scholarly journals Sensorimotor, Attentional, and Neuroanatomical Predictors of Upper Limb Motor Deficits and Rehabilitation Outcome after Stroke

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Daniela D’Imperio ◽  
Zaira Romeo ◽  
Lorenza Maistrello ◽  
Eugenia Durgoni ◽  
Camilla Della Pietà ◽  
...  
Keyword(s):  
Upper Limb ◽  
Cognitive Abilities ◽  
Large Scale ◽  
Brain Networks ◽  
Motor Recovery ◽  
Motor Deficits ◽  
Cognitive Domains ◽  
Rehabilitation Outcome ◽  
Left Brain ◽  
Left Brain Damage

The rehabilitation of motor deficits following stroke relies on both sensorimotor and cognitive abilities, thereby involving large-scale brain networks. However, few studies have investigated the integration between motor and cognitive domains, as well as its neuroanatomical basis. In this retrospective study, upper limb motor responsiveness to technology-based rehabilitation was examined in a sample of 29 stroke patients (18 with right and 11 with left brain damage). Pretreatment sensorimotor and attentional abilities were found to influence motor recovery. Training responsiveness increased as a function of the severity of motor deficits, whereas spared attentional abilities, especially visuospatial attention, supported motor improvements. Neuroanatomical analysis of structural lesions and white matter disconnections showed that the poststroke motor performance was associated with putamen, insula, corticospinal tract, and frontoparietal connectivity. Motor rehabilitation outcome was mainly associated with the superior longitudinal fasciculus and partial involvement of the corpus callosum. The latter findings support the hypothesis that motor recovery engages large-scale brain networks that involve cognitive abilities and provides insight into stroke rehabilitation strategies.

scholarly journals Mapping human brain networks with cortico-cortical evoked potentials

2014 ◽  
Vol 369 (1653) ◽  
pp. 20130528 ◽  
Author(s):  
Corey J. Keller ◽  
Christopher J. Honey ◽  
Pierre Mégevand ◽  
Laszlo Entz ◽  
Istvan Ulbert ◽  
...  
Keyword(s):  
Cerebral Cortex ◽  
Cognitive Processing ◽  
Cognitive Abilities ◽  
Large Scale ◽  
Effective Connectivity ◽  
Brain Networks ◽  
Brain Network ◽  
Fundamental Aspect ◽  
Neural Basis ◽  
Network Function

The cerebral cortex forms a sheet of neurons organized into a network of interconnected modules that is highly expanded in humans and presumably enables our most refined sensory and cognitive abilities. The links of this network form a fundamental aspect of its organization, and a great deal of research is focusing on understanding how information flows within and between different regions. However, an often-overlooked element of this connectivity regards a causal, hierarchical structure of regions, whereby certain nodes of the cortical network may exert greater influence over the others. While this is difficult to ascertain non-invasively, patients undergoing invasive electrode monitoring for epilepsy provide a unique window into this aspect of cortical organization. In this review, we highlight the potential for cortico-cortical evoked potential (CCEP) mapping to directly measure neuronal propagation across large-scale brain networks with spatio-temporal resolution that is superior to traditional neuroimaging methods. We first introduce effective connectivity and discuss the mechanisms underlying CCEP generation. Next, we highlight how CCEP mapping has begun to provide insight into the neural basis of non-invasive imaging signals. Finally, we present a novel approach to perturbing and measuring brain network function during cognitive processing. The direct measurement of CCEPs in response to electrical stimulation represents a potentially powerful clinical and basic science tool for probing the large-scale networks of the human cerebral cortex.

scholarly journals Individualized perturbation of the human connectome reveals reproducible biomarkers of network dynamics relevant to cognition

