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Jiang Y, Qi Z, Zhu H, Shen K, Liu R, Fang C, Lou W, Jiang Y, Yuan W, Cao X, Chen L, Zhuang Q. Role of the globus pallidus in motor and non-motor symptoms of Parkinson's disease. Neural Regen Res 2025; 20:1628-1643. [PMID: 38845220 DOI: 10.4103/nrr.nrr-d-23-01660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 04/21/2024] [Indexed: 08/07/2024] Open
Abstract
The globus pallidus plays a pivotal role in the basal ganglia circuit. Parkinson's disease is characterized by degeneration of dopamine-producing cells in the substantia nigra, which leads to dopamine deficiency in the brain that subsequently manifests as various motor and non-motor symptoms. This review aims to summarize the involvement of the globus pallidus in both motor and non-motor manifestations of Parkinson's disease. The firing activities of parvalbumin neurons in the medial globus pallidus, including both the firing rate and pattern, exhibit strong correlations with the bradykinesia and rigidity associated with Parkinson's disease. Increased beta oscillations, which are highly correlated with bradykinesia and rigidity, are regulated by the lateral globus pallidus. Furthermore, bradykinesia and rigidity are strongly linked to the loss of dopaminergic projections within the cortical-basal ganglia-thalamocortical loop. Resting tremors are attributed to the transmission of pathological signals from the basal ganglia through the motor cortex to the cerebellum-ventral intermediate nucleus circuit. The cortico-striato-pallidal loop is responsible for mediating pallidi-associated sleep disorders. Medication and deep brain stimulation are the primary therapeutic strategies addressing the globus pallidus in Parkinson's disease. Medication is the primary treatment for motor symptoms in the early stages of Parkinson's disease, while deep brain stimulation has been clinically proven to be effective in alleviating symptoms in patients with advanced Parkinson's disease, particularly for the movement disorders caused by levodopa. Deep brain stimulation targeting the globus pallidus internus can improve motor function in patients with tremor-dominant and non-tremor-dominant Parkinson's disease, while deep brain stimulation targeting the globus pallidus externus can alter the temporal pattern of neural activity throughout the basal ganglia-thalamus network. Therefore, the composition of the globus pallidus neurons, the neurotransmitters that act on them, their electrical activity, and the neural circuits they form can guide the search for new multi-target drugs to treat Parkinson's disease in clinical practice. Examining the potential intra-nuclear and neural circuit mechanisms of deep brain stimulation associated with the globus pallidus can facilitate the management of both motor and non-motor symptoms while minimizing the side effects caused by deep brain stimulation.
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Affiliation(s)
- Yimiao Jiang
- Department of Physiology, School of Medicine, Nantong University, Nantong, Jiangsu Province, China
| | - Zengxin Qi
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- National Center for Neurological Disorders, Shanghai, China
- Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, China
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institute of Brain Science, Fudan University, Shanghai, China
| | - Huixian Zhu
- Department of Physiology, School of Medicine, Nantong University, Nantong, Jiangsu Province, China
| | - Kangli Shen
- Department of Physiology, School of Medicine, Nantong University, Nantong, Jiangsu Province, China
| | - Ruiqi Liu
- Department of Physiology, School of Medicine, Nantong University, Nantong, Jiangsu Province, China
| | - Chenxin Fang
- Department of Physiology, School of Medicine, Nantong University, Nantong, Jiangsu Province, China
| | - Weiwei Lou
- Department of Physiology, School of Medicine, Nantong University, Nantong, Jiangsu Province, China
| | - Yifan Jiang
- Department of Physiology, School of Medicine, Nantong University, Nantong, Jiangsu Province, China
| | - Wangrui Yuan
- Department of Physiology, School of Medicine, Nantong University, Nantong, Jiangsu Province, China
| | - Xin Cao
- Department of Physiology, School of Medicine, Nantong University, Nantong, Jiangsu Province, China
| | - Liang Chen
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- National Center for Neurological Disorders, Shanghai, China
- Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, China
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institute of Brain Science, Fudan University, Shanghai, China
| | - Qianxing Zhuang
- Department of Physiology, School of Medicine, Nantong University, Nantong, Jiangsu Province, China
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Correa A, Ponzi A, Calderón VM, Migliore R. Pathological cell assembly dynamics in a striatal MSN network model. Front Comput Neurosci 2024; 18:1410335. [PMID: 38903730 PMCID: PMC11188713 DOI: 10.3389/fncom.2024.1410335] [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: 04/01/2024] [Accepted: 05/15/2024] [Indexed: 06/22/2024] Open
Abstract
Under normal conditions the principal cells of the striatum, medium spiny neurons (MSNs), show structured cell assembly activity patterns which alternate sequentially over exceedingly long timescales of many minutes. It is important to understand this activity since it is characteristically disrupted in multiple pathologies, such as Parkinson's disease and dyskinesia, and thought to be caused by alterations in the MSN to MSN lateral inhibitory connections and in the strength and distribution of cortical excitation to MSNs. To understand how these long timescales arise we extended a previous network model of MSN cells to include synapses with short-term plasticity, with parameters taken from a recent detailed striatal connectome study. We first confirmed the presence of sequentially switching cell clusters using the non-linear dimensionality reduction technique, Uniform Manifold Approximation and Projection (UMAP). We found that the network could generate non-stationary activity patterns varying extremely slowly on the order of minutes under biologically realistic conditions. Next we used Simulation Based Inference (SBI) to train a deep net to map features of the MSN network generated cell assembly activity to MSN network parameters. We used the trained SBI model to estimate MSN network parameters from ex-vivo brain slice calcium imaging data. We found that best fit network parameters were very close to their physiologically observed values. On the other hand network parameters estimated from Parkinsonian, decorticated and dyskinetic ex-vivo slice preparations were different. Our work may provide a pipeline for diagnosis of basal ganglia pathology from spiking data as well as for the design pharmacological treatments.
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Affiliation(s)
- Astrid Correa
- Institute of Biophysics, National Research Council, Palermo, Italy
| | - Adam Ponzi
- Institute of Biophysics, National Research Council, Palermo, Italy
- Center for Human Nature, Artificial Intelligence, and Neuroscience, Hokkaido University, Sapporo, Japan
| | - Vladimir M. Calderón
- Department of Developmental Neurobiology and Neurophysiology, Neurobiology Institute, National Autonomous University of Mexico, Querétaro, Mexico
| | - Rosanna Migliore
- Institute of Biophysics, National Research Council, Palermo, Italy
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Kucikova L, Danso S, Jia L, Su L. Computational Psychiatry and Computational Neurology: Seeking for Mechanistic Modeling in Cognitive Impairment and Dementia. Front Comput Neurosci 2022; 16:865805. [PMID: 35645752 PMCID: PMC9130488 DOI: 10.3389/fncom.2022.865805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 04/25/2022] [Indexed: 12/02/2022] Open
Affiliation(s)
- Ludmila Kucikova
- Department of Neuroscience, Sheffield Institute for Translational Neuroscience, Insigneo Institute for in silico Medicine, University of Sheffield, Sheffield, United Kingdom
| | - Samuel Danso
- Edinburgh Dementia Prevention and Centre for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, United Kingdom
| | - Lina Jia
- Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Li Su
- Department of Neuroscience, Sheffield Institute for Translational Neuroscience, Insigneo Institute for in silico Medicine, University of Sheffield, Sheffield, United Kingdom
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
- *Correspondence: Li Su
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West TO, Magill PJ, Sharott A, Litvak V, Farmer SF, Cagnan H. Stimulating at the right time to recover network states in a model of the cortico-basal ganglia-thalamic circuit. PLoS Comput Biol 2022; 18:e1009887. [PMID: 35245281 PMCID: PMC8939795 DOI: 10.1371/journal.pcbi.1009887] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 03/22/2022] [Accepted: 01/31/2022] [Indexed: 11/26/2022] Open
Abstract
Synchronization of neural oscillations is thought to facilitate communication in the brain. Neurodegenerative pathologies such as Parkinson's disease (PD) can result in synaptic reorganization of the motor circuit, leading to altered neuronal dynamics and impaired neural communication. Treatments for PD aim to restore network function via pharmacological means such as dopamine replacement, or by suppressing pathological oscillations with deep brain stimulation. We tested the hypothesis that brain stimulation can operate beyond a simple "reversible lesion" effect to augment network communication. Specifically, we examined the modulation of beta band (14-30 Hz) activity, a known biomarker of motor deficits and potential control signal for stimulation in Parkinson's. To do this we setup a neural mass model of population activity within the cortico-basal ganglia-thalamic (CBGT) circuit with parameters that were constrained to yield spectral features comparable to those in experimental Parkinsonism. We modulated the connectivity of two major pathways known to be disrupted in PD and constructed statistical summaries of the spectra and functional connectivity of the resulting spontaneous activity. These were then used to assess the network-wide outcomes of closed-loop stimulation delivered to motor cortex and phase locked to subthalamic beta activity. Our results demonstrate that the spatial pattern of beta synchrony is dependent upon the strength of inputs to the STN. Precisely timed stimulation has the capacity to recover network states, with stimulation phase inducing activity with distinct spectral and spatial properties. These results provide a theoretical basis for the design of the next-generation brain stimulators that aim to restore neural communication in disease.
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Affiliation(s)
- Timothy O. West
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Peter J. Magill
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Oxford Parkinson’s Disease Centre, University of Oxford, Oxford, United Kingdom
| | - Andrew Sharott
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Vladimir Litvak
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Simon F. Farmer
- Department of Neurology, National Hospital for Neurology & Neurosurgery, London, United Kingdom
- Department of Clinical and Human Neuroscience, UCL Institute of Neurology, London, United Kingdom
| | - Hayriye Cagnan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, United Kingdom
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Frässle S, Stephan KE. Test-retest reliability of regression dynamic causal modeling. Netw Neurosci 2022; 6:135-160. [PMID: 35356192 PMCID: PMC8959103 DOI: 10.1162/netn_a_00215] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 11/08/2021] [Indexed: 11/04/2022] Open
Abstract
Abstract
Regression dynamic causal modeling (rDCM) is a novel and computationally highly efficient method for inferring effective connectivity at the whole-brain level. While face and construct validity of rDCM have already been demonstrated, here we assessed its test-retest reliability—a test-theoretical property of particular importance for clinical applications—together with group-level consistency of connection-specific estimates and consistency of whole-brain connectivity patterns over sessions. Using the Human Connectome Project dataset for eight different paradigms (tasks and rest) and two different parcellation schemes, we found that rDCM provided highly consistent connectivity estimates at the group level across sessions. Second, while test-retest reliability was limited when averaging over all connections (range of mean intraclass correlation coefficient 0.24–0.42 over tasks), reliability increased with connection strength, with stronger connections showing good to excellent test-retest reliability. Third, whole-brain connectivity patterns by rDCM allowed for identifying individual participants with high (and in some cases perfect) accuracy. Comparing the test-retest reliability of rDCM connectivity estimates with measures of functional connectivity, rDCM performed favorably—particularly when focusing on strong connections. Generally, for all methods and metrics, task-based connectivity estimates showed greater reliability than those from the resting state. Our results underscore the potential of rDCM for human connectomics and clinical applications.
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Affiliation(s)
- Stefan Frässle
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Klaas E. Stephan
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
- Max Planck Institute for Metabolism Research, Cologne, Germany
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Sasi S, Bhattacharya BS. Phase entrainment by periodic stimuli in silico: A quantitative study. Neurocomputing 2022. [DOI: 10.1016/j.neucom.2021.10.077] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
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Bellot E, Kauffmann L, Coizet V, Meoni S, Moro E, Dojat M. Effective connectivity in subcortical visual structures in de novo Patients with Parkinson's Disease. Neuroimage Clin 2021; 33:102906. [PMID: 34891045 PMCID: PMC8670854 DOI: 10.1016/j.nicl.2021.102906] [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: 08/04/2021] [Revised: 10/26/2021] [Accepted: 12/01/2021] [Indexed: 10/19/2022]
Abstract
BACKGROUND Parkinson's disease (PD) manifests with the appearance of non-motor symptoms before motor symptoms onset. Among these, dysfunctioning visual structures have recently been reported to occur at early disease stages. OBJECTIVE This study addresses effective connectivity in the visual network of PD patients. METHODS Using functional MRI and dynamic causal modeling analysis, we evaluated the connectivity between the superior colliculus, the lateral geniculate nucleus and the primary visual area V1 in de novo untreated PD patients (n = 22). A subset of the PD patients (n = 8) was longitudinally assessed two times at two months and at six months after starting dopaminergic treatment. Results were compared to those of age-matched healthy controls (n = 22). RESULTS Our results indicate that the superior colliculus drives cerebral activity for luminance contrast processing both in healthy controls and untreated PD patients. The same effective connectivity was observed with neuromodulatory differences in terms of neuronal dynamic interactions. Our main findings were that the modulation induced by luminance contrast changes of the superior colliculus connectivity (self-connectivity and connectivity to the lateral geniculate nucleus) was inhibited in PD patients (effect of contrast: p = 0.79 and p = 0.77 respectively). The introduction of dopaminergic medication in a subset (n = 8) of the PD patients failed to restore the effective connectivity modulation observed in the healthy controls. INTERPRETATION The deficits in luminance contrast processing in PD was associated with a deficiency in connectivity adjustment from the superior colliculus to the lateral geniculate nucleus and to V1. No differences in cerebral blood flow were observed between controls and PD patients suggesting that the deficiency was at the neuronal level. Administration of a dopaminergic treatment over six months was not able to normalize the observed alterations in inter-regional coupling. These findings highlight the presence of early dysfunctions in primary visual areas, which might be used as early markers of the disease.
