition if and when it is available, it is interesting to note that the overall benefit of compensatory growth can cause some specific deficiencies later in life, particularly with regard to cognitive systems. Further research should investigate the consequences of varied timing of nutritional deficits and their impact on learning later in life, but for now it seems clear that we should make every effort to ensure that nutritious food is available from the beginning and throughout a child's life.
In this study, zebra finch birds were used to explore the consequences of poor nutrition early in life on cognitive performance later in life. The researchers found that the zebra finches that exhibited the most growth following the end of the period of poor nutrition showed the slowest performance on the learning task. What's interesting is that all birds tested for speed on a learning task as adults were of the same size, even though one group of birds had been subjected to nutritional deprivation. So, the researchers were able to compare the adult size of the bird with their size at the end of the period of poor nutrition to quantify the compensatory growth their bodies produced when a healthier diet became available. Similar studies are cited in the research that involved comparing the cognitive performance of human babies born at low birth weight, some of whom received a nutritionally-enriched diet and others of whom did not; the results were similar to those found in the zebra finch bird study. This study provides further support for the well-accepted idea that phenotypes are influenced by environmental variables such as nutrition, and that cognitive phenotypes are not an exception. However, this study adds significant detail on phenotype variability resulting from changes in the environment that take place during critical periods of development, particularly relative to the development of the brain. Although the "big picture" suggestion is certainly not to withhold better nutrition if and when it is available, it is interesting to note that the overall benefit of compensatory growth can cause some specific deficiencies later in life, particularly with regard to cognitive systems. Further research should investigate the consequences of varied timing of nutritional deficits and their impact on learning later in life, but for now it seems clear that we should make every effort to ensure that nutritious food is available from the beginning and throughout a child's life.
Friday, April 25, 2008
Plagiarism education, the ontology of ideas, and epistemological resources
Through my experiences in education, I've generally observed that students appear to have a relatively superficial understanding of what plagiarism is and why it's wrong. Because of the general lack of deep understanding of the issue, along with its potential repercussions, I feel that learning about plagiarism is critical to student growth and development. Traditional approaches to plagiarism education tend to be based on the misconceptions model for learning. Perhaps a better approach to promoting student learning about the issues surrounding plagiarism could be based on a cognitive resources conceptual model involving students' personal epistemological resources.
It is my experience that students reach relatively fast and easy agreement that wholesale "copy and paste" without citation is plagiarism and is wrong. Students can see that such actions deny credit to others who have put forth significant effort, and that this type of plagiarism clearly inhibit the teacher's ability to assess their personal understanding of the knowledge or skill at hand. Students do admit that it happens, but tend to blame the behavior on laziness and/or procrastination. However, in situations in which they submit work in a good-faith attempts to complete assignments according to teacher instructions, students are in much greater disagreement with regard to the more abstract forms of plagiarism that involve using ideas and/or structures of ideas without citation. For example, students are often challenged to do research for assignments, and are instructed to express "in their own words" the information they find. Many students feel that an idea that has been re-worded is sufficiently different enough from the original that citation is not required, while others feel that ideas taken from others must be cited even if expressed in alternate wording. Some students can see extensions of the issue of citation, and question whether the teacher should be cited for ideas transmitted orally in class or otherwise.
Students can become frustrated when confronted with rigorous interpretations of plagiarism that require comprehensive citation. The position of such students tends to be, in essence, that ideas are so fundamentally dependent on other non-original knowledge that they can't be copied (ie: only the expression of ideas can be copied). In other words, student frustrations about citation rules seem to be influenced by their understanding of the complexity of the "heredity" of ideas. Simply put, these students feel that ideas are either observations available to anyone or are already so dependent on other foundational concepts that they don't deserve qualification as original; in neither case is citation viewed as necessary. I think it's important to acknowledge that there is significant understanding about the origin and nature of ideas underlying the position that new ideas are based on pre-existing ideas. Perhaps the frustration these students experience has to do with uncertainty on how far back citation has to go in order to avoid plagiarism. These are pretty insightful thoughts and completely valid concerns, given that plagiarism and its significant consequences are presented in a very black & white, right & wrong dichotomy. I think these students are putting forth the effort to promote their own learning and to follow their teachers' guidelines and want a clear set of rules on how to avoid crossing the line and committing plagiarism.
