Neural Plasticity in Human Brain Connectivity: The Effects of Long Term Deep Brain Stimulation of the Subthalamic Nucleus in Parkinson’s Disease
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{"title"=>"Neural plasticity in human brain connectivity: The effects of long term deep brain stimulation of the subthalamic nucleus in Parkinson's disease", "type"=>"journal", "authors"=>[{"first_name"=>"Tim J.", "last_name"=>"Van Hartevelt", "scopus_author_id"=>"55189926000"}, {"first_name"=>"Joana", "last_name"=>"Cabral", "scopus_author_id"=>"37664694800"}, {"first_name"=>"Gustavo", "last_name"=>"Deco", "scopus_author_id"=>"7006674531"}, {"first_name"=>"Arne", "last_name"=>"Møller", "scopus_author_id"=>"7401764527"}, {"first_name"=>"Alexander L.", "last_name"=>"Green", "scopus_author_id"=>"7404024088"}, {"first_name"=>"Tipu Z.", "last_name"=>"Aziz", "scopus_author_id"=>"7102677271"}, {"first_name"=>"Morten L.", "last_name"=>"Kringelbach", "scopus_author_id"=>"6701378751"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"24466120", "doi"=>"10.1371/journal.pone.0086496", "sgr"=>"84896683686", "isbn"=>"1932-6203", "scopus"=>"2-s2.0-84896683686", "issn"=>"19326203", "pui"=>"372981715"}, "id"=>"dcc78736-6d66-3d47-9e13-ea847dd926e2", "abstract"=>"BackgroundPositive clinical outcomes are now well established for deep brain stimulation, but little is known about the effects of long-term deep brain stimulation on brain structural and functional connectivity. Here, we used the rare opportunity to acquire pre- and postoperative diffusion tensor imaging in a patient undergoing deep brain stimulation in bilateral subthalamic nuclei for Parkinson’s Disease. This allowed us to analyse the differences in structural connectivity before and after deep brain stimulation. Further, a computational model of spontaneous brain activity was used to estimate the changes in functional connectivity arising from the specific changes in structural connectivity.ResultsWe found significant localised structural changes as a result of long-term deep brain stimulation. These changes were found in sensory-motor, prefrontal/limbic, and olfactory brain regions which are known to be affected in Parkinson’s Disease. The nature of these changes was an increase of nodal efficiency in most areas and a decrease of nodal efficiency in the precentral sensory-motor area. Importantly, the computational model clearly shows the impact of deep brain stimulation-induced structural alterations on functional brain changes, which is to shift the neural dynamics back towards a healthy regime. The results demonstrate that deep brain stimulation in Parkinson’s Disease leads to a topological reorganisation towards healthy bifurcation of the functional networks measured in controls, which suggests a potential neural mechanism for the alleviation of symptoms.ConclusionsThe findings suggest that long-term deep brain stimulation has not only restorative effects on the structural connectivity, but also affects the functional connectivity at a global level. Overall, our results support causal changes in human neural plasticity after long-term deep brain stimulation and may help to identify the underlying mechanisms of deep brain stimulation.", "link"=>"http://www.mendeley.com/research/neural-plasticity-human-brain-connectivity-effects-long-term-deep-brain-stimulation-subthalamic-nucl-12", "reader_count"=>68, "reader_count_by_academic_status"=>{"Unspecified"=>6, "Professor > Associate Professor"=>2, "Researcher"=>16, "Student > Doctoral Student"=>6, "Student > Ph. D. Student"=>11, "Student > Postgraduate"=>2, "Student > Master"=>12, "Student > Bachelor"=>7, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>2, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>6, "Professor > Associate Professor"=>2, "Researcher"=>16, "Student > Doctoral Student"=>6, "Student > Ph. D. Student"=>11, "Student > Postgraduate"=>2, "Student > Master"=>12, "Student > Bachelor"=>7, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>2, "Professor"=>2}, "reader_count_by_subject_area"=>{"Engineering"=>11, "Unspecified"=>9, "Nursing and Health Professions"=>1, "Biochemistry, Genetics and Molecular Biology"=>1, "Mathematics"=>1, "Agricultural and Biological Sciences"=>10, "Medicine and Dentistry"=>12, "Neuroscience"=>8, "Physics and Astronomy"=>2, "Psychology"=>10, "Social Sciences"=>1, "Computer Science"=>2}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>11}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>12}, "Neuroscience"=>{"Neuroscience"=>8}, "Social Sciences"=>{"Social Sciences"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>2}, "Psychology"=>{"Psychology"=>10}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>10}, "Computer Science"=>{"Computer Science"=>2}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>9}}, "reader_count_by_country"=>{"South Korea"=>1, "United States"=>2, "Japan"=>1, "China"=>1, "United Kingdom"=>1, "Germany"=>1, "Spain"=>1}, "group_count"=>4}

