Exploring the relationship between resting fMRI and proactive interference in ageing
Poster No:
933
Submission Type:
Abstract Submission
Authors:
Pernilla Andersson1, Martien Schrooten1, Jonas Persson2
Institutions:
1Örebro university, Örebro, Sweden, 2Karolinska Institutet, Stockholm, Sweden
First Author:
Co-Author(s):
Introduction:
Proactive interference (PI) occurs when old information interferes with newly acquired information and has been suggested as a major source of forgetting in working memory (Oberauer, 2008). Research shows that the ability to overcome PI declines with increasing age (Loosli, 2014; Samrani, 2021). Evidence suggests that a network consisting of the inferior frontal gyrus (IFG), the striatum, and the anterior cingulum underlie the ability to resolve PI in working memory (Persson, 2013; Samrani, 2019). However, the mechanisms underlying age-related decline in this ability are not yet fully understood. In this study, we investigated, in an adult lifespan sample (N = 239), how resting state functional connectivity (rsFC) relates to the ability to resolve PI in working memory, using seed-based(bilateral IFG) analysis as a function of aging.
Methods:
The study sample consisted of 132 younger/ middle-aged (25-64 years) and 107 older (65-80 years) adult participants at baseline, and 93 younger/ middle-aged and 63 older adults at follow-up. All included participants were cognitively healthy (MMSE above 24 and no neurological condition) across the two timepoints.
PI was assessed using a modified N-back task, designed to induce interference. This version of the task includes non-familiar no-trials (new), target yes-trials, and familiar no-trials (lures). PI scores reflect the combined relative proportional difference in RT and accuracy between new trials and lure trials.
FMRI data were processed and analyzed using CONN (v.22a). Preprocessing followed the standard pipeline in CONN. Seed-based analyses were conducted (bilateral IFG) to investigate the effects of age, PI, and age group × PI interaction, respectively, on rsFC strength. All analyses were conducted cross-sectionally and longitudinally.
PI was assessed using a modified N-back task, designed to induce interference. This version of the task includes non-familiar no-trials (new), target yes-trials, and familiar no-trials (lures). PI scores reflect the combined relative proportional difference in RT and accuracy between new trials and lure trials.
FMRI data were processed and analyzed using CONN (v.22a). Preprocessing followed the standard pipeline in CONN. Seed-based analyses were conducted (bilateral IFG) to investigate the effects of age, PI, and age group × PI interaction, respectively, on rsFC strength. All analyses were conducted cross-sectionally and longitudinally.
Results:
Cross-sectional analyses revealed a significant, positive cluster related to PI across the whole sample centered in the right putamen. Additionally, age group × PI interactions identified three clusters These clusters were centered in the right inferior occipital cortex (rIOC; 5420 voxels; MNI: +50 -82 -02), the right precentral gyrus (rPCG; 2809 voxels; MNI: +34 -12 +66), and the right caudate (rC; 1974 voxels; MNI: +16 +22 +02), respectively. Interestingly, more PI was associated with more rsFC between the IFG and the rIOC and rPCG clusters in older adults but with less rsFC in younger/middle-aged adults. Similarly, more PI correlated with less rsFC between the IFG and the rC cluster in older but more rsFC in younger/middle-aged adults. Longitudinal analyses did not reveal any significant clusters.
·A: IFG seed region (left) and effect sizes- B: Heat maps (left) and scatter plots (right) depicting PI x rsFC interaction for rIOC (top), rPCG (middle), and rC (bottom) clusters.
Conclusions:
The present results demonstrate an association between IFG rsFC and PI. The association between more PI and more IFG – rPCG rsFC may be related to age-related overactivation in this region during cognitive control processing in working memory updating, which is related to worse performance (Qin, 2020). Previous studies have also found that connections between the ventrolateral prefrontal cortex (located on the IFG) and the caudate is important in working memory updating and that older adults show reduced coupling between these regions together with reduced performance (Podell, 2012). This connection may reflect inhibitory control processing involved in successfully resolving PI during working memory updating. The observed association between more PI and less IFG – rC rsFC in the present study may, thus, reflect reduced inhibitory control.
While the rIOC has primarily been associated with visual working memory, especially concerning faces, this cluster was very large and also included large portions of the cerebellum. The cerebellum has been suggested to contribute to verbal working memory by predicting future material in the phonological loop (Sheu, 2019).
Taken together, the results contribute to the understanding of decreased control of PI in aging by showing that rsFC is differentially associated with PI in older as compared with younger/middle-aged adults.
While the rIOC has primarily been associated with visual working memory, especially concerning faces, this cluster was very large and also included large portions of the cerebellum. The cerebellum has been suggested to contribute to verbal working memory by predicting future material in the phonological loop (Sheu, 2019).
Taken together, the results contribute to the understanding of decreased control of PI in aging by showing that rsFC is differentially associated with PI in older as compared with younger/middle-aged adults.
Higher Cognitive Functions:
Executive Function, Cognitive Control and Decision Making 1
Learning and Memory:
Working Memory
Lifespan Development:
Aging 2
Modeling and Analysis Methods:
Task-Independent and Resting-State Analysis
Novel Imaging Acquisition Methods:
BOLD fMRI
Keywords:
Aging
FUNCTIONAL MRI
Other - proactive interference; working memory; resting state; functional connectivity; inferior frontal gyrus
1|2Indicates the priority used for review
Provide references using author date format
Oberauer, K.(2008). 'Forgetting in immediate serial recall: decay, temporal distinctiveness, or interference?', Psychological review, 115(3), 544–576. https://doi.org/10.1037/0033-295X.115.3.544
Persson, J. (2013). 'Imaging Fatigue of Interference Control Reveals the Neural Basis of Executive Resource Depletion', Journal of Cognitive Neuroscience, 25(3), 338-351.
Podell, J. E., (2012) 'Neurophysiological correlates of age-related changes in working memory updating', Neuroimage. 2012 Sep;62(3):2151-60. doi: 10.1016/j.neuroimage.2012.05.066.
Samrani, G. (2019). 'Interference Control in Working Memory Is Associated with Ventrolateral Prefrontal Cortex Volume', Journal of Cognitive Neuroscience, 31(10), 1491-1505.
Samrani, G. (2021). 'Proactive interference in working memory is related to adult age and cognitive factors: cross-sectional and longitudinal evidence from the Betula study', Neuropsychology, Development and Cognition. Section B Aging, Neuropsychology and Cognition, 28(1), 108-127.
Sheu, Y. S., (2019). 'Disruption of Cerebellar Prediction in Verbal Working Memory', Frontiers in human neuroscience, 13, 61. https://doi.org/10.3389/fnhum.2019.00061
Qin, S. (2020). 'Age-related differences in brain activation during working memory updating: An fMRI study', Neuropsychologia, 138, 107335. https://doi.org/10.1016/j.neuropsychologia.2020.107335