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Affiliation(s)
- Emmanuelle Bellot
- University Grenoble Alpes, Inserm U1216, Centre Hospitalier Universitaire de Grenoble, Grenoble Institute of Neurosciences, Grenoble, France
| | - Louise Kauffmann
- Laboratory of Psychology and Neurocognition, CNRS UMR 5105, Grenoble, France
| | - Véronique Coizet
- University Grenoble Alpes, Inserm U1216, Centre Hospitalier Universitaire de Grenoble, Grenoble Institute of Neurosciences, Grenoble, France
| | - Sara Meoni
- University Grenoble Alpes, Inserm U1216, Centre Hospitalier Universitaire de Grenoble, Grenoble Institute of Neurosciences, Grenoble, France; Laboratory of Psychology and Neurocognition, CNRS UMR 5105, Grenoble, France; Movement Disorders Unit, Division of Neurology, CHU Grenoble Alpes, Grenoble, France
| | - Elena Moro
- University Grenoble Alpes, Inserm U1216, Centre Hospitalier Universitaire de Grenoble, Grenoble Institute of Neurosciences, Grenoble, France; Laboratory of Psychology and Neurocognition, CNRS UMR 5105, Grenoble, France
| | - Michel Dojat
- University Grenoble Alpes, Inserm U1216, Centre Hospitalier Universitaire de Grenoble, Grenoble Institute of Neurosciences, Grenoble, France.
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Wang D, Liang S. Dynamic Causal Modeling on the Identification of Interacting Networks in the Brain: A Systematic Review. IEEE Trans Neural Syst Rehabil Eng 2021; 29:2299-2311. [PMID: 34714747 DOI: 10.1109/tnsre.2021.3123964] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Dynamic causal modeling (DCM) has long been used to characterize effective connectivity within networks of distributed neuronal responses. Previous reviews have highlighted the understanding of the conceptual basis behind DCM and its variants from different aspects. However, no detailed summary or classification research on the task-related effective connectivity of various brain regions has been made formally available so far, and there is also a lack of application analysis of DCM for hemodynamic and electrophysiological measurements. This review aims to analyze the effective connectivity of different brain regions using DCM for different measurement data. We found that, in general, most studies focused on the networks between different cortical regions, and the research on the networks between other deep subcortical nuclei or between them and the cerebral cortex are receiving increasing attention, but far from the same scale. Our analysis also reveals a clear bias towards some task types. Based on these results, we identify and discuss several promising research directions that may help the community to attain a clear understanding of the brain network interactions under different tasks.
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Oswal A, Cao C, Yeh CH, Neumann WJ, Gratwicke J, Akram H, Horn A, Li D, Zhan S, Zhang C, Wang Q, Zrinzo L, Foltynie T, Limousin P, Bogacz R, Sun B, Husain M, Brown P, Litvak V. Neural signatures of hyperdirect pathway activity in Parkinson's disease. Nat Commun 2021; 12:5185. [PMID: 34465771 PMCID: PMC8408177 DOI: 10.1038/s41467-021-25366-0] [Citation(s) in RCA: 58] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Accepted: 08/02/2021] [Indexed: 11/25/2022] Open
Abstract
Parkinson's disease (PD) is characterised by the emergence of beta frequency oscillatory synchronisation across the cortico-basal-ganglia circuit. The relationship between the anatomy of this circuit and oscillatory synchronisation within it remains unclear. We address this by combining recordings from human subthalamic nucleus (STN) and internal globus pallidus (GPi) with magnetoencephalography, tractography and computational modelling. Coherence between supplementary motor area and STN within the high (21-30 Hz) but not low (13-21 Hz) beta frequency range correlated with 'hyperdirect pathway' fibre densities between these structures. Furthermore, supplementary motor area activity drove STN activity selectively at high beta frequencies suggesting that high beta frequencies propagate from the cortex to the basal ganglia via the hyperdirect pathway. Computational modelling revealed that exaggerated high beta hyperdirect pathway activity can provoke the generation of widespread pathological synchrony at lower beta frequencies. These findings suggest a spectral signature and a pathophysiological role for the hyperdirect pathway in PD.
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Affiliation(s)
- Ashwini Oswal
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK.
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
- The Wellcome Centre for Human Neuroimaging, University College London, London, UK.
| | - Chunyan Cao
- Department of Neurosurgery, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Chien-Hung Yeh
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- School of Information and Electronics Engineering, Beijing Institute of Technology, Beijing, China
| | | | - James Gratwicke
- Department of Clinical and Movement Neurosciences, University College London, London, UK
| | - Harith Akram
- Department of Clinical and Movement Neurosciences, University College London, London, UK
| | - Andreas Horn
- Department of Neurology, Charité University, Berlin, Germany
| | - Dianyou Li
- Department of Neurosurgery, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Shikun Zhan
- Department of Neurosurgery, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Chao Zhang
- Department of Neurosurgery, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Qiang Wang
- Department of Neurology, Charité University, Berlin, Germany
| | - Ludvic Zrinzo
- Department of Clinical and Movement Neurosciences, University College London, London, UK
| | - Tom Foltynie
- Department of Clinical and Movement Neurosciences, University College London, London, UK
| | - Patricia Limousin
- Department of Clinical and Movement Neurosciences, University College London, London, UK
| | - Rafal Bogacz
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Bomin Sun
- Department of Neurosurgery, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Masud Husain
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Peter Brown
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK.
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Vladimir Litvak
- The Wellcome Centre for Human Neuroimaging, University College London, London, UK.
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West TO, Berthouze L, Farmer SF, Cagnan H, Litvak V. Inference of brain networks with approximate Bayesian computation - assessing face validity with an example application in Parkinsonism. Neuroimage 2021; 236:118020. [PMID: 33839264 PMCID: PMC8270890 DOI: 10.1016/j.neuroimage.2021.118020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 03/16/2021] [Accepted: 03/21/2021] [Indexed: 11/21/2022] Open
Abstract
This paper describes and validates a novel framework using the Approximate Bayesian Computation (ABC) algorithm for parameter estimation and model selection in models of mesoscale brain network activity. We provide a proof of principle, first pass validation of this framework using a set of neural mass models of the cortico-basal ganglia thalamic circuit inverted upon spectral features from experimental, in vivo recordings. This optimization scheme relaxes an assumption of fixed-form posteriors (i.e. the Laplace approximation) taken in previous approaches to inverse modelling of spectral features. This enables the exploration of model dynamics beyond that approximated from local linearity assumptions and so fit to explicit, numerical solutions of the underlying non-linear system of equations. In this first paper, we establish a face validation of the optimization procedures in terms of: (i) the ability to approximate posterior densities over parameters that are plausible given the known causes of the data; (ii) the ability of the model comparison procedures to yield posterior model probabilities that can identify the model structure known to generate the data; and (iii) the robustness of these procedures to local minima in the face of different starting conditions. Finally, as an illustrative application we show (iv) that model comparison can yield plausible conclusions given the known neurobiology of the cortico-basal ganglia-thalamic circuit in Parkinsonism. These results lay the groundwork for future studies utilizing highly nonlinear or brittle models that can explain time dependant dynamics, such as oscillatory bursts, in terms of the underlying neural circuits.
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Affiliation(s)
- Timothy O West
- Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, Oxford OX3 9DU, United Kingdom; Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, United Kingdom; Wellcome Trust Centre for Human Neuroimaging, UCL Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom.
| | - Luc Berthouze
- Centre for Computational Neuroscience and Robotics, University of Sussex, Falmer, United Kingdom; UCL Great Ormond Street Institute of Child Health, Guildford St., London WC1N 1EH, United Kingdom
| | - Simon F Farmer
- Department of Neurology, National Hospital for Neurology & Neurosurgery, Queen Square, London WC1N 3BG, United Kingdom; Department of Clinical and Movement Neurosciences, Institute of Neurology, Queen Square, UCL, London WC1N 3BG, United Kingdom
| | - Hayriye Cagnan
- Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, Oxford OX3 9DU, United Kingdom; Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, United Kingdom; Wellcome Trust Centre for Human Neuroimaging, UCL Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom
| | - Vladimir Litvak
- Wellcome Trust Centre for Human Neuroimaging, UCL Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom
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Caligiore D, Montedori F, Buscaglione S, Capirchio A. Increasing Serotonin to Reduce Parkinsonian Tremor. Front Syst Neurosci 2021; 15:682990. [PMID: 34354572 PMCID: PMC8331097 DOI: 10.3389/fnsys.2021.682990] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 06/21/2021] [Indexed: 01/07/2023] Open
Abstract
While current dopamine-based drugs seem to be effective for most Parkinson's disease (PD) motor dysfunctions, they produce variable responsiveness for resting tremor. This lack of consistency could be explained by considering recent evidence suggesting that PD resting tremor can be divided into different partially overlapping phenotypes based on the dopamine response. These phenotypes may be associated with different pathophysiological mechanisms produced by a cortical-subcortical network involving even non-dopaminergic areas traditionally not directly related to PD. In this study, we propose a bio-constrained computational model to study the neural mechanisms underlying a possible type of PD tremor: the one mainly involving the serotoninergic system. The simulations run with the model demonstrate that a physiological serotonin increase can partially recover dopamine levels at the early stages of the disease before the manifestation of overt tremor. This result suggests that monitoring serotonin concentration changes could be critical for early diagnosis. The simulations also show the effectiveness of a new pharmacological treatment for tremor that acts on serotonin to recover dopamine levels. This latter result has been validated by reproducing existing data collected with human patients.
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Affiliation(s)
- Daniele Caligiore
- Computational and Translational Neuroscience Laboratory, Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Francesco Montedori
- Computational and Translational Neuroscience Laboratory, Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Silvia Buscaglione
- Neurophysiology and Neuroengineering of Human-Technology Interaction Research Unit (NeXT), Campus Bio-Medico University, Rome, Italy
| | - Adriano Capirchio
- Computational and Translational Neuroscience Laboratory, Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
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Charroud C, Turella L. Subcortical grey matter changes associated with motor symptoms evaluated by the Unified Parkinson's disease Rating Scale (part III): A longitudinal study in Parkinson's disease. NEUROIMAGE-CLINICAL 2021; 31:102745. [PMID: 34225020 PMCID: PMC8264213 DOI: 10.1016/j.nicl.2021.102745] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 03/26/2021] [Accepted: 06/23/2021] [Indexed: 01/18/2023]
Abstract
Decreased grey matter volume over time suggests a subcortical alteration in PD. Decreased volume in the thalamus may be related to the decline in motor skills. Increased volume in the pallidum may contribute to motor impairment. Structural changes in line with the model of basal ganglia-thalamocortical circuits. VBM and volumetry might capture complementary aspects of structural changes in PD.
Parkinson disease (PD) is characterized by motor deficits related to structural changes in the basal ganglia-thalamocortical circuits. However, it is still unclear the exact nature of the association between grey matter alterations and motor symptoms. Therefore, the aim of our investigation was to identify the subcortical modifications associated with motor symptoms of PD over time - adopting voxel-based morphometry (VBM) and automated volumetry methods. We selected fifty subjects with PD from the Parkinson’s Progression Markers Initiative (PPMI) database, who performed an MRI session at two time points: at baseline (i.e. at maximum 2 years after clinical diagnosis of PD) and after 48 months. Motor symptoms were assessed using the part III of the Unified Parkinson’s Disease Rating Scale at the two time points. Our VBM and volumetric analyses showed a general atrophy in all subcortical regions when comparing baseline with 48 months. These findings confirmed previous observations indicating a subcortical alteration over time in PD. Furthermore, our findings supported the idea that a reduced volume in the thalamus and an increased volume in pallidum may be related to the decline in motor skills. These structural modifications are in accordance with the functional model of the basal ganglia-thalamocortical circuits controlling movements. Moreover, VBM and volumetry provided partially overlapping results, suggesting that these methods might capture complementary aspects of brain degeneration in PD.
