Cognitive Neuroscience

The basic question of interest to cognitive neuroscientists - what is the relationship between mind and brain - is described; the development of the field is then put into historical context by reviewing how others - ancient philosophers and behavioral psychologists, for example - have either addressed or ignored the relationship between the mind and brain. Cognitive neuroscience has relied on new technologies as well as the insights from a variety of different fields; the importance of collaboration and different types of methodologies are explored. Finally, the implications of cognitive neuroscience research for education and learning are explored.

Keywords Brain; Cognitive Psychology; Functional Magnetic Resonance Imaging (fMRI); Information Processing Theory; Lesion Studies; Mind; Network Theory

Overview

As an academic discipline, cognitive neuroscience is in its infancy; the term itself was coined in 1970, and the Cognitive Neuroscience Society didn't hold its inaugural meeting until 1994 (Bly & Rumelhart, 1999). Lack of maturity, however, does not necessarily imply lack of productivity. Cognitive neuroscience has been a remarkably fertile field in an especially limited amount of time. "Biologist E.O. Wilson even referred to the recent period of scientific fecundity within cognitive neuroscience as the occurrence of a rare 'heroic period' of science - comparable to 'the heroic periods of molecular biology, plate tectonics in geology, and the modern synthesis of evolutional biology'" (Ilardi & Feldman, 2001, p. 1114). Cognitive neuroscience is perhaps heroic not only for its fecundity, but also for exploring what many refer to as the final frontier.

What exactly is this final frontier, the subject of study of the cognitive neuroscientist? The obvious answer for many might be 'the brain' - while correct, such an answer would be incomplete and misleading. Cognitive neuroscientists don't study an object such as the brain, per se, but rather a relationship - more specifically, the relationship between the brain and mind. Ganzaggia (2000) defines it this way: "at the core, the cognitive neuroscientist wants to understand how the brain enables the mind" (p.xii). Bly and Rumelhart (1999) provide a similar definition: "the goal of cognitive neuroscience is to understand how brain function gives rise to mental abilities such as memory, reasoning, vision, or movement" (p. 320). The focus on the relationship is what distinguishes cognitive neuroscientists from cognitive scientists; cognitive scientists also study mental processes such as memory, but they do so by focusing on the function independent of 'the organ which gives rise to the function' (Bly & Rumelhart, 1999, p. 321). In other words, cognitive neuroscientists integrate physical (neural) and functional levels of analysis.

Gazzaniga (2000) describes exploration in this final frontier as 'a very tricky business'; indeed, it's difficult to ignore the significant challenges facing those who study the brain and its relation to our cognitive faculties. But there is also something uniquely challenging about this field of study. As Smith (2002) explains, "the mind and its expression in consciousness is at the same time the subject of our study and the means by which we carry on that discussion. I believe that this makes our attempt at understanding the mind both uniquely challenging and extraordinarily interesting to all of us" (p. 2). In other words, we are using our mind to investigate itself, making it both the object and subject of study.

Development of the Field

Cognitive neuroscience might be a relatively new field, but one of the questions cognitive neuroscientists are trying to answer - what is the nature of the mind and the nature of consciousness - is one that philosophers have been grappling with for centuries. Smith (2002) argues, however, that the tools available to the philosopher - mainly introspection and logic - significantly limited their ability to answer such questions. "The classic tools of the philosopher have been the mainstay of the study of human nature, but contribute little to our understanding of the material world around us, including our physical selves. One result has been a dualistic approach to our study of ourselves, with cognition separated from anatomy and physiology by a philosophical wall" (p. 57). Only by embracing science - empiricism and observation as opposed to introspection and logic - have we gained insights into the mind.

