Background
Working memory (hereafter abbreviated as WM) is a limited capacity system responsible for maintaining and manipulating information necessary for task completion (Baddeley, 1974; 1986). This summer, we will examine a major limitation of WM capacity as well as the selection of items held within WM. In collaboration with a clinical psychology lab, we will also begin to examine WM in the context of major depressive disorder (MDD). Both lines of research will utilize behavioral and fMRI methods.
Though this conception is not undisputed (See, Bays & Husain, 2008), the capacity of WM is commonly discussed in terms of the number of items (Fukuda et al. 2010), with current estimates placing WM capacity at approximately four items (Cowan, 2001). Because WM has such a limited capacity, it is important that its contents be updated efficiently. Interference from previously relevant material, known as proactive interference (PI), is thought to be one of the major limiting factors in WM capacity (Jonides &a Nee, 2006). Attention-based processes that result in the selection of relevant material represent a method for overcoming PI (Oberauer, 2001). Our lab has previously examined the behavioral and neural correlates of PI (Yi et al., 2009) and WM selection (Oh & Leung, 2010). The goal of our research this summer is to examine the relationship between PI and WM selection.
Summer Research Plan
For all our experiments, we will utilize a delayed recognition paradigm with a selection cue inserted during the delay period. For each trial, subjects will be shown (and asked to remember) a series of 2 stimuli. After a brief delay, a cue will indicate to remember either a specific stimuli from this series or the entire set for the remainder of the trial. Following another delay, a probe item will be presented. Upon presentation of the probe, subjects will be asked to identify if the probe stimuli is the same (or not the same) as the stimuli or set of stimuli specified by the cue. Response accuracy and reaction time (RT) measurements will be taken for each trial. Trials with cues specifying to remember 1 item (WM selection) will be compared to trials specifying to remember both items (no selection). In order to measure PI, trials with highly familiar probe items (i.e. non-selected items from the initial stimulus set) will be compared to trials with less familiar probe items. In separate experiments, we will study the effect of the selection cue on holding faces, outdoor scenes, and words to determined in WM selection and PI behaviors are similar across stimuli-type. In preparation for our MDD project, we will conduct a separate series of experiments, using the same paradigm, using emotional stimuli.
Based on previous research, we expect to see a facilitation effect for selected items. Behaviorally, such an effect would manifest as higher accuracy and lower reaction time for selected items. Due to PI, highly familiar probes are expected to be associated with lower accuracy and higher RT than less familiar probes. In terms of fMRI results, previous work in our lab has found that both WM selection and PI are associated with activity in prefrontal and parietal regions (Yi et al., 2009; Oh & Leung, 2010). Similar patterns of activation are expected in the present study, though our analysis will focus on examining the processes together rather than independently.
In parallel to our research into the relationship between WM selection and PI, we will also begin a line of work focused on understanding these (and other) behaviors in the context of major depressive disorder (MDD). Though MDD is primarily considered an emotional condition, it is accompanied by a constellation of cognitive deficits including increased interference from negatively valenced material (For review, see Gotlib & Joorman, In Press). Recent work suggests that MDD may be associated with increased interference in WM regardless of stimuli valence (Joorman et al., 2010). Previous work has focused mainly on the ruminative aspects of WM interference (See Thomas & Elliot, 2009). In contrast, our work will focus on examining this interference from a cognitive neuroscience perspective. We will utilize non-emotional stimuli and a paradigm specifically designed to examine WM selection both behaviorally and neurally (Oh & Leung, 2009).
Summary
Because proactive interference represents a major limiting factor in working memory capacity and WM selection represents a method for overcoming PI, we feel that it is important to understand the behavioral and neural correlates of the interaction between WM selection and PI. Aside from providing additional insight into how and why WM is limited, this work also has significance for understanding a thus far under-researched aspect of pathologies that compromise WM capacity, such as major depressive disorder.
Works Cited Listed in Comments
Working memory (hereafter abbreviated as WM) is a limited capacity system responsible for maintaining and manipulating information necessary for task completion (Baddeley, 1974; 1986). This summer, we will examine a major limitation of WM capacity as well as the selection of items held within WM. In collaboration with a clinical psychology lab, we will also begin to examine WM in the context of major depressive disorder (MDD). Both lines of research will utilize behavioral and fMRI methods.
Though this conception is not undisputed (See, Bays & Husain, 2008), the capacity of WM is commonly discussed in terms of the number of items (Fukuda et al. 2010), with current estimates placing WM capacity at approximately four items (Cowan, 2001). Because WM has such a limited capacity, it is important that its contents be updated efficiently. Interference from previously relevant material, known as proactive interference (PI), is thought to be one of the major limiting factors in WM capacity (Jonides &a Nee, 2006). Attention-based processes that result in the selection of relevant material represent a method for overcoming PI (Oberauer, 2001). Our lab has previously examined the behavioral and neural correlates of PI (Yi et al., 2009) and WM selection (Oh & Leung, 2010). The goal of our research this summer is to examine the relationship between PI and WM selection.