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Affiliation(s)
- Céline Charroud
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto (TN), Italy.
| | - Luca Turella
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto (TN), Italy
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13
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Sharma A, Vidaurre D, Vesper J, Schnitzler A, Florin E. Differential dopaminergic modulation of spontaneous cortico-subthalamic activity in Parkinson's disease. eLife 2021; 10:66057. [PMID: 34085932 PMCID: PMC8177893 DOI: 10.7554/elife.66057] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 05/12/2021] [Indexed: 11/20/2022] Open
Abstract
Pathological oscillations including elevated beta activity in the subthalamic nucleus (STN) and between STN and cortical areas are a hallmark of neural activity in Parkinson’s disease (PD). Oscillations also play an important role in normal physiological processes and serve distinct functional roles at different points in time. We characterised the effect of dopaminergic medication on oscillatory whole-brain networks in PD in a time-resolved manner by employing a hidden Markov model on combined STN local field potentials and magnetoencephalography (MEG) recordings from 17 PD patients. Dopaminergic medication led to coherence within the medial and orbitofrontal cortex in the delta/theta frequency range. This is in line with known side effects of dopamine treatment such as deteriorated executive functions in PD. In addition, dopamine caused the beta band activity to switch from an STN-mediated motor network to a frontoparietal-mediated one. In contrast, dopamine did not modify local STN–STN coherence in PD. STN–STN synchrony emerged both on and off medication. By providing electrophysiological evidence for the differential effects of dopaminergic medication on the discovered networks, our findings open further avenues for electrical and pharmacological interventions in PD.
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Affiliation(s)
- Abhinav Sharma
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Diego Vidaurre
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom.,Department of Clinical Health, Aarhus University, Aarhus, Denmark
| | - Jan Vesper
- Department of Neurosurgery, University Hospital Düsseldorf, Düsseldorf, Germany
| | - Alfons Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany.,Department of Neurology, Center for Movement Disorders and Neuromodulation, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Esther Florin
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
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14
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Min BK, Kim HS, Pinotsis DA, Pantazis D. Thalamocortical inhibitory dynamics support conscious perception. Neuroimage 2020; 220:117066. [PMID: 32565278 DOI: 10.1016/j.neuroimage.2020.117066] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 05/25/2020] [Accepted: 06/14/2020] [Indexed: 11/28/2022] Open
Abstract
Whether thalamocortical interactions play a decisive role in conscious perception remains an open question. We presented rapid red/green color flickering stimuli, which induced the mental perception of either an illusory orange color or non-fused red and green colors. Using magnetoencephalography, we observed 6-Hz thalamic activity associated with thalamocortical inhibitory coupling only during the conscious perception of the illusory orange color. This sustained thalamic disinhibition was temporally coupled with higher visual cortical activation during the conscious perception of the orange color, providing neurophysiological evidence of the role of thalamocortical synchronization in conscious awareness of mental representation. Bayesian model comparison consistently supported the thalamocortical model in conscious perception. Taken together, experimental and theoretical evidence established the thalamocortical inhibitory network as a gateway to conscious mental representations.
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Affiliation(s)
- Byoung-Kyong Min
- Department of Brain and Cognitive Engineering, Korea University, Seoul, 02841, Republic of Korea; McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
| | - Hyun Seok Kim
- Department of Brain and Cognitive Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Dimitris A Pinotsis
- Center for Mathematical Neuroscience and Psychology, Department of Psychology, City-University of London, London, EC1V 0HB, UK; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Dimitrios Pantazis
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
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15
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Khawaldeh S, Tinkhauser G, Shah SA, Peterman K, Debove I, Nguyen TAK, Nowacki A, Lachenmayer ML, Schuepbach M, Pollo C, Krack P, Woolrich M, Brown P. Subthalamic nucleus activity dynamics and limb movement prediction in Parkinson's disease. Brain 2020; 143:582-596. [PMID: 32040563 PMCID: PMC7009471 DOI: 10.1093/brain/awz417] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Revised: 10/21/2019] [Accepted: 11/19/2019] [Indexed: 02/01/2023] Open
Abstract
Whilst exaggerated bursts of beta frequency band oscillatory synchronization in the subthalamic nucleus have been associated with motor impairment in Parkinson's disease, a plausible mechanism linking the two phenomena has been lacking. Here we test the hypothesis that increased synchronization denoted by beta bursting might compromise information coding capacity in basal ganglia networks. To this end we recorded local field potential activity in the subthalamic nucleus of 18 patients with Parkinson's disease as they executed cued upper and lower limb movements. We used the accuracy of local field potential-based classification of the limb to be moved on each trial as an index of the information held by the system with respect to intended action. Machine learning using the naïve Bayes conditional probability model was used for classification. Local field potential dynamics allowed accurate prediction of intended movements well ahead of their execution, with an area under the receiver operator characteristic curve of 0.80 ± 0.04 before imperative cues when the demanded action was known ahead of time. The presence of bursts of local field potential activity in the alpha, and even more so, in the beta frequency band significantly compromised the prediction of the limb to be moved. We conclude that low frequency bursts, particularly those in the beta band, restrict the capacity of the basal ganglia system to encode physiologically relevant information about intended actions. The current findings are also important as they suggest that local subthalamic activity may potentially be decoded to enable effector selection, in addition to force control in restorative brain-machine interface applications.
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Affiliation(s)
- Saed Khawaldeh
- MRC Brain Network Dynamics Unit, University of Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, UK.,Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, UK
| | - Gerd Tinkhauser
- MRC Brain Network Dynamics Unit, University of Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, UK.,Department of Neurology, Bern University Hospital and University of Bern, Switzerland
| | - Syed Ahmar Shah
- MRC Brain Network Dynamics Unit, University of Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, UK.,Usher Institute of Population Health Sciences and Informatics, Edinburgh Medical School, The University of Edinburgh, Edinburgh, UK
| | - Katrin Peterman
- Department of Neurology, Bern University Hospital and University of Bern, Switzerland
| | - Ines Debove
- Department of Neurology, Bern University Hospital and University of Bern, Switzerland
| | - T A Khoa Nguyen
- Department of Neurosurgery, Bern University Hospital and University of Bern, Switzerland
| | - Andreas Nowacki
- Department of Neurosurgery, Bern University Hospital and University of Bern, Switzerland
| | - M Lenard Lachenmayer
- Department of Neurology, Bern University Hospital and University of Bern, Switzerland
| | - Michael Schuepbach
- Department of Neurology, Bern University Hospital and University of Bern, Switzerland
| | - Claudio Pollo
- Department of Neurosurgery, Bern University Hospital and University of Bern, Switzerland
| | - Paul Krack
- Department of Neurology, Bern University Hospital and University of Bern, Switzerland
| | - Mark Woolrich
- Nuffield Department of Clinical Neurosciences, University of Oxford, UK.,Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, UK
| | - Peter Brown
- MRC Brain Network Dynamics Unit, University of Oxford, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, UK
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16
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Yeh CH, Al-Fatly B, Kühn AA, Meidahl AC, Tinkhauser G, Tan H, Brown P. Waveform changes with the evolution of beta bursts in the human subthalamic nucleus. Clin Neurophysiol 2020; 131:2086-2099. [PMID: 32682236 DOI: 10.1016/j.clinph.2020.05.035] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2019] [Revised: 05/19/2020] [Accepted: 05/26/2020] [Indexed: 01/11/2023]
Abstract
OBJECTIVE Phasic bursts of beta band synchronisation have been linked to motor impairment in Parkinson's disease (PD). However, little is known about what terminates bursts. METHODS We used the Hilbert-Huang transform to investigate beta bursts in the local field potential recorded from the subthalamic nucleus in nine patients with PD on and off levodopa. RESULTS The sharpness of the beta waveform extrema fell as burst amplitude dropped. Conversely, an index of phase slips between waveform extrema, and the power of concurrent theta activity increased as burst amplitude fell. Theta activity was also increased on levodopa when beta bursts were attenuated. These phenomena were associated with reduction in coupling between beta phase and high gamma activity amplitude. We discuss how these findings may suggest that beta burst termination is associated with relative desynchronization of the beta drive, increase in competing theta activity and increased phase slips in the beta activity. CONCLUSIONS We characterise the dynamical nature of beta bursts, thereby permitting inferences about underlying activities and, in particular, about why bursts terminate. SIGNIFICANCE Understanding the dynamical nature of beta bursts may help point to interventions that can cause their termination and potentially treat motor impairment in PD.
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Affiliation(s)
- Chien-Hung Yeh
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, United Kingdom; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, United Kingdom; School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China.
| | - Bassam Al-Fatly
- Department of Neurology, Charitè-Universitätsmedizin Berlin, 10177 Berlin, Germany
| | - Andrea A Kühn
- Department of Neurology, Charitè-Universitätsmedizin Berlin, 10177 Berlin, Germany
| | - Anders C Meidahl
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, United Kingdom; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, United Kingdom
| | - Gerd Tinkhauser
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, United Kingdom; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, United Kingdom; Department of Neurology, Bern University Hospital and University of Bern, 3010 Bern, Switzerland
| | - Huiling Tan
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, United Kingdom; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, United Kingdom
| | - Peter Brown
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford OX1 3TH, United Kingdom; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, United Kingdom
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17
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Kahan J, Mancini L, Flandin G, White M, Papadaki A, Thornton J, Yousry T, Zrinzo L, Hariz M, Limousin P, Friston K, Foltynie T. Deep brain stimulation has state-dependent effects on motor connectivity in Parkinson's disease. Brain 2020; 142:2417-2431. [PMID: 31219504 DOI: 10.1093/brain/awz164] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Revised: 03/12/2019] [Accepted: 04/18/2019] [Indexed: 12/17/2022] Open
Abstract
Subthalamic nucleus deep brain stimulation is an effective treatment for advanced Parkinson's disease; however, its therapeutic mechanism is unclear. Previous modelling of functional MRI data has suggested that deep brain stimulation has modulatory effects on a number of basal ganglia pathways. This work uses an enhanced data collection protocol to collect rare functional MRI data in patients with subthalamic nucleus deep brain stimulation. Eleven patients with Parkinson's disease and subthalamic nucleus deep brain stimulation underwent functional MRI at rest and during a movement task; once with active deep brain stimulation, and once with deep brain stimulation switched off. Dynamic causal modelling and Bayesian model selection were first used to compare a series of plausible biophysical models of the cortico-basal ganglia circuit that could explain the functional MRI activity at rest in an attempt to reproduce and extend the findings from our previous work. General linear modelling of the movement task functional MRI data revealed deep brain stimulation-associated signal increases in the primary motor and cerebellar cortices. Given the significance of the cerebellum in voluntary movement, we then built a more complete model of the motor system by including cerebellar-basal ganglia interactions, and compared the modulatory effects deep brain stimulation had on different circuit components during the movement task and again using the resting state data. Consistent with previous results from our independent cohort, model comparison found that the rest data were best explained by deep brain stimulation-induced increased (effective) connectivity of the cortico-striatal, thalamo-cortical and direct pathway and reduced coupling of subthalamic nucleus afferent and efferent connections. No changes in cerebellar connectivity were identified at rest. In contrast, during the movement task, there was functional recruitment of subcortical-cerebellar pathways, which were additionally modulated by deep brain stimulation, as well as modulation of local (intrinsic) cortical and cerebellar circuits. This work provides in vivo evidence for the modulatory effects of subthalamic nucleus deep brain stimulation on effective connectivity within the cortico-basal ganglia loops at rest, as well as further modulations in the cortico-cerebellar motor system during voluntary movement. We propose that deep brain stimulation has both behaviour-independent effects on basal ganglia connectivity, as well as behaviour-dependent modulatory effects.
