scholarly journals Multiple bouts of high-intensity interval exercise reverse age-related functional connectivity disruptions without affecting motor learning in older adults

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Brian Greeley ◽  
Briana Chau ◽  
Christina B. Jones ◽  
Jason L. Neva ◽  
Sarah N. Kraeutner ◽  
...  
Keyword(s):  
Older Adults ◽  
Functional Connectivity ◽  
Motor Learning ◽  
Resting State ◽  
Exercise Group ◽  
Resting State Functional Connectivity ◽  
Interval Exercise ◽  
Age Related ◽  
Implicit Motor ◽  
High Intensity Interval

AbstractExercise has emerged as an intervention that may mitigate age-related resting state functional connectivity and sensorimotor decline. Here, 42 healthy older adults rested or completed 3 sets of high-intensity interval exercise for a total of 23 min, then immediately practiced an implicit motor task with their non-dominant hand across five separate sessions. Participants completed resting state functional MRI before the first and after the fifth day of practice; they also returned 24-h and 35-days later to assess short- and long-term retention. Independent component analysis of resting state functional MRI revealed increased connectivity in the frontoparietal, the dorsal attentional, and cerebellar networks in the exercise group relative to the rest group. Seed-based analysis showed strengthened connectivity between the limbic system and right cerebellum, and between the right cerebellum and bilateral middle temporal gyri in the exercise group. There was no motor learning advantage for the exercise group. Our data suggest that exercise paired with an implicit motor learning task in older adults can augment resting state functional connectivity without enhancing behaviour beyond that stimulated by skilled motor practice.

scholarly journals Multiple bouts of high-intensity interval exercise reverse age-related functional connectivity disruptions without affecting motor learning in older adults

2021 ◽  
Author(s):  
Brian Greeley ◽  
Briana Chau ◽  
Christina B. Jones ◽  
Jason L. Neva ◽  
Sarah N. Kraeutner ◽  
...  
Keyword(s):  
Older Adults ◽  
Functional Connectivity ◽  
Motor Learning ◽  
Resting State ◽  
Exercise Group ◽  
Resting State Functional Connectivity ◽  
Interval Exercise ◽  
Age Related ◽  
Motor Practice ◽  
High Intensity Interval

AbstractOlder adults show both age-related decreases in resting state functional connectivity and diminished sensorimotor function. Exercise has emerged as an intervention that may mitigate or even reverse these age-related declines. Here we sought to understand whether exercise impacts resting state functional connectivity, and motor acquisition and learning in older adults. Forty-two healthy older adults rested or completed 3 sets of high-intensity interval exercise (3 minutes at 75% maximal power output and 3 minutes light intensity) for a total of 23 minutes, then immediately practiced a complex, implicit motor task with their non-dominant hand across five separate sessions. Participants completed resting stage functional MRI before the first and after the fifth day of practice; they also returned 24-hours and 35-days following their fifth day of practice to complete short- and long-term retention tests to assess motor learning. Independent component analysis of resting state functional MRI revealed increased connectivity in the frontoparietal, the dorsal attentional, and cerebellar networks in the exercise group relative to the rest group. Seed-based analysis showed strengthened connectivity between the limbic system and right cerebellum, and between the right cerebellum and bilateral middle temporal gyri. There was no motor learning advantage for the exercise group; both rest and exercise groups demonstrated motor learning as measured at the short- and long-term retention tests. Our data suggest that exercise paired with a challenging implicit motor learning task in older adults can augment resting state functional connectivity without enhancing behaviour beyond that stimulated by skilled motor practice.Significance statementAging is accompanied by significant declines in the capacity for motor learning and changes in resting state functional connectivity; the net result is poor motor performance. Here, we show that five separate bouts of exercise paired with skilled motor practice strengthens resting state networks in brain regions that are susceptible to declines in older adults without affecting motor acquisition or learning. Overall, our results suggest that exercise may be effective in reducing age-related disruptions to resting state networks but not in enhancing motor learning beyond that stimulated by practice alone in older adults.

scholarly journals Age-related changes in resting-state functional connectivity in older adults

2019 ◽  
Vol 14 (9) ◽  
pp. 1544 ◽  
Author(s):  
Laia Farras-Permanyer ◽  
Núria Mancho-Fora ◽  
Marc Montalà-Flaquer ◽  
David Bartrés-Faz ◽  
Lídia Vaqué-Alcázar ◽  
...  
Keyword(s):  
Older Adults ◽  
Functional Connectivity ◽  
Resting State ◽  
Resting State Functional Connectivity ◽  
Age Related ◽  
Age Related Changes

Individual differences in the relationship between episodic detail generation and resting state functional connectivity vary with age

