Posts Tagged ‘learning’
Curiosity is a basic element of our cognition, but its biological function, mechanisms, and neural underpinning remain poorly understood. It is nonetheless a motivator for learning, influential in decision-making, and crucial for healthy development. One factor limiting our understanding of it is the lack of a widely agreed upon delineation of what is and is not curiosity. Another factor is the dearth of standardized laboratory tasks that manipulate curiosity in the lab. Despite these barriers, recent years have seen a major growth of interest in both the neuroscience and psychology of curiosity. In this Perspective, we advocate for the importance of the field, provide a selective overview of its current state, and describe tasks that are used to study curiosity and information-seeking. We propose that, rather than worry about defining curiosity, it is more helpful to consider the motivations for information-seeking behavior and to study it in its ethological context.
Students asking questions and then exploring the answers. That’s something any good teacher lives for. And at the heart of it all is curiosity. But why? What, exactly, is curiosity and how does it work? A study published in the October issue of the journal Neuron, suggests that the brain’s chemistry changes when we become curious, helping us better learn and retain information.
“There’s this basic circuit in the brain that energizes people to go out and get things that are intrinsically rewarding,” Ranganath explains. This circuit lights up when we’re curious. When the circuit is activated, our brains release a chemical called dopamine which gives us a high. “The dopamine also seems to play a role in enhancing the connections between cells that are involved in learning.” Indeed, when the researchers later tested participants on what they learned, those who were more curious were more likely to remember the right answers.
Read also: How Curiosity drives Learning
People find it easier to learn about topics that interest them, but little is known about the mechanisms by which intrinsic motivational states affect learning. We used functional magnetic resonance imaging to investigate how curiosity (intrinsic motivation to learn) influences memory. In both immediate and one-day-delayed memory tests, participants showed improved memory for information that they were curious about and for incidental material learned during states of high curiosity. Functional magnetic resonance imaging results revealed that activity in the midbrain and the nucleus accumbens was enhanced during states of high curiosity. Importantly, individual variability in curiosity-driven memory benefits for incidental material was supported by anticipatory activity in the midbrain and hippocampus and by functional connectivity between these regions. These findings suggest a link between the mechanisms supporting extrinsic reward motivation and intrinsic curiosity and highlight the importance of stimulating curiosity to create more effective learning experiences.
Read also: How the Power of Interest Drives Learning
Curiosity helps us learn about a topic, and being in a curious state also helps the brain memorize unrelated information, according to researchers at the UC Davis Center for Neuroscience. Work published Oct. 2 in the journal Neuron provides insight into how piquing our curiosity changes our brains, and could help scientists find ways to enhance overall learning and memory in both healthy individuals and those with neurological conditions. “Our findings potentially have far-reaching implications for the public because they reveal insights into how a form of intrinsic motivation — curiosity — affects memory. These findings suggest ways to enhance learning in the classroom and other settings,”
James Zull’s book The Art of Changing the Brain contends that neuroscience can guide our teaching practice by revealing to us how our brains actually learn. I think his insight is reliable, and I’m particularly satisfied that he views the brain as a complex, multi-scale network and learning as changing, extending, and strengthening the connections within those networks. This fits quite nicely with connectivism, which defines learning in similar networking terms.
This definition of learning puts the student/learner at the center of the learning process, unlike traditional education, which puts the teacher/authority at the center of the learning process. Why? Because if learning is the development of new connections within existing neuronal networks, then learning depends overwhelmingly on the engagement of the student. No teacher can directly touch a student’s brain. Development of neuronal networks absolutely depends on the student exercising her own brain, and her teachers cannot do it for her, any more than a fitness trainer can exercise her muscles for her. The student must sweat and exert herself and must want to sweat and exert.
Read also: Rewiring the Classroom
Neuroscience tells us that the products of the mind — thought, emotions, artistic creation — are the result of the interactions of the biological brain with our senses and the physical world: in short, that thinking and learning are the products of a biological process. This realization, that learning actually alters the brain by changing the number and strength of synapses, offers a powerful foundation for rethinking teaching practice and one’s philosophy of teaching.
James Zull invites teachers in higher education or any other setting to accompany him in his exploration of what scientists can tell us about the brain and to discover how this knowledge can influence the practice of teaching. He describes the brain in clear non-technical language and an engaging conversational tone, highlighting its functions and parts and how they interact, and always relating them to the real world of the classroom and his own evolution as a teacher. “The Art of Changing the Brain” is grounded in the practicalities and challenges of creating effective opportunities for deep and lasting learning, and of dealing with students as unique learners.
Learning, the foundation of adaptive and intelligent behavior, is based on plastic changes in neural assemblies, reflected by the modulation of electric brain responses. In infancy, auditory learning implicates the formation and strengthening of neural long-term memory traces, improving discrimination skills, in particular those forming the prerequisites for speech perception and understanding. Although previous behavioral observations show that newborns react differentially to unfamiliar sounds vs. familiar sound material that they were exposed to as fetuses, the neural basis of fetal learning has not thus far been investigated. Here we demonstrate direct neural correlates of human fetal learning of speech-like auditory stimuli. We presented variants of words to fetuses; unlike infants with no exposure to these stimuli, the exposed fetuses showed enhanced brain activity (mismatch responses) in response to pitch changes for the trained variants after birth. Furthermore, a significant correlation existed between the amount of prenatal exposure and brain activity, with greater activity being associated with a higher amount of prenatal speech exposure. Moreover, the learning effect was generalized to other types of similar speech sounds not included in the training material. Consequently, our results indicate neural commitment specifically tuned to the speech features heard before birth and their memory representations.
Human learning is a complex phenomenon requiring flexibility to adapt existing brain function and precision in selecting new neurophysiological activities to drive desired behavior. These two attributes—flexibility and selection—must operate over multiple temporal scales as performance of a skill changes from being slow and challenging to being fast and automatic. Such selective adaptability is naturally provided by modular structure, which plays a critical role in evolution, development, and optimal network function. Using functional connectivity measurements of brain activity acquired from initial training through mastery of a simple motor skill, we investigate the role of modularity in human learning by identifying dynamic changes of modular organization spanning multiple temporal scales. Our results indicate that flexibility, which we measure by the allegiance of nodes to modules, in one experimental session predicts the relative amount of learning in a future session. We also develop a general statistical framework for the identification of modular architectures in evolving systems, which is broadly applicable to disciplines where network adaptability is crucial to the understanding of system performance.
Acute learning difficulties with maths may be as common as reading and writing difficulties. Researchers estimate that as much as three to six percent of the population in Western countries may struggle with difficulties with maths. Östergren found through his study that dyscalculia can be a combination of various factors. The brain is a complicated organ and manifold mental processes are involved in even the easiest math problems. Poor comprehension of numbers can be compensated for with other talents. Thus it’s important to train these pupils correctly and remember that a diagnosis can be seen as an opportunity, the point of departure for helpful initiatives. Dyscalculia is not the same thing as math anxiety or math phobia, terms often used for tension or fear that interferes with a student’s learning of mathematics.