The neuroscience of advanced scientific concepts

Cognitive neuroscience methods can identify the fMRI-measured neural representation of familiar individual concepts, such as apple, and decompose them into meaningful neural and semantic components. This approach was applied here to determine the neural representations and underlying dimensions of r...

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Published in	NPJ science of learning Vol. 6; no. 1; pp. 29 - 12
Main Authors	Mason, Robert A., Schumacher, Reinhard A., Just, Marcel Adam
Format	Journal Article
Language	English
Published	London Nature Publishing Group UK 11.10.2021 Nature Publishing Group Nature Portfolio
Subjects	631/378/2649/1594 706/648/160 Bayesian analysis Biomedical and Life Sciences Brain Brain mapping Cognition & reasoning Cognitive ability Cognitive Processes Educational Technology Factor analysis Functional magnetic resonance imaging Knowledge management Learning algorithms Life Sciences Machine learning Mathematical Models of Cognitive Processes and Neural Networks Nervous system Neural coding Neurobiology Neuropsychology Neurosciences Periodicity Physics Scientific Concepts Semantics
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ISSN	2056-7936 2056-7936
DOI	10.1038/s41539-021-00107-6

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Abstract	Cognitive neuroscience methods can identify the fMRI-measured neural representation of familiar individual concepts, such as apple, and decompose them into meaningful neural and semantic components. This approach was applied here to determine the neural representations and underlying dimensions of representation of far more abstract physics concepts related to matter and energy, such as fermion and dark matter, in the brains of 10 Carnegie Mellon physics faculty members who thought about the main properties of each of the concepts. One novel dimension coded the measurability vs. immeasurability of a concept. Another novel dimension of representation evoked particularly by post-classical concepts was associated with four types of cognitive processes, each linked to particular brain regions: (1) Reasoning about intangibles, taking into account their separation from direct experience and observability; (2) Assessing consilience with other, firmer knowledge; (3) Causal reasoning about relations that are not apparent or observable; and (4) Knowledge management of a large knowledge organization consisting of a multi-level structure of other concepts. Two other underlying dimensions, previously found in physics students, periodicity, and mathematical formulation, were also present in this faculty sample. The data were analyzed using factor analysis of stably responding voxels, a Gaussian-naïve Bayes machine-learning classification of the activation patterns associated with each concept, and a regression model that predicted activation patterns associated with each concept based on independent ratings of the dimensions of the concepts. The findings indicate that the human brain systematically organizes novel scientific concepts in terms of new dimensions of neural representation.
AbstractList	Abstract Cognitive neuroscience methods can identify the fMRI-measured neural representation of familiar individual concepts, such as apple, and decompose them into meaningful neural and semantic components. This approach was applied here to determine the neural representations and underlying dimensions of representation of far more abstract physics concepts related to matter and energy, such as fermion and dark matter, in the brains of 10 Carnegie Mellon physics faculty members who thought about the main properties of each of the concepts. One novel dimension coded the measurability vs. immeasurability of a concept. Another novel dimension of representation evoked particularly by post-classical concepts was associated with four types of cognitive processes, each linked to particular brain regions: (1) Reasoning about intangibles, taking into account their separation from direct experience and observability; (2) Assessing consilience with other, firmer knowledge; (3) Causal reasoning about relations that are not apparent or observable; and (4) Knowledge management of a large knowledge organization consisting of a multi-level structure of other concepts. Two other underlying dimensions, previously found in physics students, periodicity, and mathematical formulation, were also present in this faculty sample. The data were analyzed using factor analysis of stably responding voxels, a Gaussian-naïve Bayes machine-learning classification of the activation patterns associated with each concept, and a regression model that predicted activation patterns associated with each concept based on independent ratings of the dimensions of the concepts. The findings indicate that the human brain systematically organizes novel scientific concepts in terms of new dimensions of neural representation. Cognitive neuroscience methods can identify the fMRI-measured neural representation of familiar individual concepts, such as apple, and decompose them into meaningful neural and semantic components. This approach was applied here to determine the neural representations and underlying dimensions of representation of far more abstract physics concepts related to matter and energy, such as fermion and dark matter, in the brains of 10 Carnegie Mellon physics faculty members who thought about the main properties of each of the concepts. One novel dimension coded the measurability vs. immeasurability of a concept. Another novel dimension of representation evoked particularly by post-classical concepts was associated with four types of cognitive processes, each linked to particular brain regions: (1) Reasoning about intangibles, taking into account their separation from direct experience and observability; (2) Assessing consilience with other, firmer knowledge; (3) Causal reasoning about relations that are not apparent or observable; and (4) Knowledge management of a large knowledge organization consisting of a multi-level structure of other concepts. Two other underlying dimensions, previously found in physics students, periodicity, and mathematical formulation, were also present in this faculty sample. The data were analyzed using factor analysis of stably responding