Cingulo-opercular and frontoparietal control network connectivity and executive functioning in older adults

GeroScience ◽  
2021 ◽  
Author(s):  
Hanna K. Hausman ◽  
Cheshire Hardcastle ◽  
Alejandro Albizu ◽  
Jessica N. Kraft ◽  
Nicole D. Evangelista ◽  
...  
Keyword(s):  
Older Adults ◽  
Executive Functioning ◽  
Network Connectivity ◽  
Control Network ◽  
Frontoparietal Control Network

A-3 Cingulo-Opercular and Frontoparietal Control Network Connectivity and Executive Functioning in Older Adults

2021 ◽  
Vol 36 (6) ◽  
pp. 1024-1024
Author(s):  
Hanna K Hausman ◽  
Cheshire Hardcastle ◽  
Alejandro Albizu ◽  
Jessica N Kraft ◽  
Nicole D Evangelista ◽  
...  
Keyword(s):  
Older Adults ◽  
Working Memory ◽  
Executive Functioning ◽  
Resting State ◽  
Digit Span ◽  
Network Connectivity ◽  
Cognitive Domain ◽  
Set Shifting ◽  
Age Related ◽  
Memory Inhibition

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.

scholarly journals Mild Motor Signs Matter in Typical Brain Aging: The Value of the UPDRS Score Within a Functionally Intact Cohort of Older Adults

2021 ◽  
Vol 13 ◽  
Author(s):  
Jennifer Zitser ◽  
Kaitlin B. Casaletto ◽  
Adam M. Staffaroni ◽  
Claire Sexton ◽  
Sophia Weiner-Light ◽  
...  
Keyword(s):  
Older Adults ◽  
Executive Functioning ◽  
Episodic Memory ◽  
Processing Speed ◽  
Rating Scale ◽  
Brain Aging ◽  
Network Connectivity ◽  
Community Dwelling ◽  
Cognitive Outcomes ◽  
Over Time

Objectives: To characterize the clinical correlates of subclinical Parkinsonian signs, including longitudinal cognitive and neural (via functional connectivity) outcomes, among functionally normal older adults.Methods: Participants included 737 functionally intact community-dwelling older adults who performed prospective comprehensive evaluations at ~15-months intervals for an average of 4.8 years (standard deviation 3.2 years). As part of these evaluations, participants completed the Unified Parkinson's Disease Rating Scale (UPDRS) longitudinally and measures of processing speed, executive functioning and verbal episodic memory. T1-weighted structural scans and task-free functional MRI scans were acquired on 330 participants. We conducted linear mixed-effects models to determine the relationship between changes in UPDRS with cognitive and neural changes, using age, sex, and education as covariates.Results: Cognitive outcomes were processing speed, executive functioning, and episodic memory. Greater within-person increases in UPDRS were associated with more cognitive slowing over time. Although higher average UPDRS scores were significantly associated with overall poorer executive functions, there was no association between UPDRS and executive functioning longitudinally. UPDRS scores did not significantly relate to longitudinal memory performances. Regarding neural correlates, greater increases in UPDRS scores were associated with reduced intra-subcortical network connectivity over time. There were no relationships with intra-frontoparietal or inter-subcortical-frontoparietal connectivity.Conclusions: Our findings add to the aging literature by indicating that mild motor changes are negatively associated with cognition and network connectivity in functionally intact adults.

scholarly journals Resting-state based prediction of task-related activation in patients with disorders of consciousness

2021 ◽  
Author(s):  
Michael M Craig ◽  
Ioannis Pappas ◽  
Judith Allanson ◽  
Paola Finoia ◽  
Guy Williams ◽  
...  
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Resting State ◽  
Network Connectivity ◽  
Final Analysis ◽  
Brain Network ◽  
Disorders Of Consciousness ◽  
Control Network ◽  
Whole Brain ◽  
Frontoparietal Control Network