Behaviorism

Not all science has contributed to our understanding of consciousness equally. A substantial portion of the twentieth century was dominated by a theoretical orientation known as behaviorism. Behaviorists relied on observation, defining all learning as changes in observable behavior. In addition to relying on the observable, however, many behaviorists denied the existence of the mind altogether, or argued the futility of attempting to study it. Watson, often cited as the father of the behaviorist movement, wrote "the reader will find no discussion of consciousness and no reference to such terms as sensation, perception, attention, and will…" (as quoted in Smith, 2002, p. 8). For many years, the mind and brain were virtually ignored, causing many to wonder "can a serious student again undertake a serious study of consciousness after nearly half a century hiatus produced by the embracing of behaviorism?" (Smith, 2002, p. 9).

Cognitive Psychology

The answer, of course, is 'yes' and the academic discipline that gave the serious student the opportunity to study the mind again was cognitive psychology. With renewed vigor, cognitive psychologist focused their energy on the black box - the very thing behaviorists ignored - and began studying cognitive functions such as memory, attention, and language development. Even though cognitive psychologists didn't study function in relation to physiology directly, they did embrace models that suggested how the mind and brain might work. Many cognitivists adopted an information processing model, for example, theorizing that the brain worked in much the same way as a computer. Even as neuroscientists entered the scene, the computer remained a viable model, with some suggesting that the individual neuron of the brain mimicked the digital communication of artificial intelligence systems.

Network Theory

Ultimately, however, as researchers began to understand more about the structure of the brain, both the computer metaphor and the reductionist focus on the individual neuron became unsatisfactory ways to explore the mind and brain. The computer metaphor assumed human thought was logical and linear, an assumption that would prove to be false. And "individual neurons didn't provide a reasonable model of complex behavior and thought" (Smith, 2002, p. 15). Instead, scientists began developing a more sophisticated understanding of the brain, investigating neurons as clusters of cells as opposed to single entities, and recognizing that communication between neurons and clusters of neurons was bi-directional and multi-layered. The model that now guides most cognitive neuroscience research is referred to as 'network theory' (Smith, 2002).

Cognitive neuroscientists, and the field more generally, didn't evolve in isolation. In fact, Martin & Rumelhart, 1999 describe it as "inherently multi-disciplinary" and Gazzaniga (2000) explains that the pioneers of the field were "fed by the instinct that people in various camps needed to be talking to one another" (p. xiii). Smith (2002) suggests that cognitive neuroscience rests equally on the contributions of three fields - artificial intelligence, cognitive psychology, and neuroscience. Others may define the players more broadly, with even greater emphasis on the collaborative nature of the field. "In cognitive neuroscience, we consider data collected by researchers studying behavior, cognition, neurophysiology, neuroanatomy, and computation, and each new finding provides additional fodder for theories of brain function. Theory building thus becomes a process of trying to fit together a wide variety of different types of information into a more complex, integrated whole" (Bly & Rumelhart, 1999, p. 320).

Methodology

Prior to the last several decades, researchers didn't have direct access to the healthy brains of living people. The earliest studies of the relationship between the brain and cognitive function relied on observations of individuals who had suffered brain damage; loss of function was documented, and then correlated with the damaged areas of the brain upon subsequent postmortem investigation. Patient case studies such as these have been utilized since the 19th century (Chatterjee, 2005). One of the more recent well-known case studies of this sort is the study of a patient referred to as H.M.; after undergoing brain surgery as a last resort effort to eliminate seizures, H.M. suffered severe memory loss. Because doctors knew the specific areas of the brain damaged by surgery, they learned a lot of its relationship to cognitive functions such as language and memory.

Imaging Techniques

While useful, case studies of brain-damaged individuals - also referred to as lesion studies - did not give researchers information about the healthy brain in relation to cognition and learning. Not until imaging techniques were developed did scientists get a glimpse inside the brains of 'normal-functioning' individuals while they were performing mental and physical tasks. Some of the more common imaging techniques include positron emission tomography (PET scans), electroencephalography (EEG), and functional magnetic resonance imaging (fMRI). Whereas EEG measures the electrical activity of neurons in the brain, both PET scans and fMRI measure increased blood flow. As a result, different imaging techniques are used for different purposes - only the later help identify the specific location associated with a particular mental event.

