Association between Income and the Hippocampus
Publication Date
May 04, 2011
Journal
PLOS ONE
Authors
Jamie L. Hanson, Amitabh Chandra, Barbara L. Wolfe & Seth D. Pollak
Volume
6
Issue
5
Pages
e18712
DOI
https://dx.plos.org/10.1371/journal.pone.0018712
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0018712
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/21573231
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3087752
Europe PMC
http://europepmc.org/abstract/MED/21573231
Web of Science
000290224800005
Scopus
79955781831
Mendeley
http://www.mendeley.com/research/association-between-income-hippocampus
Events
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Mendeley | Further Information

{"title"=>"Association between income and the hippocampus", "type"=>"journal", "authors"=>[{"first_name"=>"Jamie L.", "last_name"=>"Hanson", "scopus_author_id"=>"26424583400"}, {"first_name"=>"Amitabh", "last_name"=>"Chandra", "scopus_author_id"=>"7201668832"}, {"first_name"=>"Barbara L.", "last_name"=>"Wolfe", "scopus_author_id"=>"7201861917"}, {"first_name"=>"Seth D.", "last_name"=>"Pollak", "scopus_author_id"=>"7103341791"}], "year"=>2011, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"79955781831", "doi"=>"10.1371/journal.pone.0018712", "issn"=>"19326203", "pui"=>"361732894", "isbn"=>"1932-6203", "pmid"=>"21573231", "scopus"=>"2-s2.0-79955781831"}, "id"=>"4c7d0a10-9bec-363d-8240-79ff1a5cffa9", "abstract"=>"Facets of the post-natal environment including the type and complexity of environmental stimuli, the quality of parenting behaviors, and the amount and type of stress experienced by a child affects brain and behavioral functioning. Poverty is a type of pervasive experience that is likely to influence biobehavioral processes because children developing in such environments often encounter high levels of stress and reduced environmental stimulation. This study explores the association between socioeconomic status and the hippocampus, a brain region involved in learning and memory that is known to be affected by stress. We employ a voxel-based morphometry analytic framework with region of interest drawing for structural brain images acquired from participants across the socioeconomic spectrum (n = 317). Children from lower income backgrounds had lower hippocampal gray matter density, a measure of volume. This finding is discussed in terms of disparities in education and health that are observed across the socioeconomic spectrum.", "link"=>"http://www.mendeley.com/research/association-between-income-hippocampus", "reader_count"=>160, "reader_count_by_academic_status"=>{"Unspecified"=>5, "Professor > Associate Professor"=>11, "Librarian"=>1, "Student > Doctoral Student"=>16, "Researcher"=>32, "Student > Ph. D. Student"=>35, "Student > Postgraduate"=>3, "Student > Master"=>12, "Other"=>13, "Student > Bachelor"=>17, "Lecturer"=>4, "Lecturer > Senior Lecturer"=>2, "Professor"=>9}, "reader_count_by_user_role"=>{"Unspecified"=>5, "Professor > Associate Professor"=>11, "Librarian"=>1, "Student > Doctoral Student"=>16, "Researcher"=>32, "Student > Ph. D. Student"=>35, "Student > Postgraduate"=>3, "Student > Master"=>12, "Other"=>13, "Student > Bachelor"=>17, "Lecturer"=>4, "Lecturer > Senior Lecturer"=>2, "Professor"=>9}, "reader_count_by_subject_area"=>{"Unspecified"=>12, "Agricultural and Biological Sciences"=>12, "Arts and Humanities"=>3, "Chemistry"=>1, "Computer Science"=>2, "Economics, Econometrics and Finance"=>4, "Engineering"=>1, "Biochemistry, Genetics and Molecular Biology"=>1, "Nursing and Health Professions"=>2, "Mathematics"=>1, "Medicine and Dentistry"=>21, "Neuroscience"=>10, "Design"=>1, "Psychology"=>75, "Social Sciences"=>14}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>21}, "Social Sciences"=>{"Social Sciences"=>14}, "Psychology"=>{"Psychology"=>75}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>12}, "Arts and Humanities"=>{"Arts and Humanities"=>3}, "Design"=>{"Design"=>1}, "Engineering"=>{"Engineering"=>1}, "Chemistry"=>{"Chemistry"=>1}, "Neuroscience"=>{"Neuroscience"=>10}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>4}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>12}, "Computer Science"=>{"Computer Science"=>2}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}}, "reader_count_by_country"=>{"Canada"=>1, "United States"=>13, "Poland"=>1, "United Kingdom"=>2, "Australia"=>2, "France"=>1, "Russia"=>1}, "group_count"=>11}

CrossRef