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Affiliation(s)
- Joshua Kahan
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Laura Mancini
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, WC1N 3BG, UK.,Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Guillaume Flandin
- The Wellcome Centre for Human Neuroimaging, UCL, London, WC1N 3AR, UK
| | - Mark White
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, WC1N 3BG, UK.,Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Anastasia Papadaki
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, WC1N 3BG, UK.,Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - John Thornton
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, WC1N 3BG, UK.,Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Tarek Yousry
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, WC1N 3BG, UK.,Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Ludvic Zrinzo
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Marwan Hariz
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Patricia Limousin
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Karl Friston
- The Wellcome Centre for Human Neuroimaging, UCL, London, WC1N 3AR, UK
| | - Tom Foltynie
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
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18
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Basal ganglia oscillations as biomarkers for targeting circuit dysfunction in Parkinson's disease. PROGRESS IN BRAIN RESEARCH 2020; 252:525-557. [PMID: 32247374 DOI: 10.1016/bs.pbr.2020.02.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Oscillations are a naturally occurring phenomenon in highly interconnected dynamical systems. However, it is thought that excessive synchronized oscillations in brain circuits can be detrimental for many brain functions by disrupting neuronal information processing. Because synchronized basal ganglia oscillations are a hallmark of Parkinson's disease (PD), it has been suggested that aberrant rhythmic activity associated with symptoms of the disease could be used as a physiological biomarker to guide pharmacological and electrical neuromodulatory interventions. We here briefly review the various manifestations of basal ganglia oscillations observed in human subjects and in animal models of PD. In this context, we also review the evidence supporting a pathophysiological role of different oscillations for the suppression of voluntary movements as well as for the induction of excessive motor activity. In light of these findings, it is discussed how oscillations could be used to guide a more precise targeting of dysfunctional circuits to obtain improved symptomatic treatment of PD.
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19
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Fleming JE, Dunn E, Lowery MM. Simulation of Closed-Loop Deep Brain Stimulation Control Schemes for Suppression of Pathological Beta Oscillations in Parkinson's Disease. Front Neurosci 2020; 14:166. [PMID: 32194372 PMCID: PMC7066305 DOI: 10.3389/fnins.2020.00166] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 02/14/2020] [Indexed: 11/17/2022] Open
Abstract
This study presents a computational model of closed-loop control of deep brain stimulation (DBS) for Parkinson's disease (PD) to investigate clinically viable control schemes for suppressing pathological beta-band activity. Closed-loop DBS for PD has shown promising results in preliminary clinical studies and offers the potential to achieve better control of patient symptoms and side effects with lower power consumption than conventional open-loop DBS. However, extensive testing of algorithms in patients is difficult. The model presented provides a means to explore a range of control algorithms in silico and optimize control parameters before preclinical testing. The model incorporates (i) the extracellular DBS electric field, (ii) antidromic and orthodromic activation of STN afferent fibers, (iii) the LFP detected at non-stimulating contacts on the DBS electrode and (iv) temporal variation of network beta-band activity within the thalamo-cortico-basal ganglia loop. The performance of on-off and dual-threshold controllers for suppressing beta-band activity by modulating the DBS amplitude were first verified, showing levels of beta suppression and reductions in power consumption comparable with previous clinical studies. Proportional (P) and proportional-integral (PI) closed-loop controllers for amplitude and frequency modulation were then investigated. A simple tuning rule was derived for selecting effective PI controller parameters to target long duration beta bursts while respecting clinical constraints that limit the rate of change of stimulation parameters. Of the controllers tested, PI controllers displayed superior performance for regulating network beta-band activity whilst accounting for clinical considerations. Proportional controllers resulted in undesirable rapid fluctuations of the DBS parameters which may exceed clinically tolerable rate limits. Overall, the PI controller for modulating DBS frequency performed best, reducing the mean error by 83% compared to DBS off and the mean power consumed to 25% of that utilized by open-loop DBS. The network model presented captures sufficient physiological detail to act as a surrogate for preclinical testing of closed-loop DBS algorithms using a clinically accessible biomarker, providing a first step for deriving and testing novel, clinically suitable closed-loop DBS controllers.
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Affiliation(s)
- John E. Fleming
- Neuromuscular Systems Laboratory, UCD School of Electrical & Electronic Engineering, University College Dublin, Dublin, Ireland
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20
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Halje P, Brys I, Mariman JJ, da Cunha C, Fuentes R, Petersson P. Oscillations in cortico-basal ganglia circuits: implications for Parkinson’s disease and other neurologic and psychiatric conditions. J Neurophysiol 2019; 122:203-231. [DOI: 10.1152/jn.00590.2018] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Cortico-basal ganglia circuits are thought to play a crucial role in the selection and control of motor behaviors and have also been implicated in the processing of motivational content and in higher cognitive functions. During the last two decades, electrophysiological recordings in basal ganglia circuits have shown that several disease conditions are associated with specific changes in the temporal patterns of neuronal activity. In particular, synchronized oscillations have been a frequent finding suggesting that excessive synchronization of neuronal activity may be a pathophysiological mechanism involved in a wide range of neurologic and psychiatric conditions. We here review the experimental support for this hypothesis primarily in relation to Parkinson’s disease but also in relation to dystonia, essential tremor, epilepsy, and psychosis/schizophrenia.
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Affiliation(s)
- Pär Halje
- Group for Integrative Neurophysiology and Neurotechnology, Department of Experimental Medical Science, Lund University, Lund, Sweden
| | - Ivani Brys
- Federal University of Vale do São Francisco, Petrolina, Brazil
| | - Juan J. Mariman
- Research and Development Direction, Universidad Tecnológica de Chile, Inacap, Santiago, Chile
- Department of Physical Therapy, Faculty of Medicine, Universidad de Chile, Santiago, Chile
- Department of Physical Therapy, Faculty of Arts and Physical Education, Universidad Metropolitana de Ciencias de la Educación, Santiago, Chile
| | - Claudio da Cunha
- Laboratório de Fisiologia e Farmacologia do Sistema Nervoso Central, Programas de Pós-Graduação em Farmacologia e Bioquímica, Universidade Federal do Paraná, Curitiba, Brazil
| | - Romulo Fuentes
- Department of Neurocience, Faculty of Medicine, Universidad de Chile, Santiago, Chile
| | - Per Petersson
- Group for Integrative Neurophysiology and Neurotechnology, Department of Experimental Medical Science, Lund University, Lund, Sweden
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
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21
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Reis C, Sharott A, Magill PJ, van Wijk BCM, Parr T, Zeidman P, Friston KJ, Cagnan H. Thalamocortical dynamics underlying spontaneous transitions in beta power in Parkinsonism. Neuroimage 2019; 193:103-114. [PMID: 30862535 PMCID: PMC6503152 DOI: 10.1016/j.neuroimage.2019.03.009] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Revised: 02/01/2019] [Accepted: 03/05/2019] [Indexed: 01/03/2023] Open
Abstract
Parkinson's disease (PD) is a neurodegenerative condition in which aberrant oscillatory synchronization of neuronal activity at beta frequencies (15–35 Hz) across the cortico-basal ganglia-thalamocortical circuit is associated with debilitating motor symptoms, such as bradykinesia and rigidity. Mounting evidence suggests that the magnitude of beta synchrony in the parkinsonian state fluctuates over time, but the mechanisms by which thalamocortical circuitry regulates the dynamic properties of cortical beta in PD are poorly understood. Using the recently developed generic Dynamic Causal Modelling (DCM) framework, we recursively optimized a set of plausible models of the thalamocortical circuit (n = 144) to infer the neural mechanisms that best explain the transitions between low and high beta power states observed in recordings of field potentials made in the motor cortex of anesthetized Parkinsonian rats. Bayesian model comparison suggests that upregulation of cortical rhythmic activity in the beta-frequency band results from changes in the coupling strength both between and within the thalamus and motor cortex. Specifically, our model indicates that high levels of cortical beta synchrony are mainly achieved by a delayed (extrinsic) input from thalamic relay cells to deep pyramidal cells and a fast (intrinsic) input from middle pyramidal cells to superficial pyramidal cells. From a clinical perspective, our study provides insights into potential therapeutic strategies that could be utilized to modulate the network mechanisms responsible for the enhancement of cortical beta in PD. Specifically, we speculate that cortical stimulation aimed to reduce the enhanced excitatory inputs to either the superficial or deep pyramidal cells could be a potential non-invasive therapeutic strategy for PD. Coupling changes within and between circuit nodes lead to cortical beta enhancement. Input propagation delays play a crucial role in the up-regulation of cortical beta. Beta power could be modulated by altering lamina specific inputs.
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Affiliation(s)
- Carolina Reis
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Andrew Sharott
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, UK
| | - Peter J Magill
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, UK; Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
| | - Bernadette C M van Wijk
- Wellcome Centre for Human Neuroimaging, University College London, UK; Integrative Model-based Cognitive Neuroscience Research Unit, Department of Psychology, University of Amsterdam, the Netherlands
| | - Thomas Parr
- Wellcome Centre for Human Neuroimaging, University College London, UK
| | - Peter Zeidman
- Wellcome Centre for Human Neuroimaging, University College London, UK
| | - Karl J Friston
- Wellcome Centre for Human Neuroimaging, University College London, UK
| | - Hayriye Cagnan
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK.
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22
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Malekmohammadi M, Shahriari Y, AuYong N, O’Keeffe A, Bordelon Y, Hu X, Pouratian N. Pallidal stimulation in Parkinson disease differentially modulates local and network β activity. J Neural Eng 2018; 15:056016. [PMID: 29972146 PMCID: PMC6125208 DOI: 10.1088/1741-2552/aad0fb] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
β hypersynchrony within the basal ganglia-thalamocortical (BGTC) network has been suggested as a hallmark of Parkinson disease (PD) pathophysiology. Subthalamic nucleus (STN)-DBS has been shown to alter cortical-subcortical synchronization. It is unclear whether this is a generalizable phenomenon of therapeutic stimulation across targets. OBJECTIVES We aimed to evaluate whether DBS of the globus pallidus internus (GPi) results in cortical-subcortical desynchronization, despite the lack of monosynaptic connections between GPi and sensorimotor cortex. APPROACH We recorded local field potentials from the GPi and electrocorticographic signals from the ipsilateral sensorimotor cortex, off medications in nine PD patients, undergoing DBS implantation. We analyzed both local oscillatory power and functional connectivity (coherence and debiased weighted phase lag index (dWPLI)) with and without stimulation while subjects were resting with eyes open. MAIN RESULTS DBS significantly suppressed low β power within the GPi (-26.98% ± 15.14%), p < 0.05) without modulation of sensorimotor cortical β power (low or high). In contrast, stimulation suppressed pallidocortical high β coherence (-38.89% ± 6.19%, p = 0.02) and dWPLI (-61.40% ± 8.75%, p = 0.02). Changes in cortical-subcortical functional connectivity were spatially specific to the motor cortex. SIGNIFICANCE We highlight the role of DBS in desynchronizing network activity, particularly in the high β band. The current study of GPi-DBS suggests these network-level effects are not necessarily dependent and potentially may be independent of the hyperdirect pathway. Importantly, these results draw a sharp distinction between the potential significance of low β oscillations locally within the basal ganglia and high β oscillations across the BGTC motor circuit.
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Affiliation(s)
| | - Yalda Shahriari
- Department of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, RI, USA
- Department of Physiological Nursing, University of California, San Francisco, CA, USA
| | - Nicholas AuYong
- Department of Neurosurgery, University of California, Los Angeles, CA, USA
| | - Andrew O’Keeffe
- Department of Neurosurgery, University of California, Los Angeles, CA, USA
| | - Yvette Bordelon
- Department of Neurology, University of California, Los Angeles, CA, USA
| | - Xiao Hu
- Department of Physiological Nursing, University of California, San Francisco, CA, USA
| | - Nader Pouratian
- Department of Neurosurgery, University of California, Los Angeles, CA, USA
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23
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Generic dynamic causal modelling: An illustrative application to Parkinson's disease. Neuroimage 2018; 181:818-830. [PMID: 30130648 PMCID: PMC7343527 DOI: 10.1016/j.neuroimage.2018.08.039] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2018] [Revised: 08/15/2018] [Accepted: 08/16/2018] [Indexed: 12/26/2022] Open
Abstract
We present a technical development in the dynamic causal modelling of
electrophysiological responses that combines qualitatively different neural mass
models within a single network. This affords the option to couple various
cortical and subcortical nodes that differ in their form and dynamics. Moreover,
it enables users to implement new neural mass models in a straightforward and
standardized way. This generic framework hence supports flexibility and
facilitates the exploration of increasingly plausible models. We illustrate this
by coupling a basal ganglia-thalamus model to a (previously validated) cortical
model developed specifically for motor cortex. The ensuing DCM is used to infer
pathways that contribute to the suppression of beta oscillations induced by
dopaminergic medication in patients with Parkinson's disease.
Experimental recordings were obtained from deep brain stimulation electrodes
(implanted in the subthalamic nucleus) and simultaneous magnetoencephalography.
In line with previous studies, our results indicate a reduction of synaptic
efficacy within the circuit between the subthalamic nucleus and external
pallidum, as well as reduced efficacy in connections of the hyperdirect and
indirect pathway leading to this circuit. This work forms the foundation for a
range of modelling studies of the synaptic mechanisms (and pathophysiology)
underlying event-related potentials and cross-spectral densities.