Even if fMRI helped researchers identify the part of the brain associated with a particular mental or physical event, they didn't always know what increased activity or blood flow actually meant. "Because fMRI is non-invasive it is ideal for monitoring the brain activity of a person conducting mental or physical tasks. But it has previously been a 'black box', because a change in neuron activity, indicated by greater blood flow, could mean one of several things" (Logothetis, Pauls, Augath, Trinath, & Oeltermann, 2001). More specifically, researchers weren't sure if the increased blood flow showed "the input to or the output from nerve cells, or something else entirely" (Logothetis, et. al., 2001). Recent research suggests the fMRI signal is most closely associated with input to nerve cells, a finding many think makes intuitive sense. Receiving a signal requires more energy than sending a signal, and the energy comes in the form of glucose which is carried by the blood. Even as fMRI has given us more insight into the specific location and processes associated with particular cognitive functions, mysteries still remain. Scientists have observed, for example, that the brain receives more energy - in the form of blood - than it often needs; the reason for it is unknown.

Imaging vs. Lesion Studies

Given the insights into the brain and cognitive function we have gained as a result of imaging technology, it is perhaps of little surprise that this methodology has grown in popularity. In 2005, for example, the bulk of research submitted to the Cognitive Neuroscience Society used imaging and electrophysiological methodologies; by comparison, only 16% used patient-based case studies (Chatterjee, 2005). Not all agree, however, that imaging studies are superior to case-based lesion studies. In fact, only lesion studies have the possibility of establishing a causal relationship between structure and function. "Functional imaging by necessity provides correlational data" (Chatterjee, 2005, p. 847). Which causes many to wonder, according to Chatterjee, "despite the greater 'in-principle' inferential strength of lesion than functional imaging studies, why in practice do they have less impact on the field?" (Chatterjee, 2005, p. 847).

Researchers cite sociological and practical considerations, as opposed to considerations based on scientific merit, as the reason for the imbalance between imaging and lesion studies. Novelty, for example, plays a role - people generally believe new technology is good technology - as does accessibility to data. It's often difficult to gain access to clinical patients. In the end, however, both methodologies are important. "The strengths and weaknesses of lesion and imaging studies are complementary. The point is not to bemoan the impact of imaging studies on cognitive neuroscience as much as to ask how the impact of lesion studies might be enhanced" (p. 849).

Applications

Educational Implications

The most obvious potential application of cognitive neuroscience research is, arguably, in the field of education and learning. Indeed, much has been written in the recent educational psychology literature about how teachers should evaluate and apply what scientists learn about the brain and cognition. Surprisingly perhaps, many urge great caution, suggesting that findings in cognitive neuroscience need to be validated further before educators begin to use them. Bruer (1997, as cited in Stanovich, 1998) describes the direct leap from cognitive neuroscience to education as "a bridge too far." Wittrock (1998) concurs, writing "Useful implications about important applied problems do not follow directly from one individual study…in neuroscience or any other field. It is a long way from research by Gauss and Maxwell to the telephone, telegraph, and the computer. Perhaps it is less of a long way from Thorndike's neural bonds…to classroom teaching, but it is still a long way" (p. 428).

Caution is urged because caution has not always been exercised. One of the most infamous examples of inappropriately applied research occurred in the late twentieth century, when information about the different hemispheres of the brain became a teaching fad. As Stanovich (1998) explains "[Educators] have no desire to spawn another round of the left-brain-right-brain nonsense that has inundated education through workshops, inservices, and the trade publications of non-academic publishers" (p. 420). Others urge caution by emphasizing the bi-directionality of neuroscience and cognitive psychology; information about the neural basis of learning disabilities, for example, is dependent upon understanding the psychological and behavior characteristics of such individuals (Stanovich, 1998).