ABSTRACTBackgroundAssessment of the level of awareness of people with disorders of consciousness (DOC) is clinically challenging, motivating several studies to combine brain imaging with machine learning to improve this process. While this work has shown promise, it has limited clinical utility, as misdiagnosis of DOC patients is relatively high. As machine learning algorithms rely on accurately labelled data, any error in diagnosis will be learned by the algorithm, resulting in an equally limited diagnostic tool. The goal of the present study is to overcome this problem by stratifying patients, not by diagnosis, but by their capacity to perform volitional tasks during functional magnetic resonance imaging (fMRI) scanning.MethodsA total of 71 patients were assessed for inclusion. They were excluded for the final analysis if they had large focal brain damage, excessive head motion during scanning, or suboptimal MRI preprocessing. Patients underwent both resting-state and task-based fMRI scanning. Univariate fMRI analysis was performed to determine if an individual patient had brain activity consistent with having retained volitional capacity (VC). Differences in resting brain network connectivity between patients with VC and patients without volitional capacity (non-VC) were measured. Connectivity data was then entered as input to a deep learning framework. We used a deep graph convolutional neural network (DGCNN) on connectivity data to identify a specific brain network that most significantly differentiates patients.FindingsWe included 30 patients in our final analysis. Univariate analysis revealed that 13 patients displayed signs of VC, while 17 did not. We found that resting-state connectivity between frontoparietal control and salience network was significantly different between VC and non-VC patients (T(28) = 3.347, p = 0.0023, Bonferroni corrected p = 0.042). Furthermore, we found that using frontoparietal control network connectivity as input to the DGCNN resulted in the best classification performance (test accuracy = 0.85; ROC AUC = 0.92).InterpretationWe found that the DGCNN performed best at discriminating between patients with VC when using only the frontoparietal control network as input to the model. The use of this deep learning method is a significant advance since its inherent flexibility permits the inclusion of both whole-brain and network-specific properties as input, allowing us to classify patients as either having or not having VC. This inclusion of multi-scale inputs (e.g. whole-brain and network-level) facilitates model interpretability and increases our understanding of the neurobiology of DOC. The results propose that the integrity of frontoparietal control network, a brain network well known to play a key role in executive functions and cognitive control, is essential for volitional capacity preservation in patients with DOC. The study also lays groundwork for development of a biomarker to aid in the diagnosis of DOC patients.RESEARCH IN CONTEXTEvidence before this studyDisorders of consciousness (DOC) are a group of severe brain disorders characterised by damage to the neural systems underlying wakefulness and awareness. DOC are often caused by traumatic brain injury, hypoxia, or neurodegenerative diseases. The motor and cognitive impairments in DOC patients make providing an accurate diagnosis very challenging. Diagnosis is primarily made at the bedside by assessing a patient’s response to motor commands.

scholarly journals Spontaneous Eye Blinks Predict Executive Functioning in Seniors

2021 ◽  
Author(s):  
Jessika I. V. Buitenweg ◽  
Jaap M. J. Murre ◽  
K. Richard Ridderinkhof
Keyword(s):  
Older Adults ◽  
Working Memory ◽  
Executive Functioning ◽  
Cognitive Training ◽  
Functional Decline ◽  
Future Research ◽  
Blink Rate ◽  
Memory Updating ◽  
Age Related ◽  
Working Memory Updating

AbstractAs the world’s population is aging rapidly, cognitive training is an extensively used approach to attempt improvement of age-related cognitive functioning. With increasing numbers of older adults required to remain in the workforce, it is important to be able to reliably predict future functional decline, as well as the individual advantages of cognitive training. Given the correlation between age-related decline and striatal dopaminergic function, we investigated whether eye blink rate (EBR), a non-invasive, indirect indicator of dopaminergic activity, could predict executive functioning (response inhibition, switching and working memory updating) as well as trainability of executive functioning in older adults. EBR was collected before and after a cognitive flexibility training, cognitive training without flexibility, or a mock training. EBR predicted working memory updating performance on two measures of updating, as well as trainability of working memory updating, whereas performance and trainability in inhibition and switching tasks could not be predicted by EBR. Our findings tentatively indicate that EBR permits prediction of working memory performance in older adults. To fully interpret the relationship with executive functioning, we suggest future research should assess both EBR and dopamine receptor availability among seniors.