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Pallidal deep brain stimulation modulates excessive cortical high β phase amplitude coupling in Parkinson disease. Brain Stimul 2018; 11:607-617. [PMID: 29422442 DOI: 10.1016/j.brs.2018.01.028] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2017] [Revised: 01/16/2018] [Accepted: 01/19/2018] [Indexed: 11/22/2022] Open
Abstract
OBJECTIVE Deep brain stimulation (DBS) of the subthalamic nucleus (STN) and globus pallidus internus (GPi) are equally efficacious in the management of Parkinson disease (PD). Studies of STN-DBS have revealed a therapeutic reduction in excessive cortical β-γ phase-amplitude coupling (PAC). It is unclear whether this is specific to STN-DBS and potentially mediated by modulation of the hyperdirect pathway or if it is a generalizable mechanism seen with DBS of other targets. Moreover, it remains unclear how cortical signals are differentially modulated by movement versus therapy. To clarify, the effects of GPi-DBS and movement on cortical β power and β-γ PAC were examined. METHODS Right sensorimotor electrocorticographic signals were recorded in 10 PD patients undergoing GPi-DBS implantation surgery. We evaluated cortical β power and β-γ PAC during blocks of rest and contralateral hand movement (finger tapping) with GPi-DBS off and on. RESULTS Movement suppressed cortical low β power (P = 0.008) and high β-γ PAC (P = 0.028). Linear mixed effect modeling (LMEM) showed that power in low and high β bands are differentially modulated by movement (P = 0.022). GPi-DBS also results in a significant suppression of high β-γ PAC but without power modulation in either β sub-band (P = 0.008). Cortical high β-γ PAC is significantly correlated with severity of bradykinesia (Rho = 0.59, P = 0.045) and changes proportionally with therapeutic improvement (Rho = 0.61, P = 0.04). CONCLUSIONS Similar to STN-DBS, GPi-DBS reduces motor cortical β-γ PAC, like that also reported with dopaminergic mediations, suggesting it is a generalizable symptom biomarker in PD, independent of therapeutic target or proximity to the hyperdirect pathway.
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Frässle S, Yao Y, Schöbi D, Aponte EA, Heinzle J, Stephan KE. Generative models for clinical applications in computational psychiatry. WILEY INTERDISCIPLINARY REVIEWS. COGNITIVE SCIENCE 2018; 9:e1460. [PMID: 29369526 DOI: 10.1002/wcs.1460] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2017] [Revised: 10/19/2017] [Accepted: 11/06/2017] [Indexed: 12/18/2022]
Abstract
Despite the success of modern neuroimaging techniques in furthering our understanding of cognitive and pathophysiological processes, translation of these advances into clinically relevant tools has been virtually absent until now. Neuromodeling represents a powerful framework for overcoming this translational deadlock, and the development of computational models to solve clinical problems has become a major scientific goal over the last decade, as reflected by the emergence of clinically oriented neuromodeling fields like Computational Psychiatry, Computational Neurology, and Computational Psychosomatics. Generative models of brain physiology and connectivity in the human brain play a key role in this endeavor, striving for computational assays that can be applied to neuroimaging data from individual patients for differential diagnosis and treatment prediction. In this review, we focus on dynamic causal modeling (DCM) and its use for Computational Psychiatry. DCM is a widely used generative modeling framework for functional magnetic resonance imaging (fMRI) and magneto-/electroencephalography (M/EEG) data. This article reviews the basic concepts of DCM, revisits examples where it has proven valuable for addressing clinically relevant questions, and critically discusses methodological challenges and recent methodological advances. We conclude this review with a more general discussion of the promises and pitfalls of generative models in Computational Psychiatry and highlight the path that lies ahead of us. This article is categorized under: Neuroscience > Computation Neuroscience > Clinical Neuroscience.
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Affiliation(s)
- Stefan Frässle
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Zurich, Switzerland
| | - Yu Yao
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Zurich, Switzerland
| | - Dario Schöbi
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Zurich, Switzerland
| | - Eduardo A Aponte
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Zurich, Switzerland
| | - Jakob Heinzle
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Zurich, Switzerland
| | - Klaas E Stephan
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Zurich, Switzerland.,Wellcome Trust Centre for Neuroimaging, University College London, London, UK
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26
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West TO, Berthouze L, Halliday DM, Litvak V, Sharott A, Magill PJ, Farmer SF. Propagation of beta/gamma rhythms in the cortico-basal ganglia circuits of the parkinsonian rat. J Neurophysiol 2018; 119:1608-1628. [PMID: 29357448 PMCID: PMC6008089 DOI: 10.1152/jn.00629.2017] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Much of the motor impairment associated with Parkinson’s disease is thought to arise from pathological activity in the networks formed by the basal ganglia (BG) and motor cortex. To evaluate several hypotheses proposed to explain the emergence of pathological oscillations in parkinsonism, we investigated changes to the directed connectivity in BG networks following dopamine depletion. We recorded local field potentials (LFPs) in the cortex and basal ganglia of rats rendered parkinsonian by injection of 6-hydroxydopamine (6-OHDA) and in dopamine-intact controls. We performed systematic analyses of the networks using a novel tool for estimation of directed interactions (nonparametric directionality, NPD). We used a “conditioned” version of the NPD analysis that reveals the dependence of the correlation between two signals on a third reference signal. We find evidence of the dopamine dependency of both low-beta (14–20 Hz) and high-beta/low-gamma (20–40 Hz) directed network interactions. Notably, 6-OHDA lesions were associated with enhancement of the cortical “hyperdirect” connection to the subthalamic nucleus (STN) and its feedback to the cortex and striatum. We find that pathological beta synchronization resulting from 6-OHDA lesioning is widely distributed across the network and cannot be located to any individual structure. Furthermore, we provide evidence that high-beta/gamma oscillations propagate through the striatum in a pathway that is independent of STN. Rhythms at high beta/gamma show susceptibility to conditioning that indicates a hierarchical organization compared with those at low beta. These results further inform our understanding of the substrates for pathological rhythms in salient brain networks in parkinsonism. NEW & NOTEWORTHY We present a novel analysis of electrophysiological recordings in the cortico-basal ganglia network with the aim of evaluating several hypotheses concerning the origins of abnormal brain rhythms associated with Parkinson’s disease. We present evidence for changes in the directed connections within the network following chronic dopamine depletion in rodents. These findings speak to the plausibility of a “short-circuiting” of the network that gives rise to the conditions from which pathological synchronization may arise.
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Affiliation(s)
- Timothy O West
- Centre for Mathematics and Physics in the Life Sciences and Experimental Biology (CoMPLEX), Department of Physics and Astronomy, University College London , London , United Kingdom.,Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London , London , United Kingdom
| | - Luc Berthouze
- Centre for Computational Neuroscience and Robotics, University of Sussex , Falmer , United Kingdom.,UCL Great Ormond Street Institute of Child Health , London , United Kingdom
| | - David M Halliday
- Department of Electronic Engineering, University of York , York , United Kingdom
| | - Vladimir Litvak
- Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London , London , United Kingdom
| | - Andrew Sharott
- Medical Research Council Brain Network Dynamics Unit, University of Oxford , Oxford , United Kingdom
| | - Peter J Magill
- Medical Research Council Brain Network Dynamics Unit, University of Oxford , Oxford , United Kingdom.,Oxford Parkinson's Disease Centre, University of Oxford , Oxford , United Kingdom
| | - Simon F Farmer
- Department of Neurology, National Hospital for Neurology & Neurosurgery , London , United Kingdom.,Sobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, University College London , London , United Kingdom
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Blesa J, Trigo-Damas I, Dileone M, Del Rey NLG, Hernandez LF, Obeso JA. Compensatory mechanisms in Parkinson's disease: Circuits adaptations and role in disease modification. Exp Neurol 2017; 298:148-161. [PMID: 28987461 DOI: 10.1016/j.expneurol.2017.10.002] [Citation(s) in RCA: 151] [Impact Index Per Article: 21.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2017] [Revised: 09/27/2017] [Accepted: 10/03/2017] [Indexed: 12/21/2022]
Abstract
The motor features of Parkinson's disease (PD) are well known to manifest only when striatal dopaminergic deficit reaches 60-70%. Thus, PD has a long pre-symptomatic and pre-motor evolution during which compensatory mechanisms take place to delay the clinical onset of disabling manifestations. Classic compensatory mechanisms have been attributed to changes and adjustments in the nigro-striatal system, such as increased neuronal activity in the substantia nigra pars compacta and enhanced dopamine synthesis and release in the striatum. However, it is not so clear currently that such changes occur early enough to account for the pre-symptomatic period. Other possible mechanisms relate to changes in basal ganglia and motor cortical circuits including the cerebellum. However, data from early PD patients are difficult to obtain as most studies have been carried out once the diagnosis and treatments have been established. Likewise, putative compensatory mechanisms taking place throughout disease evolution are nearly impossible to distinguish by themselves. Here, we review the evidence for the role of the best known and other possible compensatory mechanisms in PD. We also discuss the possibility that, although beneficial in practical terms, compensation could also play a deleterious role in disease progression.
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Affiliation(s)
- Javier Blesa
- HM CINAC, Hospital Universitario HM Puerta del Sur, Móstoles, Madrid, Spain; Biomedical Research Center of Neurodegenerative Diseases (CIBERNED), Instituto Carlos III, Madrid, Spain.
| | - Inés Trigo-Damas
- HM CINAC, Hospital Universitario HM Puerta del Sur, Móstoles, Madrid, Spain; Biomedical Research Center of Neurodegenerative Diseases (CIBERNED), Instituto Carlos III, Madrid, Spain
| | - Michele Dileone
- HM CINAC, Hospital Universitario HM Puerta del Sur, Móstoles, Madrid, Spain; Biomedical Research Center of Neurodegenerative Diseases (CIBERNED), Instituto Carlos III, Madrid, Spain
| | - Natalia Lopez-Gonzalez Del Rey
- HM CINAC, Hospital Universitario HM Puerta del Sur, Móstoles, Madrid, Spain; Biomedical Research Center of Neurodegenerative Diseases (CIBERNED), Instituto Carlos III, Madrid, Spain
| | - Ledia F Hernandez
- HM CINAC, Hospital Universitario HM Puerta del Sur, Móstoles, Madrid, Spain; Biomedical Research Center of Neurodegenerative Diseases (CIBERNED), Instituto Carlos III, Madrid, Spain
| | - José A Obeso
- HM CINAC, Hospital Universitario HM Puerta del Sur, Móstoles, Madrid, Spain; Biomedical Research Center of Neurodegenerative Diseases (CIBERNED), Instituto Carlos III, Madrid, Spain.
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Rubin JE. Computational models of basal ganglia dysfunction: the dynamics is in the details. Curr Opin Neurobiol 2017; 46:127-135. [PMID: 28888856 DOI: 10.1016/j.conb.2017.08.011] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2017] [Accepted: 08/22/2017] [Indexed: 12/18/2022]
Abstract
The development, simulation, and analysis of mathematical models offer helpful tools for integrating experimental findings and exploring or suggesting possible explanatory mechanisms. As models relating to basal ganglia dysfunction have proliferated, however, there has not always been consistency among their findings. This work points out several ways in which biological details, relating to ionic currents and synaptic pathways, can influence the dynamics of models of the basal ganglia under parkinsonian conditions and hence may be important for inclusion in models. It also suggests some additional useful directions for future modeling studies relating to basal ganglia dysfunction.
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Affiliation(s)
- Jonathan E Rubin
- Department of Mathematics and Center for the Neural Basis of Cognition, University of Pittsburgh, 301 Thackeray Hall, Pittsburgh, PA 15260, USA.
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29
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Pallidal low β-low γ phase-amplitude coupling inversely correlates with Parkinson disease symptoms. Clin Neurophysiol 2017; 128:2165-2178. [PMID: 28942154 DOI: 10.1016/j.clinph.2017.08.001] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2017] [Revised: 07/08/2017] [Accepted: 08/12/2017] [Indexed: 01/23/2023]
Abstract
OBJECTIVE Recent discoveries suggest that it is most likely the coupling of β oscillations (13-30Hz) and not merely their power that relates to Parkinson disease (PD) pathophysiology. METHODS We analyzed power and phase amplitude coupling (PAC) in local field potentials (LFP) recorded from Pallidum after placement of deep brain stimulation (DBS) leads in nineteen PD patients and three patients with dystonia. RESULTS Within GPi, we identified PAC between phase of β and amplitude of high frequency oscillations (200-300Hz) and distinct β-low γ (40-80Hz) PAC both modulated by contralateral movement. Resting β-low γ PAC, also present in dystonia patients, inversely correlated with severity of rigidity and bradykinesia (R=-0.44, P=0.028). These findings were specific to the low β band, suggesting a differential role for the two β sub-bands. CONCLUSIONS PAC is present across distinct frequency bands within the GPi. Given the presence of low β-low γ PAC in dystonia and the inverse correlation with symptom severity, we propose that this PAC may be a normal pallidal signal. SIGNIFICANCE This study provides new evidence on the pathophysiological contribution of local pallidal coupling and suggests similar and distinct patterns of coupling within GPi and STN in PD.