2021 ◽  
Author(s):  
Stephanie Matijevic ◽  
Jessica R. Andrews-Hanna ◽  
Aubrey Anne Ladd Wank ◽  
Lee Ryan ◽  
Matthew D. Grilli
Keyword(s):  
Older Adults ◽  
Individual Differences ◽  
Functional Connectivity ◽  
Resting State ◽  
Brain Regions ◽  
Resting State Functional Connectivity ◽  
Age Related ◽  
Brain Behavior ◽  
The Relationship

The ability to generate episodic details while recollecting autobiographical events is believed to depend on a collection of brain regions that form a posterior medial network (PMN). How age-related differences in episodic detail generation relate to the PMN, however, remains unclear. The present study sought to examine individual differences, and the role of age, in PMN resting state functional connectivity (rsFC) associations with episodic detail generation. Late middle-aged and older adults (N = 41, ages 52-81), and young adults (N = 21, ages 19-35) were asked to describe recent personal events, and these memory narratives were coded for episodic, semantic and ‘miscellaneous’ details. Independent components analysis and regions-of-interest analyses were used to assess rsFC within anterior PMN connections (hippocampal and medial prefrontal) and posterior PMN connections (hippocampal, parahippocampal and parieto-occipital). Compared to younger adults, older adults produced memory narratives with lower episodic specificity (ratio of episodic:total details) and a greater amount of semantic detail. Among the older adults, episodic detail amounts and episodic specificity were reduced with increasing age. There were no significant age differences in PMN rsFC. Stronger anterior PMN rsFC was related to lower episodic detail in the older adult group, but not in the young. Among the older adults, increasing age brought on an association between increased anterior PMN rsFC and reduced episodic specificity. The present study provides evidence that functional connectivity within the PMN, particularly anterior PMN, tracks individual differences in the amount of episodic details retrieved by older adults. Furthermore, these brain-behavior relationships appear to be age-specific.

scholarly journals Age-related differences in resting state functional connectivity in pediatric migraine

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Tiffany Bell ◽  
Akashroop Khaira ◽  
Mehak Stokoe ◽  
Megan Webb ◽  
Melanie Noel ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Power Spectra ◽  
Interaction Effects ◽  
Resting State Functional Connectivity ◽  
Default Mode ◽  
Pediatric Migraine ◽  
Age Related ◽  
Status Interaction ◽  
Underlying Mechanisms

Abstract Background Migraine affects roughly 10% of youth aged 5–15 years, however the underlying mechanisms of migraine in youth are poorly understood. Multiple structural and functional alterations have been shown in the brains of adult migraine sufferers. This study aims to investigate the effects of migraine on resting-state functional connectivity during the period of transition from childhood to adolescence, a critical period of brain development and the time when rates of pediatric chronic pain spikes. Methods Using independent component analysis, we compared resting state network spatial maps and power spectra between youth with migraine aged 7–15 and age-matched controls. Statistical comparisons were conducted using a MANCOVA analysis. Results We show (1) group by age interaction effects on connectivity in the visual and salience networks, group by sex interaction effects on connectivity in the default mode network and group by pubertal status interaction effects on connectivity in visual and frontal parietal networks, and (2) relationships between connectivity in the visual networks and the migraine cycle, and age by cycle interaction effects on connectivity in the visual, default mode and sensorimotor networks. Conclusions We demonstrate that brain alterations begin early in youth with migraine and are modulated by development. This highlights the need for further study into the neural mechanisms of migraine in youth specifically, to aid in the development of more effective treatments.

scholarly journals Reduced resting state functional connectivity with increasing age-related hearing loss and McGurk susceptibility

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Alina Schulte ◽  
Christiane M. Thiel ◽  
Anja Gieseler ◽  
Maike Tahden ◽  
Hans Colonius ◽  
...  
Keyword(s):  
Hearing Loss ◽  
Functional Connectivity ◽  
Resting State ◽  
Mcgurk Effect ◽  
Functional Coupling ◽  
Resting State Functional Connectivity ◽  
Visual Integration ◽  
Age Related ◽  
Hearing Thresholds ◽  
Age Related Hearing Loss

Abstract Age-related hearing loss has been related to a compensatory increase in audio-visual integration and neural reorganization including alterations in functional resting state connectivity. How these two changes are linked in elderly listeners is unclear. The current study explored modulatory effects of hearing thresholds and audio-visual integration on resting state functional connectivity. We analysed a large set of resting state data of 65 elderly participants with a widely varying degree of untreated hearing loss. Audio-visual integration, as gauged with the McGurk effect, increased with progressing hearing thresholds. On the neural level, McGurk illusions were negatively related to functional coupling between motor and auditory regions. Similarly, connectivity of the dorsal attention network to sensorimotor and primary motor cortices was reduced with increasing hearing loss. The same effect was obtained for connectivity between the salience network and visual cortex. Our findings suggest that with progressing untreated age-related hearing loss, functional coupling at rest declines, affecting connectivity of brain networks and areas associated with attentional, visual, sensorimotor and motor processes. Especially connectivity reductions between auditory and motor areas were related to stronger audio-visual integration found with increasing hearing loss.

