PMID- 22548125
OWN - NLM
STAT- MEDLINE
DCOM- 20120716
LR  - 20211021
IS  - 1748-6718 (Electronic)
IS  - 1748-670X (Print)
IS  - 1748-670X (Linking)
VI  - 2012
DP  - 2012
TI  - Multiple Subject Barycentric Discriminant Analysis (MUSUBADA): how to assign 
      scans to categories without using spatial normalization.
PG  - 634165
LID - 10.1155/2012/634165 [doi]
LID - 634165
AB  - We present a new discriminant analysis (DA) method called Multiple Subject 
      Barycentric Discriminant Analysis (MUSUBADA) suited for analyzing fMRI data 
      because it handles datasets with multiple participants that each provides 
      different number of variables (i.e., voxels) that are themselves grouped into 
      regions of interest (ROIs). Like DA, MUSUBADA (1) assigns observations to 
      predefined categories, (2) gives factorial maps displaying observations and 
      categories, and (3) optimally assigns observations to categories. MUSUBADA 
      handles cases with more variables than observations and can project portions of 
      the data table (e.g., subtables, which can represent participants or ROIs) on the 
      factorial maps. Therefore MUSUBADA can analyze datasets with different voxel 
      numbers per participant and, so does not require spatial normalization. MUSUBADA 
      statistical inferences are implemented with cross-validation techniques (e.g., 
      jackknife and bootstrap), its performance is evaluated with confusion matrices 
      (for fixed and random models) and represented with prediction, tolerance, and 
      confidence intervals. We present an example where we predict the image categories 
      (houses, shoes, chairs, and human, monkey, dog, faces,) of images watched by 
      participants whose brains were scanned. This example corresponds to a DA question 
      in which the data table is made of subtables (one per subject) and with more 
      variables than observations.
FAU - Abdi, Herve
AU  - Abdi H
AD  - School of Behavioral and Brain Sciences, University of Texas at Dallas, MS: 
      GR4.1, 800 West Campbell Road, Richardson, TX 75080-3021, USA. herve@utdallas.edu
FAU - Williams, Lynne J
AU  - Williams LJ
FAU - Connolly, Andrew C
AU  - Connolly AC
FAU - Gobbini, M Ida
AU  - Gobbini MI
FAU - Dunlop, Joseph P
AU  - Dunlop JP
FAU - Haxby, James V
AU  - Haxby JV
LA  - eng
PT  - Journal Article
DEP - 20120405
PL  - United States
TA  - Comput Math Methods Med
JT  - Computational and mathematical methods in medicine
JID - 101277751
SB  - IM
MH  - Animals
MH  - Brain/*physiology
MH  - Data Interpretation, Statistical
MH  - Discriminant Analysis
MH  - Dogs
MH  - Face
MH  - Female
MH  - Haplorhini
MH  - Humans
MH  - Magnetic Resonance Imaging/*psychology
MH  - Male
PMC - PMC3328164
EDAT- 2012/05/02 06:00
MHDA- 2012/07/17 06:00
PMCR- 2012/04/05
CRDT- 2012/05/02 06:00
PHST- 2011/09/30 00:00 [received]
PHST- 2011/12/20 00:00 [revised]
PHST- 2011/12/21 00:00 [accepted]
PHST- 2012/05/02 06:00 [entrez]
PHST- 2012/05/02 06:00 [pubmed]
PHST- 2012/07/17 06:00 [medline]
PHST- 2012/04/05 00:00 [pmc-release]
AID - 10.1155/2012/634165 [doi]
PST - ppublish
SO  - Comput Math Methods Med. 2012;2012:634165. doi: 10.1155/2012/634165. Epub 2012 
      Apr 5.