Exploring the Neural Mechanisms of Physics Learning

This dissertation presents a series of neuroimaging investigations and achievements that strive to deepen and broaden our understanding of human problem solving and physics learning. Neuroscience conceives of dynamic relationships between behavior, experience, and brain structure and function, but how neural changes enable human learning across classroom instruction remains an open question. At the same time, physics is a challenging area of study in which introductory students regularly struggle to achieve success across university instruction. Research and initiatives in neuroeducation promise a new understanding into the interactions between biology and education, including the neural mechanisms of learning and development. These insights may be particularly useful in understanding how students learn, which is crucial for helping them succeed. Towards this end, we utilize methods in functional magnetic resonance imaging (fMRI), as informed by education theory, research, and practice, to investigate the neural mechanisms of problem solving and learning in students across semester-long University-level introductory physics learning environments. In the first study, we review and synthesize the neuroimaging problem solving literature and perform quantitative coordinate-based meta-analysis on 280 problem solving experiments to characterize the common and dissociable brain networks that underlie human problem solving across different representational contexts. Then, we describe the Understanding the Neural Mechanisms of Physics Learning project, which was designed to study functional brain changes associated with learning and problem solving in undergraduate physics students before and after a semester of introductory physics instruction. We present the development, facilitation, and data acquisition for this longitudinal data collection project. We then perform a sequence of fMRI analyses of these data and characterize the first-time observations of brain networks underlying physics problem solving in students after university physics instruction. We measure sustained and sequential brain activity and functional connectivity during physics problem solving, test brain-behavior relationships between accuracy, difficulty, strategy, and conceptualization of physics ideas, and describe differences in student physics-related brain function linked with dissociations in conceptual approach. The implications of these results to inform effective instructional practices are discussed. Then, we consider how classroom learning impacts the development of student brain function by examining changes in physics problem solving-related brain activity in students before and after they completed a semester-long Modeling Instruction physics course. Our results provide the first neurobiological evidence that physics learning environments drive the functional reorganization of large-scale brain networks in physics students. Through this collection of work, we demonstrate how neuroscience studies of learning can be grounded in educational theory and pedagogy, and provide deep insights into the neural mechanisms by which students learn physics

The interaction of process and domain in prefrontal cortex during inductive reasoning

AbstractInductive reasoning is an everyday process that allows us to make sense of the world by creating rules from a series of instances. Consistent with accounts of process-based fractionations of the prefrontal cortex (PFC) along the left–right axis, inductive reasoning has been reliably localized to left PFC. However, these results may be confounded by the task domain, which is typically verbal. Indeed, some studies show that right PFC activation is seen with spatial tasks. This study used fMRI to examine the effects of process and domain on the brain regions recruited during a novel pattern discovery task. Twenty healthy young adult participants were asked to discover the rule underlying the presentation of a series of letters in varied spatial locations. The rules were either verbal (pertaining to a single semantic category) or spatial (geometric figures). Bilateral ventrolateral PFC activations were seen for the spatial domain, while the verbal domain showed only left ventrolateral PFC. A conjunction analysis revealed that the two domains recruited a common region of left ventrolateral PFC. The data support a central role of left PFC in inductive reasoning. Importantly, they also suggest that both process and domain shape the localization of reasoning in the brain

Knowledge Selection in Category-Based Inductive Reasoning

Current theories of category-based inductive reasoning can be distinguished by the emphasis they place on structured and unstructured knowledge. Theories which draw on unstructured knowledge focus on associative strength, or temporal and spatial contiguity between categories. In contrast, accounts which draw on structured knowledge make reference to the underlying theoretical frameworks which relate categories to one another, such as causal or taxonomic relationships. In this thesis, it is argued that this apparent dichotomy can be resolved if one ascribes different processing characteristics to these two types of knowledge. That is, unstructured knowledge influences inductive reasoning effortlessly and relatively automatically, whereas the use of structured knowledge requires effort and the availability of cognitive resources. Understanding these diverging processes illuminates how background knowledge is selected during the inference process. The thesis demonstrates that structured and unstructured knowledge are dissociable and influence reasoning in line with their unique processing characteristics. Using secondary task and speeded response paradigms, it shows that unstructured knowledge is most influential when people are cognitively burdened or forced to respond fast, whereas they can draw on more elaborate structured knowledge if they are not cognitively compromised. This is especially evident for the causal asymmetry effect, in which people make stronger inferences from cause to effect categories, than vice versa. This Bayesian normative effect disappears when people have to contend with a secondary task or respond under time pressure. The next experiments demonstrate that this dissociation between structured and unstructured knowledge is also evident for a more naturalistic inductive reasoning paradigm in which people generate their own inferences. In the final experiments, it is shown how the selection of appropriate knowledge ties in with more domain-general processes, and especially inhibitory control. When responses based on structured and unstructured knowledge conflict, people’s ability to reason based on appropriate structured knowledge depends upon having relevant background knowledge and on their ability to inhibit the lure from inappropriate unstructured knowledge. The thesis concludes with a discussion of how the concepts of structured and unstructured knowledge illuminate the processes underlying knowledge selection for category-based inductive reasoning. It also looks at the implications the findings have for different theories of category-based induction, and for our understanding of human reasoning processes more generally

