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Time-frequency classification of gamma oscillatory activity in the frontoparietal system during working memory

Working memory (WM) is a process that allows for the temporary and limited storage of information for an immediate goal or to be stored into a more permanent system. A large number of studies
have led to the widely accepted view that WM is mediated by the frontoparietal network (FPN), consisting
of areas in the prefrontal cortex (PFC) and posterior parietal cortex (PPC). Current evidence suggests that
task specific patterns of neuronal oscillatory activity within the FPN play a fundamental role in WM, and
yet specific spatio-temporal properties of this activity are not well characterized. This study utilized multisite
local field potential (LFP) data recorded from PFC and PPC sites in two macaque monkeys trained to
perform a rule-based, Oculomotor Delayed Match-to-Sample task. The animals were required to learn
which of two rules determined the correct match (Location matching or Identity matching). Following a
500 ms fixation period, a sample stimulus was presented for 500 ms, followed by a randomized delay
lasting 800-1200 ms in which no stimulus was present. At the end of the delay period, a match stimulus
was presented, consisting of two of three possible objects presented at two of three possible locations.
When the match stimulus appeared, the monkey made a saccadic eye movement to the target. The rule in
effect determined which object served as the target. Time-frequency plots of three spectral measures
(power, coherence, and Wiener Granger Causality (WGC) were computed from MultiVariate
AutoRegressive LFP time-series models estimated in a 100-ms window that was slid across each of three
analysis epochs (fixation, sample, and delay). Low (25- 55 Hz) and high gamma (65- 100 Hz) activity were investigated separately due to evidence that they may be functionally distinct. Within each epoch, recording sites in the PPC and PFC were classified into groups according to the similarity of their power t-f plots derived by a K-means clustering algorithm. From the power-based site groups, the corresponding coherence and WGC were analyzed. This classification procedure uncovered spatial, temporal, and frequency dynamics of FPN
involvement in WM and other co-occurring processes, such as sensory and target related processes. These processes were distinguishable by rule and performance accuracy across all three spectral measures- power,
coherence, and WGC. Location and Identity rule were distinguishable by the low and high-gamma range. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection

Identiferoai:union.ndltd.org:fau.edu/oai:fau.digital.flvc.org:fau_13503
ContributorsRomano, Tracy A. (author), Bressler, Steven L. (Thesis advisor), Florida Atlantic University (Degree grantor), Charles E. Schmidt College of Science, Center for Complex Systems and Brain Sciences
PublisherFlorida Atlantic University
Source SetsFlorida Atlantic University
LanguageEnglish
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation, Text
Format232 p., application/pdf
RightsCopyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder., http://rightsstatements.org/vocab/InC/1.0/

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