Allen, John (2018) Distraction by unintentional recognition: Neurocognitive mechanisms and modulations by ageing. Master of Research (MRes) thesis, University of Kent,. (KAR id:72254)
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Abstract
Previous research has suggested that aging is associated with increased distractibility and
impaired intentional retrieval processes. I investigated potential age differences in the
effect of unintentional recognition of to-be-ignored distractor images on intentional
recognition decisions to targets words, and the brain processes that are associated with
unintentional versus intentional recognition. This research involved comparing old (60-76)
and young (18-24) adults' performance and brain activity during a Memory Stroop task,
analysing behavioural data (accuracy and reaction times), event-related potentials (ERPs)
and induced and evoked EEG oscillations in the theta and alpha bands. At the behavioural
level, the older group exhibited the expected poorer intentional recognition memory for
targets, but the biasing effect of unintentional distractor recognition on target decisions was
very similar across age groups. In the ERP domain, the older group showed much reduced
or absent ERP effects related to 'familiarity' and 'recollection' that were strongly
expressed in the younger group. Furthermore, the older group showed a reversal of typical
old/new ERP effects for targets, suggesting that they engaged a qualitatively different
neurocognitive process during intentional recognition. This effect may reflect a
compensatory mechanism that is used as part of an adaptive strategy to address age-related
declines in the brain processes used by young adults to solve the task. However, broadly
similar patterns of old/new differences in theta and alpha power were found across both
age groups for both intentional target recognition and unintentional distractor recognition.
Overall, the results show novel evidence of how the neural correlates of recognition
memory are affected by aging and intentionality, and suggest that future research should
employ both ERP and oscillation analysis of EEG data to better understand neurocognitive
aging.
Item Type: | Thesis (Master of Research (MRes)) |
---|---|
Thesis advisor: | Bergstrom, Zara |
Uncontrolled keywords: | Memory, Recognition, Ageing, ERP, Brain oscillations, Alpha, Theta |
Divisions: | Divisions > Division of Human and Social Sciences > School of Psychology |
SWORD Depositor: | System Moodle |
Depositing User: | System Moodle |
Date Deposited: | 08 Feb 2019 13:10 UTC |
Last Modified: | 05 Nov 2024 12:34 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/72254 (The current URI for this page, for reference purposes) |
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