Perseverative Behavior and Adaptive Control in Older Adults: Performance Monitoring, Rule Induction, and Set Shifting

2002 ◽  
Vol 49 (3) ◽  
pp. 382-401 ◽  
Author(s):  
K.Richard Ridderinkhof ◽  
Mark M. Span ◽  
Maurits W. van der Molen
2019 ◽  
Vol 98 (4) ◽  
pp. 680-691 ◽  
Author(s):  
Kenneth I. Vaden ◽  
Mark A. Eckert ◽  
Judy R. Dubno ◽  
Kelly C. Harris

Author(s):  
Petra Grönholm-Nyman ◽  
Anna Soveri ◽  
Juha O. Rinne ◽  
Emilia Ek ◽  
Alexandra Nyholm ◽  
...  

2021 ◽  
Vol 36 (6) ◽  
pp. 1024-1024
Author(s):  
Hanna K Hausman ◽  
Cheshire Hardcastle ◽  
Alejandro Albizu ◽  
Jessica N Kraft ◽  
Nicole D Evangelista ◽  
...  

Abstract Objective Executive functioning is a cognitive domain that typically declines with normal aging. Age-related disrupted connectivity in cingulo-opercular (CON) and frontoparietal control (FPCN) resting-state networks is associated with worse performance across various executive functioning tasks. This study examines the relationships between CON and FPCN connectivity and executive functioning performance in older adults across three subdomains: working memory, inhibition, and set-shifting. Methods 274 healthy older adults (age M = 71.7, SD = 5.1; 87% Caucasian) from a clinical trial at the University of Florida and University of Arizona completed tasks of working memory (Digit Span Backwards [DSB]; Letter Number Sequencing [LNS]), inhibition (Stroop), and set-shifting (Trail Making Test Part B [TMT-B]). Participants underwent resting-state functional magnetic resonance imaging. CONN Toolbox (18b) was used for extracting average within-network connectivity of CON and FPCN. Multiple linear regressions were conducted with average network connectivity predicting performance, controlling for age, sex, education, and scanner. Results Greater average CON connectivity was associated with better performance on DSB (β = 0.26, p < 0.001), LNS (β = 0.23, p < 0.001), Stroop (β = 0.24, p < 0.001), and TMT-B (β = −0.26, p < 0.001). Greater average FPCN connectivity was associated with better performance on DSB (β = 0.22, p < 0.001) and LNS (β = 0.18, p = 0.002). Conclusions CON connectivity was significantly associated with working memory, inhibition, and set-shifting. FPCN connectivity was significantly associated with working memory. Future research should conduct regional connectivity analyses within these networks to identify intervention targets to improve executive functioning in older adults.


2017 ◽  
Author(s):  
J. Lucas McKay ◽  
Kimberly C. Lang ◽  
Lena H. Ting ◽  
Madeleine E. Hackney

AbstractINTRODUCTION. Individuals with Parkinson’s disease (PD) are at increased risk for falls, and exhibit deficits in executive function, including Set Shifting, which can be measured as the difference between parts B and A of the Trailmaking Test. METHODS. We conducted a cross-sectional study using baseline data of PD patients with and without freezing of gait (FOG) (n=69) and community-dwelling neurologically-normal older adults (NON-PD) (n=84) who had volunteered to participate in clinical rehabilitation research. Multivariate logistic regression analyses were performed to determine associations between Set Shifting, PD, and faller status, as determined by ≥1 self-reported falls in the previous 6 months, after adjusting for demographic and cognitive factors and clinical disease characteristics. RESULTS. Impaired Set Shifting was associated with previous falls after controlling for age, sex, overall cognitive function, PD, FOG, and PD disease duration (OR=1.29 [1.03-1.60]; P=0.02). In models controlling for age, sex, and overall cognitive function, PD was associated with increased fall prevalence among the study sample (OR=4.15 [95% CI 1.65-10.44], P<0.01) and FOG was associated with increased fall prevalence among the PD sample (OR=3.63 [1.22-10.80], P=0.02). Although the strongest associations between Set Shifting and falling were observed among PD without FOG (OR=2.11) compared to HOA (OR=1.14) and PD with FOG (OR=1.46) in a multivariate model that allowed for interaction between set shifting and PD status, there was insufficient evidence to reject the null hypothesis of no interaction. CONCLUSIONS. Set Shifting is associated with previous falls in non-demented older adults with and without PD.HighlightsIndividuals with PD are at increased risk for falls, although causes are unclear.Impaired Set Shifting was associated with falls in older adults with and without PD.Associations were strongest among those with PD but without freezing of gait.


2010 ◽  
Vol 16 (4) ◽  
pp. 640-650 ◽  
Author(s):  
JUDY PA ◽  
KATHERINE L. POSSIN ◽  
STEPHEN M. WILSON ◽  
LOVINGLY C. QUITANIA ◽  
JOEL H. KRAMER ◽  
...  

AbstractThere is increasing recognition that set-shifting, a form of cognitive control, is mediated by different neural structures. However, these regions have not yet been carefully identified as many studies do not account for the influence of component processes (e.g., motor speed). We investigated gray matter correlates of set-shifting while controlling for component processes. Using the Design Fluency (DF), Trail Making Test (TMT), and Color Word Interference (CWI) subtests from the Delis-Kaplan Executive Function System (D-KEFS), we investigated the correlation between set-shifting performance and gray matter volume in 160 subjects with neurodegenerative disease, mild cognitive impairment, and healthy older adults using voxel-based morphometry. All three set-shifting tasks correlated with multiple, widespread gray matter regions. After controlling for the component processes, set-shifting performance correlated with focal regions in prefrontal and posterior parietal cortices. We also identified bilateral prefrontal cortex and the right posterior parietal lobe as common sites for set-shifting across the three tasks. There was a high degree of multicollinearity between the set-shifting conditions and the component processes of TMT and CWI, suggesting DF may better isolate set-shifting regions. Overall, these findings highlight the neuroanatomical correlates of set-shifting and the importance of controlling for component processes when investigating complex cognitive tasks. (JINS, 2010, 16, 640–650.)


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