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Watters H, Davis A, Fazili A, Daley L, LaGrow TJ, Schumacher EH, Keilholz S. Infraslow dynamic patterns in human cortical networks track a spectrum of external to internal attention. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.22.590625. [PMID: 38712098 PMCID: PMC11071428 DOI: 10.1101/2024.04.22.590625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Early efforts to understand the human cerebral cortex focused on localization of function, assigning functional roles to specific brain regions. More recent evidence depicts the cortex as a dynamic system, organized into flexible networks with patterns of spatiotemporal activity corresponding to attentional demands. In functional MRI (fMRI), dynamic analysis of such spatiotemporal patterns is highly promising for providing non-invasive biomarkers of neurodegenerative diseases and neural disorders. However, there is no established neurotypical spectrum to interpret the burgeoning literature of dynamic functional connectivity from fMRI across attentional states. In the present study, we apply dynamic analysis of network-scale spatiotemporal patterns in a range of fMRI datasets across numerous tasks including a left-right moving dot task, visual working memory tasks, congruence tasks, multiple resting state datasets, mindfulness meditators, and subjects watching TV. We find that cortical networks show shifts in dynamic functional connectivity across a spectrum that tracks the level of external to internal attention demanded by these tasks. Dynamics of networks often grouped into a single task positive network show divergent responses along this axis of attention, consistent with evidence that definitions of a single task positive network are misleading. Additionally, somatosensory and visual networks exhibit strong phase shifting along this spectrum of attention. Results were robust on a group and individual level, further establishing network dynamics as a potential individual biomarker. To our knowledge, this represents the first study of its kind to generate a spectrum of dynamic network relationships across such an axis of attention.
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Affiliation(s)
| | - Aleah Davis
- Agnes Scott College
- Georgia Institute of Technology School of Psychology
| | | | - Lauren Daley
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology
| | - TJ LaGrow
- Georgia Institute of Technology School of Electrical and Computer Engineering
| | | | - Shella Keilholz
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology
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Metzen D, Stammen C, Fraenz C, Schlüter C, Johnson W, Güntürkün O, DeYoung CG, Genç E. Investigating robust associations between functional connectivity based on graph theory and general intelligence. Sci Rep 2024; 14:1368. [PMID: 38228689 DOI: 10.1038/s41598-024-51333-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 12/29/2023] [Indexed: 01/18/2024] Open
Abstract
Previous research investigating relations between general intelligence and graph-theoretical properties of the brain's intrinsic functional network has yielded contradictory results. A promising approach to tackle such mixed findings is multi-center analysis. For this study, we analyzed data from four independent data sets (total N > 2000) to identify robust associations amongst samples between g factor scores and global as well as node-specific graph metrics. On the global level, g showed no significant associations with global efficiency or small-world propensity in any sample, but significant positive associations with global clustering coefficient in two samples. On the node-specific level, elastic-net regressions for nodal efficiency and local clustering yielded no brain areas that exhibited consistent associations amongst data sets. Using the areas identified via elastic-net regression in one sample to predict g in other samples was not successful for local clustering and only led to one significant, one-way prediction across data sets for nodal efficiency. Thus, using conventional graph theoretical measures based on resting-state imaging did not result in replicable associations between functional connectivity and general intelligence.
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Affiliation(s)
- Dorothea Metzen
- Biopsychology, Institute for Cognitive Neuroscience, Faculty of Psychology, Ruhr-University Bochum, 44801, Bochum, Germany.
- Institute of Psychology, Department of Educational Sciences and Psychology, TU Dortmund University, 44227, Dortmund, Germany.
| | - Christina Stammen
- Department of Psychology and Neuroscience, Leibniz Research Centre for Working Environment and Human Factors (IfADo), 44139, Dortmund, Germany
| | - Christoph Fraenz
- Department of Psychology and Neuroscience, Leibniz Research Centre for Working Environment and Human Factors (IfADo), 44139, Dortmund, Germany
| | - Caroline Schlüter
- Biopsychology, Institute for Cognitive Neuroscience, Faculty of Psychology, Ruhr-University Bochum, 44801, Bochum, Germany
| | - Wendy Johnson
- Department of Psychology, University of Edinburgh, EH8 9JZ, Edinburgh, UK
| | - Onur Güntürkün
- Biopsychology, Institute for Cognitive Neuroscience, Faculty of Psychology, Ruhr-University Bochum, 44801, Bochum, Germany
| | - Colin G DeYoung
- Department of Psychology, University of Minnesota, 55455, Minneapolis, MN, USA
| | - Erhan Genç
- Department of Psychology and Neuroscience, Leibniz Research Centre for Working Environment and Human Factors (IfADo), 44139, Dortmund, Germany
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Breault MS, Sacré P, Fitzgerald ZB, Gale JT, Cullen KE, González-Martínez JA, Sarma SV. Internal states as a source of subject-dependent movement variability are represented by large-scale brain networks. Nat Commun 2023; 14:7837. [PMID: 38030611 PMCID: PMC10687170 DOI: 10.1038/s41467-023-43257-4] [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: 08/24/2022] [Accepted: 11/03/2023] [Indexed: 12/01/2023] Open
Abstract
Humans' ability to adapt and learn relies on reflecting on past performance. These experiences form latent representations called internal states that induce movement variability that improves how we interact with our environment. Our study uncovered temporal dynamics and neural substrates of two states from ten subjects implanted with intracranial depth electrodes while they performed a goal-directed motor task with physical perturbations. We identified two internal states using state-space models: one tracking past errors and the other past perturbations. These states influenced reaction times and speed errors, revealing how subjects strategize from trial history. Using local field potentials from over 100 brain regions, we found large-scale brain networks such as the dorsal attention and default mode network modulate visuospatial attention based on recent performance and environmental feedback. Notably, these networks were more prominent in higher-performing subjects, emphasizing their role in improving motor performance by regulating movement variability through internal states.
