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Classication of semantic memories using multitaper spectral estimation

Dalin-Volsing, Sebastian (2015) MASY01 20151
Mathematical Statistics
Abstract
The research on classication of semantic memories is still very young. Several methods
have been tested ranging from magnetic resonance imaging (MRI) to electrocorticog-
raphy (ECoG). This report describes an alternative way of classifying signals collected
from an electroencephalogram (EEG) into categories using the Thomson multitaper
method of spectral estimation, as well as a logistic regression model. The aim for this
report is to expand the research eld with an approach that complements the current
options of classication. Data was distributed from the department of Psychology at
Lund University, and the experimental paradigm was to classify three types of semantic
memories (faces, landmarks and objects) based on their neural... (More)
The research on classication of semantic memories is still very young. Several methods
have been tested ranging from magnetic resonance imaging (MRI) to electrocorticog-
raphy (ECoG). This report describes an alternative way of classifying signals collected
from an electroencephalogram (EEG) into categories using the Thomson multitaper
method of spectral estimation, as well as a logistic regression model. The aim for this
report is to expand the research eld with an approach that complements the current
options of classication. Data was distributed from the department of Psychology at
Lund University, and the experimental paradigm was to classify three types of semantic
memories (faces, landmarks and objects) based on their neural patterns. Based on the
cross-validation from the mentioned methods, a classier could successfully be trained
for the "faces" and "landmarks" categories with an average success rate of 55% and 51%
respectively. The classier accurately responded to the onset of the stimuli (p < 0:001
for faces, p = 0:015 for landmarks). No classier for the "objects" category could be
trained using this method. These results indicate that the multitaper method of spec-
tral estimation can be useful in detecting neural patterns. Several ways to rene these
methods are discussed. (Less)
Please use this url to cite or link to this publication:
author
Dalin-Volsing, Sebastian
supervisor
organization
course
MASY01 20151
year
type
M2 - Bachelor Degree
subject
language
English
id
7508774
date added to LUP
2015-07-01 09:22:59
date last changed
2015-07-01 09:22:59
@misc{7508774,
  abstract     = {The research on classication of semantic memories is still very young. Several methods
have been tested ranging from magnetic resonance imaging (MRI) to electrocorticog-
raphy (ECoG). This report describes an alternative way of classifying signals collected
from an electroencephalogram (EEG) into categories using the Thomson multitaper
method of spectral estimation, as well as a logistic regression model. The aim for this
report is to expand the research eld with an approach that complements the current
options of classication. Data was distributed from the department of Psychology at
Lund University, and the experimental paradigm was to classify three types of semantic
memories (faces, landmarks and objects) based on their neural patterns. Based on the
cross-validation from the mentioned methods, a classier could successfully be trained
for the "faces" and "landmarks" categories with an average success rate of 55% and 51%
respectively. The classier accurately responded to the onset of the stimuli (p < 0:001
for faces, p = 0:015 for landmarks). No classier for the "objects" category could be
trained using this method. These results indicate that the multitaper method of spec-
tral estimation can be useful in detecting neural patterns. Several ways to rene these
methods are discussed.},
  author       = {Dalin-Volsing, Sebastian},
  language     = {eng},
  note         = {Student Paper},
  title        = {Classication of semantic memories using multitaper spectral estimation},
  year         = {2015},
}