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Bath JE, Wang DD. Unraveling the threads of stability: A review of the neurophysiology of postural control in Parkinson's disease. Neurotherapeutics 2024; 21:e00354. [PMID: 38579454 PMCID: PMC11000188 DOI: 10.1016/j.neurot.2024.e00354] [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: 11/30/2023] [Revised: 03/18/2024] [Accepted: 03/23/2024] [Indexed: 04/07/2024] Open
Abstract
Postural instability is a detrimental and often treatment-refractory symptom of Parkinson's disease. While many existing studies quantify the biomechanical deficits among various postural domains (static, anticipatory, and reactive) in this population, less is known regarding the neural network dysfunctions underlying these phenomena. This review will summarize current studies on the cortical and subcortical neural activities during postural responses in healthy subjects and those with Parkinson's disease. We will also review the effects of current therapies, including neuromodulation and feedback-based wearable devices, on postural instability symptoms. With recent advances in implantable devices that allow chronic, ambulatory neural data collection from patients with Parkinson's disease, combined with sensors that can quantify biomechanical measurements of postural responses, future work using these devices will enable better understanding of the neural mechanisms of postural control. Bridging this knowledge gap will be the critical first step towards developing novel neuromodulatory interventions to enhance the treatment of postural instability in Parkinson's disease.
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Affiliation(s)
- Jessica E Bath
- Department of Physical Therapy & Rehabilitation Science, University of California, San Francisco, USA; Department of Neurological Surgery, University of California, San Francisco, USA
| | - Doris D Wang
- Department of Neurological Surgery, University of California, San Francisco, USA.
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2
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Monaghan AS, Ofori E, Fling BW, Peterson DS. Associating white matter microstructural integrity and improvements in reactive stepping in people with Parkinson's Disease. Brain Imaging Behav 2024:10.1007/s11682-024-00867-w. [PMID: 38530517 DOI: 10.1007/s11682-024-00867-w] [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] [Accepted: 02/15/2024] [Indexed: 03/28/2024]
Abstract
Reactive steps are rapid responses after balance challenges. People with Parkinson's Disease (PwPD) demonstrate impaired reactive stepping, increasing fall-risk. Although PwPD can improve steps through practice, the neural mechanisms contributing to improved reactive stepping are poorly understood. This study investigated white-matter correlates of responsiveness to reactive step training in PwPD. In an eighteen-week multiple-baseline study, participants (n = 22) underwent baseline assessments (B1 and B2 two-weeks apart), a two-week training protocol, and post-training assessments immediately (P1) and two-months (P2) post-training. Assessments involved three backward reactive step trials, measuring anterior-posterior margin of stability (AP MOS), step length, and step latency. Tract-Based Spatial Statistics correlated white-matter integrity (fractional anisotropy (FA) and radial diffusivity (RD)) with retained (P2-B2) and immediate improvements (P1-B2) in stepping. Significant and sustained improvements in step length and AP MOS were observed. Greater retention of step length improvement correlated with increased FA in the left anterior thalamic radiation (ATR), left posterior thalamic radiation (PTR), left superior longitudinal fasciculus (SLF), and right inferior longitudinal fasciculus (ILF). Step latency retention was associated with lower RD in the left posterior corona radiata and left PTR. Immediate improvements in AP MOS correlated with increased FA of the right ILF, right SLF, and right corticospinal tract. Immediate step length improvements were associated with increased FA in right and left ATR and right SLF. These findings highlight the importance of white-matter microstructural integrity in motor learning and retention processes in PD and could aid in identifying individuals with PD who would benefit most from balance rehabilitation.
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Affiliation(s)
- Andrew S Monaghan
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Edward Ofori
- College of Health Solutions, Arizona State University, Phoenix, AZ, USA
| | - Brett W Fling
- Department of Health and Exercise Science, Colorado State University, Fort Collins, CO, USA
- Molecular, Cellular and Integrative Neurosciences Program, Colorado State University, Fort Collins, USA
| | - Daniel S Peterson
- College of Health Solutions, Arizona State University, Phoenix, AZ, USA.
