Limits...
Working memory management and predicted utility.

Chatham CH, Badre D - Front Behav Neurosci (2013)

Bottom Line: An adapted Q-learning model indicated that these costs scaled with the historical utility of individual items.Finally, model-based neuroimaging demonstrated that frontal cortex tracked the utility of items to be maintained in WM, whereas ventral striatum tracked changes in the utility of items maintained in WM to the degree that these items are no longer useful.Our findings suggest that frontostriatal mechanisms track the utility of information in WM, and that these dynamics may predict delays in the removal of information from WM.

View Article: PubMed Central - PubMed

Affiliation: Cognitive, Linguistic & Psychological Sciences, Brown University, Providence RI, USA.

ABSTRACT
Given the limited capacity of working memory (WM), its resources should be allocated strategically. One strategy is filtering, whereby access to WM is granted preferentially to items with the greatest utility. However, reallocation of WM resources might be required if the utility of maintained information subsequently declines. Here, we present behavioral, computational, and neuroimaging evidence that human participants track changes in the predicted utility of information in WM. First, participants demonstrated behavioral costs when the utility of items already maintained in WM declined and resources should be reallocated. An adapted Q-learning model indicated that these costs scaled with the historical utility of individual items. Finally, model-based neuroimaging demonstrated that frontal cortex tracked the utility of items to be maintained in WM, whereas ventral striatum tracked changes in the utility of items maintained in WM to the degree that these items are no longer useful. Our findings suggest that frontostriatal mechanisms track the utility of information in WM, and that these dynamics may predict delays in the removal of information from WM.

No MeSH data available.


BOLD responses to context vs. fixation (red-yellow) and common areas of recruitment (black outlines). Relative to fixation, each of the three conditions elicited a reliable BOLD response across frontal, parietal, and occipital cortex. Most significant frontal activation, whether medial and lateral, was observed in the left hemisphere (voxelwise z > 2.3, corrected to p < 0.05 via GRF).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3713341&req=5

Figure 4: BOLD responses to context vs. fixation (red-yellow) and common areas of recruitment (black outlines). Relative to fixation, each of the three conditions elicited a reliable BOLD response across frontal, parietal, and occipital cortex. Most significant frontal activation, whether medial and lateral, was observed in the left hemisphere (voxelwise z > 2.3, corrected to p < 0.05 via GRF).

Mentions: As a first step in assessing whether the unique behavioral effects identified in the ICR condition might also be associated with unique hemodynamic patterns, we first contrasted the BOLD response to context in the ICR, RCI, and RCR conditions with fixation. These contrasts yielded robust activity throughout a frontoparietal network (Figure 4). Consistent with prior work using 2nd order hierarchical rule tasks like this one, several regions in this network were commonly activated across all three conditions (black outlined regions of Figure 4), including intraparietal sulcus, dorsal premotor (PMd) cortex in the right hemisphere and numerous left prefrontal regions, including dorsal PMd, pre-premotor (pre-PMd), and inferior frontal sulcus (IFS).


Working memory management and predicted utility.

Chatham CH, Badre D - Front Behav Neurosci (2013)

BOLD responses to context vs. fixation (red-yellow) and common areas of recruitment (black outlines). Relative to fixation, each of the three conditions elicited a reliable BOLD response across frontal, parietal, and occipital cortex. Most significant frontal activation, whether medial and lateral, was observed in the left hemisphere (voxelwise z > 2.3, corrected to p < 0.05 via GRF).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3713341&req=5

Figure 4: BOLD responses to context vs. fixation (red-yellow) and common areas of recruitment (black outlines). Relative to fixation, each of the three conditions elicited a reliable BOLD response across frontal, parietal, and occipital cortex. Most significant frontal activation, whether medial and lateral, was observed in the left hemisphere (voxelwise z > 2.3, corrected to p < 0.05 via GRF).
Mentions: As a first step in assessing whether the unique behavioral effects identified in the ICR condition might also be associated with unique hemodynamic patterns, we first contrasted the BOLD response to context in the ICR, RCI, and RCR conditions with fixation. These contrasts yielded robust activity throughout a frontoparietal network (Figure 4). Consistent with prior work using 2nd order hierarchical rule tasks like this one, several regions in this network were commonly activated across all three conditions (black outlined regions of Figure 4), including intraparietal sulcus, dorsal premotor (PMd) cortex in the right hemisphere and numerous left prefrontal regions, including dorsal PMd, pre-premotor (pre-PMd), and inferior frontal sulcus (IFS).

Bottom Line: An adapted Q-learning model indicated that these costs scaled with the historical utility of individual items.Finally, model-based neuroimaging demonstrated that frontal cortex tracked the utility of items to be maintained in WM, whereas ventral striatum tracked changes in the utility of items maintained in WM to the degree that these items are no longer useful.Our findings suggest that frontostriatal mechanisms track the utility of information in WM, and that these dynamics may predict delays in the removal of information from WM.

View Article: PubMed Central - PubMed

Affiliation: Cognitive, Linguistic & Psychological Sciences, Brown University, Providence RI, USA.

ABSTRACT
Given the limited capacity of working memory (WM), its resources should be allocated strategically. One strategy is filtering, whereby access to WM is granted preferentially to items with the greatest utility. However, reallocation of WM resources might be required if the utility of maintained information subsequently declines. Here, we present behavioral, computational, and neuroimaging evidence that human participants track changes in the predicted utility of information in WM. First, participants demonstrated behavioral costs when the utility of items already maintained in WM declined and resources should be reallocated. An adapted Q-learning model indicated that these costs scaled with the historical utility of individual items. Finally, model-based neuroimaging demonstrated that frontal cortex tracked the utility of items to be maintained in WM, whereas ventral striatum tracked changes in the utility of items maintained in WM to the degree that these items are no longer useful. Our findings suggest that frontostriatal mechanisms track the utility of information in WM, and that these dynamics may predict delays in the removal of information from WM.

No MeSH data available.