As I've been thinking about student understanding of plagiarism and its fundamental relationship with concepts on the origin and nature of ideas, I've remembered some reading I did in grad school on personal epistemology (Hofer, 2001) and on using epistemological resources in physics education (Hammer & Elby, 2003). At this stage my thoughts are still in a very formative stage with regard to using epistemological resources in plagiarism education. However, it seems to me very clear that the students I've encountered do have concepts of knowledge and knowing that are activated when they discuss plagiarism. Furthermore, it also seems clear to me that students could benefit from improvements to plagiarism education that would move it beyond the misconceptions approach and into a cognitive resources approach. Efforts in this direction include the book "Originality, Imitation, and Plagiarism" edited by Eisner and Vicinus highlighted by Inside Higher Education, which also highlighted specific plagiarism education methods presented by Hagopian and others at a recent conference on college writing. My hope is that further development of a conceptual model for student thinking on plagiarism, based on epistemological cognitive resources, will advance student and teacher understanding of a topic that is clearly more complex than a misconception of academic integrity.
EDIT: After posting this I decided to do a Google search on "plagiarism and epistemology", wondering if anyone else was thinking on the same track. Although it seems we've come to it from somewhat different paths, Rebecca Moore Howard has much more extensive and refined work on the epistemology of plagiarism, the afore-linked presented at a conference (called "Originality, Imitation, and Plagiarism") at the University of Michigan in 2005. As is clear from her publications list, I've got lots of reading to do - and I'm sure I'll find even more. It's going to be interesting to explore applying these ideas with secondary-level students ... perhaps I'll even find others in secondary-ed who are already on this track, too. I'll keep posting on this, but wanted to edit this post to include this disclaimer to avoid any potential appearance plagiarism on my own part!
References
Hammer, D. and Elby, A. (2003). Tapping Epistemological Resources for Learning Physics. Journal of the Learning Sciences, 12, 53-90.
Hofer, B. (2001). Personal epistemology research: Implications for learning and
instruction. Educational Psychology Review, 13(4), 353-382.
It is my experience that students reach relatively fast and easy agreement that wholesale "copy and paste" without citation is plagiarism and is wrong. Students can see that such actions deny credit to others who have put forth significant effort, and that this type of plagiarism clearly inhibit the teacher's ability to assess their personal understanding of the knowledge or skill at hand. Students do admit that it happens, but tend to blame the behavior on laziness and/or procrastination. However, in situations in which they submit work in a good-faith attempts to complete assignments according to teacher instructions, students are in much greater disagreement with regard to the more abstract forms of plagiarism that involve using ideas and/or structures of ideas without citation. For example, students are often challenged to do research for assignments, and are instructed to express "in their own words" the information they find. Many students feel that an idea that has been re-worded is sufficiently different enough from the original that citation is not required, while others feel that ideas taken from others must be cited even if expressed in alternate wording. Some students can see extensions of the issue of citation, and question whether the teacher should be cited for ideas transmitted orally in class or otherwise.
Students can become frustrated when confronted with rigorous interpretations of plagiarism that require comprehensive citation. The position of such students tends to be, in essence, that ideas are so fundamentally dependent on other non-original knowledge that they can't be copied (ie: only the expression of ideas can be copied). In other words, student frustrations about citation rules seem to be influenced by their understanding of the complexity of the "heredity" of ideas. Simply put, these students feel that ideas are either observations available to anyone or are already so dependent on other foundational concepts that they don't deserve qualification as original; in neither case is citation viewed as necessary. I think it's important to acknowledge that there is significant understanding about the origin and nature of ideas underlying the position that new ideas are based on pre-existing ideas. Perhaps the frustration these students experience has to do with uncertainty on how far back citation has to go in order to avoid plagiarism. These are pretty insightful thoughts and completely valid concerns, given that plagiarism and its significant consequences are presented in a very black & white, right & wrong dichotomy. I think these students are putting forth the effort to promote their own learning and to follow their teachers' guidelines and want a clear set of rules on how to avoid crossing the line and committing plagiarism.
