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Triana AM, Saramäki J, Glerean E, Hayward NMEA. Neuroscience meets behavior: A systematic literature review on magnetic resonance imaging of the brain combined with real-world digital phenotyping. Hum Brain Mapp 2024; 45:e26620. [PMID: 38436603 PMCID: PMC10911114 DOI: 10.1002/hbm.26620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 01/19/2024] [Accepted: 01/24/2024] [Indexed: 03/05/2024] Open
Abstract
A primary goal of neuroscience is to understand the relationship between the brain and behavior. While magnetic resonance imaging (MRI) examines brain structure and function under controlled conditions, digital phenotyping via portable automatic devices (PAD) quantifies behavior in real-world settings. Combining these two technologies may bridge the gap between brain imaging, physiology, and real-time behavior, enhancing the generalizability of laboratory and clinical findings. However, the use of MRI and data from PADs outside the MRI scanner remains underexplored. Herein, we present a Preferred Reporting Items for Systematic Reviews and Meta-Analysis systematic literature review that identifies and analyzes the current state of research on the integration of brain MRI and PADs. PubMed and Scopus were automatically searched using keywords covering various MRI techniques and PADs. Abstracts were screened to only include articles that collected MRI brain data and PAD data outside the laboratory environment. Full-text screening was then conducted to ensure included articles combined quantitative data from MRI with data from PADs, yielding 94 selected papers for a total of N = 14,778 subjects. Results were reported as cross-frequency tables between brain imaging and behavior sampling methods and patterns were identified through network analysis. Furthermore, brain maps reported in the studies were synthesized according to the measurement modalities that were used. Results demonstrate the feasibility of integrating MRI and PADs across various study designs, patient and control populations, and age groups. The majority of published literature combines functional, T1-weighted, and diffusion weighted MRI with physical activity sensors, ecological momentary assessment via PADs, and sleep. The literature further highlights specific brain regions frequently correlated with distinct MRI-PAD combinations. These combinations enable in-depth studies on how physiology, brain function and behavior influence each other. Our review highlights the potential for constructing brain-behavior models that extend beyond the scanner and into real-world contexts.
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Affiliation(s)
- Ana María Triana
- Department of Computer Science, School of ScienceAalto UniversityEspooFinland
| | - Jari Saramäki
- Department of Computer Science, School of ScienceAalto UniversityEspooFinland
| | - Enrico Glerean
- Department of Neuroscience and Biomedical Engineering, School of ScienceAalto UniversityEspooFinland
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McGowan AL, Boyd ZM, Kang Y, Bennett L, Mucha PJ, Ochsner KN, Bassett DS, Falk EB, Lydon-Staley DM. Within-Person Temporal Associations Among Self-Reported Physical Activity, Sleep, and Well-Being in College Students. Psychosom Med 2023; 85:141-153. [PMID: 36728904 PMCID: PMC9918680 DOI: 10.1097/psy.0000000000001159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE A holistic understanding of the naturalistic dynamics among physical activity, sleep, emotions, and purpose in life as part of a system reflecting wellness is key to promoting well-being. The main aim of this study was to examine the day-to-day dynamics within this wellness system. METHODS Using self-reported emotions (happiness, sadness, anger, anxiousness) and physical activity periods collected twice per day, and daily reports of sleep and purpose in life via smartphone experience sampling, more than 28 days as college students ( n = 226 young adults; mean [standard deviation] = 20.2 [1.7] years) went about their daily lives, we examined day-to-day temporal and contemporaneous dynamics using multilevel vector autoregressive models that consider the network of wellness together. RESULTS Network analyses revealed that higher physical activity on a given day predicted an increase of happiness the next day. Higher sleep quality on a given night predicted a decrease in negative emotions the next day, and higher purpose in life predicted decreased negative emotions up to 2 days later. Nodes with the highest centrality were sadness, anxiety, and happiness in the temporal network and purpose in life, anxiety, and anger in the contemporaneous network. CONCLUSIONS Although the effects of sleep and physical activity on emotions and purpose in life may be shorter term, a sense of purpose in life is a critical component of wellness that can have slightly longer effects, bleeding into the next few days. High-arousal emotions and purpose in life are central to motivating people into action, which can lead to behavior change.
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Affiliation(s)
- Amanda L. McGowan
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychology, Concordia University, Montréal, Québec, Canada
| | - Zachary M. Boyd
- Department of Mathematics, Brigham Young University, Provo, UT, USA
| | - Yoona Kang
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA, USA
| | - Logan Bennett
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA, USA
| | - Peter J. Mucha
- Department of Mathematics, Dartmouth College, Hanover, NH, USA
| | - Kevin N. Ochsner
- Department of Psychology, Columbia University, New York City, NY, USA
| | - Dani S. Bassett
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
- Department of Physics & Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Department of Electrical & Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Santa Fe Institute, Santa Fe, NM, USA
| | - Emily B. Falk
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
- Marketing Department, and Operations, Information and Decision Department, Wharton School, University of Pennsylvania, PA, USA
| | - David M. Lydon-Staley
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA, USA
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA
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Cui Q, Chen Y, Tang Q, Sheng W, Li D, Zeng Y, Jiang K, He Z, Chen H. Neural mechanisms of aberrant self-referential processing in patients with generalized anxiety disorder. Prog Neuropsychopharmacol Biol Psychiatry 2022; 119:110595. [PMID: 35787397 DOI: 10.1016/j.pnpbp.2022.110595] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 06/07/2022] [Accepted: 06/27/2022] [Indexed: 10/17/2022]
Abstract
Massive theoretical studies in clinical psychology have implicated the self in understanding internalizing disorders (i.e., anxiety and mood disorders), in which self-related tasks were frequently used to investigate internalizing psychopathology. As one of the most frequently seen internalizing disorder in primary care, patients with generalized anxiety disorder (GAD) are characterized by inappropriate self-related processing such as negative self-referential thinking. However, relevant neural mechanisms remain unknown. In this study, participants underwent a self-related task which they were presented with several positive and negative trait words and were required to judge the extent to which these traits matched themselves when compared to their average peers. Aberrant brain activation and functional connectivity of GAD were detected during processing positive and negative traits. Compared to healthy controls (HCs), patients with GAD exhibited abnormal self-processing which manifested as lower biased self-rating scores particularly for negative traits and weaker brain activity in the left dorsomedial prefrontal cortex, inferior frontal gyrus, superior temporal sulcus (STS), and bilateral lingual gyrus when processing trait words. Abnormal functional connections between these hypoactive regions and regions associated with reward, emotion, and theory of mind were observed in subsequent psychophysiological interaction analysis. An attenuation of connectivity between the left insula and left STS was associated with greater severity of anxiety symptom in GAD patients. These findings provide insight into the abnormal neurocognitive mechanisms of biased self-related processing in GAD patients, which involves distorted self-schema accompanied by abnormal activation and functional connections of regions implicated in self-related and social cognition processing.
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Affiliation(s)
- Qian Cui
- School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuyan Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Qin Tang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Wei Sheng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Di Li
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuhong Zeng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Kexing Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Zongling He
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Huafu Chen
- Department of Radiology, First Affiliated Hospital to Army Medical University, Chongqing, China; MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China.
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