- Phoenix VA Health Care Center, Phoenix, AZ, USA.
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Mooney MA, Hermosillo RJM, Feczko E, Miranda-Dominguez O, Moore LA, Perrone A, Byington N, Grimsrud G, Rueter A, Nousen E, Antovich D, Feldstein Ewing SW, Nagel BJ, Nigg JT, Fair DA. Cumulative Effects of Resting-State Connectivity Across All Brain Networks Significantly Correlate with Attention-Deficit Hyperactivity Disorder Symptoms. J Neurosci 2024; 44:e1202232023. [PMID: 38286629 PMCID: PMC10919250 DOI: 10.1523/jneurosci.1202-23.2023] [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: 04/19/2023] [Revised: 11/30/2023] [Accepted: 12/18/2023] [Indexed: 01/31/2024] Open
Abstract
Identification of replicable neuroimaging correlates of attention-deficit hyperactivity disorder (ADHD) has been hindered by small sample sizes, small effects, and heterogeneity of methods. Given evidence that ADHD is associated with alterations in widely distributed brain networks and the small effects of individual brain features, a whole-brain perspective focusing on cumulative effects is warranted. The use of large, multisite samples is crucial for improving reproducibility and clinical utility of brain-wide MRI association studies. To address this, a polyneuro risk score (PNRS) representing cumulative, brain-wide, ADHD-associated resting-state functional connectivity was constructed and validated using data from the Adolescent Brain Cognitive Development (ABCD, N = 5,543, 51.5% female) study, and was further tested in the independent Oregon-ADHD-1000 case-control cohort (N = 553, 37.4% female). The ADHD PNRS was significantly associated with ADHD symptoms in both cohorts after accounting for relevant covariates (p < 0.001). The most predictive PNRS involved all brain networks, though the strongest effects were concentrated among the default mode and cingulo-opercular networks. In the longitudinal Oregon-ADHD-1000, non-ADHD youth had significantly lower PNRS (Cohen's d = -0.318, robust p = 5.5 × 10-4) than those with persistent ADHD (age 7-19). The PNRS, however, did not mediate polygenic risk for ADHD. Brain-wide connectivity was robustly associated with ADHD symptoms in two independent cohorts, providing further evidence of widespread dysconnectivity in ADHD. Evaluation in enriched samples demonstrates the promise of the PNRS approach for improving reproducibility in neuroimaging studies and unraveling the complex relationships between brain connectivity and behavioral disorders.
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Affiliation(s)
- Michael A Mooney
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon 97239
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon 97239
- Center for Mental Health Innovation, Oregon Health & Science University, Portland, Oregon 97239
| | - Robert J M Hermosillo
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota 55454
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
| | - Eric Feczko
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota 55454
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
| | - Oscar Miranda-Dominguez
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota 55454
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
- Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455
| | - Lucille A Moore
- Department of Neurology, Oregon Health & Science University, Portland, Oregon 97239
| | - Anders Perrone
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
| | - Nora Byington
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
| | - Gracie Grimsrud
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
| | - Amanda Rueter
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
| | - Elizabeth Nousen
- Center for Mental Health Innovation, Oregon Health & Science University, Portland, Oregon 97239
- Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, Oregon 97239
| | - Dylan Antovich
- Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, Oregon 97239
| | | | - Bonnie J Nagel
- Center for Mental Health Innovation, Oregon Health & Science University, Portland, Oregon 97239
- Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, Oregon 97239
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon 97239
| | - Joel T Nigg
- Center for Mental Health Innovation, Oregon Health & Science University, Portland, Oregon 97239
- Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, Oregon 97239
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon 97239
| | - Damien A Fair
- Department of Pediatrics, University of Minnesota, Minneapolis, Minnesota 55454
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota 55414
- Institute of Child Development, College of Education and Human Development, University of Minnesota, Minneapolis, Minnesota 55455
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Ragothaman A, Mancini M, Nutt JG, Wang J, Fair DA, Horak FB, Miranda-Dominguez O. Motor networks, but also non-motor networks predict motor signs in Parkinson's disease. Neuroimage Clin 2023; 40:103541. [PMID: 37972450 PMCID: PMC10685308 DOI: 10.1016/j.nicl.2023.103541] [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: 06/06/2023] [Revised: 10/31/2023] [Accepted: 11/10/2023] [Indexed: 11/19/2023]
