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38 Assessing Memory for Emotions Separately from Emotion Recognition
- Gavin Sanders, Lisa J. Rapport, Robiann Broomfield, Sarah D. Patrick, Emily Flores, Robin A. Hanks, Mark A. Lumley, Scott A. Langenecker, Lauren J. Radigan
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 826-827
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- Article
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Objective:
Accurate processing of facial displays of emotion is critical for effective communication. A robust literature has documented impairment in the ability to recognize facial affect in people with traumatic brain injury (TBI), but research is scarce about memory for facial affect. Disruptions in recognizing and remembering the emotions of others can undermine relationship quality and may result in psychosocial dysfunction. Importantly, the extant literature indicates that facial affect recognition dissociates from other cognitive abilities such that it is likely a distinct neuronal process. Thus, explicit measurement of affect recognition and memory for emotions may be critical for implementing and refining rehabilitation interventions. The present study examined the relationship between recognition and memory for emotions using a novel computerized task and explored its associations with other cognitive abilities.
Participants and Methods:Participants were adults who were neurologically healthy (n = 31) or had a history of moderate to severe TBI (n = 26). The battery included the novel Assessment of Facial Affect Recognition and Memory (AFARM), Cambridge Face Memory Test (face memory without emotion), Wechsler Test of Adult Reading, Rey Auditory Verbal Learning Test, Judgment of Line Orientation, Oral Symbol Digit Modalities, Digit Span, FAS, Animal Fluency, and the Affect Intensity Measure (experienced emotion). Spearman correlations examined the relationship of AFARM performance with the test battery. Logistic regression models examined whether immediate-delay (ID-EM) and long-delay face emotion-memory (LD-EM) accounted for unique variance in group membership beyond recognition accuracy of facial affect and memory for faces.
Results:AFARM demonstrated relationships with neuropsychological and mood variables in the expected directions across and within groups, with the strongest associations observed for memory for verbal information (rs = .51 to .58) and processing speed (rs = .48 to .57). Consistent with traditional list-learning tests, ID- and LD-EM were highly correlated (r = .85). Experienced affect intensity was inversely associated with ID-EM (r = -.29) and LD-EM (r = -.38) but not with recognition accuracy (r = -.10). Logistic regression examining ID-EM was significant, χ2(3) = 26.05, p < .001, Nagelkerke R2 = .49. ID-EM accounted for unique variance in group status (p = .006; OR = 0.65) after accounting for recognition accuracy and face memory. Similarly, the model examining LD-EM was significant χ2(3) = 27.70, p < .001, Nagelkerke R2 = .43; LD-EM was significant after accounting for other variables (p = .017; OR = 0.69).
Conclusions:The findings are consistent with the hypothesis that memory for emotions represents a unique component of social cognition that is separate from recognition. Accuracy in identifying emotions, face recognition memory, and memory for emotions are strongly related but not wholly redundant processes. Consistent with prior literature, subjective experience of emotion had substantial effects on objective performance tasks, indicating that an individual's intense experience of their own emotions can disrupt sensitivity to the emotions of others. Future research should assess the extent to which memory for emotions relates to psychosocial outcomes such as the quality and quantity of interpersonal relationships.
Lateral Resolution Enhancement of Vertical Scanning Interferometry by Sub-Pixel Sampling
- Rolf S. Arvidson, Cornelius Fischer, Dale S. Sawyer, Gavin D. Scott, Douglas Natelson, Andreas Lüttge
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- Journal:
- Microscopy and Microanalysis / Volume 20 / Issue 1 / February 2014
- Published online by Cambridge University Press:
- 07 January 2014, pp. 90-98
- Print publication:
- February 2014
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We apply common image enhancement principles and sub-pixel sample positioning to achieve a significant enhancement in the spatial resolution of a vertical scanning interferometer. We illustrate the potential of this new method using a standard atomic force microscope calibration grid and other materials having motifs of known lateral and vertical dimensions. This approach combines the high vertical resolution of vertical scanning interferometry and its native advantages (large field of view, rapid and nondestructive data acquisition) with important increases in lateral resolution. This combination offers the means to address a common challenge in microscopy: the integration of properties and processes that depend on, and vary as a function of observational length.
Contributors
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- By Douglas L. Arnold, Laura J. Balcer, Amit Bar-Or, Sergio E. Baranzini, Frederik Barkhof, Robert A. Bermel, Francois A. Bethoux, Dennis N. Bourdette, Richard K. Burt, Peter A. Calabresi, Zografos Caramanos, Tanuja Chitnis, Stacey S. Cofield, Jeffrey A. Cohen, Nadine Cohen, Alasdair J. Coles, Devon Conway, Stuart D. Cook, Gary R. Cutter, Peter J. Darlington, Ann Dodds-Frerichs, Ranjan Dutta, Gilles Edan, Michelle Fabian, Franz Fazekas, Massimo Filippi, Elizabeth Fisher, Paulo Fontoura, Corey C. Ford, Robert J. Fox, Natasha Frost, Alex Z. Fu, Siegrid Fuchs, Kazuo Fujihara, Kristin M. Galetta, Jeroen J.G. Geurts, Gavin Giovannoni, Nada Gligorov, Ralf Gold, Andrew D. Goodman, Myla D. Goldman, Jenny Guerre, Stephen L. Hauser, Peter B. Imrey, Douglas R. Jeffery, Stephen E. Jones, Adam I. Kaplin, Michael W. Kattan, B. Mark Keegan, Kyle C. Kern, Zhaleh Khaleeli, Samia J. Khoury, Joep Killestein, Soo Hyun Kim, R. Philip Kinkel, Stephen C. Krieger, Lauren B. Krupp, Emmanuelle Le Page, David Leppert, Scott Litwiller, Fred D. Lublin, Henry F. McFarland, Joseph C. McGowan, Don Mahad, Jahangir Maleki, Ruth Ann Marrie, Paul M. Matthews, Francesca Milanetti, Aaron E. Miller, Deborah M. Miller, Xavier Montalban, Charity J. Morgan, Ichiro Nakashima, Sridar Narayanan, Avindra Nath, Paul W. O’Connor, Jorge R. Oksenberg, A. John Petkau, Michael D. Phillips, J. Theodore Phillips, Tammy Phinney, Sean J. Pittock, Sarah M. Planchon, Chris H. Polman, Alexander Rae-Grant, Stephen M. Rao, Stephen C. Reingold, Maria A. Rocca, Richard A. Rudick, Amber R. Salter, Paula Sandler, Jaume Sastre-Garriga, John R. Scagnelli, Dana J. Serafin, Lynne Shinto, Nancy L. Sicotte, Jack H. Simon, Per Soelberg Sørensen, Ryan E. Stagg, James M. Stankiewicz, Lael A. Stone, Amy Sullivan, Matthew Sutliff, Jessica Szpak, Alan J. Thompson, Bruce D. Trapp, Helen Tremlett, Maria Trojano, Orla Tuohy, Rhonda R. Voskuhl, Marc K. Walton, Mike P. Wattjes, Emmanuelle Waubant, Martin S. Weber, Howard L Weiner, Brian G. Weinshenker, Bianca Weinstock-Guttman, Jeffrey L. Winters, Jerry S. Wolinsky, Vijayshree Yadav, E. Ann Yeh, Scott S. Zamvil
- Edited by Jeffrey A. Cohen, Richard A. Rudick
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- Book:
- Multiple Sclerosis Therapeutics
- Published online:
- 05 December 2011
- Print publication:
- 20 October 2011, pp viii-xii
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