scholarly journals Age Differences in Executive Control Assessed with a Robotic Object Hit and Avoid Test of Rapid Motor Decision Making

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 881-882
Author(s):  
Alexandra Watral ◽  
Kevin Trewartha
Keyword(s):  
Older Adults ◽  
Decision Making ◽  
Executive Functioning ◽  
Age Differences ◽  
Executive Control ◽  
Test Performance ◽  
Cognitive Status ◽  
Younger Adults ◽  
Neuropsychological Tasks ◽  
Measures Of Performance

Abstract Motor decision-making processes are required for many standard neuropsychological tasks, including the Trail Making Test (TMT), that aim to assess cognitive functioning in older adults. However, in their standard formats, it is difficult to isolate the relative contributions of sensorimotor and cognitive processes to performance on these neuropsychological tasks. Recently developed clinical tasks use a robotic manipulandum to assess both motor and cognitive aspects of rapid motor decision making in an object hit (OH) and object hit and avoid (OHA) task. We administered the OH and OHA tasks to 77 healthy younger adults and 59 healthy older adults to assess age differences in the motor and cognitive measures of performance. We administered the TMT parts A and B to assess the extent to which OHA performance is associated with executive functioning in particular. The results indicate that after controlling for hand speed, older adults performed worse on the OH and OHA tasks than younger adults, performance declines were far greater in the OHA task, and the global performance measures, which have been associated with cognitive status, were more sensitive to age differences than motor measures of performance. Those global measures of performance were also associated with measures of executive functioning on the TMT task. These findings provide evidence that rapid motor decision making tasks are sensitive to declines in executive control in aging. They also provide a way to isolate cognitive declines from declines in sensorimotor processes that are likely a contributing factor to age differences in neuropsychological test performance.

Altered Resting-State Frontoparietal Control Network in Children with Attention-Deficit/Hyperactivity Disorder

2015 ◽  
Vol 21 (4) ◽  
pp. 271-284 ◽  
Author(s):  
Hsiang-Yuan Lin ◽  
Wen-Yih Isaac Tseng ◽  
Meng-Chuan Lai ◽  
Kayako Matsuo ◽  
Susan Shur-Fen Gau
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Prefrontal Cortex ◽  
Functional Connectivity ◽  
Resting State ◽  
Control Network ◽  
Children With Adhd ◽  
Hyperactivity Disorder ◽  
Anterior Prefrontal Cortex ◽  
The Right ◽  
Frontoparietal Control Network

AbstractThe frontoparietal control network, anatomically and functionally interposed between the dorsal attention network and default mode network, underpins executive control functions. Individuals with attention-deficit/hyperactivity disorder (ADHD) commonly exhibit deficits in executive functions, which are mainly mediated by the frontoparietal control network. Involvement of the frontoparietal control network based on the anterior prefrontal cortex in neurobiological mechanisms of ADHD has yet to be tested. We used resting-state functional MRI and seed-based correlation analyses to investigate functional connectivity of the frontoparietal control network in a sample of 25 children with ADHD (7–14 years; mean 9.94±1.77 years; 20 males), and 25 age-, sex-, and performance IQ-matched typically developing (TD) children. All participants had limited in-scanner head motion. Spearman’s rank correlations were used to test the associations between altered patterns of functional connectivity with clinical symptoms and executive functions, measured by the Conners’ Continuous Performance Test and Spatial Span in the Cambridge Neuropsychological Test Automated Battery. Compared with TD children, children with ADHD demonstrated weaker connectivity between the right anterior prefrontal cortex (PFC) and the right ventrolateral PFC, and between the left anterior PFC and the right inferior parietal lobule. Furthermore, this aberrant connectivity of the frontoparietal control network in ADHD was associated with symptoms of impulsivity and opposition-defiance, as well as impaired response inhibition and attentional control. The findings support potential integration of the disconnection model and the executive dysfunction model for ADHD. Atypical frontoparietal control network may play a pivotal role in the pathophysiology of ADHD. (JINS, 2015, 21, 271–284)

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