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Affiliation(s)
- Macauley Smith Breault
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
| | - Pierre Sacré
- Department of Electrical Engineering and Computer Science, School of Engineering, University of Liège, Liège, Belgium
| | - Zachary B Fitzgerald
- Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | | | - Kathleen E Cullen
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | | | - Sridevi V Sarma
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
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Jung C, Kim J, Park K. Cognitive and affective interaction with somatosensory afference in acupuncture-a specific brain response to compound stimulus. Front Hum Neurosci 2023; 17:1105703. [PMID: 37415858 PMCID: PMC10321409 DOI: 10.3389/fnhum.2023.1105703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 06/05/2023] [Indexed: 07/08/2023] Open
Abstract
Introduction Acupuncture is a clinical intervention consisting of multiple stimulus components, including somatosensory stimulation and manipulation of therapeutic context. Existing findings in neuroscience consolidated cognitive modulation to somatosensory afferent process, which could differ from placebo mechanism in brain. Here, we aimed to identify intrinsic process of brain interactions induced by compound stimulus of acupuncture treatment. Methods To separately and comprehensively investigate somatosensory afferent and cognitive/affective processes in brain, we implemented a novel experimental protocol of contextual manipulation with somatosensory stimulation (real acupuncture: REAL) and only contextual manipulation (phantom acupuncture: PHNT) for fMRI scan, and conducted independent component (IC)-wise assessment with the concatenated fMRI data. Results By our double (experimentally and analytically) dissociation, two ICs (CA1: executive control, CA2: goal-directed sensory process) for cognitive/affective modulation (associated with both REAL and PHNT) and other two ICs (SA1: interoceptive attention and motor-reaction, SA2: somatosensory representation) for somatosensory afference (associated with only REAL) were identified. Moreover, coupling between SA1 and SA2 was associated with a decreased heart rate during stimulation, whereas CA1 was associated with a delayed heart rate decrease post-stimulation. Furthermore, partial correlation network for these components demonstrated a bi-directional interaction between CA1 and SA1/SA2, suggesting the cognitive modulation to somatosensory process. The expectation for the treatment negatively affected CA1 but positively affected SA1 in REAL, whereas the expectation positively affected CA1 in PHNT. Discussion These specific cognitive-somatosensory interaction in REAL were differed from vicarious sensation mechanism in PHNT; and might be associated with a characteristic of acupuncture, which induces voluntary attention for interoception. Our findings on brain interactions in acupuncture treatment elucidated the underlying brain mechanisms for compound stimulus of somatosensory afferent and therapeutic contextual manipulation, which might be a specific response to acupuncture.
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Affiliation(s)
- Changjin Jung
- Department of Electronics and Information Convergence Engineering, Kyung Hee University, Yongin, Republic of Korea
- Division of KM Science Research, Korea Institute of Oriental Medicine, Daejeon, Republic of Korea
| | - Jieun Kim
- Division of KM Science Research, Korea Institute of Oriental Medicine, Daejeon, Republic of Korea
| | - Kyungmo Park
- Department of Biomedical Engineering, Kyung Hee University, Yongin, Republic of Korea
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Huang H, Li R, Zhang J. A review of visual sustained attention: neural mechanisms and computational models. PeerJ 2023; 11:e15351. [PMID: 37334118 PMCID: PMC10274610 DOI: 10.7717/peerj.15351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 04/13/2023] [Indexed: 06/20/2023] Open
Abstract
Sustained attention is one of the basic abilities of humans to maintain concentration on relevant information while ignoring irrelevant information over extended periods. The purpose of the review is to provide insight into how to integrate neural mechanisms of sustained attention with computational models to facilitate research and application. Although many studies have assessed attention, the evaluation of humans' sustained attention is not sufficiently comprehensive. Hence, this study provides a current review on both neural mechanisms and computational models of visual sustained attention. We first review models, measurements, and neural mechanisms of sustained attention and propose plausible neural pathways for visual sustained attention. Next, we analyze and compare the different computational models of sustained attention that the previous reviews have not systematically summarized. We then provide computational models for automatically detecting vigilance states and evaluation of sustained attention. Finally, we outline possible future trends in the research field of sustained attention.
