16 research outputs found

    Differential brain activity during emotional versus nonemotional reversal learning

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    The ability to change an established stimulus–behavior association based on feedback is critical for adaptive social behaviors. This ability has been examined in reversal learning tasks, where participants first learn a stimulus–response association (e.g., select a particular object to get a reward) and then need to alter their response when reinforcement contingencies change. Although substantial evidence demonstrates that the OFC is a critical region for reversal learning, previous studies have not distinguished reversal learning for emotional associations from neutral associations. The current study examined whether OFC plays similar roles in emotional versus neutral reversal learning. The OFC showed greater activity during reversals of stimulus–outcome associations for negative outcomes than for neutral outcomes. Similar OFC activity was also observed during reversals involving positive outcomes. Furthermore, OFC activity is more inversely correlated with amygdala activity during negative reversals than during neutral reversals. Overall, our results indicate that the OFC is more activated by emotional than neutral reversal learning and that OFC's interactions with the amygdala are greater for negative than neutral reversal learning

    Age-related similarities and differences in brain activity underlying reversal learning

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    The ability to update associative memory is an important aspect of episodic memory and a critical skill for social adaptation. Previous research with younger adults suggests that emotional arousal alters brain mechanisms underlying memory updating; however, it is unclear whether this applies to older adults. Given that the ability to update associative information declines with age, it is important to understand how emotion modulates the brain processes underlying memory updating in older adults. The current study investigated this question using reversal learning tasks, where younger and older participants (age ranges 19-35 and 61-78 respectively) learn a stimulus–outcome association and then update their response when contingencies change. We found that younger and older adults showed similar patterns of activation in the frontopolar OFC and the amygdala during emotional reversal learning. In contrast, when reversal learning did not involve emotion, older adults showed greater parietal cortex activity than did younger adults. Thus, younger and older adults show more similarities in brain activity during memory updating involving emotional stimuli than during memory updating not involving emotional stimuli

    Resting-state networks associated with cognitive processing show more age-related decline than those associated with emotional processing

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    Correlations in activity across disparate brain regions during rest reveal functional networks in the brain. Although previous studies largely agree that there is an age-related decline in the “default mode network,” how age affects other resting-state networks, such as motion-related networks, is still controversial. Here we used a dual regression approach to investigate age-related alterations in resting-state networks. The results revealed age-related disruptions in functional connectivity in all five identified cognitive networks, namely the default mode network, cognitive-auditory, cognitive-speech (or speech-related somatosensory) and right and left fronto-parietal networks, whereas such age effects were not observed in the three identified emotion networks. In addition, we observed age-related decline in functional connectivity in three visual and three motor/visuospatial networks. Older adults showed greater functional connectivity in regions outside four out of the five identified cognitive networks, consistent with the dedifferentiation effect previously observed in task-based fMRI studies. Both reduced within-network connectivity and increased out-of-network connectivity were correlated with poor cognitive performance, providing potential biomarkers for cognitive aging

    Effects of a randomised trial of 5-week heart rate variability biofeedback intervention on mind wandering and associated brain function

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    Previous research suggests that excessive negative self-related thought during mind wandering involves the default mode network (DMN) core subsystem and the orbitofrontal cortex (OFC). Heart rate variability (HRV) biofeedback, which involves slow paced breathing to increase HRV, is known to promote emotional well-being. However, it remains unclear whether it has positive effects on mind wandering and associated brain function. We conducted a study where young adults were randomly assigned to one of two 5-week interventions involving daily biofeedback that either increased heart rate oscillations via slow paced breathing (Osc+ condition) or had little effect on heart rate oscillations (active control or Osc- condition). The two intervention conditions did not differentially affect mind wandering and DMN core-OFC functional connectivity. However, the magnitude of participants’ heart rate oscillations during daily biofeedback practice was associated with pre-to-post decreases in mind wandering and in DMN core-OFC functional connectivity. Furthermore, the reduction in the DMN core-OFC connectivity was associated with a decrease in mind wandering. Our results suggested that daily sessions involving high amplitude heart rate oscillations may help reduce negative mind wandering and associated brain function.</p

    Age differences in brain activity during emotion processing: reflections of age-Related decline or increased emotion regulation?

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    Despite the fact that physical health and cognitive abilities decline with aging, the ability to regulate emotion remains stable and in some aspects improves across the adult life span. Older adults also show a positivity effect in their attention and memory, with diminished processing of negative stimuli relative to positive stimuli compared with younger adults. The current paper reviews functional magnetic resonance imaging studies investigating age-related differences in emotional processing and discusses how this evidence relates to two opposing theoretical accounts of older adults’ positivity effect. The aging-brain model [Cacioppo et al. in: Social Neuroscience: Toward Understanding the Underpinnings of the Social Mind. New York, Oxford University Press, 2011] proposes that older adults’ positivity effect is a consequence of age-related decline in the amygdala, whereas the cognitive control hypothesis [Kryla-Lighthall and Mather in: Handbook of Theories of Aging, ed 2. New York, Springer, 2009; Mather and Carstensen: Trends Cogn Sci 2005;9:496–502; Mather and Knight: Psychol Aging 2005;20:554–570] argues that the positivity effect is a result of older adults’ greater focus on regulating emotion. Based on evidence for structural and functional preservation of the amygdala in older adults and findings that older adults show greater prefrontal cortex activity than younger adults while engaging in emotion-processing tasks, we argue that the cognitive control hypothesis is a more likely explanation for older adults’ positivity effect than the aging-brain model

    Functional magnetic neuroimaging data on age-related differences in task switching accuracy and reverse brain-behavior relationships

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    The data presented in this article is related to the research article entitled “Age-related Differences in BOLD Modulation to Cognitive Control Costs in a Multitasking Paradigm: Global Switch, Local Switch, and Compatibility-Switch Costs” (Nashiro et al., 2018) [1]. This article describes age-related differences in accuracies for various cognitive costs incurred during task switching across three different age-cohorts: younger (18–35 years), younger-old (50–64 years) and older-old (65–80 years). The cognitive costs evaluated were global switch costs (GSC), local switch costs (LSC) and compatibility switch costs (CSC). Whole brain analyses were conducted to determine the brain regions sensitive to these cognitive costs, irrespective of age. Furthermore, age-related differences in brain-behavior relationships were evaluated by correlating activations from these regions with global switch costs, indexed by both response times and accuracies, for younger and older adults separately. Activations of age-sensitive regions during the task, where younger adults activated more than the combined groups of older adults, were also correlated with response times and accuracies to determine age-related differences in brain-behavior relationships of these under-recruited brain regions by older adults
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