As I've been thinking about student understanding of plagiarism and its fundamental relationship with concepts on the origin and nature of ideas, I've remembered some reading I did in grad school on personal epistemology (Hofer, 2001) and on using epistemological resources in physics education (Hammer & Elby, 2003). At this stage my thoughts are still in a very formative stage with regard to using epistemological resources in plagiarism education. However, it seems to me very clear that the students I've encountered do have concepts of knowledge and knowing that are activated when they discuss plagiarism. Furthermore, it also seems clear to me that students could benefit from improvements to plagiarism education that would move it beyond the misconceptions approach and into a cognitive resources approach. Efforts in this direction include the book "Originality, Imitation, and Plagiarism" edited by Eisner and Vicinus highlighted by Inside Higher Education, which also highlighted specific plagiarism education methods presented by Hagopian and others at a recent conference on college writing. My hope is that further development of a conceptual model for student thinking on plagiarism, based on epistemological cognitive resources, will advance student and teacher understanding of a topic that is clearly more complex than a misconception of academic integrity.
EDIT: After posting this I decided to do a Google search on "plagiarism and epistemology", wondering if anyone else was thinking on the same track. Although it seems we've come to it from somewhat different paths, Rebecca Moore Howard has much more extensive and refined work on the epistemology of plagiarism, the afore-linked presented at a conference (called "Originality, Imitation, and Plagiarism") at the University of Michigan in 2005. As is clear from her publications list, I've got lots of reading to do - and I'm sure I'll find even more. It's going to be interesting to explore applying these ideas with secondary-level students ... perhaps I'll even find others in secondary-ed who are already on this track, too. I'll keep posting on this, but wanted to edit this post to include this disclaimer to avoid any potential appearance plagiarism on my own part!
References
Hammer, D. and Elby, A. (2003). Tapping Epistemological Resources for Learning Physics. Journal of the Learning Sciences, 12, 53-90.
Hofer, B. (2001). Personal epistemology research: Implications for learning and
instruction. Educational Psychology Review, 13(4), 353-382.
Thursday, April 17, 2008
Using the Wiimote to research the relationship between movement and cognition
Exploring Action Dynamics as an Index of Paired-Associate Learning (Dale et al)
The above article extends support for the relationship between movement and cognition (and cites a number of interesting articles that do the same). One rather unique and interesting aspect of this study is its methodology, in particular the decision to use Nintendo's Wii Remote (Wiimote) to measure movement during a learning task. Specifically, the aim of the above study was to measure various aspects of short-time-scale movements and investigate their possible correlation with longer-time-scale learning. Although the learning task was rather simplistic (association of symbolic pairs), the results indicated a strong relationship between movement and cognition. The researchers found that movement patterns changed predictably during the learning task and argue that movement patterns could be used as an index for measuring the success of the learner in the task at hand.
The above article extends support for the relationship between movement and cognition (and cites a number of interesting articles that do the same). One rather unique and interesting aspect of this study is its methodology, in particular the decision to use Nintendo's Wii Remote (Wiimote) to measure movement during a learning task. Specifically, the aim of the above study was to measure various aspects of short-time-scale movements and investigate their possible correlation with longer-time-scale learning. Although the learning task was rather simplistic (association of symbolic pairs), the results indicated a strong relationship between movement and cognition. The researchers found that movement patterns changed predictably during the learning task and argue that movement patterns could be used as an index for measuring the success of the learner in the task at hand.
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Wednesday, April 16, 2008
Movement as a resource for vocal learning
Molecular Mapping of Movement-Associated Areas in the Avian Brain: A Motor Theory for Vocal Learning Origin (Feenders et al)
Certain groups of birds, like humans and a small number of other mammalian species, are capable of learning to use their voices to imitate what they hear. While other studies have determined genetic expression that is unique to this trait, as well as unique regions of the brain that are not present in species that are vocal but not vocal learners, the origin of these brain regions has not been well understood. The authors of this study propose that a major constraint on the evolution of vocal learning in the avian orders that feature this capability is a set of seven brain regions that correlate with specific types of movement when active. The authors suggest that not only do the movement regions of the bird brains have a feed-forward relationship with the vocal regions, but also that the vocal regions have a feed-back relationship with the movement regions. The study wraps up by suggesting a theory that in distantly related animal species the brain-based capacity for vocal learning evolved from specialized brain regions that control movement and perhaps even movement-based learning. This theory requires significant experimentation for validation, but has the potential to provide a powerful explanatory mechanism for the evolution of vocal learning not just in distantly-related bird species, but also in distantly-related mammalian species, as well as between birds and mammals. Furthermore, the authors note the gestural precursors to spoken language in early human development and the benefits that formalization of these gestures (sign language) can provide to learning to speak. In summary, this study provides further neuroscientific support for cognitive resources and suggests, specifically, that movement capacity serves as a resource for complex cognitive development.