Similar or Different? The Role of the Ventrolateral Prefrontal Cortex in Similarity Detection

Patients with frontal lobe syndrome can exhibit two types of abnormal behaviour when asked to place a banana and an orange in a single category: some patients categorize them at a concrete level (e.g., “both have peel”), while others continue to look for differences between these objects (e.g., “one is yellow, the other is orange”). These observations raise the question of whether abstraction and similarity detection are distinct processes involved in abstract categorization, and that depend on separate areas of the prefrontal cortex (PFC). We designed an original experimental paradigm for a functional magnetic resonance imaging (fMRI) study involving healthy subjects, confirming the existence of two distinct processes relying on different prefrontal areas, and thus explaining the behavioural dissociation in frontal lesion patients. We showed that: 1) Similarity detection involves the anterior ventrolateral PFC bilaterally with a right-left asymmetry: the right anterior ventrolateral PFC is only engaged in detecting physical similarities; 2) Abstraction per se activates the left dorsolateral PFC

An Electroencephalogram Investigation of Two Modes of Reasoning

The use of electroencephalography (EEG) to exam the electrical brain activity associated with reasoning provides an opportunity to quantify the functional and temporal aspects of this uniquely human capability, and at the same time expand our knowledge about what a given event-related potential (ERP) might measure. The question of what form of mental representation and transformational processes underlie human reasoning has been a central theme in cognitive psychology since its inception (Chomsky, 1957; McCarthy, 1955; Miller, 1956; Newell, Shaw, Simon, 1958). Two prominent, but competing views remain at the forefront of the discussion, one positing that human inference making is principally syntactic (Braine & O'Brien, 1998; Fodor, 1975; Pylyshyn, 1984; Rips, 1994), and the other that it is, fundamentally, semantic in nature (Gentner & Stevens, 1983; Johnson-Laird, 1983). The purpose of the proposed study is to investigate the neurophysiology of mental model (MM) and mental rule (MR) reasoning using high-density electroencephalography (EEG), with the goal of providing a characterization of the time course and a general estimate of the spatial dimensions of the brain activations correlated with these specific instances of two classic views of reasoning. The research is motivated by two questions: 1) Will violations of expectancy established by the devised MM and MR reasoning strategies evoke the N400 and P600 ERPs, respectively, and 2) Will topographical scalp distributions associated with each reasoning strategy suggest distinct psychological representations and processes? A finding of a N400 response in the MM condition suggests that reasoning about the relations between entities in the type of problems presented engages a network of cortical areas previously shown to be involved in processing violations of semantic expectancies in studies of language comprehension. By comparison, incongruent events in the MR condition are expected to evoke a bilateral anterior P600, a component previously associated with recognizing and restructuring syntactic anomalies or incongruities in sentence comprehension. If the hypothesized results are obtained they would provide potentially insightful information about the chronometry of mental processes associated with the different representations and inference making mechanisms postulated to support each mode of reasoning, and as well, broaden our understanding of the neural functionality associated with the N400 and P600 ERP

The Relationship of Four Brain Regions to an Information-Processing Model of Numerical Inductive Reasoning Process: An fMRI Study

The present study relates a four-stage information-processing model of inductive reasoning to four brain regions. We assume that there is a fusiform gyrus region-of-interest (ROI) where a stimulus is visually recognized, a DLPFC ROI where an underlying rule is identified, a caudate ROI where a rule is applied, and a motor ROI where hand movements are programmed during inductive reasoning process. Then, an fMRI experiment was performed to articulate the roles of these four regions. The present study is a 2 (task: rule induction vs. rule application) × 2 (period length: simple vs. complex) × 2 (priming effect: prime vs. target) design. As predicted, both the fusiform gyrus ROI and the motor ROI showed no effects of task, period length, and priming effect, and respectively reflected encoding of stimuli and button-pressing response. The DLPFC ROI responded to task and period length, and was confirmed to play a crucial role in rule identification. The caudate showed no effect of task and responded to period length and priming effect, and was verified to be responsible for rule application. The exploratory analysis also demonstrated our assumptions. Thus, the main stream of information-processing in inductive reasoning process can be described by using the four ROIs