Difference between revisions of "SOCR Data July2009 ID NI"

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(New page: == SOCR Datasets - Neuroimaging study of Prefrontal Cortex Volume across Species and Tissue Types == ==Data Overview== [[Image:SOCR_Data_Dinov_June2008_NI.png|150px|thumb...)
 
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== [[SOCR_Data | SOCR Datasets]] -  Neuroimaging study of Prefrontal Cortex Volume across Species and Tissue Types ==
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== [[SOCR_Data | SOCR Datasets]] -  Neuroimaging study of 27 Alzheimer's disease (AD) subjects, 35 normal controls (NC), and 42 mild cognitive impairment subjects (MCI) ==
  
 
==Data Overview==
 
==Data Overview==
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[[Image:SOCR_Data_Dinov_June2008_NI.png|150px|thumbnail|right| Neuroimaging Data ]]
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[[Image:SOCR_Data_Dinov_July2009_NI.png|150px|thumbnail|right| Neuroimaging Data ]]
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The [http://en.wikipedia.org/wiki/Prefrontal_cortex prefrontal cortex] is the anterior part of the frontal lobes of the brain in front of the premotor areas. Prefrontal cortex includes cytoarchitectonic layer IV and includes three regions: orbitofrontal (OFC), dorsolateral prefrontal cortex (PFC), anterior and ventral cingulate cortex. Human brains are much distinct from the brains of other [http://en.wikipedia.org/wiki/Primate primates] and [http://en.wikipedia.org/wiki/Ape apes] specifically in the prefrontal cortex. These structural differences induce significant functional abilities which may account for the significant associating, planning and strategic thinking in humans, compared to other primates. The study below investigated the quantitative differences between the PFC volumes across species and tissue types.
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[[SOCR_Data_July2009_ID_NI#References |This is a large neuroimaging study]] using automated volumetric data processing to obtain different shape and volume measures of local anatomy. The subject population is derived from the [http://www.loni.ucla.edu/ADNI Alzheimer's Disease Neuroimaging Initiative (ADNI) database] and includes 27 Alzheimer's disease (AD) subjects, 35 normal controls (NC), and 42 mild cognitive impairment subjects (MCI). The goals of the study were to identify associations and relationships between neuroimaging biomarkers and various subject demographics and traits.
  
 
==Data Description==
 
==Data Description==
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* '''ICV''' – intracranial volume
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* Subject_ID: index of the subject in this dataset (1, 2, 3, ..., 104)
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* '''PFC''' – prefrontal cortex
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* Group: Indicator of the subject group: Alzheimer's disease (AD), normal control (NC), or mild cognitive impairment (MCI)
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* '''GM''' – gray matter
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* MMSE: [http://en.wikipedia.org/wiki/Mini-mental_state_examination Mini-Mental State Exam score], a cognitive assessment measure
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* '''Total''' – total volume
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* CDR: [http://en.wikipedia.org/wiki/Clinical_Dementia_Rating Clinical Dementia Rating scale]
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* '''WM''' – white matter
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* Sex: Subject's gender label
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* '''SEM''' – standard error of the mean
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* Age: Subject's age
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* TBV: Total Brain Volume measure in ''mm<sum>3</sup>''
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* GMV: Gray Matter Volume in ''mm<sum>3</sup>''
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* WMV: White Matter Volume in ''mm<sum>3</sup>''
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* CSFV: Cerebrospinal Fluid Volume in ''mm<sum>3</sup>''
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* ROI: [[SOCR_Data_July2009_ID_NI#ROIs |Label/Index of a Region of Interest (ROI)]]
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* Measure: Labels of ROI measures:
 +
** SA: Surface Area of the ROI
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** SI: Shape Index of the ROI
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** CV: Curvedness of the ROI
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** FD: Fractal Dimension of the ROI
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* Value: Numerical value of the measure (above).
 +
 
 +
 
 +
==Data==
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[http://socr.ucla.edu/docs/resources/SOCR_Data/AD_NC_MCI_NI_Data2009.html Complete data set (5MB) is available here]. A small portion of the data that illustrates the complexity of this dataset is shown in the table below:
  
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==Data: Total, GM and WM volumes of ICV and PFC across species==
 
 
{| class="wikitable" style="text-align:center;" border="2"
 
{| class="wikitable" style="text-align:center;" border="2"
 