2020 ◽  
Vol 117 (14) ◽  
pp. 8115-8125 ◽  
Author(s):  
Recep A. Ozdemir ◽  
Ehsan Tadayon ◽  
Pierre Boucher ◽  
Davide Momi ◽  
Kelly A. Karakhanyan ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Resting State ◽  
Cognitive Abilities ◽  
Large Scale ◽  
Brain Networks ◽  
Blood Oxygenation ◽  
Neuronal Firing ◽  
Brain Dynamics ◽  
High Temporal Resolution ◽  
Indirect Measure

Large-scale brain networks are often described using resting-state functional magnetic resonance imaging (fMRI). However, the blood oxygenation level-dependent (BOLD) signal provides an indirect measure of neuronal firing and reflects slow-evolving hemodynamic activity that fails to capture the faster timescale of normal physiological function. Here we used fMRI-guided transcranial magnetic stimulation (TMS) and simultaneous electroencephalography (EEG) to characterize individual brain dynamics within discrete brain networks at high temporal resolution. TMS was used to induce controlled perturbations to individually defined nodes of the default mode network (DMN) and the dorsal attention network (DAN). Source-level EEG propagation patterns were network-specific and highly reproducible across sessions 1 month apart. Additionally, individual differences in high-order cognitive abilities were significantly correlated with the specificity of TMS propagation patterns across DAN and DMN, but not with resting-state EEG dynamics. Findings illustrate the potential of TMS-EEG perturbation-based biomarkers to characterize network-level individual brain dynamics at high temporal resolution, and potentially provide further insight on their behavioral significance.

scholarly journals Mitochondrial Functioning and the Relations among Health, Cognition, and Aging: Where Cell Biology Meets Cognitive Science

2021 ◽  
Vol 22 (7) ◽  
pp. 3562
Author(s):  
David C. Geary
Keyword(s):  
Cognitive Science ◽  
Cognitive Abilities ◽  
Cell Biology ◽  
Energy Production ◽  
Large Scale ◽  
Brain Networks ◽  
Mitochondrial Functions ◽  
Complex Forms ◽  
Underlying Mechanisms ◽  
Cognition And Aging

Cognitive scientists have determined that there is a set of mechanisms common to all sensory, perceptual, and cognitive abilities and correlated with age- and disease-related declines in cognition. These mechanisms also contribute to the development and functional coherence of the large-scale brain networks that support complex forms of cognition. At the same time, these brain and cognitive patterns are correlated with myriad health outcomes, indicating that at least some of the underlying mechanisms are common to all biological systems. Mitochondrial functions, including cellular energy production and control of oxidative stress, among others, are well situated to explain the relations among the brain, cognition, and health. Here, I provide an overview of the relations among cognitive abilities, associated brain networks, and the importance of mitochondrial energy production for their functioning. These are then linked to the relations between cognition, health, and aging. The discussion closes with implications for better integrating research in cognitive science and cell biology in the context of developing more sensitive measures of age- and disease-related declines in cognition.

scholarly journals Segregation, integration, and balance of large-scale resting brain networks configure different cognitive abilities

2021 ◽  
Vol 118 (23) ◽  
pp. e2022288118
Author(s):  
Rong Wang ◽  
Mianxin Liu ◽  
Xinhong Cheng ◽  
Ying Wu ◽  
Andrea Hildebrandt ◽  
...  
Keyword(s):  
Cognitive Abilities ◽  
Structural Equation ◽  
Large Scale ◽  
Functional Organization ◽  
Diffusion Tensor ◽  
Brain Activity ◽  
Brain Networks ◽  
Deep Understanding ◽  
Human Cognition ◽  
Equation Modeling