scholarly journals Motor Sequences - Separating The Sequence From The Motor. A longitudinal rsfMRI Study

2021 ◽  
Author(s):  
ATP Jäger ◽  
JM Huntenburg ◽  
SA Tremblay ◽  
U Schneider ◽  
S Grahl ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Motor Learning ◽  
Resting State ◽  
Primary Motor Cortex ◽  
Control Group ◽  
Motor Execution ◽  
Motor Sequence ◽  
Resting State Functional Connectivity ◽  
Fast Learning ◽  
Slow Learning

AbstractIn motor learning, sequence-specificity, i.e. the learning of specific sequential associations, has predominantly been studied using task-based fMRI paradigms. However, offline changes in resting state functional connectivity after sequence-specific motor learning are less well understood. Previous research has established that plastic changes following motor learning can be divided into stages including fast learning, slow learning and retention. A description of how resting state functional connectivity after sequence-specific motor sequence learning (MSL) develops across these stages is missing. This study aimed to identify plastic alterations in whole-brain functional connectivity after learning a complex motor sequence by contrasting an active group who learned a complex sequence with a control group who performed a control task matched for motor execution. Resting state fMRI and behavioural performance were collected in both groups over the course of 5 consecutive training days and at follow-up after 12 days to encompass fast learning, slow learning, overall learning and retention. Between-group interaction analyses showed sequence-specific increases in functional connectivity during fast learning in the sensorimotor territory of the internal segment of right globus pallidus (GPi), and sequence-specific decreases in right supplementary motor area (SMA) in overall learning. We found that connectivity changes in key regions of the motor network including the superior parietal cortex (SPC) and primary motor cortex (M1) were not a result of sequence-specific learning but were instead linked to motor execution. Our study confirms the sequence-specific role of SMA and GPi that has previously been identified in online task-based learning studies in humans and primates, and extends it to resting state network changes after sequence-specific MSL. Finally, our results shed light on a timing-specific plasticity mechanism between GPi and SMA following MSL.

scholarly journals Predicting dysfunctional age-related task activations from resting-state network alterations

2019 ◽  
Author(s):  
Ravi D. Mill ◽  
Brian A. Gordon ◽  
David A. Balota ◽  
Jeffrey M. Zacks ◽  
Michael W. Cole
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
At Risk ◽  
Functional Connectivity ◽  
Resting State ◽  
Cognitive Task ◽  
Low Risk ◽  
Flow Modeling ◽  
Resting State Functional Connectivity ◽  
Age Related

AbstractAlzheimer’s disease (AD) is linked to changes in fMRI task activations and fMRI resting-state functional connectivity (restFC), which can emerge early in the timecourse of illness. Study of these fMRI correlates of unhealthy aging has been conducted in largely separate subfields. Taking inspiration from neural network simulations, we propose a unifying mechanism wherein restFC network alterations associated with Alzheimer’s disease disrupt the ability for activations to flow between brain regions, leading to aberrant task activations. We apply this activity flow modeling framework in a large sample of clinically unimpaired older adults, which was segregated into healthy (low-risk) and at-risk subgroups based on established imaging (positron emission tomography amyloid) and genetic (apolipoprotein) risk factors for AD. We identified healthy task activations in individuals at low risk for AD, and then by estimating activity flow using at-risk AD restFC data we were able to predict the altered at-risk AD task activations. Thus, modeling the flow of healthy activations over at-risk AD connectivity effectively transformed the healthy aged activations into unhealthy aged activations. These results provide evidence that activity flow over altered intrinsic functional connections may act as a mechanism underlying Alzheimer’s-related dysfunction, even in very early stages of the illness. Beyond these mechanistic insights linking restFC with cognitive task activations, this approach has potential clinical utility as it enables prediction of task activations and associated cognitive dysfunction in individuals without requiring them to perform in-scanner cognitive tasks.Significance StatementDeveloping analytic approaches that can reliably predict features of Alzheimer’s disease is a major goal for cognitive and clinical neuroscience, with particular emphasis on identifying such diagnostic features early in the timeline of disease. We demonstrate the utility of an activity flow modeling approach, which predicts fMRI cognitive task activations in subjects identified as at-risk for Alzheimer’s disease. The approach makes activation predictions by transforming a healthy aged activation template via the at-risk subjects’ individual pattern of fMRI resting-state functional connectivity (restFC). The observed prediction accuracy supports activity flow as a mechanism linking age-related alterations in restFC and task activations, thereby providing a theoretical basis for incorporating restFC into imaging biomarker and personalized medicine interventions.

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