|-
 
|-
−
! || colspan=3|Cerebrum ICV (mm3) || colspan=3|PFC (mm3) || rowspan=2|% PFC/ICV
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! Subject_ID || Group || MMSE || CDR || Sex || Age || TBV || GMV || WMV || CSFV || ROI || Measure || Value
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 +
|}
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 +
== ROIs==
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{| class="wikitable" style="text-align:center;" border="2"
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|-
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! Index || ImageIntensity || ROI_Name
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|-
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| 0 || 0 || Background
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|-
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| 1 || 21 || L_superior_frontal_gyrus
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|-
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| 2 || 24 || R_middle_frontal_gyrus
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|-
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| 3 || 50 || R_precuneus
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|-
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| 4 || 181 || cerebellum
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|-
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| 5 || 47 || L_angular_gyrus
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|-
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| 6 || 122 || R_cingulate_gyrus
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|-
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| 7 || 83 || L_middle_temporal_gyrus
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|-
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| 8 || 90 || R_lingual_gyrus
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|-
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| 9 || 81 || L_superior_temporal_gyrus
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|-
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| 10 || 91 || L_fusiform_gyrus
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|-
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| 11 || 44 || R_superior_parietal_gyrus
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|-
 +
| 12 || 66 || R_inferior_occipital_gyrus
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|-
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| 13 || 87 || L_parahippocampal_gyrus
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|-
 +
| 14 || 162 || R_caudate
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|-
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| 15 || 85 || L_inferior_temporal_gyrus
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|-
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| 16 || 182 || brainstem
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|-
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| 17 || 43 || L_superior_parietal_gyrus
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|-
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| 18 || 28 || R_precentral_gyrus
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|-
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| 19 || 23 || L_middle_frontal_gyrus
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|-
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| 20 || 89 || L_lingual_gyrus
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|-
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| 21 || 41 || L_postcentral_gyrus
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|-
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| 22 || 86 || R_inferior_temporal_gyrus
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|-
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| 23 || 163 || L_putamen
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|-
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| 24 || 26 || R_inferior_frontal_gyrus
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|-
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| 25 || 102 || R_insular_cortex
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|-
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| 26 || 25 || L_inferior_frontal_gyrus
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|-
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| 27 || 46 || R_supramarginal_gyrus
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|-
 +
| 28 || 34 || R_gyrus_rectus
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|-
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| 29 || 65 || L_inferior_occipital_gyrus
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|-
 +
| 30 || 164 || R_putamen
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|-
 +
| 31 || 61 || L_superior_occipital_gyrus
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|-
 +
| 32 || 30 || R_middle_orbitofrontal_gyrus
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|-
 +
| 33 || 42 || R_postcentral_gyrus
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|-
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| 34 || 27 || L_precentral_gyrus
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|-
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| 35 || 32 || R_lateral_orbitofrontal_gyrus
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|-
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| 36 || 121 || L_cingulate_gyrus
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|-
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| 37 || 31 || L_lateral_orbitofrontal_gyrus
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|-
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| 38 || 92 || R_fusiform_gyrus
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|-
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| 39 || 45 || L_supramarginal_gyrus
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|-
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| 40 || 88 || R_parahippocampal_gyrus
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|-
 +
| 41 || 22 || R_superior_frontal_gyrus
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|-
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| 42 || 29 || L_middle_orbitofrontal_gyrus
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|-
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| 43 || 68 || R_cuneus
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|-
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| 44 || 62 || R_superior_occipital_gyrus
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|-
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| 45 || 33 || L_gyrus_rectus
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|-
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| 46 || 48 || R_angular_gyrus
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|-
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| 47 || 64 || R_middle_occipital_gyrus
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|-
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| 48 || 84 || R_middle_temporal_gyrus
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|-
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| 49 || 49 || L_precuneus
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|-
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| 50 || 67 || L_cuneus
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|-
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| 51 || 161 || L_caudate
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|-
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| 52 || 165 || L_hippocampus
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|-
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| 53 || 166 || R_hippocampus
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|-
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| 54 || 82 || R_superior_temporal_gyrus
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|-
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| 55 || 63 || L_middle_occipital_gyrus
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|-
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| 56 || 101 || L_insular_cortex
 
|}
 
|}
  
 
== References==
 
== References==
 
* Dinov ID, Van Horn JD, Lozev KM, Magsipoc R, Petrosyan P, Liu Z, MacKenzie-Graha A, Eggert P, Parker DS and Toga AW (2009) Efficient, Distributed and Interactive Neuroimaging Data Analysis using the LONI Pipeline. [http://www.frontiersin.org/neuroinformatics/ Front. Neuroinform.] (2009) 3:22. [http://www.frontiersin.org/neuroinformatics/paper/10.3389/neuro.11/022.2009/ doi:10.3389/neuro.11.022.2009], published online: 20 July 2009.
 
* Dinov ID, Van Horn JD, Lozev KM, Magsipoc R, Petrosyan P, Liu Z, MacKenzie-Graha A, Eggert P, Parker DS and Toga AW (2009) Efficient, Distributed and Interactive Neuroimaging Data Analysis using the LONI Pipeline. [http://www.frontiersin.org/neuroinformatics/ Front. Neuroinform.] (2009) 3:22. [http://www.frontiersin.org/neuroinformatics/paper/10.3389/neuro.11/022.2009/ doi:10.3389/neuro.11.022.2009], published online: 20 July 2009.
 +
 +
* David W. Shattuck, Mubeena Mirza, Vitria Adisetiyo, Cornelius Hojatkashani, Georges Salamon, Katherine L. Narr, Russell A. Poldrack, Robert M. Bilder, Arthur W. Toga, Construction of a 3D probabilistic atlas of human cortical structures, NeuroImage, Volume 39, Issue 3, 1 February 2008, Pages 1064-1080, ISSN 1053-8119, DOI: [http://dx.doi.org/10.1016/j.neuroimage.2007.09.031 10.1016/j.neuroimage.2007.09.031].
 +
  
 
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Revision as of 01:01, 24 July 2009

SOCR Datasets - Neuroimaging study of 27 Alzheimer's disease (AD) subjects, 35 normal controls (NC), and 42 mild cognitive impairment subjects (MCI)

Data Overview

Neuroimaging Data

This is a large neuroimaging study using automated volumetric data processing to obtain different shape and volume measures of local anatomy. The subject population is derived from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database and includes 27 Alzheimer's disease (AD) subjects, 35 normal controls (NC), and 42 mild cognitive impairment subjects (MCI). The goals of the study were to identify associations and relationships between neuroimaging biomarkers and various subject demographics and traits.

