Quantitative modelling demonstrates format‐invariant representations of mathematical problems in the brain
Mathematical problems can be described in either symbolic form or natural language. Previous studies have reported that activation overlaps exist for these two types of mathematical problems, but it is unclear whether they are based on similar brain representations. Furthermore, quantitative modelli...
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| Published in | The European journal of neuroscience Vol. 57; no. 6; pp. 1003 - 1017 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
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01.03.2023
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| Abstract | Mathematical problems can be described in either symbolic form or natural language. Previous studies have reported that activation overlaps exist for these two types of mathematical problems, but it is unclear whether they are based on similar brain representations. Furthermore, quantitative modelling of mathematical problem solving has yet to be attempted. In the present study, subjects underwent 3 h of functional magnetic resonance experiments involving math word and math expression problems, and a read word condition without any calculations was used as a control. To evaluate the brain representations of mathematical problems quantitatively, we constructed voxel‐wise encoding models. Both intra‐ and cross‐format encoding modelling significantly predicted brain activity predominantly in the left intraparietal sulcus (IPS), even after subtraction of the control condition. Representational similarity analysis and principal component analysis revealed that mathematical problems with different formats had similar cortical organization in the IPS. These findings support the idea that mathematical problems are represented in the brain in a format‐invariant manner.
Mathematical problems can be described either in a symbolic form or a natural language, while it has been unclear whether they rely on similar brain representations. We constructed voxel‐wise encoding models to quantitatively evaluate brain representations of math word and expression problems. Both intra‐ and cross‐format encoding modelling significantly predicted brain activity predominantly in the left intraparietal sulcus. Representational similarity and principal component analysis revealed similar cortical organization for the two formats. These findings indicate that mathematical problems are represented in the brain in a format‐invariant manner. |
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| AbstractList | Mathematical problems can be described in either symbolic form or natural language. Previous studies have reported that activation overlaps exist for these two types of mathematical problems, but it is unclear whether they are based on similar brain representations. Furthermore, quantitative modelling of mathematical problem solving has yet to be attempted. In the present study, subjects underwent 3 h of functional magnetic resonance experiments involving math word and math expression problems, and a read word condition without any calculations was used as a control. To evaluate the brain representations of mathematical problems quantitatively, we constructed voxel‐wise encoding models. Both intra‐ and cross‐format encoding modelling significantly predicted brain activity predominantly in the left intraparietal sulcus (IPS), even after subtraction of the control condition. Representational similarity analysis and principal component analysis revealed that mathematical problems with different formats had similar cortical organization in the IPS. These findings support the idea that mathematical problems are represented in the brain in a format‐invariant manner. Mathematical problems can be described in either symbolic form or natural language. Previous studies have reported that activation overlaps exist for these two types of mathematical problems, but it is unclear whether they are based on similar brain representations. Furthermore, quantitative modelling of mathematical problem solving has yet to be attempted. In the present study, subjects underwent 3 h of functional magnetic resonance experiments involving math word and math expression problems, and a read word condition without any calculations was used as a control. To evaluate the brain representations of mathematical problems quantitatively, we constructed voxel‐wise encoding models. Both intra‐ and cross‐format encoding modelling significantly predicted brain activity predominantly in the left intraparietal sulcus (IPS), even after subtraction of the control condition. Representational similarity analysis and principal component analysis revealed that mathematical problems with different formats had similar cortical organization in the IPS. These findings support the idea that mathematical problems are represented in the brain in a format‐invariant manner. Mathematical problems can be described either in a symbolic form or a natural language, while it has been unclear whether they rely on similar brain representations. We constructed voxel‐wise encoding models to quantitatively evaluate brain representations of math word and expression problems. Both intra‐ and cross‐format encoding modelling significantly predicted brain activity predominantly in the left intraparietal sulcus. Representational similarity and principal component analysis revealed similar cortical organization for the two formats. These findings indicate that mathematical problems are represented in the brain in a format‐invariant manner. Mathematical problems can be described in either symbolic form or natural language. Previous studies have reported that activation overlaps exist for these two types of mathematical problems, but it is unclear whether they are based on similar brain representations. Furthermore, quantitative modelling of mathematical problem solving has yet to be attempted. In the present study, subjects underwent 3 h of functional magnetic resonance experiments involving math word and math expression problems, and a read word condition without any calculations was used as a control. To evaluate the brain representations of mathematical problems quantitatively, we constructed voxel-wise encoding models. Both intra- and cross-format encoding modelling significantly predicted brain activity predominantly in the left intraparietal sulcus (IPS), even after subtraction of the control condition. Representational similarity analysis and principal component analysis revealed that mathematical problems with different formats had similar cortical organization in the IPS. These findings support the idea that mathematical problems are represented in the brain in a format-invariant manner.Mathematical problems can be described in either symbolic form or natural language. Previous studies have reported that activation overlaps exist for these two types of mathematical problems, but it is unclear whether they are based on similar brain representations. Furthermore, quantitative modelling of mathematical problem solving has yet to be attempted. In the present study, subjects underwent 3 h of functional magnetic resonance experiments involving math word and math expression problems, and a read word condition without any calculations was used as a control. To evaluate the brain representations of mathematical problems quantitatively, we constructed voxel-wise encoding models. Both intra- and cross-format encoding modelling significantly predicted brain activity predominantly in the left intraparietal sulcus (IPS), even after subtraction of the control condition. Representational similarity analysis and principal component analysis revealed that mathematical problems with different formats had similar cortical organization in the IPS. These findings support the idea that mathematical problems are represented in the brain in a format-invariant manner. Mathematical problems can be described in either symbolic form or natural language. Previous studies have reported that activation overlaps exist for these two types of mathematical problems, but it is unclear whether they are based on similar brain representations. Furthermore, quantitative modelling of mathematical problem solving has yet to be attempted. In the present study, subjects underwent 3 h of functional magnetic resonance experiments involving math word and math expression problems, and a read word condition without any calculations was used as a control. To evaluate the brain representations of mathematical problems quantitatively, we constructed voxel‐wise encoding models. Both intra‐ and cross‐format encoding modelling significantly predicted brain activity predominantly in the left intraparietal sulcus (IPS), even after subtraction of the control condition. Representational similarity analysis and principal component analysis revealed that mathematical problems with different formats had similar cortical organization in the IPS. These findings support the idea that mathematical problems are represented in the brain in a format‐invariant manner. |
| Author | Nakai, Tomoya Nishimoto, Shinji |
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| Snippet | Mathematical problems can be described in either symbolic form or natural language. Previous studies have reported that activation overlaps exist for these two... |
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| SubjectTerms | Brain - diagnostic imaging Brain - physiology Brain Mapping encoding fMRI Humans Intraparietal sulcus IPS Magnetic Resonance Imaging Mathematical models Mathematical problems mathematics Parietal Lobe - physiology Principal components analysis Problem solving Problem Solving - physiology RSA |
| Title | Quantitative modelling demonstrates format‐invariant representations of mathematical problems in the brain |
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