Certain groups of birds, like humans and a small number of other mammalian species, are capable of learning to use their voices to imitate what they hear. While other studies have determined genetic expression that is unique to this trait, as well as unique regions of the brain that are not present in species that are vocal but not vocal learners, the origin of these brain regions has not been well understood. The authors of this study propose that a major constraint on the evolution of vocal learning in the avian orders that feature this capability is a set of seven brain regions that correlate with specific types of movement when active. The authors suggest that not only do the movement regions of the bird brains have a feed-forward relationship with the vocal regions, but also that the vocal regions have a feed-back relationship with the movement regions. The study wraps up by suggesting a theory that in distantly related animal species the brain-based capacity for vocal learning evolved from specialized brain regions that control movement and perhaps even movement-based learning. This theory requires significant experimentation for validation, but has the potential to provide a powerful explanatory mechanism for the evolution of vocal learning not just in distantly-related bird species, but also in distantly-related mammalian species, as well as between birds and mammals. Furthermore, the authors note the gestural precursors to spoken language in early human development and the benefits that formalization of these gestures (sign language) can provide to learning to speak. In summary, this study provides further neuroscientific support for cognitive resources and suggests, specifically, that movement capacity serves as a resource for complex cognitive development.
Sunday, April 13, 2008
Pick's Disease and Creativity
A Disease That Allowed Torrents of Creativity (Blakeslee) - New York Times
It seems the meme of creativity is rising, as might be expected if we are transitioning into the Imagination Age. As we might also expect, the explanation for creativity continues to be grounded in brain-based research. The above NY Times article ties in well with previous posts on creativity and the right hemisphere, including the post on recent identification of the "Aha!" region of the brain (associative cortex in the right hemisphere's parietal lobe). This article points out an aspect of brain function that has always fascinated me: the idea that the frontal lobe acts to inhibit the activity of other regions of the brain. As we continue to build cognitive models for educational purposes, it's important to keep in mind that relationships between resources shouldn't always be "positive", such that the activity level of one resource always increases the probability of activity of another resource. Cognitive models should be robust enough to include the possibility that resources might decrease the probability of activity of other resources. As such, we can model increases in certain capacities as other aspects of cognition are reduced in activity - whether through endogenous disease such as that mentioned in the article above, or through educational experiences that train students to minimize certain thought patterns in order to maximize others.
It seems the meme of creativity is rising, as might be expected if we are transitioning into the Imagination Age. As we might also expect, the explanation for creativity continues to be grounded in brain-based research. The above NY Times article ties in well with previous posts on creativity and the right hemisphere, including the post on recent identification of the "Aha!" region of the brain (associative cortex in the right hemisphere's parietal lobe). This article points out an aspect of brain function that has always fascinated me: the idea that the frontal lobe acts to inhibit the activity of other regions of the brain. As we continue to build cognitive models for educational purposes, it's important to keep in mind that relationships between resources shouldn't always be "positive", such that the activity level of one resource always increases the probability of activity of another resource. Cognitive models should be robust enough to include the possibility that resources might decrease the probability of activity of other resources. As such, we can model increases in certain capacities as other aspects of cognition are reduced in activity - whether through endogenous disease such as that mentioned in the article above, or through educational experiences that train students to minimize certain thought patterns in order to maximize others.
Wednesday, April 9, 2008
Rodent tool use supports cognitive resources hypothesis
Tool-Use Training in a Species of Rodent: The Emergence of an Optimal Motor Strategy and Functional Understanding (Okanoya et al)
In an article that even received a writeup in the New York Times, the authors cited above present their results from training degus (Octodon degus) to use rakes. Specifically, the researchers wanted to implement an experimental design that would easily extend to studying any changes in the degus' brains that resulted from the training. A variety of other animals are able to use tools, though only a few studies have documented changes in brain activity that correlate with such ability. Interestingly, many researchers have hypothesized that proximal phylogenetic relationships with humans (the most complex of tool-using animals) influence intelligence (measured to some degree by the ability to use tools). In comparing their results from working with degus with a similar experiment done with monkeys, Okanoya and the other researchers in the above study propose that socio-ecological factors may be involved. While brain complexity is certainly not unrelated to common ancestry, another interesting proposal here is worthy of direct quotation: "These observations suggest that tool use ... may represent a standardized set of cognitive skills necessary for general implementation." Conceptual change and education researchers working within the domain of cognitive psychology have, for many years, developed the idea of resources - fundamental units of cognition that are used to construct concepts. It would appear from the research on degus that cognitive resources may be supported by observations of conceptual development in other animal models. Furthermore, and excitingly to me and others hoping to better model the brain-mind relationship, this research further supports the notion that cognitive modeling should be, as much as possible, reflective of what we know about the brain.