Data Description

  • Subject_ID: index of the subject in this dataset (1, 2, 3, ..., 104)
  • Group: Indicator of the subject group: Alzheimer's disease (AD), normal control (NC), or mild cognitive impairment (MCI)
  • MMSE: Mini-Mental State Exam score, a cognitive assessment measure
  • CDR: Clinical Dementia Rating scale
  • Sex: Subject's gender label
  • Age: Subject's age
  • TBV: Total Brain Volume measure in mm<sum>3
  • GMV: Gray Matter Volume in mm<sum>3
  • WMV: White Matter Volume in mm<sum>3
  • CSFV: Cerebrospinal Fluid Volume in mm<sum>3
  • ROI: Label/Index of a Region of Interest (ROI)
  • Measure: Labels of ROI measures:
    • SA: Surface Area of the ROI
    • SI: Shape Index of the ROI
    • CV: Curvedness of the ROI
    • FD: Fractal Dimension of the ROI
  • Value: Numerical value of the measure (above).


Data

Complete data set (5MB) is available here. A small portion of the data that illustrates the complexity of this dataset is shown in the table below:

Subject_ID Group MMSE CDR Sex Age TBV GMV WMV CSFV ROI Measure Value


ROIs

Index ImageIntensity ROI_Name
0 0 Background
1 21 L_superior_frontal_gyrus
2 24 R_middle_frontal_gyrus
3 50 R_precuneus
4 181 cerebellum
5 47 L_angular_gyrus
6 122 R_cingulate_gyrus
7 83 L_middle_temporal_gyrus
8 90 R_lingual_gyrus
9 81 L_superior_temporal_gyrus
10 91 L_fusiform_gyrus
11 44 R_superior_parietal_gyrus
12 66 R_inferior_occipital_gyrus
13 87 L_parahippocampal_gyrus
14 162 R_caudate
15 85 L_inferior_temporal_gyrus
16 182 brainstem
17 43 L_superior_parietal_gyrus
18 28 R_precentral_gyrus
19 23 L_middle_frontal_gyrus
20 89 L_lingual_gyrus
21 41 L_postcentral_gyrus
22 86 R_inferior_temporal_gyrus
23 163 L_putamen
24 26 R_inferior_frontal_gyrus
25 102 R_insular_cortex
26 25 L_inferior_frontal_gyrus
27 46 R_supramarginal_gyrus
28 34 R_gyrus_rectus
29 65 L_inferior_occipital_gyrus
30 164 R_putamen
31 61 L_superior_occipital_gyrus
32 30 R_middle_orbitofrontal_gyrus
33 42 R_postcentral_gyrus
34 27 L_precentral_gyrus
35 32 R_lateral_orbitofrontal_gyrus
36 121 L_cingulate_gyrus
37 31 L_lateral_orbitofrontal_gyrus
38 92 R_fusiform_gyrus
39 45 L_supramarginal_gyrus
40 88 R_parahippocampal_gyrus
41 22 R_superior_frontal_gyrus
42 29 L_middle_orbitofrontal_gyrus
43 68 R_cuneus
44 62 R_superior_occipital_gyrus
45 33 L_gyrus_rectus
46 48 R_angular_gyrus
47 64 R_middle_occipital_gyrus
48 84 R_middle_temporal_gyrus
49 49 L_precuneus
50 67 L_cuneus
51 161 L_caudate
52 165 L_hippocampus
53 166 R_hippocampus
54 82 R_superior_temporal_gyrus
55 63 L_middle_occipital_gyrus
56 101 L_insular_cortex

References

  • Dinov ID, Van Horn JD, Lozev KM, Magsipoc R, Petrosyan P, Liu Z, MacKenzie-Graha A, Eggert P, Parker DS and Toga AW (2009) Efficient, Distributed and Interactive Neuroimaging Data Analysis using the LONI Pipeline. Front. Neuroinform. (2009) 3:22. doi:10.3389/neuro.11.022.2009, published online: 20 July 2009.
  • David W. Shattuck, Mubeena Mirza, Vitria Adisetiyo, Cornelius Hojatkashani, Georges Salamon, Katherine L. Narr, Russell A. Poldrack, Robert M. Bilder, Arthur W. Toga, Construction of a 3D probabilistic atlas of human cortical structures, NeuroImage, Volume 39, Issue 3, 1 February 2008, Pages 1064-1080, ISSN 1053-8119, DOI: 10.1016/j.neuroimage.2007.09.031.


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