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30
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The Cerebral Network of Parkinson's Tremor: An Effective Connectivity fMRI Study. J Neurosci 2017; 36:5362-72. [PMID: 27170132 DOI: 10.1523/jneurosci.3634-15.2016] [Citation(s) in RCA: 88] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2015] [Accepted: 04/07/2016] [Indexed: 01/11/2023] Open
Abstract
UNLABELLED Parkinson's resting tremor has been linked to pathophysiological changes both in the basal ganglia and in a cerebello-thalamo-cortical motor loop, but the role of those circuits in initiating and maintaining tremor remains unclear. Here, we test whether and how the cerebello-thalamo-cortical loop is driven into a tremor-related state by virtue of its connectivity with the basal ganglia. An internal replication design on two independent cohorts of tremor-dominant Parkinson patients sampled brain activity and tremor with concurrent EMG-fMRI. Using dynamic causal modeling, we tested: (1) whether activity at the onset of tremor episodes drives tremulous network activity through the basal ganglia or the cerebello-thalamo-cortical loop and (2) whether the basal ganglia influence the cerebello-thalamo-cortical loop through connectivity with the cerebellum or motor cortex. We compared five physiologically plausible circuits, model families in which transient activity at the onset of tremor episodes (assessed using EMG) drove network activity through the internal globus pallidus (GPi), external globus pallidus, motor cortex, thalamus, or cerebellum. In each family, we compared two models in which the basal ganglia and cerebello-thalamo-cortical loop were connected through the cerebellum or motor cortex. In both cohorts, cerebral activity associated with changes in tremor amplitude (using peripheral EMG measures as a proxy for tremor-related neuronal activity) drove network activity through the GPi, which effectively influenced the cerebello-thalamo-cortical loop through the motor cortex. We conclude that cerebral activity related to Parkinson's tremor first arises in the GPi and is then propagated to the cerebello-thalamo-cortical circuit. SIGNIFICANCE STATEMENT Parkinson's resting tremor has been linked to pathophysiological changes both in the basal ganglia and in a cerebello-thalamo-cortical motor loop, but the role of those circuits in initiating and maintaining tremor remains unclear. Using dynamic causal modeling of concurrently collected EMG-fMRI data in two cohorts of Parkinson's patients, we showed that cerebral activity associated with changes in tremor amplitude drives network activity through the basal ganglia. Furthermore, the basal ganglia effectively influenced the cerebello-thalamo-cortical circuit through the motor cortex (but not the cerebellum). Out findings suggest that Parkinson's tremor-related activity first arises in the basal ganglia and is then propagated to the cerebello-thalamo-cortical circuit.
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31
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Blenkinsop A, Anderson S, Gurney K. Frequency and function in the basal ganglia: the origins of beta and gamma band activity. J Physiol 2017; 595:4525-4548. [PMID: 28334424 DOI: 10.1113/jp273760] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2016] [Accepted: 03/02/2017] [Indexed: 01/28/2023] Open
Abstract
KEY POINTS Neuronal oscillations in the basal ganglia have been observed to correlate with behaviours, although the causal mechanisms and functional significance of these oscillations remain unknown. We present a novel computational model of the healthy basal ganglia, constrained by single unit recordings from non-human primates. When the model is run using inputs that might be expected during performance of a motor task, the network shows emergent phenomena: it functions as a selection mechanism and shows spectral properties that match those seen in vivo. Beta frequency oscillations are shown to require pallido-striatal feedback, and occur with behaviourally relevant cortical input. Gamma oscillations arise in the subthalamic-globus pallidus feedback loop, and occur during movement. The model provides a coherent framework for the study of spectral, temporal and functional analyses of the basal ganglia and lays the foundation for an integrated approach to study basal ganglia pathologies such as Parkinson's disease in silico. ABSTRACT Neural oscillations in the basal ganglia (BG) are well studied yet remain poorly understood. Behavioural correlates of spectral activity are well described, yet a quantitative hypothesis linking time domain dynamics and spectral properties to BG function has been lacking. We show, for the first time, that a unified description is possible by interpreting previously ignored structure in data describing globus pallidus interna responses to cortical stimulation. These data were used to expose a pair of distinctive neuronal responses to the stimulation. This observation formed the basis for a new mathematical model of the BG, quantitatively fitted to the data, which describes the dynamics in the data, and is validated against other stimulus protocol experiments. A key new result is that when the model is run using inputs hypothesised to occur during the performance of a motor task, beta and gamma frequency oscillations emerge naturally during static-force and movement, respectively, consistent with experimental local field potentials. This new model predicts that the pallido-striatum connection has a key role in the generation of beta band activity, and that the gamma band activity associated with motor task performance has its origins in the pallido-subthalamic feedback loop. The network's functionality as a selection mechanism also occurs as an emergent property, and closer fits to the data gave better selection properties. The model provides a coherent framework for the study of spectral, temporal and functional analyses of the BG and therefore lays the foundation for an integrated approach to study BG pathologies such as Parkinson's disease in silico.
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Affiliation(s)
| | - Sean Anderson
- Automatic Control & Systems Engineering, University of Sheffield, Sheffield, S1 3JD, UK
| | - Kevin Gurney
- Department of Psychology, University of Sheffield, Sheffield, S10 2TP, UK
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32
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Dirkx MF, den Ouden HEM, Aarts E, Timmer MHM, Bloem BR, Toni I, Helmich RC. Dopamine controls Parkinson's tremor by inhibiting the cerebellar thalamus. Brain 2017; 140:721-734. [PMID: 28073788 DOI: 10.1093/brain/aww331] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2016] [Accepted: 11/14/2016] [Indexed: 11/14/2022] Open
Abstract
Parkinson's resting tremor is related to altered cerebral activity in the basal ganglia and the cerebello-thalamo-cortical circuit. Although Parkinson's disease is characterized by dopamine depletion in the basal ganglia, the dopaminergic basis of resting tremor remains unclear: dopaminergic medication reduces tremor in some patients, but many patients have a dopamine-resistant tremor. Using pharmacological functional magnetic resonance imaging, we test how a dopaminergic intervention influences the cerebral circuit involved in Parkinson's tremor. From a sample of 40 patients with Parkinson's disease, we selected 15 patients with a clearly tremor-dominant phenotype. We compared tremor-related activity and effective connectivity (using combined electromyography-functional magnetic resonance imaging) on two occasions: ON and OFF dopaminergic medication. Building on a recently developed cerebral model of Parkinson's tremor, we tested the effect of dopamine on cerebral activity associated with the onset of tremor episodes (in the basal ganglia) and with tremor amplitude (in the cerebello-thalamo-cortical circuit). Dopaminergic medication reduced clinical resting tremor scores (mean 28%, range -12 to 68%). Furthermore, dopaminergic medication reduced tremor onset-related activity in the globus pallidus and tremor amplitude-related activity in the thalamic ventral intermediate nucleus. Network analyses using dynamic causal modelling showed that dopamine directly increased self-inhibition of the ventral intermediate nucleus, rather than indirectly influencing the cerebello-thalamo-cortical circuit through the basal ganglia. Crucially, the magnitude of thalamic self-inhibition predicted the clinical dopamine response of tremor. Dopamine reduces resting tremor by potentiating inhibitory mechanisms in a cerebellar nucleus of the thalamus (ventral intermediate nucleus). This suggests that altered dopaminergic projections to the cerebello-thalamo-cortical circuit have a role in Parkinson's tremor.aww331media15307619934001.
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Affiliation(s)
- Michiel F Dirkx
- Donders Institute for Brain, Cognition and Behavior, Radboud University, 6500 HB Nijmegen, The Netherlands.,Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology and Parkinson Centre Nijmegen (ParC), 6500 HB Nijmegen, The Netherlands
| | - Hanneke E M den Ouden
- Donders Institute for Brain, Cognition and Behavior, Radboud University, 6500 HB Nijmegen, The Netherlands
| | - Esther Aarts
- Donders Institute for Brain, Cognition and Behavior, Radboud University, 6500 HB Nijmegen, The Netherlands
| | - Monique H M Timmer
- Donders Institute for Brain, Cognition and Behavior, Radboud University, 6500 HB Nijmegen, The Netherlands.,Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology and Parkinson Centre Nijmegen (ParC), 6500 HB Nijmegen, The Netherlands
| | - Bastiaan R Bloem
- Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology and Parkinson Centre Nijmegen (ParC), 6500 HB Nijmegen, The Netherlands
| | - Ivan Toni
- Donders Institute for Brain, Cognition and Behavior, Radboud University, 6500 HB Nijmegen, The Netherlands
| | - Rick C Helmich
- Donders Institute for Brain, Cognition and Behavior, Radboud University, 6500 HB Nijmegen, The Netherlands.,Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology and Parkinson Centre Nijmegen (ParC), 6500 HB Nijmegen, The Netherlands
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33
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Liu C, Zhu Y, Liu F, Wang J, Li H, Deng B, Fietkiewicz C, Loparo KA. Neural mass models describing possible origin of the excessive beta oscillations correlated with Parkinsonian state. Neural Netw 2017; 88:65-73. [PMID: 28192762 DOI: 10.1016/j.neunet.2017.01.011] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2016] [Revised: 11/18/2016] [Accepted: 01/24/2017] [Indexed: 10/20/2022]
Abstract
In Parkinson's disease, the enhanced beta rhythm is closely associated with akinesia/bradykinesia and rigidity. An increase in beta oscillations (12-35 Hz) within the basal ganglia (BG) nuclei does not proliferate throughout the cortico-basal ganglia loop in uniform fashion; rather it can be subdivided into two distinct frequency bands, i.e. the lower beta (12-20 Hz) and upper beta (21-35 Hz). A computational model of the excitatory and inhibitory neural network that focuses on the population properties is proposed to explore the mechanism underlying the pathological beta oscillations. Simulation results show several findings. The upper beta frequency in the BG originates from a high frequency cortical beta, while the emergence of exaggerated lower beta frequency in the BG depends greatly on the enhanced excitation of a reciprocal network consisting of the globus pallidus externus (GPe) and the subthalamic nucleus (STN). There is also a transition mechanism between the upper and lower beta oscillatory activities, and we explore the impact of self-inhibition within the GPe on the relationship between the upper beta and lower beta oscillations. It is shown that increased self-inhibition within the GPe contributes to increased upper beta oscillations driven by the cortical rhythm, while decrease in the self-inhibition within the GPe facilitates an enhancement of the lower beta oscillations induced by the increased excitability of the BG. This work provides an analysis for understanding the mechanism underlying pathological synchronization in neurological diseases.
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Affiliation(s)
- Chen Liu
- School of Electrical Engineering and Automation, Tianjin University, 300072, Tianjin, China; Department of Electrical Engineering and Computer Science, Case Western Reserve University, 44106, Cleveland, OH, USA
| | - Yulin Zhu
- School of Electrical Engineering and Automation, Tianjin University, 300072, Tianjin, China
| | - Fei Liu
- School of Electrical Engineering and Automation, Tianjin University, 300072, Tianjin, China
| | - Jiang Wang
- School of Electrical Engineering and Automation, Tianjin University, 300072, Tianjin, China
| | - Huiyan Li
- School of Automation and Electrical Engineering, Tianjin University of Technology and Educations, 300222, Tianjin, China
| | - Bin Deng
- School of Electrical Engineering and Automation, Tianjin University, 300072, Tianjin, China.
| | - Chris Fietkiewicz
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, 44106, Cleveland, OH, USA
| | - Kenneth A Loparo
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, 44106, Cleveland, OH, USA
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Liu F, Wang J, Liu C, Li H, Deng B, Fietkiewicz C, Loparo KA. A neural mass model of basal ganglia nuclei simulates pathological beta rhythm in Parkinson's disease. CHAOS (WOODBURY, N.Y.) 2016; 26:123113. [PMID: 28039987 DOI: 10.1063/1.4972200] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
An increase in beta oscillations within the basal ganglia nuclei has been shown to be associated with movement disorder, such as Parkinson's disease. The motor cortex and an excitatory-inhibitory neuronal network composed of the subthalamic nucleus (STN) and the external globus pallidus (GPe) are thought to play an important role in the generation of these oscillations. In this paper, we propose a neuron mass model of the basal ganglia on the population level that reproduces the Parkinsonian oscillations in a reciprocal excitatory-inhibitory network. Moreover, it is shown that the generation and frequency of these pathological beta oscillations are varied by the coupling strength and the intrinsic characteristics of the basal ganglia. Simulation results reveal that increase of the coupling strength induces the generation of the beta oscillation, as well as enhances the oscillation frequency. However, for the intrinsic properties of each nucleus in the excitatory-inhibitory network, the STN primarily influences the generation of the beta oscillation while the GPe mainly determines its frequency. Interestingly, describing function analysis applied on this model theoretically explains the mechanism of pathological beta oscillations.
