The role of causal network interactions in the retention of information in working memory: An empirical and theoretical investigation

North Dakota State University, Fargo ND

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Abstract

DESCRIPTION (provided by applicant): Working memory (WM) is a core psychological construct that plays a central role in everyday activities, from relatively simple tasks such as th temporary retention of task-relevant information, to the manipulation and use of this information in complex cognitive tasks and in the control and guidance of adaptive behaviors. Additionally, an individual's ability to retain and manipulate information in WM has been shown to be an important factor underlying individual differences across a broad spectrum of experimental and real world measures, and WM dysfunction has been strongly implicated in the cognitive deficits observed in psychiatric illnesses, most notably schizophrenia. A prominent theme in current cognitive neuroscience research is the idea that WM is supported by causal interactions between specialized brain areas linked together into functional networks. However, much of the evidence supporting this proposal has come from functional connectivity analysis of neural data (fMRI, PET, EEG), which gives a correlational rather than causal indication of the functional properties of particular brain areas, and of how network interactions might support cognition. Furthermore, a causal and mechanistic description of how causal network interactions give rise to WM functions is lacking. The proposed research addresses these issues using non-invasive brain stimulation (TMS), and neural recording (EEG) to directly probe causal interregional interactions during retention in WM, and neurally plausible modeling to provide a mechanistic description of how such interactions vary as a function of cognitive state changes. Specific Aim 1 uses combined TMS-EEG to clarify the role of causal interactions between frontal and posterior brain areas in the short-term retention of visual information. Prior work has suggested a general role for the prefrontal cortex (PFC) in the top-down control of activity in posterior sensory areas. Although the PFC has been shown to regulate WM maintenance by filtering out distracting information, PFC activation and increased frontal-posterior connectivity in the absence of distraction suggests that such interactions might also be involved in pure storage functions. This possibility will be examined by stimulating the frontal cortex during the retention of information in WM and recording the resulting response, both within the stimulated area and at distal cortical sites, using EEG. If frontal-posterior functional interactions play a direct rol in maintenance, we expect the strength of connectivity to increase with the amount of information being held in WM. Similarly, we expect to observe systematic changes in the spatial spread of TMS-evoked activations to posterior brain areas when the PFC is stimulated during the delay period of tasks requiring the storage of information that is coded in distinct posterior brain area. Specific Aim 2 will use an existing neural model of WM and change detection to implement a systems-level model of connectivity that can capture EEG signatures of WM maintenance and account for the observed state-dependence of TMS/EEG expected in Aim 1. Establishing this link between neural modeling and TMS/EEG will lay the groundwork for future work aimed at formally testing different predictions regarding how causal network interactions support WM and other cognitive functions, and will provide a basis for examining possible aberrant network interactions underlying the symptoms of debilitating mental illnesses, such as schizophrenia.