Abstract
OBJECTIVE Investigate the brain functional networks associated with motor impairment in people with Parkinson's disease (PD). BACKGROUND PD is primarily characterized by motor dysfunction. Resting-state functional connectivity (RsFC) offers a unique opportunity to non-invasively characterize brain function. In this study, we hypothesized that the motor dysfunction observed in people with PD involves atypical connectivity not only in motor but also in higher-level attention networks. Understanding the interaction between motor and non-motor RsFC that are related to the motor signs could provide insights into PD pathophysiology. METHODS We used data from 88 people with PD (mean age: 68.2(SD:10), 55 M/33F) coming from 2 cohorts. Motor severity was assessed in practical OFF-medication state, using MDS-UPDRS Part-III motor scores (mean: 49 (SD:10)). RsFC was characterized using an atlas of 384 regions that were grouped into 13 functional networks. Associations between RsFC and motor severity were assessed independently for each RsFC using predictive modeling. RESULTS The top 5 % models that predicted the MDS-UPDRS-III motor scores with effect size >0.5 were the connectivity between (1) the somatomotor and Subcortical-Basal-ganglia, (2) somatomotor and Visual and (3) CinguloOpercular (CiO) and language/Ventral attention (Lan/VeA) network pairs. DISCUSSION Our findings suggest that, along with motor networks, visual- and attention-related cortical networks are also associated with the motor symptoms of PD. Non-motor networks may be involved indirectly in motor-coordination. When people with PD have deficits in motor networks, more attention may be needed to carry out formerly automatic motor functions, consistent with compensatory mechanisms in parkinsonian movement disorders.
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Affiliation(s)
| | - Martina Mancini
- Department of Neurology, Oregon Health and Science University, Portland, OR 97239, USA
| | - John G Nutt
- Department of Neurology, Oregon Health and Science University, Portland, OR 97239, USA
| | - Junping Wang
- Department of Radiology, Tianjin Medical University General Hospital, China
| | - Damien A Fair
- Masonic Institute for the Developing Brain (MIDB), University of Minnesota, Minneapolis, MN 55455, USA; Institute of Child Development, College of Education and Human Development, University of Minnesota, Minneapolis, MN 55455, USA; Department of Pediatrics, University of Minnesota Medical School, University of Minnesota, Minneapolis, MN 55455, USA; Department of Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97239, USA
| | - Fay B Horak
- Department of Neurology, Oregon Health and Science University, Portland, OR 97239, USA; Department of Behavioral Neuroscience, Oregon Health and Science University, Portland, OR 97239, USA.
| | - Oscar Miranda-Dominguez
- Masonic Institute for the Developing Brain (MIDB), University of Minnesota, Minneapolis, MN 55455, USA; Department of Pediatrics, University of Minnesota Medical School, University of Minnesota, Minneapolis, MN 55455, USA
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Byington N, Grimsrud G, Mooney MA, Cordova M, Doyle O, Hermosillo RJM, Earl E, Houghton A, Conan G, Hendrickson TJ, Ragothaman A, Carrasco CM, Rueter A, Perrone A, Moore LA, Graham A, Nigg JT, Thompson WK, Nelson SM, Feczko E, Fair DA, Miranda-Dominguez O. Polyneuro risk scores capture widely distributed connectivity patterns of cognition. Dev Cogn Neurosci 2023; 60:101231. [PMID: 36934605 PMCID: PMC10031023 DOI: 10.1016/j.dcn.2023.101231] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 03/06/2023] [Accepted: 03/13/2023] [Indexed: 03/17/2023] Open
Abstract
Resting-state functional connectivity (RSFC) is a powerful tool for characterizing brain changes, but it has yet to reliably predict higher-order cognition. This may be attributed to small effect sizes of such brain-behavior relationships, which can lead to underpowered, variable results when utilizing typical sample sizes (N∼25). Inspired by techniques in genomics, we implement the polyneuro risk score (PNRS) framework - the application of multivariate techniques to RSFC data and validation in an independent sample. Utilizing the Adolescent Brain Cognitive Development® cohort split into two datasets, we explore the framework's ability to reliably capture brain-behavior relationships across 3 cognitive scores - general ability, executive function, learning & memory. The weight and significance of each connection is assessed in the first dataset, and a PNRS is calculated for each participant in the second. Results support the PNRS framework as a suitable methodology to inspect the distribution of connections contributing towards behavior, with explained variance ranging from 1.0 % to 21.4 %. For the outcomes assessed, the framework reveals globally distributed, rather than localized, patterns of predictive connections. Larger samples are likely necessary to systematically identify the specific connections contributing towards complex outcomes. The PNRS framework could be applied translationally to identify neurologically distinct subtypes of neurodevelopmental disorders.