voxels, a Gaussian-naïve Bayes machine-learning classification of the activation patterns associated with each concept, and a regression model that predicted activation patterns associated with each concept based on independent ratings of the dimensions of the concepts. The findings indicate that the human brain systematically organizes novel scientific concepts in terms of new dimensions of neural representation.Cognitive neuroscience methods can identify the fMRI-measured neural representation of familiar individual concepts, such as apple, and decompose them into meaningful neural and semantic components. This approach was applied here to determine the neural representations and underlying dimensions of representation of far more abstract physics concepts related to matter and energy, such as fermion and dark matter, in the brains of 10 Carnegie Mellon physics faculty members who thought about the main properties of each of the concepts. One novel dimension coded the measurability vs. immeasurability of a concept. Another novel dimension of representation evoked particularly by post-classical concepts was associated with four types of cognitive processes, each linked to particular brain regions: (1) Reasoning about intangibles, taking into account their separation from direct experience and observability; (2) Assessing consilience with other, firmer knowledge; (3) Causal reasoning about relations that are not apparent or observable; and (4) Knowledge management of a large knowledge organization consisting of a multi-level structure of other concepts. Two other underlying dimensions, previously found in physics students, periodicity, and mathematical formulation, were also present in this faculty sample. The data were analyzed using factor analysis of stably responding voxels, a Gaussian-naïve Bayes machine-learning classification of the activation patterns associated with each concept, and a regression model that predicted activation patterns associated with each concept based on independent ratings of the dimensions of the concepts. The findings indicate that the human brain systematically organizes novel scientific concepts in terms of new dimensions of neural representation. Cognitive neuroscience methods can identify the fMRI-measured neural representation of familiar individual concepts, such as apple, and decompose them into meaningful neural and semantic components. This approach was applied here to determine the neural representations and underlying dimensions of representation of far more abstract physics concepts related to matter and energy, such as fermion and dark matter, in the brains of 10 Carnegie Mellon physics faculty members who thought about the main properties of each of the concepts. One novel dimension coded the measurability vs. immeasurability of a concept. Another novel dimension of representation evoked particularly by post-classical concepts was associated with four types of cognitive processes, each linked to particular brain regions: (1) Reasoning about intangibles, taking into account their separation from direct experience and observability; (2) Assessing consilience with other, firmer knowledge; (3) Causal reasoning about relations that are not apparent or observable; and (4) Knowledge management of a large knowledge organization consisting of a multi-level structure of other concepts. Two other underlying dimensions, previously found in physics students, periodicity, and mathematical formulation, were also present in this faculty sample. The data were analyzed using factor analysis of stably responding voxels, a Gaussian-naïve Bayes machine-learning classification of the activation patterns associated with each concept, and a regression model that predicted activation patterns associated with each concept based on independent ratings of the dimensions of the concepts. The findings indicate that the human brain systematically organizes novel scientific concepts in terms of new dimensions of neural representation.
ArticleNumber	29
Author	Mason, Robert A. Schumacher, Reinhard A. Just, Marcel Adam
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Cites_doi	10.1038/s41539-020-0065-x 10.1371/journal.pone.0008622 10.1016/j.neuroimage.2011.06.034 10.1016/j.neuropsychologia.2017.12.008 10.1016/j.neuroimage.2015.02.043 10.1002/hbm.21021 10.1016/j.neuroimage.2014.12.086 10.1037/0096-3445.130.3.493 10.1093/brain/107.3.829 10.1371/journal.pone.0113879 10.1002/hbm.22087 10.1016/j.neuroimage.2019.01.001 10.1016/j.neuroimage.2008.09.028 10.1073/pnas.1603205113 10.1177/0956797616641941 10.1016/S0926-6410(01)00007-6 10.1038/s41562-017-0234-y 10.1111/j.1749-6632.1995.tb38149.x 10.1016/j.neuroimage.2007.07.041 10.1093/scan/nss022 10.1371/journal.pone.0073746 10.1080/02643290244000293 10.1073/pnas.1615773114 10.1002/hbm.20720 10.1038/nmeth.1635 10.1016/j.neuroimage.2015.05.086 10.1162/jocn_a_00887 10.1016/j.neuropsychologia.2011.04.035 10.1016/j.tics.2005.09.009 10.1006/nimg.2001.0978 10.1038/s41467-019-10053-y 10.1016/j.neuroimage.2014.02.015 10.1162/jocn.2009.21124 10.1016/j.bandl.2010.08.004 10.1016/j.neulet.2007.11.016 10.1016/j.brainres.2006.02.053 10.1016/j.neuroimage.2016.07.052 10.1371/journal.pone.0111439 10.1119/1.1972241 10.1037/e553882011-002
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Snippet	Cognitive neuroscience methods can identify the fMRI-measured neural representation of familiar individual concepts, such as apple, and decompose them into... Abstract Cognitive neuroscience methods can identify the fMRI-measured neural representation of familiar individual concepts, such as apple, and decompose them...
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SubjectTerms	631/378/2649/1594 706/648/160 Bayesian analysis Biomedical and Life Sciences Brain Brain mapping Cognition & reasoning Cognitive ability Cognitive Processes Educational Technology Factor analysis Functional magnetic resonance imaging Knowledge management Learning algorithms Life Sciences Machine learning Mathematical Models of Cognitive Processes and Neural Networks Nervous system Neural coding Neurobiology Neuropsychology Neurosciences Periodicity Physics Scientific Concepts Semantics
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Title	The neuroscience of advanced scientific concepts
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