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/777119"], "description"=>"<p>This scatterplot shows the association between total hippocampal gray matter probability and income. Total hippocampal gray matter shown on the vertical axis is displayed as a standardized residual controlling for child's age (in months), gender (dummy-coded), and whole brain volume, while log-transformed income is displayed on the horizontal axis. Higher income is associated with greater gray matter probability.</p>", "links"=>[], "tags"=>["hippocampal"], "article_id"=>447490, "categories"=>["Medicine", "Cell Biology", "Neuroscience", "Biotechnology", "Physiology"], "users"=>["Jamie L. Hanson", "Amitabh Chandra", "Barbara L. Wolfe", "Seth D. Pollak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0018712.g002", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Scatterplot_of_Total_Hippocampal_Gray_Matter_and_Income_/447490", "title"=>"Scatterplot of Total Hippocampal Gray Matter and Income.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-05-04 02:04:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/777370"], "description"=>"<p>This scatterplot shows the association between right hippocampal gray matter probability and income. Right hippocampal gray matter shown on the vertical axis is displayed as a standardized residual controlling for child's age (in months), gender (dummy-coded), and whole brain volume, while log-transformed income is displayed on the horizontal axis. Higher income is associated with greater gray matter probability.</p>", "links"=>[], "tags"=>["hippocampal"], "article_id"=>447748, "categories"=>["Medicine", "Cell Biology", "Neuroscience", "Biotechnology", "Physiology"], "users"=>["Jamie L. Hanson", "Amitabh Chandra", "Barbara L. Wolfe", "Seth D. Pollak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0018712.g004", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Scatterplot_of_Right_Hippocampal_Gray_Matter_and_Income_/447748", "title"=>"Scatterplot of Right Hippocampal Gray Matter and Income.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-05-04 02:09:08"}
  • {"files"=>["https://ndownloader.figshare.com/files/777668"], "description"=>"<p>Demographic Variables for Subjects with and without MRI Scans and/or Income.</p>", "links"=>[], "tags"=>["variables", "subjects", "mri", "scans"], "article_id"=>448039, "categories"=>["Medicine", "Cell Biology", "Neuroscience", "Biotechnology", "Physiology"], "users"=>["Jamie L. Hanson", "Amitabh Chandra", "Barbara L. Wolfe", "Seth D. Pollak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0018712.t005", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Demographic_Variables_for_Subjects_with_and_without_MRI_Scans_and_or_Income_/448039", "title"=>"Demographic Variables for Subjects with and without MRI Scans and/or Income.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-05-04 02:13:59"}
  • {"files"=>["https://ndownloader.figshare.com/files/777480"], "description"=>"<p>NB: All regression models included child age (in months), gender of the child (dummy-coded), and whole-brain volume as covariates.</p>", "links"=>[], "tags"=>["models", "examining", "hippocampus"], "article_id"=>447853, "categories"=>["Medicine", "Cell Biology", "Neuroscience", "Biotechnology", "Physiology"], "users"=>["Jamie L. Hanson", "Amitabh Chandra", "Barbara L. Wolfe", "Seth D. Pollak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0018712.t009", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Regression_Output_For_Models_Examining_the_Association_Between_the_Hippocampus_and_Income_/447853", "title"=>"Regression Output For Models Examining the Association Between the Hippocampus and Income.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-05-04 02:10:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/777748"], "description"=>"<p>Demographic Variables for Subjects with and without MRI Scans and/or Income.</p>", "links"=>[], "tags"=>["variables", "subjects", "mri", "scans"], "article_id"=>448111, "categories"=>["Medicine", "Cell Biology", "Neuroscience", "Biotechnology", "Physiology"], "users"=>["Jamie L. Hanson", "Amitabh Chandra", "Barbara L. Wolfe", "Seth D. Pollak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0018712.t007", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Demographic_Variables_for_Subjects_with_and_without_MRI_Scans_and_or_Income_/448111", "title"=>"Demographic Variables for Subjects with and without MRI Scans and/or Income.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-05-04 02:15:11"}