Although many advise educators to exercise caution, they are advising them with equal urgency to familiarize themselves with cognitive neuroscience research. The rationale for such a recommendation is two-fold. First and foremost, cognitive neuroscience has something to tell us about teaching and learning. In contrast to many school reforms, often based on politics and social and cultural issues, cognitive neuroscience provides an evidence-based approach to school change (Geake & Cooper, 2003). Secondly, becoming well-versed in how the brain works will help empower teachers, and re-establish the respect many feel is lacking. "A good reason for educationists to embrace cognitive neuroscience is the hope that such an endeavor might stem the increasing marginalization of teachers as pedagogues" (Geake and Cooper, 2003). The social status of doctors improved in the last century as they adopted evidence-based practice; so too, Geake and Cooper (2003) argue, will the social status of teachers.

Memory & Learning

Geake and Cooper (2003) define adaptive plasticity as the brain's capacity "to change at a neurophysiological level in response to changes in the cognitive environment" (p. 14). Citing a model proposed by Donald Hebb (1949), Geake and Cooper (2003) suggest that the signal between neurons - or synaptic functioning - strengthens as a result of repetition and practice, resulting in "permanent physiological change" (p. 14). As a result, they suggest that "the most important implication for education is that Hebb's model strongly supports what teachers have long known: that repetition is necessary for effective learning" (p. 14). The model also puts forth an explanation to account for difficulty of correcting erroneous learning; any learning that gets repeated, whether correct or not, is strengthened and thus more resistant to change. Naïve science beliefs of children and adults may result from this process.

Decision-Making & Emotion

In both psychology and economics, decision-making was long thought to be a rational, cognitive process in which an individual weighs the costs and benefits of a particular course of action (Naqvi, Shiv, & Bechara, 2006). More recently, however, researchers' observations of individuals in high-risk and high-uncertainty decision-making situations demonstrated that people often rely on biases and emotions in choosing an appropriate course of action. Recent neuroscience research has confirmed these observations, demonstrating that both the ventromedial prefrontal cortex (vmPFC) and amygdala play important, but different, roles in decision-making. Those with damage to the vmPFC, for example, have difficulty anticipating the emotional impact of future rewards and punishments, while those with damage to the amygdala have difficulty registering the emotional impact of rewards and punishments as they are occurring. Both deficits make it more difficult for such individuals to use information about rewards and punishments when choosing behaviors in the future. Cognitive neuroscientists have extended this research to examine the role of emotion in different types of decisions. Activation in the vmPFC is greater when making moral decisions that impact others; "these findings suggest that moral decisions, compared to nonmoral decisions, engage emotions, especially when one is required to consider the consequences of one's actions for another's well-being" (Naqvi, Shiv, & Bechara, 2006, p. 263).

Aging & Culture

Park and Gutchess' (2006) research on aging and culture provides a good example of how findings in cognitive neuroscience are used in conjunction with current knowledge about cognitive function. Behavioral data suggests decreases in efficiency in basic cognitive processes - short and long term memory, speed of processing, etc - as a result of the aging process. Researchers have assumed that deficits in functioning were mirrored by similar changes in brain circuitry - loss of volume of neurons, and less activation between neurons. Imaging research has shown that while the aging brain does demonstrate loss of volume in particular regions, it is able to compensate for such changes in other ways, rearranging circuitry so that it utilizes more parts of the brain, and both hemispheres rather than just one. "Advances in neuroimaging have been largely responsible for views suggesting that the brain has residual plasticity" (Park & Gutchess, 2006, p. 107).

In addition to aging, Park and Gutchess (2006) were also interested in the impact of culture on brain structure; they hypothesized that differences in cultural norms - East Asians' tendency to focus on relationships and group function in contrast to Westerners' tendency to focus on the individual - might translate into different neural connections. More specifically, East Asians have been found to interpret stimuli more holistically, focusing on context, while Westerners focus more on the object itself, and less on the context or background. Park and Gutchess (2006) found that young East Asians and Westerners had equally developed circuitry for responding to both object and background information, but that as individuals aged, the circuitry corresponding to the behavior not valued by their culture became less active. In other words, "the data…suggest that after a lifetime of culturally biased information processing the neural circuitry for looking at scenes may be sculpted in a culturally biased way" (Park & Gutchess, 2006, p. 107).