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Affiliation(s)
- Fei Liu
- School of Electrical Engineering and Automation, Tianjin University, 300072 Tianjin, China
| | - Jiang Wang
- School of Electrical Engineering and Automation, Tianjin University, 300072 Tianjin, China
| | - Chen Liu
- School of Electrical Engineering and Automation, Tianjin University, 300072 Tianjin, China
| | - Huiyan Li
- School of Automation and Electrical Engineering, Tianjin University of Technology and Educations, 300222 Tianjin, China
| | - Bin Deng
- School of Electrical Engineering and Automation, Tianjin University, 300072 Tianjin, China
| | - Chris Fietkiewicz
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, Ohio 44106, USA
| | - Kenneth A Loparo
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, Ohio 44106, USA
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Kern K, Naros G, Braun C, Weiss D, Gharabaghi A. Detecting a Cortical Fingerprint of Parkinson's Disease for Closed-Loop Neuromodulation. Front Neurosci 2016; 10:110. [PMID: 27065781 PMCID: PMC4811963 DOI: 10.3389/fnins.2016.00110] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2015] [Accepted: 03/07/2016] [Indexed: 01/04/2023] Open
Abstract
Recent evidence suggests that deep brain stimulation (DBS) of the subthalamic nucleus (STN) in Parkinson's disease (PD) mediates its clinical effects by modulating cortical oscillatory activity, presumably via a direct cortico-subthalamic connection. This observation might pave the way for novel closed-loop approaches comprising a cortical sensor. Enhanced beta oscillations (13-35 Hz) have been linked to the pathophysiology of PD and may serve as such a candidate marker to localize a cortical area reliably modulated by DBS. However, beta-oscillations are widely distributed over the cortical surface, necessitating an additional signal source for spotting the cortical area linked to the pathologically synchronized cortico-subcortical motor network. In this context, both cortico-subthalamic coherence and cortico-muscular coherence (CMC) have been studied in PD patients. Whereas, the former requires invasive recordings, the latter allows for non-invasive detection, but displays a rather distributed cortical synchronization pattern in motor tasks. This distributed cortical representation may conflict with the goal of detecting a cortical localization with robust biomarker properties which is detectable on a single subject basis. We propose that this limitation could be overcome when recording CMC at rest. We hypothesized that-unlike healthy subjects-PD would show CMC at rest owing to the enhanced beta oscillations observed in PD. By performing source space analysis of beta CMC recorded during resting-state magnetoencephalography, we provide preliminary evidence in one patient for a cortical hot spot that is modulated most strongly by subthalamic DBS. Such a spot would provide a prominent target region either for direct neuromodulation or for placing a potential sensor in closed-loop DBS approaches, a proposal that requires investigation in a larger cohort of PD patients.
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Affiliation(s)
- Kevin Kern
- Division of Functional and Restorative Neurosurgery and Centre for Integrative Neuroscience, Eberhard Karls University TuebingenTuebingen, Germany
| | - Georgios Naros
- Division of Functional and Restorative Neurosurgery and Centre for Integrative Neuroscience, Eberhard Karls University TuebingenTuebingen, Germany
| | - Christoph Braun
- Magnetoencephalography Center, Eberhard Karls University TuebingenTuebingen, Germany
- Center for Mind/Brain Sciences (CIMeC), University of TrentoItaly
| | - Daniel Weiss
- Department for Neurodegenerative Diseases and Hertie Institute for Clinical Brain Research and German Centre of Neurodegenerative Diseases (DZNE), Eberhard Karls University TuebingenTuebingen, Germany
| | - Alireza Gharabaghi
- Division of Functional and Restorative Neurosurgery and Centre for Integrative Neuroscience, Eberhard Karls University TuebingenTuebingen, Germany
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Oswal A, Beudel M, Zrinzo L, Limousin P, Hariz M, Foltynie T, Litvak V, Brown P. Deep brain stimulation modulates synchrony within spatially and spectrally distinct resting state networks in Parkinson's disease. Brain 2016; 139:1482-96. [PMID: 27017189 PMCID: PMC4845255 DOI: 10.1093/brain/aww048] [Citation(s) in RCA: 171] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2015] [Accepted: 01/25/2016] [Indexed: 11/13/2022] Open
Abstract
Chronic dopamine depletion in Parkinson's disease leads to progressive motor and cognitive impairment, which is associated with the emergence of characteristic patterns of synchronous oscillatory activity within cortico-basal-ganglia circuits. Deep brain stimulation of the subthalamic nucleus is an effective treatment for Parkinson's disease, but its influence on synchronous activity in cortico-basal-ganglia loops remains to be fully characterized. Here, we demonstrate that deep brain stimulation selectively suppresses certain spatially and spectrally segregated resting state subthalamic nucleus-cortical networks. To this end we used a validated and novel approach for performing simultaneous recordings of the subthalamic nucleus and cortex using magnetoencephalography (during concurrent subthalamic nucleus deep brain stimulation). Our results highlight that clinically effective subthalamic nucleus deep brain stimulation suppresses synchrony locally within the subthalamic nucleus in the low beta oscillatory range and furthermore that the degree of this suppression correlates with clinical motor improvement. Moreover, deep brain stimulation relatively selectively suppressed synchronization of activity between the subthalamic nucleus and mesial premotor regions, including the supplementary motor areas. These mesial premotor regions were predominantly coupled to the subthalamic nucleus in the high beta frequency range, but the degree of deep brain stimulation-associated suppression in their coupling to the subthalamic nucleus was not found to correlate with motor improvement. Beta band coupling between the subthalamic nucleus and lateral motor areas was not influenced by deep brain stimulation. Motor cortical coupling with subthalamic nucleus predominantly involved driving of the subthalamic nucleus, with those drives in the higher beta frequency band having much shorter net delays to subthalamic nucleus than those in the lower beta band. These observations raise the possibility that cortical connectivity with the subthalamic nucleus in the high and low beta bands may reflect coupling mediated predominantly by the hyperdirect and indirect pathways to subthalamic nucleus, respectively, and that subthalamic nucleus deep brain stimulation predominantly suppresses the former. Yet only the change in strength of local subthalamic nucleus oscillations correlates with the degree of improvement during deep brain stimulation, compatible with the current view that a strengthened hyperdirect pathway is a prerequisite for locally generated beta activity but that it is the severity of the latter that may determine or index motor impairment.
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Affiliation(s)
- Ashwini Oswal
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford, UK Medical Research Council Brain Network Dynamics Unit, University of Oxford, UK Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, 12 Queen Square, London, UK
| | - Martijn Beudel
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford, UK Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, Queen Square, London, UK University Medical Centre Groningen, Department of Neurology, University of Groningen, The Netherlands
| | - Ludvic Zrinzo
- Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, Queen Square, London, UK
| | - Patricia Limousin
- Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, Queen Square, London, UK
| | - Marwan Hariz
- Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, Queen Square, London, UK
| | - Tom Foltynie
- Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, Queen Square, London, UK
| | - Vladimir Litvak
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, 12 Queen Square, London, UK
| | - Peter Brown
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford, UK Medical Research Council Brain Network Dynamics Unit, University of Oxford, UK
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Eyes Open on Sleep and Wake: In Vivo to In Silico Neural Networks. Neural Plast 2016; 2016:1478684. [PMID: 26885400 PMCID: PMC4738930 DOI: 10.1155/2016/1478684] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2015] [Accepted: 10/11/2015] [Indexed: 12/14/2022] Open
Abstract
Functional and effective connectivity of cortical areas are essential for normal brain function under different behavioral states. Appropriate cortical activity during sleep and wakefulness is ensured by the balanced activity of excitatory and inhibitory circuits. Ultimately, fast, millisecond cortical rhythmic oscillations shape cortical function in time and space. On a much longer time scale, brain function also depends on prior sleep-wake history and circadian processes. However, much remains to be established on how the brain operates at the neuronal level in humans during sleep and wakefulness. A key limitation of human neuroscience is the difficulty in isolating neuronal excitation/inhibition drive in vivo. Therefore, computational models are noninvasive approaches of choice to indirectly access hidden neuronal states. In this review, we present a physiologically driven in silico approach, Dynamic Causal Modelling (DCM), as a means to comprehend brain function under different experimental paradigms. Importantly, DCM has allowed for the understanding of how brain dynamics underscore brain plasticity, cognition, and different states of consciousness. In a broader perspective, noninvasive computational approaches, such as DCM, may help to puzzle out the spatial and temporal dynamics of human brain function at different behavioural states.
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Elibol R, Şengör NS. Looking at the role of direct and indirect pathways in basal ganglia networks at different levels. BMC Neurosci 2015. [PMCID: PMC4699119 DOI: 10.1186/1471-2202-16-s1-p225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
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Weingarten CP, Sundman MH, Hickey P, Chen NK. Neuroimaging of Parkinson's disease: Expanding views. Neurosci Biobehav Rev 2015; 59:16-52. [PMID: 26409344 PMCID: PMC4763948 DOI: 10.1016/j.neubiorev.2015.09.007] [Citation(s) in RCA: 101] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2015] [Revised: 09/07/2015] [Accepted: 09/15/2015] [Indexed: 12/14/2022]
Abstract
Advances in molecular and structural and functional neuroimaging are rapidly expanding the complexity of neurobiological understanding of Parkinson's disease (PD). This review article begins with an introduction to PD neurobiology as a foundation for interpreting neuroimaging findings that may further lead to more integrated and comprehensive understanding of PD. Diverse areas of PD neuroimaging are then reviewed and summarized, including positron emission tomography, single photon emission computed tomography, magnetic resonance spectroscopy and imaging, transcranial sonography, magnetoencephalography, and multimodal imaging, with focus on human studies published over the last five years. These included studies on differential diagnosis, co-morbidity, genetic and prodromal PD, and treatments from L-DOPA to brain stimulation approaches, transplantation and gene therapies. Overall, neuroimaging has shown that PD is a neurodegenerative disorder involving many neurotransmitters, brain regions, structural and functional connections, and neurocognitive systems. A broad neurobiological understanding of PD will be essential for translational efforts to develop better treatments and preventive strategies. Many questions remain and we conclude with some suggestions for future directions of neuroimaging of PD.
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Affiliation(s)
- Carol P Weingarten
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, United States.
| | - Mark H Sundman
- Brain Imaging and Analysis Center, Duke University Medical Center, United States
| | - Patrick Hickey
- Department of Neurology, Duke University School of Medicine, United States
| | - Nan-kuei Chen
- Brain Imaging and Analysis Center, Duke University Medical Center, United States; Department of Radiology, Duke University School of Medicine, United States
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Pavlides A, Hogan SJ, Bogacz R. Computational Models Describing Possible Mechanisms for Generation of Excessive Beta Oscillations in Parkinson's Disease. PLoS Comput Biol 2015; 11:e1004609. [PMID: 26683341 PMCID: PMC4684204 DOI: 10.1371/journal.pcbi.1004609] [Citation(s) in RCA: 85] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2015] [Accepted: 10/07/2015] [Indexed: 01/20/2023] Open
Abstract
In Parkinson's disease, an increase in beta oscillations within the basal ganglia nuclei has been shown to be associated with difficulty in movement initiation. An important role in the generation of these oscillations is thought to be played by the motor cortex and by a network composed of the subthalamic nucleus (STN) and the external segment of globus pallidus (GPe). Several alternative models have been proposed to describe the mechanisms for generation of the Parkinsonian beta oscillations. However, a recent experimental study of Tachibana and colleagues yielded results which are challenging for all published computational models of beta generation. That study investigated how the presence of beta oscillations in a primate model of Parkinson's disease is affected by blocking different connections of the STN-GPe circuit. Due to a large number of experimental conditions, the study provides strong constraints that any mechanistic model of beta generation should satisfy. In this paper we present two models consistent with the data of Tachibana et al. The first model assumes that Parkinsonian beta oscillation are generated in the cortex and the STN-GPe circuits resonates at this frequency. The second model additionally assumes that the feedback from STN-GPe circuit to cortex is important for maintaining the oscillations in the network. Predictions are made about experimental evidence that is required to differentiate between the two models, both of which are able to reproduce firing rates, oscillation frequency and effects of lesions carried out by Tachibana and colleagues. Furthermore, an analysis of the models reveals how the amplitude and frequency of the generated oscillations depend on parameters.