Diverse cognitive processes set different demands on locally segregated and globally integrated brain activity. However, it remains an open question how resting brains configure their functional organization to balance the demands on network segregation and integration to best serve cognition. Here we use an eigenmode-based approach to identify hierarchical modules in functional brain networks and quantify the functional balance between network segregation and integration. In a large sample of healthy young adults (n = 991), we combine the whole-brain resting state functional magnetic resonance imaging (fMRI) data with a mean-filed model on the structural network derived from diffusion tensor imaging and demonstrate that resting brain networks are on average close to a balanced state. This state allows for a balanced time dwelling at segregated and integrated configurations and highly flexible switching between them. Furthermore, we employ structural equation modeling to estimate general and domain-specific cognitive phenotypes from nine tasks and demonstrate that network segregation, integration, and their balance in resting brains predict individual differences in diverse cognitive phenotypes. More specifically, stronger integration is associated with better general cognitive ability, stronger segregation fosters crystallized intelligence and processing speed, and an individual’s tendency toward balance supports better memory. Our findings provide a comprehensive and deep understanding of the brain’s functioning principles in supporting diverse functional demands and cognitive abilities and advance modern network neuroscience theories of human cognition.

scholarly journals Age-differences in information flow in executive and sensorimotor brain networks during childhood and adolescence

2020 ◽  
Author(s):  
Martina J. Lund ◽  
Dag Alnæs ◽  
Jaroslav Rokicki ◽  
Simon Schwab ◽  
Ole A. Andreassen ◽  
...  
Keyword(s):  
Information Flow ◽  
Graphical Models ◽  
Cognitive Abilities ◽  
Large Scale ◽  
Brain Networks ◽  
Brain Network ◽  
Childhood And Adolescence ◽  
Imaging Data ◽  
Fine Grained ◽  
Age Related

AbstractObjectiveMental disorders often emerge during adolescence, and age-related differences in connection strengths of brain networks (static connectivity) have been identified. However, little is known about the directionality of information flow (directed connectivity) in this period of brain development.MethodsWe employed dynamic graphical models (DGM) to estimate directed functional connectivity from resting state functional magnetic resonance imaging data on 979 participants aged 6 to 17 years from the healthy brain network (HBN) sample. We tested for effects of age, sex, cognitive abilities and psychopathology on directionality.ResultsWe show robust bi-directionality in information flow between visual-medial and visual-lateral nodes of the network, in line with prior studies in adult samples. Furthermore, we found that age in this developmental sample was associated with directionality of information flow in sensorimotor and executive control networks, yet we did not find associations with cognitive abilities or psychopathology.DiscussionOur results revealed that directionality in information flow of large-scale brain networks is sensitive to age during adolescence, warranting further studies that may explore trajectories of development in more fine-grained network parcellations and in different populations.

scholarly journals Time Course of Wrist Hyper-Resistance in Relation to Upper Limb Motor Recovery Early Post Stroke

2020 ◽  
Vol 34 (8) ◽  
pp. 690-701
Author(s):  
Aukje Andringa ◽  
Carel Meskers ◽  
Ingrid van de Port ◽  
Erwin van Wegen ◽  
Gert Kwakkel
Keyword(s):  
Upper Limb ◽  
Mixed Models ◽  
Time Course ◽  
Motor Impairment ◽  
Motor Recovery ◽  
Motor Deficits ◽  
Stroke Patients ◽  
Post Stroke ◽  
Resistance Components ◽  
Finger Extension

Background. Patients with an upper limb motor impairment are likely to develop wrist hyper-resistance during the first months post stroke. The time course of wrist hyper-resistance in terms of neural and biomechanical components, and their interaction with motor recovery, is poorly understood. Objective. To investigate the time course of neural and biomechanical components of wrist hyper-resistance in relation to upper limb motor recovery in the first 6 months post stroke. Methods. Neural (NC), biomechanical elastic (EC), and viscous (VC) components of wrist hyper-resistance (NeuroFlexor device), and upper limb motor recovery (Fugl-Meyer upper extremity scale [FM-UE]), were assessed in 17 patients within 3 weeks and at 5, 12, and 26 weeks post stroke. Patients were stratified according to the presence of voluntary finger extension (VFE) at baseline. Time course of wrist hyper-resistance components and assumed interaction effects were analyzed using linear mixed models. Results. On average, patients without VFE at baseline (n = 8) showed a significant increase in NC, EC, and VC, and an increase in FM-UE from 13 to 26 points within the first 6 months post stroke. A significant increase in NC within 5 weeks preceded a significant increase in EC between weeks 12 and 26. Patients with VFE at baseline (n = 9) showed, on average, no significant increase in components from baseline to 6 months whereas FM-UE scores improved from 38 to 60 points. Conclusion. Our findings suggest that the development of neural and biomechanical wrist hyper-resistance components in patients with severe baseline motor deficits is determined by lack of spontaneous neurobiological recovery early post stroke.