  • {"files"=>["https://ndownloader.figshare.com/files/777519"], "description"=>"<p>Demographic Variables for Subjects with and without MRI Scans and/or Income.</p>", "links"=>[], "tags"=>["variables", "subjects", "mri", "scans"], "article_id"=>447888, "categories"=>["Medicine", "Cell Biology", "Neuroscience", "Biotechnology", "Physiology"], "users"=>["Jamie L. Hanson", "Amitabh Chandra", "Barbara L. Wolfe", "Seth D. Pollak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0018712.t008", "stats"=>{"downloads"=>3, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Demographic_Variables_for_Subjects_with_and_without_MRI_Scans_and_or_Income_/447888", "title"=>"Demographic Variables for Subjects with and without MRI Scans and/or Income.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-05-04 02:11:28"}
  • {"files"=>["https://ndownloader.figshare.com/files/777554"], "description"=>"<p>Exclusionary criteria (originally appeared in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0018712#pone.0018712-Waber1\" target=\"_blank\">[20]</a> © Cambridge Journals, reproduced with permission.)</p>", "links"=>[], "tags"=>["appeared", "cambridge", "reproduced"], "article_id"=>447921, "categories"=>["Medicine", "Cell Biology", "Neuroscience", "Biotechnology", "Physiology"], "users"=>["Jamie L. Hanson", "Amitabh Chandra", "Barbara L. Wolfe", "Seth D. Pollak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0018712.t001", "stats"=>{"downloads"=>4, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Exclusionary_criteria_originally_appeared_in_20_Cambridge_Journals_reproduced_with_permission_/447921", "title"=>"Exclusionary criteria (originally appeared in [20] © Cambridge Journals, reproduced with permission.)", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-05-04 02:12:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/777713"], "description"=>"<p>Demographic Summary for full sample (based on Wave 1 data).</p>", "links"=>[], "tags"=>["public health and epidemiology", "physiology", "neuroscience", "pediatrics and child health", "neurological disorders", "Non-clinical medicine", "radiology and medical imaging"], "article_id"=>448082, "categories"=>["Medicine", "Cell Biology", "Neuroscience", "Biotechnology", "Physiology"], "users"=>["Jamie L. Hanson", "Amitabh Chandra", "Barbara L. Wolfe", "Seth D. Pollak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0018712.t004", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Demographic_Summary_for_full_sample_based_on_Wave_1_data_/448082", "title"=>"Demographic Summary for full sample (based on Wave 1 data).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-05-04 02:14:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/389982", "https://ndownloader.figshare.com/files/390019", "https://ndownloader.figshare.com/files/390053"], "description"=>"<div><p>Facets of the post-natal environment including the type and complexity of environmental stimuli, the quality of parenting behaviors, and the amount and type of stress experienced by a child affects brain and behavioral functioning. Poverty is a type of pervasive experience that is likely to influence biobehavioral processes because children developing in such environments often encounter high levels of stress and reduced environmental stimulation. This study explores the association between socioeconomic status and the hippocampus, a brain region involved in learning and memory that is known to be affected by stress. We employ a voxel-based morphometry analytic framework with region of interest drawing for structural brain images acquired from participants across the socioeconomic spectrum (n = 317). Children from lower income backgrounds had lower hippocampal gray matter density, a measure of volume. This finding is discussed in terms of disparities in education and health that are observed across the socioeconomic spectrum.</p> </div>", "links"=>[], "tags"=>["hippocampus"], "article_id"=>137011, "categories"=>["Medicine", "Cell Biology", "Neuroscience", "Biotechnology", "Physiology"], "users"=>["Jamie L. Hanson", "Amitabh Chandra", "Barbara L. Wolfe", "Seth D. Pollak"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0018712.s001", "https://dx.doi.org/10.1371/journal.pone.0018712.s002", "https://dx.doi.org/10.1371/journal.pone.0018712.s003"], "stats"=>{"downloads"=>22, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Association_between_Income_and_the_Hippocampus/137011", "title"=>"Association between Income and the Hippocampus", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2011-05-04 01:56:51"}
  • {"files"=>["https://ndownloader.figshare.com/files/777594"], "description"=>"<p>Demographic Summary for full sample (based on Wave 1 data).</p>", "links"=>[], "tags"=>["public health and epidemiology", "physiology", "neuroscience", "pediatrics and child health", "neurological disorders", "Non-clinical medicine", "radiology and medical imaging"], "article_id"=>447957, "categories"=>["Medicine", "Cell Biology", "Neuroscience", "Biotechnology", "Physiology"], "users"=>["Jamie L. Hanson", "Amitabh Chandra", "Barbara L. Wolfe", "Seth D. Pollak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0018712.t003", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Demographic_Summary_for_full_sample_based_on_Wave_1_data_/447957", "title"=>"Demographic Summary for full sample (based on Wave 1 data).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-05-04 02:12:37"}