Conclusion

Few would argue against the utility of the field of cognitive neuroscience. Disagreements won't arise over whether or not furthering our understanding of the brain is a worthwhile endeavor, but rather, as we have seen, over the methods and potential implications of such research: does cognitive neuroscience confirm or invalidate previous theories of cognitive functioning? What methods should be used to best answer our questions about brain structure and function? How and when should cognitive neuroscience research be applied in the classroom, and in larger world settings? As we move forward, the answers to these questions may shift. In the meantime, perhaps the one thing most can agree upon is the need to move forward itself. "Cognitive neuroscience is…a field of scientific inquiry that has more to do than has been done" (Gazzaniga, 2000, p. xiii).

Terms & Concepts

Brain: Cognitive neuroscientists are interesting in studying the relationship between our physical selves - specifically, our brain - and the cognitive and mental abilities it gives rise to - collectively known as 'the mind.' The relationship between mind and brain is the subject of study, rather than the brain itself.

Cognitive Psychology: Cognitive psychologists are distinct from cognitive neuroscientists in that they study cognitive function, independent of its physical origins in the brain. Cognitive neuroscientists, however, rely heavily on research conducted by cognitive psychologists (among others), as knowledge about function informs knowledge about structure.

Functional Magnetic Resonance Imaging (fMRI): Functional Magnetic Resonance Imaging is a newly developed technique that allows researchers to observe a 'normal' healthy brain as it performs a cognitive or motor task. Previously, researchers had to rely on information from patients who suffered brain damage, by correlating observed function with post-mortem investigations of brain structure. Functional Magnetic Resonance Imaging measures increased blood flow to active parts of the brain.

Information Processing Theory: Information processing theory is an example of a model put forth by cognitive psychologists to explain the way humans select, attend to, and remember information. Advances in cognitive neuropsychology help confirm or disconfirm previous understandings of cognitive function; recent evidence seems to suggest that our brains are less linear in the processing of information than we previously thought. Rather, we seem to process data in neural clusters that are multi-layered and communicate bi-directionally; researchers refer to this new model as the network theory.

Lesion Studies: Lesion studies were the first available method for studying the brain in relation to cognitive function. Individuals who suffered brain damage were observed; their cognitive deficits were then understood in relation to the changed structure of their brains, investigated post-mortem. Despite advances in technology, lesion studies are still an important methodology, allowing investigators to make more causal connections that other methodologies allow.

Mind: Cognitive neuroscientists are interesting in studying the relationship between our physical selves - specifically, our brain - and the cognitive and mental abilities it gives rise to - collectively known as 'the mind.' In the past, philosophers have attempted to study the brain using the only methods available to them - introspection and logic. Many argue such methods have yielded little insight, and suggest that furthering our knowledge of the brain holds great promise.

Bibliography

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Bly, B.M., & Rumelhart, D.E. (Eds.). (1999). Cognitive science. New York, NY: Academic Press.

Cartwright, K.B. (2012). Insights from cognitive neuroscience: The importance of executive function for early reading development and education. Early Education & Development, 23, 24-36. Retrieved December 15, 2013, from EBSCO Online Database Education Research Complete. http://search.ebscohost.com/login.aspx?direct=true&db=ehh&AN=70384068&site=ehost-live

Chatterjee, A. (2005). A madness to the methods of cognitive neuroscience? Journal of Cognitive Neuroscience, 17 , 847-849. Retrieved November 1, 2007 from EBSCO Online Database Academic Search Premier. http://search.ebscohost.com/login.aspx?direct=true&db=aph&AN=17169094&site=ehost-live

Gazzaniga, M.S. (2000). Cognitive neuroscience: A reader. Malden, MA: Blackwell Publishers, Inc.