In an article that even received a writeup in the New York Times, the authors cited above present their results from training degus (Octodon degus) to use rakes. Specifically, the researchers wanted to implement an experimental design that would easily extend to studying any changes in the degus' brains that resulted from the training. A variety of other animals are able to use tools, though only a few studies have documented changes in brain activity that correlate with such ability. Interestingly, many researchers have hypothesized that proximal phylogenetic relationships with humans (the most complex of tool-using animals) influence intelligence (measured to some degree by the ability to use tools). In comparing their results from working with degus with a similar experiment done with monkeys, Okanoya and the other researchers in the above study propose that socio-ecological factors may be involved. While brain complexity is certainly not unrelated to common ancestry, another interesting proposal here is worthy of direct quotation: "These observations suggest that tool use ... may represent a standardized set of cognitive skills necessary for general implementation." Conceptual change and education researchers working within the domain of cognitive psychology have, for many years, developed the idea of resources - fundamental units of cognition that are used to construct concepts. It would appear from the research on degus that cognitive resources may be supported by observations of conceptual development in other animal models. Furthermore, and excitingly to me and others hoping to better model the brain-mind relationship, this research further supports the notion that cognitive modeling should be, as much as possible, reflective of what we know about the brain.
Brain, Mind, and Education
What a nice feeling to discover the right niche! I've started a new blog which I think will subsume my previous work here - please join me at Brain, Mind, and Education. As much as possible given my "real life" responsibilities, I'm keeping up with current research in neuroscience, cognitive psychology, and education, and thinking about relationships among the three. I don't anticipate any further posts here, and though I'll leave the material accessible, I'll also be working to bring some aspects of it over to the new blog - I hope you'll join me and hop in on some discussion!
Sunday, April 6, 2008
Into the Imagination Age
Let Computers Compute. It's the Age of the Right Brain. (Rae-Dupree, NY Times)
An interesting article in the technology section of the NY Times this weekend seems to fit well with my last couple of posts on intuitive math skills and hemispheric differentiation in the brain. I'm wondering if we're encountering a 'paradigm shift' of sorts, from the Information Age into what might be called the Imagination Age. Reading the article reminded me of something I remember Steve Jobs saying during my time as a full-time Apple-centric computer consultant after the "Internet bubble" burst in 2000 - 2001, which I paraphrase here as "We'll have to innovate our way out of this." I doubt that many could argue with the success of Jobs' strategy. A few other examples are provided in the article, and I think the implications meld well with educational needs, too: while memorization isn't unimportant, what's most critical is that we teach our students to be creative and collaborative problem solvers. Given that many of our educational institutions are still stuck in the Industrial Age, and transitioning with significant difficulty into the Information Age, how quickly can we expect these systems to adapt to yet another paradigm shift?
An interesting article in the technology section of the NY Times this weekend seems to fit well with my last couple of posts on intuitive math skills and hemispheric differentiation in the brain. I'm wondering if we're encountering a 'paradigm shift' of sorts, from the Information Age into what might be called the Imagination Age. Reading the article reminded me of something I remember Steve Jobs saying during my time as a full-time Apple-centric computer consultant after the "Internet bubble" burst in 2000 - 2001, which I paraphrase here as "We'll have to innovate our way out of this." I doubt that many could argue with the success of Jobs' strategy. A few other examples are provided in the article, and I think the implications meld well with educational needs, too: while memorization isn't unimportant, what's most critical is that we teach our students to be creative and collaborative problem solvers. Given that many of our educational institutions are still stuck in the Industrial Age, and transitioning with significant difficulty into the Information Age, how quickly can we expect these systems to adapt to yet another paradigm shift?
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