Poster No:
909
Submission Type:
Abstract Submission
Authors:
SANCHITA MOHINDRU1, Bhoomika Kar1
Institutions:
1Centre of Behavioural and Cognitive Sciences, University of Allahabad, Prayagraj, Uttar Pradesh
First Author:
Sanchita Mohindru, Ms.
Centre of Behavioural and Cognitive Sciences, University of Allahabad
Prayagraj, Uttar Pradesh
Co-Author:
Bhoomika Kar, Prof
Centre of Behavioural and Cognitive Sciences, University of Allahabad
Prayagraj, Uttar Pradesh
Introduction:
Positivity effect (explained by Socio-emotional selectivity theory and Aging Brain Model) and increased motivation for emotion regulation is associated with benefits in aging. These benefits are aided by socioemotional context, which is prioritized in old age. Adults invest more cognitive/social resources on emotionally meaningful information as they grow older. Such emotional regulation motivation is associated with cognitive flexibility, which may decline with age. Age-related reductions in gray matter volume (GMV) in areas critical for emotional processing may affect emotion regulation. This may come as a cost for the available cognitive resource, or an outcome of the depletion in neural/cognitive resources. We investigated the association between GMV changes and the effect of task-irrelevant emotional stimuli (positive/negative/neutral) on task-switching across lifespan. Reduced switch-costs in the context of positive emotional stimuli were hypothesized in middle-aged and older adults despite age-related reductions in GMV in regions associated with cognitive/emotional regulation.
Methods:
A total of 102 participants (screened using MMSE and ACE) (Young(YA): N=37, 20 females, Mean age (MN): 24 years; Middle-aged(MA): N=35, 15 Females, MN: 46 years; Older adults(OA): N=30, 12 Females, MN: 62 years) performed a color-shape switching task (50-50 proportion of switch/no-switch trials) with and without task-irrelevant emotional stimuli (pleasant, unpleasant, neutral IAPS images) outside the scanner. Reaction time (RT) data was analyzed (age x trial-type) for the baseline switch-cost and to examine the effect of emotional stimuli on switch-cost (age x trial-type x valence). The T1-weighted high-resolution image with 2mm x2mm x 2mm voxel-size was acquired using SEIMENS 3T-Skyra scanner at the National Neuroimaging Facility, University of Allahabad. A 10-minute resting-state scan was acquired (T2*weighted images using EPI: TR=2000ms, TE=30ms, Flip angle=90°, FOV=224mm×224mm, 64×64matrix, 32axial slices of 4.5mm each).
Results:
Behavioural results suggest comparable baseline switch-costs across age groups, however task irrelevant emotional stimuli modulated the switch-costs. Age x trial-type x emotion interaction was significant [F(4,102)=4.077, p=0.003, η2p=0.074]. Switch RTs were higher in the context of positive compared to negative images across age. YA showed higher switch RTs compared to no-switch in the context of positive and negative images. In MA and OA, this effect was observed only for positive emotional stimuli which showed facilitatory effect on task switching with age.
We performed voxel-based morphometry (VBM) analysis using the Computational Anatomy Toolbox v12 (SPM12) to investigate regional and global brain volume differences among the three age groups (N=96) using 3D T1-weighted MRI data. GMV changes were observed in terms of total brain volume, GMV, white matter volume and cortical thickness. GMV (left medial temporal gyrus, right medial superior frontal gyrus, left posterior insula, right supramarginal gyrus and cerebral white matter) decreased with increasing age and was found to be associated with switch-costs in the context of emotional stimuli. In the YA, GMV was inversely correlated with the baseline and positive emotion switch-costs. In MA, GMV was inversely correlated with baseline switch-costs and was positively correlated with switch-costs in the context of positive emotional stimuli in case of OA. This brain-behaviour correlation can be substantiated with resting state connectivity.

·Figure 1: Global Brain Volume Changes across Age

·Figure 2: Region-specific Changes in Gray Matter Volume across Age
Conclusions:
GMV of the regions responsive to emotion regulation (SFG, MSFG, Insula) correlated with cognitive flexibility in the context of emotional stimuli. YA and MA showed a correlation between cognitive flexibility (non-emotional) and GMV in brain regions specific to attentional control (MFG, SFG, SMG and MTG). We find evidence for positivity effect despite gray matter volume reductions in older adults supporting the notion of affective reserve.
Emotion, Motivation and Social Neuroscience:
Emotion and Motivation Other 2
Higher Cognitive Functions:
Higher Cognitive Functions Other
Lifespan Development:
Aging 1
Novel Imaging Acquisition Methods:
Anatomical MRI
Imaging Methods Other
Keywords:
Aging
Cognition
Development
Emotions
Experimental Design
Morphometrics
MRI
STRUCTURAL MRI
Other - Task-switching
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Other
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Healthy subjects
Was this research conducted in the United States?
No
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
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Yes
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Not applicable
Please indicate which methods were used in your research:
Structural MRI
Behavior
Neuropsychological testing
Other, Please specify
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Behavioural experiment
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
SPM
Other, Please list
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Computational Anatomy Toolbox (CAT12)
Provide references using APA citation style.
1. Cacioppo, J.T., Bernston, G.G., Bechara, A., Tranel, D., Hawkley, L.C., 2011. Could an aging brain contribute to subjective well-being? The value added by a social neuroscience perspective. In: Todorov, A., Fiske, S.T., Prentice, D.A. (Eds.), Social Neuroscience: Toward Understanding the Underpinnings of the Social Mind. Oxford University Press.
2. Carstensen, L. L. (1995). Evidence for a life-span theory of socioemotional selectivity. Current directions in Psychological science, 4(5), 151-156.
3. Carstensen, L. L., Fung, H. H., & Charles, S. T. (2003). Socioemotional selectivity theory and the regulation of emotion in the second half of life. Motivation and emotion, 27, 103-123.
4. Di Rosa, E. (2024). Affective reserve: A new reserve concept we should talk about. PLOS Mental Health, 1(2), e0000083.
5. Farb, N. A. S., Anderson, A. K., and Segal, Z. V. (2012). The mindful brain and emotion regulation in mood disorders. Can. J. Psychiatry 57, 70–77.
6. Farb, N., Daubenmier, J., Price, C. J., Gard, T., Kerr, C., Dunn, B. D., ... & Mehling, W. E. (2015). Interoception, contemplative practice, and health. Frontiers in psychology, 6, 118347.
7. Mather M, Cartstensen LL (2005) Aging and motivated cognition: the positivity effect in attention and memory. Trends Cogn Sci 9:496–502.
8. Mohindru, S., Nigam, R., & Kar, B. R. (2023). Cognitive and Emotional Aging Across the Life Span: Implications for Building the Cognitive Reserve and Resilience. In Emerging Anti-Aging Strategies (pp. 287-309). Singapore: Springer Nature Singapore.
9. Scheibe, S., & Carstensen, L. L. (2010). Emotional aging: Recent findings and future trends. The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 65, 135–144. doi:10.1093/geronb/gbp132.
10. Wheeler, M. S., Arnkoff, D. B., & Glass, C. R. (2017). The neuroscience of mindfulness: How mindfulness alters the brain and facilitates emotion regulation. Mindfulness, 8(6), 1471-1487.
Yes
Please select the country that the first author on this abstract resides and works in from the UNESCO Institute of Statistics and World Bank List of Low and Middle Income Countries (based on gross national income per capita).
India