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  • {"files"=>["https://ndownloader.figshare.com/files/1355380"], "description"=>"<p>DTI and network construction based on the Automated Anatomical Labelling (AAL) parcellation <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0086496#pone.0086496-TzourioMazoyer1\" target=\"_blank\">[28]</a>.</p>", "links"=>[], "tags"=>["Anatomy and physiology", "Neurological system", "Motor systems", "neuroscience", "neuroanatomy", "Connectomics", "computational neuroscience", "neuroimaging", "Neural pathways", "neurology", "Parkinson disease", "surgery", "neurosurgery", "automated", "anatomical", "labelling", "parcellation"], "article_id"=>907853, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Tim J. van Hartevelt", "Joana Cabral", "Gustavo Deco", "Arne Møller", "Alexander L. Green", "Tipu Z. Aziz", "Morten L. Kringelbach"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0086496.g001", "stats"=>{"downloads"=>0, "page_views"=>26, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_DTI_and_network_construction_based_on_the_Automated_Anatomical_Labelling_AAL_parcellation_28_/907853", "title"=>"DTI and network construction based on the Automated Anatomical Labelling (AAL) parcellation [28].", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-22 03:03:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355381"], "description"=>"<p>The artefact from the external lead of the DBS electrodes is visible in the form of dropout in left hemisphere in A) the <i>b</i>0 weighted image and B) the diffusion tensor image.</p>", "links"=>[], "tags"=>["Anatomy and physiology", "Neurological system", "Motor systems", "neuroscience", "neuroanatomy", "Connectomics", "computational neuroscience", "neuroimaging", "Neural pathways", "neurology", "Parkinson disease", "surgery", "neurosurgery", "electrode", "artefact"], "article_id"=>907854, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Tim J. van Hartevelt", "Joana Cabral", "Gustavo Deco", "Arne Møller", "Alexander L. Green", "Tipu Z. Aziz", "Morten L. Kringelbach"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0086496.g002", "stats"=>{"downloads"=>2, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_DBS_electrode_artefact_from_lead_/907854", "title"=>"DBS electrode artefact from lead.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-22 03:03:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355385"], "description"=>"<p>The pre- and post-operative structural networks (left and right columns, respectively) are shown superimposed on a rendered brain (<b>A/B</b>) and as connectivity matrices, <i>C<sub>pre</sub></i> and <i>C<sub>post</sub></i> (<b>C/D</b>). In both representations, the full 90-node networks are highlighted in green, while the left and right hemispheres are highlighted in blue and red, correspondingly (In <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0086496#pone-0086496-t002\" target=\"_blank\"><b>Table 2</b></a> we report the indexing of brain areas). In the matrix representations, transcallosal connectivity is shown in the other diagonals. In C and D, the red arrows point to the pre- and post-operative 45×45 right hemisphere connectivity matrices.</p>", "links"=>[], "tags"=>["Anatomy and physiology", "Neurological system", "Motor systems", "neuroscience", "neuroanatomy", "Connectomics", "computational neuroscience", "neuroimaging", "Neural pathways", "neurology", "Parkinson disease", "surgery", "neurosurgery", "connectivity", "networks", "derived", "dti"], "article_id"=>907858, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Tim J. van Hartevelt", "Joana Cabral", "Gustavo Deco", "Arne Møller", "Alexander L. Green", "Tipu Z. Aziz", "Morten L. Kringelbach"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0086496.g003", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Anatomical_connectivity_networks_derived_from_DTI_data_/907858", "title"=>"Anatomical connectivity networks derived from DTI data.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-22 03:03:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355388"], "description"=>"<p>The AAL regions with more than 20% difference in nodal efficiency between pre- and postoperative measures are plotted on three-dimensional renderings of the human brain in MNI space seen from above (top) and from the side (bottom). The size and colour of the circles indicate the magnitude (size) of the increases (blue) and decrease (red) in nodal efficiency after DBS. The number inside each circle indicates the AAL ordering index reported in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0086496#pone-0086496-t002\" target=\"_blank\"><b>Table 2</b></a>.</p>", "links"=>[], "tags"=>["Anatomy and physiology", "Neurological system", "Motor systems", "neuroscience", "neuroanatomy", "Connectomics", "computational neuroscience", "neuroimaging", "Neural pathways", "neurology", "Parkinson disease", "surgery", "neurosurgery", "pre-", "post-dbs"], "article_id"=>907861, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Tim J. van Hartevelt", "Joana Cabral", "Gustavo Deco", "Arne Møller", "Alexander L. Green", "Tipu Z. Aziz", "Morten L. Kringelbach"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0086496.g004", "stats"=>{"downloads"=>1, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Nodal_efficiency_changes_between_pre_and_post_DBS_structural_networks_/907861", "title"=>"Nodal efficiency changes between pre- and post-DBS structural networks.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-22 03:03:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355393"], "description"=>"<p><b>A</b>) Schematic overview of how the simulated FC matrices are obtained from the SC matrices using the dynamic mean field (DMF) model. The simulated FC matrices are subsequently compared to the empirical resting state FC matrix. <b>B</b>) Solid lines indicate the fitting of simulated functional connectivity (FC) matrices obtained with the pre-DBS (black), post-DBS (red), and healthy controls (blue) structural connectivity matrices with the empirical healthy FC, as a function of the global coupling weight (G). Vertical dashed lines indicate the corresponding bifurcation points, above which the dynamics becomes unstable. We observe that the bifurcation point of the post-DBS FC is shifted from the pre-DBS FC bifurcation point towards the healthy bifurcation point. This means that, before DBS, the structural connectivity is weaker and therefore stronger couplings are required to reach an optimal fitting with empirical FC The shift of the post-DBS bifurcation point towards the healthy bifurcation point indicates recovery of the structural connectivity with DBS.