Geake, J., & Cooper, P. (2003). Cognitive neuroscience: Implications for education? Westminster Studies in Education, 26 , 7-20. Retrieved November 1, 2007 from ESBCO Online Database Academic Search Premier. http://search.ebscohost.com/login.aspx?direct=true&db=aph&AN=10282399&site=ehost-live

Ilardi, S.S., & Feldman, D. (2001). Cognitive neuroscience and the progress of psychological science: Once more with feeling (and other mental constructs). Journal of Clinical Psychology, 57 , 1113-1117. Retrieved November 1, 2007 from EBSCO Online Database Academic Search Premier. http://search.ebscohost.com/login.aspx?direct=true&db=aph&AN=5116408&site=ehost-live

Kroeger, L.A., Brown, R., & O'Brien, B.A. (2012). Connecting neuroscience, cognitive, and educational theories and research to practice: A review of mathematics intervention programs. Early Education & Development, 23, 37-58. Retrieved December 15, 2013, from EBSCO Online Database Education Research Complete. http://search.ebscohost.com/login.aspx?direct=true&db=ehh&AN=70384071&site=ehost-live

Naqvi, N., Shiv, B., & Bechara, A. (2006). The role of emotion in decision making: A cognitive neuroscience perspective. Current Directions in Psychological Science, 15, 260-264. Retrieved November 1, 2007 from EBSCO Online Database Academic Search Premier. http://search.ebscohost.com/login.aspx?direct=true&db=aph&AN=23162383&site=ehost-live

Logothetis, N.K., Pauls, J., Angath, M., Trinath, T., & Oeltermann, A. (2001). A neurophysiological investigation of the basis of the fMRI signal. Nature, 412, 150-157. Retrieved November 8, 2007, from http://www.nature.com/news/2001/010712/full/news010712-13.html

Park, D., & Gutchess, A. (2006). The cognitive neuroscience of aging and culture. Current Directions in Psychological Science, 15, 105-108. Retrieved November 1, 2007 from EBSCO Online Database Academic Search Premier. http://search.ebscohost.com/login.aspx?direct=true&db=aph&AN=21072893&site=ehost-live

Schunk, D.H. (1998). An educational psychologist's perspective on cognitive neuroscience. Educational Psychology Review, 10 , 411-417. Retrieved November 1, 2007 from ESBCO Online Database Academic Search Premier. http://search.ebscohost.com/login.aspx?direct=true&db=aph&AN=1334719&site=ehost-live

Smith, R.H. (2002). Cognitive neuroscience: A functionalist perspective. New York, NY: University Press of America, Inc.

Stanovich, K. (1999). Cognitive neuroscience and educational psychology: What season is it? Issues in Education, 10 , 419-426. Retrieved November 1, 2007 from EBSCO Online Database Academic Search Premier. http://search.ebscohost.com/login.aspx?direct=true&db=aph&AN=1334720&site=ehost-live

Wittrock, M.C. (1998). Comment on 'The educational relevance of research in cognitive neuroscience.' Educational Psychology Review, 10 , 427-429. Retrieved November 1, 2007 from ESBCO Online Database Academic Search Premier. http://search.ebscohost.com/login.aspx?direct=true&db=aph&AN=1334721&site=ehost-live

Suggested Reading

Banich, M.T. (2004). Cognitive neuroscience and neuropsychology (2nd ed.). New York, NY: Houghton Mifflin Company.

Easton, A., & Emery, N.J. (Eds.). (2005). Cognitive neuroscience of social behavior. New York, NY: Psychology Press.

Johnson, M. H. (1997). Developmental cognitive neuroscience: An introduction. Cambridge, MA: Blackwell Publishers, Inc.

Lane, R.D., & Nadel, L. (Eds.) (2000). Cognitive neuroscience of emotion. New York, NY: Oxford University Press.