Summer Research Plan
For all our experiments, we will utilize a delayed recognition paradigm with a selection cue inserted during the delay period. For each trial, subjects will be shown (and asked to remember) a series of 2 stimuli. After a brief delay, a cue will indicate to remember either a specific stimuli from this series or the entire set for the remainder of the trial. Following another delay, a probe item will be presented. Upon presentation of the probe, subjects will be asked to identify if the probe stimuli is the same (or not the same) as the stimuli or set of stimuli specified by the cue. Response accuracy and reaction time (RT) measurements will be taken for each trial. Trials with cues specifying to remember 1 item (WM selection) will be compared to trials specifying to remember both items (no selection). In order to measure PI, trials with highly familiar probe items (i.e. non-selected items from the initial stimulus set) will be compared to trials with less familiar probe items. In separate experiments, we will study the effect of the selection cue on holding faces, outdoor scenes, and words to determined in WM selection and PI behaviors are similar across stimuli-type. In preparation for our MDD project, we will conduct a separate series of experiments, using the same paradigm, using emotional stimuli.
Based on previous research, we expect to see a facilitation effect for selected items. Behaviorally, such an effect would manifest as higher accuracy and lower reaction time for selected items. Due to PI, highly familiar probes are expected to be associated with lower accuracy and higher RT than less familiar probes. In terms of fMRI results, previous work in our lab has found that both WM selection and PI are associated with activity in prefrontal and parietal regions (Yi et al., 2009; Oh & Leung, 2010). Similar patterns of activation are expected in the present study, though our analysis will focus on examining the processes together rather than independently.
In parallel to our research into the relationship between WM selection and PI, we will also begin a line of work focused on understanding these (and other) behaviors in the context of major depressive disorder (MDD). Though MDD is primarily considered an emotional condition, it is accompanied by a constellation of cognitive deficits including increased interference from negatively valenced material (For review, see Gotlib & Joorman, In Press). Recent work suggests that MDD may be associated with increased interference in WM regardless of stimuli valence (Joorman et al., 2010). Previous work has focused mainly on the ruminative aspects of WM interference (See Thomas & Elliot, 2009). In contrast, our work will focus on examining this interference from a cognitive neuroscience perspective. We will utilize non-emotional stimuli and a paradigm specifically designed to examine WM selection both behaviorally and neurally (Oh & Leung, 2009).
Summary
Because proactive interference represents a major limiting factor in working memory capacity and WM selection represents a method for overcoming PI, we feel that it is important to understand the behavioral and neural correlates of the interaction between WM selection and PI. Aside from providing additional insight into how and why WM is limited, this work also has significance for understanding a thus far under-researched aspect of pathologies that compromise WM capacity, such as major depressive disorder.
Works Cited Listed in Comments
1 comment:
Baddeley, A.D. (1986). Working Memory, Oxford: Oxford University Press
Baddeley, A. D., Hitch, G. J. (1974) Working memory. In: The psychology of learning and motivation, vol. 8: Advances in Research and Theory, ed. G. A. Bower. Academic Press.
Bays, P.M. & Husain, M. (2008). Dynamic shifts of limited working memory resources in human vision. Science, 321, 8510854.
Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24, 87-185.
Fukuda, K., Awh, E., & Vogel, E.K. (2010). Discrete limits in visual working memory. Current Opinion in Neurobiology, 20, 177-182.
Jonides, J. and Nee, D.E. (2006). Brain mechanisms of proactive interference in working memory. Neuroscience, 139, 181-193.
Gotlib, I.H., & Joormann, J. (In Press). Cognition and depression: Current status and future directions. Annual Review of Clinical Psychology
Joormann, J. & Gotlib, I.H. (2008). Updating the contents of working memory in depression: Interference from irrelevant negative material. Journal of Abnormal Psychology, 117, 206-213.
Joorman, J., Nee, D.E., Berman, B.G., Jonides, J., Gotlib, I.H. (2010). Interference resolution in major depression. Cognitive Affective and Behavioral Neuroscience, 10, 21-33.
Oberauer, K. (2001). Removing irrelevant information from working memory. A cognitive aging study with the modified Sternberg task. Journal of Experimental Psychology: Learning, Memory, and Cognition, 27, 948-957.
Oh, H. & Leung, H-C. (2010). Specific and non-specific neural activity during selective processing of visual representations in working memory. Journal of Cognitive Neuroscience, 22, 292-306.
Thomas, E.J., Elliot, R. (2009) Brain imaging correlates of cognitive impairment in depression, Frontiers in Human Neuroscience, 3, 1-9.
Yi, Y. Driesen, N., Leung, H-C. (2009). Behavioral and neural correlates of memory selection and interference resolution during a digit working memory task. Cognitive Affective and Behavioral Neuroscience, 9, 249-259.
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