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Affiliation(s)
- Nora Byington
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States.
| | - Gracie Grimsrud
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States
| | - Michael A Mooney
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR 97239, United States; Knight Cancer Institute, Oregon Health & Science University, Portland, OR 97239, United States
| | - Michaela Cordova
- Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California San Diego, San Diego, CA 92120, United States
| | - Olivia Doyle
- Department of Psychiatry, Oregon Health & Science University, Portland, OR 97239, United States
| | - Robert J M Hermosillo
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States
| | - Eric Earl
- Data Science and Sharing Team, National Institute of Mental Health, Bethesda, MD 20892, United States
| | - Audrey Houghton
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States
| | - Gregory Conan
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States
| | - Timothy J Hendrickson
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States
| | | | - Cristian Morales Carrasco
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States
| | - Amanda Rueter
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States
| | - Anders Perrone
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States
| | - Lucille A Moore
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States
| | - Alice Graham
- Department of Psychiatry, Oregon Health & Science University, Portland, OR 97239, United States
| | - Joel T Nigg
- Department of Psychiatry, Oregon Health & Science University, Portland, OR 97239, United States; Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR 97239, United States
| | - Wesley K Thompson
- Center for Population Neuroscience and Genetics, Laureate Institute for Brain Research, Tulsa, OK 74136, United States
| | - Steven M Nelson
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States; Department of Pediatrics, University of Minnesota, Minneapolis, MN 55414, United States
| | - Eric Feczko
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States; Department of Pediatrics, University of Minnesota, Minneapolis, MN 55414, United States
| | - Damien A Fair
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States; Department of Pediatrics, University of Minnesota, Minneapolis, MN 55414, United States; Institute of Child Development, University of Minnesota, Minneapolis, MN 55414, United States
| | - Oscar Miranda-Dominguez
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States; Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN 55414, United States; Department of Pediatrics, University of Minnesota, Minneapolis, MN 55414, United States
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Cregg JM, Mirdamadi JL, Fortunato C, Okorokova EV, Kuper C, Nayeem R, Byun AJ, Avraham C, Buonocore A, Winner TS, Mildren RL. Highlights from the 31st Annual Meeting of the Society for the Neural Control of Movement. J Neurophysiol 2023; 129:220-234. [PMID: 36541602 PMCID: PMC9844973 DOI: 10.1152/jn.00500.2022] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 12/16/2022] [Indexed: 12/24/2022] Open
Affiliation(s)
- Jared M Cregg
- Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jasmine L Mirdamadi
- Division of Physical Therapy, Department of Rehabilitation Medicine, Emory University School of Medicine, Atlanta, Georgia
| | - Cátia Fortunato
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | | | - Clara Kuper
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
- School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Rashida Nayeem
- Department of Electrical Engineering, Northeastern University, Boston, Massachusetts
| | - Andrew J Byun
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts
| | - Chen Avraham
- Department of Biomedical Engineering, Ben-Gurion University of the Negev, Beersheva, Israel
| | - Antimo Buonocore
- Werner Reichardt Centre for Integrative Neuroscience, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- Department of Educational, Psychological and Communication Sciences, Suor Orsola Benincasa University, Naples, Italy
| | - Taniel S Winner
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, Georgia
| | - Robyn L Mildren
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland
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