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Affiliation(s)
- Alex Pavlides
- MRC Unit for Brain Network Dynamics, University of Oxford, Oxford, United Kingdom
- Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
- Faculty of Engineering, University of Bristol, Bristol, United Kingdom
| | - S. John Hogan
- Faculty of Engineering, University of Bristol, Bristol, United Kingdom
| | - Rafal Bogacz
- MRC Unit for Brain Network Dynamics, University of Oxford, Oxford, United Kingdom
- Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
- Faculty of Engineering, University of Bristol, Bristol, United Kingdom
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Temporal patterning of neural synchrony in the basal ganglia in Parkinson's disease. Clin Neurophysiol 2015; 127:1743-1745. [PMID: 26433255 DOI: 10.1016/j.clinph.2015.09.005] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2015] [Revised: 09/11/2015] [Accepted: 09/11/2015] [Indexed: 11/23/2022]
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42
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Legon W, Punzell S, Dowlati E, Adams SE, Stiles AB, Moran RJ. Altered Prefrontal Excitation/Inhibition Balance and Prefrontal Output: Markers of Aging in Human Memory Networks. Cereb Cortex 2015; 26:4315-4326. [DOI: 10.1093/cercor/bhv200] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
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Davidson CM, de Paor AM, Cagnan H, Lowery MM. Analysis of Oscillatory Neural Activity in Series Network Models of Parkinson's Disease During Deep Brain Stimulation. IEEE Trans Biomed Eng 2015; 63:86-96. [PMID: 26340768 DOI: 10.1109/tbme.2015.2475166] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Parkinson's disease is a progressive, neurodegenerative disorder, characterized by hallmark motor symptoms. It is associated with pathological, oscillatory neural activity in the basal ganglia. Deep brain stimulation (DBS) is often successfully used to treat medically refractive Parkinson's disease. However, the selection of stimulation parameters is based on qualitative assessment of the patient, which can result in a lengthy tuning period and a suboptimal choice of parameters. This study explores fourth-order, control theory-based models of oscillatory activity in the basal ganglia. Describing function analysis is applied to examine possible mechanisms for the generation of oscillations in interacting nuclei and to investigate the suppression of oscillations with high-frequency stimulation. The theoretical results for the suppression of the oscillatory activity obtained using both the fourth-order model, and a previously described second-order model, are optimized to fit clinically recorded local field potential data obtained from Parkinsonian patients with implanted DBS. Close agreement between the power of oscillations recorded for a range of stimulation amplitudes is observed ( R(2)=0.69-0.99 ). The results suggest that the behavior of the system and the suppression of pathological neural oscillations with DBS is well described by the macroscopic models presented. The results also demonstrate that in this instance, a second-order model is sufficient to model the clinical data, without the need for added complexity. Describing the system behavior with computationally efficient models could aid in the identification of optimal stimulation parameters for patients in a clinical environment.
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Cagnan H, Duff EP, Brown P. The relative phases of basal ganglia activities dynamically shape effective connectivity in Parkinson's disease. Brain 2015; 138:1667-78. [PMID: 25888552 PMCID: PMC4614137 DOI: 10.1093/brain/awv093] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2014] [Accepted: 02/04/2015] [Indexed: 11/14/2022] Open
Abstract
Phase alignment between oscillatory circuits is thought to optimize information flow, but excessive synchrony within the motor circuit may impair network function. Cagnan et al. characterize the processes that underscore excessive synchronization and its termination, as well as their modulation by levodopa, before suggesting interventions that might prevent pathological circuit interactions. Optimal phase alignment between oscillatory neural circuits is hypothesized to optimize information flow and enhance system performance. This theory is known as communication-through-coherence. The basal ganglia motor circuit exhibits exaggerated oscillatory and coherent activity patterns in Parkinson's disease. Such activity patterns are linked to compromised motor system performance as evinced by bradykinesia, rigidity and tremor, suggesting that network function might actually deteriorate once a certain level of net synchrony is exceeded in the motor circuit. Here, we characterize the processes underscoring excessive synchronization and its termination. To this end, we analysed local field potential recordings from the subthalamic nucleus and globus pallidus of five patients with Parkinson's disease (four male and one female, aged 37–64 years). We observed that certain phase alignments between subthalamic nucleus and globus pallidus amplified local neural synchrony in the beta frequency band while others either suppressed it or did not induce any significant change with respect to surrogates. The increase in local beta synchrony directly correlated with how long the two nuclei locked to beta-amplifying phase alignments. Crucially, administration of the dopamine prodrug, levodopa, reduced the frequency and duration of periods during which subthalamic and pallidal populations were phase-locked to beta-amplifying alignments. Conversely ON dopamine, the total duration over which subthalamic and pallidal populations were aligned to phases that left beta-amplitude unchanged with respect to surrogates increased. Thus dopaminergic input shifted circuit dynamics from persistent periods of locking to amplifying phase alignments, associated with compromised motoric function, to more dynamic phase alignment and improved motoric function. This effect of dopamine on local circuit resonance suggests means by which novel electrical interventions might prevent resonance-related pathological circuit interactions.
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Affiliation(s)
- Hayriye Cagnan
- 1 Medical Research Council Brain Network Dynamics Unit at the University of Oxford, Mansfield Road, OX1 3TH, UK 2 Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, OX3 9DU, UK 3 The Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London WC1N 3BG, UK
| | - Eugene Paul Duff
- 4 FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU, UK
| | - Peter Brown
- 1 Medical Research Council Brain Network Dynamics Unit at the University of Oxford, Mansfield Road, OX1 3TH, UK 2 Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, OX3 9DU, UK
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Fernández-Seara MA, Mengual E, Vidorreta M, Castellanos G, Irigoyen J, Erro E, Pastor MA. Resting state functional connectivity of the subthalamic nucleus in Parkinson's disease assessed using arterial spin-labeled perfusion fMRI. Hum Brain Mapp 2015; 36:1937-50. [PMID: 25641065 DOI: 10.1002/hbm.22747] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2014] [Revised: 12/02/2014] [Accepted: 01/13/2015] [Indexed: 12/24/2022] Open
Abstract
Neurophysiological changes within the cortico-basal ganglia-thalamocortical circuits appear to be a characteristic of Parkinson's disease (PD) pathophysiology. The subthalamic nucleus (STN) is one of the basal ganglia components showing pathological neural activity patterns in PD. In this study, perfusion imaging data, acquired noninvasively using arterial spin-labeled (ASL) perfusion MRI, were used to assess the resting state functional connectivity (FC) of the STN in 24 early-to-moderate PD patients and 34 age-matched healthy controls, to determine whether altered FC in the very low frequency range of the perfusion time signal occurs as a result of the disease. Our results showed that the healthy STN was functionally connected with other nuclei of the basal ganglia and the thalamus, as well as with discrete cortical areas including the insular cortex and the hippocampus. In PD patients, connectivity of the STN was increased with two cortical areas involved in motor and cognitive processes. These findings suggest that hyperconnectivity of the STN could underlie some of the motor and cognitive deficits often present even at early stages of the disease. The FC measures provided good discrimination between controls and patients, suggesting that ASL-derived FC metrics could be a putative PD biomarker.
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Affiliation(s)
- María A Fernández-Seara
- Neuroimaging Laboratory, Division of Neuroscience, Center for Applied Medical Research (CIMA), University of Navarra, Pamplona, Spain; CIBERNED, Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, Instituto de Salud Carlos III, Spain
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Computational neurostimulation for Parkinson's disease. PROGRESS IN BRAIN RESEARCH 2015; 222:163-90. [DOI: 10.1016/bs.pbr.2015.09.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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Abstract
This scientific commentary refers to ‘On the nature of seizure dynamics’, by V. Jirsa et al. (doi:10.1093/brain/awu133).
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Abstract
The last decade has seen major progress at all levels of neuroscience, from genes and molecules up to integrated systems-level models of brain function. In particular, there have been advances in the understanding of cell-type-specific contributions to function, together with a clearer account of how these contributions are coordinated from moment to moment to organise behavior. A major current endeavor is to leverage this knowledge to develop new therapeutic approaches. In Parkinson's disease, there are a number of promising emerging treatments. Here, we will highlight three ambitious novel therapeutic approaches for this condition, each robustly driven by primary neuroscience. Pharmacogenetics genetically re-engineers neurons to produce neurotrophins that are neuroprotective to vulnerable dopaminergic cells or to directly replace dopamine through enzyme transduction. Deep brain stimulation (DBS) is undergoing a transformation, with adaptive DBS controlled by neural signals resulting in better motor outcomes and significant reductions in overall stimulation that could reduce side effects. Finally, optogenetics presents the opportunity to achieve cell-type-specific control with a high temporal specification on a large enough scale to effectively repair network-level dysfunction.
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Affiliation(s)
- S Little
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, OX3 9DU, UK
| | - P Brown
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, OX3 9DU, UK.
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49
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Origins and suppression of oscillations in a computational model of Parkinson's disease. J Comput Neurosci 2014; 37:505-21. [PMID: 25099916 DOI: 10.1007/s10827-014-0523-7] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2014] [Revised: 07/22/2014] [Accepted: 07/25/2014] [Indexed: 01/09/2023]
Abstract
Efficacy of deep brain stimulation (DBS) for motor signs of Parkinson's disease (PD) depends in part on post-operative programming of stimulus parameters. There is a need for a systematic approach to tuning parameters based on patient physiology. We used a physiologically realistic computational model of the basal ganglia network to investigate the emergence of a 34 Hz oscillation in the PD state and its optimal suppression with DBS. Discrete time transfer functions were fit to post-stimulus time histograms (PSTHs) collected in open-loop, by simulating the pharmacological block of synaptic connections, to describe the behavior of the basal ganglia nuclei. These functions were then connected to create a mean-field model of the closed-loop system, which was analyzed to determine the origin of the emergent 34 Hz pathological oscillation. This analysis determined that the oscillation could emerge from the coupling between the globus pallidus external (GPe) and subthalamic nucleus (STN). When coupled, the two resonate with each other in the PD state but not in the healthy state. By characterizing how this oscillation is affected by subthreshold DBS pulses, we hypothesize that it is possible to predict stimulus frequencies capable of suppressing this oscillation. To characterize the response to the stimulus, we developed a new method for estimating phase response curves (PRCs) from population data. Using the population PRC we were able to predict frequencies that enhance and suppress the 34 Hz pathological oscillation. This provides a systematic approach to tuning DBS frequencies and could enable closed-loop tuning of stimulation parameters.
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50
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Friston KJ, Bastos AM, Pinotsis D, Litvak V. LFP and oscillations-what do they tell us? Curr Opin Neurobiol 2014; 31:1-6. [PMID: 25079053 PMCID: PMC4376394 DOI: 10.1016/j.conb.2014.05.004] [Citation(s) in RCA: 112] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2014] [Revised: 05/07/2014] [Accepted: 05/08/2014] [Indexed: 11/28/2022]
Abstract
A brief treatment of dynamic coordination in terms of predictive coding. Understanding synchronous message passing in terms of hierarchical predictive coding. Characterising cortical gain control with the dynamic causal modelling of neural fields. Characterising pathophysiological oscillations with dynamic causal modelling of neural masses.
This review surveys recent trends in the use of local field potentials—and their non-invasive counterparts—to address the principles of functional brain architectures. In particular, we treat oscillations as the (observable) signature of context-sensitive changes in synaptic efficacy that underlie coordinated dynamics and message-passing in the brain. This rich source of information is now being exploited by various procedures—like dynamic causal modelling—to test hypotheses about neuronal circuits in health and disease. Furthermore, the roles played by neuromodulatory mechanisms can be addressed directly through their effects on oscillatory phenomena. These neuromodulatory or gain control processes are central to many theories of normal brain function (e.g. attention) and the pathophysiology of several neuropsychiatric conditions (e.g. Parkinson's disease).
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Affiliation(s)
- Karl J Friston
- The Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London WC1N 3BG, UK.
| | - André M Bastos
- Center for Neuroscience and Center for Mind and Brain, University of California-Davis, Davis, CA 95618, USA; Ernst Strüngmann Institute in Cooperation with Max Planck Society, Deutschordenstraße 46, 60528 Frankfurt, Germany
| | - Dimitris Pinotsis
- The Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London WC1N 3BG, UK
| | - Vladimir Litvak
- The Wellcome Trust Centre for Neuroimaging, University College London, Queen Square, London WC1N 3BG, UK
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