  • {"files"=>["https://ndownloader.figshare.com/files/777772"], "description"=>"<p>Demographic Variables for Subjects with and without MRI Scans and/or Income.</p>", "links"=>[], "tags"=>["variables", "subjects", "mri", "scans"], "article_id"=>448145, "categories"=>["Medicine", "Cell Biology", "Neuroscience", "Biotechnology", "Physiology"], "users"=>["Jamie L. Hanson", "Amitabh Chandra", "Barbara L. Wolfe", "Seth D. Pollak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0018712.t006", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Demographic_Variables_for_Subjects_with_and_without_MRI_Scans_and_or_Income_/448145", "title"=>"Demographic Variables for Subjects with and without MRI Scans and/or Income.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-05-04 02:15:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/777824"], "description"=>"<p>NB: All regression models included child age (in months), gender of the child (dummy-coded), and whole-brain volume as covariates.</p>", "links"=>[], "tags"=>["models", "examining", "amygdala"], "article_id"=>448196, "categories"=>["Medicine", "Cell Biology", "Neuroscience", "Biotechnology", "Physiology"], "users"=>["Jamie L. Hanson", "Amitabh Chandra", "Barbara L. Wolfe", "Seth D. Pollak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0018712.t010", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Regression_Output_For_Models_Examining_the_Association_Between_the_Amygdala_and_Income_/448196", "title"=>"Regression Output For Models Examining the Association Between the Amygdala and Income.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-05-04 02:16:36"}
  • {"files"=>["https://ndownloader.figshare.com/files/777235"], "description"=>"<p>This scatterplot shows the association between left hippocampal gray matter probability and income. Left hippocampal gray matter shown on the vertical axis is displayed as a standardized residual controlling for child's age (in months), gender (dummy-coded), and whole brain volume, while log-transformed income is displayed on the horizontal axis. Higher income is associated with greater gray matter probability.</p>", "links"=>[], "tags"=>["hippocampal"], "article_id"=>447611, "categories"=>["Medicine", "Cell Biology", "Neuroscience", "Biotechnology", "Physiology"], "users"=>["Jamie L. Hanson", "Amitabh Chandra", "Barbara L. Wolfe", "Seth D. Pollak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0018712.g003", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Scatterplot_of_Left_Hippocampal_Gray_Matter_and_Income_/447611", "title"=>"Scatterplot of Left Hippocampal Gray Matter and Income.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-05-04 02:06:51"}
  • {"files"=>["https://ndownloader.figshare.com/files/776993"], "description"=>"<p>The top left brain slice shows a sagittal brain slice with the hippocampus highlighted in yellow and the amygdala in turquoise, while the top right brain image shows an axial slice (with the hippocampus again highlighted in yellow and the amygdala in turquoise). The bottom left brain picture shows a coronal slice with the amygdala in turquoise and the hippocampus in yellow.</p>", "links"=>[], "tags"=>["amygdala"], "article_id"=>447362, "categories"=>["Medicine", "Cell Biology", "Neuroscience", "Biotechnology", "Physiology"], "users"=>["Jamie L. Hanson", "Amitabh Chandra", "Barbara L. Wolfe", "Seth D. Pollak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0018712.g001", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Hippocampal_and_amygdala_region_of_interest_drawings_/447362", "title"=>"Hippocampal and amygdala region of interest drawings.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-05-04 02:02:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/777638"], "description"=>"<p>Demographic Summary for full sample (based on Wave 1 data).</p>", "links"=>[], "tags"=>["public health and epidemiology", "physiology", "neuroscience", "pediatrics and child health", "neurological disorders", "Non-clinical medicine", "radiology and medical imaging"], "article_id"=>447999, "categories"=>["Medicine", "Cell Biology", "Neuroscience", "Biotechnology", "Physiology"], "users"=>["Jamie L. Hanson", "Amitabh Chandra", "Barbara L. Wolfe", "Seth D. Pollak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0018712.t002", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Demographic_Summary_for_full_sample_based_on_Wave_1_data_/447999", "title"=>"Demographic Summary for full sample (based on Wave 1 data).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-05-04 02:13:19"}