scholarly journals Predictive Value of Upper Extremity Outcome Measures After Stroke—A Systematic Review and Metaregression Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Silke Wolf ◽  
Christian Gerloff ◽  
Winifried Backhaus
Keyword(s):  
Outcome Measures ◽  
Upper Limb ◽  
Large Scale ◽  
Motor Recovery ◽  
Stroke Recovery ◽  
Future Research ◽  
Limb Function ◽  
Long Term Outcome ◽  
Common Assessments ◽  
Upper Limb Function

A better understanding of motor recovery after stroke requires large-scale, longitudinal trials applying suitable assessments. Currently, there is an abundance of upper limb assessments used to quantify recovery. How well various assessments can describe upper limb function change over 1 year remains uncertain. A uniform and feasible standard would be beneficial to increase future studies' comparability on stroke recovery. This review describes which assessments are common in large-scale, longitudinal stroke trials and how these quantify the change in upper limb function from stroke onset up to 1 year. A systematic search for well-powered stroke studies identified upper limb assessments classifying motor recovery during the initial year after a stroke. A metaregression investigated the association between assessments and motor recovery within 1 year after stroke. Scores from nine common assessments and 4,433 patients were combined and transformed into a standardized recovery score. A mixed-effects model on recovery scores over time confirmed significant differences between assessments (P < 0.001), with improvement following the weeks after stroke present when measuring recovery using the Action Research Arm Test (β = 0.013), Box and Block test (β = 0.011), Fugl–Meyer Assessment (β = 0.007), or grip force test (β = 0.023). A last-observation-carried-forward analysis also highlighted the peg test (β = 0.017) and Rivermead Assessment (β = 0.011) as additional, valuable long-term outcome measures. Recovery patterns and, thus, trial outcomes are dependent on the assessment implemented. Future research should include multiple common assessments and continue data collection for a full year after stroke to facilitate the consensus process on assessments measuring upper limb recovery.

Face and Word Recognition in Patients with Left and Right Hemispheric Lesions: Evidence from Reaction Times and ERPs

2002 ◽  
Vol 13 (1) ◽  
pp. 69-83 ◽  
Author(s):  
Stefan R. Schweinberger ◽  
Thomas Klos ◽  
Werner Sommer
Keyword(s):  
Slow Wave ◽  
Reaction Times ◽  
Memory Search ◽  
Event Related Potentials ◽  
Performance Deficits ◽  
Set Size ◽  
Left Brain ◽  
Related Potentials ◽  
Abstract Words ◽  
Left Brain Damage

Abstract: We recorded reaction times (RTs) and event-related potentials (ERPs) in patients with unilateral lesions during a memory search task. Participants memorized faces or abstract words, which were then recognized among new ones. The RT deficit found in patients with left brain damage (LBD) for words increased with memory set size, suggesting that their problem relates to memory search. In contrast, the RT deficit found in patients with RBD for faces was apparently related to perceptual encoding, a conclusion also supported by their reduced P100 ERP component. A late slow wave (720-1720 ms) was enhanced in patients, particularly to words in patients with LBD, and to faces in patients with RBD. Thus, the slow wave was largest in the conditions with most pronounced performance deficits, suggesting that it reflects deficit-related resource recruitment.

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