A Holistic Analysis of Individual Brain Activity Revealed the Relationship of Brain Areal Activity with the Entire Brain’s Activity
The relationship between brain areal activity and the entire brain’s activity is unknown, and understanding this relationship is imperative for understanding the neural mechanisms of human brain function at systems level. The complex activity of human brains varies from area to area and from time to...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Brain Sciences |
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| Online Access: | https://www.mdpi.com/2076-3425/13/1/6 |
| _version_ | 1797445252911464448 |
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| author | Jie Huang |
| author_facet | Jie Huang |
| author_sort | Jie Huang |
| collection | DOAJ |
| description | The relationship between brain areal activity and the entire brain’s activity is unknown, and understanding this relationship is imperative for understanding the neural mechanisms of human brain function at systems level. The complex activity of human brains varies from area to area and from time to time across the whole brain. BOLD-fMRI measures this spatiotemporal activity at a large-scale systems level. The BOLD time signal of an area reflects a collective neuronal activity of over one million neurons under that area, and the temporal correlation of this time signal with that of every point in the brain yields a full spatial map that characterizes the entire brain’s functional co-activity (FC) relative to that area’s activity. Here we show a quantitative relationship between brain areal activity and the activity of the entire brain. The temporal correlation coefficient <i>r</i> of the signal time courses of two areas quantifies the degree of co-activity between the two areas, and the spatial correlation coefficient <i>R</i> of their corresponding two FC maps quantifies the co-activity between these two maps. We found that a modified sigmoid function quantified this <i>R</i> with <i>r</i>, i.e., <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mfenced><mi>r</mi></mfenced><mo>=</mo><mfrac><mrow><msup><mrow><mfenced><mrow><mn>1</mn><mo>+</mo><mi>r</mi></mrow></mfenced></mrow><mi>a</mi></msup><mo>−</mo><msup><mrow><mfenced><mrow><mn>1</mn><mo>−</mo><mi>r</mi></mrow></mfenced></mrow><mi>a</mi></msup></mrow><mrow><msup><mrow><mfenced><mrow><mn>1</mn><mo>+</mo><mi>r</mi></mrow></mfenced></mrow><mi>a</mi></msup><mo>+</mo><msup><mrow><mfenced><mrow><mn>1</mn><mo>−</mo><mi>r</mi></mrow></mfenced></mrow><mi>a</mi></msup></mrow></mfrac></mrow></semantics></math></inline-formula>, revealing a relationship between the activity of brain areas and that of the entire brain. The parameter <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>a</mi></semantics></math></inline-formula> in this equation was found to be associated with the mean degree of the temporal co-activity among all brain areas, and its value was brain functional state dependent too. Our study demonstrated a novel approach for analyzing fMRI data to holistically characterize the entire brain’s activity quantitatively for any brain functional state in individual humans. |
| first_indexed | 2024-03-09T13:24:06Z |
| format | Article |
| id | doaj.art-2f87aa7e24ea4c61b2a75600e8586f60 |
| institution | Directory Open Access Journal |
| issn | 2076-3425 |
| language | English |
| last_indexed | 2024-03-09T13:24:06Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Brain Sciences |
| spelling | doaj.art-2f87aa7e24ea4c61b2a75600e8586f602023-11-30T21:26:15ZengMDPI AGBrain Sciences2076-34252022-12-01131610.3390/brainsci13010006A Holistic Analysis of Individual Brain Activity Revealed the Relationship of Brain Areal Activity with the Entire Brain’s ActivityJie Huang0Department of Radiology, Michigan State University, East Lansing, MI 48824, USAThe relationship between brain areal activity and the entire brain’s activity is unknown, and understanding this relationship is imperative for understanding the neural mechanisms of human brain function at systems level. The complex activity of human brains varies from area to area and from time to time across the whole brain. BOLD-fMRI measures this spatiotemporal activity at a large-scale systems level. The BOLD time signal of an area reflects a collective neuronal activity of over one million neurons under that area, and the temporal correlation of this time signal with that of every point in the brain yields a full spatial map that characterizes the entire brain’s functional co-activity (FC) relative to that area’s activity. Here we show a quantitative relationship between brain areal activity and the activity of the entire brain. The temporal correlation coefficient <i>r</i> of the signal time courses of two areas quantifies the degree of co-activity between the two areas, and the spatial correlation coefficient <i>R</i> of their corresponding two FC maps quantifies the co-activity between these two maps. We found that a modified sigmoid function quantified this <i>R</i> with <i>r</i>, i.e., <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mfenced><mi>r</mi></mfenced><mo>=</mo><mfrac><mrow><msup><mrow><mfenced><mrow><mn>1</mn><mo>+</mo><mi>r</mi></mrow></mfenced></mrow><mi>a</mi></msup><mo>−</mo><msup><mrow><mfenced><mrow><mn>1</mn><mo>−</mo><mi>r</mi></mrow></mfenced></mrow><mi>a</mi></msup></mrow><mrow><msup><mrow><mfenced><mrow><mn>1</mn><mo>+</mo><mi>r</mi></mrow></mfenced></mrow><mi>a</mi></msup><mo>+</mo><msup><mrow><mfenced><mrow><mn>1</mn><mo>−</mo><mi>r</mi></mrow></mfenced></mrow><mi>a</mi></msup></mrow></mfrac></mrow></semantics></math></inline-formula>, revealing a relationship between the activity of brain areas and that of the entire brain. The parameter <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>a</mi></semantics></math></inline-formula> in this equation was found to be associated with the mean degree of the temporal co-activity among all brain areas, and its value was brain functional state dependent too. Our study demonstrated a novel approach for analyzing fMRI data to holistically characterize the entire brain’s activity quantitatively for any brain functional state in individual humans.https://www.mdpi.com/2076-3425/13/1/6BOLD-fMRIfunctional area of unitary pooled activityFAUPAbrain areal activityentire brain activity |
| spellingShingle | Jie Huang A Holistic Analysis of Individual Brain Activity Revealed the Relationship of Brain Areal Activity with the Entire Brain’s Activity Brain Sciences BOLD-fMRI functional area of unitary pooled activity FAUPA brain areal activity entire brain activity |
| title | A Holistic Analysis of Individual Brain Activity Revealed the Relationship of Brain Areal Activity with the Entire Brain’s Activity |
| title_full | A Holistic Analysis of Individual Brain Activity Revealed the Relationship of Brain Areal Activity with the Entire Brain’s Activity |
| title_fullStr | A Holistic Analysis of Individual Brain Activity Revealed the Relationship of Brain Areal Activity with the Entire Brain’s Activity |
| title_full_unstemmed | A Holistic Analysis of Individual Brain Activity Revealed the Relationship of Brain Areal Activity with the Entire Brain’s Activity |
| title_short | A Holistic Analysis of Individual Brain Activity Revealed the Relationship of Brain Areal Activity with the Entire Brain’s Activity |
| title_sort | holistic analysis of individual brain activity revealed the relationship of brain areal activity with the entire brain s activity |
| topic | BOLD-fMRI functional area of unitary pooled activity FAUPA brain areal activity entire brain activity |
| url | https://www.mdpi.com/2076-3425/13/1/6 |
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