</p>", "links"=>[], "tags"=>["Anatomy and physiology", "Neurological system", "Motor systems", "neuroscience", "neuroanatomy", "Connectomics", "computational neuroscience", "neuroimaging", "Neural pathways", "neurology", "Parkinson disease", "surgery", "neurosurgery", "dbs-induced", "resting-state"], "article_id"=>907864, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Tim J. van Hartevelt", "Joana Cabral", "Gustavo Deco", "Arne Møller", "Alexander L. Green", "Tipu Z. Aziz", "Morten L. Kringelbach"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0086496.g005", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Exploring_the_impact_of_DBS_induced_structural_changes_on_resting_state_functional_connectivity_/907864", "title"=>"Exploring the impact of DBS-induced structural changes on resting-state functional connectivity.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-01-22 03:03:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355394"], "description"=>"<p>Graph properties of the preoperative, postoperative and control structural networks (right hemisphere only).</p>", "links"=>[], "tags"=>["Anatomy and physiology", "Neurological system", "Motor systems", "neuroscience", "neuroanatomy", "Connectomics", "computational neuroscience", "neuroimaging", "Neural pathways", "neurology", "Parkinson disease", "surgery", "neurosurgery", "postoperative", "networks", "hemisphere"], "article_id"=>907865, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Tim J. van Hartevelt", "Joana Cabral", "Gustavo Deco", "Arne Møller", "Alexander L. Green", "Tipu Z. Aziz", "Morten L. Kringelbach"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0086496.t001", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Graph_properties_of_the_preoperative_postoperative_and_control_structural_networks_right_hemisphere_only_/907865", "title"=>"Graph properties of the preoperative, postoperative and control structural networks (right hemisphere only).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-01-22 03:03:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355395"], "description"=>"<p>Graph properties of simulated functional networks derived from the dynamic mean field model with the 3 structural connectomes from the preoperative PD, postoperative PD and healthy controls.</p>", "links"=>[], "tags"=>["Anatomy and physiology", "Neurological system", "Motor systems", "neuroscience", "neuroanatomy", "Connectomics", "computational neuroscience", "neuroimaging", "Neural pathways", "neurology", "Parkinson disease", "surgery", "neurosurgery", "simulated", "networks", "derived", "connectomes", "preoperative", "postoperative", "pd"], "article_id"=>907866, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Tim J. van Hartevelt", "Joana Cabral", "Gustavo Deco", "Arne Møller", "Alexander L. Green", "Tipu Z. Aziz", "Morten L. Kringelbach"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0086496.t003", "stats"=>{"downloads"=>0, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Graph_properties_of_simulated_functional_networks_derived_from_the_dynamic_mean_field_model_with_the_3_structural_connectomes_from_the_preoperative_PD_postoperative_PD_and_healthy_controls_/907866", "title"=>"Graph properties of simulated functional networks derived from the dynamic mean field model with the 3 structural connectomes from the preoperative PD, postoperative PD and healthy controls.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-01-22 03:03:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/1355396"], "description"=>"<p>Pre- and post-operative nodal efficiency measures and corresponding percentage differences are reported. AAL regions identified to have more than 20% difference between preoperative and postoperative nodal efficiency are shown in bold.</p>", "links"=>[], "tags"=>["Anatomy and physiology", "Neurological system", "Motor systems", "neuroscience", "neuroanatomy", "Connectomics", "computational neuroscience", "neuroimaging", "Neural pathways", "neurology", "Parkinson disease", "surgery", "neurosurgery"], "article_id"=>907867, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Tim J. van Hartevelt", "Joana Cabral", "Gustavo Deco", "Arne Møller", "Alexander L. Green", "Tipu Z. Aziz", "Morten L. Kringelbach"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0086496.t002", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Listing_the_45_Figure_3_/907867", "title"=>"Listing the 45<b>Figure 3</b>.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-01-22 03:03:00"}

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Relative Metric

{"start_date"=>"2014-01-01T00:00:00Z", "end_date"=>"2014-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[291]}, {"subject_area"=>"/Biology and life sciences/Anatomy", "average_usage"=>[267]}, {"subject_area"=>"/Computer and information sciences", "average_usage"=>[327, 511]}, {"subject_area"=>"/Computer and information sciences/Neural networks", "average_usage"=>[359, 536]}, {"subject_area"=>"/Medicine and health sciences", "average_usage"=>[285]}]}
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