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Boydstun
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Neural Representations of Physics Concepts

"Considerable advances have been made in developing brain-based theories of semantic knowledge, such as knowledge of concrete objects or emotions. Brain-imaging research has uncovered sets of brain systems that collectively contain the neural representations of such concepts, including information about the way the human body interacts with them (in the case of objects) or their intensity (in the case of emotions; Just, Cherkassky, Aryal, & Mitchell, 2010; Kassam, Markey, Cherkassky, Loewenstein, & Just, 2013). What has not yet been investigated with this approach is the neural representation of specialized abstract knowledge acquired through academic study, such as science learning. The current article addresses this issue in the area of physics knowledge. . . ."

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Mapping Visual Symbols Onto Spoken Language Along the Ventral Visual Stream

"In summary, our study provides strong empirical support for a hierarchical, posterior-to-anterior gradient in vOT that represents increasingly abstract information about written words. In line with Dehaene et al.’s (8) proposal, we found that representations in posterior visual regions are tied to location and may encode low-level visual information, whereas letter identity was represented in left midanterior vOT with a degree of location invariance. These location-invariant letter representations are then further transformed in left midanterior vOT to encode aspects of a word’s pronunciation and meaning. These results contribute to our understanding of how the brain maps from arbitrary visual symbols to rich linguistic representations, ultimately enabling the experience of language through the visual modality."

 

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A Brain-Based Account of "Basic-Level" Concepts

"This study provides a brain-based account of how object concepts at an intermediate (basic) level of specificity are represented, offering an enriched view of what it means for a concept to be a basic-level concept, a research topic pioneered by Rosch and others (Rosch et al., 1976). Applying machine learning techniques to fMRI data, it was possible to determine the semantic content encoded in the neural representations of object concepts at basic and subordinate levels of abstraction. The representation of basic-level concepts (e.g. bird) was spatially broad, encompassing sensorimotor brain areas that encode concrete object properties, and also language and heteromodal integrative areas that encode abstract semantic content. The representation of subordinate-level concepts (robin) was less widely distributed, concentrated in perceptual areas that underlie concrete content. Furthermore, basic-level concepts were representative of their subordinates in that they were neurally similar to their typical but not atypical subordinates (bird was neurally similar to robin but not woodpecker). The findings provide a brain-based account of the advantages that basic-level concepts enjoy in everyday life over subordinate-level concepts: the basic level is a broad topographical representation that encompasses both concrete and abstract semantic content, reflecting the multifaceted yet intuitive meaning of basic-level concepts."

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A Similarity-Based Process for Human Judgment in the Parietal Cortex

"One important distinction in psychology is between inferences based on associative memory and inferences based on analysis and rules. Much previous empirical work conceive of associative and analytical processes as two exclusive ways of addressing a judgment task, where only one process is selected and engaged at a time, in an either-or fashion. However, related work indicate that the processes are better understood as being in interplay and simultaneously engaged. Based on computational modeling and brain imaging of spontaneously adopted judgment strategies together with analyses of brain activity elicited in tasks where participants were explicitly instructed to perform similarity-based associative judgments or rule-based judgments (n = 74), we identified brain regions related to the two types of processes. We observed considerable overlap in activity patterns. The precuneus was activated for both types of judgments, and its activity predicted how well a similarity-based model fit the judgments. Activity in the superior frontal gyrus predicted the fit of a rule-based judgment model. The results suggest the precuneus as a key node for similarity-based judgments, engaged both when overt responses are guided by similarity-based and rule-based processes. These results are interpreted such that similarity-based processes are engaged in parallel to rule-based-processes, a finding with direct implications for cognitive theories of judgment."

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On Human Perception of a Starry Sky

"For millennia, humans have looked to the night sky and chosen star groups to name. But why does Centaurus comprise that specific set of stars rather than some other? We hypothesize that the perception of star groups (constellations) can be explained by a simple model of eye movements taking a random walk along a network of star-to-star transition probabilities. The walk is biased by angular distances between stars, preferred angular distances of human eye movements (also known as saccades), and stars’ apparent magnitudes. To derive predicted constellations from the random walk, we employ a free energy model of mental calculations that maximizes the accuracy of perception while minimizing computational complexity. The model transforms the true transition probability matrix among stars into a perceived matrix, in which star clusters are evident. We show that the statistics of the perceived star clusters naturally align with the boundaries between true constellations. Our findings offer a simple explanation for the identities of the 88 standard constellations."

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