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  • {"unique-ip"=>"16", "full-text"=>"22", "pdf"=>"7", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"8", "supp-data"=>"6", "cited-by"=>"2", "year"=>"2014", "month"=>"10"}
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  • {"unique-ip"=>"14", "full-text"=>"19", "pdf"=>"7", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"1", "cited-by"=>"1", "year"=>"2016", "month"=>"4"}
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  • {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"6"}
  • {"unique-ip"=>"6", "full-text"=>"8", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"7"}
  • {"unique-ip"=>"9", "full-text"=>"20", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"8"}
  • {"unique-ip"=>"10", "full-text"=>"12", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"9"}
  • {"unique-ip"=>"10", "full-text"=>"9", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"10"}
  • {"unique-ip"=>"9", "full-text"=>"11", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"11"}
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  • {"unique-ip"=>"20", "full-text"=>"12", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"3", "year"=>"2017", "month"=>"1"}
  • {"unique-ip"=>"13", "full-text"=>"12", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2017", "month"=>"2"}
  • {"unique-ip"=>"10", "full-text"=>"9", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"3"}
  • {"unique-ip"=>"10", "full-text"=>"10", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2017", "month"=>"4"}
  • {"unique-ip"=>"17", "full-text"=>"11", "pdf"=>"9", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"5"}
  • {"unique-ip"=>"6", "full-text"=>"8", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"6"}
  • {"unique-ip"=>"12", "full-text"=>"12", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2017", "month"=>"7"}
  • {"unique-ip"=>"7", "full-text"=>"5", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"8"}
  • {"unique-ip"=>"8", "full-text"=>"9", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"9"}
  • {"unique-ip"=>"17", "full-text"=>"13", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"10"}
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  • {"unique-ip"=>"10", "full-text"=>"11", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"1"}
  • {"unique-ip"=>"16", "full-text"=>"17", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"3"}
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  • {"unique-ip"=>"16", "full-text"=>"22", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"4"}
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  • {"unique-ip"=>"33", "full-text"=>"35", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"5"}
  • {"unique-ip"=>"10", "full-text"=>"8", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"6"}
  • {"unique-ip"=>"13", "full-text"=>"9", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
  • {"unique-ip"=>"9", "full-text"=>"9", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
  • {"unique-ip"=>"20", "full-text"=>"18", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
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  • {"unique-ip"=>"21", "full-text"=>"21", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"20", "full-text"=>"26", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"6", "full-text"=>"5", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"21", "full-text"=>"24", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
  • {"unique-ip"=>"9", "full-text"=>"9", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}
  • {"unique-ip"=>"9", "full-text"=>"9", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"8"}
  • {"unique-ip"=>"18", "full-text"=>"15", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"9"}
  • {"unique-ip"=>"17", "full-text"=>"16", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2019", "month"=>"10"}
  • {"unique-ip"=>"13", "full-text"=>"11", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"12"}
  • {"unique-ip"=>"16", "full-text"=>"12", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"2"}
  • {"unique-ip"=>"26", "full-text"=>"33", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"6", "cited-by"=>"1", "year"=>"2020", "month"=>"3"}
  • {"unique-ip"=>"22", "full-text"=>"27", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"4"}
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Relative Metric

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