THE STRUCTURAL ORGANIZATION AND SPECTRAL CHARACTERISTICS OF VISUAL WORKING MEMORY IN THE MONKEY FRONTOPARIETAL NETWORK

Working memory is a mental workspace which utilizes short and long-term memory to maintain and manipulate information. It is crucial in enabling cognitive control and is largely controlled by interactions within and between frontal and parietal cortices. Recent work has identified visual nonspatial, spatial, and visuospatial working memory spectral characteristics of the local field potential through simultaneous recordings from various areas across the monkey frontoparietal network. However, the reports are minimal in number, and there is no clear narrative tying together the heterogenous functionality of the characteristics. Here, a new spectral model of monkey visual working memory is proposed to address these shortcomings. It highlights functional roles for low, mid, and high frequency bands. Next, the organization of structural connectivity which gives rise to these spectral characteristics is investigated. A new binary association matrix representing connections in the frontoparietal network is proposed. A graph theoretic analysis on the matrix found that a 3-node dynamical relaying M9 motif was a fundamental building block of the network. It is optimally structured for the synchrony found in the spectral model. The network was also found to have a small-world architecture, which confers the integration and specialization of function required by visual working memory. Afterwards, three hypotheses generated by the spectral model are tested on non-spatial data. The low and mid band hypotheses were supported by evidence, while the high band hypothesized activity was not observed. This adds credibility to the roles identified in the model for the low and mid band and identifies a need for further investigation of the high band role. Finally, opportunities to expand the spectral model, analyze the M9 motif, and further test the model are explored. In the future, the spectral model could evolve to apply its predictions to humans in the pursuit of treatments for neurological disorders.