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Affiliation(s)
- Huimin Huang
- National Engineering Research Center for E-learning, Central China Normal University, Wuhan, Hubei, China
| | - Rui Li
- National Engineering Research Center for E-learning, Central China Normal University, Wuhan, Hubei, China
| | - Junsong Zhang
- Brain Cognition and Intelligent Computing Lab, Department of Artificial Intelligence, School of Informatics, Xiamen University, Xiamen, Fujian, China
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Nie Z, Xie X, Kang L, Wang W, Xu S, Chen M, Yao L, Gong Q, Zhou E, Li M, Wang H, Bu L, Liu Z. A Cross-Sectional Study: Structural and Related Functional Connectivity Changes in the Brain: Stigmata of Adverse Parenting in Patients with Major Depressive Disorder? Brain Sci 2023; 13:brainsci13040694. [PMID: 37190659 DOI: 10.3390/brainsci13040694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 04/17/2023] [Accepted: 04/18/2023] [Indexed: 05/17/2023] Open
Abstract
Background: There is a high correlation between the risk of major depressive disorder (MDD) and adverse childhood experiences (ACEs) such as adverse parenting (AP). While there appears to be an association between ACEs and changes in brain structure and function, there have yet to be multimodal neuroimaging studies of associations between parenting style and brain developmental changes in MDD patients. To explore the effect of AP on brain structure and function. Methods: In this cross-sectional study, 125 MDD outpatients were included in the study and divided into the AP group and the optimal parenting (OP) group. Participants completed self-rating scales to assess depressive severity, symptoms, and their parents' styles. They also completed magnetic resonance imaging within one week of filling out the instruments. The differences between groups of gender, educational level, and medications were analyzed using the chi-squared test and those of age, duration of illness, and scores on scales using the independent samples t-test. Differences in gray matter volume (GMV) and resting-state functional connectivity (RS-FC) were assessed between groups. Results: AP was associated with a significant increase in GMV in the right superior parietal lobule (SPL) and FC between the right SPL and the bilateral medial superior frontal cortex in MDD patients. Limitations: The cross-cultural characteristics of AP will result in the lack of generalizability of the findings. Conclusions: The results support the hypothesis that AP during childhood may imprint the brain and affect depressive symptoms in adulthood. Parents should pay attention to the parenting style and avoid a style that lacks warmth.
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Affiliation(s)
- Zhaowen Nie
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Xinhui Xie
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Lijun Kang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Wei Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Shuxian Xu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Mianmian Chen
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Lihua Yao
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Qian Gong
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Enqi Zhou
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Meng Li
- PET/CT/MRI and Molecular Imaging Center, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Huiling Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Lihong Bu
- PET/CT/MRI and Molecular Imaging Center, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Zhongchun Liu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Taikang Center for Life and Medical Sciences, Wuhan University, Wuhan 430072, China
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Spangler DP, Yang X, Weidler BJ, Thayer JF, McGinley JJ. Unraveling the cognitive correlates of heart rate variability with the drift diffusion model. Int J Psychophysiol 2022; 181:73-84. [PMID: 36029919 DOI: 10.1016/j.ijpsycho.2022.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 07/20/2022] [Accepted: 08/18/2022] [Indexed: 11/19/2022]
Abstract
The Neurovisceral Integration Model posits a link between resting vagally mediated heart rate variability (vmHRV) and cognitive control. Empirical support for this link is mixed, potentially due to coarse performance metrics such as mean response time (RT). To clarify this issue, we tested the relationships between resting vmHRV and refined estimates of cognitive control- as revealed by the ex-Gaussian model of RT and, to a greater extent, the drift diffusion model (DDM, a computational model of two-choice performance). Participants (N = 174) completed a five-minute resting baseline while ECG was collected followed by a Simon spatial conflict task. The root mean square of successive differences in interbeat intervals was calculated to index resting vmHRV. Resting vmHRV was unrelated to Simon's mean RT and accuracy rates, but was inversely related to the ex-Gaussian parameter reflecting slow RTs (tau); however, this finding was attenuated after adjustment for covariates. High resting vmHRV was related to faster drift rates and slower non-decision times, DDM parameters reflecting goal-directed cognition and sensorimotor processes, respectively. The DDM effects survived covariate adjustment and were specific to incongruent trials (i.e., when cognitive control demands were high). Findings suggest a link between vmHRV and cognitive control vis-a-vis drift rate, and potentially, a link between vmHRV and motoric inhibition vis-a-vis non-decision time. These cognitive correlates would have been missed with reliance on traditional performance. Findings are discussed with respect to the inhibitory processes that promote effective performance in high vmHRV individuals.
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Affiliation(s)
- Derek P Spangler
- Department of Biobehavioral Health, Penn State University, United States of America.
| | - Xiao Yang
- Department of Psychology, Old Dominion University, United States of America
| | - Blaire J Weidler
- Department of Psychology, Towson University, United States of America
| | - Julian F Thayer
- Department of Psychological Science, University of California, Irvine, United States of America; The Ohio State University, Deparatment of Psychology, United States of America
| | - Jared J McGinley
- Department of Psychology, Towson University, United States of America
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